From fc151573a73640400e4d7aefa4c7a6e50a535abb Mon Sep 17 00:00:00 2001 From: Yuchen Xu Date: Wed, 15 Jun 2022 14:34:08 -0700 Subject: [PATCH 01/12] draft for profiling Signed-off-by: Yuchen Xu --- .gitignore | 4 + acceleration/fast_training_tutorial.ipynb | 702 +++++++++++++++++----- 2 files changed, 562 insertions(+), 144 deletions(-) diff --git a/.gitignore b/.gitignore index 2baecac0f9..38f0461f3c 100644 --- a/.gitignore +++ b/.gitignore @@ -150,3 +150,7 @@ deployment/bentoml/mednist_classifier_bentoml.py deployment/ray/mednist_classifier_start.py *.nii.gz 3d_segmentation/out + +# archives +archives/ +acceleration/*.nsys-rep diff --git a/acceleration/fast_training_tutorial.ipynb b/acceleration/fast_training_tutorial.ipynb index 30c405581c..77b60745ad 100644 --- a/acceleration/fast_training_tutorial.ipynb +++ b/acceleration/fast_training_tutorial.ipynb @@ -36,21 +36,33 @@ }, { "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Note: you may need to restart the kernel to use updated packages.\n" - ] + "execution_count": 1, + "metadata": { + "vscode": { + "languageId": "python" } - ], + }, + "outputs": [], "source": [ - "!python -c \"import monai\" || pip install -q \"monai-weekly[nibabel, tqdm]\"\n", - "!python -c \"import matplotlib\" || pip install -q matplotlib\n", - "%matplotlib inline" + "# NOTE: if you are unsure if you have monai and/or matplotlib installed, uncomment to check/install\n", + "# these are commented out to ensure the converted python script runs smoothly\n", + "# !python3 -c \"import monai\" || pip install -q \"monai-weekly[nibabel, tqdm]\"\n", + "# !python3 -c \"import matplotlib\" || pip install -q matplotlib\n", + "\n", + "# NOTE: uncomment when running as Jupyter notebook\n", + "# %matplotlib inline\n", + "\n", + "# TODO: set preferred parameters\n", + "\n", + "# to use profiling, make sure Nsight systems is installed, and use the following command to run in TERMINAL ONLY:\n", + "# jupyter nbconvert fast_training_tutorial.ipynb --to python && nsys profile --output ./output_base --force-overwrite true --trace-fork-before-exec true python3 fast_training_tutorial.py && rm fast_training_tutorial.py\n", + "# output will be generated in the current directory (you can change --output)\n", + "profiling = True\n", + "\n", + "# if profiling = True, it is recommended to set max_epochs = 6 for faster prototyping\n", + "# to see the trend in training curve and dice results, set max_epochs to be larger (600)\n", + "# note that before optimization, training can be quite a bit slower\n", + "max_epochs = 6" ] }, { @@ -62,9 +74,55 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 2, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/conda/lib/python3.8/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", + " from .autonotebook import tqdm as notebook_tqdm\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MONAI version: 0.9.0rc2\n", + "Numpy version: 1.22.3\n", + "Pytorch version: 1.12.0a0+bd13bc6\n", + "MONAI flags: HAS_EXT = True, USE_COMPILED = False\n", + "MONAI rev id: d8d24eed0ee7705afd55050af0709613fddacb96\n", + "MONAI __file__: /opt/monai/monai/__init__.py\n", + "\n", + "Optional dependencies:\n", + "Pytorch Ignite version: 0.4.8\n", + "Nibabel version: 3.2.2\n", + "scikit-image version: 0.19.2\n", + "Pillow version: 9.0.1\n", + "Tensorboard version: 2.8.0\n", + "gdown version: 4.4.0\n", + "TorchVision version: 0.13.0a0\n", + "tqdm version: 4.64.0\n", + "lmdb version: 1.3.0\n", + "psutil version: 5.9.0\n", + "pandas version: 1.3.5\n", + "einops version: 0.4.1\n", + "transformers version: 4.19.2\n", + "mlflow version: 1.26.1\n", + "pynrrd version: 0.4.3\n", + "\n", + "For details about installing the optional dependencies, please visit:\n", + " https://docs.monai.io/en/latest/installation.html#installing-the-recommended-dependencies\n", + "\n" + ] + } + ], "source": [ "# Copyright 2020 MONAI Consortium\n", "# Licensed under the Apache License, Version 2.0 (the \"License\");\n", @@ -121,6 +179,29 @@ "print_config()" ] }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "# added profiling option\n", + "# set profiling = True to obtain results\n", + "\n", + "# NOTE: if you are unsure if you have nvtx installed, uncomment to check/install\n", + "# !python3 -c \"import nvtx\" || pip install -q nvtx\n", + "\n", + "import nvtx\n", + "from monai.utils.nvtx import Range\n", + "\n", + "import contextlib # to improve code readability (combining training/validation loop with and without profiling)\n", + "no_profiling = contextlib.nullcontext()" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -134,14 +215,18 @@ }, { "cell_type": "code", - "execution_count": 2, - "metadata": {}, + "execution_count": 4, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "root dir is: /workspace/data/medical\n" + "root dir is: /tmp/tmpsq9rl1ek\n" ] } ], @@ -162,9 +247,43 @@ }, { "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], + "execution_count": 5, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Task09_Spleen.tar: 1.50GB [01:14, 21.8MB/s] " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2022-06-15 13:56:09,544 - INFO - Downloaded: /tmp/tmpsq9rl1ek/Task09_Spleen.tar\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2022-06-15 13:56:12,908 - INFO - Verified 'Task09_Spleen.tar', md5: 410d4a301da4e5b2f6f86ec3ddba524e.\n", + "2022-06-15 13:56:12,909 - INFO - Writing into directory: /tmp/tmpsq9rl1ek.\n" + ] + } + ], "source": [ "resource = \"https://msd-for-monai.s3-us-west-2.amazonaws.com/Task09_Spleen.tar\"\n", "md5 = \"410d4a301da4e5b2f6f86ec3ddba524e\"\n", @@ -184,8 +303,12 @@ }, { "cell_type": "code", - "execution_count": 4, - "metadata": {}, + "execution_count": 6, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [], "source": [ "train_images = sorted(\n", @@ -210,51 +333,80 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": {}, + "execution_count": 18, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [], "source": [ "def transformations(fast=False):\n", " train_transforms = [\n", - " LoadImaged(keys=[\"image\", \"label\"]),\n", - " AddChanneld(keys=[\"image\", \"label\"]),\n", - " Orientationd(keys=[\"image\", \"label\"], axcodes=\"RAS\"),\n", - " Spacingd(\n", + " Range(\"LoadImage\")(LoadImaged(keys=[\"image\", \"label\"])) if profiling else LoadImaged(keys=[\"image\", \"label\"]),\n", + " Range()(AddChanneld(keys=[\"image\", \"label\"])) if profiling else AddChanneld(keys=[\"image\", \"label\"]),\n", + " Range()(Orientationd(keys=[\"image\", \"label\"], axcodes=\"RAS\")) if profiling else Orientationd(keys=[\"image\", \"label\"], axcodes=\"RAS\"),\n", + " Range(\"Spacing\")(\n", + " Spacingd(\n", " keys=[\"image\", \"label\"],\n", " pixdim=(1.5, 1.5, 2.0),\n", " mode=(\"bilinear\", \"nearest\"),\n", - " ),\n", - " ScaleIntensityRanged(\n", + " )) if profiling else \n", + " Spacingd(\n", + " keys=[\"image\", \"label\"],\n", + " pixdim=(1.5, 1.5, 2.0),\n", + " mode=(\"bilinear\", \"nearest\"),\n", + " ),\n", + " Range()(\n", + " ScaleIntensityRanged(\n", " keys=[\"image\"],\n", " a_min=-57,\n", " a_max=164,\n", " b_min=0.0,\n", " b_max=1.0,\n", " clip=True,\n", - " ),\n", - " CropForegroundd(keys=[\"image\", \"label\"], source_key=\"image\"),\n", + " )) if profiling else \n", + " ScaleIntensityRanged(\n", + " keys=[\"image\"],\n", + " a_min=-57,\n", + " a_max=164,\n", + " b_min=0.0,\n", + " b_max=1.0,\n", + " clip=True,\n", + " ),\n", + " Range()(CropForegroundd(keys=[\"image\", \"label\"], source_key=\"image\")) if profiling else CropForegroundd(keys=[\"image\", \"label\"], source_key=\"image\"),\n", " # pre-compute foreground and background indexes\n", " # and cache them to accelerate training\n", - " FgBgToIndicesd(\n", + " Range(\"Indexing\")(\n", + " FgBgToIndicesd(\n", " keys=\"label\",\n", " fg_postfix=\"_fg\",\n", " bg_postfix=\"_bg\",\n", " image_key=\"image\",\n", - " ),\n", + " )) if profiling else \n", + " FgBgToIndicesd(\n", + " keys=\"label\",\n", + " fg_postfix=\"_fg\",\n", + " bg_postfix=\"_bg\",\n", + " image_key=\"image\",\n", + " ),\n", " # change to execute transforms with Tensor data\n", " EnsureTyped(keys=[\"image\", \"label\"]),\n", " ]\n", + " \n", " if fast:\n", " # move the data to GPU and cache to avoid CPU -> GPU sync in every epoch\n", " train_transforms.append(\n", " ToDeviced(keys=[\"image\", \"label\"], device=\"cuda:0\")\n", " )\n", + "\n", " train_transforms.append(\n", " # randomly crop out patch samples from big\n", " # image based on pos / neg ratio\n", " # the image centers of negative samples\n", " # must be in valid image area\n", - " RandCropByPosNegLabeld(\n", + " Range(\"RandCrop\")(\n", + " RandCropByPosNegLabeld(\n", " keys=[\"image\", \"label\"],\n", " label_key=\"label\",\n", " spatial_size=(96, 96, 96),\n", @@ -263,9 +415,19 @@ " num_samples=4,\n", " fg_indices_key=\"label_fg\",\n", " bg_indices_key=\"label_bg\",\n", - " ),\n", + " )) if profiling else \n", + " RandCropByPosNegLabeld(\n", + " keys=[\"image\", \"label\"],\n", + " label_key=\"label\",\n", + " spatial_size=(96, 96, 96),\n", + " pos=1,\n", + " neg=1,\n", + " num_samples=4,\n", + " fg_indices_key=\"label_fg\",\n", + " bg_indices_key=\"label_bg\",\n", + " ),\n", " )\n", - "\n", + " \n", " val_transforms = [\n", " LoadImaged(keys=[\"image\", \"label\"]),\n", " AddChanneld(keys=[\"image\", \"label\"]),\n", @@ -313,17 +475,25 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 16, "metadata": { - "scrolled": true + "vscode": { + "languageId": "python" + } }, "outputs": [], "source": [ + "# reference used from https://stackoverflow.com/questions/27803059/conditional-with-statement-in-python/53088625#53088625\n", + "# accessed June 14, 2022\n", + "\n", "def train_process(fast=False):\n", - " max_epochs = 600\n", " learning_rate = 2e-4\n", " val_interval = 5 # do validation for every epoch\n", - " device = torch.device(\"cuda:0\")\n", + "\n", + " if torch.cuda.is_available():\n", + " device = torch.device(\"cuda:0\")\n", + " else:\n", + " raise RuntimeError('this tutorial is intended for GPU, but no CUDA device is available')\n", "\n", " train_trans, val_trans = transformations(fast=fast)\n", " # set CacheDataset, ThreadDataLoader and DiceCE loss for MONAI fast training\n", @@ -411,93 +581,138 @@ " metric_values = []\n", " epoch_times = []\n", " total_start = time.time()\n", + "\n", " for epoch in range(max_epochs):\n", " epoch_start = time.time()\n", " print(\"-\" * 10)\n", " print(f\"epoch {epoch + 1}/{max_epochs}\")\n", - " model.train()\n", - " epoch_loss = 0\n", - " step = 0\n", - " for batch_data in train_loader:\n", - " step_start = time.time()\n", - " step += 1\n", - " inputs, labels = (\n", - " batch_data[\"image\"].to(device),\n", - " batch_data[\"label\"].to(device),\n", - " )\n", - " optimizer.zero_grad()\n", - " # set AMP for MONAI training\n", - " if fast:\n", - " with torch.cuda.amp.autocast():\n", - " outputs = model(inputs)\n", - " loss = loss_function(outputs, labels)\n", - " scaler.scale(loss).backward()\n", - " scaler.step(optimizer)\n", - " scaler.update()\n", - " else:\n", - " outputs = model(inputs)\n", - " loss = loss_function(outputs, labels)\n", - " loss.backward()\n", - " optimizer.step()\n", - " epoch_loss += loss.item()\n", - " epoch_len = math.ceil(len(train_ds) / train_loader.batch_size)\n", - " print(\n", - " f\"{step}/{epoch_len}, train_loss: {loss.item():.4f}\"\n", - " f\" step time: {(time.time() - step_start):.4f}\"\n", - " )\n", - " epoch_loss /= step\n", - " epoch_loss_values.append(epoch_loss)\n", - " print(f\"epoch {epoch + 1} average loss: {epoch_loss:.4f}\")\n", - "\n", - " if (epoch + 1) % val_interval == 0:\n", - " model.eval()\n", - " with torch.no_grad():\n", - " for val_data in val_loader:\n", - " val_inputs, val_labels = (\n", - " val_data[\"image\"].to(device),\n", - " val_data[\"label\"].to(device),\n", + "\n", + " # profiling: full epoch\n", + " with nvtx.annotate(\"epoch\", color=\"red\") if profiling else no_profiling:\n", + " model.train()\n", + " epoch_loss = 0\n", + " train_loader_iterator = iter(train_loader)\n", + "\n", + " # using step instead of iterate through train_loader directly to track data loading time\n", + " # steps are 1-indexed for printing and calculation purposes\n", + " for step in range(1, len(train_loader) + 1):\n", + " step_start = time.time()\n", + "\n", + " # profiling: train dataload\n", + " with nvtx.annotate(\"dataload\", color=\"red\") if profiling else no_profiling:\n", + " # rng_train_dataload = nvtx.start_range(message=\"dataload\", color=\"red\")\n", + " batch_data = next(train_loader_iterator)\n", + " inputs, labels = (\n", + " batch_data[\"image\"].to(device),\n", + " batch_data[\"label\"].to(device),\n", " )\n", - " roi_size = (160, 160, 160)\n", - " sw_batch_size = 4\n", - " # set AMP for MONAI validation\n", - " if fast:\n", + "\n", + " optimizer.zero_grad()\n", + " # set AMP for MONAI training\n", + " if fast:\n", + " # profiling: forward\n", + " with nvtx.annotate(\"forward\", color=\"green\") if profiling else no_profiling:\n", " with torch.cuda.amp.autocast():\n", - " val_outputs = sliding_window_inference(\n", - " val_inputs, roi_size, sw_batch_size, model\n", + " outputs = model(inputs)\n", + " loss = loss_function(outputs, labels)\n", + "\n", + " # profiling: backward\n", + " with nvtx.annotate(\"backward\", color=\"blue\") if profiling else no_profiling:\n", + " scaler.scale(loss).backward()\n", + "\n", + " # profiling: update\n", + " with nvtx.annotate(\"update\", color=\"yellow\") if profiling else no_profiling:\n", + " scaler.step(optimizer)\n", + " scaler.update()\n", + " else:\n", + " # profiling: forward\n", + " with nvtx.annotate(\"forward\", color=\"green\") if profiling else no_profiling:\n", + " outputs = model(inputs)\n", + " loss = loss_function(outputs, labels)\n", + "\n", + " # profiling: backward\n", + " with nvtx.annotate(\"backward\", color=\"blue\") if profiling else no_profiling:\n", + " loss.backward()\n", + "\n", + " # profiling: update\n", + " with nvtx.annotate(\"update\", color=\"yellow\") if profiling else no_profiling:\n", + " optimizer.step()\n", + "\n", + " epoch_loss += loss.item()\n", + " epoch_len = math.ceil(len(train_ds) / train_loader.batch_size)\n", + " print(\n", + " f\"{step}/{epoch_len}, train_loss: {loss.item():.4f}\"\n", + " f\" step time: {(time.time() - step_start):.4f}\"\n", + " )\n", + " epoch_loss /= step\n", + " epoch_loss_values.append(epoch_loss)\n", + " print(f\"epoch {epoch + 1} average loss: {epoch_loss:.4f}\")\n", + "\n", + " if (epoch + 1) % val_interval == 0:\n", + " model.eval()\n", + " with torch.no_grad():\n", + " val_loader_iterator = iter(val_loader)\n", + "\n", + " for val_step in range(len(val_loader)):\n", + " # profiling: val dataload\n", + " with nvtx.annotate(\"dataload\", color=\"red\") if profiling else no_profiling:\n", + " val_data = next(val_loader_iterator)\n", + " val_inputs, val_labels = (\n", + " val_data[\"image\"].to(device),\n", + " val_data[\"label\"].to(device),\n", " )\n", - " else:\n", - " val_outputs = sliding_window_inference(\n", - " val_inputs, roi_size, sw_batch_size, model\n", + "\n", + " roi_size = (160, 160, 160)\n", + " sw_batch_size = 4\n", + "\n", + " # profiling: sliding window\n", + " with nvtx.annotate(\"sliding window\", color=\"green\") if profiling else no_profiling:\n", + " # set AMP for MONAI validation\n", + " if fast:\n", + " with torch.cuda.amp.autocast():\n", + " val_outputs = sliding_window_inference(\n", + " val_inputs, roi_size, sw_batch_size, model\n", + " )\n", + " else:\n", + " val_outputs = sliding_window_inference(\n", + " val_inputs, roi_size, sw_batch_size, model\n", + " )\n", + "\n", + " # profiling: decollate batch\n", + " with nvtx.annotate(\"decollate batch\", color=\"blue\") if profiling else no_profiling:\n", + " val_outputs = [post_pred(i) for i in decollate_batch(val_outputs)]\n", + " val_labels = [post_label(i) for i in decollate_batch(val_labels)]\n", + "\n", + " # profiling: compute metric\n", + " with nvtx.annotate(\"compute metric\", color=\"yellow\") if profiling else no_profiling:\n", + " dice_metric(y_pred=val_outputs, y=val_labels)\n", + "\n", + " metric = dice_metric.aggregate().item()\n", + " dice_metric.reset()\n", + " metric_values.append(metric)\n", + " if metric > best_metric:\n", + " best_metric = metric\n", + " best_metric_epoch = epoch + 1\n", + " best_metrics_epochs_and_time[0].append(best_metric)\n", + " best_metrics_epochs_and_time[1].append(best_metric_epoch)\n", + " best_metrics_epochs_and_time[2].append(\n", + " time.time() - total_start\n", " )\n", - " val_outputs = [post_pred(i) for i in decollate_batch(val_outputs)]\n", - " val_labels = [post_label(i) for i in decollate_batch(val_labels)]\n", - " dice_metric(y_pred=val_outputs, y=val_labels)\n", - "\n", - " metric = dice_metric.aggregate().item()\n", - " dice_metric.reset()\n", - " metric_values.append(metric)\n", - " if metric > best_metric:\n", - " best_metric = metric\n", - " best_metric_epoch = epoch + 1\n", - " best_metrics_epochs_and_time[0].append(best_metric)\n", - " best_metrics_epochs_and_time[1].append(best_metric_epoch)\n", - " best_metrics_epochs_and_time[2].append(\n", - " time.time() - total_start\n", + " torch.save(model.state_dict(), os.path.join(root_dir, \"best_metric_model.pt\"))\n", + " print(\"saved new best metric model\")\n", + " print(\n", + " f\"current epoch: {epoch + 1} current\"\n", + " f\" mean dice: {metric:.4f}\"\n", + " f\" best mean dice: {best_metric:.4f}\"\n", + " f\" at epoch: {best_metric_epoch}\"\n", " )\n", - " torch.save(model.state_dict(), os.path.join(root_dir, \"best_metric_model.pt\"))\n", - " print(\"saved new best metric model\")\n", - " print(\n", - " f\"current epoch: {epoch + 1} current\"\n", - " f\" mean dice: {metric:.4f}\"\n", - " f\" best mean dice: {best_metric:.4f}\"\n", - " f\" at epoch: {best_metric_epoch}\"\n", - " )\n", + "\n", " print(\n", " f\"time consuming of epoch {epoch + 1} is:\"\n", " f\" {(time.time() - epoch_start):.4f}\"\n", " )\n", " epoch_times.append(time.time() - epoch_start)\n", - "\n", + " \n", " total_time = time.time() - total_start\n", " print(\n", " f\"train completed, best_metric: {best_metric:.4f}\"\n", @@ -523,9 +738,109 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 9, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "----------\n", + "epoch 1/6\n", + "1/8, train_loss: 0.6697 step time: 17.1861\n", + "2/8, train_loss: 0.6850 step time: 0.5286\n", + "3/8, train_loss: 0.6906 step time: 0.5972\n", + "4/8, train_loss: 0.6771 step time: 0.7087\n", + "5/8, train_loss: 0.6635 step time: 14.4775\n", + "6/8, train_loss: 0.6723 step time: 0.5318\n", + "7/8, train_loss: 0.6568 step time: 0.8064\n", + "8/8, train_loss: 0.6648 step time: 0.8314\n", + "epoch 1 average loss: 0.6725\n", + "time consuming of epoch 1 is: 35.7880\n", + "----------\n", + "epoch 2/6\n", + "1/8, train_loss: 0.6596 step time: 17.1820\n", + "2/8, train_loss: 0.6672 step time: 0.5447\n", + "3/8, train_loss: 0.6405 step time: 2.0512\n", + "4/8, train_loss: 0.6333 step time: 0.5276\n", + "5/8, train_loss: 0.6444 step time: 14.9559\n", + "6/8, train_loss: 0.6272 step time: 0.5306\n", + "7/8, train_loss: 0.6257 step time: 2.3935\n", + "8/8, train_loss: 0.6351 step time: 0.5314\n", + "epoch 2 average loss: 0.6416\n", + "time consuming of epoch 2 is: 39.0296\n", + "----------\n", + "epoch 3/6\n", + "1/8, train_loss: 0.6546 step time: 14.9289\n", + "2/8, train_loss: 0.6126 step time: 0.7670\n", + "3/8, train_loss: 0.6392 step time: 3.2424\n", + "4/8, train_loss: 0.6240 step time: 0.5350\n", + "5/8, train_loss: 0.6224 step time: 7.0118\n", + "6/8, train_loss: 0.6048 step time: 6.8399\n", + "7/8, train_loss: 0.6162 step time: 2.2157\n", + "8/8, train_loss: 0.6155 step time: 2.4475\n", + "epoch 3 average loss: 0.6237\n", + "time consuming of epoch 3 is: 38.3414\n", + "----------\n", + "epoch 4/6\n", + "1/8, train_loss: 0.5985 step time: 15.8969\n", + "2/8, train_loss: 0.5991 step time: 3.9983\n", + "3/8, train_loss: 0.5989 step time: 0.5365\n", + "4/8, train_loss: 0.6410 step time: 0.5532\n", + "5/8, train_loss: 0.6391 step time: 10.6800\n", + "6/8, train_loss: 0.5883 step time: 5.4085\n", + "7/8, train_loss: 0.6105 step time: 0.5291\n", + "8/8, train_loss: 0.6171 step time: 0.5268\n", + "epoch 4 average loss: 0.6116\n", + "time consuming of epoch 4 is: 38.4674\n", + "----------\n", + "epoch 5/6\n", + "1/8, train_loss: 0.6162 step time: 12.5105\n", + "2/8, train_loss: 0.5857 step time: 5.8914\n", + "3/8, train_loss: 0.6034 step time: 0.5373\n", + "4/8, train_loss: 0.5965 step time: 0.6103\n", + "5/8, train_loss: 0.6278 step time: 6.4330\n", + "6/8, train_loss: 0.6098 step time: 8.6285\n", + "7/8, train_loss: 0.5912 step time: 0.8754\n", + "8/8, train_loss: 0.6127 step time: 4.0549\n", + "epoch 5 average loss: 0.6054\n", + "saved new best metric model\n", + "current epoch: 5 current mean dice: 0.0557 best mean dice: 0.0557 at epoch: 5\n", + "time consuming of epoch 5 is: 49.2248\n", + "----------\n", + "epoch 6/6\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "positional arguments and argument \"destination\" are deprecated. nn.Module.state_dict will not accept them in the future. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1/8, train_loss: 0.6376 step time: 20.9606\n", + "2/8, train_loss: 0.6001 step time: 0.5595\n", + "3/8, train_loss: 0.5945 step time: 0.5393\n", + "4/8, train_loss: 0.5741 step time: 0.5403\n", + "5/8, train_loss: 0.5921 step time: 14.4849\n", + "6/8, train_loss: 0.5781 step time: 0.5264\n", + "7/8, train_loss: 0.5985 step time: 0.5275\n", + "8/8, train_loss: 0.5880 step time: 0.5300\n", + "epoch 6 average loss: 0.5954\n", + "time consuming of epoch 6 is: 39.0105\n", + "train completed, best_metric: 0.0557 at epoch: 5 total time: 239.8618\n", + "total time of 6 epochs with regular PyTorch training: 241.8329\n" + ] + } + ], "source": [ "set_determinism(seed=0)\n", "regular_start = time.time()\n", @@ -552,9 +867,104 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 19, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Loading dataset: 100%|███████████████████████████████████████████████████████████████████| 32/32 [00:30<00:00, 1.04it/s]\n", + "Loading dataset: 100%|█████████████████████████████████████████████████████████████████████| 9/9 [00:07<00:00, 1.14it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "----------\n", + "epoch 1/6\n", + "1/8, train_loss: 0.8296 step time: 0.2284\n", + "2/8, train_loss: 0.7642 step time: 0.1946\n", + "3/8, train_loss: 0.5814 step time: 0.1904\n", + "4/8, train_loss: 0.4989 step time: 0.1937\n", + "5/8, train_loss: 0.4850 step time: 0.1941\n", + "6/8, train_loss: 0.4719 step time: 0.1941\n", + "7/8, train_loss: 0.4115 step time: 0.1805\n", + "8/8, train_loss: 0.4362 step time: 0.1840\n", + "epoch 1 average loss: 0.5598\n", + "time consuming of epoch 1 is: 1.5611\n", + "----------\n", + "epoch 2/6\n", + "1/8, train_loss: 0.4431 step time: 0.2278\n", + "2/8, train_loss: 0.4596 step time: 0.1946\n", + "3/8, train_loss: 0.4200 step time: 0.1961\n", + "4/8, train_loss: 0.5280 step time: 0.1859\n", + "5/8, train_loss: 0.5630 step time: 0.1963\n", + "6/8, train_loss: 0.4473 step time: 0.1947\n", + "7/8, train_loss: 0.5153 step time: 0.1825\n", + "8/8, train_loss: 0.5343 step time: 0.1811\n", + "epoch 2 average loss: 0.4888\n", + "time consuming of epoch 2 is: 1.5602\n", + "----------\n", + "epoch 3/6\n", + "1/8, train_loss: 0.4977 step time: 0.2356\n", + "2/8, train_loss: 0.4521 step time: 0.1989\n", + "3/8, train_loss: 0.5149 step time: 0.1996\n", + "4/8, train_loss: 0.4855 step time: 0.1986\n", + "5/8, train_loss: 0.3748 step time: 0.2000\n", + "6/8, train_loss: 0.4201 step time: 0.1978\n", + "7/8, train_loss: 0.3917 step time: 0.1817\n", + "8/8, train_loss: 0.4210 step time: 0.1831\n", + "epoch 3 average loss: 0.4447\n", + "time consuming of epoch 3 is: 1.5968\n", + "----------\n", + "epoch 4/6\n", + "1/8, train_loss: 0.3355 step time: 0.2370\n", + "2/8, train_loss: 0.3301 step time: 0.1972\n", + "3/8, train_loss: 0.1822 step time: 0.1979\n", + "4/8, train_loss: 0.1790 step time: 0.2007\n", + "5/8, train_loss: 0.2337 step time: 0.1998\n", + "6/8, train_loss: 0.2721 step time: 0.2019\n", + "7/8, train_loss: 0.2848 step time: 0.1802\n", + "8/8, train_loss: 0.2908 step time: 0.1816\n", + "epoch 4 average loss: 0.2635\n", + "time consuming of epoch 4 is: 1.5977\n", + "----------\n", + "epoch 5/6\n", + "1/8, train_loss: 0.1574 step time: 0.2378\n", + "2/8, train_loss: 0.1780 step time: 0.1999\n", + "3/8, train_loss: 0.1966 step time: 0.1980\n", + "4/8, train_loss: 0.1346 step time: 0.1988\n", + "5/8, train_loss: 0.1601 step time: 0.2002\n", + "6/8, train_loss: 0.2479 step time: 0.1984\n", + "7/8, train_loss: 0.3215 step time: 0.1812\n", + "8/8, train_loss: 0.1730 step time: 0.1823\n", + "epoch 5 average loss: 0.1961\n", + "saved new best metric model\n", + "current epoch: 5 current mean dice: 0.0511 best mean dice: 0.0511 at epoch: 5\n", + "time consuming of epoch 5 is: 2.4953\n", + "----------\n", + "epoch 6/6\n", + "1/8, train_loss: 0.1274 step time: 0.2372\n", + "2/8, train_loss: 0.1602 step time: 0.1979\n", + "3/8, train_loss: 0.2628 step time: 0.2015\n", + "4/8, train_loss: 0.1241 step time: 0.1984\n", + "5/8, train_loss: 0.1801 step time: 0.1987\n", + "6/8, train_loss: 0.1538 step time: 0.1991\n", + "7/8, train_loss: 0.2318 step time: 0.1811\n", + "8/8, train_loss: 0.2172 step time: 0.1802\n", + "epoch 6 average loss: 0.1822\n", + "time consuming of epoch 6 is: 1.5954\n", + "train completed, best_metric: 0.0511 at epoch: 5 total time: 10.4065\n", + "total time of 6 epochs with MONAI fast training: 10.4065, time of preparing cache: 38.9820\n" + ] + } + ], "source": [ "set_determinism(seed=0)\n", "monai_start = time.time()\n", @@ -582,12 +992,16 @@ }, { "cell_type": "code", - "execution_count": 52, - "metadata": {}, + "execution_count": 11, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [ { "data": { - "image/png": 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\n", 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", 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" ] @@ -645,12 +1059,16 @@ }, { "cell_type": "code", - "execution_count": 49, - "metadata": {}, + "execution_count": 12, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [ { "data": { - "image/png": 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\n", 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", 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" ] @@ -694,12 +1112,16 @@ }, { "cell_type": "code", - "execution_count": 50, - "metadata": {}, + "execution_count": 13, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [ { "data": { - "image/png": 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\n", 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", 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" ] @@ -784,7 +1206,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [], "source": [ "if directory is None:\n", @@ -797,18 +1223,6 @@ "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.13" } }, "nbformat": 4, From 450a0a3281694b6032e627e1c47a2c74357b046d Mon Sep 17 00:00:00 2001 From: Yuchen Xu Date: Thu, 16 Jun 2022 14:25:20 -0700 Subject: [PATCH 02/12] fixed coding style errors --- acceleration/fast_training_tutorial.ipynb | 117 +++++++++++----------- 1 file changed, 58 insertions(+), 59 deletions(-) diff --git a/acceleration/fast_training_tutorial.ipynb b/acceleration/fast_training_tutorial.ipynb index 77b60745ad..e22b210624 100644 --- a/acceleration/fast_training_tutorial.ipynb +++ b/acceleration/fast_training_tutorial.ipynb @@ -48,21 +48,10 @@ "# these are commented out to ensure the converted python script runs smoothly\n", "# !python3 -c \"import monai\" || pip install -q \"monai-weekly[nibabel, tqdm]\"\n", "# !python3 -c \"import matplotlib\" || pip install -q matplotlib\n", + "# !python3 -c \"import nvtx\" || pip install -q nvtx\n", "\n", "# NOTE: uncomment when running as Jupyter notebook\n", - "# %matplotlib inline\n", - "\n", - "# TODO: set preferred parameters\n", - "\n", - "# to use profiling, make sure Nsight systems is installed, and use the following command to run in TERMINAL ONLY:\n", - "# jupyter nbconvert fast_training_tutorial.ipynb --to python && nsys profile --output ./output_base --force-overwrite true --trace-fork-before-exec true python3 fast_training_tutorial.py && rm fast_training_tutorial.py\n", - "# output will be generated in the current directory (you can change --output)\n", - "profiling = True\n", - "\n", - "# if profiling = True, it is recommended to set max_epochs = 6 for faster prototyping\n", - "# to see the trend in training curve and dice results, set max_epochs to be larger (600)\n", - "# note that before optimization, training can be quite a bit slower\n", - "max_epochs = 6" + "# %matplotlib inline" ] }, { @@ -176,6 +165,11 @@ ")\n", "from monai.utils import set_determinism\n", "\n", + "# for profiling\n", + "import nvtx\n", + "from monai.utils.nvtx import Range\n", + "import contextlib # to improve code readability (combining training/validation loop with and without profiling)\n", + "\n", "print_config()" ] }, @@ -189,16 +183,19 @@ }, "outputs": [], "source": [ - "# added profiling option\n", + "# TODO: set preferred parameters\n", "# set profiling = True to obtain results\n", "\n", - "# NOTE: if you are unsure if you have nvtx installed, uncomment to check/install\n", - "# !python3 -c \"import nvtx\" || pip install -q nvtx\n", + "# to use profiling, make sure Nsight systems is installed, and use the following command to run in TERMINAL ONLY:\n", + "# jupyter nbconvert fast_training_tutorial.ipynb --to python && nsys profile --output ./output_base --force-overwrite true --trace-fork-before-exec true python3 fast_training_tutorial.py && rm fast_training_tutorial.py\n", + "# output will be generated in the current directory (you can change --output)\n", + "profiling = True\n", "\n", - "import nvtx\n", - "from monai.utils.nvtx import Range\n", + "# if profiling = True, it is recommended to set max_epochs = 6 for faster prototyping\n", + "# to see the trend in training curve and dice results, set max_epochs to be larger (600)\n", + "# note that before optimization, training can be quite a bit slower\n", + "max_epochs = 6\n", "\n", - "import contextlib # to improve code readability (combining training/validation loop with and without profiling)\n", "no_profiling = contextlib.nullcontext()" ] }, @@ -345,55 +342,57 @@ " train_transforms = [\n", " Range(\"LoadImage\")(LoadImaged(keys=[\"image\", \"label\"])) if profiling else LoadImaged(keys=[\"image\", \"label\"]),\n", " Range()(AddChanneld(keys=[\"image\", \"label\"])) if profiling else AddChanneld(keys=[\"image\", \"label\"]),\n", - " Range()(Orientationd(keys=[\"image\", \"label\"], axcodes=\"RAS\")) if profiling else Orientationd(keys=[\"image\", \"label\"], axcodes=\"RAS\"),\n", + " Range()(Orientationd(keys=[\"image\", \"label\"], axcodes=\"RAS\")) if profiling else\n", + " Orientationd(keys=[\"image\", \"label\"], axcodes=\"RAS\"),\n", " Range(\"Spacing\")(\n", " Spacingd(\n", + " keys=[\"image\", \"label\"],\n", + " pixdim=(1.5, 1.5, 2.0),\n", + " mode=(\"bilinear\", \"nearest\"),\n", + " )) if profiling else\n", + " Spacingd(\n", " keys=[\"image\", \"label\"],\n", " pixdim=(1.5, 1.5, 2.0),\n", " mode=(\"bilinear\", \"nearest\"),\n", - " )) if profiling else \n", - " Spacingd(\n", - " keys=[\"image\", \"label\"],\n", - " pixdim=(1.5, 1.5, 2.0),\n", - " mode=(\"bilinear\", \"nearest\"),\n", - " ),\n", + " ),\n", " Range()(\n", " ScaleIntensityRanged(\n", + " keys=[\"image\"],\n", + " a_min=-57,\n", + " a_max=164,\n", + " b_min=0.0,\n", + " b_max=1.0,\n", + " clip=True,\n", + " )) if profiling else\n", + " ScaleIntensityRanged(\n", " keys=[\"image\"],\n", " a_min=-57,\n", " a_max=164,\n", " b_min=0.0,\n", " b_max=1.0,\n", " clip=True,\n", - " )) if profiling else \n", - " ScaleIntensityRanged(\n", - " keys=[\"image\"],\n", - " a_min=-57,\n", - " a_max=164,\n", - " b_min=0.0,\n", - " b_max=1.0,\n", - " clip=True,\n", - " ),\n", - " Range()(CropForegroundd(keys=[\"image\", \"label\"], source_key=\"image\")) if profiling else CropForegroundd(keys=[\"image\", \"label\"], source_key=\"image\"),\n", + " ),\n", + " Range()(CropForegroundd(keys=[\"image\", \"label\"], source_key=\"image\")\n", + " ) if profiling else CropForegroundd(keys=[\"image\", \"label\"], source_key=\"image\"),\n", " # pre-compute foreground and background indexes\n", " # and cache them to accelerate training\n", " Range(\"Indexing\")(\n", " FgBgToIndicesd(\n", + " keys=\"label\",\n", + " fg_postfix=\"_fg\",\n", + " bg_postfix=\"_bg\",\n", + " image_key=\"image\",\n", + " )) if profiling else\n", + " FgBgToIndicesd(\n", " keys=\"label\",\n", " fg_postfix=\"_fg\",\n", " bg_postfix=\"_bg\",\n", " image_key=\"image\",\n", - " )) if profiling else \n", - " FgBgToIndicesd(\n", - " keys=\"label\",\n", - " fg_postfix=\"_fg\",\n", - " bg_postfix=\"_bg\",\n", - " image_key=\"image\",\n", - " ),\n", + " ),\n", " # change to execute transforms with Tensor data\n", " EnsureTyped(keys=[\"image\", \"label\"]),\n", " ]\n", - " \n", + "\n", " if fast:\n", " # move the data to GPU and cache to avoid CPU -> GPU sync in every epoch\n", " train_transforms.append(\n", @@ -407,6 +406,16 @@ " # must be in valid image area\n", " Range(\"RandCrop\")(\n", " RandCropByPosNegLabeld(\n", + " keys=[\"image\", \"label\"],\n", + " label_key=\"label\",\n", + " spatial_size=(96, 96, 96),\n", + " pos=1,\n", + " neg=1,\n", + " num_samples=4,\n", + " fg_indices_key=\"label_fg\",\n", + " bg_indices_key=\"label_bg\",\n", + " )) if profiling else\n", + " RandCropByPosNegLabeld(\n", " keys=[\"image\", \"label\"],\n", " label_key=\"label\",\n", " spatial_size=(96, 96, 96),\n", @@ -415,19 +424,9 @@ " num_samples=4,\n", " fg_indices_key=\"label_fg\",\n", " bg_indices_key=\"label_bg\",\n", - " )) if profiling else \n", - " RandCropByPosNegLabeld(\n", - " keys=[\"image\", \"label\"],\n", - " label_key=\"label\",\n", - " spatial_size=(96, 96, 96),\n", - " pos=1,\n", - " neg=1,\n", - " num_samples=4,\n", - " fg_indices_key=\"label_fg\",\n", - " bg_indices_key=\"label_bg\",\n", - " ),\n", + " ),\n", " )\n", - " \n", + "\n", " val_transforms = [\n", " LoadImaged(keys=[\"image\", \"label\"]),\n", " AddChanneld(keys=[\"image\", \"label\"]),\n", @@ -600,7 +599,7 @@ "\n", " # profiling: train dataload\n", " with nvtx.annotate(\"dataload\", color=\"red\") if profiling else no_profiling:\n", - " # rng_train_dataload = nvtx.start_range(message=\"dataload\", color=\"red\")\n", + " # rng_train_dataload = nvtx.start_range(message=\"dataload\", color=\"red\")\n", " batch_data = next(train_loader_iterator)\n", " inputs, labels = (\n", " batch_data[\"image\"].to(device),\n", @@ -667,7 +666,7 @@ "\n", " # profiling: sliding window\n", " with nvtx.annotate(\"sliding window\", color=\"green\") if profiling else no_profiling:\n", - " # set AMP for MONAI validation\n", + " # set AMP for MONAI validation\n", " if fast:\n", " with torch.cuda.amp.autocast():\n", " val_outputs = sliding_window_inference(\n", @@ -712,7 +711,7 @@ " f\" {(time.time() - epoch_start):.4f}\"\n", " )\n", " epoch_times.append(time.time() - epoch_start)\n", - " \n", + "\n", " total_time = time.time() - total_start\n", " print(\n", " f\"train completed, best_metric: {best_metric:.4f}\"\n", From 4ee23b191f8eca5b4025681578d6ca749c5fc6ba Mon Sep 17 00:00:00 2001 From: Yuchen Xu Date: Thu, 16 Jun 2022 15:49:00 -0700 Subject: [PATCH 03/12] ready for discussion --- .gitignore | 2 +- acceleration/fast_training_tutorial.ipynb | 472 +++++++++------------- 2 files changed, 186 insertions(+), 288 deletions(-) diff --git a/.gitignore b/.gitignore index 38f0461f3c..c230ba527a 100644 --- a/.gitignore +++ b/.gitignore @@ -153,4 +153,4 @@ deployment/ray/mednist_classifier_start.py # archives archives/ -acceleration/*.nsys-rep +acceleration/output diff --git a/acceleration/fast_training_tutorial.ipynb b/acceleration/fast_training_tutorial.ipynb index e22b210624..8a080989f8 100644 --- a/acceleration/fast_training_tutorial.ipynb +++ b/acceleration/fast_training_tutorial.ipynb @@ -37,11 +37,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "vscode": { - "languageId": "python" - } - }, + "metadata": {}, "outputs": [], "source": [ "# NOTE: if you are unsure if you have monai and/or matplotlib installed, uncomment to check/install\n", @@ -51,7 +47,7 @@ "# !python3 -c \"import nvtx\" || pip install -q nvtx\n", "\n", "# NOTE: uncomment when running as Jupyter notebook\n", - "# %matplotlib inline" + "%matplotlib inline" ] }, { @@ -64,11 +60,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "vscode": { - "languageId": "python" - } - }, + "metadata": {}, "outputs": [ { "name": "stderr", @@ -175,19 +167,18 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": { - "vscode": { - "languageId": "python" - } - }, + "execution_count": 3, + "metadata": {}, "outputs": [], "source": [ "# TODO: set preferred parameters\n", - "# set profiling = True to obtain results\n", "\n", + "# overwrite and create a new output directory, True by default\n", + "output_overwrite = True\n", + "\n", + "# set profiling = True to obtain results\n", "# to use profiling, make sure Nsight systems is installed, and use the following command to run in TERMINAL ONLY:\n", - "# jupyter nbconvert fast_training_tutorial.ipynb --to python && nsys profile --output ./output_base --force-overwrite true --trace-fork-before-exec true python3 fast_training_tutorial.py && rm fast_training_tutorial.py\n", + "# jupyter nbconvert fast_training_tutorial.ipynb --to python && nsys profile --output ./outputs/output_base --force-overwrite true --trace-fork-before-exec true python3 fast_training_tutorial.py && rm fast_training_tutorial.py\n", "# output will be generated in the current directory (you can change --output)\n", "profiling = True\n", "\n", @@ -213,17 +204,13 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "vscode": { - "languageId": "python" - } - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "root dir is: /tmp/tmpsq9rl1ek\n" + "root dir is: /tmp/tmp7wd9gqnn\n" ] } ], @@ -233,6 +220,21 @@ "print(f\"root dir is: {root_dir}\")" ] }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# outputs\n", + "\n", + "out_dir = \"outputs/\"\n", + "\n", + "if os.path.exists(out_dir) and output_overwrite:\n", + " shutil.rmtree(out_dir)\n", + "os.makedirs(out_dir, exist_ok=True)" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -244,25 +246,21 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": { - "vscode": { - "languageId": "python" - } - }, + "execution_count": 6, + "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "Task09_Spleen.tar: 1.50GB [01:14, 21.8MB/s] " + "Task09_Spleen.tar: 1.50GB [01:05, 24.5MB/s] " ] }, { "name": "stdout", "output_type": "stream", "text": [ - "2022-06-15 13:56:09,544 - INFO - Downloaded: /tmp/tmpsq9rl1ek/Task09_Spleen.tar\n" + "2022-06-16 22:39:46,307 - INFO - Downloaded: /tmp/tmp7wd9gqnn/Task09_Spleen.tar\n" ] }, { @@ -276,8 +274,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "2022-06-15 13:56:12,908 - INFO - Verified 'Task09_Spleen.tar', md5: 410d4a301da4e5b2f6f86ec3ddba524e.\n", - "2022-06-15 13:56:12,909 - INFO - Writing into directory: /tmp/tmpsq9rl1ek.\n" + "2022-06-16 22:39:49,673 - INFO - Verified 'Task09_Spleen.tar', md5: 410d4a301da4e5b2f6f86ec3ddba524e.\n", + "2022-06-16 22:39:49,674 - INFO - Writing into directory: /tmp/tmp7wd9gqnn.\n" ] } ], @@ -300,12 +298,8 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": { - "vscode": { - "languageId": "python" - } - }, + "execution_count": 7, + "metadata": {}, "outputs": [], "source": [ "train_images = sorted(\n", @@ -330,12 +324,8 @@ }, { "cell_type": "code", - "execution_count": 18, - "metadata": { - "vscode": { - "languageId": "python" - } - }, + "execution_count": 8, + "metadata": {}, "outputs": [], "source": [ "def transformations(fast=False):\n", @@ -474,12 +464,8 @@ }, { "cell_type": "code", - "execution_count": 16, - "metadata": { - "vscode": { - "languageId": "python" - } - }, + "execution_count": 9, + "metadata": {}, "outputs": [], "source": [ "# reference used from https://stackoverflow.com/questions/27803059/conditional-with-statement-in-python/53088625#53088625\n", @@ -737,81 +723,77 @@ }, { "cell_type": "code", - "execution_count": 9, - "metadata": { - "vscode": { - "languageId": "python" - } - }, + "execution_count": null, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "----------\n", - "epoch 1/6\n", - "1/8, train_loss: 0.6697 step time: 17.1861\n", - "2/8, train_loss: 0.6850 step time: 0.5286\n", - "3/8, train_loss: 0.6906 step time: 0.5972\n", - "4/8, train_loss: 0.6771 step time: 0.7087\n", - "5/8, train_loss: 0.6635 step time: 14.4775\n", - "6/8, train_loss: 0.6723 step time: 0.5318\n", - "7/8, train_loss: 0.6568 step time: 0.8064\n", - "8/8, train_loss: 0.6648 step time: 0.8314\n", + "epoch 1/600\n", + "1/8, train_loss: 0.6697 step time: 17.1989\n", + "2/8, train_loss: 0.6850 step time: 0.5307\n", + "3/8, train_loss: 0.6906 step time: 0.6115\n", + "4/8, train_loss: 0.6771 step time: 0.6116\n", + "5/8, train_loss: 0.6635 step time: 14.3529\n", + "6/8, train_loss: 0.6723 step time: 0.5333\n", + "7/8, train_loss: 0.6568 step time: 0.5963\n", + "8/8, train_loss: 0.6648 step time: 0.6781\n", "epoch 1 average loss: 0.6725\n", - "time consuming of epoch 1 is: 35.7880\n", + "time consuming of epoch 1 is: 35.2439\n", "----------\n", - "epoch 2/6\n", - "1/8, train_loss: 0.6596 step time: 17.1820\n", - "2/8, train_loss: 0.6672 step time: 0.5447\n", - "3/8, train_loss: 0.6405 step time: 2.0512\n", - "4/8, train_loss: 0.6333 step time: 0.5276\n", - "5/8, train_loss: 0.6444 step time: 14.9559\n", - "6/8, train_loss: 0.6272 step time: 0.5306\n", - "7/8, train_loss: 0.6257 step time: 2.3935\n", - "8/8, train_loss: 0.6351 step time: 0.5314\n", + "epoch 2/600\n", + "1/8, train_loss: 0.6596 step time: 17.1786\n", + "2/8, train_loss: 0.6672 step time: 0.5336\n", + "3/8, train_loss: 0.6405 step time: 2.1023\n", + "4/8, train_loss: 0.6333 step time: 0.5300\n", + "5/8, train_loss: 0.6444 step time: 14.7795\n", + "6/8, train_loss: 0.6272 step time: 0.5311\n", + "7/8, train_loss: 0.6257 step time: 2.4035\n", + "8/8, train_loss: 0.6351 step time: 0.5317\n", "epoch 2 average loss: 0.6416\n", - "time consuming of epoch 2 is: 39.0296\n", + "time consuming of epoch 2 is: 38.8903\n", "----------\n", - "epoch 3/6\n", - "1/8, train_loss: 0.6546 step time: 14.9289\n", - "2/8, train_loss: 0.6126 step time: 0.7670\n", - "3/8, train_loss: 0.6392 step time: 3.2424\n", - "4/8, train_loss: 0.6240 step time: 0.5350\n", - "5/8, train_loss: 0.6224 step time: 7.0118\n", - "6/8, train_loss: 0.6048 step time: 6.8399\n", - "7/8, train_loss: 0.6162 step time: 2.2157\n", - "8/8, train_loss: 0.6155 step time: 2.4475\n", + "epoch 3/600\n", + "1/8, train_loss: 0.6546 step time: 14.9130\n", + "2/8, train_loss: 0.6126 step time: 0.8331\n", + "3/8, train_loss: 0.6392 step time: 3.5149\n", + "4/8, train_loss: 0.6240 step time: 0.5408\n", + "5/8, train_loss: 0.6224 step time: 6.8608\n", + "6/8, train_loss: 0.6048 step time: 6.7214\n", + "7/8, train_loss: 0.6162 step time: 2.6038\n", + "8/8, train_loss: 0.6155 step time: 2.0409\n", "epoch 3 average loss: 0.6237\n", - "time consuming of epoch 3 is: 38.3414\n", + "time consuming of epoch 3 is: 38.3689\n", "----------\n", - "epoch 4/6\n", - "1/8, train_loss: 0.5985 step time: 15.8969\n", - "2/8, train_loss: 0.5991 step time: 3.9983\n", - "3/8, train_loss: 0.5989 step time: 0.5365\n", - "4/8, train_loss: 0.6410 step time: 0.5532\n", - "5/8, train_loss: 0.6391 step time: 10.6800\n", - "6/8, train_loss: 0.5883 step time: 5.4085\n", - "7/8, train_loss: 0.6105 step time: 0.5291\n", - "8/8, train_loss: 0.6171 step time: 0.5268\n", + "epoch 4/600\n", + "1/8, train_loss: 0.5985 step time: 15.5692\n", + "2/8, train_loss: 0.5991 step time: 4.0304\n", + "3/8, train_loss: 0.5989 step time: 0.5350\n", + "4/8, train_loss: 0.6410 step time: 0.5364\n", + "5/8, train_loss: 0.6391 step time: 10.7004\n", + "6/8, train_loss: 0.5883 step time: 5.4216\n", + "7/8, train_loss: 0.6105 step time: 0.5272\n", + "8/8, train_loss: 0.6171 step time: 0.5292\n", "epoch 4 average loss: 0.6116\n", - "time consuming of epoch 4 is: 38.4674\n", + "time consuming of epoch 4 is: 38.1987\n", "----------\n", - "epoch 5/6\n", - "1/8, train_loss: 0.6162 step time: 12.5105\n", - "2/8, train_loss: 0.5857 step time: 5.8914\n", - "3/8, train_loss: 0.6034 step time: 0.5373\n", - "4/8, train_loss: 0.5965 step time: 0.6103\n", - "5/8, train_loss: 0.6278 step time: 6.4330\n", - "6/8, train_loss: 0.6098 step time: 8.6285\n", - "7/8, train_loss: 0.5912 step time: 0.8754\n", - "8/8, train_loss: 0.6127 step time: 4.0549\n", + "epoch 5/600\n", + "1/8, train_loss: 0.6162 step time: 12.5617\n", + "2/8, train_loss: 0.5857 step time: 6.3806\n", + "3/8, train_loss: 0.6034 step time: 0.5551\n", + "4/8, train_loss: 0.5965 step time: 0.5431\n", + "5/8, train_loss: 0.6278 step time: 6.4910\n", + "6/8, train_loss: 0.6098 step time: 8.7140\n", + "7/8, train_loss: 0.5912 step time: 0.8915\n", + "8/8, train_loss: 0.6127 step time: 3.9683\n", "epoch 5 average loss: 0.6054\n", "saved new best metric model\n", "current epoch: 5 current mean dice: 0.0557 best mean dice: 0.0557 at epoch: 5\n", - "time consuming of epoch 5 is: 49.2248\n", + "time consuming of epoch 5 is: 49.6878\n", "----------\n", - "epoch 6/6\n" + "epoch 6/600\n" ] }, { @@ -825,18 +807,72 @@ "name": "stdout", "output_type": "stream", "text": [ - "1/8, train_loss: 0.6376 step time: 20.9606\n", - "2/8, train_loss: 0.6001 step time: 0.5595\n", - "3/8, train_loss: 0.5945 step time: 0.5393\n", - "4/8, train_loss: 0.5741 step time: 0.5403\n", - "5/8, train_loss: 0.5921 step time: 14.4849\n", - "6/8, train_loss: 0.5781 step time: 0.5264\n", - "7/8, train_loss: 0.5985 step time: 0.5275\n", - "8/8, train_loss: 0.5880 step time: 0.5300\n", + "1/8, train_loss: 0.6376 step time: 21.4406\n", + "2/8, train_loss: 0.6001 step time: 0.5391\n", + "3/8, train_loss: 0.5945 step time: 0.5352\n", + "4/8, train_loss: 0.5741 step time: 0.5328\n", + "5/8, train_loss: 0.5921 step time: 15.2412\n", + "6/8, train_loss: 0.5781 step time: 0.5316\n", + "7/8, train_loss: 0.5985 step time: 0.5329\n", + "8/8, train_loss: 0.5880 step time: 0.5338\n", "epoch 6 average loss: 0.5954\n", - "time consuming of epoch 6 is: 39.0105\n", - "train completed, best_metric: 0.0557 at epoch: 5 total time: 239.8618\n", - "total time of 6 epochs with regular PyTorch training: 241.8329\n" + "time consuming of epoch 6 is: 40.2421\n", + "----------\n", + "epoch 7/600\n", + "1/8, train_loss: 0.5818 step time: 17.3160\n", + "2/8, train_loss: 0.5802 step time: 0.7001\n", + "3/8, train_loss: 0.5856 step time: 0.5309\n", + "4/8, train_loss: 0.5847 step time: 0.5294\n", + "5/8, train_loss: 0.5955 step time: 14.5025\n", + "6/8, train_loss: 0.5791 step time: 0.5279\n", + "7/8, train_loss: 0.5697 step time: 0.9032\n", + "8/8, train_loss: 0.5984 step time: 0.5315\n", + "epoch 7 average loss: 0.5844\n", + "time consuming of epoch 7 is: 35.8987\n", + "----------\n", + "epoch 8/600\n", + "1/8, train_loss: 0.5269 step time: 19.6493\n", + "2/8, train_loss: 0.5973 step time: 0.5280\n", + "3/8, train_loss: 0.5655 step time: 0.5366\n", + "4/8, train_loss: 0.5506 step time: 0.5332\n", + "5/8, train_loss: 0.5897 step time: 16.4449\n", + "6/8, train_loss: 0.5974 step time: 0.5314\n", + "7/8, train_loss: 0.5880 step time: 0.5313\n", + "8/8, train_loss: 0.5854 step time: 0.5317\n", + "epoch 8 average loss: 0.5751\n", + "time consuming of epoch 8 is: 39.6344\n", + "----------\n", + "epoch 9/600\n", + "1/8, train_loss: 0.5801 step time: 17.1434\n", + "2/8, train_loss: 0.5771 step time: 2.3748\n", + "3/8, train_loss: 0.5979 step time: 0.5221\n", + "4/8, train_loss: 0.5484 step time: 0.5908\n", + "5/8, train_loss: 0.5557 step time: 14.9387\n", + "6/8, train_loss: 0.5978 step time: 0.5339\n", + "7/8, train_loss: 0.5727 step time: 0.5332\n", + "8/8, train_loss: 0.5846 step time: 0.5344\n", + "epoch 9 average loss: 0.5768\n", + "time consuming of epoch 9 is: 37.5275\n", + "----------\n", + "epoch 10/600\n", + "1/8, train_loss: 0.5683 step time: 21.5493\n", + "2/8, train_loss: 0.5436 step time: 0.5359\n", + "3/8, train_loss: 0.5819 step time: 0.5328\n", + "4/8, train_loss: 0.5825 step time: 0.5401\n", + "5/8, train_loss: 0.5347 step time: 13.0271\n", + "6/8, train_loss: 0.5402 step time: 0.5289\n", + "7/8, train_loss: 0.5912 step time: 0.5301\n", + "8/8, train_loss: 0.5952 step time: 0.5317\n", + "epoch 10 average loss: 0.5672\n", + "saved new best metric model\n", + "current epoch: 10 current mean dice: 0.0645 best mean dice: 0.0645 at epoch: 10\n", + "time consuming of epoch 10 is: 47.3924\n", + "----------\n", + "epoch 11/600\n", + "1/8, train_loss: 0.5565 step time: 19.8168\n", + "2/8, train_loss: 0.5777 step time: 0.5435\n", + "3/8, train_loss: 0.5736 step time: 0.5426\n", + "4/8, train_loss: 0.5809 step time: 0.5388\n" ] } ], @@ -866,104 +902,9 @@ }, { "cell_type": "code", - "execution_count": 19, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Loading dataset: 100%|███████████████████████████████████████████████████████████████████| 32/32 [00:30<00:00, 1.04it/s]\n", - "Loading dataset: 100%|█████████████████████████████████████████████████████████████████████| 9/9 [00:07<00:00, 1.14it/s]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "----------\n", - "epoch 1/6\n", - "1/8, train_loss: 0.8296 step time: 0.2284\n", - "2/8, train_loss: 0.7642 step time: 0.1946\n", - "3/8, train_loss: 0.5814 step time: 0.1904\n", - "4/8, train_loss: 0.4989 step time: 0.1937\n", - "5/8, train_loss: 0.4850 step time: 0.1941\n", - "6/8, train_loss: 0.4719 step time: 0.1941\n", - "7/8, train_loss: 0.4115 step time: 0.1805\n", - "8/8, train_loss: 0.4362 step time: 0.1840\n", - "epoch 1 average loss: 0.5598\n", - "time consuming of epoch 1 is: 1.5611\n", - "----------\n", - "epoch 2/6\n", - "1/8, train_loss: 0.4431 step time: 0.2278\n", - "2/8, train_loss: 0.4596 step time: 0.1946\n", - "3/8, train_loss: 0.4200 step time: 0.1961\n", - "4/8, train_loss: 0.5280 step time: 0.1859\n", - "5/8, train_loss: 0.5630 step time: 0.1963\n", - "6/8, train_loss: 0.4473 step time: 0.1947\n", - "7/8, train_loss: 0.5153 step time: 0.1825\n", - "8/8, train_loss: 0.5343 step time: 0.1811\n", - "epoch 2 average loss: 0.4888\n", - "time consuming of epoch 2 is: 1.5602\n", - "----------\n", - "epoch 3/6\n", - "1/8, train_loss: 0.4977 step time: 0.2356\n", - "2/8, train_loss: 0.4521 step time: 0.1989\n", - "3/8, train_loss: 0.5149 step time: 0.1996\n", - "4/8, train_loss: 0.4855 step time: 0.1986\n", - "5/8, train_loss: 0.3748 step time: 0.2000\n", - "6/8, train_loss: 0.4201 step time: 0.1978\n", - "7/8, train_loss: 0.3917 step time: 0.1817\n", - "8/8, train_loss: 0.4210 step time: 0.1831\n", - "epoch 3 average loss: 0.4447\n", - "time consuming of epoch 3 is: 1.5968\n", - "----------\n", - "epoch 4/6\n", - "1/8, train_loss: 0.3355 step time: 0.2370\n", - "2/8, train_loss: 0.3301 step time: 0.1972\n", - "3/8, train_loss: 0.1822 step time: 0.1979\n", - "4/8, train_loss: 0.1790 step time: 0.2007\n", - "5/8, train_loss: 0.2337 step time: 0.1998\n", - "6/8, train_loss: 0.2721 step time: 0.2019\n", - "7/8, train_loss: 0.2848 step time: 0.1802\n", - "8/8, train_loss: 0.2908 step time: 0.1816\n", - "epoch 4 average loss: 0.2635\n", - "time consuming of epoch 4 is: 1.5977\n", - "----------\n", - "epoch 5/6\n", - "1/8, train_loss: 0.1574 step time: 0.2378\n", - "2/8, train_loss: 0.1780 step time: 0.1999\n", - "3/8, train_loss: 0.1966 step time: 0.1980\n", - "4/8, train_loss: 0.1346 step time: 0.1988\n", - "5/8, train_loss: 0.1601 step time: 0.2002\n", - "6/8, train_loss: 0.2479 step time: 0.1984\n", - "7/8, train_loss: 0.3215 step time: 0.1812\n", - "8/8, train_loss: 0.1730 step time: 0.1823\n", - "epoch 5 average loss: 0.1961\n", - "saved new best metric model\n", - "current epoch: 5 current mean dice: 0.0511 best mean dice: 0.0511 at epoch: 5\n", - "time consuming of epoch 5 is: 2.4953\n", - "----------\n", - "epoch 6/6\n", - "1/8, train_loss: 0.1274 step time: 0.2372\n", - "2/8, train_loss: 0.1602 step time: 0.1979\n", - "3/8, train_loss: 0.2628 step time: 0.2015\n", - "4/8, train_loss: 0.1241 step time: 0.1984\n", - "5/8, train_loss: 0.1801 step time: 0.1987\n", - "6/8, train_loss: 0.1538 step time: 0.1991\n", - "7/8, train_loss: 0.2318 step time: 0.1811\n", - "8/8, train_loss: 0.2172 step time: 0.1802\n", - "epoch 6 average loss: 0.1822\n", - "time consuming of epoch 6 is: 1.5954\n", - "train completed, best_metric: 0.0511 at epoch: 5 total time: 10.4065\n", - "total time of 6 epochs with MONAI fast training: 10.4065, time of preparing cache: 38.9820\n" - ] - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "set_determinism(seed=0)\n", "monai_start = time.time()\n", @@ -991,26 +932,9 @@ }, { "cell_type": "code", - "execution_count": 11, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "plt.figure(\"train\", (12, 12))\n", "plt.subplot(2, 2, 1)\n", @@ -1046,7 +970,7 @@ "plt.ylim(0, 1)\n", "plt.grid(alpha=0.4, linestyle=\":\")\n", "plt.plot(x, y, color=\"green\")\n", - "plt.show()" + "plt.savefig(\"outputs/loss_dice_comparison.png\")" ] }, { @@ -1058,26 +982,9 @@ }, { "cell_type": "code", - "execution_count": 12, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "plt.figure(\"train\", (12, 6))\n", "plt.subplot(1, 2, 1)\n", @@ -1099,7 +1006,7 @@ "plt.plot(x, m_epoch_times, label=\"Fast training\", color=\"green\")\n", "plt.grid(alpha=0.4, linestyle=\":\")\n", "plt.legend(loc=\"best\")\n", - "plt.show()" + "plt.savefig(\"outputs/total_epoch_time_comparison.png\")" ] }, { @@ -1111,26 +1018,9 @@ }, { "cell_type": "code", - "execution_count": 13, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "def get_best_metric_time(threshold, best_values):\n", " for i, v in enumerate(best_values[0]):\n", @@ -1190,7 +1080,7 @@ " plt.text(l, value, \"%s\" % value, ha=\"center\", va=\"bottom\")\n", "plt.grid(alpha=0.4, linestyle=\":\")\n", "plt.legend(loc=\"best\")\n", - "plt.show()" + "plt.savefig(\"outputs/metric_time_epochs.png\")" ] }, { @@ -1205,11 +1095,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, + "metadata": {}, "outputs": [], "source": [ "if directory is None:\n", @@ -1222,6 +1108,18 @@ "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.13" } }, "nbformat": 4, From b10856184eeece2021ed036f81c24a4798f22329 Mon Sep 17 00:00:00 2001 From: Yuchen Xu Date: Tue, 21 Jun 2022 14:53:51 -0700 Subject: [PATCH 04/12] checkpoint missing nsys figures --- .gitignore | 5 +- acceleration/Figures/nsys-all.png | Bin 0 -> 128697 bytes acceleration/Figures/nsys-epoch-long.png | Bin 0 -> 16026 bytes acceleration/Figures/nsys-fast-transform.png | Bin 0 -> 6327 bytes acceleration/Figures/nsys-transform.png | Bin 0 -> 96097 bytes acceleration/fast_training_tutorial.ipynb | 692 +++++++++--------- acceleration/outputs/loss_dice_comparison.png | Bin 0 -> 76807 bytes acceleration/outputs/metric_time_epochs.png | Bin 0 -> 52227 bytes .../outputs/total_epoch_time_comparison.png | Bin 0 -> 43054 bytes 9 files changed, 331 insertions(+), 366 deletions(-) create mode 100644 acceleration/Figures/nsys-all.png create mode 100644 acceleration/Figures/nsys-epoch-long.png create mode 100644 acceleration/Figures/nsys-fast-transform.png create mode 100644 acceleration/Figures/nsys-transform.png create mode 100644 acceleration/outputs/loss_dice_comparison.png create mode 100644 acceleration/outputs/metric_time_epochs.png create mode 100644 acceleration/outputs/total_epoch_time_comparison.png diff --git a/.gitignore b/.gitignore index c230ba527a..7106fe50ab 100644 --- a/.gitignore +++ b/.gitignore @@ -150,7 +150,4 @@ deployment/bentoml/mednist_classifier_bentoml.py deployment/ray/mednist_classifier_start.py *.nii.gz 3d_segmentation/out - -# archives -archives/ -acceleration/output +*.nsys-rep diff --git a/acceleration/Figures/nsys-all.png b/acceleration/Figures/nsys-all.png new file mode 100644 index 0000000000000000000000000000000000000000..efb42c16170cacc13b8a35f007fb5c303d2c0d18 GIT binary patch literal 128697 zcmZ6y2|Sxw`}nO-XKFfKJkw6AD5hgd)ix+<30O!d4JFIo=@&i?)yH;eV=o#bFOoJuj`zr zcU{%gM<vD2Um}9&5zCE};`rx)tteo80i~n;RvUmSwRZecd%Ko?Oo{8Wkiu{Z7x3Dz<(%EIh 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Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", - " from .autonotebook import tqdm as notebook_tqdm\n" - ] - }, { "name": "stdout", "output_type": "stream", @@ -165,36 +174,11 @@ "print_config()" ] }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "# TODO: set preferred parameters\n", - "\n", - "# overwrite and create a new output directory, True by default\n", - "output_overwrite = True\n", - "\n", - "# set profiling = True to obtain results\n", - "# to use profiling, make sure Nsight systems is installed, and use the following command to run in TERMINAL ONLY:\n", - "# jupyter nbconvert fast_training_tutorial.ipynb --to python && nsys profile --output ./outputs/output_base --force-overwrite true --trace-fork-before-exec true python3 fast_training_tutorial.py && rm fast_training_tutorial.py\n", - "# output will be generated in the current directory (you can change --output)\n", - "profiling = True\n", - "\n", - "# if profiling = True, it is recommended to set max_epochs = 6 for faster prototyping\n", - "# to see the trend in training curve and dice results, set max_epochs to be larger (600)\n", - "# note that before optimization, training can be quite a bit slower\n", - "max_epochs = 6\n", - "\n", - "no_profiling = contextlib.nullcontext()" - ] - }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Setup data directory\n", + "## Setup data & output directories\n", "\n", "You can specify a directory with the `MONAI_DATA_DIRECTORY` environment variable. \n", "This allows you to save results and reuse downloads. \n", @@ -203,14 +187,18 @@ }, { "cell_type": "code", - "execution_count": 4, - "metadata": {}, + "execution_count": 26, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "root dir is: /tmp/tmp7wd9gqnn\n" + "root dir is: /tmp/tmp6rnyagom\n" ] } ], @@ -221,18 +209,104 @@ ] }, { - "cell_type": "code", - "execution_count": 5, + "cell_type": "markdown", "metadata": {}, + "source": [ + "By default, outputs will go to `outputs/`. \n", + "\n", + "You can run this tutorial twice, once with profiling and once without, and the outputs will not conflict with each other. \n", + "- When profiling, the output is `outputs/output_base.nsys-rep`, which you can then visualize using the GUI of Nsight systems (more details below).\n", + "- When not profiling, the outputs are `outputs/loss_dice_comparison.png`, `outputs/metric_time_epochs`, and `outputs/total_epoch_time_comparison.png`.\n", + "\n", + "We set up the tutorial such that figures are only generated when not profiling, but that does not have to be the case. In general, the figures make more sense when training is run for a higher number of epochs (e.g., hundreds), which is usually not the case when profiling." + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [], "source": [ "# outputs\n", "\n", "out_dir = \"outputs/\"\n", "\n", - "if os.path.exists(out_dir) and output_overwrite:\n", - " shutil.rmtree(out_dir)\n", - "os.makedirs(out_dir, exist_ok=True)" + "if not os.path.exists(out_dir):\n", + " os.makedirs(out_dir, exist_ok=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Profiling" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This section sets up profiling for this tutorial.\n", + "\n", + "The number of epochs is automatically set based on whether profiling is being performed, but you can modify as needed.\n", + "\n", + "- If you are not interested in profiling, please set `profiling = False` and move on.\n", + "\n", + "- If you are profiling:\n", + "\n", + " - Because of the currently supported functionality of Nsight systems (`nsys`), profiling can only be performed from the terminal, and not from within this tutorial. For more information, including installation, refer to the [NVIDIA Nsight Systems page](https://developer.nvidia.com/nsight-systems).\n", + " - Perform the following steps:\n", + " \n", + " 1) Make sure `nsys` is installed;\n", + " \n", + " 2) Set `profiling = True`;\n", + " \n", + " 3) Make sure all lines in \"Setup environment\" (first code cell in this tutorial above) are commented out;\n", + " \n", + " 4) Save this notebook;\n", + " \n", + " 5) Open the terminal and ensure that you are in the directory of this notebook, then run this command:\n", + " `jupyter nbconvert fast_training_tutorial.ipynb --to python && nsys profile --output ./outputs/output_base --force-overwrite true --trace-fork-before-exec true python3 fast_training_tutorial.py ; rm fast_training_tutorial.py`\n", + " \n", + " This command converts the notebook to a Python script locally and runs nsys. The output file is outputs/output_base.nsys-rep, but you can modify --output to specify the desired location." + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [], + "source": [ + "profiling = False\n", + "\n", + "# if profiling = True, it is recommended to set max_epochs = 6 for faster prototyping\n", + "# to see the trend in training curve and dice results, set max_epochs to be larger (600)\n", + "# note that before optimization, training can be quite a bit slower\n", + "max_epochs = 6 if profiling else 600\n", + "\n", + "# to improve readability\n", + "range_func_named = lambda x, y: Range(x)(y) if profiling else y\n", + "range_func = lambda y: Range()(y) if profiling else y\n", + "no_profiling = contextlib.nullcontext()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here we give a brief overview of key observations from the `nsys-rep` output file when opened in Nsight systems (2022.2.1).\n", + "\n", + "In the GUI, select File -> Open -> output_base.nsys-rep. Here is a sample of the display:\n", + "\n", + "![png](Figures/nsys-all.PNG)" ] }, { @@ -246,21 +320,25 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": {}, + "execution_count": 29, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "Task09_Spleen.tar: 1.50GB [01:05, 24.5MB/s] " + "Task09_Spleen.tar: 1.50GB [00:41, 39.1MB/s] " ] }, { "name": "stdout", "output_type": "stream", "text": [ - "2022-06-16 22:39:46,307 - INFO - Downloaded: /tmp/tmp7wd9gqnn/Task09_Spleen.tar\n" + "2022-06-21 21:48:22,519 - INFO - Downloaded: /tmp/tmp6rnyagom/Task09_Spleen.tar\n" ] }, { @@ -274,8 +352,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "2022-06-16 22:39:49,673 - INFO - Verified 'Task09_Spleen.tar', md5: 410d4a301da4e5b2f6f86ec3ddba524e.\n", - "2022-06-16 22:39:49,674 - INFO - Writing into directory: /tmp/tmp7wd9gqnn.\n" + "2022-06-21 21:48:25,920 - INFO - Verified 'Task09_Spleen.tar', md5: 410d4a301da4e5b2f6f86ec3ddba524e.\n", + "2022-06-21 21:48:25,921 - INFO - Writing into directory: /tmp/tmp6rnyagom.\n" ] } ], @@ -298,8 +376,12 @@ }, { "cell_type": "code", - "execution_count": 7, - "metadata": {}, + "execution_count": 30, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [], "source": [ "train_images = sorted(\n", @@ -324,28 +406,21 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 31, "metadata": {}, "outputs": [], "source": [ "def transformations(fast=False):\n", " train_transforms = [\n", - " Range(\"LoadImage\")(LoadImaged(keys=[\"image\", \"label\"])) if profiling else LoadImaged(keys=[\"image\", \"label\"]),\n", - " Range()(AddChanneld(keys=[\"image\", \"label\"])) if profiling else AddChanneld(keys=[\"image\", \"label\"]),\n", - " Range()(Orientationd(keys=[\"image\", \"label\"], axcodes=\"RAS\")) if profiling else\n", - " Orientationd(keys=[\"image\", \"label\"], axcodes=\"RAS\"),\n", - " Range(\"Spacing\")(\n", - " Spacingd(\n", + " range_func_named(\"LoadImage\", LoadImaged(keys=[\"image\", \"label\"])),\n", + " range_func(AddChanneld(keys=[\"image\", \"label\"])),\n", + " range_func(Orientationd(keys=[\"image\", \"label\"], axcodes=\"RAS\")),\n", + " range_func_named(\"Spacing\", Spacingd(\n", " keys=[\"image\", \"label\"],\n", " pixdim=(1.5, 1.5, 2.0),\n", " mode=(\"bilinear\", \"nearest\"),\n", - " )) if profiling else\n", - " Spacingd(\n", - " keys=[\"image\", \"label\"],\n", - " pixdim=(1.5, 1.5, 2.0),\n", - " mode=(\"bilinear\", \"nearest\"),\n", - " ),\n", - " Range()(\n", + " )),\n", + " range_func(\n", " ScaleIntensityRanged(\n", " keys=[\"image\"],\n", " a_min=-57,\n", @@ -353,32 +428,16 @@ " b_min=0.0,\n", " b_max=1.0,\n", " clip=True,\n", - " )) if profiling else\n", - " ScaleIntensityRanged(\n", - " keys=[\"image\"],\n", - " a_min=-57,\n", - " a_max=164,\n", - " b_min=0.0,\n", - " b_max=1.0,\n", - " clip=True,\n", - " ),\n", - " Range()(CropForegroundd(keys=[\"image\", \"label\"], source_key=\"image\")\n", - " ) if profiling else CropForegroundd(keys=[\"image\", \"label\"], source_key=\"image\"),\n", + " )),\n", + " range_func(CropForegroundd(keys=[\"image\", \"label\"], source_key=\"image\")),\n", " # pre-compute foreground and background indexes\n", " # and cache them to accelerate training\n", - " Range(\"Indexing\")(\n", - " FgBgToIndicesd(\n", + " range_func_named(\"Indexing\", FgBgToIndicesd(\n", " keys=\"label\",\n", " fg_postfix=\"_fg\",\n", " bg_postfix=\"_bg\",\n", " image_key=\"image\",\n", - " )) if profiling else\n", - " FgBgToIndicesd(\n", - " keys=\"label\",\n", - " fg_postfix=\"_fg\",\n", - " bg_postfix=\"_bg\",\n", - " image_key=\"image\",\n", - " ),\n", + " )),\n", " # change to execute transforms with Tensor data\n", " EnsureTyped(keys=[\"image\", \"label\"]),\n", " ]\n", @@ -394,8 +453,7 @@ " # image based on pos / neg ratio\n", " # the image centers of negative samples\n", " # must be in valid image area\n", - " Range(\"RandCrop\")(\n", - " RandCropByPosNegLabeld(\n", + " range_func_named(\"RandCrop\", RandCropByPosNegLabeld(\n", " keys=[\"image\", \"label\"],\n", " label_key=\"label\",\n", " spatial_size=(96, 96, 96),\n", @@ -404,17 +462,7 @@ " num_samples=4,\n", " fg_indices_key=\"label_fg\",\n", " bg_indices_key=\"label_bg\",\n", - " )) if profiling else\n", - " RandCropByPosNegLabeld(\n", - " keys=[\"image\", \"label\"],\n", - " label_key=\"label\",\n", - " spatial_size=(96, 96, 96),\n", - " pos=1,\n", - " neg=1,\n", - " num_samples=4,\n", - " fg_indices_key=\"label_fg\",\n", - " bg_indices_key=\"label_bg\",\n", - " ),\n", + " )),\n", " )\n", "\n", " val_transforms = [\n", @@ -464,8 +512,12 @@ }, { "cell_type": "code", - "execution_count": 9, - "metadata": {}, + "execution_count": 32, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [], "source": [ "# reference used from https://stackoverflow.com/questions/27803059/conditional-with-statement-in-python/53088625#53088625\n", @@ -476,7 +528,7 @@ " val_interval = 5 # do validation for every epoch\n", "\n", " if torch.cuda.is_available():\n", - " device = torch.device(\"cuda:0\")\n", + " device = torch.device(\"cuda:1\")\n", " else:\n", " raise RuntimeError('this tutorial is intended for GPU, but no CUDA device is available')\n", "\n", @@ -724,158 +776,13 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "----------\n", - "epoch 1/600\n", - "1/8, train_loss: 0.6697 step time: 17.1989\n", - "2/8, train_loss: 0.6850 step time: 0.5307\n", - "3/8, train_loss: 0.6906 step time: 0.6115\n", - "4/8, train_loss: 0.6771 step time: 0.6116\n", - "5/8, train_loss: 0.6635 step time: 14.3529\n", - "6/8, train_loss: 0.6723 step time: 0.5333\n", - "7/8, train_loss: 0.6568 step time: 0.5963\n", - "8/8, train_loss: 0.6648 step time: 0.6781\n", - "epoch 1 average loss: 0.6725\n", - "time consuming of epoch 1 is: 35.2439\n", - "----------\n", - "epoch 2/600\n", - "1/8, train_loss: 0.6596 step time: 17.1786\n", - "2/8, train_loss: 0.6672 step time: 0.5336\n", - "3/8, train_loss: 0.6405 step time: 2.1023\n", - "4/8, train_loss: 0.6333 step time: 0.5300\n", - "5/8, train_loss: 0.6444 step time: 14.7795\n", - "6/8, train_loss: 0.6272 step time: 0.5311\n", - "7/8, train_loss: 0.6257 step time: 2.4035\n", - "8/8, train_loss: 0.6351 step time: 0.5317\n", - "epoch 2 average loss: 0.6416\n", - "time consuming of epoch 2 is: 38.8903\n", - "----------\n", - "epoch 3/600\n", - "1/8, train_loss: 0.6546 step time: 14.9130\n", - "2/8, train_loss: 0.6126 step time: 0.8331\n", - "3/8, train_loss: 0.6392 step time: 3.5149\n", - "4/8, train_loss: 0.6240 step time: 0.5408\n", - "5/8, train_loss: 0.6224 step time: 6.8608\n", - "6/8, train_loss: 0.6048 step time: 6.7214\n", - "7/8, train_loss: 0.6162 step time: 2.6038\n", - "8/8, train_loss: 0.6155 step time: 2.0409\n", - "epoch 3 average loss: 0.6237\n", - "time consuming of epoch 3 is: 38.3689\n", - "----------\n", - "epoch 4/600\n", - "1/8, train_loss: 0.5985 step time: 15.5692\n", - "2/8, train_loss: 0.5991 step time: 4.0304\n", - "3/8, train_loss: 0.5989 step time: 0.5350\n", - "4/8, train_loss: 0.6410 step time: 0.5364\n", - "5/8, train_loss: 0.6391 step time: 10.7004\n", - "6/8, train_loss: 0.5883 step time: 5.4216\n", - "7/8, train_loss: 0.6105 step time: 0.5272\n", - "8/8, train_loss: 0.6171 step time: 0.5292\n", - "epoch 4 average loss: 0.6116\n", - "time consuming of epoch 4 is: 38.1987\n", - "----------\n", - "epoch 5/600\n", - "1/8, train_loss: 0.6162 step time: 12.5617\n", - "2/8, train_loss: 0.5857 step time: 6.3806\n", - "3/8, train_loss: 0.6034 step time: 0.5551\n", - "4/8, train_loss: 0.5965 step time: 0.5431\n", - "5/8, train_loss: 0.6278 step time: 6.4910\n", - "6/8, train_loss: 0.6098 step time: 8.7140\n", - "7/8, train_loss: 0.5912 step time: 0.8915\n", - "8/8, train_loss: 0.6127 step time: 3.9683\n", - "epoch 5 average loss: 0.6054\n", - "saved new best metric model\n", - "current epoch: 5 current mean dice: 0.0557 best mean dice: 0.0557 at epoch: 5\n", - "time consuming of epoch 5 is: 49.6878\n", - "----------\n", - "epoch 6/600\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "positional arguments and argument \"destination\" are deprecated. nn.Module.state_dict will not accept them in the future. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "1/8, train_loss: 0.6376 step time: 21.4406\n", - "2/8, train_loss: 0.6001 step time: 0.5391\n", - "3/8, train_loss: 0.5945 step time: 0.5352\n", - "4/8, train_loss: 0.5741 step time: 0.5328\n", - "5/8, train_loss: 0.5921 step time: 15.2412\n", - "6/8, train_loss: 0.5781 step time: 0.5316\n", - "7/8, train_loss: 0.5985 step time: 0.5329\n", - "8/8, train_loss: 0.5880 step time: 0.5338\n", - "epoch 6 average loss: 0.5954\n", - "time consuming of epoch 6 is: 40.2421\n", - "----------\n", - "epoch 7/600\n", - "1/8, train_loss: 0.5818 step time: 17.3160\n", - "2/8, train_loss: 0.5802 step time: 0.7001\n", - "3/8, train_loss: 0.5856 step time: 0.5309\n", - "4/8, train_loss: 0.5847 step time: 0.5294\n", - "5/8, train_loss: 0.5955 step time: 14.5025\n", - "6/8, train_loss: 0.5791 step time: 0.5279\n", - "7/8, train_loss: 0.5697 step time: 0.9032\n", - "8/8, train_loss: 0.5984 step time: 0.5315\n", - "epoch 7 average loss: 0.5844\n", - "time consuming of epoch 7 is: 35.8987\n", - "----------\n", - "epoch 8/600\n", - "1/8, train_loss: 0.5269 step time: 19.6493\n", - "2/8, train_loss: 0.5973 step time: 0.5280\n", - "3/8, train_loss: 0.5655 step time: 0.5366\n", - "4/8, train_loss: 0.5506 step time: 0.5332\n", - "5/8, train_loss: 0.5897 step time: 16.4449\n", - "6/8, train_loss: 0.5974 step time: 0.5314\n", - "7/8, train_loss: 0.5880 step time: 0.5313\n", - "8/8, train_loss: 0.5854 step time: 0.5317\n", - "epoch 8 average loss: 0.5751\n", - "time consuming of epoch 8 is: 39.6344\n", - "----------\n", - "epoch 9/600\n", - "1/8, train_loss: 0.5801 step time: 17.1434\n", - "2/8, train_loss: 0.5771 step time: 2.3748\n", - "3/8, train_loss: 0.5979 step time: 0.5221\n", - "4/8, train_loss: 0.5484 step time: 0.5908\n", - "5/8, train_loss: 0.5557 step time: 14.9387\n", - "6/8, train_loss: 0.5978 step time: 0.5339\n", - "7/8, train_loss: 0.5727 step time: 0.5332\n", - "8/8, train_loss: 0.5846 step time: 0.5344\n", - "epoch 9 average loss: 0.5768\n", - "time consuming of epoch 9 is: 37.5275\n", - "----------\n", - "epoch 10/600\n", - "1/8, train_loss: 0.5683 step time: 21.5493\n", - "2/8, train_loss: 0.5436 step time: 0.5359\n", - "3/8, train_loss: 0.5819 step time: 0.5328\n", - "4/8, train_loss: 0.5825 step time: 0.5401\n", - "5/8, train_loss: 0.5347 step time: 13.0271\n", - "6/8, train_loss: 0.5402 step time: 0.5289\n", - "7/8, train_loss: 0.5912 step time: 0.5301\n", - "8/8, train_loss: 0.5952 step time: 0.5317\n", - "epoch 10 average loss: 0.5672\n", - "saved new best metric model\n", - "current epoch: 10 current mean dice: 0.0645 best mean dice: 0.0645 at epoch: 10\n", - "time consuming of epoch 10 is: 47.3924\n", - "----------\n", - "epoch 11/600\n", - "1/8, train_loss: 0.5565 step time: 19.8168\n", - "2/8, train_loss: 0.5777 step time: 0.5435\n", - "3/8, train_loss: 0.5736 step time: 0.5426\n", - "4/8, train_loss: 0.5809 step time: 0.5388\n" - ] + "metadata": { + "scrolled": false, + "vscode": { + "languageId": "python" } - ], + }, + "outputs": [], "source": [ "set_determinism(seed=0)\n", "regular_start = time.time()\n", @@ -903,7 +810,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [], "source": [ "set_determinism(seed=0)\n", @@ -932,45 +843,63 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 12, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "

" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ - "plt.figure(\"train\", (12, 12))\n", - "plt.subplot(2, 2, 1)\n", - "plt.title(\"Regular Epoch Average Loss\")\n", - "x = [i + 1 for i in range(len(epoch_loss_values))]\n", - "y = epoch_loss_values\n", - "plt.xlabel(\"epoch\")\n", - "plt.grid(alpha=0.4, linestyle=\":\")\n", - "plt.plot(x, y, color=\"red\")\n", - "\n", - "plt.subplot(2, 2, 2)\n", - "plt.title(\"Regular Val Mean Dice\")\n", - "x = [i + 1 for i in range(len(metric_values))]\n", - "y = metric_values\n", - "plt.xlabel(\"epoch\")\n", - "plt.ylim(0, 1)\n", - "plt.grid(alpha=0.4, linestyle=\":\")\n", - "plt.plot(x, y, color=\"red\")\n", - "\n", - "plt.subplot(2, 2, 3)\n", - "plt.title(\"Fast Epoch Average Loss\")\n", - "x = [i + 1 for i in range(len(m_epoch_loss_values))]\n", - "y = m_epoch_loss_values\n", - "plt.xlabel(\"epoch\")\n", - "plt.grid(alpha=0.4, linestyle=\":\")\n", - "plt.plot(x, y, color=\"green\")\n", - "\n", - "plt.subplot(2, 2, 4)\n", - "plt.title(\"Fast Val Mean Dice\")\n", - "x = [i + 1 for i in range(len(m_metric_values))]\n", - "y = m_metric_values\n", - "plt.xlabel(\"epoch\")\n", - "plt.ylim(0, 1)\n", - "plt.grid(alpha=0.4, linestyle=\":\")\n", - "plt.plot(x, y, color=\"green\")\n", - "plt.savefig(\"outputs/loss_dice_comparison.png\")" + "if not profiling:\n", + " plt.figure(\"train\", (12, 12))\n", + " plt.subplot(2, 2, 1)\n", + " plt.title(\"Regular Epoch Average Loss\")\n", + " x = [i + 1 for i in range(len(epoch_loss_values))]\n", + " y = epoch_loss_values\n", + " plt.xlabel(\"epoch\")\n", + " plt.grid(alpha=0.4, linestyle=\":\")\n", + " plt.plot(x, y, color=\"red\")\n", + "\n", + " plt.subplot(2, 2, 2)\n", + " plt.title(\"Regular Val Mean Dice\")\n", + " x = [i + 1 for i in range(len(metric_values))]\n", + " y = metric_values\n", + " plt.xlabel(\"epoch\")\n", + " plt.ylim(0, 1)\n", + " plt.grid(alpha=0.4, linestyle=\":\")\n", + " plt.plot(x, y, color=\"red\")\n", + "\n", + " plt.subplot(2, 2, 3)\n", + " plt.title(\"Fast Epoch Average Loss\")\n", + " x = [i + 1 for i in range(len(m_epoch_loss_values))]\n", + " y = m_epoch_loss_values\n", + " plt.xlabel(\"epoch\")\n", + " plt.grid(alpha=0.4, linestyle=\":\")\n", + " plt.plot(x, y, color=\"green\")\n", + "\n", + " plt.subplot(2, 2, 4)\n", + " plt.title(\"Fast Val Mean Dice\")\n", + " x = [i + 1 for i in range(len(m_metric_values))]\n", + " y = m_metric_values\n", + " plt.xlabel(\"epoch\")\n", + " plt.ylim(0, 1)\n", + " plt.grid(alpha=0.4, linestyle=\":\")\n", + " plt.plot(x, y, color=\"green\")\n", + " plt.savefig(\"outputs/loss_dice_comparison.png\")" ] }, { @@ -982,31 +911,49 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 13, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ - "plt.figure(\"train\", (12, 6))\n", - "plt.subplot(1, 2, 1)\n", - "plt.title(\"Total Train Time(600 epochs)\")\n", - "plt.bar(\n", - " \"regular PyTorch\", total_time, 1, label=\"Regular training\", color=\"red\"\n", - ")\n", - "plt.bar(\"Fast\", m_total_time, 1, label=\"Fast training\", color=\"green\")\n", - "plt.ylabel(\"secs\")\n", - "plt.grid(alpha=0.4, linestyle=\":\")\n", - "plt.legend(loc=\"best\")\n", - "\n", - "plt.subplot(1, 2, 2)\n", - "plt.title(\"Epoch Time\")\n", - "x = [i + 1 for i in range(len(epoch_times))]\n", - "plt.xlabel(\"epoch\")\n", - "plt.ylabel(\"secs\")\n", - "plt.plot(x, epoch_times, label=\"Regular training\", color=\"red\")\n", - "plt.plot(x, m_epoch_times, label=\"Fast training\", color=\"green\")\n", - "plt.grid(alpha=0.4, linestyle=\":\")\n", - "plt.legend(loc=\"best\")\n", - "plt.savefig(\"outputs/total_epoch_time_comparison.png\")" + "if not profiling:\n", + " plt.figure(\"train\", (12, 6))\n", + " plt.subplot(1, 2, 1)\n", + " plt.title(\"Total Train Time(600 epochs)\")\n", + " plt.bar(\n", + " \"regular PyTorch\", total_time, 1, label=\"Regular training\", color=\"red\"\n", + " )\n", + " plt.bar(\"Fast\", m_total_time, 1, label=\"Fast training\", color=\"green\")\n", + " plt.ylabel(\"secs\")\n", + " plt.grid(alpha=0.4, linestyle=\":\")\n", + " plt.legend(loc=\"best\")\n", + "\n", + " plt.subplot(1, 2, 2)\n", + " plt.title(\"Epoch Time\")\n", + " x = [i + 1 for i in range(len(epoch_times))]\n", + " plt.xlabel(\"epoch\")\n", + " plt.ylabel(\"secs\")\n", + " plt.plot(x, epoch_times, label=\"Regular training\", color=\"red\")\n", + " plt.plot(x, m_epoch_times, label=\"Fast training\", color=\"green\")\n", + " plt.grid(alpha=0.4, linestyle=\":\")\n", + " plt.legend(loc=\"best\")\n", + " plt.savefig(\"outputs/total_epoch_time_comparison.png\")" ] }, { @@ -1018,9 +965,26 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 14, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "def get_best_metric_time(threshold, best_values):\n", " for i, v in enumerate(best_values[0]):\n", @@ -1044,43 +1008,43 @@ " else:\n", " return None\n", "\n", + "if not profiling:\n", + " plt.figure(\"train\", (18, 6))\n", + " plt.subplot(1, 3, 1)\n", + " plt.title(\"Metrics Time\")\n", + " plt.xlabel(\"secs\")\n", + " plt.ylabel(\"best mean_dice\")\n", + " plt.plot(best[2], best[0], label=\"Regular training\", color=\"red\")\n", + " plt.plot(m_best[2], m_best[0], label=\"Fast training\", color=\"green\")\n", + " plt.grid(alpha=0.4, linestyle=\":\")\n", + " plt.legend(loc=\"best\")\n", "\n", - "plt.figure(\"train\", (18, 6))\n", - "plt.subplot(1, 3, 1)\n", - "plt.title(\"Metrics Time\")\n", - "plt.xlabel(\"secs\")\n", - "plt.ylabel(\"best mean_dice\")\n", - "plt.plot(best[2], best[0], label=\"Regular training\", color=\"red\")\n", - "plt.plot(m_best[2], m_best[0], label=\"Fast training\", color=\"green\")\n", - "plt.grid(alpha=0.4, linestyle=\":\")\n", - "plt.legend(loc=\"best\")\n", - "\n", - "plt.subplot(1, 3, 2)\n", - "plt.title(\"Typical Metrics Time\")\n", - "plt.xlabel(\"best mean_dice\")\n", - "plt.ylabel(\"secs\")\n", - "labels = [\"0.80\", \"0.80 \", \"0.90\", \"0.90 \", \"0.92\", \"0.92 \", \"0.94\", \"0.94 \"]\n", - "x_values = [0.8, 0.8, 0.9, 0.9, 0.92, 0.92, 0.94, 0.94]\n", - "for i, (l, x) in enumerate(zip(labels, x_values)):\n", - " value = int(get_best_metric_time(x, best if i % 2 == 0 else m_best))\n", - " color = \"red\" if i % 2 == 0 else \"green\"\n", - " plt.bar(l, value, 0.5, label=get_label(i), color=color)\n", - " plt.text(l, value, \"%s\" % value, ha=\"center\", va=\"bottom\")\n", - "plt.grid(alpha=0.4, linestyle=\":\")\n", - "plt.legend(loc=\"best\")\n", - "\n", - "plt.subplot(1, 3, 3)\n", - "plt.title(\"Typical Metrics Epochs\")\n", - "plt.xlabel(\"best mean_dice\")\n", - "plt.ylabel(\"epochs\")\n", - "for i, (l, x) in enumerate(zip(labels, x_values)):\n", - " value = int(get_best_metric_epochs(x, best if i % 2 == 0 else m_best))\n", - " color = \"red\" if i % 2 == 0 else \"green\"\n", - " plt.bar(l, value, 0.5, label=get_label(i), color=color)\n", - " plt.text(l, value, \"%s\" % value, ha=\"center\", va=\"bottom\")\n", - "plt.grid(alpha=0.4, linestyle=\":\")\n", - "plt.legend(loc=\"best\")\n", - "plt.savefig(\"outputs/metric_time_epochs.png\")" + " plt.subplot(1, 3, 2)\n", + " plt.title(\"Typical Metrics Time\")\n", + " plt.xlabel(\"best mean_dice\")\n", + " plt.ylabel(\"secs\")\n", + " labels = [\"0.80\", \"0.80 \", \"0.90\", \"0.90 \", \"0.92\", \"0.92 \", \"0.94\", \"0.94 \"]\n", + " x_values = [0.8, 0.8, 0.9, 0.9, 0.92, 0.92, 0.94, 0.94]\n", + " for i, (l, x) in enumerate(zip(labels, x_values)):\n", + " value = int(get_best_metric_time(x, best if i % 2 == 0 else m_best))\n", + " color = \"red\" if i % 2 == 0 else \"green\"\n", + " plt.bar(l, value, 0.5, label=get_label(i), color=color)\n", + " plt.text(l, value, \"%s\" % value, ha=\"center\", va=\"bottom\")\n", + " plt.grid(alpha=0.4, linestyle=\":\")\n", + " plt.legend(loc=\"best\")\n", + "\n", + " plt.subplot(1, 3, 3)\n", + " plt.title(\"Typical Metrics Epochs\")\n", + " plt.xlabel(\"best mean_dice\")\n", + " plt.ylabel(\"epochs\")\n", + " for i, (l, x) in enumerate(zip(labels, x_values)):\n", + " value = int(get_best_metric_epochs(x, best if i % 2 == 0 else m_best))\n", + " color = \"red\" if i % 2 == 0 else \"green\"\n", + " plt.bar(l, value, 0.5, label=get_label(i), color=color)\n", + " plt.text(l, value, \"%s\" % value, ha=\"center\", va=\"bottom\")\n", + " plt.grid(alpha=0.4, linestyle=\":\")\n", + " plt.legend(loc=\"best\")\n", + " plt.savefig(\"outputs/metric_time_epochs.png\")" ] }, { @@ -1094,8 +1058,12 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, + "execution_count": 15, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [], "source": [ "if directory is 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\n", + "image/png": 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", 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\n", 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"text/plain": [ "
" ] @@ -1087,18 +1091,6 @@ "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.13" } }, "nbformat": 4, From 880738ae58230168796eb0a8cb2b82a4e61a2694 Mon Sep 17 00:00:00 2001 From: Yuchen Xu Date: Fri, 24 Jun 2022 09:23:14 -0700 Subject: [PATCH 08/12] removed output files --- acceleration/fast_training_tutorial.ipynb | 30 ++++++++++-------- acceleration/outputs/loss_dice_comparison.png | Bin 76807 -> 0 bytes acceleration/outputs/metric_time_epochs.png | Bin 52227 -> 0 bytes .../outputs/total_epoch_time_comparison.png | Bin 43054 -> 0 bytes 4 files changed, 17 insertions(+), 13 deletions(-) delete mode 100644 acceleration/outputs/loss_dice_comparison.png delete mode 100644 acceleration/outputs/metric_time_epochs.png delete mode 100644 acceleration/outputs/total_epoch_time_comparison.png diff --git a/acceleration/fast_training_tutorial.ipynb b/acceleration/fast_training_tutorial.ipynb index be47bf6351..51c5c78861 100644 --- a/acceleration/fast_training_tutorial.ipynb +++ b/acceleration/fast_training_tutorial.ipynb @@ -46,7 +46,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 13, "metadata": { "vscode": { "languageId": "python" @@ -72,21 +72,13 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 14, "metadata": { "vscode": { "languageId": "python" } }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/conda/lib/python3.8/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", - " from .autonotebook import tqdm as notebook_tqdm\n" - ] - }, { "name": "stdout", "output_type": "stream", @@ -195,7 +187,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 16, "metadata": { "vscode": { "languageId": "python" @@ -206,7 +198,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "root dir is: /tmp/tmp87h4yebg\n" + "root dir is: /tmp/tmpospsolbn\n" ] } ], @@ -231,7 +223,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 17, "metadata": { "vscode": { "languageId": "python" @@ -1091,6 +1083,18 @@ "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.13" } }, "nbformat": 4, 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z+lr~z+2N?iXw3RjDfk zTI}v%zs;Q}D}L53acZ7D1g;){e6`rhL50hqaCKG)}Q|GCCpa|asU_~+i!s?6ep z<1vJp^Uau{TL}jBo0PoT`X@CXag!qY&A`no&|lDC!CI%%tzDoEUXR)%oi{M`(SH;7 eKm7iG4@)!pJ;5goZ~9(9yKn(V{G0zyD*YF$EAZF= From 5a9cd3f563270c29e201281ec03f7385abf6457a Mon Sep 17 00:00:00 2001 From: Yuchen Xu Date: Tue, 28 Jun 2022 19:27:58 -0700 Subject: [PATCH 09/12] intermediate commit with experiments included --- .gitignore | 1 + acceleration/fast_training_tutorial.ipynb | 23137 +++++++++++++++- .../nsys-all-annotated.png | Bin .../{Figures => figures}/nsys-epoch-long.png | Bin .../{Figures => figures}/nsys-epoch-short.png | Bin .../nsys-fast-transform.png | Bin .../nsys-transforms-annotated.png | Bin 7 files changed, 23113 insertions(+), 25 deletions(-) rename acceleration/{Figures => figures}/nsys-all-annotated.png (100%) rename acceleration/{Figures => figures}/nsys-epoch-long.png (100%) rename acceleration/{Figures => figures}/nsys-epoch-short.png (100%) rename acceleration/{Figures => figures}/nsys-fast-transform.png (100%) rename acceleration/{Figures => figures}/nsys-transforms-annotated.png (100%) diff --git a/.gitignore b/.gitignore index 7106fe50ab..2327c1d595 100644 --- a/.gitignore +++ b/.gitignore @@ -151,3 +151,4 @@ deployment/ray/mednist_classifier_start.py *.nii.gz 3d_segmentation/out *.nsys-rep +acceleration/outputs diff --git a/acceleration/fast_training_tutorial.ipynb b/acceleration/fast_training_tutorial.ipynb index 51c5c78861..62aef50be6 100644 --- a/acceleration/fast_training_tutorial.ipynb +++ b/acceleration/fast_training_tutorial.ipynb @@ -1,7 +1,7 @@ { "cells": [ { - "cell_type": "markdown", + "cell_type": "raw", "metadata": {}, "source": [ "# Fast training with MONAI features" @@ -46,7 +46,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 1, "metadata": { "vscode": { "languageId": "python" @@ -60,7 +60,7 @@ "# !python3 -c \"import matplotlib\" || pip install -q matplotlib\n", "# !python3 -c \"import nvtx\" || pip install -q nvtx\n", "\n", - "# %matplotlib inline" + "%matplotlib inline" ] }, { @@ -72,28 +72,36 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 2, "metadata": { "vscode": { "languageId": "python" } }, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/conda/lib/python3.8/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", + " from .autonotebook import tqdm as notebook_tqdm\n" + ] + }, { "name": "stdout", "output_type": "stream", "text": [ - "MONAI version: 0.9.0rc2\n", + "MONAI version: 0.9.0\n", "Numpy version: 1.22.3\n", "Pytorch version: 1.12.0a0+bd13bc6\n", "MONAI flags: HAS_EXT = True, USE_COMPILED = False\n", - "MONAI rev id: d8d24eed0ee7705afd55050af0709613fddacb96\n", + "MONAI rev id: af0e0e9f757558d144b655c63afcea3a4e0a06f5\n", "MONAI __file__: /opt/monai/monai/__init__.py\n", "\n", "Optional dependencies:\n", "Pytorch Ignite version: 0.4.8\n", "Nibabel version: 3.2.2\n", - "scikit-image version: 0.19.2\n", + "scikit-image version: 0.19.3\n", "Pillow version: 9.0.1\n", "Tensorboard version: 2.8.0\n", "gdown version: 4.4.0\n", @@ -103,7 +111,7 @@ "psutil version: 5.9.0\n", "pandas version: 1.3.5\n", "einops version: 0.4.1\n", - "transformers version: 4.19.2\n", + "transformers version: 4.19.4\n", "mlflow version: 1.26.1\n", "pynrrd version: 0.4.3\n", "\n", @@ -187,7 +195,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 3, "metadata": { "vscode": { "languageId": "python" @@ -198,7 +206,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "root dir is: /tmp/tmpospsolbn\n" + "root dir is: /tmp/tmpv0msvmnr\n" ] } ], @@ -223,7 +231,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 4, "metadata": { "vscode": { "languageId": "python" @@ -277,7 +285,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "metadata": { "vscode": { "languageId": "python" @@ -285,7 +293,7 @@ }, "outputs": [], "source": [ - "profiling = True\n", + "profiling = False\n", "\n", "# if profiling = True, it is recommended to set max_epochs = 6 for faster prototyping\n", "# to see the trend in training curve and dice results, set max_epochs to be larger (600)\n", @@ -312,13 +320,43 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": { "vscode": { "languageId": "python" } }, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Task09_Spleen.tar: 1.50GB [01:00, 26.7MB/s] " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2022-06-28 03:56:26,901 - INFO - Downloaded: /tmp/tmpv0msvmnr/Task09_Spleen.tar\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2022-06-28 03:56:30,190 - INFO - Verified 'Task09_Spleen.tar', md5: 410d4a301da4e5b2f6f86ec3ddba524e.\n", + "2022-06-28 03:56:30,191 - INFO - Writing into directory: /tmp/tmpv0msvmnr.\n" + ] + } + ], "source": [ "resource = \"https://msd-for-monai.s3-us-west-2.amazonaws.com/Task09_Spleen.tar\"\n", "md5 = \"410d4a301da4e5b2f6f86ec3ddba524e\"\n", @@ -338,7 +376,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 7, "metadata": { "vscode": { "languageId": "python" @@ -368,7 +406,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 8, "metadata": { "vscode": { "languageId": "python" @@ -478,7 +516,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 31, "metadata": { "vscode": { "languageId": "python" @@ -514,6 +552,7 @@ " # disable multi-workers because `ThreadDataLoader` works with multi-threads\n", " train_loader = ThreadDataLoader(train_ds, num_workers=0, batch_size=4, shuffle=True)\n", " val_loader = ThreadDataLoader(val_ds, num_workers=0, batch_size=1)\n", + "\n", " loss_function = DiceCELoss(\n", " include_background=False,\n", " to_onehot_y=True,\n", @@ -532,7 +571,7 @@ " channels=(32, 64, 128, 256, 512),\n", " strides=(2, 2, 2, 2),\n", " num_res_units=2,\n", - " norm=Norm.BATCH,\n", + " norm=Norm.instance,\n", " kernel_size=3,\n", " up_kernel_size=3,\n", " act=Act.PRELU,\n", @@ -797,6 +836,23054 @@ ")" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Experiments" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Loading dataset: 100%|█████████████████████████████████████████████████████████████████████████| 32/32 [00:33<00:00, 1.04s/it]\n", + "Loading dataset: 100%|███████████████████████████████████████████████████████████████████████████| 9/9 [00:08<00:00, 1.11it/s]\n" + ] + } + ], + "source": [ + "set_determinism(seed=0)\n", + "fast = True\n", + "\n", + "learning_rate = 2e-4\n", + "val_interval = 5 # do validation for every epoch\n", + "\n", + "if torch.cuda.is_available():\n", + " device = torch.device(\"cuda:0\")\n", + "else:\n", + " raise RuntimeError('this tutorial is intended for GPU, but no CUDA device is available')\n", + "\n", + "train_trans, val_trans = transformations(fast=fast, device=device)\n", + "# set CacheDataset, ThreadDataLoader and DiceCE loss for MONAI fast training\n", + "\n", + "# as `RandCropByPosNegLabeld` crops from the cached content and `deepcopy`\n", + "# the crop area instead of modifying the cached value, we can set `copy_cache=False`\n", + "# to avoid unnecessary deepcopy of cached content in `CacheDataset`\n", + "train_ds = CacheDataset(\n", + " data=train_files,\n", + " transform=train_trans,\n", + " cache_rate=1.0,\n", + " num_workers=8,\n", + " copy_cache=False,\n", + ")\n", + "val_ds = CacheDataset(\n", + " data=val_files, transform=val_trans, cache_rate=1.0, num_workers=5, copy_cache=False\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "# disable multi-workers because `ThreadDataLoader` works with multi-threads\n", + "train_loader = ThreadDataLoader(train_ds, use_thread_workers=False, num_workers=0, batch_size=4, shuffle=True)\n", + "val_loader = ThreadDataLoader(val_ds, use_thread_workers=False, num_workers=0, batch_size=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [], + "source": [ + "# disable multi-workers because `ThreadDataLoader` works with multi-threads\n", + "loss_function = DiceCELoss(\n", + " include_background=False,\n", + " to_onehot_y=True,\n", + " softmax=True,\n", + " squared_pred=True,\n", + " batch=True,\n", + " smooth_nr=0.00001,\n", + " smooth_dr=0.00001,\n", + " lambda_dice=0.5,\n", + " lambda_ce=0.5,\n", + ")\n", + "model = UNet(\n", + " spatial_dims=3,\n", + " in_channels=1,\n", + " out_channels=2,\n", + " channels=(32, 64, 128, 256, 512),\n", + " strides=(2, 2, 2, 2),\n", + " num_res_units=2,\n", + " norm=Norm.BATCH,\n", + " kernel_size=3,\n", + " up_kernel_size=3,\n", + " act=Act.PRELU,\n", + " dropout=0.2,\n", + " bias=True,\n", + " dimensions=None,\n", + ").to(device)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "\n", + "# train_load_per_op = tlpo\n", + "tlpo_dict, time_dict, metric_dict, loss_dict = {}, {}, {}, {}" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "----------\n", + "epoch 1/600\n", + "1/8, train_loss: 0.7790 step time: 0.2530\n", + "2/8, train_loss: 0.6703 step time: 0.1966\n", + "3/8, train_loss: 0.5067 step time: 0.1951\n", + "4/8, train_loss: 0.4607 step time: 0.1928\n", + "5/8, train_loss: 0.4546 step time: 0.1955\n", + "6/8, train_loss: 0.4509 step time: 0.1940\n", + "7/8, train_loss: 0.4756 step time: 0.1836\n", + "8/8, train_loss: 0.4160 step time: 0.1828\n", + "epoch 1 average loss: 0.5267\n", + "time consuming of epoch 1 is: 1.5947\n", + "----------\n", + "epoch 2/600\n", + "1/8, train_loss: 0.4516 step time: 0.2394\n", + "2/8, train_loss: 0.4172 step time: 0.2041\n", + "3/8, train_loss: 0.6438 step time: 0.1905\n", + "4/8, train_loss: 0.6094 step time: 0.1995\n", + "5/8, train_loss: 0.4216 step time: 0.2017\n", + "6/8, train_loss: 0.5499 step time: 0.2015\n", + "7/8, train_loss: 0.5725 step time: 0.1833\n", + "8/8, train_loss: 0.5541 step time: 0.1823\n", + "epoch 2 average loss: 0.5275\n", + "time consuming of epoch 2 is: 1.6041\n", + "----------\n", + "epoch 3/600\n", + "1/8, train_loss: 0.6049 step time: 0.2423\n", + "2/8, train_loss: 0.5896 step time: 0.2031\n", + "3/8, train_loss: 0.5955 step time: 0.2001\n", + "4/8, train_loss: 0.5692 step time: 0.2019\n", + "5/8, train_loss: 0.5608 step time: 0.2036\n", + "6/8, train_loss: 0.5988 step time: 0.2058\n", + "7/8, train_loss: 0.5444 step time: 0.1822\n", + "8/8, train_loss: 0.4742 step time: 0.1823\n", + "epoch 3 average loss: 0.5672\n", + "time consuming of epoch 3 is: 1.6230\n", + "----------\n", + "epoch 4/600\n", + "1/8, train_loss: 0.5163 step time: 0.2313\n", + "2/8, train_loss: 0.4702 step time: 0.1990\n", + "3/8, train_loss: 0.4418 step time: 0.1977\n", + "4/8, train_loss: 0.4512 step time: 0.1951\n", + "5/8, train_loss: 0.4361 step time: 0.1976\n", + "6/8, train_loss: 0.4215 step time: 0.2001\n", + "7/8, train_loss: 0.4655 step time: 0.1824\n", + "8/8, train_loss: 0.4448 step time: 0.1830\n", + "epoch 4 average loss: 0.4559\n", + "time consuming of epoch 4 is: 1.5878\n", + "----------\n", + "epoch 5/600\n", + "1/8, train_loss: 0.4356 step time: 0.2428\n", + "2/8, train_loss: 0.4663 step time: 0.2005\n", + "3/8, train_loss: 0.4176 step time: 0.2092\n", + "4/8, train_loss: 0.4016 step time: 0.2069\n", + "5/8, train_loss: 0.4068 step time: 0.2041\n", + "6/8, train_loss: 0.4240 step time: 0.2069\n", + "7/8, train_loss: 0.4158 step time: 0.1844\n", + "8/8, train_loss: 0.4185 step time: 0.1848\n", + "epoch 5 average loss: 0.4233\n", + "saved new best metric model\n", + "current epoch: 5 current mean dice: 0.0000 best mean dice: 0.0000 at epoch: 5\n", + "time consuming of epoch 5 is: 2.5513\n", + "----------\n", + "epoch 6/600\n", + "1/8, train_loss: 0.4299 step time: 0.2405\n", + "2/8, train_loss: 0.3908 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"stream", + "text": [ + "saved new best metric model\n", + "current epoch: 505 current mean dice: 0.9601 best mean dice: 0.9601 at epoch: 505\n", + "time consuming of epoch 505 is: 2.5339\n", + "----------\n", + "epoch 506/600\n", + "1/8, train_loss: 0.0122 step time: 0.2301\n", + "2/8, train_loss: 0.0118 step time: 0.1953\n", + "3/8, train_loss: 0.0135 step time: 0.1988\n", + "4/8, train_loss: 0.0116 step time: 0.2029\n", + "5/8, train_loss: 0.0111 step time: 0.1980\n", + "6/8, train_loss: 0.0141 step time: 0.2013\n", + "7/8, train_loss: 0.0103 step time: 0.1822\n", + "8/8, train_loss: 0.0106 step time: 0.1820\n", + "epoch 506 average loss: 0.0119\n", + "time consuming of epoch 506 is: 1.5921\n", + "----------\n", + "epoch 507/600\n", + "1/8, train_loss: 0.0143 step time: 0.2373\n", + "2/8, train_loss: 0.0100 step time: 0.2017\n", + "3/8, train_loss: 0.0115 step time: 0.1992\n", + "4/8, train_loss: 0.0099 step time: 0.2005\n", + "5/8, train_loss: 0.0112 step time: 0.2019\n", + "6/8, 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"time consuming of epoch 516 is: 1.6025\n", + "----------\n", + "epoch 517/600\n", + "1/8, train_loss: 0.0160 step time: 0.2407\n", + "2/8, train_loss: 0.0105 step time: 0.2038\n", + "3/8, train_loss: 0.0122 step time: 0.1999\n", + "4/8, train_loss: 0.0085 step time: 0.2005\n", + "5/8, train_loss: 0.0102 step time: 0.2006\n", + "6/8, train_loss: 0.0110 step time: 0.2007\n", + "7/8, train_loss: 0.0109 step time: 0.1829\n", + "8/8, train_loss: 0.0123 step time: 0.1823\n", + "epoch 517 average loss: 0.0114\n", + "time consuming of epoch 517 is: 1.6129\n", + "----------\n", + "epoch 518/600\n", + "1/8, train_loss: 0.0121 step time: 0.2398\n", + "2/8, train_loss: 0.0118 step time: 0.2030\n", + "3/8, train_loss: 0.0128 step time: 0.1998\n", + "4/8, train_loss: 0.0113 step time: 0.2006\n", + "5/8, train_loss: 0.0113 step time: 0.1976\n", + "6/8, train_loss: 0.0126 step time: 0.1998\n", + "7/8, train_loss: 0.0109 step time: 0.1830\n", + "8/8, train_loss: 0.0106 step time: 0.1829\n", + "epoch 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205\n", + "time consuming of epoch 265 is: 2.3695\n", + "----------\n", + "epoch 266/600\n", + "1/8, train_loss: 0.0117 step time: 0.2320\n", + "2/8, train_loss: 0.0088 step time: 0.1971\n", + "3/8, train_loss: 0.0095 step time: 0.1953\n", + "4/8, train_loss: 0.0101 step time: 0.1934\n", + "5/8, train_loss: 0.0096 step time: 0.1943\n", + "6/8, train_loss: 0.0113 step time: 0.1941\n", + "7/8, train_loss: 0.0089 step time: 0.1808\n", + "8/8, train_loss: 0.0087 step time: 0.1807\n", + "epoch 266 average loss: 0.0098\n", + "time consuming of epoch 266 is: 1.5689\n", + "----------\n", + "epoch 267/600\n", + "1/8, train_loss: 0.0095 step time: 0.2397\n", + "2/8, train_loss: 0.0093 step time: 0.2009\n", + "3/8, train_loss: 0.0081 step time: 0.2000\n", + "4/8, train_loss: 0.0085 step time: 0.2001\n", + "5/8, train_loss: 0.0111 step time: 0.1987\n", + "6/8, train_loss: 0.0098 step time: 0.1990\n", + "7/8, train_loss: 0.0111 step time: 0.1824\n", + "8/8, train_loss: 0.0123 step time: 0.1819\n", 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205\n", + "time consuming of epoch 490 is: 2.3896\n", + "----------\n", + "epoch 491/600\n", + "1/8, train_loss: 0.0089 step time: 0.2409\n", + "2/8, train_loss: 0.0088 step time: 0.1990\n", + "3/8, train_loss: 0.0083 step time: 0.2014\n", + "4/8, train_loss: 0.0114 step time: 0.1988\n", + "5/8, train_loss: 0.0092 step time: 0.1990\n", + "6/8, train_loss: 0.0081 step time: 0.1981\n", + "7/8, train_loss: 0.0105 step time: 0.1810\n", + "8/8, train_loss: 0.0093 step time: 0.1818\n", + "epoch 491 average loss: 0.0093\n", + "time consuming of epoch 491 is: 1.6012\n", + "----------\n", + "epoch 492/600\n", + "1/8, train_loss: 0.0086 step time: 0.2401\n", + "2/8, train_loss: 0.0087 step time: 0.2051\n", + "3/8, train_loss: 0.0077 step time: 0.2044\n", + "4/8, train_loss: 0.0092 step time: 0.2001\n", + "5/8, train_loss: 0.0105 step time: 0.2009\n", + "6/8, train_loss: 0.0101 step time: 0.2001\n", + "7/8, train_loss: 0.0077 step time: 0.1838\n", + "8/8, train_loss: 0.0115 step time: 0.1829\n", 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train_loss: 0.0088 step time: 0.1980\n", + "4/8, train_loss: 0.0071 step time: 0.2027\n", + "5/8, train_loss: 0.0118 step time: 0.1975\n", + "6/8, train_loss: 0.0086 step time: 0.2020\n", + "7/8, train_loss: 0.0077 step time: 0.1840\n", + "8/8, train_loss: 0.0094 step time: 0.1826\n", + "epoch 576 average loss: 0.0088\n", + "time consuming of epoch 576 is: 1.6046\n", + "----------\n", + "epoch 577/600\n", + "1/8, train_loss: 0.0092 step time: 0.2413\n", + "2/8, train_loss: 0.0091 step time: 0.1992\n", + "3/8, train_loss: 0.0086 step time: 0.1985\n", + "4/8, train_loss: 0.0095 step time: 0.2004\n", + "5/8, train_loss: 0.0095 step time: 0.1992\n", + "6/8, train_loss: 0.0077 step time: 0.1990\n", + "7/8, train_loss: 0.0083 step time: 0.1835\n", + "8/8, train_loss: 0.0082 step time: 0.1819\n", + "epoch 577 average loss: 0.0088\n", + "time consuming of epoch 577 is: 1.6042\n", + "----------\n", + "epoch 578/600\n", + "1/8, train_loss: 0.0090 step time: 0.2407\n", + "2/8, train_loss: 0.0096 step time: 0.1957\n", + "3/8, train_loss: 0.0109 step time: 0.1979\n", + "4/8, train_loss: 0.0089 step time: 0.1981\n", + "5/8, train_loss: 0.0095 step time: 0.1955\n", + "6/8, train_loss: 0.0072 step time: 0.1957\n", + "7/8, train_loss: 0.0077 step time: 0.1822\n", + "8/8, train_loss: 0.0080 step time: 0.1824\n", + "epoch 578 average loss: 0.0089\n", + "time consuming of epoch 578 is: 1.5896\n", + "----------\n", + "epoch 579/600\n", + "1/8, train_loss: 0.0078 step time: 0.2435\n", + "2/8, train_loss: 0.0061 step time: 0.2016\n", + "3/8, train_loss: 0.0113 step time: 0.1997\n", + "4/8, train_loss: 0.0101 step time: 0.2064\n", + "5/8, train_loss: 0.0098 step time: 0.2028\n", + "6/8, train_loss: 0.0088 step time: 0.2023\n", + "7/8, train_loss: 0.0084 step time: 0.1837\n", + "8/8, train_loss: 0.0091 step time: 0.1839\n", + "epoch 579 average loss: 0.0089\n", + "time consuming of epoch 579 is: 1.6256\n", + "----------\n", + "epoch 580/600\n", + "1/8, train_loss: 0.0076 step time: 0.2404\n", + "2/8, train_loss: 0.0086 step time: 0.2030\n", + "3/8, train_loss: 0.0087 step time: 0.2000\n", + "4/8, train_loss: 0.0077 step time: 0.2014\n", + "5/8, train_loss: 0.0079 step time: 0.2020\n", + "6/8, train_loss: 0.0069 step time: 0.2027\n", + "7/8, train_loss: 0.0079 step time: 0.1843\n", + "8/8, train_loss: 0.0120 step time: 0.1840\n", + "epoch 580 average loss: 0.0084\n", + "current epoch: 580 current mean dice: 0.9619 best mean dice: 0.9623 at epoch: 525\n", + "time consuming of epoch 580 is: 2.3768\n", + "----------\n", + "epoch 581/600\n", + "1/8, train_loss: 0.0074 step time: 0.2408\n", + "2/8, train_loss: 0.0087 step time: 0.2014\n", + "3/8, train_loss: 0.0102 step time: 0.1988\n", + "4/8, train_loss: 0.0113 step time: 0.1992\n", + "5/8, train_loss: 0.0077 step time: 0.1993\n", + "6/8, train_loss: 0.0083 step time: 0.2015\n", + "7/8, train_loss: 0.0075 step time: 0.1806\n", + "8/8, train_loss: 0.0086 step time: 0.1813\n", + "epoch 581 average loss: 0.0087\n", + "time consuming of epoch 581 is: 1.6041\n", + "----------\n", + "epoch 582/600\n", + "1/8, train_loss: 0.0098 step time: 0.2399\n", + "2/8, train_loss: 0.0083 step time: 0.2023\n", + "3/8, train_loss: 0.0067 step time: 0.1999\n", + "4/8, train_loss: 0.0078 step time: 0.2035\n", + "5/8, train_loss: 0.0097 step time: 0.2093\n", + "6/8, train_loss: 0.0078 step time: 0.2111\n", + "7/8, train_loss: 0.0075 step time: 0.1826\n", + "8/8, train_loss: 0.0097 step time: 0.1822\n", + "epoch 582 average loss: 0.0084\n", + "time consuming of epoch 582 is: 1.6324\n", + "----------\n", + "epoch 583/600\n", + "1/8, train_loss: 0.0092 step time: 0.2395\n", + "2/8, train_loss: 0.0075 step time: 0.2018\n", + "3/8, train_loss: 0.0087 step time: 0.1989\n", + "4/8, train_loss: 0.0074 step time: 0.2004\n", + "5/8, train_loss: 0.0078 step time: 0.1995\n", + "6/8, train_loss: 0.0086 step time: 0.2009\n", + "7/8, train_loss: 0.0083 step time: 0.1823\n", + "8/8, train_loss: 0.0104 step time: 0.1821\n", + "epoch 583 average loss: 0.0085\n", + "time consuming of epoch 583 is: 1.6068\n", + "----------\n", + "epoch 584/600\n", + "1/8, train_loss: 0.0092 step time: 0.2347\n", + "2/8, train_loss: 0.0080 step time: 0.2001\n", + "3/8, train_loss: 0.0078 step time: 0.1987\n", + "4/8, train_loss: 0.0080 step time: 0.1984\n", + "5/8, train_loss: 0.0090 step time: 0.1978\n", + "6/8, train_loss: 0.0100 step time: 0.2001\n", + "7/8, train_loss: 0.0082 step time: 0.1833\n", + "8/8, train_loss: 0.0083 step time: 0.1821\n", + "epoch 584 average loss: 0.0086\n", + "time consuming of epoch 584 is: 1.5967\n", + "----------\n", + "epoch 585/600\n", + "1/8, train_loss: 0.0081 step time: 0.2389\n", + "2/8, train_loss: 0.0097 step time: 0.2037\n", + "3/8, train_loss: 0.0082 step time: 0.2003\n", + "4/8, train_loss: 0.0096 step time: 0.1960\n", + "5/8, train_loss: 0.0107 step time: 0.1975\n", + "6/8, train_loss: 0.0083 step time: 0.1972\n", + "7/8, train_loss: 0.0083 step time: 0.1792\n", + "8/8, train_loss: 0.0081 step time: 0.1792\n", + "epoch 585 average loss: 0.0089\n", + "current epoch: 585 current mean dice: 0.9621 best mean dice: 0.9623 at epoch: 525\n", + "time consuming of epoch 585 is: 2.3456\n", + "----------\n", + "epoch 586/600\n", + "1/8, train_loss: 0.0088 step time: 0.2361\n", + "2/8, train_loss: 0.0079 step time: 0.1947\n", + "3/8, train_loss: 0.0088 step time: 0.1974\n", + "4/8, train_loss: 0.0084 step time: 0.1955\n", + "5/8, train_loss: 0.0096 step time: 0.1976\n", + "6/8, train_loss: 0.0085 step time: 0.1981\n", + "7/8, train_loss: 0.0117 step time: 0.1795\n", + "8/8, train_loss: 0.0082 step time: 0.1793\n", + "epoch 586 average loss: 0.0090\n", + "time consuming of epoch 586 is: 1.5793\n", + "----------\n", + "epoch 587/600\n", + "1/8, train_loss: 0.0093 step time: 0.2343\n", + "2/8, train_loss: 0.0080 step time: 0.1944\n", + "3/8, train_loss: 0.0077 step time: 0.1973\n", + "4/8, train_loss: 0.0074 step time: 0.1982\n", + "5/8, train_loss: 0.0089 step time: 0.1978\n", + "6/8, train_loss: 0.0082 step time: 0.1980\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "7/8, train_loss: 0.0096 step time: 0.1790\n", + "8/8, train_loss: 0.0113 step time: 0.1791\n", + "epoch 587 average loss: 0.0088\n", + "time consuming of epoch 587 is: 1.5791\n", + "----------\n", + "epoch 588/600\n", + "1/8, train_loss: 0.0096 step time: 0.2337\n", + "2/8, train_loss: 0.0072 step time: 0.1953\n", + "3/8, train_loss: 0.0086 step time: 0.1974\n", + "4/8, train_loss: 0.0102 step time: 0.1984\n", + "5/8, train_loss: 0.0101 step time: 0.1986\n", + "6/8, train_loss: 0.0083 step time: 0.1981\n", + "7/8, train_loss: 0.0094 step time: 0.1794\n", + "8/8, train_loss: 0.0075 step time: 0.1791\n", + "epoch 588 average loss: 0.0089\n", + "time consuming of epoch 588 is: 1.5811\n", + "----------\n", + "epoch 589/600\n", + "1/8, train_loss: 0.0088 step time: 0.2340\n", + "2/8, train_loss: 0.0086 step time: 0.1943\n", + "3/8, train_loss: 0.0088 step time: 0.2028\n", + "4/8, train_loss: 0.0118 step time: 0.2103\n", + "5/8, train_loss: 0.0082 step time: 0.2039\n", + "6/8, train_loss: 0.0098 step time: 0.2011\n", + "7/8, train_loss: 0.0088 step time: 0.1836\n", + "8/8, train_loss: 0.0080 step time: 0.1839\n", + "epoch 589 average loss: 0.0091\n", + "time consuming of epoch 589 is: 1.6152\n", + "----------\n", + "epoch 590/600\n", + "1/8, train_loss: 0.0085 step time: 0.2399\n", + "2/8, train_loss: 0.0076 step time: 0.2031\n", + "3/8, train_loss: 0.0090 step time: 0.1990\n", + "4/8, train_loss: 0.0102 step time: 0.1999\n", + "5/8, train_loss: 0.0085 step time: 0.2043\n", + "6/8, train_loss: 0.0088 step time: 0.1998\n", + "7/8, train_loss: 0.0083 step time: 0.1818\n", + "8/8, train_loss: 0.0077 step time: 0.1818\n", + "epoch 590 average loss: 0.0086\n", + "saved new best metric model\n", + "current epoch: 590 current mean dice: 0.9626 best mean dice: 0.9626 at epoch: 590\n", + "time consuming of epoch 590 is: 2.5070\n", + "----------\n", + "epoch 591/600\n", + "1/8, train_loss: 0.0083 step time: 0.2424\n", + "2/8, train_loss: 0.0077 step time: 0.2013\n", + "3/8, train_loss: 0.0073 step time: 0.2012\n", + "4/8, train_loss: 0.0099 step time: 0.2004\n", + "5/8, train_loss: 0.0081 step time: 0.2012\n", + "6/8, train_loss: 0.0085 step time: 0.1974\n", + "7/8, train_loss: 0.0092 step time: 0.1826\n", + "8/8, train_loss: 0.0093 step time: 0.1834\n", + "epoch 591 average loss: 0.0085\n", + "time consuming of epoch 591 is: 1.6113\n", + "----------\n", + "epoch 592/600\n", + "1/8, train_loss: 0.0080 step time: 0.2386\n", + "2/8, train_loss: 0.0080 step time: 0.1979\n", + "3/8, train_loss: 0.0089 step time: 0.1974\n", + "4/8, train_loss: 0.0111 step time: 0.2002\n", + "5/8, train_loss: 0.0101 step time: 0.1989\n", + "6/8, train_loss: 0.0086 step time: 0.2028\n", + "7/8, train_loss: 0.0113 step time: 0.1817\n", + "8/8, train_loss: 0.0082 step time: 0.1818\n", + "epoch 592 average loss: 0.0093\n", + "time consuming of epoch 592 is: 1.6007\n", + "----------\n", + "epoch 593/600\n", + "1/8, train_loss: 0.0076 step time: 0.2339\n", + "2/8, train_loss: 0.0122 step time: 0.2003\n", + "3/8, train_loss: 0.0103 step time: 0.1962\n", + "4/8, train_loss: 0.0084 step time: 0.1994\n", + "5/8, train_loss: 0.0100 step time: 0.1939\n", + "6/8, train_loss: 0.0116 step time: 0.1951\n", + "7/8, train_loss: 0.0094 step time: 0.1825\n", + "8/8, train_loss: 0.0124 step time: 0.1825\n", + "epoch 593 average loss: 0.0103\n", + "time consuming of epoch 593 is: 1.5853\n", + "----------\n", + "epoch 594/600\n", + "1/8, train_loss: 0.0095 step time: 0.2392\n", + "2/8, train_loss: 0.0085 step time: 0.2089\n", + "3/8, train_loss: 0.0116 step time: 0.2013\n", + "4/8, train_loss: 0.0100 step time: 0.2018\n", + "5/8, train_loss: 0.1568 step time: 0.1916\n", + "6/8, train_loss: 0.0277 step time: 0.2064\n", + "7/8, train_loss: 0.0105 step time: 0.1823\n", + "8/8, train_loss: 0.0116 step time: 0.1823\n", + "epoch 594 average loss: 0.0308\n", + "time consuming of epoch 594 is: 1.6157\n", + "----------\n", + "epoch 595/600\n", + "1/8, train_loss: 0.0185 step time: 0.2398\n", + "2/8, train_loss: 0.0244 step time: 0.2027\n", + "3/8, train_loss: 0.0183 step time: 0.2049\n", + "4/8, train_loss: 0.0210 step time: 0.2012\n", + "5/8, train_loss: 0.0167 step time: 0.1982\n", + "6/8, train_loss: 0.0410 step time: 0.1990\n", + "7/8, train_loss: 0.0310 step time: 0.1822\n", + "8/8, train_loss: 0.0206 step time: 0.1821\n", + "epoch 595 average loss: 0.0239\n", + "current epoch: 595 current mean dice: 0.3226 best mean dice: 0.9626 at epoch: 590\n", + "time consuming of epoch 595 is: 2.3674\n", + "----------\n", + "epoch 596/600\n", + "1/8, train_loss: 0.0235 step time: 0.2339\n", + "2/8, train_loss: 0.0318 step time: 0.1962\n", + "3/8, train_loss: 0.0333 step time: 0.1960\n", + "4/8, train_loss: 0.0261 step time: 0.1952\n", + "5/8, train_loss: 0.0256 step time: 0.1965\n", + "6/8, train_loss: 0.0298 step time: 0.1951\n", + "7/8, train_loss: 0.0255 step time: 0.1812\n", + "8/8, train_loss: 0.0249 step time: 0.1822\n", + "epoch 596 average loss: 0.0276\n", + "time consuming of epoch 596 is: 1.5774\n", + "----------\n", + "epoch 597/600\n", + "1/8, train_loss: 0.0206 step time: 0.2423\n", + "2/8, train_loss: 0.0201 step time: 0.2032\n", + "3/8, train_loss: 0.0203 step time: 0.1987\n", + "4/8, train_loss: 0.0305 step time: 0.2002\n", + "5/8, train_loss: 0.1941 step time: 0.1979\n", + "6/8, train_loss: 0.0986 step time: 0.2003\n", + "7/8, train_loss: 0.0906 step time: 0.1821\n", + "8/8, train_loss: 0.1580 step time: 0.1823\n", + "epoch 597 average loss: 0.0791\n", + "time consuming of epoch 597 is: 1.6086\n", + "----------\n", + "epoch 598/600\n", + "1/8, train_loss: 0.2204 step time: 0.2387\n", + "2/8, train_loss: 0.0536 step time: 0.1979\n", + "3/8, train_loss: 0.3122 step time: 0.2009\n", + "4/8, train_loss: 0.0878 step time: 0.1988\n", + "5/8, train_loss: 0.2671 step time: 0.1993\n", + "6/8, train_loss: 0.1398 step time: 0.2015\n", + "7/8, train_loss: 0.1585 step time: 0.1825\n", + "8/8, train_loss: 0.1076 step time: 0.1811\n", + "epoch 598 average loss: 0.1684\n", + "time consuming of epoch 598 is: 1.6022\n", + "----------\n", + "epoch 599/600\n", + "1/8, train_loss: 0.1258 step time: 0.2353\n", + "2/8, train_loss: 0.1146 step time: 0.1993\n", + "3/8, train_loss: 0.1364 step time: 0.1930\n", + "4/8, train_loss: 0.1370 step time: 0.1989\n", + "5/8, train_loss: 0.1109 step time: 0.1980\n", + "6/8, train_loss: 0.1330 step time: 0.1974\n", + "7/8, train_loss: 0.3919 step time: 0.1813\n", + "8/8, train_loss: 0.1513 step time: 0.1817\n", + "epoch 599 average loss: 0.1626\n", + "time consuming of epoch 599 is: 1.5865\n", + "----------\n", + "epoch 600/600\n", + "1/8, train_loss: 0.1059 step time: 0.2391\n", + "2/8, train_loss: 0.1771 step time: 0.2036\n", + "3/8, train_loss: 0.2619 step time: 0.1958\n", + "4/8, train_loss: 0.1859 step time: 0.2003\n", + "5/8, train_loss: 0.0641 step time: 0.1999\n", + "6/8, train_loss: 0.1746 step time: 0.2021\n", + "7/8, train_loss: 0.1851 step time: 0.1823\n", + "8/8, train_loss: 0.1490 step time: 0.1827\n", + "epoch 600 average loss: 0.1629\n", + "current epoch: 600 current mean dice: 0.1629 best mean dice: 0.9626 at epoch: 590\n", + "time consuming of epoch 600 is: 2.3632\n", + "train completed, best_metric: 0.9626 at epoch: 590 total time: 1055.6900\n", + "\n", + "\n", + "\n", + "\n", + "times: [1061.2309420108795, 1057.999614238739, 1055.689969778061]\n", + "Average time: 1058.3068420092266\n", + "times per load operation: [0.0052551844716072086, 0.005239255477984746, 0.005237527986367544]\n", + "Average time per load operation: 0.005243989311986499\n" + ] + } + ], + "source": [ + "name = 'orig'\n", + "max_epochs = 600\n", + "repeats = 3\n", + "tlpo_sum, total_time_sum, tlpo_list, time_list, losses, metrics = 0, 0, [], [], np.zeros((max_epochs)), np.zeros((max_epochs // 5))\n", + "for _ in range(repeats):\n", + " total_time, loss, metric, tlpo = func()\n", + " total_time_sum += total_time\n", + " time_list.append(total_time)\n", + " metrics += metric\n", + " losses += loss\n", + " tlpo_list.append(tlpo)\n", + " tlpo_sum += tlpo\n", + "\n", + "print('\\n\\n\\n')\n", + "print(f\"times: {time_list}\")\n", + "print(f\"Average time: {total_time_sum / 3}\")\n", + "print(f\"times per load operation: {tlpo_list}\")\n", + "print(f\"Average time per load operation: {tlpo_sum / 3}\")\n", + "\n", + "time_dict[name] = total_time_sum / 3\n", + "metric_dict[name] = metrics / 3\n", + "loss_dict[name] = losses / 3\n", + "tlpo_dict[name] = tlpo_sum / 3" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'thread3': 1237.1164457798004,\n", + " 'thread2': 1142.810050725937,\n", + " 'thread1': 1068.8605738480885,\n", + " 'thread4': 1323.9301082293193,\n", + " 'instance': 903.4545698165894,\n", + " 'instance_nvfuser': 888.926282564799,\n", + " 'orig': 1058.3068420092266}" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "time_dict" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'thread3': 0.028458230362998115,\n", + " 'thread2': 0.0172835976878802,\n", + " 'thread1': 0.008170056641101837,\n", + " 'thread4': 0.04543388206097815,\n", + " 'instance': 0.005219863222704994,\n", + " 'instance_nvfuser': 0.00524735818306605,\n", + " 'orig': 0.005243989311986499}" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "tlpo_dict" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 56, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.title(\"Epoch Average Loss\")\n", + "x = [i + 1 for i in range(max_epochs)]\n", + "plt.xlabel(\"epoch\")\n", + "plt.grid(alpha=0.4, linestyle=\":\")\n", + "plt.plot(x, loss_dict['orig'], label='Batch', color=\"red\")\n", + "plt.plot(x, loss_dict['instance'], label='Instance', color=\"blue\")\n", + "plt.plot(x, loss_dict['instance_nvfuser'], label='Instance_NVFuser', color=\"green\")\n", + "plt.legend()" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 57, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.title(\"Val Mean Dice\")\n", + "x = [(i + 1) * 5 for i in range(max_epochs // 5)]\n", + "plt.xlabel(\"epoch\")\n", + "plt.grid(alpha=0.4, linestyle=\":\")\n", + "plt.plot(x, metric_dict['orig'], label='Batch', color=\"red\")\n", + "plt.plot(x, metric_dict['instance'], label='Instance', color=\"blue\")\n", + "plt.plot(x, metric_dict['instance_nvfuser'], label='Instance_NVFuser', color=\"green\")\n", + "plt.legend()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "def func():\n", + " load_ops, load_time = 0, 0\n", + " post_pred = Compose([EnsureType(), AsDiscrete(argmax=True, to_onehot=2)])\n", + " post_label = Compose([EnsureType(), AsDiscrete(to_onehot=2)])\n", + "\n", + " dice_metric = DiceMetric(include_background=False, reduction=\"mean\", get_not_nans=False)\n", + "\n", + " if fast:\n", + " # SGD prefer to much bigger learning rate\n", + " optimizer = SGD(\n", + " model.parameters(),\n", + " lr=learning_rate * 1000,\n", + " momentum=0.9,\n", + " weight_decay=0.00004,\n", + " )\n", + " scaler = torch.cuda.amp.GradScaler()\n", + " else:\n", + " optimizer = Adam(model.parameters(), learning_rate)\n", + "\n", + " best_metric = -1\n", + " best_metric_epoch = -1\n", + " best_metrics_epochs_and_time = [[], [], []]\n", + " epoch_loss_values = []\n", + " metric_values = []\n", + " epoch_times = []\n", + " total_start = time.time()\n", + "\n", + " for epoch in range(max_epochs):\n", + " epoch_start = time.time()\n", + " print(\"-\" * 10)\n", + " print(f\"epoch {epoch + 1}/{max_epochs}\")\n", + "\n", + " # profiling: full epoch\n", + " with nvtx.annotate(\"epoch\", color=\"red\") if profiling else no_profiling:\n", + " model.train()\n", + " epoch_loss = 0\n", + " train_loader_iterator = iter(train_loader)\n", + "\n", + " # using step instead of iterate through train_loader directly to track data loading time\n", + " # steps are 1-indexed for printing and calculation purposes\n", + " for step in range(1, len(train_loader) + 1):\n", + " step_start = time.time()\n", + "\n", + " # profiling: train dataload\n", + " with nvtx.annotate(\"dataload\", color=\"red\") if profiling else no_profiling:\n", + " # rng_train_dataload = nvtx.start_range(message=\"dataload\", color=\"red\")\n", + " load_start = time.time()\n", + " batch_data = next(train_loader_iterator)\n", + " load_time += time.time() - load_start\n", + " load_ops += 1\n", + " inputs, labels = (\n", + " batch_data[\"image\"].to(device),\n", + " batch_data[\"label\"].to(device),\n", + " )\n", + "\n", + " optimizer.zero_grad()\n", + " # set AMP for MONAI training\n", + " # profiling: forward\n", + " with nvtx.annotate(\"forward\", color=\"green\") if profiling else no_profiling:\n", + " with torch.cuda.amp.autocast():\n", + " outputs = model(inputs)\n", + " loss = loss_function(outputs, labels)\n", + "\n", + " # profiling: backward\n", + " with nvtx.annotate(\"backward\", color=\"blue\") if profiling else no_profiling:\n", + " scaler.scale(loss).backward()\n", + "\n", + " # profiling: update\n", + " with nvtx.annotate(\"update\", color=\"yellow\") if profiling else no_profiling:\n", + " scaler.step(optimizer)\n", + " scaler.update()\n", + " epoch_loss += loss.item()\n", + " epoch_len = math.ceil(len(train_ds) / train_loader.batch_size)\n", + " print(\n", + " f\"{step}/{epoch_len}, train_loss: {loss.item():.4f}\"\n", + " f\" step time: {(time.time() - step_start):.4f}\"\n", + " )\n", + " epoch_loss /= step\n", + " epoch_loss_values.append(epoch_loss)\n", + " print(f\"epoch {epoch + 1} average loss: {epoch_loss:.4f}\")\n", + "\n", + " if (epoch + 1) % val_interval == 0:\n", + " model.eval()\n", + " with torch.no_grad():\n", + " val_loader_iterator = iter(val_loader)\n", + "\n", + " for val_step in range(len(val_loader)):\n", + " # profiling: val dataload\n", + " with nvtx.annotate(\"dataload\", color=\"red\") if profiling else no_profiling:\n", + " val_data = next(val_loader_iterator)\n", + " val_inputs, val_labels = (\n", + " val_data[\"image\"].to(device),\n", + " val_data[\"label\"].to(device),\n", + " )\n", + "\n", + " roi_size = (160, 160, 160)\n", + " sw_batch_size = 4\n", + "\n", + " # profiling: sliding window\n", + " with nvtx.annotate(\"sliding window\", color=\"green\") if profiling else no_profiling:\n", + " # set AMP for MONAI validation\n", + " if fast:\n", + " with torch.cuda.amp.autocast():\n", + " val_outputs = sliding_window_inference(\n", + " val_inputs, roi_size, sw_batch_size, model\n", + " )\n", + " else:\n", + " val_outputs = sliding_window_inference(\n", + " val_inputs, roi_size, sw_batch_size, model\n", + " )\n", + "\n", + " # profiling: decollate batch\n", + " with nvtx.annotate(\"decollate batch\", color=\"blue\") if profiling else no_profiling:\n", + " val_outputs = [post_pred(i) for i in decollate_batch(val_outputs)]\n", + " val_labels = [post_label(i) for i in decollate_batch(val_labels)]\n", + "\n", + " # profiling: compute metric\n", + " with nvtx.annotate(\"compute metric\", color=\"yellow\") if profiling else no_profiling:\n", + " dice_metric(y_pred=val_outputs, y=val_labels)\n", + "\n", + " metric = dice_metric.aggregate().item()\n", + " dice_metric.reset()\n", + " metric_values.append(metric)\n", + " if metric > best_metric:\n", + " best_metric = metric\n", + " best_metric_epoch = epoch + 1\n", + " best_metrics_epochs_and_time[0].append(best_metric)\n", + " best_metrics_epochs_and_time[1].append(best_metric_epoch)\n", + " best_metrics_epochs_and_time[2].append(\n", + " time.time() - total_start\n", + " )\n", + " torch.save(model.state_dict(), os.path.join(root_dir, \"best_metric_model.pt\"))\n", + " print(\"saved new best metric model\")\n", + " print(\n", + " f\"current epoch: {epoch + 1} current\"\n", + " f\" mean dice: {metric:.4f}\"\n", + " f\" best mean dice: {best_metric:.4f}\"\n", + " f\" at epoch: {best_metric_epoch}\"\n", + " )\n", + "\n", + " print(\n", + " f\"time consuming of epoch {epoch + 1} is:\"\n", + " f\" {(time.time() - epoch_start):.4f}\"\n", + " )\n", + " epoch_times.append(time.time() - epoch_start)\n", + "\n", + " total_time = time.time() - total_start\n", + " print(\n", + " f\"train completed, best_metric: {best_metric:.4f}\"\n", + " f\" at epoch: {best_metric_epoch}\"\n", + " f\" total time: {total_time:.4f}\"\n", + " )\n", + " \n", + " return total_time, epoch_loss_values, metric_values, load_time / load_ops" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -812,24 +23899,24 @@ "\n", "In the GUI, select File -> Open -> output_base.nsys-rep. Here is a sample of the display:\n", "\n", - "![png](Figures/nsys-all-annotated.png)\n", + "![png](figures/nsys-all-annotated.png)\n", "- To get a better view of details, you can left-click and select a horizontal section, then right-click and \"Zoom into Selection.\" To return, right-click and select \"Reset Zoom.\"\n", "- Sections B and C show training before and after acceleration (when fast=False and fast=True, accordingly). Clearly, MONAI optimized training is much faster than regular PyTorch training. B and C both contain two rows; the upper row shows per-epoch time, and the lower row shows per-action time (user-defined, like dataloading, forward, backward, etc.).\n", "- Section A shows GPU utilization, where the height of the blue bars represents utilization rate. Regular PyTorch training shows sporadic and varying levels of GPU utilization, while MONAI optimized training shows consistent and high levels of GPU utilization.\n", "\n", "Expanding one more thread in the lower left corner and several more threads below \\[4648\\], we see the following:\n", "\n", - "![png](Figures/nsys-transforms-annotated.png)\n", + "![png](figures/nsys-transforms-annotated.png)\n", "\n", "Sections D and E both include information on the transform chain.\n", "- Section E: In MONAI optimized training, results of all transforms in the chain until the first randomized transform is stored to prevent repeated operations. This explains why E is chronologically before any of the training epochs in the figure.\n", "- Section D: In regular PyTorch training, CacheDataset is not in use, and the transform chain is performed every epoch on all data used.\n", "\n", "Here is the display of the transform chain when zoomed in:\n", - "![png](Figures/nsys-fast-transform.png)\n", + "![png](figures/nsys-fast-transform.png)\n", "\n", "And a display of one training epoch of MONAI optimized training when zoomed in:\n", - "![png](Figures/nsys-epoch-short.png)\n", + "![png](figures/nsys-epoch-short.png)\n", "Notice that the per-epoch time is >20 times faster than the regular PyTorch training." ] }, @@ -875,7 +23962,7 @@ "\n", " plt.subplot(2, 2, 2)\n", " plt.title(\"Regular Val Mean Dice\")\n", - " x = [i + 1 for i in range(len(metric_values))]\n", + " x = [(i + 1) * 5 for i in range(len(metric_values))]\n", " y = metric_values\n", " plt.xlabel(\"epoch\")\n", " plt.ylim(0, 1)\n", @@ -892,7 +23979,7 @@ "\n", " plt.subplot(2, 2, 4)\n", " plt.title(\"Fast Val Mean Dice\")\n", - " x = [i + 1 for i in range(len(m_metric_values))]\n", + " x = [(i + 1) * 5 for i in range(len(m_metric_values))]\n", " y = m_metric_values\n", " plt.xlabel(\"epoch\")\n", " plt.ylim(0, 1)\n", diff --git a/acceleration/Figures/nsys-all-annotated.png b/acceleration/figures/nsys-all-annotated.png similarity index 100% rename from acceleration/Figures/nsys-all-annotated.png rename to acceleration/figures/nsys-all-annotated.png diff --git a/acceleration/Figures/nsys-epoch-long.png b/acceleration/figures/nsys-epoch-long.png similarity index 100% rename from acceleration/Figures/nsys-epoch-long.png rename to acceleration/figures/nsys-epoch-long.png diff --git a/acceleration/Figures/nsys-epoch-short.png b/acceleration/figures/nsys-epoch-short.png similarity index 100% rename from acceleration/Figures/nsys-epoch-short.png rename to acceleration/figures/nsys-epoch-short.png diff --git a/acceleration/Figures/nsys-fast-transform.png b/acceleration/figures/nsys-fast-transform.png similarity index 100% rename from acceleration/Figures/nsys-fast-transform.png rename to acceleration/figures/nsys-fast-transform.png diff --git a/acceleration/Figures/nsys-transforms-annotated.png b/acceleration/figures/nsys-transforms-annotated.png similarity index 100% rename from acceleration/Figures/nsys-transforms-annotated.png rename to acceleration/figures/nsys-transforms-annotated.png From f93f35dbee8603155efa1906ff892934e0faf359 Mon Sep 17 00:00:00 2001 From: Yuchen Xu Date: Wed, 29 Jun 2022 23:02:37 -0700 Subject: [PATCH 10/12] ready for review --- acceleration/fast_training_tutorial.ipynb | 23370 +------------------- 1 file changed, 147 insertions(+), 23223 deletions(-) diff --git a/acceleration/fast_training_tutorial.ipynb b/acceleration/fast_training_tutorial.ipynb index 62aef50be6..4335fd084d 100644 --- a/acceleration/fast_training_tutorial.ipynb +++ b/acceleration/fast_training_tutorial.ipynb @@ -1,7 +1,7 @@ { "cells": [ { - "cell_type": "raw", + "cell_type": "markdown", "metadata": {}, "source": [ "# Fast training with MONAI features" @@ -19,6 +19,7 @@ "4. multi-threads `ThreadDataLoader` is faster than PyTorch DataLoader in light-weight task.\n", "5. Use MONAI `DiceCE` loss instead of regular `Dice` loss.\n", "6. Analyzed training curve and tuned algorithm: Use `SGD` optimizer, different network parameters, etc.\n", + "7. Instance norm in place of batch norm.\n", "\n", "With a V100 GPU and the target validation `mean dice = 0.94` of the `forground` channel only, it's more than `100x` speedup compared with the Pytorch regular implementation when achieving the same metric. And every epoch is `20x` faster than regular training.\n", "\n", @@ -206,7 +207,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "root dir is: /tmp/tmpv0msvmnr\n" + "root dir is: /tmp/tmpnhldk6uv\n" ] } ], @@ -320,43 +321,13 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": { "vscode": { "languageId": "python" } }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Task09_Spleen.tar: 1.50GB [01:00, 26.7MB/s] " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2022-06-28 03:56:26,901 - INFO - Downloaded: /tmp/tmpv0msvmnr/Task09_Spleen.tar\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2022-06-28 03:56:30,190 - INFO - Verified 'Task09_Spleen.tar', md5: 410d4a301da4e5b2f6f86ec3ddba524e.\n", - "2022-06-28 03:56:30,191 - INFO - Writing into directory: /tmp/tmpv0msvmnr.\n" - ] - } - ], + "outputs": [], "source": [ "resource = \"https://msd-for-monai.s3-us-west-2.amazonaws.com/Task09_Spleen.tar\"\n", "md5 = \"410d4a301da4e5b2f6f86ec3ddba524e\"\n", @@ -510,13 +481,14 @@ "4. `ThreadDataLoader`: uses multi-threads instead of multi-processing, faster than `DataLoader` in light-weight task as we already cached the results of most computation.\n", "5. `DiceCE` loss function: computes Dice loss and Cross Entropy Loss, returns the weighted sum of these two losses.\n", "6. Analyzed the training curve and tuned algorithm: Use `SGD` optimizer, different network parameters, etc.\n", + "7. `Instance_NVFuser` norm (`Norm.INSTANCE_NVFUSER`) instead of batch norm (`Norm.BATCH`). This norm may take a while to set up in the beginning, but it still results in faster training with comparable results. As an alternative, use instance norm (`Norm.INSTANCE`), which is slightly slower but has more uniform time cost. For more details, refer to the [source code](https://github.com/Project-MONAI/MONAI/blob/812275ae5f4a1bc8a69b70a9823632b6f30a5724/monai/networks/layers/factories.py#L253) of all defined norms.\n", "\n", "(A note on code: to improve readability and support the profiling flag, we used the `with nvtx(...) if profiling else no_profiling` context pattern, where `no_profiling` is a null context from Python's native `contextlib` with no effect on the code. An acknowledgement is provided here[1](#fn1).)" ] }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 18, "metadata": { "vscode": { "languageId": "python" @@ -571,7 +543,7 @@ " channels=(32, 64, 128, 256, 512),\n", " strides=(2, 2, 2, 2),\n", " num_res_units=2,\n", - " norm=Norm.instance,\n", + " norm=Norm.INSTANCE_NVFUSER,\n", " kernel_size=3,\n", " up_kernel_size=3,\n", " act=Act.PRELU,\n", @@ -779,7 +751,7 @@ "cell_type": "code", "execution_count": null, "metadata": { - "scrolled": false, + "scrolled": true, "vscode": { "languageId": "python" } @@ -840,23227 +812,179 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Experiments" + "## Profiling visualization" ] }, { - "cell_type": "code", - "execution_count": 9, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here we give a brief overview of key observations from the `nsys-rep` output file when opened in Nsight systems (2022.2.1).\n", + "\n", + "In the GUI, select File -> Open -> output_base.nsys-rep. Here is a sample of the display:\n", + "\n", + "![png](figures/nsys-all-annotated.png)\n", + "- To get a better view of details, you can left-click and select a horizontal section, then right-click and \"Zoom into Selection.\" To return, right-click and select \"Reset Zoom.\"\n", + "- Sections B and C show training before and after acceleration (when fast=False and fast=True, accordingly). Clearly, MONAI optimized training is much faster than regular PyTorch training. B and C both contain two rows; the upper row shows per-epoch time, and the lower row shows per-action time (user-defined, like dataloading, forward, backward, etc.).\n", + "- Section A shows GPU utilization, where the height of the blue bars represents utilization rate. Regular PyTorch training shows sporadic and varying levels of GPU utilization, while MONAI optimized training shows consistent and high levels of GPU utilization.\n", + "\n", + "Expanding one more thread in the lower left corner and several more threads below \\[4648\\], we see the following:\n", + "\n", + "![png](figures/nsys-transforms-annotated.png)\n", + "\n", + "Sections D and E both include information on the transform chain.\n", + "- Section E: In MONAI optimized training, results of all transforms in the chain until the first randomized transform is stored to prevent repeated operations. This explains why E is chronologically before any of the training epochs in the figure.\n", + "- Section D: In regular PyTorch training, CacheDataset is not in use, and the transform chain is performed every epoch on all data used.\n", + "\n", + "Here is the display of the transform chain when zoomed in:\n", + "![png](figures/nsys-fast-transform.png)\n", + "\n", + "And a display of one training epoch of MONAI optimized training when zoomed in:\n", + "![png](figures/nsys-epoch-short.png)\n", + "Notice that the per-epoch time is >20 times faster than the regular PyTorch training." + ] + }, + { + "cell_type": "markdown", "metadata": {}, + "source": [ + "## Plot training loss and validation metrics" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [ { - "name": "stderr", - "output_type": "stream", - "text": [ - "Loading dataset: 100%|█████████████████████████████████████████████████████████████████████████| 32/32 [00:33<00:00, 1.04s/it]\n", - "Loading dataset: 100%|███████████████████████████████████████████████████████████████████████████| 9/9 [00:08<00:00, 1.11it/s]\n" - ] + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" } ], "source": [ - "set_determinism(seed=0)\n", - "fast = True\n", - "\n", - "learning_rate = 2e-4\n", - "val_interval = 5 # do validation for every epoch\n", + "if not profiling:\n", + " plt.figure(\"train\", (12, 12))\n", + " plt.subplot(2, 2, 1)\n", + " plt.title(\"Regular Epoch Average Loss\")\n", + " x = [i + 1 for i in range(len(epoch_loss_values))]\n", + " y = epoch_loss_values\n", + " plt.xlabel(\"epoch\")\n", + " plt.grid(alpha=0.4, linestyle=\":\")\n", + " plt.plot(x, y, color=\"red\")\n", "\n", - "if torch.cuda.is_available():\n", - " device = torch.device(\"cuda:0\")\n", - "else:\n", - " raise RuntimeError('this tutorial is intended for GPU, but no CUDA device is available')\n", + " plt.subplot(2, 2, 2)\n", + " plt.title(\"Regular Val Mean Dice\")\n", + " x = [(i + 1) * 5 for i in range(len(metric_values))]\n", + " y = metric_values\n", + " plt.xlabel(\"epoch\")\n", + " plt.ylim(0, 1)\n", + " plt.grid(alpha=0.4, linestyle=\":\")\n", + " plt.plot(x, y, color=\"red\")\n", "\n", - "train_trans, val_trans = transformations(fast=fast, device=device)\n", - "# set CacheDataset, ThreadDataLoader and DiceCE loss for MONAI fast training\n", + " plt.subplot(2, 2, 3)\n", + " plt.title(\"Fast Epoch Average Loss\")\n", + " x = [i + 1 for i in range(len(m_epoch_loss_values))]\n", + " y = m_epoch_loss_values\n", + " plt.xlabel(\"epoch\")\n", + " plt.grid(alpha=0.4, linestyle=\":\")\n", + " plt.plot(x, y, color=\"green\")\n", "\n", - "# as `RandCropByPosNegLabeld` crops from the cached content and `deepcopy`\n", - "# the crop area instead of modifying the cached value, we can set `copy_cache=False`\n", - "# to avoid unnecessary deepcopy of cached content in `CacheDataset`\n", - "train_ds = CacheDataset(\n", - " data=train_files,\n", - " transform=train_trans,\n", - " cache_rate=1.0,\n", - " num_workers=8,\n", - " copy_cache=False,\n", - ")\n", - "val_ds = CacheDataset(\n", - " data=val_files, transform=val_trans, cache_rate=1.0, num_workers=5, copy_cache=False\n", - ")" + " plt.subplot(2, 2, 4)\n", + " plt.title(\"Fast Val Mean Dice\")\n", + " x = [(i + 1) * 5 for i in range(len(m_metric_values))]\n", + " y = m_metric_values\n", + " plt.xlabel(\"epoch\")\n", + " plt.ylim(0, 1)\n", + " plt.grid(alpha=0.4, linestyle=\":\")\n", + " plt.plot(x, y, color=\"green\")\n", + " plt.savefig(\"outputs/loss_dice_comparison.png\")" ] }, { - "cell_type": "code", - "execution_count": 28, + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "# disable multi-workers because `ThreadDataLoader` works with multi-threads\n", - "train_loader = ThreadDataLoader(train_ds, use_thread_workers=False, num_workers=0, batch_size=4, shuffle=True)\n", - "val_loader = ThreadDataLoader(val_ds, use_thread_workers=False, num_workers=0, batch_size=1)" + "## Plot total time and every epoch time" ] }, { "cell_type": "code", - "execution_count": 41, - "metadata": {}, - "outputs": [], + "execution_count": 21, + "metadata": { + "vscode": { + "languageId": "python" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ - "# disable multi-workers because `ThreadDataLoader` works with multi-threads\n", - "loss_function = DiceCELoss(\n", - " include_background=False,\n", - " to_onehot_y=True,\n", - " softmax=True,\n", - " squared_pred=True,\n", - " batch=True,\n", - " smooth_nr=0.00001,\n", - " smooth_dr=0.00001,\n", - " lambda_dice=0.5,\n", - " lambda_ce=0.5,\n", - ")\n", - "model = UNet(\n", - " spatial_dims=3,\n", - " in_channels=1,\n", - " out_channels=2,\n", - " channels=(32, 64, 128, 256, 512),\n", - " strides=(2, 2, 2, 2),\n", - " num_res_units=2,\n", - " norm=Norm.BATCH,\n", - " kernel_size=3,\n", - " up_kernel_size=3,\n", - " act=Act.PRELU,\n", - " dropout=0.2,\n", - " bias=True,\n", - " dimensions=None,\n", - ").to(device)" + "if not profiling:\n", + " plt.figure(\"train\", (12, 6))\n", + " plt.subplot(1, 2, 1)\n", + " plt.title(\"Total Train Time(600 epochs)\")\n", + " plt.bar(\n", + " \"regular PyTorch\", total_time, 1, label=\"Regular training\", color=\"red\"\n", + " )\n", + " plt.bar(\"Fast\", m_total_time, 1, label=\"Fast training\", color=\"green\")\n", + " plt.ylabel(\"secs\")\n", + " plt.grid(alpha=0.4, linestyle=\":\")\n", + " plt.legend(loc=\"best\")\n", + "\n", + " plt.subplot(1, 2, 2)\n", + " plt.title(\"Epoch Time\")\n", + " x = [i + 1 for i in range(len(epoch_times))]\n", + " plt.xlabel(\"epoch\")\n", + " plt.ylabel(\"secs\")\n", + " plt.plot(x, epoch_times, label=\"Regular training\", color=\"red\")\n", + " plt.plot(x, m_epoch_times, label=\"Fast training\", color=\"green\")\n", + " plt.grid(alpha=0.4, linestyle=\":\")\n", + " plt.legend(loc=\"best\")\n", + " plt.savefig(\"outputs/total_epoch_time_comparison.png\")" ] }, { - "cell_type": "code", - "execution_count": 12, + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "import numpy as np\n", - "\n", - "# train_load_per_op = tlpo\n", - "tlpo_dict, time_dict, metric_dict, loss_dict = {}, {}, {}, {}" + "## Plot total time to achieve metrics" ] }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 22, "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "----------\n", - "epoch 1/600\n", - "1/8, train_loss: 0.7790 step time: 0.2530\n", - "2/8, train_loss: 0.6703 step time: 0.1966\n", - "3/8, train_loss: 0.5067 step time: 0.1951\n", - "4/8, train_loss: 0.4607 step time: 0.1928\n", - "5/8, train_loss: 0.4546 step time: 0.1955\n", - "6/8, train_loss: 0.4509 step time: 0.1940\n", - "7/8, train_loss: 0.4756 step time: 0.1836\n", - "8/8, train_loss: 0.4160 step time: 0.1828\n", - "epoch 1 average loss: 0.5267\n", - "time consuming of epoch 1 is: 1.5947\n", - "----------\n", - "epoch 2/600\n", - "1/8, train_loss: 0.4516 step time: 0.2394\n", - "2/8, train_loss: 0.4172 step time: 0.2041\n", - "3/8, train_loss: 0.6438 step time: 0.1905\n", - "4/8, train_loss: 0.6094 step time: 0.1995\n", - "5/8, train_loss: 0.4216 step time: 0.2017\n", - "6/8, train_loss: 0.5499 step time: 0.2015\n", - "7/8, train_loss: 0.5725 step time: 0.1833\n", - "8/8, train_loss: 0.5541 step time: 0.1823\n", - "epoch 2 average loss: 0.5275\n", - "time consuming of epoch 2 is: 1.6041\n", - "----------\n", - "epoch 3/600\n", - "1/8, train_loss: 0.6049 step time: 0.2423\n", - "2/8, train_loss: 0.5896 step time: 0.2031\n", - "3/8, train_loss: 0.5955 step time: 0.2001\n", - "4/8, train_loss: 0.5692 step time: 0.2019\n", - "5/8, train_loss: 0.5608 step time: 0.2036\n", - "6/8, train_loss: 0.5988 step time: 0.2058\n", - "7/8, train_loss: 0.5444 step time: 0.1822\n", - "8/8, train_loss: 0.4742 step time: 0.1823\n", - "epoch 3 average loss: 0.5672\n", - "time consuming of epoch 3 is: 1.6230\n", - "----------\n", - "epoch 4/600\n", - "1/8, train_loss: 0.5163 step time: 0.2313\n", - "2/8, train_loss: 0.4702 step time: 0.1990\n", - "3/8, train_loss: 0.4418 step time: 0.1977\n", - "4/8, train_loss: 0.4512 step time: 0.1951\n", - "5/8, train_loss: 0.4361 step time: 0.1976\n", - "6/8, train_loss: 0.4215 step time: 0.2001\n", - "7/8, train_loss: 0.4655 step time: 0.1824\n", - "8/8, train_loss: 0.4448 step time: 0.1830\n", - "epoch 4 average loss: 0.4559\n", - "time consuming of epoch 4 is: 1.5878\n", - "----------\n", - "epoch 5/600\n", - "1/8, train_loss: 0.4356 step time: 0.2428\n", - "2/8, train_loss: 0.4663 step time: 0.2005\n", - "3/8, train_loss: 0.4176 step time: 0.2092\n", - "4/8, train_loss: 0.4016 step time: 0.2069\n", - "5/8, train_loss: 0.4068 step time: 0.2041\n", - "6/8, train_loss: 0.4240 step time: 0.2069\n", - "7/8, train_loss: 0.4158 step time: 0.1844\n", - "8/8, train_loss: 0.4185 step time: 0.1848\n", - "epoch 5 average loss: 0.4233\n", - "saved new best metric model\n", - "current epoch: 5 current mean dice: 0.0000 best mean dice: 0.0000 at epoch: 5\n", - "time consuming of epoch 5 is: 2.5513\n", - "----------\n", - "epoch 6/600\n", - "1/8, train_loss: 0.4299 step time: 0.2405\n", - "2/8, train_loss: 0.3908 step time: 0.1995\n", - "3/8, train_loss: 0.3484 step time: 0.2000\n", - "4/8, train_loss: 0.4706 step time: 0.1995\n", - "5/8, train_loss: 0.4433 step time: 0.1992\n", - "6/8, train_loss: 0.4395 step time: 0.2049\n", - "7/8, train_loss: 0.3777 step time: 0.1817\n", - "8/8, train_loss: 0.3902 step time: 0.1837\n", - "epoch 6 average loss: 0.4113\n", - "time consuming of epoch 6 is: 1.6101\n", - "----------\n", - "epoch 7/600\n", - "1/8, train_loss: 0.3943 step time: 0.2373\n", - "2/8, train_loss: 0.4173 step time: 0.2036\n", - "3/8, train_loss: 0.3792 step time: 0.2016\n", - "4/8, train_loss: 0.3475 step time: 0.2058\n", - "5/8, train_loss: 0.3828 step time: 0.2002\n", - "6/8, train_loss: 0.4743 step time: 0.2006\n", - "7/8, train_loss: 0.4055 step time: 0.1847\n", - "8/8, train_loss: 0.3738 step time: 0.1825\n", - "epoch 7 average loss: 0.3969\n", - "time consuming of epoch 7 is: 1.6177\n", - "----------\n", - "epoch 8/600\n", - "1/8, train_loss: 0.4478 step time: 0.2419\n", - "2/8, train_loss: 0.4176 step time: 0.1984\n", - "3/8, train_loss: 0.4070 step time: 0.2024\n", - "4/8, train_loss: 0.3698 step time: 0.2010\n", - "5/8, train_loss: 0.3812 step time: 0.1977\n", - "6/8, train_loss: 0.4036 step time: 0.2037\n", - "7/8, train_loss: 0.3601 step time: 0.1827\n", - "8/8, train_loss: 0.3408 step time: 0.1827\n", - "epoch 8 average loss: 0.3910\n", - "time consuming of epoch 8 is: 1.6120\n", - "----------\n", - "epoch 9/600\n", - "1/8, train_loss: 0.2896 step time: 0.2382\n", - "2/8, train_loss: 0.2501 step time: 0.2057\n", - "3/8, train_loss: 0.2276 step time: 0.2064\n", - "4/8, train_loss: 0.2586 step time: 0.2023\n", - "5/8, train_loss: 0.1842 step time: 0.2000\n", - "6/8, train_loss: 0.1824 step time: 0.1993\n", - "7/8, train_loss: 0.3053 step time: 0.1827\n", - "8/8, train_loss: 0.1747 step time: 0.1827\n", - "epoch 9 average loss: 0.2341\n", - "time consuming of epoch 9 is: 1.6187\n", - "----------\n", - "epoch 10/600\n", - "1/8, train_loss: 0.2341 step time: 0.2366\n", - "2/8, train_loss: 0.2003 step time: 0.2046\n", - "3/8, train_loss: 0.1749 step time: 0.1979\n", - "4/8, train_loss: 0.1433 step time: 0.2013\n", - "5/8, train_loss: 0.1587 step time: 0.2013\n", - "6/8, train_loss: 0.1589 step time: 0.2023\n", - "7/8, train_loss: 0.1875 step time: 0.1852\n", - "8/8, train_loss: 0.1372 step time: 0.1829\n", - "epoch 10 average loss: 0.1744\n", - "saved new best metric model\n", - "current epoch: 10 current mean dice: 0.1068 best mean dice: 0.1068 at epoch: 10\n", - "time consuming of epoch 10 is: 2.5124\n", - "----------\n", - "epoch 11/600\n", - "1/8, train_loss: 0.1378 step time: 0.2297\n", - "2/8, train_loss: 0.2098 step time: 0.1908\n", - "3/8, train_loss: 0.2831 step time: 0.1925\n", - "4/8, train_loss: 0.1949 step time: 0.1906\n", - "5/8, train_loss: 0.1745 step time: 0.1932\n", - "6/8, train_loss: 0.1226 step time: 0.1943\n", - "7/8, train_loss: 0.0827 step time: 0.1815\n", - "8/8, train_loss: 0.1060 step time: 0.1819\n", - "epoch 11 average loss: 0.1639\n", - "time consuming of epoch 11 is: 1.5557\n", - "----------\n", - "epoch 12/600\n", - "1/8, train_loss: 0.1774 step time: 0.2400\n", - "2/8, train_loss: 0.1407 step time: 0.1999\n", - "3/8, train_loss: 0.1289 step time: 0.2016\n", - "4/8, train_loss: 0.1057 step time: 0.2020\n", - "5/8, train_loss: 0.1392 step time: 0.2047\n", - "6/8, train_loss: 0.1048 step time: 0.1983\n", - "7/8, train_loss: 0.0981 step time: 0.1821\n", - "8/8, train_loss: 0.0990 step time: 0.1829\n", - "epoch 12 average loss: 0.1242\n", - "time consuming of epoch 12 is: 1.6129\n", - "----------\n", - "epoch 13/600\n", - "1/8, train_loss: 0.1046 step time: 0.2436\n", - "2/8, train_loss: 0.0908 step time: 0.2041\n", - "3/8, train_loss: 0.1271 step time: 0.2037\n", - "4/8, train_loss: 0.0839 step time: 0.2000\n", - "5/8, train_loss: 0.0979 step time: 0.1989\n", - "6/8, train_loss: 0.1252 step time: 0.1979\n", - "7/8, train_loss: 0.0859 step time: 0.1824\n", - "8/8, train_loss: 0.0649 step time: 0.1820\n", - "epoch 13 average loss: 0.0975\n", - "time consuming of epoch 13 is: 1.6140\n", - "----------\n", - "epoch 14/600\n", - "1/8, train_loss: 0.0967 step time: 0.2303\n", - "2/8, train_loss: 0.1382 step time: 0.1969\n", - "3/8, train_loss: 0.0975 step time: 0.2004\n", - "4/8, train_loss: 0.0869 step time: 0.1967\n", - "5/8, train_loss: 0.0781 step time: 0.2007\n", - "6/8, train_loss: 0.0707 step time: 0.2008\n", - "7/8, train_loss: 0.0899 step time: 0.1836\n", - "8/8, train_loss: 0.1534 step time: 0.1838\n", - "epoch 14 average loss: 0.1014\n", - "time consuming of epoch 14 is: 1.5948\n", - "----------\n", - "epoch 15/600\n", - "1/8, train_loss: 0.0912 step time: 0.2400\n", - "2/8, train_loss: 0.1302 step time: 0.2023\n", - "3/8, train_loss: 0.1661 step time: 0.2071\n", - "4/8, train_loss: 0.0708 step time: 0.2010\n", - "5/8, train_loss: 0.1633 step time: 0.1983\n", - "6/8, train_loss: 0.1116 step time: 0.2027\n", - "7/8, train_loss: 0.0953 step time: 0.1827\n", - "8/8, train_loss: 0.1799 step time: 0.1814\n", - "epoch 15 average loss: 0.1261\n", - "saved new best metric model\n", - "current epoch: 15 current mean dice: 0.8073 best mean dice: 0.8073 at epoch: 15\n", - "time consuming of epoch 15 is: 2.5141\n", - "----------\n", - "epoch 16/600\n", - "1/8, train_loss: 0.0548 step time: 0.2415\n", - "2/8, train_loss: 0.0920 step time: 0.2027\n", - "3/8, train_loss: 0.0603 step time: 0.2005\n", - "4/8, train_loss: 0.1169 step time: 0.2061\n", - "5/8, train_loss: 0.0845 step time: 0.2032\n", - "6/8, train_loss: 0.0729 step time: 0.1997\n", - "7/8, train_loss: 0.1074 step time: 0.1816\n", - "8/8, train_loss: 0.0948 step time: 0.1811\n", - "epoch 16 average loss: 0.0854\n", - "time consuming of epoch 16 is: 1.6177\n", - "----------\n", - "epoch 17/600\n", - "1/8, train_loss: 0.0736 step time: 0.2401\n", - "2/8, train_loss: 0.0861 step time: 0.2021\n", - "3/8, train_loss: 0.0714 step time: 0.1979\n", - "4/8, train_loss: 0.0665 step time: 0.2010\n", - "5/8, train_loss: 0.0529 step time: 0.2012\n", - "6/8, train_loss: 0.0782 step time: 0.1974\n", - "7/8, train_loss: 0.0718 step time: 0.1813\n", - "8/8, train_loss: 0.0777 step time: 0.1821\n", - "epoch 17 average loss: 0.0723\n", - "time consuming of epoch 17 is: 1.6044\n", - "----------\n", - "epoch 18/600\n", - "1/8, train_loss: 0.0624 step time: 0.2401\n", - "2/8, train_loss: 0.0586 step time: 0.2019\n", - "3/8, train_loss: 0.0582 step time: 0.2002\n", - "4/8, train_loss: 0.0550 step time: 0.2010\n", - "5/8, train_loss: 0.0804 step time: 0.2000\n", - "6/8, train_loss: 0.0520 step time: 0.2028\n", - "7/8, train_loss: 0.1280 step time: 0.1822\n", - "8/8, train_loss: 0.0832 step time: 0.1824\n", - "epoch 18 average loss: 0.0722\n", - "time consuming of epoch 18 is: 1.6122\n", - "----------\n", - "epoch 19/600\n", - "1/8, train_loss: 0.0654 step time: 0.2376\n", - "2/8, train_loss: 0.0484 step time: 0.2031\n", - "3/8, train_loss: 0.0586 step time: 0.2019\n", - "4/8, train_loss: 0.0825 step time: 0.2016\n", - "5/8, train_loss: 0.0613 step time: 0.1992\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "6/8, train_loss: 0.0792 step time: 0.1981\n", - "7/8, train_loss: 0.0976 step time: 0.1831\n", - "8/8, train_loss: 0.1049 step time: 0.1825\n", - "epoch 19 average loss: 0.0747\n", - "time consuming of epoch 19 is: 1.6088\n", - "----------\n", - "epoch 20/600\n", - "1/8, train_loss: 0.0475 step time: 0.2454\n", - "2/8, train_loss: 0.0501 step time: 0.2053\n", - "3/8, train_loss: 0.1487 step time: 0.2004\n", - "4/8, train_loss: 0.0799 step time: 0.2018\n", - "5/8, train_loss: 0.0755 step time: 0.2042\n", - "6/8, train_loss: 0.0698 step time: 0.1989\n", - "7/8, train_loss: 0.1062 step time: 0.1849\n", - "8/8, train_loss: 0.0962 step time: 0.1835\n", - "epoch 20 average loss: 0.0842\n", - "current epoch: 20 current mean dice: 0.4622 best mean dice: 0.8073 at epoch: 15\n", - "time consuming of epoch 20 is: 2.3804\n", - "----------\n", - "epoch 21/600\n", - "1/8, train_loss: 0.0822 step time: 0.2378\n", - "2/8, train_loss: 0.0768 step time: 0.1999\n", - "3/8, train_loss: 0.0955 step time: 0.1997\n", - "4/8, train_loss: 0.1280 step time: 0.1976\n", - "5/8, train_loss: 0.0909 step time: 0.2006\n", - "6/8, train_loss: 0.0863 step time: 0.1997\n", - "7/8, train_loss: 0.0898 step time: 0.1822\n", - "8/8, train_loss: 0.0465 step time: 0.1830\n", - "epoch 21 average loss: 0.0870\n", - "time consuming of epoch 21 is: 1.6015\n", - "----------\n", - "epoch 22/600\n", - "1/8, train_loss: 0.0963 step time: 0.2411\n", - "2/8, train_loss: 0.0807 step time: 0.2014\n", - "3/8, train_loss: 0.0771 step time: 0.1998\n", - "4/8, train_loss: 0.0743 step time: 0.2007\n", - "5/8, train_loss: 0.0655 step time: 0.2021\n", - "6/8, train_loss: 0.0555 step time: 0.1985\n", - "7/8, train_loss: 0.0626 step time: 0.1835\n", - "8/8, train_loss: 0.1538 step time: 0.1834\n", - "epoch 22 average loss: 0.0832\n", - "time consuming of epoch 22 is: 1.6121\n", - "----------\n", - "epoch 23/600\n", - "1/8, train_loss: 0.0610 step time: 0.2389\n", - "2/8, train_loss: 0.0752 step time: 0.2043\n", - "3/8, train_loss: 0.0663 step time: 0.1988\n", - "4/8, train_loss: 0.1190 step time: 0.2011\n", - "5/8, train_loss: 0.1953 step time: 0.2000\n", - "6/8, train_loss: 0.1097 step time: 0.2017\n", - "7/8, train_loss: 0.1115 step time: 0.1842\n", - "8/8, train_loss: 0.0917 step time: 0.1818\n", - "epoch 23 average loss: 0.1037\n", - "time consuming of epoch 23 is: 1.6122\n", - "----------\n", - "epoch 24/600\n", - "1/8, train_loss: 0.0594 step time: 0.2400\n", - "2/8, train_loss: 0.0888 step time: 0.2024\n", - "3/8, train_loss: 0.0995 step time: 0.2044\n", - "4/8, train_loss: 0.1074 step time: 0.2000\n", - "5/8, train_loss: 0.0455 step time: 0.2010\n", - "6/8, train_loss: 0.0826 step time: 0.2000\n", - "7/8, train_loss: 0.1648 step time: 0.1840\n", - "8/8, train_loss: 0.0631 step time: 0.1820\n", - "epoch 24 average loss: 0.0889\n", - "time consuming of epoch 24 is: 1.6151\n", - "----------\n", - "epoch 25/600\n", - "1/8, train_loss: 0.0632 step time: 0.2387\n", - "2/8, train_loss: 0.0760 step time: 0.2000\n", - "3/8, train_loss: 0.0905 step time: 0.2014\n", - "4/8, train_loss: 0.0921 step time: 0.1992\n", - "5/8, train_loss: 0.1081 step time: 0.2040\n", - "6/8, train_loss: 0.0840 step time: 0.2043\n", - "7/8, train_loss: 0.0754 step time: 0.1845\n", - "8/8, train_loss: 0.0628 step time: 0.1817\n", - "epoch 25 average loss: 0.0815\n", - "current epoch: 25 current mean dice: 0.7745 best mean dice: 0.8073 at epoch: 15\n", - "time consuming of epoch 25 is: 2.3701\n", - "----------\n", - "epoch 26/600\n", - "1/8, train_loss: 0.0655 step time: 0.2370\n", - "2/8, train_loss: 0.0690 step time: 0.1979\n", - "3/8, train_loss: 0.0417 step time: 0.1985\n", - "4/8, train_loss: 0.0498 step time: 0.1978\n", - "5/8, train_loss: 0.0769 step time: 0.1972\n", - "6/8, train_loss: 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0.1975\n", - "6/8, train_loss: 0.0533 step time: 0.1947\n", - "7/8, train_loss: 0.0592 step time: 0.1834\n", - "8/8, train_loss: 0.0877 step time: 0.1812\n", - "epoch 28 average loss: 0.0554\n", - "time consuming of epoch 28 is: 1.5944\n", - "----------\n", - "epoch 29/600\n", - "1/8, train_loss: 0.0589 step time: 0.2377\n", - "2/8, train_loss: 0.0454 step time: 0.1995\n", - "3/8, train_loss: 0.0479 step time: 0.2016\n", - "4/8, train_loss: 0.0416 step time: 0.2032\n", - "5/8, train_loss: 0.1278 step time: 0.2020\n", - "6/8, train_loss: 0.0667 step time: 0.1994\n", - "7/8, train_loss: 0.0497 step time: 0.1839\n", - "8/8, train_loss: 0.0375 step time: 0.1812\n", - "epoch 29 average loss: 0.0594\n", - "time consuming of epoch 29 is: 1.6097\n", - "----------\n", - "epoch 30/600\n", - "1/8, train_loss: 0.0402 step time: 0.2385\n", - "2/8, train_loss: 0.0489 step time: 0.2082\n", - "3/8, train_loss: 0.0468 step time: 0.2077\n", - "4/8, train_loss: 0.0424 step time: 0.2035\n", - "5/8, 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95\n", - "time consuming of epoch 135 is: 2.3720\n", - "----------\n", - "epoch 136/600\n", - "1/8, train_loss: 0.0141 step time: 0.2377\n", - "2/8, train_loss: 0.0121 step time: 0.1998\n", - "3/8, train_loss: 0.0148 step time: 0.2020\n", - "4/8, train_loss: 0.0163 step time: 0.2023\n", - "5/8, train_loss: 0.0146 step time: 0.2034\n", - "6/8, train_loss: 0.0119 step time: 0.2009\n", - "7/8, train_loss: 0.0147 step time: 0.1847\n", - "8/8, train_loss: 0.0185 step time: 0.1843\n", - "epoch 136 average loss: 0.0146\n", - "time consuming of epoch 136 is: 1.6163\n", - "----------\n", - "epoch 137/600\n", - "1/8, train_loss: 0.0130 step time: 0.2401\n", - "2/8, train_loss: 0.0111 step time: 0.1974\n", - "3/8, train_loss: 0.0137 step time: 0.1960\n", - "4/8, train_loss: 0.0142 step time: 0.1950\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "5/8, train_loss: 0.0119 step time: 0.2011\n", - "6/8, train_loss: 0.0151 step time: 0.2010\n", - "7/8, train_loss: 0.0137 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95\n", - "time consuming of epoch 295 is: 2.3675\n", - "----------\n", - "epoch 296/600\n", - "1/8, train_loss: 0.0150 step time: 0.2380\n", - "2/8, train_loss: 0.0149 step time: 0.1993\n", - "3/8, train_loss: 0.0134 step time: 0.1995\n", - "4/8, train_loss: 0.0147 step time: 0.2051\n", - "5/8, train_loss: 0.0125 step time: 0.1989\n", - "6/8, train_loss: 0.0139 step time: 0.2033\n", - "7/8, train_loss: 0.0138 step time: 0.1854\n", - "8/8, train_loss: 0.0127 step time: 0.1828\n", - "epoch 296 average loss: 0.0139\n", - "time consuming of epoch 296 is: 1.6134\n", - "----------\n", - "epoch 297/600\n", - "1/8, train_loss: 0.0137 step time: 0.2412\n", - "2/8, train_loss: 0.0142 step time: 0.2001\n", - "3/8, train_loss: 0.0154 step time: 0.2024\n", - "4/8, train_loss: 0.0130 step time: 0.2027\n", - "5/8, train_loss: 0.0130 step time: 0.2073\n", - "6/8, train_loss: 0.0153 step time: 0.2065\n", - "7/8, train_loss: 0.0126 step time: 0.1829\n", - "8/8, train_loss: 0.0134 step time: 0.1821\n", - 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time: 0.1826\n", - "epoch 492 average loss: 0.0123\n", - "time consuming of epoch 492 is: 1.6222\n", - "----------\n", - "epoch 493/600\n", - "1/8, train_loss: 0.0097 step time: 0.2407\n", - "2/8, train_loss: 0.0130 step time: 0.2050\n", - "3/8, train_loss: 0.0143 step time: 0.2026\n", - "4/8, train_loss: 0.0128 step time: 0.2003\n", - "5/8, train_loss: 0.0116 step time: 0.2031\n", - "6/8, train_loss: 0.0114 step time: 0.2024\n", - "7/8, train_loss: 0.0087 step time: 0.1830\n", - "8/8, train_loss: 0.0115 step time: 0.1819\n", - "epoch 493 average loss: 0.0116\n", - "time consuming of epoch 493 is: 1.6207\n", - "----------\n", - "epoch 494/600\n", - "1/8, train_loss: 0.0141 step time: 0.2405\n", - "2/8, train_loss: 0.0125 step time: 0.2028\n", - "3/8, train_loss: 0.0106 step time: 0.2020\n", - "4/8, train_loss: 0.0115 step time: 0.2526\n", - "5/8, train_loss: 0.0119 step time: 0.1970\n", - "6/8, train_loss: 0.0136 step time: 0.1988\n", - "7/8, train_loss: 0.0107 step time: 0.1818\n", - "8/8, train_loss: 0.0101 step time: 0.1817\n", - "epoch 494 average loss: 0.0119\n", - "time consuming of epoch 494 is: 1.6587\n", - "----------\n", - "epoch 495/600\n", - "1/8, train_loss: 0.0119 step time: 0.2409\n", - "2/8, train_loss: 0.0117 step time: 0.2000\n", - "3/8, train_loss: 0.0128 step time: 0.1981\n", - "4/8, train_loss: 0.0105 step time: 0.1990\n", - "5/8, train_loss: 0.0126 step time: 0.2003\n", - "6/8, train_loss: 0.0100 step time: 0.1997\n", - "7/8, train_loss: 0.0120 step time: 0.1834\n", - "8/8, train_loss: 0.0111 step time: 0.1815\n", - "epoch 495 average loss: 0.0116\n", - "current epoch: 495 current mean dice: 0.9596 best mean dice: 0.9597 at epoch: 480\n", - "time consuming of epoch 495 is: 2.3592\n", - "----------\n", - "epoch 496/600\n", - "1/8, train_loss: 0.0129 step time: 0.2389\n", - "2/8, train_loss: 0.0094 step time: 0.2000\n", - "3/8, train_loss: 0.0109 step time: 0.2026\n", - "4/8, train_loss: 0.0112 step time: 0.1985\n", - "5/8, train_loss: 0.0122 step time: 0.1973\n", - "6/8, train_loss: 0.0134 step time: 0.1956\n", - "7/8, train_loss: 0.0115 step time: 0.1815\n", - "8/8, train_loss: 0.0124 step time: 0.1812\n", - "epoch 496 average loss: 0.0117\n", - "time consuming of epoch 496 is: 1.5968\n", - "----------\n", - "epoch 497/600\n", - "1/8, train_loss: 0.0148 step time: 0.2385\n", - "2/8, train_loss: 0.0116 step time: 0.2018\n", - "3/8, train_loss: 0.0135 step time: 0.2003\n", - "4/8, train_loss: 0.0107 step time: 0.2019\n", - "5/8, train_loss: 0.0113 step time: 0.2014\n", - "6/8, train_loss: 0.0114 step time: 0.2021\n", - "7/8, train_loss: 0.0109 step time: 0.1827\n", - "8/8, train_loss: 0.0120 step time: 0.1829\n", - "epoch 497 average loss: 0.0120\n", - "time consuming of epoch 497 is: 1.6129\n", - "----------\n", - "epoch 498/600\n", - "1/8, train_loss: 0.0133 step time: 0.2399\n", - "2/8, train_loss: 0.0129 step time: 0.2042\n", - "3/8, train_loss: 0.0112 step time: 0.1950\n", - "4/8, train_loss: 0.0116 step time: 0.2031\n", - "5/8, train_loss: 0.0114 step time: 0.2033\n", - "6/8, train_loss: 0.0093 step time: 0.1993\n", - "7/8, train_loss: 0.0128 step time: 0.1830\n", - "8/8, train_loss: 0.0105 step time: 0.1840\n", - "epoch 498 average loss: 0.0116\n", - "time consuming of epoch 498 is: 1.6135\n", - "----------\n", - "epoch 499/600\n", - "1/8, train_loss: 0.0135 step time: 0.2406\n", - "2/8, train_loss: 0.0124 step time: 0.1958\n", - "3/8, train_loss: 0.0118 step time: 0.1964\n", - "4/8, train_loss: 0.0103 step time: 0.1974\n", - "5/8, train_loss: 0.0094 step time: 0.1986\n", - "6/8, train_loss: 0.0127 step time: 0.1968\n", - "7/8, train_loss: 0.0138 step time: 0.1831\n", - "8/8, train_loss: 0.0132 step time: 0.1827\n", - "epoch 499 average loss: 0.0121\n", - "time consuming of epoch 499 is: 1.5931\n", - "----------\n", - "epoch 500/600\n", - "1/8, train_loss: 0.0107 step time: 0.2428\n", - "2/8, train_loss: 0.0112 step time: 0.2017\n", - "3/8, train_loss: 0.0141 step time: 0.2015\n", - "4/8, train_loss: 0.0106 step time: 0.2018\n", - "5/8, train_loss: 0.0106 step time: 0.2072\n", - "6/8, train_loss: 0.0134 step time: 0.2045\n", - "7/8, train_loss: 0.0111 step time: 0.1809\n", - "8/8, train_loss: 0.0158 step time: 0.1855\n", - "epoch 500 average loss: 0.0122\n", - "current epoch: 500 current mean dice: 0.9591 best mean dice: 0.9597 at epoch: 480\n", - "time consuming of epoch 500 is: 2.3833\n", - "----------\n", - "epoch 501/600\n", - "1/8, train_loss: 0.0132 step time: 0.2296\n", - "2/8, train_loss: 0.0091 step time: 0.1996\n", - "3/8, train_loss: 0.0126 step time: 0.1997\n", - "4/8, train_loss: 0.0105 step time: 0.1976\n", - "5/8, train_loss: 0.0106 step time: 0.1975\n", - "6/8, train_loss: 0.0133 step time: 0.1968\n", - "7/8, train_loss: 0.0121 step time: 0.1813\n", - "8/8, train_loss: 0.0119 step time: 0.1811\n", - "epoch 501 average loss: 0.0117\n", - "time consuming of epoch 501 is: 1.5843\n", - "----------\n", - "epoch 502/600\n", - "1/8, train_loss: 0.0114 step time: 0.2362\n", - "2/8, train_loss: 0.0135 step time: 0.2022\n", - "3/8, train_loss: 0.0096 step time: 0.1996\n", - "4/8, train_loss: 0.0101 step time: 0.2000\n", - "5/8, train_loss: 0.0097 step time: 0.1958\n", - "6/8, train_loss: 0.0098 step time: 0.2001\n", - "7/8, train_loss: 0.0139 step time: 0.1829\n", - "8/8, train_loss: 0.0133 step time: 0.1827\n", - "epoch 502 average loss: 0.0114\n", - "time consuming of epoch 502 is: 1.6009\n", - "----------\n", - "epoch 503/600\n", - "1/8, train_loss: 0.0131 step time: 0.2397\n", - "2/8, train_loss: 0.0115 step time: 0.2005\n", - "3/8, train_loss: 0.0113 step time: 0.2008\n", - "4/8, train_loss: 0.0134 step time: 0.2020\n", - "5/8, train_loss: 0.0106 step time: 0.1981\n", - "6/8, train_loss: 0.0148 step time: 0.2028\n", - "7/8, train_loss: 0.0110 step time: 0.1825\n", - "8/8, train_loss: 0.0116 step time: 0.1826\n", - "epoch 503 average loss: 0.0122\n", - "time consuming of epoch 503 is: 1.6106\n", - "----------\n", - "epoch 504/600\n", - "1/8, train_loss: 0.0130 step time: 0.2401\n", - "2/8, train_loss: 0.0095 step time: 0.2035\n", - "3/8, train_loss: 0.0104 step time: 0.2041\n", - "4/8, train_loss: 0.0111 step time: 0.1991\n", - "5/8, train_loss: 0.0136 step time: 0.2017\n", - "6/8, train_loss: 0.0117 step time: 0.1990\n", - "7/8, train_loss: 0.0117 step time: 0.1837\n", - "8/8, train_loss: 0.0100 step time: 0.1827\n", - "epoch 504 average loss: 0.0114\n", - "time consuming of epoch 504 is: 1.6152\n", - "----------\n", - "epoch 505/600\n", - "1/8, train_loss: 0.0123 step time: 0.2457\n", - "2/8, train_loss: 0.0100 step time: 0.1954\n", - "3/8, train_loss: 0.0120 step time: 0.1992\n", - "4/8, train_loss: 0.0119 step time: 0.1975\n", - "5/8, train_loss: 0.0107 step time: 0.1970\n", - "6/8, train_loss: 0.0121 step time: 0.1956\n", - "7/8, train_loss: 0.0130 step time: 0.1852\n", - "8/8, train_loss: 0.0104 step time: 0.1951\n", - "epoch 505 average loss: 0.0116\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "saved new best metric model\n", - "current epoch: 505 current mean dice: 0.9601 best mean dice: 0.9601 at epoch: 505\n", - "time consuming of epoch 505 is: 2.5339\n", - "----------\n", - "epoch 506/600\n", - "1/8, train_loss: 0.0122 step time: 0.2301\n", - "2/8, train_loss: 0.0118 step time: 0.1953\n", - "3/8, train_loss: 0.0135 step time: 0.1988\n", - "4/8, train_loss: 0.0116 step time: 0.2029\n", - "5/8, train_loss: 0.0111 step time: 0.1980\n", - "6/8, train_loss: 0.0141 step time: 0.2013\n", - "7/8, train_loss: 0.0103 step time: 0.1822\n", - "8/8, train_loss: 0.0106 step time: 0.1820\n", - "epoch 506 average loss: 0.0119\n", - "time consuming of epoch 506 is: 1.5921\n", - "----------\n", - "epoch 507/600\n", - "1/8, train_loss: 0.0143 step time: 0.2373\n", - "2/8, train_loss: 0.0100 step time: 0.2017\n", - "3/8, train_loss: 0.0115 step time: 0.1992\n", - "4/8, train_loss: 0.0099 step time: 0.2005\n", - "5/8, train_loss: 0.0112 step time: 0.2019\n", - "6/8, train_loss: 0.0117 step time: 0.2054\n", - "7/8, train_loss: 0.0119 step time: 0.1838\n", - "8/8, train_loss: 0.0104 step time: 0.1830\n", - "epoch 507 average loss: 0.0114\n", - "time consuming of epoch 507 is: 1.6144\n", - "----------\n", - "epoch 508/600\n", - "1/8, train_loss: 0.0115 step time: 0.2391\n", - "2/8, train_loss: 0.0105 step time: 0.2020\n", - "3/8, train_loss: 0.0142 step time: 0.2023\n", - "4/8, train_loss: 0.0140 step time: 0.2019\n", - "5/8, train_loss: 0.0116 step time: 0.2010\n", - "6/8, train_loss: 0.0112 step time: 0.2003\n", - "7/8, train_loss: 0.0102 step time: 0.1847\n", - "8/8, train_loss: 0.0119 step time: 0.1819\n", - "epoch 508 average loss: 0.0119\n", - "time consuming of epoch 508 is: 1.6150\n", - "----------\n", - "epoch 509/600\n", - "1/8, train_loss: 0.0104 step time: 0.2419\n", - "2/8, train_loss: 0.0112 step time: 0.2072\n", - "3/8, train_loss: 0.0117 step time: 0.2016\n", - "4/8, train_loss: 0.0107 step time: 0.1993\n", - "5/8, train_loss: 0.0100 step time: 0.2022\n", - "6/8, train_loss: 0.0125 step time: 0.2058\n", - "7/8, train_loss: 0.0110 step time: 0.1842\n", - "8/8, train_loss: 0.0138 step time: 0.1831\n", - "epoch 509 average loss: 0.0114\n", - "time consuming of epoch 509 is: 1.6267\n", - "----------\n", - "epoch 510/600\n", - "1/8, train_loss: 0.0120 step time: 0.2392\n", - "2/8, train_loss: 0.0112 step time: 0.2070\n", - "3/8, train_loss: 0.0110 step time: 0.1971\n", - "4/8, train_loss: 0.0099 step time: 0.1979\n", - "5/8, train_loss: 0.0132 step time: 0.1968\n", - "6/8, train_loss: 0.0102 step time: 0.1967\n", - "7/8, train_loss: 0.0138 step time: 0.1796\n", - "8/8, train_loss: 0.0126 step time: 0.1790\n", - "epoch 510 average loss: 0.0117\n", - "current epoch: 510 current mean dice: 0.9601 best mean dice: 0.9601 at epoch: 505\n", - "time consuming of epoch 510 is: 2.3472\n", - "----------\n", - "epoch 511/600\n", - "1/8, train_loss: 0.0139 step time: 0.2397\n", - "2/8, train_loss: 0.0134 step time: 0.2016\n", - 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0.2409\n", - "2/8, train_loss: 0.0106 step time: 0.2017\n", - "3/8, train_loss: 0.0136 step time: 0.2006\n", - "4/8, train_loss: 0.0114 step time: 0.2071\n", - "5/8, train_loss: 0.0095 step time: 0.2001\n", - "6/8, train_loss: 0.0102 step time: 0.2020\n", - "7/8, train_loss: 0.0130 step time: 0.1822\n", - "8/8, train_loss: 0.0129 step time: 0.1820\n", - "epoch 515 average loss: 0.0116\n", - "current epoch: 515 current mean dice: 0.9600 best mean dice: 0.9601 at epoch: 505\n", - "time consuming of epoch 515 is: 2.3734\n", - "----------\n", - "epoch 516/600\n", - "1/8, train_loss: 0.0125 step time: 0.2375\n", - "2/8, train_loss: 0.0106 step time: 0.2001\n", - "3/8, train_loss: 0.0115 step time: 0.1998\n", - "4/8, train_loss: 0.0114 step time: 0.2032\n", - "5/8, train_loss: 0.0121 step time: 0.1993\n", - "6/8, train_loss: 0.0118 step time: 0.1983\n", - "7/8, train_loss: 0.0121 step time: 0.1818\n", - "8/8, train_loss: 0.0130 step time: 0.1814\n", - "epoch 516 average loss: 0.0119\n", - "time consuming of epoch 516 is: 1.6025\n", - "----------\n", - "epoch 517/600\n", - "1/8, train_loss: 0.0160 step time: 0.2407\n", - "2/8, train_loss: 0.0105 step time: 0.2038\n", - "3/8, train_loss: 0.0122 step time: 0.1999\n", - "4/8, train_loss: 0.0085 step time: 0.2005\n", - "5/8, train_loss: 0.0102 step time: 0.2006\n", - "6/8, train_loss: 0.0110 step time: 0.2007\n", - "7/8, train_loss: 0.0109 step time: 0.1829\n", - "8/8, train_loss: 0.0123 step time: 0.1823\n", - "epoch 517 average loss: 0.0114\n", - "time consuming of epoch 517 is: 1.6129\n", - "----------\n", - "epoch 518/600\n", - "1/8, train_loss: 0.0121 step time: 0.2398\n", - "2/8, train_loss: 0.0118 step time: 0.2030\n", - "3/8, train_loss: 0.0128 step time: 0.1998\n", - "4/8, train_loss: 0.0113 step time: 0.2006\n", - "5/8, train_loss: 0.0113 step time: 0.1976\n", - "6/8, train_loss: 0.0126 step time: 0.1998\n", - "7/8, train_loss: 0.0109 step time: 0.1830\n", - "8/8, train_loss: 0.0106 step time: 0.1829\n", - "epoch 518 average loss: 0.0117\n", - "time consuming of epoch 518 is: 1.6081\n", - "----------\n", - "epoch 519/600\n", - "1/8, train_loss: 0.0098 step time: 0.2384\n", - "2/8, train_loss: 0.0126 step time: 0.2005\n", - "3/8, train_loss: 0.0129 step time: 0.2008\n", - "4/8, train_loss: 0.0102 step time: 0.1985\n", - "5/8, train_loss: 0.0121 step time: 0.2060\n", - "6/8, train_loss: 0.0105 step time: 0.2029\n", - "7/8, train_loss: 0.0114 step time: 0.1825\n", - "8/8, train_loss: 0.0146 step time: 0.1826\n", - "epoch 519 average loss: 0.0118\n", - "time consuming of epoch 519 is: 1.6135\n", - "----------\n", - "epoch 520/600\n", - "1/8, train_loss: 0.0083 step time: 0.2410\n", - "2/8, train_loss: 0.0095 step time: 0.1999\n", - "3/8, train_loss: 0.0108 step time: 0.1989\n", - "4/8, train_loss: 0.0120 step time: 0.1993\n", - "5/8, train_loss: 0.0125 step time: 0.1996\n", - "6/8, train_loss: 0.0113 step time: 0.1993\n", - "7/8, train_loss: 0.0110 step time: 0.1837\n", - "8/8, train_loss: 0.0147 step time: 0.1847\n", - "epoch 520 average loss: 0.0113\n", - "saved new best metric model\n", - "current epoch: 520 current mean dice: 0.9603 best mean dice: 0.9603 at epoch: 520\n", - "time consuming of epoch 520 is: 2.5019\n", - "----------\n", - "epoch 521/600\n", - "1/8, train_loss: 0.0116 step time: 0.2390\n", - "2/8, train_loss: 0.0123 step time: 0.1993\n", - "3/8, train_loss: 0.0122 step time: 0.1989\n", - "4/8, train_loss: 0.0108 step time: 0.1995\n", - "5/8, train_loss: 0.0135 step time: 0.2002\n", - "6/8, train_loss: 0.0119 step time: 0.1982\n", - "7/8, train_loss: 0.0113 step time: 0.1798\n", - "8/8, train_loss: 0.0112 step time: 0.1827\n", - "epoch 521 average loss: 0.0118\n", - "time consuming of epoch 521 is: 1.5987\n", - "----------\n", - "epoch 522/600\n", - "1/8, train_loss: 0.0136 step time: 0.2379\n", - "2/8, train_loss: 0.0103 step time: 0.2014\n", - "3/8, train_loss: 0.0109 step time: 0.1998\n", - "4/8, train_loss: 0.0126 step time: 0.2009\n", - "5/8, train_loss: 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205\n", - "time consuming of epoch 265 is: 2.3695\n", - "----------\n", - "epoch 266/600\n", - "1/8, train_loss: 0.0117 step time: 0.2320\n", - "2/8, train_loss: 0.0088 step time: 0.1971\n", - "3/8, train_loss: 0.0095 step time: 0.1953\n", - "4/8, train_loss: 0.0101 step time: 0.1934\n", - "5/8, train_loss: 0.0096 step time: 0.1943\n", - "6/8, train_loss: 0.0113 step time: 0.1941\n", - "7/8, train_loss: 0.0089 step time: 0.1808\n", - "8/8, train_loss: 0.0087 step time: 0.1807\n", - "epoch 266 average loss: 0.0098\n", - "time consuming of epoch 266 is: 1.5689\n", - "----------\n", - "epoch 267/600\n", - "1/8, train_loss: 0.0095 step time: 0.2397\n", - "2/8, train_loss: 0.0093 step time: 0.2009\n", - "3/8, train_loss: 0.0081 step time: 0.2000\n", - "4/8, train_loss: 0.0085 step time: 0.2001\n", - "5/8, train_loss: 0.0111 step time: 0.1987\n", - "6/8, train_loss: 0.0098 step time: 0.1990\n", - "7/8, train_loss: 0.0111 step time: 0.1824\n", - "8/8, train_loss: 0.0123 step time: 0.1819\n", 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0.2013\n", - "7/8, train_loss: 0.0089 step time: 0.1825\n", - "8/8, train_loss: 0.0112 step time: 0.1833\n", - "epoch 429 average loss: 0.0099\n", - "time consuming of epoch 429 is: 1.6076\n", - "----------\n", - "epoch 430/600\n", - "1/8, train_loss: 0.0086 step time: 0.2410\n", - "2/8, train_loss: 0.0077 step time: 0.2037\n", - "3/8, train_loss: 0.0089 step time: 0.2023\n", - "4/8, train_loss: 0.0086 step time: 0.1999\n", - "5/8, train_loss: 0.0084 step time: 0.2001\n", - "6/8, train_loss: 0.0102 step time: 0.1991\n", - "7/8, train_loss: 0.0086 step time: 0.1833\n", - "8/8, train_loss: 0.0135 step time: 0.1824\n", - "epoch 430 average loss: 0.0093\n", - "current epoch: 430 current mean dice: 0.9620 best mean dice: 0.9622 at epoch: 205\n", - "time consuming of epoch 430 is: 2.3702\n", - "----------\n", - "epoch 431/600\n", - "1/8, train_loss: 0.0080 step time: 0.2375\n", - "2/8, train_loss: 0.0087 step time: 0.2014\n", - "3/8, train_loss: 0.0080 step time: 0.1983\n", - "4/8, 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205\n", - "time consuming of epoch 490 is: 2.3896\n", - "----------\n", - "epoch 491/600\n", - "1/8, train_loss: 0.0089 step time: 0.2409\n", - "2/8, train_loss: 0.0088 step time: 0.1990\n", - "3/8, train_loss: 0.0083 step time: 0.2014\n", - "4/8, train_loss: 0.0114 step time: 0.1988\n", - "5/8, train_loss: 0.0092 step time: 0.1990\n", - "6/8, train_loss: 0.0081 step time: 0.1981\n", - "7/8, train_loss: 0.0105 step time: 0.1810\n", - "8/8, train_loss: 0.0093 step time: 0.1818\n", - "epoch 491 average loss: 0.0093\n", - "time consuming of epoch 491 is: 1.6012\n", - "----------\n", - "epoch 492/600\n", - "1/8, train_loss: 0.0086 step time: 0.2401\n", - "2/8, train_loss: 0.0087 step time: 0.2051\n", - "3/8, train_loss: 0.0077 step time: 0.2044\n", - "4/8, train_loss: 0.0092 step time: 0.2001\n", - "5/8, train_loss: 0.0105 step time: 0.2009\n", - "6/8, train_loss: 0.0101 step time: 0.2001\n", - "7/8, train_loss: 0.0077 step time: 0.1838\n", - "8/8, train_loss: 0.0115 step time: 0.1829\n", 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0.1998\n", - "7/8, train_loss: 0.0072 step time: 0.1814\n", - "8/8, train_loss: 0.0093 step time: 0.1839\n", - "epoch 546 average loss: 0.0091\n", - "time consuming of epoch 546 is: 1.6009\n", - "----------\n", - "epoch 547/600\n", - "1/8, train_loss: 0.0095 step time: 0.2431\n", - "2/8, train_loss: 0.0078 step time: 0.2027\n", - "3/8, train_loss: 0.0100 step time: 0.1989\n", - "4/8, train_loss: 0.0083 step time: 0.2013\n", - "5/8, train_loss: 0.0124 step time: 0.2017\n", - "6/8, train_loss: 0.0077 step time: 0.2002\n", - "7/8, train_loss: 0.0074 step time: 0.1832\n", - "8/8, train_loss: 0.0075 step time: 0.1826\n", - "epoch 547 average loss: 0.0088\n", - "time consuming of epoch 547 is: 1.6150\n", - "----------\n", - "epoch 548/600\n", - "1/8, train_loss: 0.0089 step time: 0.2385\n", - "2/8, train_loss: 0.0098 step time: 0.1995\n", - "3/8, train_loss: 0.0101 step time: 0.2011\n", - "4/8, train_loss: 0.0081 step time: 0.2005\n", - "5/8, train_loss: 0.0102 step time: 0.2016\n", - "6/8, 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step time: 0.1951\n", - "6/8, train_loss: 0.0093 step time: 0.1963\n", - "7/8, train_loss: 0.0074 step time: 0.1828\n", - "8/8, train_loss: 0.0074 step time: 0.1823\n", - "epoch 550 average loss: 0.0089\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "current epoch: 550 current mean dice: 0.9607 best mean dice: 0.9623 at epoch: 525\n", - "time consuming of epoch 550 is: 2.3482\n", - "----------\n", - "epoch 551/600\n", - "1/8, train_loss: 0.0078 step time: 0.2374\n", - "2/8, train_loss: 0.0065 step time: 0.1992\n", - "3/8, train_loss: 0.0107 step time: 0.2007\n", - "4/8, train_loss: 0.0089 step time: 0.1996\n", - "5/8, train_loss: 0.0106 step time: 0.2003\n", - "6/8, train_loss: 0.0071 step time: 0.1997\n", - "7/8, train_loss: 0.0082 step time: 0.1818\n", - "8/8, train_loss: 0.0119 step time: 0.1814\n", - "epoch 551 average loss: 0.0090\n", - "time consuming of epoch 551 is: 1.6011\n", - "----------\n", - "epoch 552/600\n", - "1/8, train_loss: 0.0074 step 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0.1827\n", - "8/8, train_loss: 0.0097 step time: 0.1823\n", - "epoch 559 average loss: 0.0090\n", - "time consuming of epoch 559 is: 1.6199\n", - "----------\n", - "epoch 560/600\n", - "1/8, train_loss: 0.0112 step time: 0.2429\n", - "2/8, train_loss: 0.0109 step time: 0.2063\n", - "3/8, train_loss: 0.0107 step time: 0.2043\n", - "4/8, train_loss: 0.0075 step time: 0.2000\n", - "5/8, train_loss: 0.0078 step time: 0.2012\n", - "6/8, train_loss: 0.0078 step time: 0.2000\n", - "7/8, train_loss: 0.0087 step time: 0.1823\n", - "8/8, train_loss: 0.0081 step time: 0.1822\n", - "epoch 560 average loss: 0.0091\n", - "current epoch: 560 current mean dice: 0.9619 best mean dice: 0.9623 at epoch: 525\n", - "time consuming of epoch 560 is: 2.3759\n", - "----------\n", - "epoch 561/600\n", - "1/8, train_loss: 0.0090 step time: 0.2374\n", - "2/8, train_loss: 0.0089 step time: 0.1978\n", - "3/8, train_loss: 0.0081 step time: 0.1997\n", - "4/8, train_loss: 0.0086 step time: 0.1992\n", - "5/8, 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0.2043\n", - "6/8, train_loss: 0.0081 step time: 0.2029\n", - "7/8, train_loss: 0.0102 step time: 0.1838\n", - "8/8, train_loss: 0.0088 step time: 0.1834\n", - "epoch 574 average loss: 0.0092\n", - "time consuming of epoch 574 is: 1.5988\n", - "----------\n", - "epoch 575/600\n", - "1/8, train_loss: 0.0104 step time: 0.2416\n", - "2/8, train_loss: 0.0099 step time: 0.2006\n", - "3/8, train_loss: 0.0096 step time: 0.2020\n", - "4/8, train_loss: 0.0092 step time: 0.2022\n", - "5/8, train_loss: 0.0096 step time: 0.2036\n", - "6/8, train_loss: 0.0089 step time: 0.1986\n", - "7/8, train_loss: 0.0084 step time: 0.1831\n", - "8/8, train_loss: 0.0076 step time: 0.1821\n", - "epoch 575 average loss: 0.0092\n", - "current epoch: 575 current mean dice: 0.9622 best mean dice: 0.9623 at epoch: 525\n", - "time consuming of epoch 575 is: 2.3719\n", - "----------\n", - "epoch 576/600\n", - "1/8, train_loss: 0.0087 step time: 0.2378\n", - "2/8, train_loss: 0.0085 step time: 0.1989\n", - "3/8, train_loss: 0.0088 step time: 0.1980\n", - "4/8, train_loss: 0.0071 step time: 0.2027\n", - "5/8, train_loss: 0.0118 step time: 0.1975\n", - "6/8, train_loss: 0.0086 step time: 0.2020\n", - "7/8, train_loss: 0.0077 step time: 0.1840\n", - "8/8, train_loss: 0.0094 step time: 0.1826\n", - "epoch 576 average loss: 0.0088\n", - "time consuming of epoch 576 is: 1.6046\n", - "----------\n", - "epoch 577/600\n", - "1/8, train_loss: 0.0092 step time: 0.2413\n", - "2/8, train_loss: 0.0091 step time: 0.1992\n", - "3/8, train_loss: 0.0086 step time: 0.1985\n", - "4/8, train_loss: 0.0095 step time: 0.2004\n", - "5/8, train_loss: 0.0095 step time: 0.1992\n", - "6/8, train_loss: 0.0077 step time: 0.1990\n", - "7/8, train_loss: 0.0083 step time: 0.1835\n", - "8/8, train_loss: 0.0082 step time: 0.1819\n", - "epoch 577 average loss: 0.0088\n", - "time consuming of epoch 577 is: 1.6042\n", - "----------\n", - "epoch 578/600\n", - "1/8, train_loss: 0.0090 step time: 0.2407\n", - "2/8, train_loss: 0.0096 step time: 0.1957\n", - "3/8, train_loss: 0.0109 step time: 0.1979\n", - "4/8, train_loss: 0.0089 step time: 0.1981\n", - "5/8, train_loss: 0.0095 step time: 0.1955\n", - "6/8, train_loss: 0.0072 step time: 0.1957\n", - "7/8, train_loss: 0.0077 step time: 0.1822\n", - "8/8, train_loss: 0.0080 step time: 0.1824\n", - "epoch 578 average loss: 0.0089\n", - "time consuming of epoch 578 is: 1.5896\n", - "----------\n", - "epoch 579/600\n", - "1/8, train_loss: 0.0078 step time: 0.2435\n", - "2/8, train_loss: 0.0061 step time: 0.2016\n", - "3/8, train_loss: 0.0113 step time: 0.1997\n", - "4/8, train_loss: 0.0101 step time: 0.2064\n", - "5/8, train_loss: 0.0098 step time: 0.2028\n", - "6/8, train_loss: 0.0088 step time: 0.2023\n", - "7/8, train_loss: 0.0084 step time: 0.1837\n", - "8/8, train_loss: 0.0091 step time: 0.1839\n", - "epoch 579 average loss: 0.0089\n", - "time consuming of epoch 579 is: 1.6256\n", - "----------\n", - "epoch 580/600\n", - "1/8, train_loss: 0.0076 step time: 0.2404\n", - "2/8, train_loss: 0.0086 step time: 0.2030\n", - "3/8, train_loss: 0.0087 step time: 0.2000\n", - "4/8, train_loss: 0.0077 step time: 0.2014\n", - "5/8, train_loss: 0.0079 step time: 0.2020\n", - "6/8, train_loss: 0.0069 step time: 0.2027\n", - "7/8, train_loss: 0.0079 step time: 0.1843\n", - "8/8, train_loss: 0.0120 step time: 0.1840\n", - "epoch 580 average loss: 0.0084\n", - "current epoch: 580 current mean dice: 0.9619 best mean dice: 0.9623 at epoch: 525\n", - "time consuming of epoch 580 is: 2.3768\n", - "----------\n", - "epoch 581/600\n", - "1/8, train_loss: 0.0074 step time: 0.2408\n", - "2/8, train_loss: 0.0087 step time: 0.2014\n", - "3/8, train_loss: 0.0102 step time: 0.1988\n", - "4/8, train_loss: 0.0113 step time: 0.1992\n", - "5/8, train_loss: 0.0077 step time: 0.1993\n", - "6/8, train_loss: 0.0083 step time: 0.2015\n", - "7/8, train_loss: 0.0075 step time: 0.1806\n", - "8/8, train_loss: 0.0086 step time: 0.1813\n", - "epoch 581 average loss: 0.0087\n", - "time consuming of epoch 581 is: 1.6041\n", - "----------\n", - "epoch 582/600\n", - "1/8, train_loss: 0.0098 step time: 0.2399\n", - "2/8, train_loss: 0.0083 step time: 0.2023\n", - "3/8, train_loss: 0.0067 step time: 0.1999\n", - "4/8, train_loss: 0.0078 step time: 0.2035\n", - "5/8, train_loss: 0.0097 step time: 0.2093\n", - "6/8, train_loss: 0.0078 step time: 0.2111\n", - "7/8, train_loss: 0.0075 step time: 0.1826\n", - "8/8, train_loss: 0.0097 step time: 0.1822\n", - "epoch 582 average loss: 0.0084\n", - "time consuming of epoch 582 is: 1.6324\n", - "----------\n", - "epoch 583/600\n", - "1/8, train_loss: 0.0092 step time: 0.2395\n", - "2/8, train_loss: 0.0075 step time: 0.2018\n", - "3/8, train_loss: 0.0087 step time: 0.1989\n", - "4/8, train_loss: 0.0074 step time: 0.2004\n", - "5/8, train_loss: 0.0078 step time: 0.1995\n", - "6/8, train_loss: 0.0086 step time: 0.2009\n", - "7/8, train_loss: 0.0083 step time: 0.1823\n", - "8/8, train_loss: 0.0104 step time: 0.1821\n", - "epoch 583 average loss: 0.0085\n", - "time consuming of epoch 583 is: 1.6068\n", - "----------\n", - "epoch 584/600\n", - "1/8, train_loss: 0.0092 step time: 0.2347\n", - "2/8, train_loss: 0.0080 step time: 0.2001\n", - "3/8, train_loss: 0.0078 step time: 0.1987\n", - "4/8, train_loss: 0.0080 step time: 0.1984\n", - "5/8, train_loss: 0.0090 step time: 0.1978\n", - "6/8, train_loss: 0.0100 step time: 0.2001\n", - "7/8, train_loss: 0.0082 step time: 0.1833\n", - "8/8, train_loss: 0.0083 step time: 0.1821\n", - "epoch 584 average loss: 0.0086\n", - "time consuming of epoch 584 is: 1.5967\n", - "----------\n", - "epoch 585/600\n", - "1/8, train_loss: 0.0081 step time: 0.2389\n", - "2/8, train_loss: 0.0097 step time: 0.2037\n", - "3/8, train_loss: 0.0082 step time: 0.2003\n", - "4/8, train_loss: 0.0096 step time: 0.1960\n", - "5/8, train_loss: 0.0107 step time: 0.1975\n", - "6/8, train_loss: 0.0083 step time: 0.1972\n", - "7/8, train_loss: 0.0083 step time: 0.1792\n", - "8/8, train_loss: 0.0081 step time: 0.1792\n", - "epoch 585 average loss: 0.0089\n", - "current epoch: 585 current mean dice: 0.9621 best mean dice: 0.9623 at epoch: 525\n", - "time consuming of epoch 585 is: 2.3456\n", - "----------\n", - "epoch 586/600\n", - "1/8, train_loss: 0.0088 step time: 0.2361\n", - "2/8, train_loss: 0.0079 step time: 0.1947\n", - "3/8, train_loss: 0.0088 step time: 0.1974\n", - "4/8, train_loss: 0.0084 step time: 0.1955\n", - "5/8, train_loss: 0.0096 step time: 0.1976\n", - "6/8, train_loss: 0.0085 step time: 0.1981\n", - "7/8, train_loss: 0.0117 step time: 0.1795\n", - "8/8, train_loss: 0.0082 step time: 0.1793\n", - "epoch 586 average loss: 0.0090\n", - "time consuming of epoch 586 is: 1.5793\n", - "----------\n", - "epoch 587/600\n", - "1/8, train_loss: 0.0093 step time: 0.2343\n", - "2/8, train_loss: 0.0080 step time: 0.1944\n", - "3/8, train_loss: 0.0077 step time: 0.1973\n", - "4/8, train_loss: 0.0074 step time: 0.1982\n", - "5/8, train_loss: 0.0089 step time: 0.1978\n", - "6/8, train_loss: 0.0082 step time: 0.1980\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "7/8, train_loss: 0.0096 step time: 0.1790\n", - "8/8, train_loss: 0.0113 step time: 0.1791\n", - "epoch 587 average loss: 0.0088\n", - "time consuming of epoch 587 is: 1.5791\n", - "----------\n", - "epoch 588/600\n", - "1/8, train_loss: 0.0096 step time: 0.2337\n", - "2/8, train_loss: 0.0072 step time: 0.1953\n", - "3/8, train_loss: 0.0086 step time: 0.1974\n", - "4/8, train_loss: 0.0102 step time: 0.1984\n", - "5/8, train_loss: 0.0101 step time: 0.1986\n", - "6/8, train_loss: 0.0083 step time: 0.1981\n", - "7/8, train_loss: 0.0094 step time: 0.1794\n", - "8/8, train_loss: 0.0075 step time: 0.1791\n", - "epoch 588 average loss: 0.0089\n", - "time consuming of epoch 588 is: 1.5811\n", - "----------\n", - "epoch 589/600\n", - "1/8, train_loss: 0.0088 step time: 0.2340\n", - "2/8, train_loss: 0.0086 step time: 0.1943\n", - "3/8, train_loss: 0.0088 step time: 0.2028\n", - "4/8, train_loss: 0.0118 step time: 0.2103\n", - "5/8, train_loss: 0.0082 step time: 0.2039\n", - "6/8, train_loss: 0.0098 step time: 0.2011\n", - "7/8, train_loss: 0.0088 step time: 0.1836\n", - "8/8, train_loss: 0.0080 step time: 0.1839\n", - "epoch 589 average loss: 0.0091\n", - "time consuming of epoch 589 is: 1.6152\n", - "----------\n", - "epoch 590/600\n", - "1/8, train_loss: 0.0085 step time: 0.2399\n", - "2/8, train_loss: 0.0076 step time: 0.2031\n", - "3/8, train_loss: 0.0090 step time: 0.1990\n", - "4/8, train_loss: 0.0102 step time: 0.1999\n", - "5/8, train_loss: 0.0085 step time: 0.2043\n", - "6/8, train_loss: 0.0088 step time: 0.1998\n", - "7/8, train_loss: 0.0083 step time: 0.1818\n", - "8/8, train_loss: 0.0077 step time: 0.1818\n", - "epoch 590 average loss: 0.0086\n", - "saved new best metric model\n", - "current epoch: 590 current mean dice: 0.9626 best mean dice: 0.9626 at epoch: 590\n", - "time consuming of epoch 590 is: 2.5070\n", - "----------\n", - "epoch 591/600\n", - "1/8, train_loss: 0.0083 step time: 0.2424\n", - "2/8, train_loss: 0.0077 step time: 0.2013\n", - "3/8, train_loss: 0.0073 step time: 0.2012\n", - "4/8, train_loss: 0.0099 step time: 0.2004\n", - "5/8, train_loss: 0.0081 step time: 0.2012\n", - "6/8, train_loss: 0.0085 step time: 0.1974\n", - "7/8, train_loss: 0.0092 step time: 0.1826\n", - "8/8, train_loss: 0.0093 step time: 0.1834\n", - "epoch 591 average loss: 0.0085\n", - "time consuming of epoch 591 is: 1.6113\n", - "----------\n", - "epoch 592/600\n", - "1/8, train_loss: 0.0080 step time: 0.2386\n", - "2/8, train_loss: 0.0080 step time: 0.1979\n", - "3/8, train_loss: 0.0089 step time: 0.1974\n", - "4/8, train_loss: 0.0111 step time: 0.2002\n", - "5/8, train_loss: 0.0101 step time: 0.1989\n", - "6/8, train_loss: 0.0086 step time: 0.2028\n", - "7/8, train_loss: 0.0113 step time: 0.1817\n", - "8/8, train_loss: 0.0082 step time: 0.1818\n", - "epoch 592 average loss: 0.0093\n", - "time consuming of epoch 592 is: 1.6007\n", - "----------\n", - "epoch 593/600\n", - "1/8, train_loss: 0.0076 step time: 0.2339\n", - "2/8, train_loss: 0.0122 step time: 0.2003\n", - "3/8, train_loss: 0.0103 step time: 0.1962\n", - "4/8, train_loss: 0.0084 step time: 0.1994\n", - "5/8, train_loss: 0.0100 step time: 0.1939\n", - "6/8, train_loss: 0.0116 step time: 0.1951\n", - "7/8, train_loss: 0.0094 step time: 0.1825\n", - "8/8, train_loss: 0.0124 step time: 0.1825\n", - "epoch 593 average loss: 0.0103\n", - "time consuming of epoch 593 is: 1.5853\n", - "----------\n", - "epoch 594/600\n", - "1/8, train_loss: 0.0095 step time: 0.2392\n", - "2/8, train_loss: 0.0085 step time: 0.2089\n", - "3/8, train_loss: 0.0116 step time: 0.2013\n", - "4/8, train_loss: 0.0100 step time: 0.2018\n", - "5/8, train_loss: 0.1568 step time: 0.1916\n", - "6/8, train_loss: 0.0277 step time: 0.2064\n", - "7/8, train_loss: 0.0105 step time: 0.1823\n", - "8/8, train_loss: 0.0116 step time: 0.1823\n", - "epoch 594 average loss: 0.0308\n", - "time consuming of epoch 594 is: 1.6157\n", - "----------\n", - "epoch 595/600\n", - "1/8, train_loss: 0.0185 step time: 0.2398\n", - "2/8, train_loss: 0.0244 step time: 0.2027\n", - "3/8, train_loss: 0.0183 step time: 0.2049\n", - "4/8, train_loss: 0.0210 step time: 0.2012\n", - "5/8, train_loss: 0.0167 step time: 0.1982\n", - "6/8, train_loss: 0.0410 step time: 0.1990\n", - "7/8, train_loss: 0.0310 step time: 0.1822\n", - "8/8, train_loss: 0.0206 step time: 0.1821\n", - "epoch 595 average loss: 0.0239\n", - "current epoch: 595 current mean dice: 0.3226 best mean dice: 0.9626 at epoch: 590\n", - "time consuming of epoch 595 is: 2.3674\n", - "----------\n", - "epoch 596/600\n", - "1/8, train_loss: 0.0235 step time: 0.2339\n", - "2/8, train_loss: 0.0318 step time: 0.1962\n", - "3/8, train_loss: 0.0333 step time: 0.1960\n", - "4/8, train_loss: 0.0261 step time: 0.1952\n", - "5/8, train_loss: 0.0256 step time: 0.1965\n", - "6/8, train_loss: 0.0298 step time: 0.1951\n", - "7/8, train_loss: 0.0255 step time: 0.1812\n", - "8/8, train_loss: 0.0249 step time: 0.1822\n", - "epoch 596 average loss: 0.0276\n", - "time consuming of epoch 596 is: 1.5774\n", - "----------\n", - "epoch 597/600\n", - "1/8, train_loss: 0.0206 step time: 0.2423\n", - "2/8, train_loss: 0.0201 step time: 0.2032\n", - "3/8, train_loss: 0.0203 step time: 0.1987\n", - "4/8, train_loss: 0.0305 step time: 0.2002\n", - "5/8, train_loss: 0.1941 step time: 0.1979\n", - "6/8, train_loss: 0.0986 step time: 0.2003\n", - "7/8, train_loss: 0.0906 step time: 0.1821\n", - "8/8, train_loss: 0.1580 step time: 0.1823\n", - "epoch 597 average loss: 0.0791\n", - "time consuming of epoch 597 is: 1.6086\n", - "----------\n", - "epoch 598/600\n", - "1/8, train_loss: 0.2204 step time: 0.2387\n", - "2/8, train_loss: 0.0536 step time: 0.1979\n", - "3/8, train_loss: 0.3122 step time: 0.2009\n", - "4/8, train_loss: 0.0878 step time: 0.1988\n", - "5/8, train_loss: 0.2671 step time: 0.1993\n", - "6/8, train_loss: 0.1398 step time: 0.2015\n", - "7/8, train_loss: 0.1585 step time: 0.1825\n", - "8/8, train_loss: 0.1076 step time: 0.1811\n", - "epoch 598 average loss: 0.1684\n", - "time consuming of epoch 598 is: 1.6022\n", - "----------\n", - "epoch 599/600\n", - "1/8, train_loss: 0.1258 step time: 0.2353\n", - "2/8, train_loss: 0.1146 step time: 0.1993\n", - "3/8, train_loss: 0.1364 step time: 0.1930\n", - "4/8, train_loss: 0.1370 step time: 0.1989\n", - "5/8, train_loss: 0.1109 step time: 0.1980\n", - "6/8, train_loss: 0.1330 step time: 0.1974\n", - "7/8, train_loss: 0.3919 step time: 0.1813\n", - "8/8, train_loss: 0.1513 step time: 0.1817\n", - "epoch 599 average loss: 0.1626\n", - "time consuming of epoch 599 is: 1.5865\n", - "----------\n", - "epoch 600/600\n", - "1/8, train_loss: 0.1059 step time: 0.2391\n", - "2/8, train_loss: 0.1771 step time: 0.2036\n", - "3/8, train_loss: 0.2619 step time: 0.1958\n", - "4/8, train_loss: 0.1859 step time: 0.2003\n", - "5/8, train_loss: 0.0641 step time: 0.1999\n", - "6/8, train_loss: 0.1746 step time: 0.2021\n", - "7/8, train_loss: 0.1851 step time: 0.1823\n", - "8/8, train_loss: 0.1490 step time: 0.1827\n", - "epoch 600 average loss: 0.1629\n", - "current epoch: 600 current mean dice: 0.1629 best mean dice: 0.9626 at epoch: 590\n", - "time consuming of epoch 600 is: 2.3632\n", - "train completed, best_metric: 0.9626 at epoch: 590 total time: 1055.6900\n", - "\n", - "\n", - "\n", - "\n", - "times: [1061.2309420108795, 1057.999614238739, 1055.689969778061]\n", - "Average time: 1058.3068420092266\n", - "times per load operation: [0.0052551844716072086, 0.005239255477984746, 0.005237527986367544]\n", - "Average time per load operation: 0.005243989311986499\n" - ] - } - ], - "source": [ - "name = 'orig'\n", - "max_epochs = 600\n", - "repeats = 3\n", - "tlpo_sum, total_time_sum, tlpo_list, time_list, losses, metrics = 0, 0, [], [], np.zeros((max_epochs)), np.zeros((max_epochs // 5))\n", - "for _ in range(repeats):\n", - " total_time, loss, metric, tlpo = func()\n", - " total_time_sum += total_time\n", - " time_list.append(total_time)\n", - " metrics += metric\n", - " losses += loss\n", - " tlpo_list.append(tlpo)\n", - " tlpo_sum += tlpo\n", - "\n", - "print('\\n\\n\\n')\n", - "print(f\"times: {time_list}\")\n", - "print(f\"Average time: {total_time_sum / 3}\")\n", - "print(f\"times per load operation: {tlpo_list}\")\n", - "print(f\"Average time per load operation: {tlpo_sum / 3}\")\n", - "\n", - "time_dict[name] = total_time_sum / 3\n", - "metric_dict[name] = metrics / 3\n", - "loss_dict[name] = losses / 3\n", - "tlpo_dict[name] = tlpo_sum / 3" - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "{'thread3': 1237.1164457798004,\n", - " 'thread2': 1142.810050725937,\n", - " 'thread1': 1068.8605738480885,\n", - " 'thread4': 1323.9301082293193,\n", - " 'instance': 903.4545698165894,\n", - " 'instance_nvfuser': 888.926282564799,\n", - " 'orig': 1058.3068420092266}" - ] - }, - "execution_count": 45, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "time_dict" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'thread3': 0.028458230362998115,\n", - " 'thread2': 0.0172835976878802,\n", - " 'thread1': 0.008170056641101837,\n", - " 'thread4': 0.04543388206097815,\n", - " 'instance': 0.005219863222704994,\n", - " 'instance_nvfuser': 0.00524735818306605,\n", - " 'orig': 0.005243989311986499}" - ] - }, - "execution_count": 49, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "tlpo_dict" - ] - }, - { - "cell_type": "code", - "execution_count": 56, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 56, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "plt.title(\"Epoch Average Loss\")\n", - "x = [i + 1 for i in range(max_epochs)]\n", - "plt.xlabel(\"epoch\")\n", - "plt.grid(alpha=0.4, linestyle=\":\")\n", - "plt.plot(x, loss_dict['orig'], label='Batch', color=\"red\")\n", - "plt.plot(x, loss_dict['instance'], label='Instance', color=\"blue\")\n", - "plt.plot(x, loss_dict['instance_nvfuser'], label='Instance_NVFuser', color=\"green\")\n", - "plt.legend()" - ] - }, - { - "cell_type": "code", - "execution_count": 57, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 57, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "plt.title(\"Val Mean Dice\")\n", - "x = [(i + 1) * 5 for i in range(max_epochs // 5)]\n", - "plt.xlabel(\"epoch\")\n", - "plt.grid(alpha=0.4, linestyle=\":\")\n", - "plt.plot(x, metric_dict['orig'], label='Batch', color=\"red\")\n", - "plt.plot(x, metric_dict['instance'], label='Instance', color=\"blue\")\n", - "plt.plot(x, metric_dict['instance_nvfuser'], label='Instance_NVFuser', color=\"green\")\n", - "plt.legend()" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "def func():\n", - " load_ops, load_time = 0, 0\n", - " post_pred = Compose([EnsureType(), AsDiscrete(argmax=True, to_onehot=2)])\n", - " post_label = Compose([EnsureType(), AsDiscrete(to_onehot=2)])\n", - "\n", - " dice_metric = DiceMetric(include_background=False, reduction=\"mean\", get_not_nans=False)\n", - "\n", - " if fast:\n", - " # SGD prefer to much bigger learning rate\n", - " optimizer = SGD(\n", - " model.parameters(),\n", - " lr=learning_rate * 1000,\n", - " momentum=0.9,\n", - " weight_decay=0.00004,\n", - " )\n", - " scaler = torch.cuda.amp.GradScaler()\n", - " else:\n", - " optimizer = Adam(model.parameters(), learning_rate)\n", - "\n", - " best_metric = -1\n", - " best_metric_epoch = -1\n", - " best_metrics_epochs_and_time = [[], [], []]\n", - " epoch_loss_values = []\n", - " metric_values = []\n", - " epoch_times = []\n", - " total_start = time.time()\n", - "\n", - " for epoch in range(max_epochs):\n", - " epoch_start = time.time()\n", - " print(\"-\" * 10)\n", - " print(f\"epoch {epoch + 1}/{max_epochs}\")\n", - "\n", - " # profiling: full epoch\n", - " with nvtx.annotate(\"epoch\", color=\"red\") if profiling else no_profiling:\n", - " model.train()\n", - " epoch_loss = 0\n", - " train_loader_iterator = iter(train_loader)\n", - "\n", - " # using step instead of iterate through train_loader directly to track data loading time\n", - " # steps are 1-indexed for printing and calculation purposes\n", - " for step in range(1, len(train_loader) + 1):\n", - " step_start = time.time()\n", - "\n", - " # profiling: train dataload\n", - " with nvtx.annotate(\"dataload\", color=\"red\") if profiling else no_profiling:\n", - " # rng_train_dataload = nvtx.start_range(message=\"dataload\", color=\"red\")\n", - " load_start = time.time()\n", - " batch_data = next(train_loader_iterator)\n", - " load_time += time.time() - load_start\n", - " load_ops += 1\n", - " inputs, labels = (\n", - " batch_data[\"image\"].to(device),\n", - " batch_data[\"label\"].to(device),\n", - " )\n", - "\n", - " optimizer.zero_grad()\n", - " # set AMP for MONAI training\n", - " # profiling: forward\n", - " with nvtx.annotate(\"forward\", color=\"green\") if profiling else no_profiling:\n", - " with torch.cuda.amp.autocast():\n", - " outputs = model(inputs)\n", - " loss = loss_function(outputs, labels)\n", - "\n", - " # profiling: backward\n", - " with nvtx.annotate(\"backward\", color=\"blue\") if profiling else no_profiling:\n", - " scaler.scale(loss).backward()\n", - "\n", - " # profiling: update\n", - " with nvtx.annotate(\"update\", color=\"yellow\") if profiling else no_profiling:\n", - " scaler.step(optimizer)\n", - " scaler.update()\n", - " epoch_loss += loss.item()\n", - " epoch_len = math.ceil(len(train_ds) / train_loader.batch_size)\n", - " print(\n", - " f\"{step}/{epoch_len}, train_loss: {loss.item():.4f}\"\n", - " f\" step time: {(time.time() - step_start):.4f}\"\n", - " )\n", - " epoch_loss /= step\n", - " epoch_loss_values.append(epoch_loss)\n", - " print(f\"epoch {epoch + 1} average loss: {epoch_loss:.4f}\")\n", - "\n", - " if (epoch + 1) % val_interval == 0:\n", - " model.eval()\n", - " with torch.no_grad():\n", - " val_loader_iterator = iter(val_loader)\n", - "\n", - " for val_step in range(len(val_loader)):\n", - " # profiling: val dataload\n", - " with nvtx.annotate(\"dataload\", color=\"red\") if profiling else no_profiling:\n", - " val_data = next(val_loader_iterator)\n", - " val_inputs, val_labels = (\n", - " val_data[\"image\"].to(device),\n", - " val_data[\"label\"].to(device),\n", - " )\n", - "\n", - " roi_size = (160, 160, 160)\n", - " sw_batch_size = 4\n", - "\n", - " # profiling: sliding window\n", - " with nvtx.annotate(\"sliding window\", color=\"green\") if profiling else no_profiling:\n", - " # set AMP for MONAI validation\n", - " if fast:\n", - " with torch.cuda.amp.autocast():\n", - " val_outputs = sliding_window_inference(\n", - " val_inputs, roi_size, sw_batch_size, model\n", - " )\n", - " else:\n", - " val_outputs = sliding_window_inference(\n", - " val_inputs, roi_size, sw_batch_size, model\n", - " )\n", - "\n", - " # profiling: decollate batch\n", - " with nvtx.annotate(\"decollate batch\", color=\"blue\") if profiling else no_profiling:\n", - " val_outputs = [post_pred(i) for i in decollate_batch(val_outputs)]\n", - " val_labels = [post_label(i) for i in decollate_batch(val_labels)]\n", - "\n", - " # profiling: compute metric\n", - " with nvtx.annotate(\"compute metric\", color=\"yellow\") if profiling else no_profiling:\n", - " dice_metric(y_pred=val_outputs, y=val_labels)\n", - "\n", - " metric = dice_metric.aggregate().item()\n", - " dice_metric.reset()\n", - " metric_values.append(metric)\n", - " if metric > best_metric:\n", - " best_metric = metric\n", - " best_metric_epoch = epoch + 1\n", - " best_metrics_epochs_and_time[0].append(best_metric)\n", - " best_metrics_epochs_and_time[1].append(best_metric_epoch)\n", - " best_metrics_epochs_and_time[2].append(\n", - " time.time() - total_start\n", - " )\n", - " torch.save(model.state_dict(), os.path.join(root_dir, \"best_metric_model.pt\"))\n", - " print(\"saved new best metric model\")\n", - " print(\n", - " f\"current epoch: {epoch + 1} current\"\n", - " f\" mean dice: {metric:.4f}\"\n", - " f\" best mean dice: {best_metric:.4f}\"\n", - " f\" at epoch: {best_metric_epoch}\"\n", - " )\n", - "\n", - " print(\n", - " f\"time consuming of epoch {epoch + 1} is:\"\n", - " f\" {(time.time() - epoch_start):.4f}\"\n", - " )\n", - " epoch_times.append(time.time() - epoch_start)\n", - "\n", - " total_time = time.time() - total_start\n", - " print(\n", - " f\"train completed, best_metric: {best_metric:.4f}\"\n", - " f\" at epoch: {best_metric_epoch}\"\n", - " f\" total time: {total_time:.4f}\"\n", - " )\n", - " \n", - " return total_time, epoch_loss_values, metric_values, load_time / load_ops" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Profiling visualization" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Here we give a brief overview of key observations from the `nsys-rep` output file when opened in Nsight systems (2022.2.1).\n", - "\n", - "In the GUI, select File -> Open -> output_base.nsys-rep. Here is a sample of the display:\n", - "\n", - "![png](figures/nsys-all-annotated.png)\n", - "- To get a better view of details, you can left-click and select a horizontal section, then right-click and \"Zoom into Selection.\" To return, right-click and select \"Reset Zoom.\"\n", - "- Sections B and C show training before and after acceleration (when fast=False and fast=True, accordingly). Clearly, MONAI optimized training is much faster than regular PyTorch training. B and C both contain two rows; the upper row shows per-epoch time, and the lower row shows per-action time (user-defined, like dataloading, forward, backward, etc.).\n", - "- Section A shows GPU utilization, where the height of the blue bars represents utilization rate. Regular PyTorch training shows sporadic and varying levels of GPU utilization, while MONAI optimized training shows consistent and high levels of GPU utilization.\n", - "\n", - "Expanding one more thread in the lower left corner and several more threads below \\[4648\\], we see the following:\n", - "\n", - "![png](figures/nsys-transforms-annotated.png)\n", - "\n", - "Sections D and E both include information on the transform chain.\n", - "- Section E: In MONAI optimized training, results of all transforms in the chain until the first randomized transform is stored to prevent repeated operations. This explains why E is chronologically before any of the training epochs in the figure.\n", - "- Section D: In regular PyTorch training, CacheDataset is not in use, and the transform chain is performed every epoch on all data used.\n", - "\n", - "Here is the display of the transform chain when zoomed in:\n", - "![png](figures/nsys-fast-transform.png)\n", - "\n", - "And a display of one training epoch of MONAI optimized training when zoomed in:\n", - "![png](figures/nsys-epoch-short.png)\n", - "Notice that the per-epoch time is >20 times faster than the regular PyTorch training." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Plot training loss and validation metrics" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "if not profiling:\n", - " plt.figure(\"train\", (12, 12))\n", - " plt.subplot(2, 2, 1)\n", - " plt.title(\"Regular Epoch Average Loss\")\n", - " x = [i + 1 for i in range(len(epoch_loss_values))]\n", - " y = epoch_loss_values\n", - " plt.xlabel(\"epoch\")\n", - " plt.grid(alpha=0.4, linestyle=\":\")\n", - " plt.plot(x, y, color=\"red\")\n", - "\n", - " plt.subplot(2, 2, 2)\n", - " plt.title(\"Regular Val Mean Dice\")\n", - " x = [(i + 1) * 5 for i in range(len(metric_values))]\n", - " y = metric_values\n", - " plt.xlabel(\"epoch\")\n", - " plt.ylim(0, 1)\n", - " plt.grid(alpha=0.4, linestyle=\":\")\n", - " plt.plot(x, y, color=\"red\")\n", - "\n", - " plt.subplot(2, 2, 3)\n", - " plt.title(\"Fast Epoch Average Loss\")\n", - " x = [i + 1 for i in range(len(m_epoch_loss_values))]\n", - " y = m_epoch_loss_values\n", - " plt.xlabel(\"epoch\")\n", - " plt.grid(alpha=0.4, linestyle=\":\")\n", - " plt.plot(x, y, color=\"green\")\n", - "\n", - " plt.subplot(2, 2, 4)\n", - " plt.title(\"Fast Val Mean Dice\")\n", - " x = [(i + 1) * 5 for i in range(len(m_metric_values))]\n", - " y = m_metric_values\n", - " plt.xlabel(\"epoch\")\n", - " plt.ylim(0, 1)\n", - " plt.grid(alpha=0.4, linestyle=\":\")\n", - " plt.plot(x, y, color=\"green\")\n", - " plt.savefig(\"outputs/loss_dice_comparison.png\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Plot total time and every epoch time" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "if not profiling:\n", - " plt.figure(\"train\", (12, 6))\n", - " plt.subplot(1, 2, 1)\n", - " plt.title(\"Total Train Time(600 epochs)\")\n", - " plt.bar(\n", - " \"regular PyTorch\", total_time, 1, label=\"Regular training\", color=\"red\"\n", - " )\n", - " plt.bar(\"Fast\", m_total_time, 1, label=\"Fast training\", color=\"green\")\n", - " plt.ylabel(\"secs\")\n", - " plt.grid(alpha=0.4, linestyle=\":\")\n", - " plt.legend(loc=\"best\")\n", - "\n", - " plt.subplot(1, 2, 2)\n", - " plt.title(\"Epoch Time\")\n", - " x = [i + 1 for i in range(len(epoch_times))]\n", - " plt.xlabel(\"epoch\")\n", - " plt.ylabel(\"secs\")\n", - " plt.plot(x, epoch_times, label=\"Regular training\", color=\"red\")\n", - " plt.plot(x, m_epoch_times, label=\"Fast training\", color=\"green\")\n", - " plt.grid(alpha=0.4, linestyle=\":\")\n", - " plt.legend(loc=\"best\")\n", - " plt.savefig(\"outputs/total_epoch_time_comparison.png\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Plot total time to achieve metrics" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": { - "vscode": { - "languageId": "python" - } + "vscode": { + "languageId": "python" + } }, "outputs": [ { "data": { - "image/png": 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", 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\n", 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" ] @@ -24145,7 +1069,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "metadata": { "vscode": { "languageId": "python" From 2839422fca0b45bee9a0eb31dee27f06a845054e Mon Sep 17 00:00:00 2001 From: Yuchen Xu Date: Sat, 2 Jul 2022 21:58:42 -0700 Subject: [PATCH 11/12] various updates; ready for review --- .gitignore | 1 - acceleration/fast_training_tutorial.ipynb | 93 +++++------------------ 2 files changed, 20 insertions(+), 74 deletions(-) diff --git a/.gitignore b/.gitignore index 2327c1d595..7106fe50ab 100644 --- a/.gitignore +++ b/.gitignore @@ -151,4 +151,3 @@ deployment/ray/mednist_classifier_start.py *.nii.gz 3d_segmentation/out *.nsys-rep -acceleration/outputs diff --git a/acceleration/fast_training_tutorial.ipynb b/acceleration/fast_training_tutorial.ipynb index 4335fd084d..6b6c1d3cdb 100644 --- a/acceleration/fast_training_tutorial.ipynb +++ b/acceleration/fast_training_tutorial.ipynb @@ -19,7 +19,6 @@ "4. multi-threads `ThreadDataLoader` is faster than PyTorch DataLoader in light-weight task.\n", "5. Use MONAI `DiceCE` loss instead of regular `Dice` loss.\n", "6. Analyzed training curve and tuned algorithm: Use `SGD` optimizer, different network parameters, etc.\n", - "7. Instance norm in place of batch norm.\n", "\n", "With a V100 GPU and the target validation `mean dice = 0.94` of the `forground` channel only, it's more than `100x` speedup compared with the Pytorch regular implementation when achieving the same metric. And every epoch is `20x` faster than regular training.\n", "\n", @@ -39,10 +38,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "To support profiling, the following lines have been commented out. \n", + "This cell verifies that you have key packages installed and sets up the matplotlib environment.\n", "\n", - "- To verify that you have key packages installed, uncomment the middle section (3 lines).\n", - "- If you are not interested in profiling (i.e., you will run this as a Jupyter notebook), uncomment the last line." + "Important: if you are interested in profiling, comment out this cell after you finish the checks." ] }, { @@ -55,11 +53,11 @@ }, "outputs": [], "source": [ - "# these are commented out to ensure the converted python script runs smoothly\n", + "# if profiling, comment out this cell to ensure the converted python script runs smoothly\n", "\n", - "# !python3 -c \"import monai\" || pip install -q \"monai-weekly[nibabel, tqdm]\"\n", - "# !python3 -c \"import matplotlib\" || pip install -q matplotlib\n", - "# !python3 -c \"import nvtx\" || pip install -q nvtx\n", + "!python3 -c \"import monai\" || pip install -q \"monai-weekly[nibabel, tqdm]\"\n", + "!python3 -c \"import matplotlib\" || pip install -q matplotlib\n", + "!python3 -c \"import nvtx\" || pip install -q nvtx\n", "\n", "%matplotlib inline" ] @@ -73,55 +71,13 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": { "vscode": { "languageId": "python" } }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/conda/lib/python3.8/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", - " from .autonotebook import tqdm as notebook_tqdm\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MONAI version: 0.9.0\n", - "Numpy version: 1.22.3\n", - "Pytorch version: 1.12.0a0+bd13bc6\n", - "MONAI flags: HAS_EXT = True, USE_COMPILED = False\n", - "MONAI rev id: af0e0e9f757558d144b655c63afcea3a4e0a06f5\n", - "MONAI __file__: /opt/monai/monai/__init__.py\n", - "\n", - "Optional dependencies:\n", - "Pytorch Ignite version: 0.4.8\n", - "Nibabel version: 3.2.2\n", - "scikit-image version: 0.19.3\n", - "Pillow version: 9.0.1\n", - "Tensorboard version: 2.8.0\n", - "gdown version: 4.4.0\n", - "TorchVision version: 0.13.0a0\n", - "tqdm version: 4.64.0\n", - "lmdb version: 1.3.0\n", - "psutil version: 5.9.0\n", - "pandas version: 1.3.5\n", - "einops version: 0.4.1\n", - "transformers version: 4.19.4\n", - "mlflow version: 1.26.1\n", - "pynrrd version: 0.4.3\n", - "\n", - "For details about installing the optional dependencies, please visit:\n", - " https://docs.monai.io/en/latest/installation.html#installing-the-recommended-dependencies\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "# Copyright 2020 MONAI Consortium\n", "# Licensed under the Apache License, Version 2.0 (the \"License\");\n", @@ -196,21 +152,13 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": { "vscode": { "languageId": "python" } }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "root dir is: /tmp/tmpnhldk6uv\n" - ] - } - ], + "outputs": [], "source": [ "directory = os.environ.get(\"MONAI_DATA_DIRECTORY\")\n", "root_dir = tempfile.mkdtemp() if directory is None else directory\n", @@ -347,7 +295,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 19, "metadata": { "vscode": { "languageId": "python" @@ -481,14 +429,13 @@ "4. `ThreadDataLoader`: uses multi-threads instead of multi-processing, faster than `DataLoader` in light-weight task as we already cached the results of most computation.\n", "5. `DiceCE` loss function: computes Dice loss and Cross Entropy Loss, returns the weighted sum of these two losses.\n", "6. Analyzed the training curve and tuned algorithm: Use `SGD` optimizer, different network parameters, etc.\n", - "7. `Instance_NVFuser` norm (`Norm.INSTANCE_NVFUSER`) instead of batch norm (`Norm.BATCH`). This norm may take a while to set up in the beginning, but it still results in faster training with comparable results. As an alternative, use instance norm (`Norm.INSTANCE`), which is slightly slower but has more uniform time cost. For more details, refer to the [source code](https://github.com/Project-MONAI/MONAI/blob/812275ae5f4a1bc8a69b70a9823632b6f30a5724/monai/networks/layers/factories.py#L253) of all defined norms.\n", "\n", "(A note on code: to improve readability and support the profiling flag, we used the `with nvtx(...) if profiling else no_profiling` context pattern, where `no_profiling` is a null context from Python's native `contextlib` with no effect on the code. An acknowledgement is provided here[1](#fn1).)" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 16, "metadata": { "vscode": { "languageId": "python" @@ -543,7 +490,7 @@ " channels=(32, 64, 128, 256, 512),\n", " strides=(2, 2, 2, 2),\n", " num_res_units=2,\n", - " norm=Norm.INSTANCE_NVFUSER,\n", + " norm=Norm.BATCH,\n", " kernel_size=3,\n", " up_kernel_size=3,\n", " act=Act.PRELU,\n", @@ -853,7 +800,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 23, "metadata": { "vscode": { "languageId": "python" @@ -862,7 +809,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -921,7 +868,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 24, "metadata": { "vscode": { "languageId": "python" @@ -930,7 +877,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -975,7 +922,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 25, "metadata": { "vscode": { "languageId": "python" @@ -984,7 +931,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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H888/nxUrVvA///M/tLe3M3r0aH7+85+z7777Yozh/PPP5+GHH6asrIybb76ZJUuW5E1vFGXlTldijnGp1zQbfPChHtzBBx8+ePCFjo4OKisrs/5j5tIXF3BLT760iAiVlZUD/oLq2vk3EvScccYZPPLII9tt37BhA3/5y1+YOXNm77YLL7yQFStWsGLFCq644gre//73M3nyZFatWsWvf/1rnnvuOV566SUeeugh1q1b1/u+r3zlK73vy1XnA7hXXr4wHG2xS+0ejEw9mbbD4N655JKefGspLi7mJz/5CatXr+bZZ5/l+uuvZ/Xq1Vx00UV873vf47nnnuPSSy/loosuAuDPf/4za9euZe3atfzqV7/i3HPPzaveKMrKndqRY7q7u6OWMCz44EM9uIMPPnzw4BPD8aUsOTvPHVzSk08tmZSla+ffSNDzgQ98gMmTJ2+3/Stf+QpXXnllv+V25513ctxxxwGwZs0a9ttvP8rKyiguLuaDH/wgf/jDH4Zd60C4Vl4+kW1b7FK7ByNXT6bl6Nq55JKefGvZaaedekcwTJgwgXnz5rFp0yZEhObmZrq7u2lqamLatGkAPPDAA5x22mmICPvvvz+NjY1s3pyTazL0SRRlNWI6IEpLS6OWMCz44EM9uIMPPnzwoITJ5otzUVERixcvZuHChXz84x+nsbFx2PV86EMfYtmyZUM+3v3338/q1asH/b4HH3yQK6+80rrP22+/zSc/+cmhShs0rp1/I1XPAw88wPTp09lrr736fL29vZ1HHnmEE044AYCFCxfy1FNPUVdXR3t7Ow8//DAbNmzo3f9nP/sZe+65J2eeeSYNDQ050+1aeSlbybYDY7jb4r70aFu8FdfOJZf0RKll/fr1vPjii+y3335cc801XHjhhcyfP5+vfe1rXHHFFQBs2rSJGTNm9L6nurqaTZs25U1jFPmMmA6Itra2qCUMCz74UA/u4IMPHzx4i8iQbqOKivp+LQPGjh3LihUrWLVqFZMnT+b666/P2kYikcjq/T09PaHnti+98Xi83+McddRRXHjhhdbPmjZtGvfee+/gRQ4R186/kainvb2dyy+/nEsvvbTfff74xz/yvve9r3ehsXnz5vH1r3+dQw45hMMOO4zFixf3zmc/99xzef3111mxYgU77bQTX/3qV3Om3bXy8pbhbIcjaouzbYdB2+J84pKeqLS0trZy3HHHcc011zBx4kRuuOEGrr76alauXMnVV1/NWWedFYmubYkinxHTATFx4sSoJQwLPvhQD+7ggw8fPCi54b3vfW/vrwivv/46hx12GPvssw/vf//7efXVV3u377///ixatIhvf/vbjB8/HoAnnniCj33sY0Dyl7zzzjuPm2++ebvPOPfcc1m6dCkLFizge9/7Xu/2WbNm8fWvf50lS5bwu9/9rnf7v/71Lx588EEuvPBCFi9ezOuvv86HPvQhvvzlL7N06VKuvfZa/vjHP7Lffvux995789GPfpR3330XgJtvvpnzzz8fSK4D8KUvfYkDDjiAXXfdtfeL7vr161m4cGHv/sceeyyHHXYYc+bM6Z1vCnDjjTey++67s++++3L22Wdz3nnnDSlj186/kajn9ddf580332SvvfZi1qxZbNy4kSVLlvDOO+/07nPXXXdx0kknhfScddZZvPDCC/zjH/+goqKC3XffHYAdd9yRoqIiRo0axdlnn81zzz2XM+2ulZeSG4ajLU51kGlb3DeunUsu6YlCS3d3N8cddxynnHIKxx57LAC33HILxx57LBMnTuT444/vbVunT58eGoG2ceNGpk+fnjetUeQzYjogcjmEMJ/44EM9uIMPPnzwoAw/PT09PPbYYxx11FEAnHPOOfz0pz/lhRde4KqrruLzn/88AOeffz7nn38+K1eupLq6ut9j9cdll13GsmXLePnll3nyySd5+eWXe1+rrKxk+fLlnHjiib3bDjjgAI466ih+/OMfs2LFCmbPng1AV1cXy5Yt46tf/SoHHnggzz77LC+++CInnnhiaKhv+rzjzZs38/TTT/PQQw9x8cUX96lvxYoV3H333axcuZK7776bDRs28Pbbb/ODH/yAZ599ln/+85+9/wAMBdfOv5GoZ9GiRWzZsoX169ezfv16qqurWb58OVOnTgWgqamJJ598kqOPPjqkZ8uWLQD897//5Q9/+AMnn3wyQGju8X333df7T1QucK28lOFnuNpiWzsM2ha7di65pCffWowxnHXWWcybN48LLrigd/u0adN48sknaWho4O9//ztz5swBkiNqbr31VowxPPvss5SXl7PTTjvlTW8UZTViLsNZWVk54D5tXW2s2rKK/ar3y4OioZGJD9dRD+7ggw8fPCjDRywWY/HixWzatIl58+Zx8MEH09rayr/+9S+OP/743v06OzsBeOaZZ7j//vsBOPnkk/na17623TGLi/v/U3nPPffwq1/9ing8zubNm1m9ejV77rknAJ/61Kcy1p2+78aNG/nUpz7F5s2b6erqCl1+LX216mOOOYZRo0Yxf/783l/mtuWggw6ivLwcgPnz5/PWW29RW1vLBz/4wd6FDI8//nj+85//ZKw1HdfOv5Gg56STTuKJJ56gtraW6upqvv/971uH8t53330ccsghjBs3jnHjxvVuP+6446irq6OkpITrr7+eSZMmAXDRRRexYsUKRIRZs2bxy1/+ctg9pHCtvJThY7jbYls7DNoWu3YuuaQn31r++c9/ctttt7Fo0SIWL14MJC9n/Otf/5rzzz+feDxOaWkpv/rVrwA44ogjePjhh9ltt90oKyvjt7/9bV71RlFWI6YDoqampvea1ineaX2HB197kBfefoHVtat5+r9PU1ZSxpvnv8kO43aISKmdvnwUGurBHXzw4YMHZfhIzTtub2/n0EMP5frrr+eMM85g0qRJrFixIuPjFBcX98457u7u7vMyaG+++SZXXXUVzz//PBUVFZxxxhmh/dL/2RuI9H2/+MUvcsEFF3DUUUfxxBNPcMkll/S+lj4POjWfH/pfkT19n6KiIuu85qHg2vk3EvTceeed1tfXr18fen7GGWdwxhlnbKfnqaee6vP9t912W9YaM8W18lKGj+Fui7u7uykpKdG2uB9cO5dc0pNvLQceeGC/9eCFF17YTo+IDMt6VUMlirIaMVMwUsHeu/pevvP37/DRWz/KjKtn8LmHPsfv1/yehEnw5f2+zAMnPuBs5wPgzMmcDerBHXzwMWQPxkAiAfE4dHdDVxd0dEAsBu3tycdKwVJWVsZ1113HT37yE8rKythll1165/8aY3jppZcA2H///fn9738PJOfJp9h5551ZvXo1nZ2dtLW18dhjj233Gc3NzYwbN47y8nLeffdd/vznP2ekbcKECbS0tPT7elNTU+/8z1tuuSX02nBcr/s973lP7zDQeDze638ouNaGjGg9GSwsWLXDDgPvl0dcKy9l+BmutjiRSNDY2KhtcT+4di65pEfbYTtRlNWIGgFRL/Uc/7vksK89puzBJ/b4BBcecCHvmf6eiNVljks9ikNFPURALAYvvADPPgsbNvT+0x1rbWVsUdHWf8JT993d0NOT/Ac99Y/6tvfbbsvnLe0zEz09yZ7UPl7r93Em1+8+7DDI8EuM4iZ77703e+65J3feeSd33HEH5557Lj/84Q/p7u7mxBNPZK+99uKaa67h1FNP5bLLLuOwww7rHSI7Y8YMTjjhBBYuXMisWbPYe++9tzv+Xnvtxd57780ee+zBjBkzeN/73peRrhNPPJGzzz6b6667rs9V0i+55BKOP/54Kioq+MhHPsKbb77Z+9pwrAQ/ffp0vvnNb7LvvvsyefJk9thjj17fg8W1tlD12KlZtIiqlSujltGLa/kouWG42uJddtlF2+J+cO1cckmPS1pA22EA6W+IiMssXbrUDPa6vwmTYM5P5/Dfpv/y8v+8zLyqeTlSpyhDwJjkP/9dXVs7AGyPW1qgsRGamrbepz/e9j69h7+8HEpKkrfi4v7vi4pg1KjkTaTv+9TjfN7SP3Pbz+/vtaE83nVXGOQ1vEXkBWPM0uGrGO7SVzu8Zs0a5s0rrLa1vb2dsWPHIiLcdddd3HnnnTzwwANRy8o5ra2tjB8/nng8zic+8QnOPPNMPvGJT2y3XyGW6YhluH41K8DvhduibXHhnbfaFvffFhdieY5YtB3uxdYOj5gREE+89gRvNLzBb4/+bUF3PtTX1/cuVlOoFJyHRALWroV//xtWr4bOTjpaWigdNWrgjoJtH/f3end3dhqLimDSpGTnQup+zpzkfXk5TJ4MixfDfvvBjjv2vq3gyqIPfPCghInH4wMuODZcvPDCC5x33nkYY5g0aRI33XRTpHoGYri0XHLJJfztb3+jo6ODQw45hGOOOWZIx3Ht/FM9durnzmXya69FLaMX1/JRtpLvdm+gttildhi0LR4Il/S4pAW0HYYR1AHxeuvrAHxw5w9GrCQ7hjo0yyWc91BXl+xs+Pe/k1MWnnsuOZIAkqMDSksZU1ICo0dvHUmQepy+bexYmDix/9cHetzf6yUlyeOmdzaUlQ2p19X5ssgAHzwoYVLXe88H73//+3vnIPdHPvUMxHBpueqqq4blOK6df6rHTvkbb0QtIYRr+ShbyXe7N1Bb7FI7DNoWD4RLelzSAtoOwwjqgKhpqQGgYmxFxEqyo7W11bkTabA45aGzE774RXj88a3PN2xIPh41ChYuhOOPh/33T44e2GMPKCqiuanJHQ9Z4FRZDBEfPChhenp6nPqlyyU9LmkB984/1WOndfp0yre5SkaUuJaPshXX2hrVY8e1c8klPS5pAW2HYQR1QHSa5HWGx48eH7GS7Bg7dmzUErLGGQ/NzfCJT8Df/w7HHJMcRVBUBAsWJDsbli6F8X3XF2c8ZIkPPnzwoIQZjtXFhxOX9LikBdw7/1SPnbG1tVFLCOFaPspWXGtrVI8d184ll/S4pAW0HYYR1AHRFGtiTNEYikcVtuWuri5Gjx4dtYyscMLDu+/CEUfAyy/DrbfCpz89qLc74WEY8MGHDx6UMK4tjuySHpe0gHvnn+qx0zVxIqNbW6OW0Ytr+Shbca2tUT12XDuXXNLjkhbQdhhGUAdEt+mmtLg0ahlZ49ocuKEQuYc334RDDoFNm+DBB+Hwwwd9iMg9DBM++PDBgxJG8nwN7IFwSY9LWsC980/12Cnq7IxaQgjX8lG24lpbo3rsuHYuuaTHJS2g7TCAW+OHckh3TzclRSVRy1Ci5qWX4IADoL4+OfViCJ0PiqK4S1FREYsXL+69rR/kPMtrrrmG9vb2Qb9m47vf/S5/+9vfrPs8+OCD/OhHPxr0sRVFUVxE22JFUfpjxIyA6OrpomRU4XdA9PT0RC0hayLz8OSTcNRRyStI/P3vkMU1lX0oB/DDhw8efEW+P7y/EJnvDTzkdezYsaxYsWLIn3HNNddw6qmnUlZWtvVzg6G2fb2Woqenp99fES699NIBP/eoo47iqKOOGnA/14b9unb+qR47PWPGRC0hhGv5+IoPbXF626dt8fa4di65pMclLaDtMIygERAJEl6MgHBpDtNQicTDfffBoYfC9Onwr39l1fkAfpQD+OHDBw9K7mhtbeWggw5iyZIlLFq0iAceeACAtrY2jjzySPbaay8WLlzI3XffzXXXXcfbb7/Nhz/8YT784Q/3HkNE+nxt/PjxfPWrX2WvvfbimWee4dJLL+U973kPCxcu5Jxzzun9gnrGGWdw7733AjBr1iy+973v9ep59dVXAbj55ps577zzevf/0pe+xAEHHMCuu+7a+95EIsF5553HHnvswcEHH8wRRxzR+1pUuHb+qR47o5ubo5YQwrV8lNyRbVucmvKgbXHfuHYuuaTHJS2g7TCMoA6Ijq4OL0ZAxGKxqCVkTd49/PrX8MlPwt57w1NPwYwZWR/Sh3IAP3z44EEZPmKxWO+Q30984hOUlpZy3333sXz5ch5//HG++tWvYozhkUceYdq0abz00kusWrWKww47jC996UtMmzaNxx9/nMdTl+Yl+WWzr9fa2trYb7/9eOmllzjwwAM577zzeP7551m1ahWxWIyHHnqoT41Tpkxh+fLlnHvuuf1eA37z5s08/fTTPPTQQ1x88cUA/OEPf2D9+vWsXr2a2267jWeeeWaY0xs8rp1/qsdObMqUqCWEcC0fZfgY7rY4kUgAaFvcD66dSy7pcUkLaDsMI6gDwowyXoyAGN/PZSELibx5MAZ++EM455zk6Ie//Q0qK4fl0D6UA/jhwwcPAyEiN4nIFhFZ1cdrXxURIyJTguciIteJyDoReVlElqTte7qIrA1up6dt30dEVgbvuU5cW11rEKSG/a5YsYL77rsPYwzf/OY32XPPPfnoRz/Kpk2bePfdd1m0aBF//etf+frXv85TTz1lvQZ2f8N5i4qKOO6443qfP/744+y3334sWrSIv//977zyyit9vu/YY48FYJ999ul3XvQxxxzDqFGjmD9/Pu+++y4ATz/9NMcffzyjRo1i6tSpoVEaUZGL8+/MM89khx12YOHChb3bvvOd77DnnnuyePFiDjnkEN5++20AfvzjH/f+k7Nw4UImT55MfX197/t6enrYe++9+djHPta7zRjDt771LXbffXfmzZvHddddN+weUrjWPo3ftClqCSFcy0cZPoa7LbYtlKdtcX7PpQ0bNvDhD3+Y+fPns2DBAq699tre137605+yxx57cMABB3DRRRf1br/iiivYbbfdmDt3Lo8++mjetIJ77Yy2wyOoA6K9s92LERBNTU1RS8iavHioqYHzzoPvfCd5ic0HHoBx44bt8D6UA/jhwwcPGXAzcNi2G0VkBnAI8N+0zYcDc4LbOcANwb6Tge8B+wH7At8TkYrgPTcAZ6e9b7vPKlTuuOMOampqeOGFF1ixYgU77rgjHR0d7L777ixfvpxFixbx7W9/2zo3uL/5kaWlpb1fijs6Ovj85z/Pvffey8qVKzn77LPp6Ojo831jgvmfRUVFxONx6z4Qnmuc+hXQFXJx/p1xxhk88sgjoW0XXnghL7/8MitWrOBjH/tYb3ldeOGFvf/kXHHFFRxwwAFMnjy5933XXnst87aZcnfzzTezYcMGXn31VdasWcOJJ5447B5SuNY+Ne26a9QSQriWj5I7sm2LbfPUtS3O77lUXFzMT37yE1avXs2zzz7L9ddfz+rVq3n88cd54IEHeOmll3jqqaf42te+BsDq1au56667eOWVV3jkkUf4/Oc/n9d1B1xrZ7QdHkEdEFIkXoyASP9iVajkzMP69XD11fDBD8LUqfDzn8NXvwo33wwlw1v2PpQD+OHDBw8DYYz5B1Dfx0tXAxcB6athHQ3capI8C0wSkZ2AQ4G/GmPqjTENwF+Bw4LXJhpjnjXJb1e3Asfk0E5eaWpqYocddqCkpITHH3+ct956C4C3336bsrIyTj31VC688EKWL18OwIQJE2hpaQkdo7i4uN/XUqS+4E6ZMoXW1taczAd+3/vex/33308ikeDdd9/liSeeGPbPGCy5OP8+8IEPbHfciRMn9j5ua2vr8xJ4d955J6eddlrv840bN/KnP/2Jz372s6H9brjhBr773e8yalTyK9AOO+wwnPJDuNY+TX7ttaglhHAtHyV3ZNsWp9rhvl5LR9vi3LPTTjuxZElycOWECROYN28emzZt4oYbbuDiiy9mzJgxTJ48ubdtfeCBBzjxxBMZM2YMu+yyC7vtthvPPfdc3vS61s5oOzyCOiDaO9opHlX4F/2oqamJWkLWDJsHY+Dll+H730+u77DLLnDBBdDQAN/+NqxYAVddBaOGv5r7UA7ghw8fPAwFETka2GSMeWmbl6YDG9Kebwy22bZv7GO7F5xyyiksW7aMRYsWceutt7LHHnsAsHLlSvbdd18WL17M97//fb797W8DcM4553DYYYeFhtR2d3f3+1qKSZMmcfbZZ7Nw4UIOPfRQ3vOe9wy7l+OOO45p06Yxf/58Tj31VJYsWWKdOpIP8nn+fetb32LGjBnccccd2/1K2t7eziOPPMIHP/jB3m1f/vKXufLKK3s7GlK8/vrr3H333SxdupTDDz+ctWvX5kyza+1TzaJFUUsI4Vo+Su7Iti1OtcN9vZaOtsX5Zf369bz44ovst99+/Oc//+Gpp55iv/3244ADDuD5558HYNOmTcxIW3+turqaTXmchuBaO6PtMMnhRIV222effcxg+cgtHzHvu/F9g36f4hg9PcY89ZQxF1xgzK67GgPGiBhz4IHGXHWVMevWRa1QGcEAy0yO2j1gFrAqeFwG/BsoD56vB6YEjx8CDkx732PAUuBrwLfTtn8n2LYU+Fva9vcDD/Wj4RxgGbBsxowZJhaLmba2NtPa2mo6OjrMqlWrTCKRMN3d3SaRSJiuri5jjAndp78ej8dNT0+Picfjocc9PT29+3R3d293DGNM6PX09w3HMbbV45KnhoYGk0gkzDvvvGN23XVX89///jennl555RXT1NRkOjo6TGtrq2lrazOxWMw0Nzebrq4u09DQYHp6ekxtba0xxpgtW7aE7uvq6kw8HjeNjY2ms7PTtLS0mPb2dtPe3m5aWlpMZ2enaWxsNPF43NTV1fW+98033zR77LGHMcaY2traXu9dXV3me9/7nvnmN78Zqns33XSTOfLII019fb1JJBLmjjvuMOeee67ZsmWLefzxx83BBx9sEomEqa+vN+PGjTM//OEPTUdHh7njjjvMAQcckBdP6ffbempubt7ufGpqajLd3d29nmpqakLHqKmp6fXU3d1tmmbONB3l5aZ16lTTVlVlYhUVprm62nSVlZmG2bNNT1GRqZ03zxgwWxYtCt3XzZ1r4iUlpnHWLLc8DbHu5bItdu3W13fi1atXb7dNGV5aWlqMMcl6v+uuu5rNmzfn7LNcLc+WlhazZMkS8/vf/94YY8yCBQvMeeedZxKJhPn3v/9tZs2aZRKJhPnCF75gbrvttt73nXnmmeZ3v/tdVLJzS/Ln0exvHmBrhwt/SECGtHe0UzqmNGoZWVNTU0NVVVXUMrJiSB7eegt++9vk7b//hdGj4aMfhYsvhqOOgh13zI3YfvChHMAPHz54GAKzgV2Al4Kh6NXAchHZF9gEpF/qpTrYtgn40Dbbnwi2V/ex/3YYY34F/Apg6dKlprQ03KaOGjUKEekdKlsSTH3a9j71en+LinV3d2+3b3/HSB+Wuy2pX76zOca2eobqabj0HH300TQ1NdHV1cV3vvOd3l+VBuvJpiP9WCLSO/0hfS50quy7u7sZNWoUlcECv6lzMXWfGtqZ+nWwr8t9pbal9q2qqqKtra03y9SxJ02aBCQXqTziiCO47LLLeo/x4IMPcvLJJxOPxxERVq5cyYMPPsjDDz9MR0cHzc3NfPrTn+b222+nurqak08+mTFjxnDSSSdx7rnnUlpa2usp9TnD4Sk1z3nbY2zrqaSPaYKpvCsqkku1TAlWTk8dI/U89frE/yaXghmTNp+3tKEh+Tmvvw5AIijzqpUrQ/epIcHl69fD6NEZl1O2npLfUS2eLHVvoHJSsiO93XMB1/QceeSRobZ46tSpkerJ93eh7u5ujjvuOE455ZTexTyrq6s59thjERF22WUXRo0aRW1tLdOnT2fDhq0DMDdu3Mj06fkbaOna98SaRYt6214XiCKfEdMBQRFeLELp0gk0VDL20NkJDz4Iv/kN/PWvyW0HHww/+hEceSSkzQnONz6UA/jhwwcPg8UYsxLonbguIuuBpcaYWhF5EDhPRO4iueBkkzFms4g8ClyetvDkIcA3jDH1ItIsIvuTHFVxGvDTfPrZFpe+ZIJbep588smoJYTI1/m3du1a5syZAyTnE6eGb0NybvmTTz7J7bffzrhgseErrriCK664AoAnnniCq666ittvvx1Irmr/+OOPs8suu/Dkk0+y++6750y3a+2TS196wb18lK241O6Be3pGalsMyY7Ds846i3nz5nHBBRf0bk+1rR/+8IdpaGigq6uLKVOmcNRRR3HyySdzwQUX8Pbbb7N27Vr23XffvOl1rZ3RdngEdUDEOmNMHuvWIiRDoa6urre3v1AZ0MOqVXDjjXDbbVBXBzNnwne/C5/5DOy8c/6EWvChHMAPHz54GAgRuZPk6IUpIrIR+J4x5sZ+dn8YOAJYB7QDnwEIOhp+ADwf7HepMSa1sOXnSV5pYyzw5+AWGfF4PKNf8POFS3pc0gK5Of9OOukknnjiCWpra6murub73/8+Dz/8MK+99hqjRo1i55135he/+EXv/vfddx+HHHII48aNy0jPxRdfzCmnnMLVV1/N+PHj+c1vfjOs+tNxrX2qmzePyjVropbRi2v5KFtxra1RPXbyeS7985//5LbbbmPRokUsXrwYgMsvv5wzzzyTM888k4ULFzJq1ChuueUWRIQFCxZwwgknMH/+fIqLi7n++uutowWHG9faGW2HQVLD3wqJpUuXmmXLlg3qPYt/sZidJ+3MAyc+kCNV+SGRSGy3oFahYfVw7bXw5S8nr1pxzDHw2c/CQQdBHhuqTPChHMAPHy55EJEXjDFLo9aRD/pqh9esWcMee+zR5xUKBoMxJutjDCcu6cmnFmMMr7766naXsUzHpfMPRrieDOpFoqiIUQNd/i6P3wtzlY+2xdm3xS61ezBy9WTSDsMIb/sGQNthO1G0w27UjDzQFe/y4ioYzc3NUUvIGquHlSuhshLefhvuuQcOOcS5zgfwoxzADx8+ePCF0tJS6urqyLZjO5/XB88El/TkS4sxhrq6OrZd52Nb8nr+iQx4a95994H3yyOutU/Ns2ZFLSGEa/n4wnC0xS61ezAy9WTaDoO2xTZca2e0HR5BUzAMhlFS+P0tqfmthYzVQywGkyZBsBCVq/hQDuCHDx88+EJ1dTUbN27M+pJOI/WXrkzIp5bS0lKqq6ut+7h2/o3bvDlqCSE0Hzuu5eMLw9EWu9TuwcjVk0k7DO6dSy61NZqNnSjyGTEdED2JHorEvV/SB0tHR4dzC/EMFquHWAzGjs2voCHgQzmAHz588OALJSUl7LLLLlkfp6WlhQkTJgyDouHBJT0uaQH3zr+OyZMpaW+PWkYvmo8d1/LxheFoi11ra1SPHdfOJZfaGs3GThT5FP6QgAzxZQSESyfQULF6KJAOCB/KAfzw4YMHJYxrZeqSHpe0gIN62tqilhBC87HjWj7KVlwrG9Vjxzk9DrU1mo2dKPIp/P/IM6Qn0eNFB0QikYhaQtZYPcRiUFaWPzFDxIdyAD98+OBBCeNambqkxyUt4KAeh1alB81nIFzLR9mKa2Wjeuw4p8ehtkazsRNFPoX/H3mGJEyColGFPwWjEK9asi1WD+3tBTECwodyAD98+OBBCeNambqkxyUt4KAexxYt1nzsuJaPshXXykb12HFOj0NtjWZjJ4p8RkwHRA9+jIBw6ZrDQ8XqoUCmYPhQDuCHDx88KGFcK1OX9LikBRzUE4tFLSGE5mPHtXyUrbhWNqrHjnN6HGprNBs7UeRT+P+RZ0gikfBiEcrOzs6oJWSN1UOBdED4UA7ghw8fPChhXCtTl/S4pAUc1FNeHrWEEJqPHdfyUbbiWtmoHjvO6XGordFs7ESRz8jpgDAJL0ZAlBXA+ggDYfVQIB0QPpQD+OHDBw9KGNfK1CU9LmkBB/Vs2RK1hBCajx3X8hluRGSGiDwuIqtF5BUROT/YfomIbBKRFcHtiLT3fENE1onIayJyaFTaXSsb1WPHOT0OtTWajZ0o8in8/8gzJJ6IezECoqWlJWoJWWP1UCAdED6UA/jhwwcPShjXytQlPS5pAQf1zJgRtYQQmo8d1/LJAXHgq8aY+cD+wBdEZH7w2tXGmMXB7WGA4LUTgQXAYcDPRaL58upa2ageO87pcait0WzsRJHPiOmASODHIpSTJk2KWkLWWD0USAeED+UAfvjwwYMSxrUydUmPS1rAQT3r1kUtIYTmY8e1fIYbY8xmY8zy4HELsAaYbnnL0cBdxphOY8ybwDpg39wr3R7Xykb12HFOj0NtjWZjJ4p8RkwHRLzHjxEQdXV1UUvImn49GAMdHQXRAeFDOYAfPnzwoIRxrUxd0uOSFnBQz4IFUUsIofnYcS2fXCIis4C9gX8Hm84TkZdF5CYRqQi2TQc2pL1tI/YOi5zhWtmoHjvO6XGordFs7ESRz4jpgPBlBMSUKVOilpA1/Xro6EjeOzZXqy98KAfww4cPHpQwrpWpS3pc0gIO6lm1KmoJITQfO67lkytEZDzwe+DLxphm4AZgNrAY2Az8ZJDHO0dElonIsi1bttDR0UF7ezttbW10dnbS3NxMPB6noaEBYwy1tbUA1NTUAFBbW4sxhoaGBuLxOM3NzXR2dtLW1kZ7ezsdHR2MGTOG7u5uGhsbSSQSvf+kpI6Ruq+vr6enp4empia6urpobW0lFosRi8VobW2lq6uLpqYmenp6qK+v7/MYdXV1JBIJGhsb6e7upqWlZTtPo0ePztpTS0vLsHkqKSnJ2tNwlFPKU3Fxcf7KafZsusvKaKmupqOigvaqKtqmTqWzvJzmmTOJl5ZS1NmJEaF24cLkMYL72oULMSI0zJmTl3JqamqioqIif+VUWkrzzJl0lpfTNnUq7VVVdFRU0FJdTXdZGY2zZzN5zRrq5s1LHmPRotB9/dy59JSU5Px8SvdUWVmZk/PJijGm4G777LOPGSxjfzjWfO3Rrw36fa6xZcuWqCVkTb8eamuNAWOuvTa/goaAD+VgjB8+XPIALDMOtJH5uA2lHc4Ul8rUmNzo+cxnPmOqqqrMggULerd97WtfM3PnzjWLFi0yxxxzjGloaOh97aWXXjL777+/mTt3rlm4cKGJxWLGGGPuuusus2jRIjN//nxz0UUX9e7f0dFhTjjhBDN79myz7777mjfffHPYPRiT57JKjpOz3rYsXDjwfnlE87GTq3xcaouBEuBR4IJ+Xp8FrAoefwP4RtprjwLvtR0/V23xSGiH++O///2v+dCHPmTmzZtn5s+fb6655prQ61dddZUBTE1NjTHGmEQiYb74xS+a2bNnm0WLFpkXXnghb1pTaFvTP5qNnSja4REzAqLH9HgxAqKqqipqCVnTr4fUdXELYAqGD+UAfvjwwYMSxrUyzYWeM844g0ceeSS07eCDD2bVqlW8/PLL7L777lxxxRUAxONxTj31VH7xi1/w6quv8sQTT1BSUkJdXR0XXnghjz32GK+88grvvPMOjz32GAA33ngjFRUVrFu3jq985St8/etfH3YP4GBZOfYLv+Zjx7V8hhsREeBGYI0x5v/Stu+UttsngFTBPAicKCJjRGQXYA7wXL70puNa2eRTT3FxMT/5yU9YvXo1zz77LNdffz2rV68GYMOGDfzlL39h5syZvfv/+c9/Zu3ataxdu5Zf/epXnHvuuXnTmsK58nKordFs7ESRz8jpgEj0eLEGRGqITCHTr4cC6oDwoRzADx8+eFDCuFamudDzgQ98gMmTJ4e2HXLIIRQXFwOw//77s3HjRgD+8pe/sOeee7LXXntRW1tLZWUlRUVFvPHGG8yZM6f3y8NHP/pRfv/73wPwwAMPcPrppwPwyU9+ksceeyz1i+qw4lxZBcN8XUHzseNaPjngfcCngY9sc8nNK0VkpYi8DHwY+AqAMeYV4B5gNfAI8AVjTE8Uwl0rm3zq2WmnnViyZAkAEyZMYN68eWzatAmAr3zlK1x55ZWh9vSBBx7gtNNOQ0TYf//9aWxsZPPmzXnTCw6Wl0NtjWZjJ4p8ivP+iRGRMAlGSeH3t1RWVkYtIWv69VBAHRA+lAP44cMHD0oY18o0Cj033XQTn/rUpwD4z3/+g4hw6KGHUlNTw4knnshFF13Ebrvtxmuvvcb69euprq7m/vvvp6urC4BNmzYxI7jUV3FxMeXl5dTV1Q37nHvnyuqVV6KWEELzseNaPsONMeZpQPp46WHLey4DLsuZqAxxrWyi0rN+/XpefPFF9ttvPx544AGmT5/OXnvtxahRW/+nSG9vAaqrq9m0aRM77bRTX4fMCc6Vl0NtjWZjJ4p8Cv8/8gwxGC86IBobG6OWkDX9eiigDggfygH88OGDByWMa2Wabz2XXXYZxcXFnHLKKUByCsbTTz/NHXfcwR//+Efuu+8+HnvsMSoqKrjhhhv41Kc+xfvf/35mzZpFUVF+R/o5V1a77Ra1hBCajx3X8lG24lrZRKGntbWV4447jmuuuYbi4mIuv/xyLr30UgASiUTe9dhwrrwcams0GztR5FP4/5GPMCZMmBC1hKzp10MBdUD4UA7ghw8fPChhXCvTfOq5+eabeeihh7jjjjtITh9P/pr2gQ98gClTprDjjjtyxBFHsHz5cgA+/vGP8+9//5tnnnmGuXPnsvvuuwMwffp0NmxIXs0vHo/T1NSUk185nCurDRsG3imPaD52XMtH2YprZZNvPd3d3Rx33HGccsopHHvssbz++uu8+eab7LXXXsyaNYu3336bJUuW8M4774TaW4CNGzcyfXp+r57qXHk51NZoNnaiyGdEdUCkvswVMu3t7VFLyJp+PRRQB4QP5QB++PDBgxLGtTLNl55HHnmEK6+8kgcffJCytMsRH3rooaxcuZL29naam5t58sknmT9/PgBbtmwBoKGhgZ///Od89rOfBeCoo47illtuAeDee+/lIx/5SE7+BjpXVjvsELWEEJqPHdfyUbbiWtnkU48xhrPOOot58+ZxwQUXALBo0SK2bNnC+vXrWb9+PdOnT2f58uVMnTqVo446iltvvRVjDM8++yzl5eV5nX4BDpaXQ22NZmMninxGxBoQuVh4KyrGjBkTtYSs6ddDqgMi7Yu3q/hQDuCHDx88KGFcK9Nc6DnppJN44oknqK2tpbq6mu9///tcccUVdHZ2cvDBBwPJhSh/8YtfUFFRwQUXXMB73vMeAI488kiOPPJIAM4//3xeeuklAL773e/2joA466yz+PSnP81uu+3G5MmTueuuu4bdAzhYVk1NUUsIofnYcS0fZSuulU0+9fzzn//ktttuY9GiRSxevBiAyy+/nCOOOKLP/Y844ggefvhhdtttN8rKyvjtb3+bN60pnCsvh9oazcZOFPmMiA6IFNLnOkCFRTwed+5EGiz9ekj1wBXACAgfygH88OGDByWMa2WaCz133nnndtvOOuusfvc/9dRTOfXUU2lra2PcuHHW4wCUlpbyu9/9LnuhA+BcWY0d69SXO83Hjmv5KFtxrWzyqefAAw8c8MfL1atX97bFIsL111+fD2n94lx5OdTWaDZ2oshnRHRAGPwZAeHDNJJ+PRTQFAwfygH88OGDByWMa2WaVz0DfJZUVUFNjf0YeRz151xZ9URyxcJ+0XzsuJaPshXXykb12HFOj0NtjWZjJ4p8RkQHRArXKuBQSL/sT6HSr4cC6oDwoRzADx8+eFDCuFamLukZFY9HLSGES9mA5jMQmo+SKa6VTV71ZPD/wqiKCmhosO+Ux85g58rLobZGs7ETRT5ulUiO8GkNiO7u7qglZE2/HgqoA8KHcgA/fPjgQQnjWpm6pKc7bfqFC7iUDWg+A6H5KJniWtk4p0fPJSsu5aPZ2Ikin5x3QIjIYSLymoisE5GL+3h9pog8LiIvisjLItL3Ci/DocWDNSBKS0ujlpA1/XpIdUAUgEcfygH88OGDByWMa2Xqkp7S+vqoJYRwKRvQfAZC81EyxbWycU6PnktWXMpHs7ETRT457YAQkSLgeuBwYD5wkojM32a3bwP3GGP2Bk4Efj7cOnxaA6KtrS1qCVnTr4dYDMaMAceGSvWFD+UAfvjwwYMSxrUydUlPW54v7TYQLmUDms9AaD5KprhWNs7p0XPJikv5aDZ2osgn1//p7QusM8a8YYzpAu4Cjt5mHwNMDB6XA28Pt4jUFAwf1oCYOHHiwDs5Tr8eYrGCuAQn+FEO4IcPHzwoYVwrU5f0TFy/PmoJIVzKBjSfgdB8lExxrWyc06PnkhWX8tFs7ESRT647IKYDG9Kebwy2pXMJcKqIbAQeBr6YKzE+TMFoGGjBmwKgXw/t7QWx/gP4UQ7ghw8fPChhXCtTl/Q07L571BJCuJQNaD4DofkomeJa2TinR88lKy7lo9nYiSIfF8a6nwTcbIypBo4AbhOR7XSJyDkiskxElm3ZsoWOjg7a29tpa2ujs7OT5uZm4vE4DQ0NGGOora0FoKampncKhsHQ0NBAPB6nubmZzs5O2traaG9vp6Ojg5aWFrq7u2lsbCSRSFBXV9d7jPT7+vp6enp6aGpqoquri9bWVmKxGLFYjNbWVrq6umhqaqKnp4f6YJ7Ptseoq6sjkUjQ2NhId3c3LS0tGXmqrKzsPUZtbS3GFJ6n8vLyPsuJWIye0aMLwtPYsWMzqnuul9PEiRMzrnuueqqsrBzy+TTcnpThobKyMmoJIVzSU7lmTdQSQriUDWg+A6H5KJniWtk4p0fPJSsu5aPZ2IkiH8nlFSJE5L3AJcaYQ4Pn3wAwxlyRts8rwGHGmA3B8zeA/Y0xW/o77tKlS82yZcsy1tHV08WYH47hso9cxjff/82hmXGEmpoaqqqqopaRFf16OPZYWLsWVq7Mv6hB4kM5gB8+XPIgIi8YY5ZGrSMfDLYdHgwulSnkWc8AUwVrFi2iaqA2Mo9XfnIpG9B8BmKk5KNtcfZoO2xnpJxLfVJg+Wg2dqJoh3M9AuJ5YI6I7CIio0kuMvngNvv8FzgIQETmAaXAsP6c6NNlOF36YzBU+vUQixXMFAwfygH88OGDByWMa2Xqkp4Bv7TkGZeyAc1nIDQfJVNcKxvn9Oi5ZMWlfDQbO1Hkk9MOCGNMHDgPeBRYQ/JqF6+IyKUiclSw21eBs0XkJeBO4AyTox4DH9aA8GGod78eCqgDwodyAD98+OBBCeNambqkp2bRoqglhHApG9B8BkLzUTLFtbJxTo+eS1ZcykezsRNFPjlfA8IY87AxZndjzGxjzGXBtu8aYx4MHq82xrzPGLOXMWaxMeYvw67Bo8twutaLNxR0BIQ7+ODDBw8DISI3icgWEVmVtu3HIvKqiLwsIveJyKS0174hIutE5DUROTRt+2HBtnUicnHa9l1E5N/B9ruDEWuR4VqZuqRHfzmxo/nY0XyUTHGtbJzTo+eSFZfy0WzseDcCwjV8uAxnahG+QqZfDwXUAeFDOYAfPnzwkAE3A4dts+2vwEJjzJ7Af4BvAIjIfJLT3RYE7/m5iBSJSBFwPXA4MB84KdgX4H+Bq40xuwENwFm5tWPHtTJ1SU/93LlRSwjhUjag+QyE5qNkimtl45wePZesuJSPZmMninxGRAeET2tAlJeXRy0ha/r1EItBWVl+xQwRH8oB/PDhg4eBMMb8A6jfZttfgmluAM8C1cHjo4G7jDGdxpg3gXXAvsFtnTHmDWNMF3AXcLQke2Y/AtwbvP8W4Jhc+hkI18rUJT3lb7wRtYQQLmUDms9AaD5KprhWNs7p0XPJikv5aDZ2oshnRHRApPBhDYjW1taoJWRNvx7a2wtmBIQP5QB++PDBwzBwJvDn4PF0YEPaaxuDbf1trwQa0zozUtsjw7UydUlP6/RIi2Y7XMoGNJ+B0HyUTHGtbJzTo+eSFZfy0WzsRJHPiOiA8GkNiLEF8g+6jX49FNAUDB/KAfzw4YOHbBCRbwFx4I48fNY5IrJMRJZt2bKFjo4O2tvbaWtro7Ozk+bmZuLxOA0NDRhjqK2tBbYucFRbW4sxhoaGBuLxOM3NzXR2dtLW1kZ7ezsdHR20tLRQXFxMY2MjiUSCurq60DFS9/X19fT09NDU1ERXVxetra3EYjFisRitra10dXXR1NRET09P7/DCbY9RV1dHIpGgsbGR7u5uWlpa+vRUUlKStafu7u7MPJWU0DRrFl3jx9M6bRqxykpilZW0TptG1/jxdJeV0VNS0juEM7WYVeq+bt68jDwNRzl1d3fT1dWVv3KaPZvusjJaqqvpqKigvaqKtqlT6Swvp3nmTOKlpXROnIgRoXbhwuQxgvvahQsxIjTMmTM85ZShp46Ojqzq3qDKaeZMOsvLaZs6lfaqKjoqKmiprqa7rIzG2bNJFBURmzy5z3pTP3fu1rqX4/Mp3VN7e3vOziclO1z72+qcnuB8dAXNp380GztR5COFOD1hsNc8bu9uZ9zl4/jfj/4vF73vohwqyz2tra2MHz8+ahlZ0a+HsWPhi1+EK6/Mv6hB4kM5gB8+XPKQy2vPi8gs4CFjzMK0bWcAnwMOMsa0B9u+AWCMuSJ4/ihwSfCWS4wxh6bvB/yI5KWPpxpj4iLy3vT9+iNX154Ht8oU8qxngLWKWqdNY/zbb9uPkce/6y5lA5rPQIyUfHLZFrtGrtpibYftjJRzqU8KLB/Nxk4U7fDIGAFRgJ0s/VFUVBS1hKzp04Mx0NFRMCMgfCgH8MOHDx6GgogcBlwEHJXqfAh4EDhRRMaIyC7AHOA54HlgTnDFi9EkF6p8MLjs8ePAJ4P3nw48kC8ffeFambqkp6izM2oJIVzKBjSfgdB8lExxrWyc06PnkhWX8tFs7ESRz8jogAimYPiwBoS3BMNUC6UDQlHyiYjcCTwDzBWRjSJyFvAzYALwVxFZISK/ADDGvALcA6wGHgG+YIzpCdZ4OA94FFgD3BPsC/B14AIRWUdyTYgb82hPURRFURRFGSEURy0gn/hwGc6enp6oJWRNnx5iseR9gXRA+FAO4IcPHzwMhDHmpD4299tJYIy5DLisj+0PAw/3sf0NklfJcALXytQlPT1jxkQtIYRL2YDmMxCaj5IprpWNc3r0XLLiUj6ajZ0o8hkZIyA8moIxevToqCVkTZ8eCqwDwodyAD98+OBBCeNambqkZ3Rzc9QSQriUDWg+A6H5KJniWtk4p0fPJSsu5aPZ2IkinxHRAZHChykYsdQ/6gVMnx5S28rK8itmiPhQDuCHDx88KGFcK1OX9MSmTIlaQgiXsgHNZyA0HyVTXCsb5/TouWTFpXw0GztR5DMiOiB8ugynSysSD5U+PQSX4iqUERA+lAP44cMHD0oY18rUJT3jN22KWkIIl7IBzWcgNB8lU1wrG+f06LlkxaV8NBs7UeQzIjogUviwBkRTU1PUErKmTw8FNgXDh3IAP3z44EEJ41qZuqSnadddo5YQwqVsQPMZCM1HyRTXysY5PXouWXEpH83GThT5jIgOCJ/WgJg8eXLUErKmTw8F1gHhQzmAHz588KCEca1MXdIz+bXXopYQwqVsQPMZCM1HyRTXysY5PXouWXEpH83GThT5jIgOiBQ+rAFRU1MTtYSs6dNDgXVA+FAO4IcPHzwoYVwrU5f01CxaFLWEEC5lA5rPQGg+Sqa4VjbO6dFzyYpL+Wg2dqLIZ0R0QPi0BkRVVVXUErKmTw8F1gHhQzmAHz588KCEca1MXdJTtXJl1BJCuJQNaD4DofkomeJa2TinR88lKy7lo9nYiSKfEdEBkcKHNSBc68UbCjoCwh188OGDByWMa2Xqkh795cSO5mNH81EyxbWycU6PnktWXMpHs7GjIyByhE9rQLjWizcUrCMgCuQynD6UA/jhwwcPShjXytQlPfrLiR3Nx47mo2SKa2XjnB49l6y4lI9mY0dHQOQYH9aAqKuri1pC1vTpocAuw+lDOYAfPnzwoIRxrUxd0lM3b17UEkK4lA1oPgOh+SiZ4lrZOKdHzyUrLuWj2diJIp8R0QHh0xoQFRUVUUvImj49FNgUDB/KAfzw4YMHHznzzDPZYYcdWLhwYe+2+vp6Dj74YObMmcPBBx9MQ0MDkLwE1Mc//nH22msvFixYwP333w/AihUreO9738uCBQvYc889ufvuu3uPZYzhW9/6Frvvvjvz5s3juuuuy5kXl+pYxX/+E7WEEC5lA5rPQGg+SooNGzbw4Q9/mPnz57NgwQKuvfZaYGs7vf/++4fa6SeeeILy8nIWL17M4sWLufTSS/Oq17W6oueSHZfy0WzsRJHPiOiASOHDGhDNzc1RS8iaPj2kOiBKS/MrZoj4UA7ghw8fPPjIGWecwSOPPBLa9qMf/YiDDjqItWvXctBBB/GjH/0IgOuvv5758+fz0ksv8cQTT/C1r32Nrq4uysrKuPXWW3nllVd45JFH+PKXv0xjYyMAN998Mxs2bODVV19lzZo1nHjiiTnz4lIda541K2oJIVzKBjSfgdB8lBTFxcX85Cc/YfXq1Tz77LNcf/31rF69uredfv7550PtNMD73/9+VqxYwYoVK/jud7+bV72u1RU9l+y4lI9mYyeKfEZEB4RPa0CMGzcuaglZ06eHWAzGjIFRhVElfSgH8MOHDx585AMf+MB215Z+4IEHOP300wE4/fTTe0c6iAgtLS0YY2htbaWyspLi4mJ233135syZA8C0adPYYYcdehdLuuGGG/jud7/LqKDN2GGHHXLmxaU6Nm7z5qglhHApG9B8BkLzUVLstNNOLFmyBIAJEyYwb948Nm3a1NtOjxs3LtROR41rdUXPJTsu5aPZ2Ikin8L4by9LUlMwfFgDoqOjI2oJWdOnh1isYKZfgB/lAH748MHDSOHdd99lp512AmDq1Km8++67AJx33nmsWbOGadOmsWjRIq644orejoUUzz33HF1dXcyePRuA119/nbvvvpulS5dy+OGHs3bt2pzpdqmOdWzTqRM1LmUDms9AaD5KX6xfv54XX3yR/fbbr7ed7ujoCLXTAM888wx77bUXhx9+OK+88kpeNbpWV/RcsuNSPpqNnSjyGREdECl8mIJRUlIStYSs6dNDgXVA+FAO4IcPHzyMRESkt01+9NFHWbx4MW+//TYrVqzgwgsvDA0J3Lx5M5/+9Kf57W9/29sx0dnZSWlpKcuWLePss8/mzDPPzJlWl+pYSVtb1BJCuJQNaD4Dofko29La2spxxx3HNddcw8SJE3u3l5SUhNrpJUuW8NZbb/HSSy/xxS9+kWOOOSavOl2rK3ou2XEpH83GThT5jIgOCJ+mYCQSiaglZE2fHgqsA8KHcgA/fPjgYaSw4447sjkYerh58+beaRO//e1vOfbYYxERdtttN3beeWdeffVVIDk38cgjj+Syyy5j//337z1WdXU1xx57LACf+MQnePnll3Om26U6ligujlpCCJeyAc1nIDQfJZ3u7m6OO+44TjnllN72NNVOJxKJUDs9ceJExo8fD8ARRxxBd3c3tbW1edPqWl3Rc8mOS/loNnaiyGdEdECk8GEKhg+dKX16iMWgrCz/YoaID+UAfvjwwcNI4aijjuKWW24B4JZbbuHoo48GYObMmTz22GNAcprG2rVr2XXXXenq6uITn/gEp512Gp/85CdDxzrmmGN4/PHHAXjyySfZfffdc6bbpTpmioqilhDCpWxA8xkIzUdJYYzhrLPOYt68eVxwwQW921PttDEm1E6/8847veX13HPPkUgkqKyszKtel9BzyY5L+Wg2dqLIx60umBzh02U4ix3rNRsKfXpoby+oERA+lAP44cMHDz5y0kkn8cQTT1BbW0t1dTXf//73ufjiiznhhBO48cYb2XnnnbnnnnsA+M53vsMZZ5zBokWLMMZw2WWXMWXKFG6//Xb+8Y9/UFdXx8033wwkr36xePFiLr74Yk455RSuvvpqxo8fz29+85uceXGpjhWnrhjkCC5lA5rPQGg+Sop//vOf3HbbbSxatIjFixcDcPnll/e207/5zW+YNWtWbzt97733csMNN1BcXMzYsWO566678jq12bW6oueSHZfy0WzsRJGPWyWSY3xYA6Kzs5MxY8ZELSMr+vRQYFMwfCgH8MOHDx585M477+xze2qkQzrTpk3jL3/5S+/z1PoPp556Kqeeemqfx5k0aRJ/+tOfhkHpwLhUxzrLyxnT1BS1jF5cygY0n4HQfJQUBx54YL+/fD722GM0NzeH1oQ477zzOO+88/Ilbztcqyt6LtlxKR/Nxk4U+YyIDgjXht5kQ1kBTVPojz49xGJQUZF/MUPEh3IAP3z44EEJ41qZuqSnbMuWqCWEcCkb0HwGQvNRAMjgB7my0lIYaHX8PH6/dq2u6Llkx6V8NBs7UeSja0AUGC0tLVFLyJo+PRTYCAgfygH88OGDhxGFyIC3lvnzB94vj7hUx1pmzIhaQgiXsgHNZyA0HyVTtK7Y0XzsuJSPZmMninxGRAeET2tATJo0KWoJWdOnhwLrgPChHMAPHz54UMJMWrcuagkhXKpjmo0dzceO5pNfRGSGiDwuIqtF5BUROT/YPllE/ioia4P7imC7iMh1IrJORF4WkSVRade6YkfzseNSPpqNnSjyGREdECl8WAOirq4uaglZ06eHAuuA8KEcwA8fPnhQwtQtWBC1hBAu1THNxo7mY0fzyTtx4KvGmPnA/sAXRGQ+cDHwmDFmDvBY8BzgcGBOcDsHuCH/kpNoXbGj+dhxKR/Nxk4U+YyIDgif1oCYMmVK1BKypk8PBdYB4UM5gB8+fPCghJmyalXUEkK4VMc0Gzuajx3NJ78YYzYbY5YHj1uANcB04GjglmC3W4BjgsdHA7eaJM8Ck0Rkp/yqTqJ1xY7mY8elfDQbO1HkMyI6IFL4sAZETU1N1BKypk8PsRg4tkiMDR/KAfzw4YMHJUzNwoVRSwjhUh3TbOxoPnY0n+gQkVnA3sC/gR2NMZuDl94BdgweTwc2pL1tY7At72hdsaP52HEpH83GThT5jIgOCJ/WgKiqqopaQtZs58GYghsB4UM5gB8+fPCghKly7NcBl+qYZmNH87Gj+USDiIwHfg982RjTnP6aSQ7THdQXVRE5R0SWiciyLVu20NHRQXt7O21tbXR2dtLc3Ew8HqehoQFjDLW1tcDWfzRqFy7EiNAwZw7x0lKaZ86ks7yctqlTaa+qoqOigtLGRrrLymicPZtEURF18+Ylj7FoUei+vr6enp4empqa6OrqorW1lVgsRiwWo7W1la6uLpqamujp6aG+vj6kI3VfV1dHIpGgsbGR7u5uWlpatvM0ZswYu6faWowxNDQ0EI/HaW5uprOzk7a2Ntrb2+no6KClpYXu7m4aGxtJJBK9Q8+31VM/dy49JSU0zZpF1/jxtE6bRqyyklhlJa3TptE1fjyjW1vpKSmhfu7cPnOpmzdvQE8DltMgPJWUlNg9DWc5zZ5Nd1kZLdXVdFRU0F5VRdvUqXSWl9M8cybx0lKKOzsxItQG/2yn/ukO1b1syylDT5MnT86q7g2qnPo5n1qqq3vPp8o1a/o/n1J1L8fnU7qnKVOm5OR8siGFOD1h6dKlZtmyZRnvv6l5E9VXV/PLj/2Sc/Y5J4fKck9tba1zQ4kGy3YeUqMfrrgCLr64/zc6hA/lAH74cMmDiLxgjFkatY58MNh2uJcM1uKpXbhw4CGKefzbldc6NkA+mo0dzcfOSMnHpbZYREqAh4BHjTH/F2x7DfiQMWZzMMXiCWPMXBH5ZfD4zm336+/4Q2qLta7Y0XzsFFg+mo2dKNrhETECIoUPUzAqKyujlpA123mIxZL3BTQCwodyAD98+OBBCVP5yitRSwjhUh3TbOxoPnY0n/wiydXPbwTWpDofAh4ETg8enw48kLb9tOBqGPsDTbbOh1yidcWO5mPHpXw0GztR5DMiOiB8moLR2NgYtYSs2c5DAXZA+FAO4IcPHzwoYRp32y1qCSFcqmOajR3Nx47mk3feB3wa+IiIrAhuRwA/Ag4WkbXAR4PnAA8DbwDrgF8Dn49AM6B1ZSA0Hzsu5aPZ2Ikin+K8f2KE+HAZzgkTJkQtIWu281CAHRA+lAP44cMHD0qYCRs2DLxTHnGpjmk2djQfO5pPfjHGPA39Dr89qI/9DfCFnIrKEK0rdjQfOy7lo9nYiSKfkTECogDXueiP9vb2qCVkzXYeCrADwodyAD98+OBBCdO+ww5RSwjhUh3TbOxoPnY0HyVTtK7Y0XzsuJSPZmMninxGRAdECh/WgBgzZkzUErJmOw8F2AHhQzmAHz588KCEGdPUFLWEEC7VMc3GjuZjR/NRMkXrih3Nx45L+Wg2dqLIZ0R0QPi0BkQ8Ho9aQtZs5yHV81ZWln8xQ8SHcgA/fPjgQQkTd6wz0qU6ptnY0XzsaD5KpmhdsaP52HEpH83GThT5jIgOiBQ+rAHhpYcCHAHhQzmAHz588DAQInKTiGwRkVVp2yaLyF9FZG1wXxFsFxG5TkTWicjLIrIk7T2nB/uvFZHT07bvIyIrg/dcJxGHKj09UX78drhUxzQbO5qPHc1HyRStK3Y0Hzsu5aPZ2IkinxHRAeHTGhCjRhV+kW3noQA7IHwoB/DDhw8eMuBm4LBttl0MPGaMmQM8FjwHOByYE9zOAW6AZIcF8D1gP2Bf4HupTotgn7PT3rftZ+WVUY79WuFSHdNs7Gg+djQfJVO0rtjRfOy4lI9mYyeKfNwqkRzjwxoQ3d3dUUvImu08FGAHhA/lAH748MHDQBhj/gHUb7P5aOCW4PEtwDFp2281SZ4FJonITsChwF+NMfXGmAbgr8BhwWsTjTHPBiuw35p2rEjoHjcuyo/fDpfqmGZjR/Oxo/komaJ1xY7mY8elfDQbO1HkMyI6IHxaA6K0tDRqCVmznYcC7IDwoRzADx8+eBgiOxpjNgeP3wF2DB5PB9Kv8bQx2GbbvrGP7ZFRWr9tX0u0uFTHNBs7mo8dzUfJFK0rdjQfOy7lo9nYiSKfEdEBkcK1OUBDoa2tLWoJWbOdhwLsgPChHMAPHz54yJZg5ELOe1pF5BwRWSYiy7Zs2UJHRwft7e20tbXR2dlJc3Mz8XichoYGjDHU1tYCUFNTA0BtbS1GhIY5c4iXltI8cyad5eW0TZ1Ke1UVHRUVtFRX07TLLjTOnk2iqIi6efOSx1i0KHRfX19PT08PTU1NdHV10draSiwWIxaL0draSldXF01NTfT09FAf/LFP6Ujd19XVkUgkaGxspLu7m5aWlj49NTc32z0ZQ0NDA/F4nObmZjo7O2lra6O9vZ2Ojg5aWlro7u6msbGRRCJBXV1dn3rq6+vpKSmhadYsusaPp3XaNGKVlcQqK2mdNo2u8eN5d8kSekpKqJ87t89c6ubNy8jTgOWUoad33nlnYE/DVU6zZ9NdVkZLdTUdFRW0V1XRNnUqneXlNM+cSby0lM377osRoXbhwuQxgvvahQu31r3hKKcMPb399ttZ1b1BlVM/51N3WVnv+fT2AQf0fT7Nnbu17uX4fEr3tGnTppydT0p2tO20U9QSQrj2t17zseNSPpqNnSjykUJcH2Hp0qVm2bJlGe//ZsOb7Hrdrvz26N9yxuIzcicsDyQSCefmMg2W7TxceSV8/evQ2gqODUvqDx/KAfzw4ZIHEXnBGLM0R8eeBTxkjFkYPH8N+JAxZnMwjeIJY8xcEfll8PjO9P1SN2PM54LtvwSeCG6PG2P2CLaflL5ffwy2HU4zMuAuiaIiRg20SFMe/3bltY4NkI9mY0fzsTNS8sllW+waQ2qLta7Y0XzsFFg+mo2dKNphN7615wkf1oBoaGiIWkLWbOehAEdA+FAO4IcPHzwMkQeB1JUsTgceSNt+WnA1jP2BpmCqxqPAISJSESw+eQjwaPBas4jsH1z94rS0Y0VCw+67R/nx2+FSHdNs7Gg+djQfJVO0rtjRfOy4lI9mYyeKfIrz/okR4NMaEJWVlVFLyJrtPLS3w5gx4Miv2JngQzmAHz588DAQInInyREMU0RkI8mrWfwIuEdEzgLeAk4Idn8YOAJYB7QDnwEwxtSLyA+A54P9LjXGpCYifp7klTbGAn8ObpFRuWZNlB+/HS7VMc3GjuZjR/NRMkXrih3Nx45L+Wg2dqLIp3D+48uC1DQTH9aA8GFu43YeYrGCGv0AfpQD+OHDBw8DYYw5yRizkzGmxBhTbYy50RhTZ4w5yBgzxxjz0VRnQnD1iy8YY2YbYxYZY5alHecmY8xuwe23aduXGWMWBu85z0Q8Ny81L90VXKpjmo0dzceO5qNkitYVO5qPHZfy0WzsRJHPiOiASOHDFIyqqqqoJWTNdh4KsAPCh3IAP3z44EEJU7VyZdQSQrhUxzQbO5qPHc1HyRStK3Y0Hzsu5aPZ2IkinxHRAeHTFAzXevGGgo6AcAcffPjgQQmjvw70j2ZjR/Oxo/komaJ1xY7mY8elfDQbOzoCIsf4MAXDtV68oaAjINzBBx8+eFDC6K8D/aPZ2NF87Gg+SqZoXbGj+dhxKR/Nxo6OgMgRhXip0f5IXX+7kNnOQwF2QPhQDuCHDx88KGHq586NWkIIl+qYZmNH87Gj+SiZonXFjuZjx6V8NBs7UeSTcQeEiIwVEbcSGyQ+rAFRXl4etYSs2c5DAXZA+FAO4IcPHzwoYcrfeCNqCSFcqmOajR3Nx47mo2SK1hU7mo8dl/LRbOxEkU9GHRAi8nFgBfBI8HyxiDyYQ13Dik9rQLS2tkYtIWu28xCLQVlZNGKGiA/lAH748MGDEqZ1+vSoJYRwqY5pNnY0Hzuaj5IpWlfsaD52XMpHs7ETRT6ZjoC4BNgXaAQwxqwAdsmJohziwxoQYwtspEBfbOehvb3gRkD4UA7ghw8fPChhxtbWRi0hhEt1TLOxo/nY0XyUTNG6YkfzseNSPpqNnSjyybQDotsY07TNtoyGFYjIYSLymoisE5GL+9nnBBFZLSKviMj/y1BTxvi0BkRXV1fUErJmOw8FOAXDh3IAP3z44EEJ0zVxYtQSQrhUxzQbO5qPHc1HyRStK3Y0Hzsu5aPZ2Ikin+IM93tFRE4GikRkDvAl4F8DvUlEioDrgYOBjcDzIvKgMWZ12j5zgG8A7zPGNIjIDoM1kSk+rAFRVFQUtYSs2c5DAXZA+FAO4IcPHzwoYYo6O6OWEMKlOqbZ2NF87Gg+SqZoXbGj+dhxKR/Nxk4U+WQ6AuKLwAKgE/h/QBPw5Qzety+wzhjzhjGmC7gLOHqbfc4GrjfGNAAYY7ZkqCljfFoDwksKsANCURRFURRFURRFGRwZdUAYY9qNMd8yxrwnuH3bGNORwVunAxvSnm8MtqWzO7C7iPxTRJ4VkcP6OpCInCMiy0Rk2ZYtW+jo6KC9vZ22tjY6Oztpbm4mHo/T0NCAMYbaYH5NTU1N6DgNDQ3E43Gam5vp7Oykra2N9vZ2Ojo6aGlpobu7m8bGRhKJBHV1daFjpO7r6+vp6emhqamJrq4uWltbicVixGIxWltb6erqoqmpiZ6ent5Lm2x7jLq6OhKJBI2NjXR3d9PS0pKRp56ent5j1NbWYowpOE+dnZ3hcorFaA+myRSKp9bW1ozrnsueOjs7M657rnrq6ekZ8vk03J6U4aFnzJioJYTo6emJWkIvmo0dzceO5qNkitYVO5qPHZfy0WzsRJGPZLI+goj8FTjeGNMYPK8A7jLGHDrA+z4JHGaM+Wzw/NPAfsaY89L2eQjoBk4AqoF/AItSn9UXS5cuNcuWLRtQd4o1NWuY//P53HncnZy48MSM3+ciXV1djB49OmoZWRHyYAyMGgXf+Q5cemm0wgaBD+UAfvhwyYOIvGCMWRq1jnww2Ha4lwwWA+4aP57RA63KnMe1ffJaxwbIR7Oxo/nYGSn5aFs8AFpX7Gg+dgosH83GThTtcKZTMKakdwgE0yUyWathEzAj7Xl1sC2djcCDxphuY8ybwH+AORnqyojUFAwf1oCIxWJRS8iakIfUPKgCm4LhQzmAHz588KCEiU2ZErWEEC7VMc3GjuZjR/NRMkXrih3Nx45L+Wg2dqLIJ9MOiISIzEw9EZGdyewqGM8Dc0RkFxEZDZwIPLjNPvcDHwqOO4XklIw3MtQ14hg/fnzUErIm5KG9PXlfVhaNmCHiQzmAHz588KCEGb9p237qaHGpjmk2djQfO5qPkilaV+xoPnZcykezsRNFPpl2QHwLeFpEbhOR20lOk/jGQG8yxsSB84BHgTXAPcaYV0TkUhE5KtjtUaBORFYDjwMXGmPqBmtkAB0ASAbDYlynqWnbq6EWHiEPqV63AhsB4UM5gB8+fPCghGnaddeoJYRwqY5pNnY0Hzuaj5IpWlfsaD52XMpHs7ETRT4ZXYbTGPOIiCwB9g82fdkYU5vhex8GHt5m23fTHhvgguCWU3yYgjF58uSoJWRNyEOBdkD4UA7ghw8fPChhJr/2WtQSQrhUxzQbO5qPHc1HyRStK3Y0Hzsu5aPZ2IkiH+sICBHZI7hfAswE3g5uM4NtBYFPl+H0YbX9kIcC7YDwoRzADx8+eFDC1CxaFLWEEC7VMc3GjuZjR/NRMkXrih3Nx45L+Wg2dqLIZ6AREF8FzgZ+0sdrBvjIsCvKIT5MwaiqqopaQtaEPBRoB4QP5QB++PDBgxKmauXKqCWEcKmOaTZ2NB87mo+SKVpX7Gg+dlzKR7OxE0U+1hEQxpizg/sP93ErmM6HTC41Wii41os3FHQEhDv44MMHD0oY/XWgfzQbO5qPHc1HyRStK3Y0Hzsu5aPZ2HFuBISIHGt73Rjzh+GVk1t8WAPCtV68oaAjINzBBx8+eFDC6K8D/aPZ2NF87Gg+SqZoXbGj+dhxKR/Nxo5zIyCAjwe3s4AbgVOC22+AM3MrbfjwaQ2IurphvUBIJIQ8pDogCuwynD6UA/jhwwcPSpi6efOilhDCpTqm2djRfOxoPkqmaF2xo/nYcSkfzcZOFPlYR0AYYz4DICJ/AeYbYzYHz3cCbs65umHGhzUgKioqopaQNSEP7e3J+wIbAeFDOYAfPnzwoISp+M9/opYQwqU6ptnY0XzsaD5KpmhdsaP52HEpH83GThT5DDQCIsWMVOdDwLskr4pREPi0BkRzc3PUErIm5KFAp2D4UA7ghw8fPChhmmfNilpCCJfqmGZjR/Oxo/komaJ1xY7mY8elfDQbO1HkM9BVMFI8JiKPAncGzz8F/C03knKHD2tAjBs3LmoJWRPyUKAdED6UA/jhwwcPSphxmzcPvFMecamOaTZ2NB87mo+SKVpX7Gg+dlzKR7OxE0U+GY2AMMacB/wC2Cu4/coY88VcChtOfFoDoqOjI2oJWRPyUKAdED6UA/jhwwcPSpiOyZOjlhDCpTqm2djRfOxoPkqmaF2xo/nYcSkfzcZOFPlkOgICY8x9wH19vSYizxhj3jtsqnKED2tAlJSURC0ha0IeCrQDwodyAD98+OBBCVPS1ha1hBAu1THNxo7mY0fzUTJF64odzceOS/loNnaiyCfTNSAGonSYjpMTfFoDIpFIRC0ha0IeYjEYPRpGDVdVzA8+lAP44cMHD0qYRHHGfeN5waU6ptnY0XzsaD5KpmhdsaP52HEpH83GThT5DNd/fU7/h5+aguHDGhA+dKaEPMRiBTf6AfwoB/DDhw8elDCmqChqCSFcqmOajR3Nx47mMzRE5EoRmSgiJSLymIjUiMipUevKJVpX7Gg+dlzKR7OxE0U+hfWzc5b4MAWj2LFes6EQ8hCLQVlZdGKGiA/lAH748MGDEqY4NTXLEVyqY5qNHc3HjuYzZA4xxjQDHwPWA7sBF0aqKMdoXbGj+dhxKR/Nxk4U+QxXB4TT/9m71vOVDZ2dnVFLyJqQh/b2ghwB4UM5gB8+fPCghOksL49aQgiX6phmY0fzsaP5DJnUN/Qjgd8ZY5qiFJMPtK7Y0XzsuJSPZmMninyGq8vj08N0nJziwxSMsgIcLbAtIQ8FOgXDh3IAP3z44EEJU7ZlS9QSQrhUxzQbO5qPHc1nyDwkIq8CMeBcEakC3Fpaf5jRumJH87HjUj6ajZ0o8sloBISIHCsia0WkSUSaRaRFRJpTrxtjVuVOYvb4dBnOlpaWqCVkTchDgXZA+FAO4IcPHzwoYVpmzIhaQgiX6phmY0fzsaP5DA1jzMXAAcBSY0w30AYcHa2q3KJ1xY7mY8elfDQbO1Hkk+kIiCuBjxtj1uRSTK7xYQ2ISZMmRS0ha0IeCrQDwodyAD98+OBBCTNp3bqoJYRwqY5pNnY0HzuaT1bsAcwSkfTvzrdGJSbXaF2xo/nYcSkfzcZOFPlkugbEu4Xc+eDTGhB1dXVRS8iakIcC7YDwoRzADx+F5kFE3ici44LHp4rI/4nIzlkc7ysi8oqIrBKRO0WkVER2EZF/i8g6EblbREYH+44Jnq8LXp+VdpxvBNtfE5FDszaaBXULFkT58dvhUh3TbOxoPnY0n6EhIrcBVwEHAu8JbksjFZVjtK7Y0XzsuJSPZmMninwyHQGxTETuBu4HeleqMMb8IReicoUPa0BMmTIlaglZE/IQi8HUqdGJGSI+lAP44aMAPdwA7CUiewFfBX5D8le0Dw72QCIyHfgSMN8YExORe4ATgSOAq40xd4nIL4Czgs89C2gwxuwmIicC/wt8SkTmB+9bAEwD/iYiuxtjerI1OxSmrHJrVp9LdUyzsaP52NF8hsxSku2sP79oDYDWFTuajx2X8tFs7ESRT6YjICYC7cAhwMeD28dyJWq48WkNiJqamqglZE3IQ4GOgPChHMAPHwXoIR58iT0a+Jkx5npgQhbHKwbGBsOCy4DNwEeAe4PXbwGOCR4fHTwneP0gSc5NOxq4yxjTaYx5E1gH7JuFpqyoWbgwqo/uE5fqmGZjR/Oxo/kMmVXAoH8tEZGbRGSLiKxK23aJiGwSkRXB7Yi015wZiaZ1xY7mY8elfDQbO1Hkk9EICGPMZ3ItJB/4sAZEVVVV1BKyJuQhFgPHVqfNBB/KAfzwUYAeWkTkG8CpwAdEZBRQMpQDGWM2ichVwH9Jrs7+F+AFoNEYEw922whMDx5PBzYE742LSBNQGWx/Nu3Q6e/JO1WO/TrgUh3TbOxoPnY0n8EhIn8EDMlO4tUi8hzhkcBHDXCIm4Gfsf1aEVcbY67a5rOcGommdcWO5mPHpXw0GztR5JPpVTBKReQLIvLzoDf3JhG5KdfihgufRszV1tZGLSFrQh7a2wtyBIQP5QB++ChAD58i+QX2LGPMO0A18OOhHEhEKkiOXtiF5BfWccBhw6Szr887R0SWiciyLVu20NHRQXt7O21tbXR2dtLc3Ew8HqehoQFjTG/ZpHrXa2trMSI0zJlDvLSU5pkz6Swvp23qVNqrquioqKClupp39tmHxtmzSRQVUTdvXvIYixaF7uvr6+np6aGpqYmuri5aW1uJxWLEYjFaW1vp6uqiqamJnp4e6uvrQzpS93V1dSQSCRobG+nu7qalpaVPT++++67dkzE0NDQQj8dpbm6ms7OTtrY22tvb6ejooKWlhe7ubhobG0kkEr3zLbfVU19fT09JCU2zZtE1fjyt06YRq6wkVllJ67RpdI0fz1sf/Sg9JSXUz53bZy518+Zl5GnAcsrQ0/r16wf2NFzlNHs23WVltFRX01FRQXtVFW1Tp9JZXk7zzJnES0t589BDMSLUBr8wpX5pql24cGvdG45yytDTG2+8kVXdG1Q59XM+dZeV9Z5Pbxx5ZN/n09y5W+tejs+ndE+vv/56zs6nYeIq4CfAJSRHkl0ePE/drBhj/gHUZ/hZTo1Eq3XsV1rX/tZrPnZcykezsRNJPsaYAW/A74AfAK8Dp5P8le3aTN6bi9s+++xjBsOzG541XIJ5+D8PD+p9LpJIJKKWkDUhD2PHGvO1r0UnZoj4UA7G+OHDJQ/AMjNwe7oLMDbt+Vhg1kDv6+dYxwM3pj0/jeRaD7VAcbDtvcCjweNHgfcGj4uD/QT4BvCNtOP07tffbbDtcFpIA94SIgPvl0fyWsc0m/7RumNH8+klk7Z4MLeg3S5Ne55xuw3MAlalPb8EWA+8DNwEVATbfwacmrbfjcAn+znmOcAyYNmMGTNMLBYzbW1tprW11XR0dJimpibT3d1t6uvrTSKRMDU1NcYYY7Zs2WKMMaZm4UKTEDH1c+aY7tJS0zRzpukoLzetU6eatqoqE6uoME0zZpiusjLTMHu26SkqMrXz5hkDZsuiRVvvjTF1dXUmHo+bxsZG09nZaVpaWkx7e7tpb283LS0tprOz0zQ2Npp4PG7q6upCOlL3tbW1pqenxzQ0NJiuri7T3Ny8nafGxka7p5oak0gkTH19venu7jZNTU2mo6PDtLa2mra2NhOLxUxzc7Pp6uoyDQ0Npqenx9TW1vapp27uXBMvKTGNs2aZzvHjTcu0aaa9stK0V1aalmnTTOf48aZhl11MvKTE1M2du30uYGrnzRvQ04DlNAhP9fX1dk/DWU6zZ5uusjLTXF1tYhUVpq2qyrROnWo6ystN08yZpru01NTtvrtJiJiahQuTuQT3obqXbTll6Km7uzurujeocurnfGquru49n+LFxX2fT7C17uX4fEr31NPTk5PzydYOZ9rwvhjcvxzclwDPZvLeXNwG+8X3mQ3PeNMBUV9fH7WErOn1kEgkq+B3vhOtoCHgQzkY44cPlzxk2AGxDBid9nw08PxA7+vnWPsBr5Bc+0FIru/wxaDT+MRgn18Anw8efwH4RfD4ROCe4PEC4CVgTPBF+w2gyPbZueyAqJ8zZ+D98khe65hm0z9ad+xoPr3koANiyO12Hx0QOwJFJEchXwbcFGzPuAMi/Taktljrih3Nx06B5aPZ2ImiHc70KhjdwX2jiCwE3gF2yPC9zuDDGhATJmSzVp0b9HroDKZRFuAUDB/KAfzwUYAeio0xXaknxpiu1GUyB4sx5t8ici+wHIgDLwK/Av4E3CUiPwy23Ri85UbgNhFZR3JY8InBcV4JrqCxOjjOF0xE844BJmzYENVH94lLdUyzsaP52NF8hsxwttvvph6LyK+Bh4Knm4AZabtWB9siQeuKHc3Hjkv5aDZ2osgn06tg/CqYa/wd4EGSX1KvzJmqYSbZCeMH7e3tUUvIml4PsVjyvgA7IHwoB/DDRwF6qBGR3oXLRORoklMhhoQx5nvGmD2MMQuNMZ82yfnDbxhj9jXG7GaMOd4Y0xns2xE83y14/Y2041xmjJltjJlrjPlzVg6zpH0Ht/q3Xapjmo0dzceO5jNkhq3dFpGd0p5+guQVNiD5/fpEERkjIrsAc4Dnhqg3a7Su2NF87LiUj2ZjJ4p8Mr0Kxm+Ch08Cu+ZOTm4wwWU4hcIfATFmzJioJWRNr4cC7oDwoRzADx8F6OF/gDtE5HrAkLzixGnRSnKLMU1NUUsI4VId02zsaD52NJ8hk95uQ/JqQp8e6E0icifwIWCKiGwEvgd8SEQWk2z/1wOfA/dGomldsaP52HEpH83GThT5ZNQBISI7klz5d5ox5vDgUkHvNcbcOMBbncKHKRjxeNy5E2mw9HpIdUAU4GU4fSgH8MNHoXkwxrwO7C8i44PnrRFLco742LFO/YF2qY5pNnY0Hzuaz9AYarttjDmpj839fnc2xlxGcl2IyNG6YkfzseNSPpqNnSjyyXQKxs0kV0WfFjz/D/DlHOjJCT5NwfChE6XXQ2rITwGOgPChHMAPH4XmQUR2FJEbgd8ZY1pFZL6InBW1LpeQnsh+9OsTl+qYZmNH87Gj+QwNESkXkf8DngCeEJGfiEh5xLJyitYVO5qPHZfy0WzsRJFPph0QU4wx9wAJAGNMHHArvQzwYQrGqFGZFpm79Hoo4CkYPpQD+OGjAD3cTAF36OaDUfF41BJCuFTHNBs7mo8dzWfI3AS0ACcEt2bgt5EqyjFaV+xoPnZcykezsRNFPpl+YpuIVJKcr4aI7A+4M3ZkAFJrQPhAd3f3wDs5Tq+HAu6A8KEcwA8fBejBiw7dXNI9blzUEkK4VMc0Gzuajx3NZ8jMDhb8fSO4fZ8CXBNtMGhdsaP52HEpH83GThT5ZHoZzgtIrs47W0T+CVQBn8yZqhzh2hCcoVBaWhq1hKzp9VDAHRA+lAP44aMAPRR0h24+KK2vj1pCCJfqmGZjR/Oxo/kMmZiIHGiMeRpARN4HxCLWlFO0rtjRfOy4lI9mYyeKfDIaAWGMWQ58EDiA5Gq9C4wxL+dS2HDi0xoQbW1tUUvIml4PBdwB4UM5gB8+CtDDth26twJfjFaSW7TttNPAO+URl+qYZmNH87Gj+QyZc4HrRWS9iLwF/Izg6hW+onXFjuZjx6V8NBs7UeST6VUwioAjgFnBew4REYwx/5dDbcOOD2tATJw4MWoJWdProYA7IHwoB/DDRwF6mA0cDswAjgP2I/PRaCOCievXRy0hhEt1TLOxo/nY0XyGhjFmBbCXiEwMnjdHqyj3aF2xo/nYcSkfzcZOFPlkugbEH4EzgEpgQtqtIPBpDYiGhoaoJWRNr4cC7oDwoRzADx8F6OE7wZfXCuDDwM+BG6KV5BYNu+8etYQQLtUxzcaO5mNH8xkaIlIpIteRvArG4yJybTCVzlu0rtjRfOy4lI9mYyeKfDL91a3aGLNnTpXkAR/WgKisLPy/d70eUh0QZWXRiRkiPpQD+OGjAD2kFpw8Evi1MeZPIvLDKAW5RuWaNVFLCOFSHdNs7Gg+djSfIXMX8A+So9YATgHuBj4amaIco3XFjuZjx6V8NBs7UeST6QiIP4vIITlVkkN8WgOipqYmaglZ0+uhvT15X4AjIHwoB/DDRwF62CQivwQ+BTwsImPIvC0eEdQsWhS1hBAu1THNxo7mY0fzGTI7GWN+YIx5M7j9ENgxalG5ROuKHc3Hjkv5aDZ2osgn0y+9zwL3iUhMRJpFpEVECm7+mw9rQFRVVUUtIWt6PRTwFAwfygH88FGAHk4AHgUONcY0ApOBCyNV5BhVK1dGLSGES3VMs7Gj+djRfIbMX0TkRBEZFdxS7bi3aF2xo/nYcSkfzcZOFPlk2gHxf8B7gTJjzERjzARjjFsreljwaQ0I13rxhkKvh1gMRo+GUYX3468P5QB++Cg0D8aYdmPMH4wxa4Pnm40xf4lal0vorwP9o9nY0XzsaD5D5mzgDqAzuN0FfK5Qf5DLBK0rdjQfOy7lo9nYcXkExAZglSnQuQwp2T6sAeFaL95QCI2AKMDRD+BHOYAfPnzwoITRXwf6R7Oxo/nY0XyGTDnJxdh/YIwpIXlVuI8W2g9yg0Hrih3Nx45L+Wg2dlweAfEG8ISIfENELkjdciksF/gwBaO+vj5qCVnT66GAOyB8KAfww4cPHpQw9XPnRi0hhEt1TLOxo/nY0XyGzPXA/sBJwfMW4GfRyck9WlfsaD52XMpHs7ETRT6ZXgXjzeA2OrgVFD5NwSgvL49aQtb0eijgDggfygH88OGDByVM+RtvRC0hhEt1TLOxo/nY0XyGzH7GmCUi8iKAMaZBRAru+/Bg0LpiR/Ox41I+mo2dKPLJaASEMeb7fd1yLW648WEKRmtra9QSsqbXQwF3QPhQDuCHDx88KGFap0+PWkIIl+qYZmNH87Gj+QyZbhEpguQvWiJSBSSilZRbtK7Y0XzsuJSPZmMninwKb/W/Ec7YAv2HPZ1eD7EYlJVFK2aI+FAO4IcPHzwoYcbW1kYtIYRLdUyzsaP52NF8hsx1wH3ADiJyGfA0cHm0knKL1hU7mo8dl/LRbOxEkY92QBQYXV1dUUvIml4PjY0wfnykWoaKD+UAfvjwwYMSpmuiW2u6uVTHNBs7mo8dzWdoGGPuAC4CrgA2A8cYY34XrarconXFjuZjx6V8NBs7UeSTUQeEiLwvk21K7ikqKopaQtYUFRVBIgErV8KCBVHLGRI+lAP44cMHD0qYos7OqCWEcKmOaTZ2NB87ms/QMca8aoy53hjzM2PMmqj15BqtK3Y0Hzsu5aPZ2Ikin0xHQPw0w22Kkhmvvw4tLbBkSdRKFEVRFEVRFEVRlDxgvQqGiLwXOACo2uaymxMBt7qTLBjjz1Uwenp6opaQNT09PbB8efJJgXZA+FAO4IcPHzwoYXrGjIlaQgiX6phmY0fzsaP5KJmidcWO5mPHpXw0GztR5DPQZThHA+OD/SakbW8GPpkrUblCKPyrYIweXfhXfRo9ejS88AKMHg3z50ctZ0j4UA7ghw8fPChhRjc3Ry0hhEt1TLOxo/nY0XyUTNG6YkfzseNSPpqNnSjysXZAGGOeBJ4UkZuNMW8BiMgoYLwxxq30RgixWMy5E2mwxGIxRi9fDosWJTshChAfygH88OGDByVMbMoURjt02SyX6phmY0fzsaP5KJmidcWO5mPHpXw0GztR5JPpGhBXiMhEERkHrAJWi8iFOdSl9MP4Ar1qRDrjx41LTsEo0OkX4Ec5gB8+fPCghBm/aVPUEkK4VMc0Gzuajx3NR8kUrSt2NB87LuWj2diJIp9MOyDmByMejgH+DOwCfDpXopT+aWpqilpC1rSsWgUNDQXdAeFDOYAfPnzwoIRp2nXXqCWEcKmOaTZ2NB87mo+SKVpX7Gg+dlzKR7OxE0U+mXZAlIhICckOiAeNMd2APys7FhCTJ0+OWkLWTHrjjeSDAu6A8KEcwA8fPnhQwkx+7bWoJYRwqY5pNnY0Hzuaj5IpWlfsaD52XMpHs7ETRT6ZdkD8ElgPjAP+ISI7k1yIsiAwHvWV1NTURC0ha9qefhqKipJrQBQoPpQD+OHDBw9KmBrH2gaX6phmY0fzsaP5KJmidcWO5mPHpXw0GztR5DPQVTAAMMZcB1yXtuktEflwbiTlDpHCvwpGVVVV1BKyZtyrryavfjF2bNRShowP5QB++PDBgxKmauXKqCWEcKmOaTZ2NB87mo+SKVpX7Gg+dlzKR7OxE0U+GY2AEJEdReRGEflz8Hw+cHpOlSl94lov3qAxhsTzz8M++0StJCsKvhwCfPDhgwcljP460D+ajR3Nx47mo2SK1hU7mo8dl/LRbOxEkU+mUzBuBh4FpgXP/wN8OZM3ishhIvKaiKwTkYst+x0nIkZElmaoaUTiWi/eoNm8mVG1tQW9/gN4UA4BPvjwwYMSRn8d6B/Nxo7mY0fzUTJF64odzceOS/loNnacHQEBTDHG3AMkAIwxcaBnoDeJSBFwPXA4MB84KRg9se1+E4DzgX9nqGfEUldXF7WE7Fi+PHlf4B0QBV8OAT748MGDEqZu3ryoJYRwqY5pNnY0Hzuaj5IpWlfsaD52XMpHs7ETRT6ZdkC0iUglwZUvRGR/IJNrduwLrDPGvGGM6QLuAo7uY78fAP8LdGSoZ8RSUVERtYTsWL4cIwJ77RW1kqwo+HII8MGHDx6UMBX/+U/UEkK4VMc0Gzuajx3NR8kUrSt2NB87LuWj2diJIp9MOyAuAB4EZovIP4FbgS9m8L7pwIa05xuDbb2IyBJghjHmTxlqGTTG+HMVjObmgrn4SN8sX05izhwYPz5qJVlR8OUQ4IMPHzxkg4hMEpF7ReRVEVkjIu8Vkcki8lcRWRvcVwT7iohcF0yJezlof1PHOT3Yf62IRLrGT/OsWVF+/Ha4VMc0Gzuajx3NR8kUrSt2NB87LuWj2diJIp+MOiCMMcuBDwIHAJ8DFhhjXs72w0VkFPB/wFcz2PccEVkmIsu2bNlCR0cH7e3ttLW10dnZSXNzM/F4nIaGBowx1NbWAtssrGGgoaGBeDxOc3MznZ2dtLW10d7eTkdHBy0tLXR3d9PY2EgikegdkpI6Ruq+vr6enp4empqa6OrqorW1lVgsRiwWo7W1la6uLpqamujp6aG+vr7PY9TV1ZFIJGhsbKS7u5uWlpaMPI0bN673GLW1tRhjCspTYtkyzN5791tOheJp1KhRGdc9lz2NHj0647rnqqdx48YN+Xwabk8RcS3wiDFmD2AvYA1wMfCYMWYO8FjwHJLT4eYEt3OAGwBEZDLwPWA/kiPXvpfqtIiCcZs3R/XRfTJu3LioJfSi2djRfOxoPkqmaF2xo/nYcSkfzcZOFPlIJqMDRKQU+DxwIMlpGE8BvzDGWKdMiMh7gUuMMYcGz78BYIy5InheDrwOtAZvmQrUA0cZY5b1d9ylS5eaZcv6fXk7/vr6Xznk9kN4+jNP876Z78v4fS7S0tLChAkTopYxNLZsgR13pOOyyyj95jejVpMVBV0OafjgwyUPIvKCMSZvC+kGbegKYFeT1piLyGvAh4wxm0VkJ+AJY8xcEfll8PjO9P1SN2PM54Ltof36YrDtcJroAXdpqa5mwsaN9p3yOLItr3VsgHw0Gzuaj52Rkk++2+IoGVJbrHXFjuZjp8Dy0WzsRNEOZzoF41ZgAfBT4GfB49syeN/zwBwR2UVERgMnkpzKAYAxpskYM8UYM8sYMwt4lgE6H0Y6JSUlUUsYOi++CMCoAr8EJxR4OaThgw8fPGTBLkAN8FsReVFEfiMi44AdjTGpLvZ3gB2Dx/1Nixtwulw+KWlri+qj+8SlOqbZ2NF87Gg+SqZoXbGj+dhxKR/Nxk4U+WTaAbHQGHOWMebx4HY2yU4IK8HVMs4jeQnPNcA9xphXRORSETlq6LJHLolEImoJQye4AkbcsevfDoWCLoc0fPDhg4csKAaWADcYY/YG2tg63QKAYGTEsHSlZzsVrra2FiNCw5w5xEtLaZ45k87yctqmTqW9qoqOigpaqqvpnDCBxtmzSRQV9a4Wnbpuduo+n1Phurq68jcdqaSEplmz6Bo/ntZp04hVVhKrrKR12jS6xo+nadYsekpKqJ87t89c6ubNc2I6Uk6mjc2eTXdZGS3V1XRUVNBeVUXb1Kl0lpfTPHMm8dJSGnbbDSNC7cKFyWME97ULF26tey55Gs5y6ud86i4r23o+7bFH3+fT3Llb655LnrIoJyU7EsXFUUsI4drfes3Hjkv5aDZ2osgn0ykYtwM/M8Y8GzzfD/iCMea0HOvrk5E8BaOtrc25uUwZc/zxsHw5bS+/XLgeAgq6HNLwwYdLHiKYgjEVeDYYQYaIvJ9kB8RuFPAUjLapUxn3zjv2nfI4PDGvdWyAfDQbO5qPnZGSj07BGACtK3Y0HzsFlo9mYyeKdtg6AkJEVorIy8A+wL9EZL2IvAk8A4yIht01ih3rNRsUy5fDkiWF7SHABw/ghw8fPAwVY8w7wAYRmRtsOghYTXKqW+pKFqcDDwSPHwROC66GsT/QFEzVeBQ4REQqgsUnDwm2RUJxLBbVR/eJS3VMs7Gj+djRfJRM0bpiR/Ox41I+mo2dKPIZ6BM/lhcVOcYMz+hjJ+js7GTMmDFRyxg8DQ3wxhvw2c8Wroc0fPAAfvjwwUOWfBG4I1hn5w3gMyQ7l+8RkbOAt4ATgn0fBo4A1gHtwb4YY+pF5Ack1+0BuNQYU58/C2E6y8sZ09QU1cdvh0t1TLOxo/nY0XyUTNG6YkfzseNSPpqNnSjysXZAGGPeypeQfCAZDItxnbKysqglDI0VK5L3++xTuB7S8MED+OHDBw/ZYIxZQd8j0g7qY18DfKGf49wE3DSs4oZI2ZYtUUsI4VId02zsaD52NB8lU7Su2NF87LiUj2ZjJ4p8Ml2EUnGElpaWqCUMjWABSvbeu3A9pOGDB/DDhw8elDAtM2ZELSGES3VMs7Gj+djRfJRM0bpiR/Ox41I+mo2dKPJxa1KMMiCTJk2KWsLQWL4cZsyAqiom5XFhlVxRsOWwDT748MGDEmbSunVRSwjhUh3TbOxoPnY0HyVTtK7Y0XzsuJSPZmMninx0BESBkbrcVMERLEAJBewhDR88gB8+fPCghKlbMOBVnvOKS3VMs7Gj+djRfJRM0bpiR/Ox41I+mo2dKPLRDogCY8qUKVFLGDytrfDaa70dEAXpYRt88AB++PDBgxJmyqpVUUsI4VId02zsaD52NB8lU7Su2NF87LiUj2ZjJ4p8RkQHhPFgyH+KmpqaqCUMnpdeSl7PNuiAKEgP2+CDB/DDhw8elDA1CxdGLSGES3VMs7Gj+djRfJRM0bpiR/Ox41I+mo2dKPIZER0QKYTCvwpGVVVV1BIGzwsvJO+DDoiC9LANPngAP3z44EEJU+XYrwMu1THNxo7mY0fzUTJF64odzceOS/loNnaiyGdEdUD4QG1tbdQSBs/y5bDjjrDTTkCBetgGHzyAHz588KCEqXXs1wGX6phmY0fzsaP55BcRuUlEtojIqrRtk0XkryKyNrivCLaLiFwnIutE5GURWRKdcq0rA6H52HEpH83GThT5aAdEgVFZWRm1hMGTWoBSkiNQCtLDNvjgAfzw4YMHJUzlK69ELSGES3VMs7Gj+djRfPLOzcBh22y7GHjMGDMHeCx4DnA4MCe4nQPckCeNfaJ1xY7mY8elfDQbO1Hkox0QBUZjY2PUEgZHLAarV/dOv4AC9NAHPngAP3z44EEJ07jbblFLCOFSHdNs7Gg+djSf/GKM+QdQv83mo4Fbgse3AMekbb/VJHkWmCQiO+VFaB9oXbGj+dhxKR/Nxk4U+WgHRIExYcKEqCUMjpUroacn1AFRcB76wAcP4IcPHzwoYSZs2BC1hBAu1THNxo7mY0fzcYIdjTGbg8fvADsGj6cD6QW0MdgWCVpX7Gg+dlzKR7OxE0U+I6IDwuDPVTDa29ujljA4li9P3qd1QBSchz7wwQP44cMHD0qY9h12iFpCCJfqmGZjR/Oxo/m4hUlepm3QX1JF5BwRWSYiy7Zs2UJHRwft7e20tbXR2dlJc3Mz8XichoYGjDG9c7xTq93XLlyIEaFhzhzipaU0z5xJZ3k5bVOn0l5VRUdFBTWLFtFdVkbj7NkkioqomzcveYxFi0L39fX19PT00NTURFdXF62trcRiMWKxGK2trXR1ddHU1ERPTw/19fUhHan7uro6EokEjY2NdHd309LSsp2nLVu22D3V1mKMoaGhgXg8TnNzM52dnbS1tdHe3k5HRwctLS10d3fT2NhIIpGgrq6uTz31c+fSU1JC06xZdI0fT+u0acQqK4lVVtI6bRpd48ezZfFiekpKqJ87t89c6ubNG9DTgOU0CE/vvvuu3dNwltPs2XSXldFSXU1HRQXtVVW0TZ1KZ3k5zTNnEi8t5Z2lSzEivesdpK78EKp72ZZThp5aWlqyqnuDKqd+zqeW6ure86l16tT+z6dU3cvx+ZTuqa2tLSfnkw0pxEtULl261Cxbtizj/R9Z9wiH33E4z5z1DPtX759DZbmns7OTMWPGRC0jc845B37/e6it7V0DouA89IEPHsAPHy55EJEXjDFLo9aRDwbbDvciA1+NqLO8nDFNTfad8vi3K691bIB8NBs7mo+dkZKPS22xiMwCHjLGLAyevwZ8yBizOZhi8YQxZq6I/DJ4fOe2+9mOP6S2WOuKHc3HToHlo9nYiaIdHhEjIHwiHo9HLWFwbLMAJRSghz7wwQP44cMHD0qY+NixUUsI4VId02zsaD52NB8neBA4PXh8OvBA2vbTgqth7A80DdT5kEu0rtjRfOy4lI9mYyeKfLQDosCQDHrWnKGrK7kGxJLwlaQKykM/+OAB/PDhgwcljPT0RC0hhEt1TLOxo/nY0Xzyi4jcCTwDzBWRjSJyFvAj4GARWQt8NHgO8DDwBrAO+DXw+Qgk96J1xY7mY8elfDQbO1HkU5z3T1SyYtSoAuozWr062QmxTQdEQXnoBx88gB8+fPCghBnl2K8VLtUxzcaO5mNH88kvxpiT+nnpoD72NcAXcqsoc7Su2NF87LiUj2ZjJ4p83CoRZUC6u7ujlpA5fSxACQXmoR988AB++PDBgxKme9y4qCWEcKmOaTZ2NB87mo+SKVpX7Gg+dlzKR7OxE0U+I6IDohAX2uyP0tLSqCVkzvLlMGECzJ4d2lxQHvrBBw/ghw8fPChhSoOVnV3BpTqm2djRfOxoPkqmaF2xo/nYcSkfzcZOFPmMiA6IFIJbc4CGQltbW9QSMmf5cth7b9hmaE9BeegHHzyAHz588KCEadtpp6glhHCpjmk2djQfO5qPkilaV+xoPnZcykezsRNFPiOqA8IHJk6cGLWEzIjHYcWK7aZfQAF5sOCDB/DDhw8elDAT16+PWkIIl+qYZmNH87Gj+SiZonXFjuZjx6V8NBs7UeSjHRAFRkNDQ9QSMuO11yAW67MDomA8WPDBA/jhwwcPSpiG3XePWkIIl+qYZmNH87Gj+SiZonXFjuZjx6V8NBs7UeSjHRAFRmVlZdQSMqOfBSihgDxY8MED+OHDBw9KmMo1a6KWEMKlOqbZ2NF87Gg+SqZoXbGj+dhxKR/Nxk4U+WgHRIFRU1MTtYTMWL4cxo6FuXO3e6lgPFjwwQP44cMHD0qYmkWLopYQwqU6ptnY0XzsaD5KpmhdsaP52HEpH83GThT5jIgOCIM/V8GoqqqKWkJmLF8Oe+0FxcXbvVQwHiz44AH88OGDByVM1cqVUUsI4VId02zsaD52NB8lU7Su2NF87LiUj2ZjJ4p8RkQHRAqRwr8Khmu9eH2SSMCLL8I++/T5ckF4GAAfPIAfPnzwoITRXwf6R7Oxo/nY0XyUTNG6YkfzseNSPpqNHR0BoQyIa714ffL669DS0uf6D1AgHgbABw/ghw8fPChh9NeB/tFs7Gg+djQfJVO0rtjRfOy4lI9mY0dHQCgDUl9fH7WEgbEsQAkF4mEAfPAAfvjwwYMSpr6PtWOixKU6ptnY0XzsaD5KpmhdsaP52HEpH83GThT5aAdEgVFeXh61hIFZvhxGj4b58/t8uSA8DIAPHsAPHz54UMKUv/FG1BJCuFTHNBs7mo8dzUfJFK0rdjQfOy7lo9nYiSIf7YAoMFpbW6OWMDDLl8OiRclOiD4oCA8D4IMH8MOHDx6UMK3Tp0ctIYRLdUyzsaP52NF8lEzRumJH87HjUj6ajZ0o8hkRHRDG+HMVjLFjx0YtwY4xyQ6IfqZfQAF4yAAfPIAfPnzwoIQZW1sbtYQQLtUxzcaO5mNH81EyReuKHc3Hjkv5aDZ2oshnRHRApBAK/yoYXV1dUUuw89//Qn29tQPCeQ8Z4IMH8MOHDx6UMF0TJ0YtIYRLdUyzsaP52NF8lEzRumJH87HjUj6ajZ0o8hlRHRA+UFRUFLUEOwMsQAkF4CEDfPAAfvjwwYMSpqizM2oJIVyqY5qNHc3HjuajZIrWFTuajx2X8tFs7ESRj3ZAKMPLCy9AUVFyDQhFURRFURRFURRFCdAOiAKjp6cnagl2li9PXv3CMp/IeQ8Z4IMH8MOHDx6UMD1jxkQtIYRLdUyzsaP52NF8lEzRumJH87HjUj6ajZ0o8tEOiAJjdD9XlnACY5IjICzTL8BxDxnigwfww4cPHrJFRIpE5EUReSh4vouI/FtE1onI3SIyOtg+Jni+Lnh9VtoxvhFsf01EDo3ICgCjm5uj/PjtcKmOaTZ2NB87mo+SKVpX7Gg+dlzKR7OxE0U+I6IDwuDPVTBisVjUEvpn82bYsmXADginPWSIDx7ADx8+eBgGzgfWpD3/X+BqY8xuQANwVrD9LKAh2H51sB8iMh84EVgAHAb8XEQimzQZmzIlqo/uE5fqmGZjR/Oxo/komaJ1xY7mY8elfDQbO1HkMyI6IFKIFP5VMMaPHx+1hP5JLUC5zz7W3Zz2kCE+eAA/fPjgIRtEpBo4EvhN8FyAjwD3BrvcAhwTPD46eE7w+kHB/kcDdxljOo0xbwLrgH3zYqAPxm/aFNVH94lLdUyzsaP52NF8lEzRumJH87HjUj6ajZ0o8hlRHRA+0NTUFLWE/lm+HERgr72suzntIUN88AB++PDBQ5ZcA1wEJILnlUCjMSYePN8ITA8eTwc2AASvNwX7927v4z15p2nXXaP66D5xqY5pNnY0Hzuaj5IpWlfsaD52XMpHs7ETRT7aAVFgTJ48OWoJ/bN8OcydCwP0pDntIUN88AB++PDBw1ARkY8BW4wxL+Tp884RkWUismzLli10dHTQ3t5OW1sbnZ2dNDc3E4/HaWhowBhDbW0tADU1NQDU1tZiRGiYM4d4aSnNM2fSWV5O29SptFdV0VFRQUt1NRM2bKBx9mwSRUXUzZuXPEZwZZ3UfX19PT09PTQ1NdHV1UVrayuxWIxYLEZraytdXV00NTXR09NDfX19SEfqvq6ujkQiQWNjI93d3bS0tPTpaeLEiXZPxtDQ0EA8Hqe5uZnOzk7a2tpob2+no6ODlpYWuru7aWxsJJFIUFdX16ee+vp6ekpKaJo1i67x42mdNo1YZSWxykpap02ja/x4ijo76SkpoX7u3D5zqZs3LyNPA5ZThp5GjRo1sKfhKqfZs+kuK6OlupqOigraq6pomzqVzvJymmfOJF5aiiQSGBFqFy5MHiO4r124cGvdG45yytBTiqHWvUGVUz/nU3dZWe/5ZEaN6vt8mjt3a93L8fmU7imRSOTsfFKyY/Jrr0UtIYRrf+s1Hzsu5aPZ2IkiHzGm8NZHWLp0qVm2bFnG+z/0n4f4+J0f5/mzn2fptKU5VJZ7ampqqKqqilpG38ycCe9/P9xxh3U3pz1kiA8ewA8fLnkQkReMMXlrZETkCuDTQBwoBSYC9wGHAlONMXEReS9wiTHmUBF5NHj8jIgUA+8AVcDFAMaYK4Lj9u7X32cPth1OEz3gLjWLFlG1cqV9pzz+7cprHRsgH83GjuZjZ6Tkk++2OEqG1BZrXbGj+dgpsHw0GztRtMM6AqLAcOUfre2oqYENGwZcgBIc9jAIfPAAfvjwwcNQMcZ8wxhTbYyZRXIRyb8bY04BHgc+Gex2OvBA8PjB4DnB6383yV7oB4ETg6tk7ALMAZ7Lk43tGPAPc55xqY5pNnY0Hzuaj5IpWlfsaD52XMpHs7ETRT4jogOiEEd59IezQwtffDF5n0EHhLMeBoEPHsAPHz54yAFfBy4QkXUk13i4Mdh+I1AZbL+ArSMfXgHuAVYDjwBfMMZEduHs1LBwV3Cpjmk2djQfO5qPkilaV+xoPnZcykezsRNFPsV5/8QIEQr/Khiu9eL1kroCxt57D7irsx4GgQ8ewA8fPngYDowxTwBPBI/foI+rWBhjOoDj+3n/ZcBluVOYOfrrQP9oNnY0Hzuaj5IpWlfsaD52XMpHs7GjIyCUAUkttuQc//oX7LorTJo04K7OehgEPngAP3z44EEJk1p40hVcqmOajR3Nx47mo2SK1hU7mo8dl/LRbOxEkY92QBQYFRUVUUvYnvp6ePRROProjHZ30sMg8cED+OHDBw9KmIr//CdqCSFcqmOajR3Nx47mo2SK1hU7mo8dl/LRbOxEkY92QBQYzc3NUUvYnnvvha4uOPXUjHZ30sMg8cED+OHDBw9KmOZZs6KWEMKlOqbZ2NF87Gg+SqZoXbGj+dhxKR/Nxk4U+WgHRIExbty4qCVsz+23w7x5Ga3/AI56GCQ+eAA/fPjgQQkzbvPmqCWEcKmOaTZ2NB87mo+SKVpX7Gg+dlzKR7PZSmNjI5/85CfZY489mDdvHs888wydnZ0cfPDBzJkzh4MPPpiGhoac6xgRHRAGf66C0dHREbWEMG+9BU89lRz9kMG1b8FBD0PABw/ghw8fPChhOiZPjlpCCJfqmGZjR/Oxo/komaJ1xY7mY8elfDSbrZx//vkcdthhvPrqq7z00kvMmzePK664goMOOoi1a9dy0EEH8aMf/SjnOkZEB0QKyfAfZJcpKSmJWkKY//f/kvcnn5zxW5zzMAR88AB++PDBgxKmpK0tagkhXKpjmo0dzceO5qNkitYVO5qPHZfy0WySNDU18Y9//IOzzjoLgNGjRzNp0iQefvhhTj/9dABOP/107r///pxrGVEdED6QSCSilrAVY+C22+DAA2EQ85mc8jBEfPAAfvjwwYMSJlHs1hWiXapjmo0dzceO5qNkitYVO5qPHZfy0WySvPnmm1RVVfGZz3yGvffem89+9rO0tbWxZcsWdtppJwCmTp3Ku+++m3Mt2gFRYBjj0HSSFStgzZqMF59M4ZSHIeKDB/DDhw8elDCmqChqCSFcqmOajR3Nx47mo2SK1hU7mo8dl/LRbJLE43GWL1/Oueeey4svvsi4ceO2m24hInmZMaAdEAVGsUM9itxxB5SUwPHHD+ptTnkYIj54AD98+OBBCVMci0UtIYRLdUyzsaP52NF8lEzRumJH87HjUj6aTZLq6mqqq6vZb7/9APjkJz/J8uXL2WGHHdgcLIy5efNmdthhh5xr0Q6IAqOzszNqCUl6epLrPxxxBAxyMRVnPGSBDx7ADx8+eFDCdJaXRy0hhEt1TLOxo/nY0XyUTNG6YkfzseNSPppNkqlTpzJjxgxee+01AB577DHmz5/PYYcdxi233ALALbfcwtFHH51zLW51CeUI14beZENZWVnUEpI8/jhs3jzo6RfgkIcs8MED+OHDBw9KmLItW6KWEMKlOqbZ2NF87Gg+SqZoXbGj+dhxKR/NZis//elPOeWUU+jq6mLXXXflt7/9LV1dXZx88snceOON7Lzzztxzzz051zGiRkAIhX8VjJaWlqglJLn9dpg4ET72sUG/1RkPWeCDB/DDhw8elDAtM2ZELSGES3VMs7Gj+djRfJRM0bpiR/Ox41I+ms1WFi9ezLJly3j55Ze5//77qaioYPTo0Tz22GOsXbuWv/3tb0zOw2VCcz4CQkQOA64FioDfGGN+tM3rFwCfBeJADXCmMeatXOsqVCZNmhS1BGhvhz/8Ibn2Q2npoN/uhIcs8cED+OHDBw9KmEnr1kUtIYRLdUyzsaP52NF8lEzRumJH87HjUj4jORv5/sA/vguCwT5bwHxveGcT5HQEhIgUAdcDhwPzgZNEZP42u70ILDXG7AncC1yZS02FTl1dXdQS4I9/hJaWIU2/AEc8ZIkPHsAPHz54UMLULVgQtYQQLtUxzcaO5mNH81EyReuKHc3Hjkv5aDZ2FozPv55cj4DYF1hnjHkDQETuAo4GVqd2MMY8nrb/s8DQ/qsdIUyZMiVqCcnpF9XV8MEPDuntTnjIEh88gB8+fPCghJmyalXUEkK4VMc0Gzuajx3NR8kUrSt2osxn1qxZTJgwgaKiIoqLi1m2bBmjRo3i4IMPZv369cyaNYt77rmHioqKyDS6lk99fT2f+tSnnMjHtXNrVWv+9eR6DYjpwIa05xuDbf1xFvDnvl4QkXNEZJmILNuyZQsdHR20t7fT1tZGZ2cnzc3NxONxGhoaMMZQW1sLQE1NTe8xjDE0NDQQj8dpbm6ms7OTtrY22tvb6ejooKWlhe7ubhobG0kkEr09ZqljpO7r6+vp6emhqamJrq4uWltbicVixGIxWltb6erqoqmpiZ6eHurr6/s8Rl1dHYlEgsbGRrq7u2lpacnIU01NTe8xamtr8+/p3XcxjzwCJ59MzTbHytTTO++80285ReJpCOW0YcOGjOuey542b96ccd37/+2deXhU5dn/P3dCTEISAgkBwmZQFgMJhEWwriguuDTI6lKr1IVWitZaqbT1VbTaUqstpX27qOUnVit1qcqr1qoIbXFHDLvihhWIIYQQyEqW5/fHnMQMJCeTZGbOM5P7c11zzZkzZ8753t9zn3tmnvOc59gaU3FxcYePp2DHpASH4pwcryX4YdP+VW/cUX/cUX+UQNFcccdrf9asWUNBQQHr168H4Pbbb2fKlCl89NFHTJkyhSVLlrSxhtBikz/FxcUsWbLEGn+89uZIcpLDr0dCeYcIEZkFTDXGXOu8/iYwyRizoIVlrwAWAGcYY1zvlzJhwgTTeMAFwrMfPMv0v01nw7wNjM0c264YlCP4/e/hu9+FjRth9Giv1SiKVYjIe8aYCV7rCAftrcNNSJAGA46iuxv5EQx/1Bt31B93osAfrcVtoLnijuX+ZGVlsX79er9eISNGjGDt2rVkZmZSWFjI5MmTm263GHTUn9axzJtAxoAIhI6MAeFWh0PdA2I30Hyoz4HOPD9E5GzgJ0B+W40PnUGClRQe0njW1jMefRRyczvV+OB5DEEgGmKA6IgjGmJQ/Nln2dkBm3JMvXFH/XFH/VECRXPFHS/9ERHOPfdcxo8fzwMPPADAl19+SWZmJgD9+vWjqKjIM31glz/79u2jqKjIGn9sO7a86AER6jEg3gWGicgQfA0PlwKXN19ARMYCf8LXU8Kem8ZaSnp6uncb/+QTePNN+MUvOrUaT2MIEtEQA0RHHNEQg+JP+tatXkvww6YcU2/cUX/cUX+UQNFcccdLf9atW8eAAQPYu3cv55xzDieccILfSVYR8fykq03+jBgxwu99r/2x7djaWh5+PSHtAWGMqcN3WcU/ge3AE8aYrSJyl4jkO4v9EkgGnhSRAhFZFUpNkc6BAwe82/hf/+rrWnTZZZ1ajacxBIloiAGiI45oiEHx58DQoV5L8MOmHFNv3FF/3FF/lEDRXHHHS38GDPANp9enTx+mT5/OO++8Q0ZGBoWFhQAUFhbSp08fz/SBXf7861//om/fvtb4Y9uxNbR7+PWE+hIMjDEvGmOGG2OON8bc48y73Rizypk+2xjT1xiT5zzy3dfYtUlJSfFmw8b4Lr844wwYNKjt5V3wLIYgEg0xQHTEEQ0xKP6kfPFF2wuFEZtyTL1xR/1xR/2xBxHZKSKbnZNv6515aSLyioh85Dx7dhsDzRV3vPKnoqKCQ4cONU2//PLL5OTkkJ+fz4oVKwBYsWIF06ZN80RfIzb5M378eKv8se3Y+qI6/HpC3gChBJfKykpvNrx+PezYAVd0/i6pnsUQRKIhBoiOOKIhBsWfSo/P3ByJTTmm3rij/rij/ljHmc7Jt8aB2hYBq40xw4DVzmtP0Fxxxyt/ioqKOPXUUxkzZgwTJ07kwgsvZOrUqdxwww288sorDBs2jFdffZVFizxLHcAuf0477TQWLVpkjT+2HVt9jgm/nlCPAWEFobzTR7iJj4/3ZsOPPgrx8TBzZqdX5VkMQSQaYoDoiCMaYlD8iS8r81qCHzblmHrjjvrjjvpjPdOAyc70CmAtcKsXQjRX3PHKn+OOO46NGzceNT8zM5PVq1d7oKhlbPKnpqaGHj16WOOPbcdWWV349XSJBohGhMi/C0ZdXV34i3BdHaxcCRddBD17BmF1HsQQZKIhBoiOOKIhBsWfusREq76gbcox9cYd9ccd9ccqDPCyiBjgT8aYB4C+xphC5/0vgb4tfVBE5gHzAAYNGkR1dTUNDQ0YY+jWrRs1NTV0796dQ4cO0bNnT0pKSujduzfFxcVkZGSwLyeH9K1bOTB0KClffEFlnz7El5VRl5iI1NcTU1fHwWOPpdeOHVRkZtJj505Khw8nfft2inNzydi82fcM7N+/n9TUVMrLy0lMTOTw4cPExsYCUF9fzzHHHENVVRXJycmUlZWRlpbWpKPxuaSkhF69enHw4EGSkpKorq4mLi7OL6YDBw6Qnp7eekz79pGens6BAwdISUmhsrKS+Ph46urqEBFiYmKora0lISGBiooKevToQWlpKenp6Ufp2T9iBKmffkr5gAEk7tvH4R49iK3x3aSvPj6eYw4epHToUDI2baLsuONI+/BDf182b6YkO5teDQ2uMbW5n5yYRtw3gi+qv6DPMX0oqysjMSaRelNPnakjKTaJ/bX7yUnO4b2D7zE8aTjbK7aTm5zL5vLNTc8juo9g681bg7Ofjj+epMJCqtPSiKuooKFbN0xsLN2qqqhJTaX73r2UZGeT+fbblIwaRe8tWyjOySFjyxb/3Kur69x+2r+ffr/rx4D4Aeyr3UePbj2oafDtp/iYeA7WHaR3XO8mnz6s/PAoX7KTstlRsYN939vX6f104MABUhISWjyeapOSSNi/n4rMTGKrqijv3//o42nz5q9yr6wsKMdT95jupMWlUVFfQTfpRqzEUtVQRWq3VPYe3sughEGU15UzKHkQW8q3kJOc0/S8tXwrQ7sP5YvqLzh48GC795MbEom9A9p7z+Nntj/DjCdmUPDtAsb0GxNCZaGnsrKS7t27h3ejL70E558PzzwDF1/c6dV5EkOQiYYYIDrisCkGvfd8AAQw8nRlRgbdi4vdFwrjd1dYc6wNf9Qbd9Qfd7qKP5FQi0VkgDFmt4j0AV4BbgBWGWN6Nlum1BjjOg5Eh2qx5oo7lvkjd7atJyMug+Jadz3mjiDtL4v8UW/akOOhP251WMeAiDBiYjzYZY8+Cr16+RohgoAnMQSZaIgBoiOOaIhB8Semrs5rCX7YlGPqjTvqjzvqjz0YY3Y7z3uBZ4CJQJGIZAI4z57dnl5zxR3b/KkzdumxyR/1xh0v/LHraFbapLa2NrwbLC/39XyYM8c3BkQQCHsMISAaYoDoiCMaYlD8qU1K8lqCHzblmHrjjvrjjvpjByKSJCIpjdPAucAWYBVwlbPYVcBz3ijUXGkL2/xJirVLj03+qDfueOFPlxoDIhpISEgI7wafew4qK+Eb3wjaKsMeQwiIhhggOuKIhhgUfxL27/dagh825Zh644764476Yw19gWfE1127G/BXY8xLIvIu8ISIXAN8DszxSqDmiju2+bO/1i49Nvmj3rjjhT9dogeEIfLGuWiNioqK8G7w0Ufh2GPhlFOCtsqwxxACoiEGiI44oiEGxZ+KzEyvJfhhU46pN+6oP+6oP3ZgjPnUGDPGeYwyxtzjzC8xxkwxxgwzxpxtjPHsn4rmiju2+ZMZb5cem/xRb9zxwp8u0QDRiAQwMIjt9OjRI3wbKyqCl1/29X4I4rV3YY0hRERDDBAdcURDDIo/PXbu9FqCHzblmHrjjvrjjvqjBIrmiju2+bOzaqfXEvywyR/1xh0v/OlSDRDRQGlpafg2tnIlNDQE9fILCHMMISIaYoDoiCMaYlD8KR0+3GsJftiUY+qNO+qPO+qPEiiaK+7Y5s/wJLv02OSPeuOOF/5oA0SEkZ6eHr6NPfYYjB0LI0cGdbVhjSFEREMMEB1xREMMij/p27d7LcEPm3JMvXFH/XFH/VECRXPFHdv82V5hlx6b/FFv3PHCH22AiDCK27pvbLD48EN491244oqgrzpsMYSQaIgBoiOOaIhB8ac4N9drCX7YlGPqjTvqjzvqjxIomivu2OZPbrJdemzyR71xxwt/tAEiwsjIyAjPhh57zDfuw6WXBn3VYYshhERDDBAdcURDDB1FRAaJyBoR2SYiW0Xke878NBF5RUQ+cp57OfNFRJaJyMcisklExjVb11XO8h+JyFWtbTMcZGze7OXmj8KmHFNv3FF/3FF/lEDRXHHHNn82l9ulxyZ/1Bt3vPCnSzRAGBM9d8EISwuwMb4GiLPOgv79g75621qxO0I0xADREUc0xNAJ6oAfGGNGAicB3xWRkcAiYLUxZhiw2nkNcD4wzHnMA/4AvgYL4A5gEjARuKOx0cILbDs7YFOOqTfuqD/uqD9KoGiuuGObP3qWv3XUG3e0B0SIESL/LhhhaQF+6y349NOQXH4B9rVid4RoiAGiI45oiKGjGGMKjTEbnOlDwHZgADANWOEstgK42JmeBjxifLwF9BSRTOA84BVjzH5jTCnwCjA1fJH4Y9vZAZtyTL1xR/1xR/1RAkVzxR3b/NGz/K2j3rijPSCUNtm/P8S3hP7vf2HxYkhMhOnTQ7KJkMcQBqIhBoiOOKIhhmAgIlnAWOBtoK8xptB560ugrzM9APii2cd2OfNam+8J+0eM8GrTLWJTjqk37qg/7qg/SqBorrhjmz8jutulxyZ/1Bt3vPBHGyAijNTU1NCs+JNP4Npr4fjjYc0auOMOCNE9l0MWQxiJhhggOuKIhhg6i4gkA08DNxljDjZ/z/iuQQvKdWgiMk9E1ovI+r1791JdXU1lZSUVFRXU1NRw8OBB6urqKC0txRjDvn37gK+6zu7btw8jQumwYdQlJHBw8GBqUlOp6NePyowMqnv14tDAgXT/8ksOHH88DbGxlGRn+9bhdFlsfN6/fz/19fWUlZVx+PBhysvLqaqqoqqqivLycg4fPkxZWRn19fVNP1wbdTQ+l5SU0NDQwIEDB6itreXQoUMtxpSUlOQekzGUlpZSV1fHwYMHqampoaKigsrKSqqrqzl06BC1tbUcOHCAhoYGSkpKWtSzf/9+6uPiKMvK4nByMuX9+1OVnk5Vejrl/ftzODkZqa+nPi6u6QfMkb6UZGcHFFOb+ynAmIwxbccUrP10/PHUdu/OoYEDqe7Vi8qMDCr69aMmNZWDgwdTl5BAQ0wMRoR9OTm+dTjP+3Jyvsq9YOynAGNqaGjoVO61az+1cjzVdu/edDzVH3NMy8fTiBFf5V6Ij6fmMdXW1obseFI6R+qnn3otwQ/bvutt8+fTKrv02OSPeuOOF/5IJI6PMGHCBLN+/fqAl39629PMenIWm76zidy+dl13017KysqCW4S3b4ef/Qz++leIi4PrroOFC2Hw4OBt4wiCHoMHREMMEB1x2BSDiLxnjJkQ5m3GAc8D/zTG/MqZ9yEw2RhT6FxisdYYM0JE/uRMP958ucaHMebbzny/5VqivXW4meA2FynLyiJ15073hcL43RXWHGvDH/XGHfXHna7ijxe12Cs6VIs1V9yxzB+5s209WQlZ7Kx212PuCNL+ssgf9aYNOR7641aHtQdEhJGYmBicFW3cCHPmwKhR8Pe/w/e/D599Br/9bUgbHyCIMXhINMQA0RFHNMTQUUREgD8D2xsbHxxWAY13srgKeK7Z/Cudu2GcBJQ5l2r8EzhXRHo5g0+e68zzhETnTK8t2JRj6o076o876o8SKJor7tjmz75au/TY5I96444X/nSJBggTnN7HVnD48OHOreCdd2DaNMjLg5degh/9CD7/HO67DzIzg6KxLTodgwVEQwwQHXFEQwyd4BTgm8BZIlLgPC4AlgDniMhHwNnOa4AXgU+Bj4EHgfkAxpj9wE+Bd53HXc48Tzgcosu/OopNOabeuKP+uKP+KIGiueKObf706GaXHpv8UW/c8cKfbmHfoodIAN1ibCc2NrZjH1y3Dn76U3j5ZejVC+66CxYs8E2HmQ7HYBEdiaG2tpZdu3ZRXV0dAkUdwxgT8ceFFzEkJCQwcOBA4uLiwrrdIzHGrINWb+8zpYXlDfDdVta1HFgePHUdJ7amxmsJfthUs9Qbd9Qfd9QfJVA0V9yxzZ+aBrv02OSPeuOOF/50qQaILocx8NprvoaHf/0L+vSBX/wCrr8eUlK8Vtfl2LVrFykpKWRlZVnzp7+hoYGYmMjuCBXuGIwxlJSUsGvXLoYMGRK27SqKoihKV+CLL77gyiuvpKioCBFh3rx5zJs3j8WLF/Pggw823ZLzZz/7GRdccIHHahVFaS/aABFh1NfXt72QMfDii3D33fDWW9C/Pyxd6htgsnv3kGtsi4BisJyOxFBdXW1V4wP4/kxHOuGOQURIT0/XkdZDSH18vNcS/LCpZqk37qg/7qg/SqB4mSvdunXj/vvvZ9y4cRw6dIjx48dzyimnAPD973+fW265xTNtjdh2LMXH2KXHJn/UG3e88EcbICKMY5xbaLVIQwM8+6yv4eH99+HYY+EPf4C5cyEhIVwS28Q1hgihozHY1PgA9unpCF7EEA2+2cwxBw+2vVAYsalmqTfuqD/uqD9KoHiZK5mZmWQ645KlpKSQnZ3N3r17PdPTErYdSwfr7NJjkz/qjTte+BPZfa+7IFVVVUfPrK+Hxx+H0aNh5kw4dAiWL4ePPoLvfMeqxgdoJYYII1JjiI2NJS8vj5ycHL7+9a833c89mEyePJkO3Z7R4dlnn2Xbtm0BL9/Q0ADAqlWrWLJkieuye/bsYdasWR3WpoSHqt69vZbgh03Hu3rjjvrjjvqjBIotubJz507ef/99cnNzAfjd737H6NGjufrqqyktLfVMly3+NNI7zi49Nvmj3rjjhT9dogEiGrqZN5KcnOy7xGL3bt9dLJYsgexsuPxy3/zHHoPt2+Fb3wKPB8hrjeTkZK8ldJpIjSExMZGCggK2bNlCWloaf/zjH72WdFQXXLcGiLq6uqPmNQ5MlZ+fz6JFi1y31b9/f5566qkOKlXCRfLu3V5L8MOm4129cUf9cUf9UQLFhlwpLy9n5syZLF26lP79+3P99dfzySefUFBQQGZmJj/4wQ8802aDP83ZXWOXHpv8UW/c8cKfLtEA0Yi0Oli8xZSXw9tvw4MPwo030nDGGdC7NwwcCOef77uNZkoKPPUUbN7sa4joZveVNWVlZV5L6DTREMPXvvY1du3aBcAnn3zC1KlTGT9+PKeddhoffPBB0/yTTjqJ3NxcbrvttqYfi2vXruWiiy5qWteCBQt4+OGHj9rG9ddfz4QJExg1ahR33HFH0/ysrCxuvfVWxo0bx5NPPtk0/4033mDVqlUsXLiQvLw8PvnkEyZPnsxNN93EhAkT+M1vfsP//d//MWnSJMaOHcvZZ5/Nnj17AHj44YdZsGABAHPnzuXGG2/k5JNP5rjjjmtqdNi5cyc5OTlNy8+YMYOpU6cybNgwfvjDHzbp+POf/8zw4cOZOHEi1113XdN6lfBQdtxxXkvww6bjXb1xR/1xR/1RAsXrXKmtrWXmzJl84xvfYMaMGZSVldG3b19iY2OJiYnhuuuu45133vFMn9f+HMlxiXbpsckf9cYdL/yx+59qV6K+Hj75xNeIsGmT77F5s29eI8nJxOXmwqxZvsstRo+GnBxPbqXZGdLS0ryW0Gk6HcNNN0FBQTCkfEVenm+w0QCor69n9erVXHPNNQDMmzePP/7xjwwbNoy3336b+fPn89prr/G9732P733ve1x22WUd6i1xzz33kJaWRn19PVOmTGHTpk2MHj0agPT0dDZs2OC3/Mknn0x+fj4XXXSR36UShw8fbrqso7S0lLfeegsR4aGHHuJXv/oV999//1HbLiwsZN26dXzwwQfk5+e3eOlFQUEB77//PvHx8YwYMYIbbriB2NhYfvrTn7JhwwZSUlI466yzGDNmTLtjVzpO2ocfei3BD5tqlnrjjvrjjvqjBIqXuWKM4ZprriE7O5ubb77ZpyctjcLCwqaxIZ555pmmEwpeYNux9GGlXXps8ke9cccLf7QBwguKi79qaGh83roVGq+FjImBYcNg3Di46qqvGhuOPZbikpKm2w9FKsXFxRqDR1RVVZGXl8fu3bvJzs5m8uTJlJeX88YbbzB79uym5WqcexS/+eabPPvsswBcfvnl7R55+oknnuCBBx6grq6OwsJCtm3b1tQAcckllwS8nubL7tq1i0suuYTCwkIOHz5MVlZWi5+5+OKLiYmJYeTIkRQVFbW4zJQpU0hNTQVg5MiRfP755+zbt48zzjij6Yfx7Nmz2bFjR8Balc5TnJtLxubNXstowqbjXb1xR/1xR/1RAsXLXHn99df5y1/+Qm5uLnl5eQDceuutvPjiixQUFCAiZGVl8ac//ckTfWDfsZSbnMvmcnv02OSPeuOOF/5oA0Qoqa72jcdwZGPDl19+tUyfPr7Ghe98x/ecmwsjR0JiYourjIYvao2BgHsqBJvGMSAqKys577zzeOCBB5g7dy49e/akoB09Mrp169Y0+CP4bjF6JJ999hn33Xcf7777Lr169WLu3Ll+yyUlJQW8vebL3nDDDdx8883k5+ezdu1aFi9e3OJn4pvd5qi1cWCaLxMbG9viGBNK+LHpixnsqlnqjTvqjzvqjxIoXubKqaee2uL39mWXXeaBmpax7Viy6Q822OWPeuOOF/5oA0QwMAY+//zohoYdO3yXVgDEx8OoUTB1qq+RobGxoW/fdm0qGs4WaAze0717d5YtW8bFF1/M/PnzGTJkCE8++SSzZ8/GGMOmTZsYM2YMJ510Ek8//TSXXHIJK1eubPr8sccey7Zt26ipqaGqqorVq1dz6qmn+m3j4MGDJCUlkZqaSlFREf/4xz+YPHlym9pSUlI4dOhQq++XlZUxYMAAAFasWBH0QWZPPPFEbrrpJkpLS0lJSeHpp59uGn1bCQ+2nR2w6XhXb9xRf9xRf5RACWeuyJ1tj9EWyFlac0f4Bp237VjSs/yto964oz0gQoQhiAWprMzXwNC8sWHzZmh+T9chQ3yNCzNnftXYMHRoUAaHjIYvao3BDsaOHcvo0aN5/PHHeeyxx7j++uu5++67qa2t5dJLL2XMmDEsXbqUK664gnvuuYepU6c2Xa4waNAg5syZQ05ODkOGDGHs2LFHrX/MmDGMHTuWE044gUGDBnHKKacEpOvSSy/luuuuY9myZS3esWLx4sXMnj2bXr16cdZZZ/HZZ591zogjGDBgAD/+8Y+ZOHEiaWlpnHDCCU1xK+HBpi9msOt4V2/cUX/cUX+UQLEtV2z6AwnqT1vY5I96444X/kgk3qJywoQJpnFAukB4YusTXPLUJWydv5WRGSPbt7HCQvjPf+Df//Y9tmzx9XgASE39qidD4zgNo0ZBjx7t20Y7KCkpIT09PWTrDwddNYbt27eTnZ0dIkUdo66ujm4uDWOVlZUkJiYiIqxcuZLHH3+c5557LowK26atGDpCeXk5ycnJ1NXVMX36dK6++mqmT5/ut0xL+1NE3jPGTAiqGEtpbx1uQto+01WSnU369u3uC4XxuyusNasNf9Qbd9Qfd7qKP1qL28CyXAmkB0R2UjbbK9z1BK0HhPrThiB7/FFv2pDjoT9udbhL9IAIGGPgs898DQ2NjQ4ff+x7LykJTj4ZZs/2DQ45erTvVpgBJFow6RVhd7xoCY3BHmJjY13ff++991iwYAHGGHr27Mny5cvDpCxw2oqhIyxevJhXX32V6upqzj33XC6++OKgb0NpnV6WDfpp0/Gu3rij/rij/iiBYluu7KiwS4/6445N/qg37njhjzZAALz5Jixb5mt02L3bNy8tDU491Tc45Omn+25xGBfnqUzwXVffs2dPr2V0Co3BHurr6117D5x22mls3LgxjIraT1sxdIT77rsvqOtT2sfBrCx6Nr8FscfYdLyrN+6oP+6oP0qg2JYrWYlZfFJljx71xx2b/FFv3PHCH22A+PRTOP98X+PC2WfDaaf5GhxGjvTdDtMy2nPnAFvRGOwhxsIcby/REIPiT1JhodcS/LDpeFdv3FF/3FF/lECxLVcKa+zSo/64Y5M/6o07XvjTtRsgqqt9l1SIwDvv+AaPtJzq6mriLOiJ0Rk0BnuIxDFgjiQaYlD8qU5LI66y0msZTdh0vKs37qg/7qg/SqDYlitpcWlU1tijR/1xxyZ/1Bt3vPCnSzRAtPoH5eabYcMGeO65iGh8AKLii1pjsAcJ8xgmoSAaYlD8iauo8FqCHzYd7+qNO+qPO+qPEii25UpFvV161B93bPJHvXHHC3+6VN9lodkflT//Gf7wB1i4EPLzvRPVThoaGryW0Gk0BnuIht4D0RCD4k9DkMf06Cw2He/qjTvqjzvqjxIotuVKN7FLj/rjjk3+qDfueOFPl2qAaOKFF+Db34bzzoN77vFaTbuIhj9bGoN3xMbGkpeX1/TYuXNnuz6/dOlSKlvpNub2nhu33347r776qusyq1atYsmSJe1etxKZmBDc2aQz2HS8qzfuqD/uqD9KoNiWK7Filx71xx2b/FFv3PHCH7uaYMLBO+/AnDm+u1o89ZQVd7ZoD8Ee7d8LNAbvSExMpKCgoOl1e88+LV26lCuuuILu3bu36736+vpWb5d51113tbnd/Px88lvpqaSXYEQf3aqqvJbgh03Hu3rjjvrjjvqjBIptuVLVYJce9ccdm/xRb9zxwp+u1QOipgamT4e+fX29IJKTvVbUbmpqaryW0Gk0Bns4dOgQU6ZMYdy4ceTm5vLcc88BUFFRwYUXXsiYMWPIycnhb3/7G8uWLWPPnj2ceeaZnHnmmX7raem95ORkfvCDHzBmzBjefPNN7rrrLk488URycnKYN29e05mvuXPn8tRTTwGQlZXFHXfc0aTngw8+AODhhx9mwYIFTcvfeOONnHzyyRx33HFNn21oaGD+/PmccMIJnHPOOVxwwQVN7ymRRU1qqtcS/LDpeFdv3FF/3FF/lECxLVdSu9mlR/1xxyZ/1Bt3vPCnazU9x8fDI4/AoEG+RogIpKWzy5GGxgA3vXQTBV8WBEeMQ16/PJZOXeq6TFVVFXl5eQAMGTKEJ554gmeeeYYePXqwb98+TjrpJPLz83nppZfo378/L7zwAgBlZWWkpqbyq1/9ijVr1tC7d2+/9d54441HvVdRUcGkSZO4//77ARg5ciS33347AN/85jd5/vnn+frXv36Uxt69e7NhwwZ+//vfc9999/HQQw8dtUxhYSHr1q3jgw8+ID8/nzlz5vD3v/+dnTt3sm3bNvbu3Ut2djZXX311uzxU7KD73r1eS/DDppql3rij/rij/iiBYluu7D1slx71xx2b/FFv3PHCny7RAyI1IZVRvUcR3y0epkyB4cO9ltRhDh065LWETqMxeEfjJRgFBQU888wz1NXV8eMf/5jRo0dz9tlns3v3boqKisjNzeWVV17h1ltv5T//+Q+pHWitjY2NZebMmU2v16xZw6RJk8jNzeW1115j69atLX5uxowZAIwfP77VMSouvvhiYmJiGDlyJEVFRQCsW7eO2bNnExMTQ79+/Y7qpaFEDocGDfJagh82He/qjTvqjzvqjxIotuXKoAS79Kg/7tjkj3rjjhf+dIkeEFOHTuW848+LimvFe/bs6bWETqMx0GZPhXCxcuVKiouLee+994iLiyMrK4vq6mqGDx/Ohg0bePHFF7ntttuYMmVKU++FQElISGga96G6upr58+ezfv16Bg0axOLFi6murm7xc/Hx8YCvAaOurs51GdBBzKKRnh9/7LUEP2yqWeqNO+qPO+qPEii25crHlXbpUX/csckf9cYdL/zpEj0gAEpKSryWEBSiIQ6NwR5KS0vp06cPcXFxrFmzhs8//xyAPXv20L17d6644goWLlzIhg0bAEhJSWn1jJXbe42NDb1796a8vDwkYzOccsopPP300zQ0NFBUVMTatWuDvg0lPJSMGuW1BD9sOt7VG3fUH3fUHyVQbMuVUcl26VF/3LHJH/XGHS/86TINEEdesx6pREMcGoM9XHnllaxfv57c3FweeeQRTjjhBAA2b97MxIkTycvL48477+S2224DYN68eUydOrXFyxvc3uvZsyfXXXcdOTk5nHfeeZx44olBj2XmzJkMHDiQkSNHcsUVVzBu3LgOXTqieE/vLVu8luCHTce7euOO+uNOOP25+uqr6dOnDzk5OU3z9u/fzznnnMOwYcM455xz/O6OtHbtWvLy8hg1ahRnnHFG2HQqLWPbsbSl3C496o87Nvmj3rjjhT8Sid2XJ0yYYNavX9+uzxQXF5ORkREiReEjGuLoqjFs376d7OzsECnqGLW1tcRF2K1oj6R5DOXl5SQnJ1NSUsLEiRN5/fXX6devX0i229L+FJH3jDETQrJBy+hIHQYggEvhinNyyGjrCzqE31319fVMmDCBAQMG8Pzzzzcd7zfeeCPLly+nvLw8ZNtuyx+vvfn1r3/NQw89hIiQm5vLvffey44dO1i4cCENDQ0kJyfz8MMPM3To0OBv3PLcOdKb//f//h8vvPAC99xzT+i9Aev8+fe//01ycjJXXnklW5xt/vCHPyQtLY1FixaxZMkSdu/ezW9/+1sOHDjAySefzEsvvcTgwYPZu3cvffr06fC2tRa3gWW5Ine2rScnOafNP0rmjiAd2+pPG4Ls8Ue9aUOOh/641eEu0wMi0v/wNhINcWgM9hDpjQ/gH8NFF11EXl4ep512Gv/zP/8TssYHJbS0+cUcYn7zm9/4NS5lZGSwfv16SktLPVTlaPHQm927d7Ns2TLWr1/Pli1bqK+vZ/Xq1Vx//fU89thjFBQUcPnll3P33Xd7ptErf1ryZuXKlfzoRz+yxhsIrz+nn346aWlpfvOee+45rrrqKgCuuuoqXn75ZQD++te/MmPGDAYPHgzQqcYHJTh4XYePxLaz2OqPOzb5o96444U/XaYBYt++fV5LCArREIfGYA+1tbVeS+g0zWNYu3YtBQUFbNu2jblz53onSukU+5p12Q43u3bt4oUXXuDaa69tmldUVMTChQu59957PdPViJfeANTV1VFVVUVdXR2VlZUkJSUhIhw8eBDw3bK3f//+nunz0p8jvenfvz8NDQ3WeAPe509RURGZmZkA9OvXjy+//BKAHTt2UFpayuTJkxk/fjyPPPKIlzIVvM+VI8lJtkuP+uOOTf6oN+544U+XuAsGQHp6utcSgkI0xKEx2EO3bpFfAqIhBsWf9FZu0RoObrrpJu69916/AVUff/xx8vPzm/44eYmX3gwYMIBbbrmFwYMHk5iYyLnnnsusWbPo168fF1xwAYmJifTo0YO33nrLM41e+dOSN+eeey7Lly+3xhvwNn+ORESIifGdB6urq+O9995j9erVVFVV8bWvfY2TTjqJ4RF82/RIx6ZcAdhabpce9ccdm/xRb9zxwp8u0wPiwIEDXksICtEQR1eOwbYxV+rr672W0Gm8iMG2/RhtHAjVNfJt8Pzzz9OnTx/Gjx/fNG/Pnj2sXLmSG264wRNNR+KVN+C7a85zzz3HZ599xp49e6ioqOCBBx7g17/+NS+++CK7du3iW9/6FjfffLNnGr3ypyVvHn30UX75y19a4w14mz8Affv2pbCwEIDCwsKmQToHDhzIeeedR1JSEr179+b0009n48aNXkrt8nidK0cytLtdetQfd2zyR71xxwt/ukwDREpKitcSgkI0xNFVY0hISKCkpMSqP6/NRyCPVMIdgzGGkpISEhISwrrdrkTKF194st3XX3+dVatWkZWVxaWXXsprr73GqFGj2LlzJ0OHDiUrK4vKysrQDSIYAF55A/Dqq68yZMgQMjIyiIuLY8aMGWzYsIGNGzcyadIkAC655BLeeOMNzzR65U9L3rz++uts27bNGm/A2/wByM/PZ8WKFQCsWLGCadOmATBt2jTWrVvXdPnK22+/bd2gzV0Nr3PlSL6otkuP+uOOTf6oN+544U+X6btcWVlJjx49vJbRaaIhjq4aw8CBA9m1axfFxcUhUtV+GhoamrrARipexJCQkMDAgQPDus2uRGWfPvT473/Dvt2f//zn/PznPwd844ncd999PP/88xw8eLDpeE9OTubjjz8Ou7ZGvPIGYPDgwbz11ltUVlaSmJjI6tWrycnJ4emnn2bHjh0MHz6cV155xdM/jl7505I3EyZM4IknnrDGGwivP5dddhlr165l3759DBw4kDvvvJNFixYxZ84c/vznP3Psscfy0EMPAZCdnc3UqVMZPXo0MTExXHvttX6371TCj5e1piX6HNOH/1bbo0f9cccmf9Qbd7zwp8s0QMTHx3stIShEQxxdNYa4uDiGDBkSAjUdp6amJuL3RzTEYAsiMhX4DRALPGSMWeKFjviyMi822yo25ZeX3kyaNIlZs2Yxbtw4unXrxtixY/n2t7/N0KFDmTlzJjExMfTq1Yvly5d7ptErf1ryZt68efTt29cabyC8/jz++OMtzl+9enXTdE1NTdP0woULWbhwYch12Y7W4ZYpq7NLj/rjjk3+qDfueOFPl2mAqKurs+pHZEeJhjg0BnuIhjiiIQYbEJFY4H+Bc4BdwLsissoYsy3cWuoSEz3/gp48eTKTJ0/26WmWY+Xl5R6q8t6bO++8kzvvvLPpdUVFBdOnT2f69OmeaWqOl/4c6Q3AhRdeyJw5czzR0xJe58+RaP32R+tw6yTGJFKGPXrUH3ds8ke9cccLf7pMA4SIeC0hKERDHBqDPURDHNEQgyVMBD42xnwKICIrgWlA2H/4imWDo9qUY+H0Ru5sO+6MuAyKa90vKzN3hG/cG/XHnUjzJ5zeWILW4VaoN3bpUX/csckf9cYdL/zpMg0QkX6deyPREIfGYA/REEc0xGAJA4DmIxHtAiZ5ISSmri5s2wrkT1Kvbr0orSt1XSZcf5TC6U0g1Bm79Kg/7qg/1tMl63Ag2JYr6o87Nvmj3rjjhT9i04j8gSIixcDn7fxYb2BfCOSEm2iIQ2Owh2iIw6YYjjXGZHgtoiOIyCxgqjHmWuf1N4FJxpgFzZaZB8xzXo4APgyRHJv2KdilxyYtoHraQvW4Eyo9EVmLA6nDzvxw1OKukisdRfW4Y5Mem7RA19HTah2OyB4QHflSEZH1xpgJodATTqIhDo3BHqIhjmiIwRJ2A4OavR7ozGvCGPMA8ECohdi2T23SY5MWUD1toXrcsU2PBbRZhyE8tdi2faN63FE9rWOTFlA9ANp3WVEURQF4FxgmIkNE5BjgUmCVx5oURVG6ElqHFUWJeiKyB4SiKIoSXIwxdSKyAPgnvtu/LTfGbPVYlqIoSpdB67CiKF2BrtQAEfJuw2EiGuLQGOwhGuKIhhiswBjzIvCi1zqwb5/apMcmLaB62kL1uGObHs/ROtwqqscd1dM6NmkB1ROZg1AqiqIoiqIoiqIoihJZ6BgQiqIoiqIoiqIoiqKEnC7RACEiU0XkQxH5WEQWea3nSERkp4hsFpECEVnvzEsTkVdE5CPnuZczX0RkmRPLJhEZ12w9VznLfyQiV4VY83IR2SsiW5rNC5pmERnvePKx81kJYxyLRWS3sz8KROSCZu/9yNH0oYic12x+iznmDCT1tjP/b86gUsGOYZCIrBGRbSKyVUS+58yPmP3hEkNE7QvFnbZqsYgMdvLgfSc329zfodARTi3t0SUix4rIakfPWhEZ2Oy9oNX/AP0Ji5b26GpNk4jkicibTm3ZJCKXhEpDuHS0V5fb/nLe7yEiu0Tkd6HUEU4tSutoLe6crnDUP63DndMRTi3t0RWO+hcRddgYE9UPfIP4fAIcBxwDbARGeq3rCI07gd5HzLsXWORMLwJ+4UxfAPwDEOAk4G1nfhrwqfPcy5nuFULNpwPjgC2h0Ay84ywrzmfPD2Mci4FbWlh2pJM/8cAQJ69i3XIMeAK41Jn+I3B9CGLIBMY50ynADkdrxOwPlxgial/ow3Uft1mL8V2HeH2zfbzTbX+HSke4tHTAnyeBq5zps4C/ONNBq//t8CfkWoLoz3BgmDPdHygEenrgTVB0BNObZu//Bvgr8LtQ6giXFn10Ol+0FntYi4NQa6K2DgfJn6itxZ31Jlg62np0hR4QE4GPjTGfGmMOAyuBaR5rCoRpwApnegVwcbP5jxgfbwE9RSQTOA94xRiz3xhTCrwCTA2VOGPMv4H9odDsvNfDGPOW8R0FjzRbVzjiaI1pwEpjTI0x5jPgY3z51WKOiYjgO6ifcj7f3JOgYYwpNMZscKYPAduBAUTQ/nCJoTWs3BeKK4HUYgP0cKZTgT3OdGv7O1Q6wqWlvbpGAq8502uavR/M+h+oP+HQ0l5dLWoyxuwwxnzkTO8B9gIZIdIQDh0d0dXa/kJExgN9gZfDoCNcWpTW0VrceV2hrn9ahzuvI1xa2qsr1PUvIupwV2iAGAB80ez1Ltz/2HiBAV4WkfdEZJ4zr68xptCZ/hJfIkDr8dgQZ7A0D3Cmj5wfThY43ZKWi3PpAu2PIx04YIypO2J+yBCRLGAs8DYRuj+OiAEidF8oRxFIjVoMXCEiu/CNAn9DOz4bTB3h0tJeXRuBGc70dCBFRNKDrCnQdYVDS3t1taapCRGZiO+s0Cch0hAOHR3R1aImEYkB7gduCZOOcGlRWkdrced1hbr+aR3uvI5waWmvrlDXv4iow12hASISONUYMw44H/iuiJze/E3nrLPxRFkHiUTNzfgDcDyQh69b1v2eqgkQEUkGngZuMsYcbP5epOyPFmKIyH2hdJjLgIeNMQPxXSr0F+fLsKtraeQW4AwReR84A9gN1KuWJlw1Ob25/gJ8yxjT0AV0BKJpPvCiMWaX24ejWIvSMjbVP5u0NGJL/bNFR3Nsqn82aWlLU7jrn6c6uoVy5ZawGxjU7PVAZ541GGN2O897ReQZfN1nikQk0xhT6Bwge53FW4tnNzD5iPlrQyz9SIKlebczfeTyYcEYU9Q4LSIPAs87L91yqaX5Jfgub+jmnHkPWRwiEofvj/tjxpi/O7Mjan+0FEMk7gulVQKpxdfgdBM1xrwpIglA7wA/G0wd4dLSLl1OV9EZ0NRYN9MYc0BEgln/A4ovTFrapas1Tc7rHsALwE+cS89CoiFMOtqty2V/fQ04TUTmA8nAMSJSbozpyIDdnc2dYGpRWkdrcSd1haH+aR3upI4wammXrjDUv8iowyYEA0vY9MDXyPIpvgFqGgfjGOW1rmb6koCUZtNv4Cu0v8R/AMF7nekL8R9A8B1nfhrwGb7BZno502kh1p6F/+CNQdPM0YMeXhDGODKbTX8f3zWGAKPwH/DoU3yDvbSaY/gGeWk+8OH8EOgXfOMyLD1ifsTsD5cYImpf6MN1H7dZi53cmutMZ+O71lda29+h0hEuLR3wpzcQ40zfA9zlTAet/rfDn5BrCaI/xwCr8fWsCqmGcOgIpjdHLDOXzg1C2Sl/gqlFH53OF63FHtbiINSaqK3DQfInamtxZ70Jlo42dYZipbY98HXZ2oHv+p6feK3nCG3HOcmxEdjaqA/fNeurgY+AV/nqj6AA/+vEshmY0GxdV+MbhOdjfN2JQqn7cXxd4mvxXV90TTA1AxOALc5nfgdIGOP4i6NzE7AK/z/BP3E0fUizO0G0lmPO/n3Hie9JID4EMZyK7/KKTUCB87ggkvaHSwwRtS/00eZ+PmrfAHcB+c70SOB1fPWwADi3rf0dLB1eaWmnP7Oc43kH8FDzHG7t2A2hP2HREgx/gCvw1fiCZo+8cHsTTB3BzJ1m65hLJ39sdjZ3gqlFH53KF63FHtfizh5LwdIRLG8Icv3rjD/B1hKs3Gm2jrl0rjHY+joszgYURVEURVEURVEURVFChteDuCiKoiiKoiiKoiiK0gXQBghFURRFURRFURRFUUKONkAoiqIoiqIoiqIoihJytAFCURRFURRFURRFUZSQow0QiqIoiqIoiqIoiqKEHG2AUBRFURRFURRFURQl5GgDhKIoiqJ0AUQkS0S2BGE9k0Xk5GBoCgci8rCIzHKmHxKRkV5rUhSla6J1WOuwAt28FqAooUBEkoAngIFALPBT4GPgV0AysA+Ya4wpFJGhwB+BDKAemA1UAn8DeuA7Tq43xvwn3HEoiqJYyGSgHHjDYx3txhhzrdcaFEVRgsBktA4rEYr2gFCilanAHmPMGGNMDvAS8FtgljFmPLAcuMdZ9jHgf40xY4CTgULgcuCfxpg8YAxQEF75iqIoIaGbiDwmIttF5CkR6Q4gIuNF5F8i8p6I/FNEMp35N4rINhHZJCIrRSQL+A7wfREpEJHTmq9cRBaLyAoR+Y+IfC4iM0TkXhHZLCIviUhcG9u7TkTeFZGNIvJ0M30Pi8gyEXlDRD5tPJPWEuLjdyLyoYi8CvRp9t5aEZngTE8VkQ3OtlY785JEZLmIvCMi74vItOBZryiKAmgd1jrcxdEGCCVa2QycIyK/cArzICAHeEVECoDbgIEikgIMMMY8A2CMqTbGVALvAt8SkcVArjHmkBdBKIqiBJkRwO+NMdnAQWC+82O0tQbaRcBYY8xo4DvGmJ34eoz92hiT10rPsOOBs4B84FFgjTEmF6gCLmxje383xpzoNAhvB65ptt5M4FTgImCJS4zTnThHAlfia1j2Q0QygAeBmc62Zjtv/QR4zRgzETgT+KX4etQpiqIEC63DaB3uyuglGEpUYozZISLjgAuAu4HXgK3GmK81X85pgGjp8/8WkdOBC4GHReRXxphHQq1bURQlxHxhjHndmX4UuBFfD7HGBlrwXbZW6CyzCXhMRJ4Fng1wG/8wxtSKyGZnXS858zcDWfh+lLa2vRwRuRvoie9yuX82W++zxpgGYJuI9HXZ/unA48aYemCPiLzWwjInAf82xnwGYIzZ78w/F8gXkVuc1wnAYHw/whVFUYKB1mEfWoe7KNoAoUQlItIf2G+MeVREDgDzgQwR+Zox5k2n5Xe4MWariOwSkYuNMc+KSDy+IpwB7DLGPOjMGwdoA4SiKJGOaeG10EIDrcOF+H5Ifh34iYjkBrCNGgBjTIOI1BpjGrfZgO93h9v2HgYuNsZsFJG5+K5z9luvgwSgoyMIvrNxH4Zo/YqiKFqH3dE6HOXoJRhKtJILvONcbnEHcDswC/iFiGzEN6ZDY3ewbwI3isgmfIP59MNXbDeKyPvAJcBvwileURQlRAwWkcYfnJcD64APcRpoAUQkTkRGiUgMMMgYswa4FUjFdzbsENBi77EAaXF7znspQKHTSPyNDq7/38AlIhLrXNN8ZgvLvAWcLiJDHA1pzvx/AjeIc0pQRMZ2UIOiKEpraB32oXW4i6I9IJSoxBjzT/y7jDVyegvLfoTvOrnmfAqsCIE0RVEUL/kQ+K6ILAe2AX8wxhx2BhNbJiKp+H4bLAV2AI868wRYZow5ICL/BzzlDAx2Q3vvEOSyva3A/wBvA8XOc0d+YD+Dr6ZvA/4LvNmChmIRmQf83fmBvxc4B98dk5YCm5z5n+G71llRFCVYaB1G63BXRr7qkaMoiqIoiqIoiqIoihIa9BIMRVEURVEURVEURVFCjl6CoSiKoihKxOEMxPaXI2bXGGMmeaFHURSlq6F1WOkIegmGoiiKoiiKoiiKoighRy/BUBRFURRFURRFURQl5GgDhKIoiqIoiqIoiqIoIUcbIBRFURRFURRFURRFCTnaAKEoiqIoiqIoiqIoSsjRBghFURRFURRFURRFUULO/wdy8uN7dgMKAQAAAABJRU5ErkJggg==\n", 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" ] @@ -1069,7 +1016,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": { "vscode": { "languageId": "python" From cc9349563dbcf935ece1f487e8ac3cb338fb8023 Mon Sep 17 00:00:00 2001 From: Yuchen Xu Date: Mon, 4 Jul 2022 21:34:08 -0700 Subject: [PATCH 12/12] addressed style comments --- acceleration/fast_training_tutorial.ipynb | 14 +++++++++----- 1 file changed, 9 insertions(+), 5 deletions(-) diff --git a/acceleration/fast_training_tutorial.ipynb b/acceleration/fast_training_tutorial.ipynb index 6b6c1d3cdb..dcfe2d295b 100644 --- a/acceleration/fast_training_tutorial.ipynb +++ b/acceleration/fast_training_tutorial.ipynb @@ -247,7 +247,10 @@ "# if profiling = True, it is recommended to set max_epochs = 6 for faster prototyping\n", "# to see the trend in training curve and dice results, set max_epochs to be larger (600)\n", "# note that before optimization, training can be quite a bit slower\n", - "max_epochs = 6 if profiling else 600\n", + "if profiling:\n", + " max_epochs = 6\n", + "else:\n", + " max_epochs = 600\n", "\n", "# to improve readability\n", "\n", @@ -788,6 +791,7 @@ "\n", "And a display of one training epoch of MONAI optimized training when zoomed in:\n", "![png](figures/nsys-epoch-short.png)\n", + "\n", "Notice that the per-epoch time is >20 times faster than the regular PyTorch training." ] }, @@ -809,7 +813,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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", 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" ] @@ -877,7 +881,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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", 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" ] @@ -931,7 +935,7 @@ "outputs": [ { "data": { - "image/png": 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H888/nxUrVvA///M/tLe3M3r0aH7+85+z7777Yozh/PPP5+GHH6asrIybb76ZJUuW5E1vFGXlTldijnGp1zQbfPChHtzBBx8+ePCFjo4OKisrs/5j5tIXF3BLT760iAiVlZUD/oLq2vk3EvScccYZPPLII9tt37BhA3/5y1+YOXNm77YLL7yQFStWsGLFCq644gre//73M3nyZFatWsWvf/1rnnvuOV566SUeeugh1q1b1/u+r3zlK73vy1XnA7hXXr4wHG2xS+0ejEw9mbbD4N655JKefGspLi7mJz/5CatXr+bZZ5/l+uuvZ/Xq1Vx00UV873vf47nnnuPSSy/loosuAuDPf/4za9euZe3atfzqV7/i3HPPzaveKMrKndqRY7q7u6OWMCz44EM9uIMPPnzw4BPD8aUsOTvPHVzSk08tmZSla+ffSNDzgQ98gMmTJ2+3/Stf+QpXXnllv+V25513ctxxxwGwZs0a9ttvP8rKyiguLuaDH/wgf/jDH4Zd60C4Vl4+kW1b7FK7ByNXT6bl6Nq55JKefGvZaaedekcwTJgwgXnz5rFp0yZEhObmZrq7u2lqamLatGkAPPDAA5x22mmICPvvvz+NjY1s3pyTazL0SRRlNWI6IEpLS6OWMCz44EM9uIMPPnzwoITJ5otzUVERixcvZuHChXz84x+nsbFx2PV86EMfYtmyZUM+3v3338/q1asH/b4HH3yQK6+80rrP22+/zSc/+cmhShs0rp1/I1XPAw88wPTp09lrr736fL29vZ1HHnmEE044AYCFCxfy1FNPUVdXR3t7Ow8//DAbNmzo3f9nP/sZe+65J2eeeSYNDQ050+1aeSlbybYDY7jb4r70aFu8FdfOJZf0RKll/fr1vPjii+y3335cc801XHjhhcyfP5+vfe1rXHHFFQBs2rSJGTNm9L6nurqaTZs25U1jFPmMmA6Itra2qCUMCz74UA/u4IMPHzx4i8iQbqOKivp+LQPGjh3LihUrWLVqFZMnT+b666/P2kYikcjq/T09PaHnti+98Xi83+McddRRXHjhhdbPmjZtGvfee+/gRQ4R186/kainvb2dyy+/nEsvvbTfff74xz/yvve9r3ehsXnz5vH1r3+dQw45hMMOO4zFixf3zmc/99xzef3111mxYgU77bQTX/3qV3Om3bXy8pbhbIcjaouzbYdB2+J84pKeqLS0trZy3HHHcc011zBx4kRuuOEGrr76alauXMnVV1/NWWedFYmubYkinxHTATFx4sSoJQwLPvhQD+7ggw8fPCi54b3vfW/vrwivv/46hx12GPvssw/vf//7efXVV3u377///ixatIhvf/vbjB8/HoAnnniCj33sY0Dyl7zzzjuPm2++ebvPOPfcc1m6dCkLFizge9/7Xu/2WbNm8fWvf50lS5bwu9/9rnf7v/71Lx588EEuvPBCFi9ezOuvv86HPvQhvvzlL7N06VKuvfZa/vjHP7Lffvux995789GPfpR3330XgJtvvpnzzz8fSK4D8KUvfYkDDjiAXXfdtfeL7vr161m4cGHv/sceeyyHHXYYc+bM6Z1vCnDjjTey++67s++++3L22Wdz3nnnDSlj186/kajn9ddf580332SvvfZi1qxZbNy4kSVLlvDOO+/07nPXXXdx0kknhfScddZZvPDCC/zjH/+goqKC3XffHYAdd9yRoqIiRo0axdlnn81zzz2XM+2ulZeSG4ajLU51kGlb3DeunUsu6YlCS3d3N8cddxynnHIKxx57LAC33HILxx57LBMnTuT444/vbVunT58eGoG2ceNGpk+fnjetUeQzYjogcjmEMJ/44EM9uIMPPnzwoAw/PT09PPbYYxx11FEAnHPOOfz0pz/lhRde4KqrruLzn/88AOeffz7nn38+K1eupLq6ut9j9cdll13GsmXLePnll3nyySd5+eWXe1+rrKxk+fLlnHjiib3bDjjgAI466ih+/OMfs2LFCmbPng1AV1cXy5Yt46tf/SoHHnggzz77LC+++CInnnhiaKhv+rzjzZs38/TTT/PQQw9x8cUX96lvxYoV3H333axcuZK7776bDRs28Pbbb/ODH/yAZ599ln/+85+9/wAMBdfOv5GoZ9GiRWzZsoX169ezfv16qqurWb58OVOnTgWgqamJJ598kqOPPjqkZ8uWLQD897//5Q9/+AMnn3wyQGju8X333df7T1QucK28lOFnuNpiWzsM2ha7di65pCffWowxnHXWWcybN48LLrigd/u0adN48sknaWho4O9//ztz5swBkiNqbr31VowxPPvss5SXl7PTTjvlTW8UZTViLsNZWVk54D5tXW2s2rKK/ar3y4OioZGJD9dRD+7ggw8fPCjDRywWY/HixWzatIl58+Zx8MEH09rayr/+9S+OP/743v06OzsBeOaZZ7j//vsBOPnkk/na17623TGLi/v/U3nPPffwq1/9ing8zubNm1m9ejV77rknAJ/61Kcy1p2+78aNG/nUpz7F5s2b6erqCl1+LX216mOOOYZRo0Yxf/783l/mtuWggw6ivLwcgPnz5/PWW29RW1vLBz/4wd6FDI8//nj+85//ZKw1HdfOv5Gg56STTuKJJ56gtraW6upqvv/971uH8t53330ccsghjBs3jnHjxvVuP+6446irq6OkpITrr7+eSZMmAXDRRRexYsUKRIRZs2bxy1/+ctg9pHCtvJThY7jbYls7DNoWu3YuuaQn31r++c9/ctttt7Fo0SIWL14MJC9n/Otf/5rzzz+feDxOaWkpv/rVrwA44ogjePjhh9ltt90oKyvjt7/9bV71RlFWI6YDoqampvea1ineaX2HB197kBfefoHVtat5+r9PU1ZSxpvnv8kO43aISKmdvnwUGurBHXzw4YMHZfhIzTtub2/n0EMP5frrr+eMM85g0qRJrFixIuPjFBcX98457u7u7vMyaG+++SZXXXUVzz//PBUVFZxxxhmh/dL/2RuI9H2/+MUvcsEFF3DUUUfxxBNPcMkll/S+lj4POjWfH/pfkT19n6KiIuu85qHg2vk3EvTceeed1tfXr18fen7GGWdwxhlnbKfnqaee6vP9t912W9YaM8W18lKGj+Fui7u7uykpKdG2uB9cO5dc0pNvLQceeGC/9eCFF17YTo+IDMt6VUMlirIaMVMwUsHeu/pevvP37/DRWz/KjKtn8LmHPsfv1/yehEnw5f2+zAMnPuBs5wPgzMmcDerBHXzwMWQPxkAiAfE4dHdDVxd0dEAsBu3tycdKwVJWVsZ1113HT37yE8rKythll1165/8aY3jppZcA2H///fn9738PJOfJp9h5551ZvXo1nZ2dtLW18dhjj233Gc3NzYwbN47y8nLeffdd/vznP2ekbcKECbS0tPT7elNTU+/8z1tuuSX02nBcr/s973lP7zDQeDze638ouNaGjGg9GSwsWLXDDgPvl0dcKy9l+BmutjiRSNDY2KhtcT+4di65pEfbYTtRlNWIGgFRL/Uc/7vksK89puzBJ/b4BBcecCHvmf6eiNVljks9ikNFPURALAYvvADPPgsbNvT+0x1rbWVsUdHWf8JT993d0NOT/Ac99Y/6tvfbbsvnLe0zEz09yZ7UPl7r93Em1+8+7DDI8EuM4iZ77703e+65J3feeSd33HEH5557Lj/84Q/p7u7mxBNPZK+99uKaa67h1FNP5bLLLuOwww7rHSI7Y8YMTjjhBBYuXMisWbPYe++9tzv+Xnvtxd57780ee+zBjBkzeN/73peRrhNPPJGzzz6b6667rs9V0i+55BKOP/54Kioq+MhHPsKbb77Z+9pwrAQ/ffp0vvnNb7LvvvsyefJk9thjj17fg8W1tlD12KlZtIiqlSujltGLa/kouWG42uJddtlF2+J+cO1cckmPS1pA22EA6W+IiMssXbrUDPa6vwmTYM5P5/Dfpv/y8v+8zLyqeTlSpyhDwJjkP/9dXVs7AGyPW1qgsRGamrbepz/e9j69h7+8HEpKkrfi4v7vi4pg1KjkTaTv+9TjfN7SP3Pbz+/vtaE83nVXGOQ1vEXkBWPM0uGrGO7SVzu8Zs0a5s0rrLa1vb2dsWPHIiLcdddd3HnnnTzwwANRy8o5ra2tjB8/nng8zic+8QnOPPNMPvGJT2y3XyGW6YhluH41K8DvhduibXHhnbfaFvffFhdieY5YtB3uxdYOj5gREE+89gRvNLzBb4/+bUF3PtTX1/cuVlOoFJyHRALWroV//xtWr4bOTjpaWigdNWrgjoJtH/f3end3dhqLimDSpGTnQup+zpzkfXk5TJ4MixfDfvvBjjv2vq3gyqIPfPCghInH4wMuODZcvPDCC5x33nkYY5g0aRI33XRTpHoGYri0XHLJJfztb3+jo6ODQw45hGOOOWZIx3Ht/FM9durnzmXya69FLaMX1/JRtpLvdm+gttildhi0LR4Il/S4pAW0HYYR1AHxeuvrAHxw5w9GrCQ7hjo0yyWc91BXl+xs+Pe/k1MWnnsuOZIAkqMDSksZU1ICo0dvHUmQepy+bexYmDix/9cHetzf6yUlyeOmdzaUlQ2p19X5ssgAHzwoYVLXe88H73//+3vnIPdHPvUMxHBpueqqq4blOK6df6rHTvkbb0QtIYRr+ShbyXe7N1Bb7FI7DNoWD4RLelzSAtoOwwjqgKhpqQGgYmxFxEqyo7W11bkTabA45aGzE774RXj88a3PN2xIPh41ChYuhOOPh/33T44e2GMPKCqiuanJHQ9Z4FRZDBEfPChhenp6nPqlyyU9LmkB984/1WOndfp0yre5SkaUuJaPshXX2hrVY8e1c8klPS5pAW2HYQR1QHSa5HWGx48eH7GS7Bg7dmzUErLGGQ/NzfCJT8Df/w7HHJMcRVBUBAsWJDsbli6F8X3XF2c8ZIkPPnzwoIQZjtXFhxOX9LikBdw7/1SPnbG1tVFLCOFaPspWXGtrVI8d184ll/S4pAW0HYYR1AHRFGtiTNEYikcVtuWuri5Gjx4dtYyscMLDu+/CEUfAyy/DrbfCpz89qLc74WEY8MGHDx6UMK4tjuySHpe0gHvnn+qx0zVxIqNbW6OW0Ytr+Shbca2tUT12XDuXXNLjkhbQdhhGUAdEt+mmtLg0ahlZ49ocuKEQuYc334RDDoFNm+DBB+Hwwwd9iMg9DBM++PDBgxJG8nwN7IFwSY9LWsC980/12Cnq7IxaQgjX8lG24lpbo3rsuHYuuaTHJS2g7TCAW+OHckh3TzclRSVRy1Ci5qWX4IADoL4+OfViCJ0PiqK4S1FREYsXL+69rR/kPMtrrrmG9vb2Qb9m47vf/S5/+9vfrPs8+OCD/OhHPxr0sRVFUVxE22JFUfpjxIyA6OrpomRU4XdA9PT0RC0hayLz8OSTcNRRyStI/P3vkMU1lX0oB/DDhw8efEW+P7y/EJnvDTzkdezYsaxYsWLIn3HNNddw6qmnUlZWtvVzg6G2fb2Woqenp99fES699NIBP/eoo47iqKOOGnA/14b9unb+qR47PWPGRC0hhGv5+IoPbXF626dt8fa4di65pMclLaDtMIygERAJEl6MgHBpDtNQicTDfffBoYfC9Onwr39l1fkAfpQD+OHDBw9K7mhtbeWggw5iyZIlLFq0iAceeACAtrY2jjzySPbaay8WLlzI3XffzXXXXcfbb7/Nhz/8YT784Q/3HkNE+nxt/PjxfPWrX2WvvfbimWee4dJLL+U973kPCxcu5Jxzzun9gnrGGWdw7733AjBr1iy+973v9ep59dVXAbj55ps577zzevf/0pe+xAEHHMCuu+7a+95EIsF5553HHnvswcEHH8wRRxzR+1pUuHb+qR47o5ubo5YQwrV8lNyRbVucmvKgbXHfuHYuuaTHJS2g7TCMoA6Ijq4OL0ZAxGKxqCVkTd49/PrX8MlPwt57w1NPwYwZWR/Sh3IAP3z44EEZPmKxWO+Q30984hOUlpZy3333sXz5ch5//HG++tWvYozhkUceYdq0abz00kusWrWKww47jC996UtMmzaNxx9/nMdTl+Yl+WWzr9fa2trYb7/9eOmllzjwwAM577zzeP7551m1ahWxWIyHHnqoT41Tpkxh+fLlnHvuuf1eA37z5s08/fTTPPTQQ1x88cUA/OEPf2D9+vWsXr2a2267jWeeeWaY0xs8rp1/qsdObMqUqCWEcC0fZfgY7rY4kUgAaFvcD66dSy7pcUkLaDsMI6gDwowyXoyAGN/PZSELibx5MAZ++EM455zk6Ie//Q0qK4fl0D6UA/jhwwcPAyEiN4nIFhFZ1cdrXxURIyJTguciIteJyDoReVlElqTte7qIrA1up6dt30dEVgbvuU5cW11rEKSG/a5YsYL77rsPYwzf/OY32XPPPfnoRz/Kpk2bePfdd1m0aBF//etf+frXv85TTz1lvQZ2f8N5i4qKOO6443qfP/744+y3334sWrSIv//977zyyit9vu/YY48FYJ999ul3XvQxxxzDqFGjmD9/Pu+++y4ATz/9NMcffzyjRo1i6tSpoVEaUZGL8+/MM89khx12YOHChb3bvvOd77DnnnuyePFiDjnkEN5++20AfvzjH/f+k7Nw4UImT55MfX197/t6enrYe++9+djHPta7zRjDt771LXbffXfmzZvHddddN+weUrjWPo3ftClqCSFcy0cZPoa7LbYtlKdtcX7PpQ0bNvDhD3+Y+fPns2DBAq699tre137605+yxx57cMABB3DRRRf1br/iiivYbbfdmDt3Lo8++mjetIJ77Yy2wyOoA6K9s92LERBNTU1RS8iavHioqYHzzoPvfCd5ic0HHoBx44bt8D6UA/jhwwcPGXAzcNi2G0VkBnAI8N+0zYcDc4LbOcANwb6Tge8B+wH7At8TkYrgPTcAZ6e9b7vPKlTuuOMOampqeOGFF1ixYgU77rgjHR0d7L777ixfvpxFixbx7W9/2zo3uL/5kaWlpb1fijs6Ovj85z/Pvffey8qVKzn77LPp6Ojo831jgvmfRUVFxONx6z4Qnmuc+hXQFXJx/p1xxhk88sgjoW0XXnghL7/8MitWrOBjH/tYb3ldeOGFvf/kXHHFFRxwwAFMnjy5933XXnst87aZcnfzzTezYcMGXn31VdasWcOJJ5447B5SuNY+Ne26a9QSQriWj5I7sm2LbfPUtS3O77lUXFzMT37yE1avXs2zzz7L9ddfz+rVq3n88cd54IEHeOmll3jqqaf42te+BsDq1au56667eOWVV3jkkUf4/Oc/n9d1B1xrZ7QdHkEdEFIkXoyASP9iVajkzMP69XD11fDBD8LUqfDzn8NXvwo33wwlw1v2PpQD+OHDBw8DYYz5B1Dfx0tXAxcB6athHQ3capI8C0wSkZ2AQ4G/GmPqjTENwF+Bw4LXJhpjnjXJb1e3Asfk0E5eaWpqYocddqCkpITHH3+ct956C4C3336bsrIyTj31VC688EKWL18OwIQJE2hpaQkdo7i4uN/XUqS+4E6ZMoXW1taczAd+3/vex/33308ikeDdd9/liSeeGPbPGCy5OP8+8IEPbHfciRMn9j5ua2vr8xJ4d955J6eddlrv840bN/KnP/2Jz372s6H9brjhBr773e8yalTyK9AOO+wwnPJDuNY+TX7ttaglhHAtHyV3ZNsWp9rhvl5LR9vi3LPTTjuxZElycOWECROYN28emzZt4oYbbuDiiy9mzJgxTJ48ubdtfeCBBzjxxBMZM2YMu+yyC7vtthvPPfdc3vS61s5oOzyCOiDaO9opHlX4F/2oqamJWkLWDJsHY+Dll+H730+u77DLLnDBBdDQAN/+NqxYAVddBaOGv5r7UA7ghw8fPAwFETka2GSMeWmbl6YDG9Kebwy22bZv7GO7F5xyyiksW7aMRYsWceutt7LHHnsAsHLlSvbdd18WL17M97//fb797W8DcM4553DYYYeFhtR2d3f3+1qKSZMmcfbZZ7Nw4UIOPfRQ3vOe9wy7l+OOO45p06Yxf/58Tj31VJYsWWKdOpIP8nn+fetb32LGjBnccccd2/1K2t7eziOPPMIHP/jB3m1f/vKXufLKK3s7GlK8/vrr3H333SxdupTDDz+ctWvX5kyza+1TzaJFUUsI4Vo+Su7Iti1OtcN9vZaOtsX5Zf369bz44ovst99+/Oc//+Gpp55iv/3244ADDuD5558HYNOmTcxIW3+turqaTXmchuBaO6PtMMnhRIV222effcxg+cgtHzHvu/F9g36f4hg9PcY89ZQxF1xgzK67GgPGiBhz4IHGXHWVMevWRa1QGcEAy0yO2j1gFrAqeFwG/BsoD56vB6YEjx8CDkx732PAUuBrwLfTtn8n2LYU+Fva9vcDD/Wj4RxgGbBsxowZJhaLmba2NtPa2mo6OjrMqlWrTCKRMN3d3SaRSJiuri5jjAndp78ej8dNT0+Picfjocc9PT29+3R3d293DGNM6PX09w3HMbbV45KnhoYGk0gkzDvvvGN23XVX89///jennl555RXT1NRkOjo6TGtrq2lrazOxWMw0Nzebrq4u09DQYHp6ekxtba0xxpgtW7aE7uvq6kw8HjeNjY2ms7PTtLS0mPb2dtPe3m5aWlpMZ2enaWxsNPF43NTV1fW+98033zR77LGHMcaY2traXu9dXV3me9/7nvnmN78Zqns33XSTOfLII019fb1JJBLmjjvuMOeee67ZsmWLefzxx83BBx9sEomEqa+vN+PGjTM//OEPTUdHh7njjjvMAQcckBdP6ffbempubt7ufGpqajLd3d29nmpqakLHqKmp6fXU3d1tmmbONB3l5aZ16lTTVlVlYhUVprm62nSVlZmG2bNNT1GRqZ03zxgwWxYtCt3XzZ1r4iUlpnHWLLc8DbHu5bItdu3W13fi1atXb7dNGV5aWlqMMcl6v+uuu5rNmzfn7LNcLc+WlhazZMkS8/vf/94YY8yCBQvMeeedZxKJhPn3v/9tZs2aZRKJhPnCF75gbrvttt73nXnmmeZ3v/tdVLJzS/Ln0exvHmBrhwt/SECGtHe0UzqmNGoZWVNTU0NVVVXUMrJiSB7eegt++9vk7b//hdGj4aMfhYsvhqOOgh13zI3YfvChHMAPHz54GAKzgV2Al4Kh6NXAchHZF9gEpF/qpTrYtgn40Dbbnwi2V/ex/3YYY34F/Apg6dKlprQ03KaOGjUKEekdKlsSTH3a9j71en+LinV3d2+3b3/HSB+Wuy2pX76zOca2eobqabj0HH300TQ1NdHV1cV3vvOd3l+VBuvJpiP9WCLSO/0hfS50quy7u7sZNWoUlcECv6lzMXWfGtqZ+nWwr8t9pbal9q2qqqKtra03y9SxJ02aBCQXqTziiCO47LLLeo/x4IMPcvLJJxOPxxERVq5cyYMPPsjDDz9MR0cHzc3NfPrTn+b222+nurqak08+mTFjxnDSSSdx7rnnUlpa2usp9TnD4Sk1z3nbY2zrqaSPaYKpvCsqkku1TAlWTk8dI/U89frE/yaXghmTNp+3tKEh+Tmvvw5AIijzqpUrQ/epIcHl69fD6NEZl1O2npLfUS2eLHVvoHJSsiO93XMB1/QceeSRobZ46tSpkerJ93eh7u5ujjvuOE455ZTexTyrq6s59thjERF22WUXRo0aRW1tLdOnT2fDhq0DMDdu3Mj06fkbaOna98SaRYt6214XiCKfEdMBQRFeLELp0gk0VDL20NkJDz4Iv/kN/PWvyW0HHww/+hEceSSkzQnONz6UA/jhwwcPg8UYsxLonbguIuuBpcaYWhF5EDhPRO4iueBkkzFms4g8ClyetvDkIcA3jDH1ItIsIvuTHFVxGvDTfPrZFpe+ZIJbep588smoJYTI1/m3du1a5syZAyTnE6eGb0NybvmTTz7J7bffzrhgseErrriCK664AoAnnniCq666ittvvx1Irmr/+OOPs8suu/Dkk0+y++6750y3a+2TS196wb18lK241O6Be3pGalsMyY7Ds846i3nz5nHBBRf0bk+1rR/+8IdpaGigq6uLKVOmcNRRR3HyySdzwQUX8Pbbb7N27Vr23XffvOl1rZ3RdngEdUDEOmNMHuvWIiRDoa6urre3v1AZ0MOqVXDjjXDbbVBXBzNnwne/C5/5DOy8c/6EWvChHMAPHz54GAgRuZPk6IUpIrIR+J4x5sZ+dn8YOAJYB7QDnwEIOhp+ADwf7HepMSa1sOXnSV5pYyzw5+AWGfF4PKNf8POFS3pc0gK5Of9OOukknnjiCWpra6murub73/8+Dz/8MK+99hqjRo1i55135he/+EXv/vfddx+HHHII48aNy0jPxRdfzCmnnMLVV1/N+PHj+c1vfjOs+tNxrX2qmzePyjVropbRi2v5KFtxra1RPXbyeS7985//5LbbbmPRokUsXrwYgMsvv5wzzzyTM888k4ULFzJq1ChuueUWRIQFCxZwwgknMH/+fIqLi7n++uutowWHG9faGW2HQVLD3wqJpUuXmmXLlg3qPYt/sZidJ+3MAyc+kCNV+SGRSGy3oFahYfVw7bXw5S8nr1pxzDHw2c/CQQdBHhuqTPChHMAPHy55EJEXjDFLo9aRD/pqh9esWcMee+zR5xUKBoMxJutjDCcu6cmnFmMMr7766naXsUzHpfMPRrieDOpFoqiIUQNd/i6P3wtzlY+2xdm3xS61ezBy9WTSDsMIb/sGQNthO1G0w27UjDzQFe/y4ioYzc3NUUvIGquHlSuhshLefhvuuQcOOcS5zgfwoxzADx8+ePCF0tJS6urqyLZjO5/XB88El/TkS4sxhrq6OrZd52Nb8nr+iQx4a95994H3yyOutU/Ns2ZFLSGEa/n4wnC0xS61ezAy9WTaDoO2xTZca2e0HR5BUzAMhlFS+P0tqfmthYzVQywGkyZBsBCVq/hQDuCHDx88+EJ1dTUbN27M+pJOI/WXrkzIp5bS0lKqq6ut+7h2/o3bvDlqCSE0Hzuu5eMLw9EWu9TuwcjVk0k7DO6dSy61NZqNnSjyGTEdED2JHorEvV/SB0tHR4dzC/EMFquHWAzGjs2voCHgQzmAHz588OALJSUl7LLLLlkfp6WlhQkTJgyDouHBJT0uaQH3zr+OyZMpaW+PWkYvmo8d1/LxheFoi11ra1SPHdfOJZfaGs3GThT5FP6QgAzxZQSESyfQULF6KJAOCB/KAfzw4YMHJYxrZeqSHpe0gIN62tqilhBC87HjWj7KVlwrG9Vjxzk9DrU1mo2dKPIp/P/IM6Qn0eNFB0QikYhaQtZYPcRiUFaWPzFDxIdyAD98+OBBCeNambqkxyUt4KAeh1alB81nIFzLR9mKa2Wjeuw4p8ehtkazsRNFPoX/H3mGJEyColGFPwWjEK9asi1WD+3tBTECwodyAD98+OBBCeNambqkxyUt4KAexxYt1nzsuJaPshXXykb12HFOj0NtjWZjJ4p8RkwHRA9+jIBw6ZrDQ8XqoUCmYPhQDuCHDx88KGFcK1OX9LikBRzUE4tFLSGE5mPHtXyUrbhWNqrHjnN6HGprNBs7UeRT+P+RZ0gikfBiEcrOzs6oJWSN1UOBdED4UA7ghw8fPChhXCtTl/S4pAUc1FNeHrWEEJqPHdfyUbbiWtmoHjvO6XGordFs7ESRz8jpgDAJL0ZAlBXA+ggDYfVQIB0QPpQD+OHDBw9KGNfK1CU9LmkBB/Vs2RK1hBCajx3X8hluRGSGiDwuIqtF5BUROT/YfomIbBKRFcHtiLT3fENE1onIayJyaFTaXSsb1WPHOT0OtTWajZ0o8in8/8gzJJ6IezECoqWlJWoJWWP1UCAdED6UA/jhwwcPShjXytQlPS5pAQf1zJgRtYQQmo8d1/LJAXHgq8aY+cD+wBdEZH7w2tXGmMXB7WGA4LUTgQXAYcDPRaL58upa2ageO87pcait0WzsRJHPiOmASODHIpSTJk2KWkLWWD0USAeED+UAfvjwwYMSxrUydUmPS1rAQT3r1kUtIYTmY8e1fIYbY8xmY8zy4HELsAaYbnnL0cBdxphOY8ybwDpg39wr3R7Xykb12HFOj0NtjWZjJ4p8RkwHRLzHjxEQdXV1UUvImn49GAMdHQXRAeFDOYAfPnzwoIRxrUxd0uOSFnBQz4IFUUsIofnYcS2fXCIis4C9gX8Hm84TkZdF5CYRqQi2TQc2pL1tI/YOi5zhWtmoHjvO6XGordFs7ESRz4jpgPBlBMSUKVOilpA1/Xro6EjeOzZXqy98KAfww4cPHpQwrpWpS3pc0gIO6lm1KmoJITQfO67lkytEZDzwe+DLxphm4AZgNrAY2Az8ZJDHO0dElonIsi1bttDR0UF7ezttbW10dnbS3NxMPB6noaEBYwy1tbUA1NTUAFBbW4sxhoaGBuLxOM3NzXR2dtLW1kZ7ezsdHR2MGTOG7u5uGhsbSSQSvf+kpI6Ruq+vr6enp4empia6urpobW0lFosRi8VobW2lq6uLpqYmenp6qK+v7/MYdXV1JBIJGhsb6e7upqWlZTtPo0ePztpTS0vLsHkqKSnJ2tNwlFPKU3Fxcf7KafZsusvKaKmupqOigvaqKtqmTqWzvJzmmTOJl5ZS1NmJEaF24cLkMYL72oULMSI0zJmTl3JqamqioqIif+VUWkrzzJl0lpfTNnUq7VVVdFRU0FJdTXdZGY2zZzN5zRrq5s1LHmPRotB9/dy59JSU5Px8SvdUWVmZk/PJijGm4G777LOPGSxjfzjWfO3Rrw36fa6xZcuWqCVkTb8eamuNAWOuvTa/goaAD+VgjB8+XPIALDMOtJH5uA2lHc4Ul8rUmNzo+cxnPmOqqqrMggULerd97WtfM3PnzjWLFi0yxxxzjGloaOh97aWXXjL777+/mTt3rlm4cKGJxWLGGGPuuusus2jRIjN//nxz0UUX9e7f0dFhTjjhBDN79myz7777mjfffHPYPRiT57JKjpOz3rYsXDjwfnlE87GTq3xcaouBEuBR4IJ+Xp8FrAoefwP4RtprjwLvtR0/V23xSGiH++O///2v+dCHPmTmzZtn5s+fb6655prQ61dddZUBTE1NjTHGmEQiYb74xS+a2bNnm0WLFpkXXnghb1pTaFvTP5qNnSja4REzAqLH9HgxAqKqqipqCVnTr4fUdXELYAqGD+UAfvjwwYMSxrUyzYWeM844g0ceeSS07eCDD2bVqlW8/PLL7L777lxxxRUAxONxTj31VH7xi1/w6quv8sQTT1BSUkJdXR0XXnghjz32GK+88grvvPMOjz32GAA33ngjFRUVrFu3jq985St8/etfH3YP4GBZOfYLv+Zjx7V8hhsREeBGYI0x5v/Stu+UttsngFTBPAicKCJjRGQXYA7wXL70puNa2eRTT3FxMT/5yU9YvXo1zz77LNdffz2rV68GYMOGDfzlL39h5syZvfv/+c9/Zu3ataxdu5Zf/epXnHvuuXnTmsK58nKordFs7ESRz8jpgEj0eLEGRGqITCHTr4cC6oDwoRzADx8+eFDCuFamudDzgQ98gMmTJ4e2HXLIIRQXFwOw//77s3HjRgD+8pe/sOeee7LXXntRW1tLZWUlRUVFvPHGG8yZM6f3y8NHP/pRfv/73wPwwAMPcPrppwPwyU9+ksceeyz1i+qw4lxZBcN8XUHzseNaPjngfcCngY9sc8nNK0VkpYi8DHwY+AqAMeYV4B5gNfAI8AVjTE8Uwl0rm3zq2WmnnViyZAkAEyZMYN68eWzatAmAr3zlK1x55ZWh9vSBBx7gtNNOQ0TYf//9aWxsZPPmzXnTCw6Wl0NtjWZjJ4p8ivP+iRGRMAlGSeH3t1RWVkYtIWv69VBAHRA+lAP44cMHD0oY18o0Cj033XQTn/rUpwD4z3/+g4hw6KGHUlNTw4knnshFF13Ebrvtxmuvvcb69euprq7m/vvvp6urC4BNmzYxI7jUV3FxMeXl5dTV1Q37nHvnyuqVV6KWEELzseNaPsONMeZpQPp46WHLey4DLsuZqAxxrWyi0rN+/XpefPFF9ttvPx544AGmT5/OXnvtxahRW/+nSG9vAaqrq9m0aRM77bRTX4fMCc6Vl0NtjWZjJ4p8Cv8/8gwxGC86IBobG6OWkDX9eiigDggfygH88OGDByWMa2Wabz2XXXYZxcXFnHLKKUByCsbTTz/NHXfcwR//+Efuu+8+HnvsMSoqKrjhhhv41Kc+xfvf/35mzZpFUVF+R/o5V1a77Ra1hBCajx3X8lG24lrZRKGntbWV4447jmuuuYbi4mIuv/xyLr30UgASiUTe9dhwrrwcams0GztR5FP4/5GPMCZMmBC1hKzp10MBdUD4UA7ghw8fPChhXCvTfOq5+eabeeihh7jjjjtITh9P/pr2gQ98gClTprDjjjtyxBFHsHz5cgA+/vGP8+9//5tnnnmGuXPnsvvuuwMwffp0NmxIXs0vHo/T1NSUk185nCurDRsG3imPaD52XMtH2YprZZNvPd3d3Rx33HGccsopHHvssbz++uu8+eab7LXXXsyaNYu3336bJUuW8M4774TaW4CNGzcyfXp+r57qXHk51NZoNnaiyGdEdUCkvswVMu3t7VFLyJp+PRRQB4QP5QB++PDBgxLGtTLNl55HHnmEK6+8kgcffJCytMsRH3rooaxcuZL29naam5t58sknmT9/PgBbtmwBoKGhgZ///Od89rOfBeCoo47illtuAeDee+/lIx/5SE7+BjpXVjvsELWEEJqPHdfyUbbiWtnkU48xhrPOOot58+ZxwQUXALBo0SK2bNnC+vXrWb9+PdOnT2f58uVMnTqVo446iltvvRVjDM8++yzl5eV5nX4BDpaXQ22NZmMninxGxBoQuVh4KyrGjBkTtYSs6ddDqgMi7Yu3q/hQDuCHDx88KGFcK9Nc6DnppJN44oknqK2tpbq6mu9///tcccUVdHZ2cvDBBwPJhSh/8YtfUFFRwQUXXMB73vMeAI488kiOPPJIAM4//3xeeuklAL773e/2joA466yz+PSnP81uu+3G5MmTueuuu4bdAzhYVk1NUUsIofnYcS0fZSuulU0+9fzzn//ktttuY9GiRSxevBiAyy+/nCOOOKLP/Y844ggefvhhdtttN8rKyvjtb3+bN60pnCsvh9oazcZOFPmMiA6IFNLnOkCFRTwed+5EGiz9ekj1wBXACAgfygH88OGDByWMa2WaCz133nnndtvOOuusfvc/9dRTOfXUU2lra2PcuHHW4wCUlpbyu9/9LnuhA+BcWY0d69SXO83Hjmv5KFtxrWzyqefAAw8c8MfL1atX97bFIsL111+fD2n94lx5OdTWaDZ2oshnRHRAGPwZAeHDNJJ+PRTQFAwfygH88OGDByWMa2WaVz0DfJZUVUFNjf0YeRz151xZ9URyxcJ+0XzsuJaPshXXykb12HFOj0NtjWZjJ4p8RkQHRArXKuBQSL/sT6HSr4cC6oDwoRzADx8+eFDCuFamLukZFY9HLSGES9mA5jMQmo+SKa6VTV71ZPD/wqiKCmhosO+Ux85g58rLobZGs7ETRT5ulUiO8GkNiO7u7qglZE2/HgqoA8KHcgA/fPjgQQnjWpm6pKc7bfqFC7iUDWg+A6H5KJniWtk4p0fPJSsu5aPZ2Ikin5x3QIjIYSLymoisE5GL+3h9pog8LiIvisjLItL3Ci/DocWDNSBKS0ujlpA1/XpIdUAUgEcfygH88OGDByWMa2Xqkp7S+vqoJYRwKRvQfAZC81EyxbWycU6PnktWXMpHs7ETRT457YAQkSLgeuBwYD5wkojM32a3bwP3GGP2Bk4Efj7cOnxaA6KtrS1qCVnTr4dYDMaMAceGSvWFD+UAfvjwwYMSxrUydUlPW54v7TYQLmUDms9AaD5KprhWNs7p0XPJikv5aDZ2osgn1//p7QusM8a8YYzpAu4Cjt5mHwNMDB6XA28Pt4jUFAwf1oCYOHHiwDs5Tr8eYrGCuAQn+FEO4IcPHzwoYVwrU5f0TFy/PmoJIVzKBjSfgdB8lExxrWyc06PnkhWX8tFs7ESRT647IKYDG9Kebwy2pXMJcKqIbAQeBr6YKzE+TMFoGGjBmwKgXw/t7QWx/gP4UQ7ghw8fPChhXCtTl/Q07L571BJCuJQNaD4DofkomeJa2TinR88lKy7lo9nYiSIfF8a6nwTcbIypBo4AbhOR7XSJyDkiskxElm3ZsoWOjg7a29tpa2ujs7OT5uZm4vE4DQ0NGGOora0FoKampncKhsHQ0NBAPB6nubmZzs5O2traaG9vp6Ojg5aWFrq7u2lsbCSRSFBXV9d7jPT7+vp6enp6aGpqoquri9bWVmKxGLFYjNbWVrq6umhqaqKnp4f6YJ7Ptseoq6sjkUjQ2NhId3c3LS0tGXmqrKzsPUZtbS3GFJ6n8vLyPsuJWIye0aMLwtPYsWMzqnuul9PEiRMzrnuueqqsrBzy+TTcnpThobKyMmoJIVzSU7lmTdQSQriUDWg+A6H5KJniWtk4p0fPJSsu5aPZ2IkiH8nlFSJE5L3AJcaYQ4Pn3wAwxlyRts8rwGHGmA3B8zeA/Y0xW/o77tKlS82yZcsy1tHV08WYH47hso9cxjff/82hmXGEmpoaqqqqopaRFf16OPZYWLsWVq7Mv6hB4kM5gB8+XPIgIi8YY5ZGrSMfDLYdHgwulSnkWc8AUwVrFi2iaqA2Mo9XfnIpG9B8BmKk5KNtcfZoO2xnpJxLfVJg+Wg2dqJoh3M9AuJ5YI6I7CIio0kuMvngNvv8FzgIQETmAaXAsP6c6NNlOF36YzBU+vUQixXMFAwfygH88OGDByWMa2Xqkp4Bv7TkGZeyAc1nIDQfJVNcKxvn9Oi5ZMWlfDQbO1Hkk9MOCGNMHDgPeBRYQ/JqF6+IyKUiclSw21eBs0XkJeBO4AyTox4DH9aA8GGod78eCqgDwodyAD98+OBBCeNambqkp2bRoqglhHApG9B8BkLzUTLFtbJxTo+eS1ZcykezsRNFPjlfA8IY87AxZndjzGxjzGXBtu8aYx4MHq82xrzPGLOXMWaxMeYvw67Bo8twutaLNxR0BIQ7+ODDBw8DISI3icgWEVmVtu3HIvKqiLwsIveJyKS0174hIutE5DUROTRt+2HBtnUicnHa9l1E5N/B9ruDEWuR4VqZuqRHfzmxo/nY0XyUTHGtbJzTo+eSFZfy0WzseDcCwjV8uAxnahG+QqZfDwXUAeFDOYAfPnzwkAE3A4dts+2vwEJjzJ7Af4BvAIjIfJLT3RYE7/m5iBSJSBFwPXA4MB84KdgX4H+Bq40xuwENwFm5tWPHtTJ1SU/93LlRSwjhUjag+QyE5qNkimtl45wePZesuJSPZmMninxGRAeET2tAlJeXRy0ha/r1EItBWVl+xQwRH8oB/PDhg4eBMMb8A6jfZttfgmluAM8C1cHjo4G7jDGdxpg3gXXAvsFtnTHmDWNMF3AXcLQke2Y/AtwbvP8W4Jhc+hkI18rUJT3lb7wRtYQQLmUDms9AaD5KprhWNs7p0XPJikv5aDZ2oshnRHRApPBhDYjW1taoJWRNvx7a2wtmBIQP5QB++PDBwzBwJvDn4PF0YEPaaxuDbf1trwQa0zozUtsjw7UydUlP6/RIi2Y7XMoGNJ+B0HyUTHGtbJzTo+eSFZfy0WzsRJHPiOiA8GkNiLEF8g+6jX49FNAUDB/KAfzw4YOHbBCRbwFx4I48fNY5IrJMRJZt2bKFjo4O2tvbaWtro7Ozk+bmZuLxOA0NDRhjqK2tBbYucFRbW4sxhoaGBuLxOM3NzXR2dtLW1kZ7ezsdHR20tLRQXFxMY2MjiUSCurq60DFS9/X19fT09NDU1ERXVxetra3EYjFisRitra10dXXR1NRET09P7/DCbY9RV1dHIpGgsbGR7u5uWlpa+vRUUlKStafu7u7MPJWU0DRrFl3jx9M6bRqxykpilZW0TptG1/jxdJeV0VNS0juEM7WYVeq+bt68jDwNRzl1d3fT1dWVv3KaPZvusjJaqqvpqKigvaqKtqlT6Swvp3nmTOKlpXROnIgRoXbhwuQxgvvahQsxIjTMmTM85ZShp46Ojqzq3qDKaeZMOsvLaZs6lfaqKjoqKmiprqa7rIzG2bNJFBURmzy5z3pTP3fu1rqX4/Mp3VN7e3vOziclO1z72+qcnuB8dAXNp380GztR5COFOD1hsNc8bu9uZ9zl4/jfj/4vF73vohwqyz2tra2MHz8+ahlZ0a+HsWPhi1+EK6/Mv6hB4kM5gB8+XPKQy2vPi8gs4CFjzMK0bWcAnwMOMsa0B9u+AWCMuSJ4/ihwSfCWS4wxh6bvB/yI5KWPpxpj4iLy3vT9+iNX154Ht8oU8qxngLWKWqdNY/zbb9uPkce/6y5lA5rPQIyUfHLZFrtGrtpibYftjJRzqU8KLB/Nxk4U7fDIGAFRgJ0s/VFUVBS1hKzp04Mx0NFRMCMgfCgH8MOHDx6GgogcBlwEHJXqfAh4EDhRRMaIyC7AHOA54HlgTnDFi9EkF6p8MLjs8ePAJ4P3nw48kC8ffeFambqkp6izM2oJIVzKBjSfgdB8lExxrWyc06PnkhWX8tFs7ESRz8jogAimYPiwBoS3BMNUC6UDQlHyiYjcCTwDzBWRjSJyFvAzYALwVxFZISK/ADDGvALcA6wGHgG+YIzpCdZ4OA94FFgD3BPsC/B14AIRWUdyTYgb82hPURRFURRFGSEURy0gn/hwGc6enp6oJWRNnx5iseR9gXRA+FAO4IcPHzwMhDHmpD4299tJYIy5DLisj+0PAw/3sf0NklfJcALXytQlPT1jxkQtIYRL2YDmMxCaj5IprpWNc3r0XLLiUj6ajZ0o8hkZIyA8moIxevToqCVkTZ8eCqwDwodyAD98+OBBCeNambqkZ3Rzc9QSQriUDWg+A6H5KJniWtk4p0fPJSsu5aPZ2IkinxHRAZHChykYsdQ/6gVMnx5S28rK8itmiPhQDuCHDx88KGFcK1OX9MSmTIlaQgiXsgHNZyA0HyVTXCsb5/TouWTFpXw0GztR5DMiOiB8ugynSysSD5U+PQSX4iqUERA+lAP44cMHD0oY18rUJT3jN22KWkIIl7IBzWcgNB8lU1wrG+f06LlkxaV8NBs7UeQzIjogUviwBkRTU1PUErKmTw8FNgXDh3IAP3z44EEJ41qZuqSnadddo5YQwqVsQPMZCM1HyRTXysY5PXouWXEpH83GThT5jIgOCJ/WgJg8eXLUErKmTw8F1gHhQzmAHz588KCEca1MXdIz+bXXopYQwqVsQPMZCM1HyRTXysY5PXouWXEpH83GThT5jIgOiBQ+rAFRU1MTtYSs6dNDgXVA+FAO4IcPHzwoYVwrU5f01CxaFLWEEC5lA5rPQGg+Sqa4VjbO6dFzyYpL+Wg2dqLIZ0R0QPi0BkRVVVXUErKmTw8F1gHhQzmAHz588KCEca1MXdJTtXJl1BJCuJQNaD4DofkomeJa2TinR88lKy7lo9nYiSKfEdEBkcKHNSBc68UbCjoCwh188OGDByWMa2Xqkh795cSO5mNH81EyxbWycU6PnktWXMpHs7GjIyByhE9rQLjWizcUrCMgCuQynD6UA/jhwwcPShjXytQlPfrLiR3Nx47mo2SKa2XjnB49l6y4lI9mY0dHQOQYH9aAqKuri1pC1vTpocAuw+lDOYAfPnzwoIRxrUxd0lM3b17UEkK4lA1oPgOh+SiZ4lrZOKdHzyUrLuWj2diJIp8R0QHh0xoQFRUVUUvImj49FNgUDB/KAfzw4YMHHznzzDPZYYcdWLhwYe+2+vp6Dj74YObMmcPBBx9MQ0MDkLwE1Mc//nH22msvFixYwP333w/AihUreO9738uCBQvYc889ufvuu3uPZYzhW9/6Frvvvjvz5s3juuuuy5kXl+pYxX/+E7WEEC5lA5rPQGg+SooNGzbw4Q9/mPnz57NgwQKuvfZaYGs7vf/++4fa6SeeeILy8nIWL17M4sWLufTSS/Oq17W6oueSHZfy0WzsRJHPiOiASOHDGhDNzc1RS8iaPj2kOiBKS/MrZoj4UA7ghw8fPPjIGWecwSOPPBLa9qMf/YiDDjqItWvXctBBB/GjH/0IgOuvv5758+fz0ksv8cQTT/C1r32Nrq4uysrKuPXWW3nllVd45JFH+PKXv0xjYyMAN998Mxs2bODVV19lzZo1nHjiiTnz4lIda541K2oJIVzKBjSfgdB8lBTFxcX85Cc/YfXq1Tz77LNcf/31rF69uredfv7550PtNMD73/9+VqxYwYoVK/jud7+bV72u1RU9l+y4lI9mYyeKfEZEB4RPa0CMGzcuaglZ06eHWAzGjIFRhVElfSgH8MOHDx585AMf+MB215Z+4IEHOP300wE4/fTTe0c6iAgtLS0YY2htbaWyspLi4mJ233135syZA8C0adPYYYcdehdLuuGGG/jud7/LqKDN2GGHHXLmxaU6Nm7z5qglhHApG9B8BkLzUVLstNNOLFmyBIAJEyYwb948Nm3a1NtOjxs3LtROR41rdUXPJTsu5aPZ2Ikin8L4by9LUlMwfFgDoqOjI2oJWdOnh1isYKZfgB/lAH748MHDSOHdd99lp512AmDq1Km8++67AJx33nmsWbOGadOmsWjRIq644orejoUUzz33HF1dXcyePRuA119/nbvvvpulS5dy+OGHs3bt2pzpdqmOdWzTqRM1LmUDms9AaD5KX6xfv54XX3yR/fbbr7ed7ujoCLXTAM888wx77bUXhx9+OK+88kpeNbpWV/RcsuNSPpqNnSjyGREdECl8mIJRUlIStYSs6dNDgXVA+FAO4IcPHzyMRESkt01+9NFHWbx4MW+//TYrVqzgwgsvDA0J3Lx5M5/+9Kf57W9/29sx0dnZSWlpKcuWLePss8/mzDPPzJlWl+pYSVtb1BJCuJQNaD4Dofko29La2spxxx3HNddcw8SJE3u3l5SUhNrpJUuW8NZbb/HSSy/xxS9+kWOOOSavOl2rK3ou2XEpH83GThT5jIgOCJ+mYCQSiaglZE2fHgqsA8KHcgA/fPjgYaSw4447sjkYerh58+beaRO//e1vOfbYYxERdtttN3beeWdeffVVIDk38cgjj+Syyy5j//337z1WdXU1xx57LACf+MQnePnll3Om26U6ligujlpCCJeyAc1nIDQfJZ3u7m6OO+44TjnllN72NNVOJxKJUDs9ceJExo8fD8ARRxxBd3c3tbW1edPqWl3Rc8mOS/loNnaiyGdEdECk8GEKhg+dKX16iMWgrCz/YoaID+UAfvjwwcNI4aijjuKWW24B4JZbbuHoo48GYObMmTz22GNAcprG2rVr2XXXXenq6uITn/gEp512Gp/85CdDxzrmmGN4/PHHAXjyySfZfffdc6bbpTpmioqilhDCpWxA8xkIzUdJYYzhrLPOYt68eVxwwQW921PttDEm1E6/8847veX13HPPkUgkqKyszKtel9BzyY5L+Wg2dqLIx60umBzh02U4ix3rNRsKfXpoby+oERA+lAP44cMHDz5y0kkn8cQTT1BbW0t1dTXf//73ufjiiznhhBO48cYb2XnnnbnnnnsA+M53vsMZZ5zBokWLMMZw2WWXMWXKFG6//Xb+8Y9/UFdXx8033wwkr36xePFiLr74Yk455RSuvvpqxo8fz29+85uceXGpjhWnrhjkCC5lA5rPQGg+Sop//vOf3HbbbSxatIjFixcDcPnll/e207/5zW+YNWtWbzt97733csMNN1BcXMzYsWO566678jq12bW6oueSHZfy0WzsRJGPWyWSY3xYA6Kzs5MxY8ZELSMr+vRQYFMwfCgH8MOHDx585M477+xze2qkQzrTpk3jL3/5S+/z1PoPp556Kqeeemqfx5k0aRJ/+tOfhkHpwLhUxzrLyxnT1BS1jF5cygY0n4HQfJQUBx54YL+/fD722GM0NzeH1oQ477zzOO+88/Ilbztcqyt6LtlxKR/Nxk4U+YyIDgjXht5kQ1kBTVPojz49xGJQUZF/MUPEh3IAP3z44EEJ41qZuqSnbMuWqCWEcCkb0HwGQvNRAMjgB7my0lIYaHX8PH6/dq2u6Llkx6V8NBs7UeSja0AUGC0tLVFLyJo+PRTYCAgfygH88OGDhxGFyIC3lvnzB94vj7hUx1pmzIhaQgiXsgHNZyA0HyVTtK7Y0XzsuJSPZmMninxGRAeET2tATJo0KWoJWdOnhwLrgPChHMAPHz54UMJMWrcuagkhXKpjmo0dzceO5pNfRGSGiDwuIqtF5BUROT/YPllE/ioia4P7imC7iMh1IrJORF4WkSVRade6YkfzseNSPpqNnSjyGREdECl8WAOirq4uaglZ06eHAuuA8KEcwA8fPnhQwtQtWBC1hBAu1THNxo7mY0fzyTtx4KvGmPnA/sAXRGQ+cDHwmDFmDvBY8BzgcGBOcDsHuCH/kpNoXbGj+dhxKR/Nxk4U+YyIDgif1oCYMmVK1BKypk8PBdYB4UM5gB8+fPCghJmyalXUEkK4VMc0Gzuajx3NJ78YYzYbY5YHj1uANcB04GjglmC3W4BjgsdHA7eaJM8Ck0Rkp/yqTqJ1xY7mY8elfDQbO1HkMyI6IFL4sAZETU1N1BKypk8PsRg4tkiMDR/KAfzw4YMHJUzNwoVRSwjhUh3TbOxoPnY0n+gQkVnA3sC/gR2NMZuDl94BdgweTwc2pL1tY7At72hdsaP52HEpH83GThT5jIgOCJ/WgKiqqopaQtZs58GYghsB4UM5gB8+fPCghKly7NcBl+qYZmNH87Gj+USDiIwHfg982RjTnP6aSQ7THdQXVRE5R0SWiciyLVu20NHRQXt7O21tbXR2dtLc3Ew8HqehoQFjDLW1tcDWfzRqFy7EiNAwZw7x0lKaZ86ks7yctqlTaa+qoqOigtLGRrrLymicPZtEURF18+Ylj7FoUei+vr6enp4empqa6OrqorW1lVgsRiwWo7W1la6uLpqamujp6aG+vj6kI3VfV1dHIpGgsbGR7u5uWlpatvM0ZswYu6faWowxNDQ0EI/HaW5uprOzk7a2Ntrb2+no6KClpYXu7m4aGxtJJBK9Q8+31VM/dy49JSU0zZpF1/jxtE6bRqyyklhlJa3TptE1fjyjW1vpKSmhfu7cPnOpmzdvQE8DltMgPJWUlNg9DWc5zZ5Nd1kZLdXVdFRU0F5VRdvUqXSWl9M8cybx0lKKOzsxItQG/2yn/ukO1b1syylDT5MnT86q7g2qnPo5n1qqq3vPp8o1a/o/n1J1L8fnU7qnKVOm5OR8siGFOD1h6dKlZtmyZRnvv6l5E9VXV/PLj/2Sc/Y5J4fKck9tba1zQ4kGy3YeUqMfrrgCLr64/zc6hA/lAH74cMmDiLxgjFkatY58MNh2uJcM1uKpXbhw4CGKefzbldc6NkA+mo0dzcfOSMnHpbZYREqAh4BHjTH/F2x7DfiQMWZzMMXiCWPMXBH5ZfD4zm336+/4Q2qLta7Y0XzsFFg+mo2dKNrhETECIoUPUzAqKyujlpA123mIxZL3BTQCwodyAD98+OBBCVP5yitRSwjhUh3TbOxoPnY0n/wiydXPbwTWpDofAh4ETg8enw48kLb9tOBqGPsDTbbOh1yidcWO5mPHpXw0GztR5DMiOiB8moLR2NgYtYSs2c5DAXZA+FAO4IcPHzwoYRp32y1qCSFcqmOajR3Nx47mk3feB3wa+IiIrAhuRwA/Ag4WkbXAR4PnAA8DbwDrgF8Dn49AM6B1ZSA0Hzsu5aPZ2Ikin+K8f2KE+HAZzgkTJkQtIWu281CAHRA+lAP44cMHD0qYCRs2DLxTHnGpjmk2djQfO5pPfjHGPA39Dr89qI/9DfCFnIrKEK0rdjQfOy7lo9nYiSKfkTECogDXueiP9vb2qCVkzXYeCrADwodyAD98+OBBCdO+ww5RSwjhUh3TbOxoPnY0HyVTtK7Y0XzsuJSPZmMninxGRAdECh/WgBgzZkzUErJmOw8F2AHhQzmAHz588KCEGdPUFLWEEC7VMc3GjuZjR/NRMkXrih3Nx45L+Wg2dqLIZ0R0QPi0BkQ8Ho9aQtZs5yHV81ZWln8xQ8SHcgA/fPjgQQkTd6wz0qU6ptnY0XzsaD5KpmhdsaP52HEpH83GThT5jIgOiBQ+rAHhpYcCHAHhQzmAHz588DAQInKTiGwRkVVp2yaLyF9FZG1wXxFsFxG5TkTWicjLIrIk7T2nB/uvFZHT07bvIyIrg/dcJxGHKj09UX78drhUxzQbO5qPHc1HyRStK3Y0Hzsu5aPZ2IkinxHRAeHTGhCjRhV+kW3noQA7IHwoB/DDhw8eMuBm4LBttl0MPGaMmQM8FjwHOByYE9zOAW6AZIcF8D1gP2Bf4HupTotgn7PT3rftZ+WVUY79WuFSHdNs7Gg+djQfJVO0rtjRfOy4lI9mYyeKfNwqkRzjwxoQ3d3dUUvImu08FGAHhA/lAH748MHDQBhj/gHUb7P5aOCW4PEtwDFp2281SZ4FJonITsChwF+NMfXGmAbgr8BhwWsTjTHPBiuw35p2rEjoHjcuyo/fDpfqmGZjR/Oxo/komaJ1xY7mY8elfDQbO1HkMyI6IHxaA6K0tDRqCVmznYcC7IDwoRzADx8+eBgiOxpjNgeP3wF2DB5PB9Kv8bQx2GbbvrGP7ZFRWr9tX0u0uFTHNBs7mo8dzUfJFK0rdjQfOy7lo9nYiSKfEdEBkcK1OUBDoa2tLWoJWbOdhwLsgPChHMAPHz54yJZg5ELOe1pF5BwRWSYiy7Zs2UJHRwft7e20tbXR2dlJc3Mz8XichoYGjDHU1tYCUFNTA0BtbS1GhIY5c4iXltI8cyad5eW0TZ1Ke1UVHRUVtFRX07TLLjTOnk2iqIi6efOSx1i0KHRfX19PT08PTU1NdHV10draSiwWIxaL0draSldXF01NTfT09FAf/LFP6Ujd19XVkUgkaGxspLu7m5aWlj49NTc32z0ZQ0NDA/F4nObmZjo7O2lra6O9vZ2Ojg5aWlro7u6msbGRRCJBXV1dn3rq6+vpKSmhadYsusaPp3XaNGKVlcQqK2mdNo2u8eN5d8kSekpKqJ87t89c6ubNy8jTgOWUoad33nlnYE/DVU6zZ9NdVkZLdTUdFRW0V1XRNnUqneXlNM+cSby0lM377osRoXbhwuQxgvvahQu31r3hKKcMPb399ttZ1b1BlVM/51N3WVnv+fT2AQf0fT7Nnbu17uX4fEr3tGnTppydT0p2tO20U9QSQrj2t17zseNSPpqNnSjykUJcH2Hp0qVm2bJlGe//ZsOb7Hrdrvz26N9yxuIzcicsDyQSCefmMg2W7TxceSV8/evQ2gqODUvqDx/KAfzw4ZIHEXnBGLM0R8eeBTxkjFkYPH8N+JAxZnMwjeIJY8xcEfll8PjO9P1SN2PM54LtvwSeCG6PG2P2CLaflL5ffwy2HU4zMuAuiaIiRg20SFMe/3bltY4NkI9mY0fzsTNS8sllW+waQ2qLta7Y0XzsFFg+mo2dKNphN7615wkf1oBoaGiIWkLWbOehAEdA+FAO4IcPHzwMkQeB1JUsTgceSNt+WnA1jP2BpmCqxqPAISJSESw+eQjwaPBas4jsH1z94rS0Y0VCw+67R/nx2+FSHdNs7Gg+djQfJVO0rtjRfOy4lI9mYyeKfIrz/okR4NMaEJWVlVFLyJrtPLS3w5gx4Miv2JngQzmAHz588DAQInInyREMU0RkI8mrWfwIuEdEzgLeAk4Idn8YOAJYB7QDnwEwxtSLyA+A54P9LjXGpCYifp7klTbGAn8ObpFRuWZNlB+/HS7VMc3GjuZjR/NRMkXrih3Nx45L+Wg2dqLIp3D+48uC1DQTH9aA8GFu43YeYrGCGv0AfpQD+OHDBw8DYYw5yRizkzGmxBhTbYy50RhTZ4w5yBgzxxjz0VRnQnD1iy8YY2YbYxYZY5alHecmY8xuwe23aduXGWMWBu85z0Q8Ny81L90VXKpjmo0dzceO5qNkitYVO5qPHZfy0WzsRJHPiOiASOHDFIyqqqqoJWTNdh4KsAPCh3IAP3z44EEJU7VyZdQSQrhUxzQbO5qPHc1HyRStK3Y0Hzsu5aPZ2IkinxHRAeHTFAzXevGGgo6AcAcffPjgQQmjvw70j2ZjR/Oxo/komaJ1xY7mY8elfDQbOzoCIsf4MAXDtV68oaAjINzBBx8+eFDC6K8D/aPZ2NF87Gg+SqZoXbGj+dhxKR/Nxo6OgMgRhXip0f5IXX+7kNnOQwF2QPhQDuCHDx88KGHq586NWkIIl+qYZmNH87Gj+SiZonXFjuZjx6V8NBs7UeSTcQeEiIwVEbcSGyQ+rAFRXl4etYSs2c5DAXZA+FAO4IcPHzwoYcrfeCNqCSFcqmOajR3Nx47mo2SK1hU7mo8dl/LRbOxEkU9GHRAi8nFgBfBI8HyxiDyYQ13Dik9rQLS2tkYtIWu28xCLQVlZNGKGiA/lAH748MGDEqZ1+vSoJYRwqY5pNnY0Hzuaj5IpWlfsaD52XMpHs7ETRT6ZjoC4BNgXaAQwxqwAdsmJohziwxoQYwtspEBfbOehvb3gRkD4UA7ghw8fPChhxtbWRi0hhEt1TLOxo/nY0XyUTNG6YkfzseNSPpqNnSjyybQDotsY07TNtoyGFYjIYSLymoisE5GL+9nnBBFZLSKviMj/y1BTxvi0BkRXV1fUErJmOw8FOAXDh3IAP3z44EEJ0zVxYtQSQrhUxzQbO5qPHc1HyRStK3Y0Hzsu5aPZ2Ikin+IM93tFRE4GikRkDvAl4F8DvUlEioDrgYOBjcDzIvKgMWZ12j5zgG8A7zPGNIjIDoM1kSk+rAFRVFQUtYSs2c5DAXZA+FAO4IcPHzwoYYo6O6OWEMKlOqbZ2NF87Gg+SqZoXbGj+dhxKR/Nxk4U+WQ6AuKLwAKgE/h/QBPw5Qzety+wzhjzhjGmC7gLOHqbfc4GrjfGNAAYY7ZkqCljfFoDwksKsANCURRFURRFURRFGRwZdUAYY9qNMd8yxrwnuH3bGNORwVunAxvSnm8MtqWzO7C7iPxTRJ4VkcP6OpCInCMiy0Rk2ZYtW+jo6KC9vZ22tjY6Oztpbm4mHo/T0NCAMYbaYH5NTU1N6DgNDQ3E43Gam5vp7Oykra2N9vZ2Ojo6aGlpobu7m8bGRhKJBHV1daFjpO7r6+vp6emhqamJrq4uWltbicVixGIxWltb6erqoqmpiZ6ent5Lm2x7jLq6OhKJBI2NjXR3d9PS0pKRp56ent5j1NbWYowpOE+dnZ3hcorFaA+myRSKp9bW1ozrnsueOjs7M657rnrq6ekZ8vk03J6U4aFnzJioJYTo6emJWkIvmo0dzceO5qNkitYVO5qPHZfy0WzsRJGPZLI+goj8FTjeGNMYPK8A7jLGHDrA+z4JHGaM+Wzw/NPAfsaY89L2eQjoBk4AqoF/AItSn9UXS5cuNcuWLRtQd4o1NWuY//P53HncnZy48MSM3+ciXV1djB49OmoZWRHyYAyMGgXf+Q5cemm0wgaBD+UAfvhwyYOIvGCMWRq1jnww2Ha4lwwWA+4aP57RA63KnMe1ffJaxwbIR7Oxo/nYGSn5aFs8AFpX7Gg+dgosH83GThTtcKZTMKakdwgE0yUyWathEzAj7Xl1sC2djcCDxphuY8ybwH+AORnqyojUFAwf1oCIxWJRS8iakIfUPKgCm4LhQzmAHz588KCEiU2ZErWEEC7VMc3GjuZjR/NRMkXrih3Nx45L+Wg2dqLIJ9MOiISIzEw9EZGdyewqGM8Dc0RkFxEZDZwIPLjNPvcDHwqOO4XklIw3MtQ14hg/fnzUErIm5KG9PXlfVhaNmCHiQzmAHz588KCEGb9p237qaHGpjmk2djQfO5qPkilaV+xoPnZcykezsRNFPpl2QHwLeFpEbhOR20lOk/jGQG8yxsSB84BHgTXAPcaYV0TkUhE5KtjtUaBORFYDjwMXGmPqBmtkAB0ASAbDYlynqWnbq6EWHiEPqV63AhsB4UM5gB8+fPCghGnaddeoJYRwqY5pNnY0Hzuaj5IpWlfsaD52XMpHs7ETRT4ZXYbTGPOIiCwB9g82fdkYU5vhex8GHt5m23fTHhvgguCWU3yYgjF58uSoJWRNyEOBdkD4UA7ghw8fPChhJr/2WtQSQrhUxzQbO5qPHc1HyRStK3Y0Hzsu5aPZ2IkiH+sICBHZI7hfAswE3g5uM4NtBYFPl+H0YbX9kIcC7YDwoRzADx8+eFDC1CxaFLWEEC7VMc3GjuZjR/NRMkXrih3Nx45L+Wg2dqLIZ6AREF8FzgZ+0sdrBvjIsCvKIT5MwaiqqopaQtaEPBRoB4QP5QB++PDBgxKmauXKqCWEcKmOaTZ2NB87mo+SKVpX7Gg+dlzKR7OxE0U+1hEQxpizg/sP93ErmM6HTC41Wii41os3FHQEhDv44MMHD0oY/XWgfzQbO5qPHc1HyRStK3Y0Hzsu5aPZ2HFuBISIHGt73Rjzh+GVk1t8WAPCtV68oaAjINzBBx8+eFDC6K8D/aPZ2NF87Gg+SqZoXbGj+dhxKR/Nxo5zIyCAjwe3s4AbgVOC22+AM3MrbfjwaQ2IurphvUBIJIQ8pDogCuwynD6UA/jhwwcPSpi6efOilhDCpTqm2djRfOxoPkqmaF2xo/nYcSkfzcZOFPlYR0AYYz4DICJ/AeYbYzYHz3cCbs65umHGhzUgKioqopaQNSEP7e3J+wIbAeFDOYAfPnzwoISp+M9/opYQwqU6ptnY0XzsaD5KpmhdsaP52HEpH83GThT5DDQCIsWMVOdDwLskr4pREPi0BkRzc3PUErIm5KFAp2D4UA7ghw8fPChhmmfNilpCCJfqmGZjR/Oxo/komaJ1xY7mY8elfDQbO1HkM9BVMFI8JiKPAncGzz8F/C03knKHD2tAjBs3LmoJWRPyUKAdED6UA/jhwwcPSphxmzcPvFMecamOaTZ2NB87mo+SKVpX7Gg+dlzKR7OxE0U+GY2AMMacB/wC2Cu4/coY88VcChtOfFoDoqOjI2oJWRPyUKAdED6UA/jhwwcPSpiOyZOjlhDCpTqm2djRfOxoPkqmaF2xo/nYcSkfzcZOFPlkOgICY8x9wH19vSYizxhj3jtsqnKED2tAlJSURC0ha0IeCrQDwodyAD98+OBBCVPS1ha1hBAu1THNxo7mY0fzUTJF64odzceOS/loNnaiyCfTNSAGonSYjpMTfFoDIpFIRC0ha0IeYjEYPRpGDVdVzA8+lAP44cMHD0qYRHHGfeN5waU6ptnY0XzsaD5KpmhdsaP52HEpH83GThT5DNd/fU7/h5+aguHDGhA+dKaEPMRiBTf6AfwoB/DDhw8elDCmqChqCSFcqmOajR3Nx47mMzRE5EoRmSgiJSLymIjUiMipUevKJVpX7Gg+dlzKR7OxE0U+hfWzc5b4MAWj2LFes6EQ8hCLQVlZdGKGiA/lAH748MGDEqY4NTXLEVyqY5qNHc3HjuYzZA4xxjQDHwPWA7sBF0aqKMdoXbGj+dhxKR/Nxk4U+QxXB4TT/9m71vOVDZ2dnVFLyJqQh/b2ghwB4UM5gB8+fPCghOksL49aQgiX6phmY0fzsaP5DJnUN/Qjgd8ZY5qiFJMPtK7Y0XzsuJSPZmMninyGq8vj08N0nJziwxSMsgIcLbAtIQ8FOgXDh3IAP3z44EEJU7ZlS9QSQrhUxzQbO5qPHc1nyDwkIq8CMeBcEakC3Fpaf5jRumJH87HjUj6ajZ0o8sloBISIHCsia0WkSUSaRaRFRJpTrxtjVuVOYvb4dBnOlpaWqCVkTchDgXZA+FAO4IcPHzwoYVpmzIhaQgiX6phmY0fzsaP5DA1jzMXAAcBSY0w30AYcHa2q3KJ1xY7mY8elfDQbO1Hkk+kIiCuBjxtj1uRSTK7xYQ2ISZMmRS0ha0IeCrQDwodyAD98+OBBCTNp3bqoJYRwqY5pNnY0HzuaT1bsAcwSkfTvzrdGJSbXaF2xo/nYcSkfzcZOFPlkugbEu4Xc+eDTGhB1dXVRS8iakIcC7YDwoRzADx+F5kFE3ici44LHp4rI/4nIzlkc7ysi8oqIrBKRO0WkVER2EZF/i8g6EblbREYH+44Jnq8LXp+VdpxvBNtfE5FDszaaBXULFkT58dvhUh3TbOxoPnY0n6EhIrcBVwEHAu8JbksjFZVjtK7Y0XzsuJSPZmMninwyHQGxTETuBu4HeleqMMb8IReicoUPa0BMmTIlaglZE/IQi8HUqdGJGSI+lAP44aMAPdwA7CUiewFfBX5D8le0Dw72QCIyHfgSMN8YExORe4ATgSOAq40xd4nIL4Czgs89C2gwxuwmIicC/wt8SkTmB+9bAEwD/iYiuxtjerI1OxSmrHJrVp9LdUyzsaP52NF8hsxSku2sP79oDYDWFTuajx2X8tFs7ESRT6YjICYC7cAhwMeD28dyJWq48WkNiJqamqglZE3IQ4GOgPChHMAPHwXoIR58iT0a+Jkx5npgQhbHKwbGBsOCy4DNwEeAe4PXbwGOCR4fHTwneP0gSc5NOxq4yxjTaYx5E1gH7JuFpqyoWbgwqo/uE5fqmGZjR/Oxo/kMmVXAoH8tEZGbRGSLiKxK23aJiGwSkRXB7Yi015wZiaZ1xY7mY8elfDQbO1Hkk9EICGPMZ3ItJB/4sAZEVVVV1BKyJuQhFgPHVqfNBB/KAfzwUYAeWkTkG8CpwAdEZBRQMpQDGWM2ichVwH9Jrs7+F+AFoNEYEw922whMDx5PBzYE742LSBNQGWx/Nu3Q6e/JO1WO/TrgUh3TbOxoPnY0n8EhIn8EDMlO4tUi8hzhkcBHDXCIm4Gfsf1aEVcbY67a5rOcGommdcWO5mPHpXw0GztR5JPpVTBKReQLIvLzoDf3JhG5KdfihgufRszV1tZGLSFrQh7a2wtyBIQP5QB++ChAD58i+QX2LGPMO0A18OOhHEhEKkiOXtiF5BfWccBhw6Szr887R0SWiciyLVu20NHRQXt7O21tbXR2dtLc3Ew8HqehoQFjTG/ZpHrXa2trMSI0zJlDvLSU5pkz6Swvp23qVNqrquioqKClupp39tmHxtmzSRQVUTdvXvIYixaF7uvr6+np6aGpqYmuri5aW1uJxWLEYjFaW1vp6uqiqamJnp4e6uvrQzpS93V1dSQSCRobG+nu7qalpaVPT++++67dkzE0NDQQj8dpbm6ms7OTtrY22tvb6ejooKWlhe7ubhobG0kkEr3zLbfVU19fT09JCU2zZtE1fjyt06YRq6wkVllJ67RpdI0fz1sf/Sg9JSXUz53bZy518+Zl5GnAcsrQ0/r16wf2NFzlNHs23WVltFRX01FRQXtVFW1Tp9JZXk7zzJnES0t589BDMSLUBr8wpX5pql24cGvdG45yytDTG2+8kVXdG1Q59XM+dZeV9Z5Pbxx5ZN/n09y5W+tejs+ndE+vv/56zs6nYeIq4CfAJSRHkl0ePE/drBhj/gHUZ/hZTo1Eq3XsV1rX/tZrPnZcykezsRNJPsaYAW/A74AfAK8Dp5P8le3aTN6bi9s+++xjBsOzG541XIJ5+D8PD+p9LpJIJKKWkDUhD2PHGvO1r0UnZoj4UA7G+OHDJQ/AMjNwe7oLMDbt+Vhg1kDv6+dYxwM3pj0/jeRaD7VAcbDtvcCjweNHgfcGj4uD/QT4BvCNtOP07tffbbDtcFpIA94SIgPvl0fyWsc0m/7RumNH8+klk7Z4MLeg3S5Ne55xuw3MAlalPb8EWA+8DNwEVATbfwacmrbfjcAn+znmOcAyYNmMGTNMLBYzbW1tprW11XR0dJimpibT3d1t6uvrTSKRMDU1NcYYY7Zs2WKMMaZm4UKTEDH1c+aY7tJS0zRzpukoLzetU6eatqoqE6uoME0zZpiusjLTMHu26SkqMrXz5hkDZsuiRVvvjTF1dXUmHo+bxsZG09nZaVpaWkx7e7tpb283LS0tprOz0zQ2Npp4PG7q6upCOlL3tbW1pqenxzQ0NJiuri7T3Ny8nafGxka7p5oak0gkTH19venu7jZNTU2mo6PDtLa2mra2NhOLxUxzc7Pp6uoyDQ0Npqenx9TW1vapp27uXBMvKTGNs2aZzvHjTcu0aaa9stK0V1aalmnTTOf48aZhl11MvKTE1M2du30uYGrnzRvQ04DlNAhP9fX1dk/DWU6zZ5uusjLTXF1tYhUVpq2qyrROnWo6ystN08yZpru01NTtvrtJiJiahQuTuQT3obqXbTll6Km7uzurujeocurnfGquru49n+LFxX2fT7C17uX4fEr31NPTk5PzydYOZ9rwvhjcvxzclwDPZvLeXNwG+8X3mQ3PeNMBUV9fH7WErOn1kEgkq+B3vhOtoCHgQzkY44cPlzxk2AGxDBid9nw08PxA7+vnWPsBr5Bc+0FIru/wxaDT+MRgn18Anw8efwH4RfD4ROCe4PEC4CVgTPBF+w2gyPbZueyAqJ8zZ+D98khe65hm0z9ad+xoPr3koANiyO12Hx0QOwJFJEchXwbcFGzPuAMi/Taktljrih3Nx06B5aPZ2ImiHc70KhjdwX2jiCwE3gF2yPC9zuDDGhATJmSzVp0b9HroDKZRFuAUDB/KAfzwUYAeio0xXaknxpiu1GUyB4sx5t8ici+wHIgDLwK/Av4E3CUiPwy23Ri85UbgNhFZR3JY8InBcV4JrqCxOjjOF0xE844BJmzYENVH94lLdUyzsaP52NF8hsxwttvvph6LyK+Bh4Knm4AZabtWB9siQeuKHc3Hjkv5aDZ2osgn06tg/CqYa/wd4EGSX1KvzJmqYSbZCeMH7e3tUUvIml4PsVjyvgA7IHwoB/DDRwF6qBGR3oXLRORoklMhhoQx5nvGmD2MMQuNMZ82yfnDbxhj9jXG7GaMOd4Y0xns2xE83y14/Y2041xmjJltjJlrjPlzVg6zpH0Ht/q3Xapjmo0dzceO5jNkhq3dFpGd0p5+guQVNiD5/fpEERkjIrsAc4Dnhqg3a7Su2NF87LiUj2ZjJ4p8Mr0Kxm+Ch08Cu+ZOTm4wwWU4hcIfATFmzJioJWRNr4cC7oDwoRzADx8F6OF/gDtE5HrAkLzixGnRSnKLMU1NUUsI4VId02zsaD52NJ8hk95uQ/JqQp8e6E0icifwIWCKiGwEvgd8SEQWk2z/1wOfA/dGomldsaP52HEpH83GThT5ZNQBISI7klz5d5ox5vDgUkHvNcbcOMBbncKHKRjxeNy5E2mw9HpIdUAU4GU4fSgH8MNHoXkwxrwO7C8i44PnrRFLco742LFO/YF2qY5pNnY0Hzuaz9AYarttjDmpj839fnc2xlxGcl2IyNG6YkfzseNSPpqNnSjyyXQKxs0kV0WfFjz/D/DlHOjJCT5NwfChE6XXQ2rITwGOgPChHMAPH4XmQUR2FJEbgd8ZY1pFZL6InBW1LpeQnsh+9OsTl+qYZmNH87Gj+QwNESkXkf8DngCeEJGfiEh5xLJyitYVO5qPHZfy0WzsRJFPph0QU4wx9wAJAGNMHHArvQzwYQrGqFGZFpm79Hoo4CkYPpQD+OGjAD3cTAF36OaDUfF41BJCuFTHNBs7mo8dzWfI3AS0ACcEt2bgt5EqyjFaV+xoPnZcykezsRNFPpl+YpuIVJKcr4aI7A+4M3ZkAFJrQPhAd3f3wDs5Tq+HAu6A8KEcwA8fBejBiw7dXNI9blzUEkK4VMc0Gzuajx3NZ8jMDhb8fSO4fZ8CXBNtMGhdsaP52HEpH83GThT5ZHoZzgtIrs47W0T+CVQBn8yZqhzh2hCcoVBaWhq1hKzp9VDAHRA+lAP44aMAPRR0h24+KK2vj1pCCJfqmGZjR/Oxo/kMmZiIHGiMeRpARN4HxCLWlFO0rtjRfOy4lI9mYyeKfDIaAWGMWQ58EDiA5Gq9C4wxL+dS2HDi0xoQbW1tUUvIml4PBdwB4UM5gB8+CtDDth26twJfjFaSW7TttNPAO+URl+qYZmNH87Gj+QyZc4HrRWS9iLwF/Izg6hW+onXFjuZjx6V8NBs7UeST6VUwioAjgFnBew4REYwx/5dDbcOOD2tATJw4MWoJWdProYA7IHwoB/DDRwF6mA0cDswAjgP2I/PRaCOCievXRy0hhEt1TLOxo/nY0XyGhjFmBbCXiEwMnjdHqyj3aF2xo/nYcSkfzcZOFPlkugbEH4EzgEpgQtqtIPBpDYiGhoaoJWRNr4cC7oDwoRzADx8F6OE7wZfXCuDDwM+BG6KV5BYNu+8etYQQLtUxzcaO5mNH8xkaIlIpIteRvArG4yJybTCVzlu0rtjRfOy4lI9mYyeKfDL91a3aGLNnTpXkAR/WgKisLPy/d70eUh0QZWXRiRkiPpQD+OGjAD2kFpw8Evi1MeZPIvLDKAW5RuWaNVFLCOFSHdNs7Gg+djSfIXMX8A+So9YATgHuBj4amaIco3XFjuZjx6V8NBs7UeST6QiIP4vIITlVkkN8WgOipqYmaglZ0+uhvT15X4AjIHwoB/DDRwF62CQivwQ+BTwsImPIvC0eEdQsWhS1hBAu1THNxo7mY0fzGTI7GWN+YIx5M7j9ENgxalG5ROuKHc3Hjkv5aDZ2osgn0y+9zwL3iUhMRJpFpEVECm7+mw9rQFRVVUUtIWt6PRTwFAwfygH88FGAHk4AHgUONcY0ApOBCyNV5BhVK1dGLSGES3VMs7Gj+djRfIbMX0TkRBEZFdxS7bi3aF2xo/nYcSkfzcZOFPlk2gHxf8B7gTJjzERjzARjjFsreljwaQ0I13rxhkKvh1gMRo+GUYX3468P5QB++Cg0D8aYdmPMH4wxa4Pnm40xf4lal0vorwP9o9nY0XzsaD5D5mzgDqAzuN0FfK5Qf5DLBK0rdjQfOy7lo9nYcXkExAZglSnQuQwp2T6sAeFaL95QCI2AKMDRD+BHOYAfPnzwoITRXwf6R7Oxo/nY0XyGTDnJxdh/YIwpIXlVuI8W2g9yg0Hrih3Nx45L+Wg2dlweAfEG8ISIfENELkjdciksF/gwBaO+vj5qCVnT66GAOyB8KAfww4cPHpQw9XPnRi0hhEt1TLOxo/nY0XyGzPXA/sBJwfMW4GfRyck9WlfsaD52XMpHs7ETRT6ZXgXjzeA2OrgVFD5NwSgvL49aQtb0eijgDggfygH88OGDByVM+RtvRC0hhEt1TLOxo/nY0XyGzH7GmCUi8iKAMaZBRAru+/Bg0LpiR/Ox41I+mo2dKPLJaASEMeb7fd1yLW648WEKRmtra9QSsqbXQwF3QPhQDuCHDx88KGFap0+PWkIIl+qYZmNH87Gj+QyZbhEpguQvWiJSBSSilZRbtK7Y0XzsuJSPZmMninwKb/W/Ec7YAv2HPZ1eD7EYlJVFK2aI+FAO4IcPHzwoYcbW1kYtIYRLdUyzsaP52NF8hsx1wH3ADiJyGfA0cHm0knKL1hU7mo8dl/LRbOxEkY92QBQYXV1dUUvIml4PjY0wfnykWoaKD+UAfvjwwYMSpmuiW2u6uVTHNBs7mo8dzWdoGGPuAC4CrgA2A8cYY34XrarconXFjuZjx6V8NBs7UeSTUQeEiLwvk21K7ikqKopaQtYUFRVBIgErV8KCBVHLGRI+lAP44cMHD0qYos7OqCWEcKmOaTZ2NB87ms/QMca8aoy53hjzM2PMmqj15BqtK3Y0Hzsu5aPZ2Ikin0xHQPw0w22Kkhmvvw4tLbBkSdRKFEVRFEVRFEVRlDxgvQqGiLwXOACo2uaymxMBt7qTLBjjz1Uwenp6opaQNT09PbB8efJJgXZA+FAO4IcPHzwoYXrGjIlaQgiX6phmY0fzsaP5KJmidcWO5mPHpXw0GztR5DPQZThHA+OD/SakbW8GPpkrUblCKPyrYIweXfhXfRo9ejS88AKMHg3z50ctZ0j4UA7ghw8fPChhRjc3Ry0hhEt1TLOxo/nY0XyUTNG6YkfzseNSPpqNnSjysXZAGGOeBJ4UkZuNMW8BiMgoYLwxxq30RgixWMy5E2mwxGIxRi9fDosWJTshChAfygH88OGDByVMbMoURjt02SyX6phmY0fzsaP5KJmidcWO5mPHpXw0GztR5JPpGhBXiMhEERkHrAJWi8iFOdSl9MP4Ar1qRDrjx41LTsEo0OkX4Ec5gB8+fPCghBm/aVPUEkK4VMc0Gzuajx3NR8kUrSt2NB87LuWj2diJIp9MOyDmByMejgH+DOwCfDpXopT+aWpqilpC1rSsWgUNDQXdAeFDOYAfPnzwoIRp2nXXqCWEcKmOaTZ2NB87mo+SKVpX7Gg+dlzKR7OxE0U+mXZAlIhICckOiAeNMd2APys7FhCTJ0+OWkLWTHrjjeSDAu6A8KEcwA8fPnhQwkx+7bWoJYRwqY5pNnY0Hzuaj5IpWlfsaD52XMpHs7ETRT6ZdkD8ElgPjAP+ISI7k1yIsiAwHvWV1NTURC0ha9qefhqKipJrQBQoPpQD+OHDBw9KmBrH2gaX6phmY0fzsaP5KJmidcWO5mPHpXw0GztR5DPQVTAAMMZcB1yXtuktEflwbiTlDpHCvwpGVVVV1BKyZtyrryavfjF2bNRShowP5QB++PDBgxKmauXKqCWEcKmOaTZ2NB87mo+SKVpX7Gg+dlzKR7OxE0U+GY2AEJEdReRGEflz8Hw+cHpOlSl94lov3qAxhsTzz8M++0StJCsKvhwCfPDhgwcljP460D+ajR3Nx47mo2SK1hU7mo8dl/LRbOxEkU+mUzBuBh4FpgXP/wN8OZM3ishhIvKaiKwTkYst+x0nIkZElmaoaUTiWi/eoNm8mVG1tQW9/gN4UA4BPvjwwYMSRn8d6B/Nxo7mY0fzUTJF64odzceOS/loNnacHQEBTDHG3AMkAIwxcaBnoDeJSBFwPXA4MB84KRg9se1+E4DzgX9nqGfEUldXF7WE7Fi+PHlf4B0QBV8OAT748MGDEqZu3ryoJYRwqY5pNnY0Hzuaj5IpWlfsaD52XMpHs7ETRT6ZdkC0iUglwZUvRGR/IJNrduwLrDPGvGGM6QLuAo7uY78fAP8LdGSoZ8RSUVERtYTsWL4cIwJ77RW1kqwo+HII8MGHDx6UMBX/+U/UEkK4VMc0Gzuajx3NR8kUrSt2NB87LuWj2diJIp9MOyAuAB4EZovIP4FbgS9m8L7pwIa05xuDbb2IyBJghjHmTxlqGTTG+HMVjObmgrn4SN8sX05izhwYPz5qJVlR8OUQ4IMPHzxkg4hMEpF7ReRVEVkjIu8Vkcki8lcRWRvcVwT7iohcF0yJezlof1PHOT3Yf62IRLrGT/OsWVF+/Ha4VMc0Gzuajx3NR8kUrSt2NB87LuWj2diJIp+MOiCMMcuBDwIHAJ8DFhhjXs72w0VkFPB/wFcz2PccEVkmIsu2bNlCR0cH7e3ttLW10dnZSXNzM/F4nIaGBowx1NbWAtssrGGgoaGBeDxOc3MznZ2dtLW10d7eTkdHBy0tLXR3d9PY2EgikegdkpI6Ruq+vr6enp4empqa6OrqorW1lVgsRiwWo7W1la6uLpqamujp6aG+vr7PY9TV1ZFIJGhsbKS7u5uWlpaMPI0bN673GLW1tRhjCspTYtkyzN5791tOheJp1KhRGdc9lz2NHj0647rnqqdx48YN+Xwabk8RcS3wiDFmD2AvYA1wMfCYMWYO8FjwHJLT4eYEt3OAGwBEZDLwPWA/kiPXvpfqtIiCcZs3R/XRfTJu3LioJfSi2djRfOxoPkqmaF2xo/nYcSkfzcZOFPlIJqMDRKQU+DxwIMlpGE8BvzDGWKdMiMh7gUuMMYcGz78BYIy5InheDrwOtAZvmQrUA0cZY5b1d9ylS5eaZcv6fXk7/vr6Xznk9kN4+jNP876Z78v4fS7S0tLChAkTopYxNLZsgR13pOOyyyj95jejVpMVBV0OafjgwyUPIvKCMSZvC+kGbegKYFeT1piLyGvAh4wxm0VkJ+AJY8xcEfll8PjO9P1SN2PM54Ltof36YrDtcJroAXdpqa5mwsaN9p3yOLItr3VsgHw0Gzuaj52Rkk++2+IoGVJbrHXFjuZjp8Dy0WzsRNEOZzoF41ZgAfBT4GfB49syeN/zwBwR2UVERgMnkpzKAYAxpskYM8UYM8sYMwt4lgE6H0Y6JSUlUUsYOi++CMCoAr8EJxR4OaThgw8fPGTBLkAN8FsReVFEfiMi44AdjTGpLvZ3gB2Dx/1Nixtwulw+KWlri+qj+8SlOqbZ2NF87Gg+SqZoXbGj+dhxKR/Nxk4U+WTaAbHQGHOWMebx4HY2yU4IK8HVMs4jeQnPNcA9xphXRORSETlq6LJHLolEImoJQye4AkbcsevfDoWCLoc0fPDhg4csKAaWADcYY/YG2tg63QKAYGTEsHSlZzsVrra2FiNCw5w5xEtLaZ45k87yctqmTqW9qoqOigpaqqvpnDCBxtmzSRQV9a4Wnbpuduo+n1Phurq68jcdqaSEplmz6Bo/ntZp04hVVhKrrKR12jS6xo+nadYsekpKqJ87t89c6ubNc2I6Uk6mjc2eTXdZGS3V1XRUVNBeVUXb1Kl0lpfTPHMm8dJSGnbbDSNC7cKFyWME97ULF26tey55Gs5y6ud86i4r23o+7bFH3+fT3Llb655LnrIoJyU7EsXFUUsI4drfes3Hjkv5aDZ2osgn0ykYtwM/M8Y8GzzfD/iCMea0HOvrk5E8BaOtrc25uUwZc/zxsHw5bS+/XLgeAgq6HNLwwYdLHiKYgjEVeDYYQYaIvJ9kB8RuFPAUjLapUxn3zjv2nfI4PDGvdWyAfDQbO5qPnZGSj07BGACtK3Y0HzsFlo9mYyeKdtg6AkJEVorIy8A+wL9EZL2IvAk8A4yIht01ih3rNRsUy5fDkiWF7SHABw/ghw8fPAwVY8w7wAYRmRtsOghYTXKqW+pKFqcDDwSPHwROC66GsT/QFEzVeBQ4REQqgsUnDwm2RUJxLBbVR/eJS3VMs7Gj+djRfJRM0bpiR/Ox41I+mo2dKPIZ6BM/lhcVOcYMz+hjJ+js7GTMmDFRyxg8DQ3wxhvw2c8Wroc0fPAAfvjwwUOWfBG4I1hn5w3gMyQ7l+8RkbOAt4ATgn0fBo4A1gHtwb4YY+pF5Ack1+0BuNQYU58/C2E6y8sZ09QU1cdvh0t1TLOxo/nY0XyUTNG6YkfzseNSPpqNnSjysXZAGGPeypeQfCAZDItxnbKysqglDI0VK5L3++xTuB7S8MED+OHDBw/ZYIxZQd8j0g7qY18DfKGf49wE3DSs4oZI2ZYtUUsI4VId02zsaD52NB8lU7Su2NF87LiUj2ZjJ4p8Ml2EUnGElpaWqCUMjWABSvbeu3A9pOGDB/DDhw8elDAtM2ZELSGES3VMs7Gj+djRfJRM0bpiR/Ox41I+mo2dKPJxa1KMMiCTJk2KWsLQWL4cZsyAqiom5XFhlVxRsOWwDT748MGDEmbSunVRSwjhUh3TbOxoPnY0HyVTtK7Y0XzsuJSPZmMninx0BESBkbrcVMERLEAJBewhDR88gB8+fPCghKlbMOBVnvOKS3VMs7Gj+djRfJRM0bpiR/Ox41I+mo2dKPLRDogCY8qUKVFLGDytrfDaa70dEAXpYRt88AB++PDBgxJmyqpVUUsI4VId02zsaD52NB8lU7Su2NF87LiUj2ZjJ4p8RkQHhPFgyH+KmpqaqCUMnpdeSl7PNuiAKEgP2+CDB/DDhw8elDA1CxdGLSGES3VMs7Gj+djRfJRM0bpiR/Ox41I+mo2dKPIZER0QKYTCvwpGVVVV1BIGzwsvJO+DDoiC9LANPngAP3z44EEJU+XYrwMu1THNxo7mY0fzUTJF64odzceOS/loNnaiyGdEdUD4QG1tbdQSBs/y5bDjjrDTTkCBetgGHzyAHz588KCEqXXs1wGX6phmY0fzsaP55BcRuUlEtojIqrRtk0XkryKyNrivCLaLiFwnIutE5GURWRKdcq0rA6H52HEpH83GThT5aAdEgVFZWRm1hMGTWoBSkiNQCtLDNvjgAfzw4YMHJUzlK69ELSGES3VMs7Gj+djRfPLOzcBh22y7GHjMGDMHeCx4DnA4MCe4nQPckCeNfaJ1xY7mY8elfDQbO1Hkox0QBUZjY2PUEgZHLAarV/dOv4AC9NAHPngAP3z44EEJ07jbblFLCOFSHdNs7Gg+djSf/GKM+QdQv83mo4Fbgse3AMekbb/VJHkWmCQiO+VFaB9oXbGj+dhxKR/Nxk4U+WgHRIExYcKEqCUMjpUroacn1AFRcB76wAcP4IcPHzwoYSZs2BC1hBAu1THNxo7mY0fzcYIdjTGbg8fvADsGj6cD6QW0MdgWCVpX7Gg+dlzKR7OxE0U+I6IDwuDPVTDa29ujljA4li9P3qd1QBSchz7wwQP44cMHD0qY9h12iFpCCJfqmGZjR/Oxo/m4hUlepm3QX1JF5BwRWSYiy7Zs2UJHRwft7e20tbXR2dlJc3Mz8XichoYGjDG9c7xTq93XLlyIEaFhzhzipaU0z5xJZ3k5bVOn0l5VRUdFBTWLFtFdVkbj7NkkioqomzcveYxFi0L39fX19PT00NTURFdXF62trcRiMWKxGK2trXR1ddHU1ERPTw/19fUhHan7uro6EokEjY2NdHd309LSsp2nLVu22D3V1mKMoaGhgXg8TnNzM52dnbS1tdHe3k5HRwctLS10d3fT2NhIIpGgrq6uTz31c+fSU1JC06xZdI0fT+u0acQqK4lVVtI6bRpd48ezZfFiekpKqJ87t89c6ubNG9DTgOU0CE/vvvuu3dNwltPs2XSXldFSXU1HRQXtVVW0TZ1KZ3k5zTNnEi8t5Z2lSzEivesdpK78EKp72ZZThp5aWlqyqnuDKqd+zqeW6ure86l16tT+z6dU3cvx+ZTuqa2tLSfnkw0pxEtULl261Cxbtizj/R9Z9wiH33E4z5z1DPtX759DZbmns7OTMWPGRC0jc845B37/e6it7V0DouA89IEPHsAPHy55EJEXjDFLo9aRDwbbDvciA1+NqLO8nDFNTfad8vi3K691bIB8NBs7mo+dkZKPS22xiMwCHjLGLAyevwZ8yBizOZhi8YQxZq6I/DJ4fOe2+9mOP6S2WOuKHc3HToHlo9nYiaIdHhEjIHwiHo9HLWFwbLMAJRSghz7wwQP44cMHD0qY+NixUUsI4VId02zsaD52NB8neBA4PXh8OvBA2vbTgqth7A80DdT5kEu0rtjRfOy4lI9mYyeKfLQDosCQDHrWnKGrK7kGxJLwlaQKykM/+OAB/PDhgwcljPT0RC0hhEt1TLOxo/nY0Xzyi4jcCTwDzBWRjSJyFvAj4GARWQt8NHgO8DDwBrAO+DXw+Qgk96J1xY7mY8elfDQbO1HkU5z3T1SyYtSoAuozWr062QmxTQdEQXnoBx88gB8+fPCghBnl2K8VLtUxzcaO5mNH88kvxpiT+nnpoD72NcAXcqsoc7Su2NF87LiUj2ZjJ4p83CoRZUC6u7ujlpA5fSxACQXmoR988AB++PDBgxKme9y4qCWEcKmOaTZ2NB87mo+SKVpX7Gg+dlzKR7OxE0U+I6IDohAX2uyP0tLSqCVkzvLlMGECzJ4d2lxQHvrBBw/ghw8fPChhSoOVnV3BpTqm2djRfOxoPkqmaF2xo/nYcSkfzcZOFPmMiA6IFIJbc4CGQltbW9QSMmf5cth7b9hmaE9BeegHHzyAHz588KCEadtpp6glhHCpjmk2djQfO5qPkilaV+xoPnZcykezsRNFPiOqA8IHJk6cGLWEzIjHYcWK7aZfQAF5sOCDB/DDhw8elDAT16+PWkIIl+qYZmNH87Gj+SiZonXFjuZjx6V8NBs7UeSjHRAFRkNDQ9QSMuO11yAW67MDomA8WPDBA/jhwwcPSpiG3XePWkIIl+qYZmNH87Gj+SiZonXFjuZjx6V8NBs7UeSjHRAFRmVlZdQSMqOfBSihgDxY8MED+OHDBw9KmMo1a6KWEMKlOqbZ2NF87Gg+SqZoXbGj+dhxKR/Nxk4U+WgHRIFRU1MTtYTMWL4cxo6FuXO3e6lgPFjwwQP44cMHD0qYmkWLopYQwqU6ptnY0XzsaD5KpmhdsaP52HEpH83GThT5jIgOCIM/V8GoqqqKWkJmLF8Oe+0FxcXbvVQwHiz44AH88OGDByVM1cqVUUsI4VId02zsaD52NB8lU7Su2NF87LiUj2ZjJ4p8RkQHRAqRwr8Khmu9eH2SSMCLL8I++/T5ckF4GAAfPIAfPnzwoITRXwf6R7Oxo/nY0XyUTNG6YkfzseNSPpqNHR0BoQyIa714ffL669DS0uf6D1AgHgbABw/ghw8fPChh9NeB/tFs7Gg+djQfJVO0rtjRfOy4lI9mY0dHQCgDUl9fH7WEgbEsQAkF4mEAfPAAfvjwwYMSpr6PtWOixKU6ptnY0XzsaD5KpmhdsaP52HEpH83GThT5aAdEgVFeXh61hIFZvhxGj4b58/t8uSA8DIAPHsAPHz54UMKUv/FG1BJCuFTHNBs7mo8dzUfJFK0rdjQfOy7lo9nYiSIf7YAoMFpbW6OWMDDLl8OiRclOiD4oCA8D4IMH8MOHDx6UMK3Tp0ctIYRLdUyzsaP52NF8lEzRumJH87HjUj6ajZ0o8hkRHRDG+HMVjLFjx0YtwY4xyQ6IfqZfQAF4yAAfPIAfPnzwoIQZW1sbtYQQLtUxzcaO5mNH81EyReuKHc3Hjkv5aDZ2oshnRHRApBAK/yoYXV1dUUuw89//Qn29tQPCeQ8Z4IMH8MOHDx6UMF0TJ0YtIYRLdUyzsaP52NF8lEzRumJH87HjUj6ajZ0o8hlRHRA+UFRUFLUEOwMsQAkF4CEDfPAAfvjwwYMSpqizM2oJIVyqY5qNHc3HjuajZIrWFTuajx2X8tFs7ESRj3ZAKMPLCy9AUVFyDQhFURRFURRFURRFCdAOiAKjp6cnagl2li9PXv3CMp/IeQ8Z4IMH8MOHDx6UMD1jxkQtIYRLdUyzsaP52NF8lEzRumJH87HjUj6ajZ0o8tEOiAJjdD9XlnACY5IjICzTL8BxDxnigwfww4cPHrJFRIpE5EUReSh4vouI/FtE1onI3SIyOtg+Jni+Lnh9VtoxvhFsf01EDo3ICgCjm5uj/PjtcKmOaTZ2NB87mo+SKVpX7Gg+dlzKR7OxE0U+I6IDwuDPVTBisVjUEvpn82bYsmXADginPWSIDx7ADx8+eBgGzgfWpD3/X+BqY8xuQANwVrD9LKAh2H51sB8iMh84EVgAHAb8XEQimzQZmzIlqo/uE5fqmGZjR/Oxo/komaJ1xY7mY8elfDQbO1HkMyI6IFKIFP5VMMaPHx+1hP5JLUC5zz7W3Zz2kCE+eAA/fPjgIRtEpBo4EvhN8FyAjwD3BrvcAhwTPD46eE7w+kHB/kcDdxljOo0xbwLrgH3zYqAPxm/aFNVH94lLdUyzsaP52NF8lEzRumJH87HjUj6ajZ0o8hlRHRA+0NTUFLWE/lm+HERgr72suzntIUN88AB++PDBQ5ZcA1wEJILnlUCjMSYePN8ITA8eTwc2AASvNwX7927v4z15p2nXXaP66D5xqY5pNnY0Hzuaj5IpWlfsaD52XMpHs7ETRT7aAVFgTJ48OWoJ/bN8OcydCwP0pDntIUN88AB++PDBw1ARkY8BW4wxL+Tp884RkWUismzLli10dHTQ3t5OW1sbnZ2dNDc3E4/HaWhowBhDbW0tADU1NQDU1tZiRGiYM4d4aSnNM2fSWV5O29SptFdV0VFRQUt1NRM2bKBx9mwSRUXUzZuXPEZwZZ3UfX19PT09PTQ1NdHV1UVrayuxWIxYLEZraytdXV00NTXR09NDfX19SEfqvq6ujkQiQWNjI93d3bS0tPTpaeLEiXZPxtDQ0EA8Hqe5uZnOzk7a2tpob2+no6ODlpYWuru7aWxsJJFIUFdX16ee+vp6ekpKaJo1i67x42mdNo1YZSWxykpap02ja/x4ijo76SkpoX7u3D5zqZs3LyNPA5ZThp5GjRo1sKfhKqfZs+kuK6OlupqOigraq6pomzqVzvJymmfOJF5aiiQSGBFqFy5MHiO4r124cGvdG45yytBTiqHWvUGVUz/nU3dZWe/5ZEaN6vt8mjt3a93L8fmU7imRSOTsfFKyY/Jrr0UtIYRrf+s1Hzsu5aPZ2IkiHzGm8NZHWLp0qVm2bFnG+z/0n4f4+J0f5/mzn2fptKU5VJZ7ampqqKqqilpG38ycCe9/P9xxh3U3pz1kiA8ewA8fLnkQkReMMXlrZETkCuDTQBwoBSYC9wGHAlONMXEReS9wiTHmUBF5NHj8jIgUA+8AVcDFAMaYK4Lj9u7X32cPth1OEz3gLjWLFlG1cqV9pzz+7cprHRsgH83GjuZjZ6Tkk++2OEqG1BZrXbGj+dgpsHw0GztRtMM6AqLAcOUfre2oqYENGwZcgBIc9jAIfPAAfvjwwcNQMcZ8wxhTbYyZRXIRyb8bY04BHgc+Gex2OvBA8PjB4DnB6383yV7oB4ETg6tk7ALMAZ7Lk43tGPAPc55xqY5pNnY0Hzuaj5IpWlfsaD52XMpHs7ETRT4jogOiEEd59IezQwtffDF5n0EHhLMeBoEPHsAPHz54yAFfBy4QkXUk13i4Mdh+I1AZbL+ArSMfXgHuAVYDjwBfMMZEduHs1LBwV3Cpjmk2djQfO5qPkilaV+xoPnZcykezsRNFPsV5/8QIEQr/Khiu9eL1kroCxt57D7irsx4GgQ8ewA8fPngYDowxTwBPBI/foI+rWBhjOoDj+3n/ZcBluVOYOfrrQP9oNnY0Hzuaj5IpWlfsaD52XMpHs7GjIyCUAUkttuQc//oX7LorTJo04K7OehgEPngAP3z44EEJk1p40hVcqmOajR3Nx47mo2SK1hU7mo8dl/LRbOxEkY92QBQYFRUVUUvYnvp6ePRROProjHZ30sMg8cED+OHDBw9KmIr//CdqCSFcqmOajR3Nx47mo2SK1hU7mo8dl/LRbOxEkY92QBQYzc3NUUvYnnvvha4uOPXUjHZ30sMg8cED+OHDBw9KmOZZs6KWEMKlOqbZ2NF87Gg+SqZoXbGj+dhxKR/Nxk4U+WgHRIExbty4qCVsz+23w7x5Ga3/AI56GCQ+eAA/fPjgQQkzbvPmqCWEcKmOaTZ2NB87mo+SKVpX7Gg+dlzKR7PZSmNjI5/85CfZY489mDdvHs888wydnZ0cfPDBzJkzh4MPPpiGhoac6xgRHRAGf66C0dHREbWEMG+9BU89lRz9kMG1b8FBD0PABw/ghw8fPChhOiZPjlpCCJfqmGZjR/Oxo/komaJ1xY7mY8elfDSbrZx//vkcdthhvPrqq7z00kvMmzePK664goMOOoi1a9dy0EEH8aMf/SjnOkZEB0QKyfAfZJcpKSmJWkKY//f/kvcnn5zxW5zzMAR88AB++PDBgxKmpK0tagkhXKpjmo0dzceO5qNkitYVO5qPHZfy0WySNDU18Y9//IOzzjoLgNGjRzNp0iQefvhhTj/9dABOP/107r///pxrGVEdED6QSCSilrAVY+C22+DAA2EQ85mc8jBEfPAAfvjwwYMSJlHs1hWiXapjmo0dzceO5qNkitYVO5qPHZfy0WySvPnmm1RVVfGZz3yGvffem89+9rO0tbWxZcsWdtppJwCmTp3Ku+++m3Mt2gFRYBjj0HSSFStgzZqMF59M4ZSHIeKDB/DDhw8elDCmqChqCSFcqmOajR3Nx47mo2SK1hU7mo8dl/LRbJLE43GWL1/Oueeey4svvsi4ceO2m24hInmZMaAdEAVGsUM9itxxB5SUwPHHD+ptTnkYIj54AD98+OBBCVMci0UtIYRLdUyzsaP52NF8lEzRumJH87HjUj6aTZLq6mqqq6vZb7/9APjkJz/J8uXL2WGHHdgcLIy5efNmdthhh5xr0Q6IAqOzszNqCUl6epLrPxxxBAxyMRVnPGSBDx7ADx8+eFDCdJaXRy0hhEt1TLOxo/nY0XyUTNG6YkfzseNSPppNkqlTpzJjxgxee+01AB577DHmz5/PYYcdxi233ALALbfcwtFHH51zLW51CeUI14beZENZWVnUEpI8/jhs3jzo6RfgkIcs8MED+OHDBw9KmLItW6KWEMKlOqbZ2NF87Gg+SqZoXbGj+dhxKR/NZis//elPOeWUU+jq6mLXXXflt7/9LV1dXZx88snceOON7Lzzztxzzz051zGiRkAIhX8VjJaWlqglJLn9dpg4ET72sUG/1RkPWeCDB/DDhw8elDAtM2ZELSGES3VMs7Gj+djRfJRM0bpiR/Ox41I+ms1WFi9ezLJly3j55Ze5//77qaioYPTo0Tz22GOsXbuWv/3tb0zOw2VCcz4CQkQOA64FioDfGGN+tM3rFwCfBeJADXCmMeatXOsqVCZNmhS1BGhvhz/8Ibn2Q2npoN/uhIcs8cED+OHDBw9KmEnr1kUtIYRLdUyzsaP52NF8lEzRumJH87HjUj4jORv5/sA/vguCwT5bwHxveGcT5HQEhIgUAdcDhwPzgZNEZP42u70ILDXG7AncC1yZS02FTl1dXdQS4I9/hJaWIU2/AEc8ZIkPHsAPHz54UMLULVgQtYQQLtUxzcaO5mNH81EyReuKHc3Hjkv5aDZ2FozPv55cj4DYF1hnjHkDQETuAo4GVqd2MMY8nrb/s8DQ/qsdIUyZMiVqCcnpF9XV8MEPDuntTnjIEh88gB8+fPCghJmyalXUEkK4VMc0Gzuajx3NR8kUrSt2osxn1qxZTJgwgaKiIoqLi1m2bBmjRo3i4IMPZv369cyaNYt77rmHioqKyDS6lk99fT2f+tSnnMjHtXNrVWv+9eR6DYjpwIa05xuDbf1xFvDnvl4QkXNEZJmILNuyZQsdHR20t7fT1tZGZ2cnzc3NxONxGhoaMMZQW1sLQE1NTe8xjDE0NDQQj8dpbm6ms7OTtrY22tvb6ejooKWlhe7ubhobG0kkEr09ZqljpO7r6+vp6emhqamJrq4uWltbicVixGIxWltb6erqoqmpiZ6eHurr6/s8Rl1dHYlEgsbGRrq7u2lpacnIU01NTe8xamtr8+/p3XcxjzwCJ59MzTbHytTTO++80285ReJpCOW0YcOGjOuey542b96ccd37/+2deXhU5dn/P3dCTEISAgkBwmZQFgMJhEWwriguuDTI6lKr1IVWitZaqbT1VbTaUqstpX27qOUnVit1qcqr1qoIbXFHDLvihhWIIYQQyEqW5/fHnMQMJCeTZGbOM5P7c11zzZkzZ8753t9zn3tmnvOc59gaU3FxcYePp2DHpASH4pwcryX4YdP+VW/cUX/cUX+UQNFcccdrf9asWUNBQQHr168H4Pbbb2fKlCl89NFHTJkyhSVLlrSxhtBikz/FxcUsWbLEGn+89uZIcpLDr0dCeYcIEZkFTDXGXOu8/iYwyRizoIVlrwAWAGcYY1zvlzJhwgTTeMAFwrMfPMv0v01nw7wNjM0c264YlCP4/e/hu9+FjRth9Giv1SiKVYjIe8aYCV7rCAftrcNNSJAGA46iuxv5EQx/1Bt31B93osAfrcVtoLnijuX+ZGVlsX79er9eISNGjGDt2rVkZmZSWFjI5MmTm263GHTUn9axzJtAxoAIhI6MAeFWh0PdA2I30Hyoz4HOPD9E5GzgJ0B+W40PnUGClRQe0njW1jMefRRyczvV+OB5DEEgGmKA6IgjGmJQ/Nln2dkBm3JMvXFH/XFH/VECRXPFHS/9ERHOPfdcxo8fzwMPPADAl19+SWZmJgD9+vWjqKjIM31glz/79u2jqKjIGn9sO7a86AER6jEg3gWGicgQfA0PlwKXN19ARMYCf8LXU8Kem8ZaSnp6uncb/+QTePNN+MUvOrUaT2MIEtEQA0RHHNEQg+JP+tatXkvww6YcU2/cUX/cUX+UQNFcccdLf9atW8eAAQPYu3cv55xzDieccILfSVYR8fykq03+jBgxwu99r/2x7djaWh5+PSHtAWGMqcN3WcU/ge3AE8aYrSJyl4jkO4v9EkgGnhSRAhFZFUpNkc6BAwe82/hf/+rrWnTZZZ1ajacxBIloiAGiI45oiEHx58DQoV5L8MOmHFNv3FF/3FF/lEDRXHHHS38GDPANp9enTx+mT5/OO++8Q0ZGBoWFhQAUFhbSp08fz/SBXf7861//om/fvtb4Y9uxNbR7+PWE+hIMjDEvGmOGG2OON8bc48y73Rizypk+2xjT1xiT5zzy3dfYtUlJSfFmw8b4Lr844wwYNKjt5V3wLIYgEg0xQHTEEQ0xKP6kfPFF2wuFEZtyTL1xR/1xR/2xBxHZKSKbnZNv6515aSLyioh85Dx7dhsDzRV3vPKnoqKCQ4cONU2//PLL5OTkkJ+fz4oVKwBYsWIF06ZN80RfIzb5M378eKv8se3Y+qI6/HpC3gChBJfKykpvNrx+PezYAVd0/i6pnsUQRKIhBoiOOKIhBsWfSo/P3ByJTTmm3rij/rij/ljHmc7Jt8aB2hYBq40xw4DVzmtP0Fxxxyt/ioqKOPXUUxkzZgwTJ07kwgsvZOrUqdxwww288sorDBs2jFdffZVFizxLHcAuf0477TQWLVpkjT+2HVt9jgm/nlCPAWEFobzTR7iJj4/3ZsOPPgrx8TBzZqdX5VkMQSQaYoDoiCMaYlD8iS8r81qCHzblmHrjjvrjjvpjPdOAyc70CmAtcKsXQjRX3PHKn+OOO46NGzceNT8zM5PVq1d7oKhlbPKnpqaGHj16WOOPbcdWWV349XSJBohGhMi/C0ZdXV34i3BdHaxcCRddBD17BmF1HsQQZKIhBoiOOKIhBsWfusREq76gbcox9cYd9ccd9ccqDPCyiBjgT8aYB4C+xphC5/0vgb4tfVBE5gHzAAYNGkR1dTUNDQ0YY+jWrRs1NTV0796dQ4cO0bNnT0pKSujduzfFxcVkZGSwLyeH9K1bOTB0KClffEFlnz7El5VRl5iI1NcTU1fHwWOPpdeOHVRkZtJj505Khw8nfft2inNzydi82fcM7N+/n9TUVMrLy0lMTOTw4cPExsYCUF9fzzHHHENVVRXJycmUlZWRlpbWpKPxuaSkhF69enHw4EGSkpKorq4mLi7OL6YDBw6Qnp7eekz79pGens6BAwdISUmhsrKS+Ph46urqEBFiYmKora0lISGBiooKevToQWlpKenp6Ufp2T9iBKmffkr5gAEk7tvH4R49iK3x3aSvPj6eYw4epHToUDI2baLsuONI+/BDf182b6YkO5teDQ2uMbW5n5yYRtw3gi+qv6DPMX0oqysjMSaRelNPnakjKTaJ/bX7yUnO4b2D7zE8aTjbK7aTm5zL5vLNTc8juo9g681bg7Ofjj+epMJCqtPSiKuooKFbN0xsLN2qqqhJTaX73r2UZGeT+fbblIwaRe8tWyjOySFjyxb/3Kur69x+2r+ffr/rx4D4Aeyr3UePbj2oafDtp/iYeA7WHaR3XO8mnz6s/PAoX7KTstlRsYN939vX6f104MABUhISWjyeapOSSNi/n4rMTGKrqijv3//o42nz5q9yr6wsKMdT95jupMWlUVFfQTfpRqzEUtVQRWq3VPYe3sughEGU15UzKHkQW8q3kJOc0/S8tXwrQ7sP5YvqLzh48GC795MbEom9A9p7z+Nntj/DjCdmUPDtAsb0GxNCZaGnsrKS7t27h3ejL70E558PzzwDF1/c6dV5EkOQiYYYIDrisCkGvfd8AAQw8nRlRgbdi4vdFwrjd1dYc6wNf9Qbd9Qfd7qKP5FQi0VkgDFmt4j0AV4BbgBWGWN6Nlum1BjjOg5Eh2qx5oo7lvkjd7atJyMug+Jadz3mjiDtL4v8UW/akOOhP251WMeAiDBiYjzYZY8+Cr16+RohgoAnMQSZaIgBoiOOaIhB8Semrs5rCX7YlGPqjTvqjzvqjz0YY3Y7z3uBZ4CJQJGIZAI4z57dnl5zxR3b/KkzdumxyR/1xh0v/LHraFbapLa2NrwbLC/39XyYM8c3BkQQCHsMISAaYoDoiCMaYlD8qU1K8lqCHzblmHrjjvrjjvpjByKSJCIpjdPAucAWYBVwlbPYVcBz3ijUXGkL2/xJirVLj03+qDfueOFPlxoDIhpISEgI7wafew4qK+Eb3wjaKsMeQwiIhhggOuKIhhgUfxL27/dagh825Zh644764476Yw19gWfE1127G/BXY8xLIvIu8ISIXAN8DszxSqDmiju2+bO/1i49Nvmj3rjjhT9dogeEIfLGuWiNioqK8G7w0Ufh2GPhlFOCtsqwxxACoiEGiI44oiEGxZ+KzEyvJfhhU46pN+6oP+6oP3ZgjPnUGDPGeYwyxtzjzC8xxkwxxgwzxpxtjPHsn4rmiju2+ZMZb5cem/xRb9zxwp8u0QDRiAQwMIjt9OjRI3wbKyqCl1/29X4I4rV3YY0hRERDDBAdcURDDIo/PXbu9FqCHzblmHrjjvrjjvqjBIrmiju2+bOzaqfXEvywyR/1xh0v/OlSDRDRQGlpafg2tnIlNDQE9fILCHMMISIaYoDoiCMaYlD8KR0+3GsJftiUY+qNO+qPO+qPEiiaK+7Y5s/wJLv02OSPeuOOF/5oA0SEkZ6eHr6NPfYYjB0LI0cGdbVhjSFEREMMEB1xREMMij/p27d7LcEPm3JMvXFH/XFH/VECRXPFHdv82V5hlx6b/FFv3PHCH22AiDCK27pvbLD48EN491244oqgrzpsMYSQaIgBoiOOaIhB8ac4N9drCX7YlGPqjTvqjzvqjxIomivu2OZPbrJdemzyR71xxwt/tAEiwsjIyAjPhh57zDfuw6WXBn3VYYshhERDDBAdcURDDB1FRAaJyBoR2SYiW0Xke878NBF5RUQ+cp57OfNFRJaJyMcisklExjVb11XO8h+JyFWtbTMcZGze7OXmj8KmHFNv3FF/3FF/lEDRXHHHNn82l9ulxyZ/1Bt3vPCnSzRAGBM9d8EISwuwMb4GiLPOgv79g75621qxO0I0xADREUc0xNAJ6oAfGGNGAicB3xWRkcAiYLUxZhiw2nkNcD4wzHnMA/4AvgYL4A5gEjARuKOx0cILbDs7YFOOqTfuqD/uqD9KoGiuuGObP3qWv3XUG3e0B0SIESL/LhhhaQF+6y349NOQXH4B9rVid4RoiAGiI45oiKGjGGMKjTEbnOlDwHZgADANWOEstgK42JmeBjxifLwF9BSRTOA84BVjzH5jTCnwCjA1fJH4Y9vZAZtyTL1xR/1xR/1RAkVzxR3b/NGz/K2j3rijPSCUNtm/P8S3hP7vf2HxYkhMhOnTQ7KJkMcQBqIhBoiOOKIhhmAgIlnAWOBtoK8xptB560ugrzM9APii2cd2OfNam+8J+0eM8GrTLWJTjqk37qg/7qg/SqBorrhjmz8jutulxyZ/1Bt3vPBHGyAijNTU1NCs+JNP4Npr4fjjYc0auOMOCNE9l0MWQxiJhhggOuKIhhg6i4gkA08DNxljDjZ/z/iuQQvKdWgiMk9E1ovI+r1791JdXU1lZSUVFRXU1NRw8OBB6urqKC0txRjDvn37gK+6zu7btw8jQumwYdQlJHBw8GBqUlOp6NePyowMqnv14tDAgXT/8ksOHH88DbGxlGRn+9bhdFlsfN6/fz/19fWUlZVx+PBhysvLqaqqoqqqivLycg4fPkxZWRn19fVNP1wbdTQ+l5SU0NDQwIEDB6itreXQoUMtxpSUlOQekzGUlpZSV1fHwYMHqampoaKigsrKSqqrqzl06BC1tbUcOHCAhoYGSkpKWtSzf/9+6uPiKMvK4nByMuX9+1OVnk5Vejrl/ftzODkZqa+nPi6u6QfMkb6UZGcHFFOb+ynAmIwxbccUrP10/PHUdu/OoYEDqe7Vi8qMDCr69aMmNZWDgwdTl5BAQ0wMRoR9OTm+dTjP+3Jyvsq9YOynAGNqaGjoVO61az+1cjzVdu/edDzVH3NMy8fTiBFf5V6Ij6fmMdXW1obseFI6R+qnn3otwQ/bvutt8+fTKrv02OSPeuOOF/5IJI6PMGHCBLN+/fqAl39629PMenIWm76zidy+dl13017KysqCW4S3b4ef/Qz++leIi4PrroOFC2Hw4OBt4wiCHoMHREMMEB1x2BSDiLxnjJkQ5m3GAc8D/zTG/MqZ9yEw2RhT6FxisdYYM0JE/uRMP958ucaHMebbzny/5VqivXW4meA2FynLyiJ15073hcL43RXWHGvDH/XGHfXHna7ijxe12Cs6VIs1V9yxzB+5s209WQlZ7Kx212PuCNL+ssgf9aYNOR7641aHtQdEhJGYmBicFW3cCHPmwKhR8Pe/w/e/D599Br/9bUgbHyCIMXhINMQA0RFHNMTQUUREgD8D2xsbHxxWAY13srgKeK7Z/Cudu2GcBJQ5l2r8EzhXRHo5g0+e68zzhETnTK8t2JRj6o076o876o8SKJor7tjmz75au/TY5I96444X/nSJBggTnN7HVnD48OHOreCdd2DaNMjLg5degh/9CD7/HO67DzIzg6KxLTodgwVEQwwQHXFEQwyd4BTgm8BZIlLgPC4AlgDniMhHwNnOa4AXgU+Bj4EHgfkAxpj9wE+Bd53HXc48Tzgcosu/OopNOabeuKP+uKP+KIGiueKObf706GaXHpv8UW/c8cKfbmHfoodIAN1ibCc2NrZjH1y3Dn76U3j5ZejVC+66CxYs8E2HmQ7HYBEdiaG2tpZdu3ZRXV0dAkUdwxgT8ceFFzEkJCQwcOBA4uLiwrrdIzHGrINWb+8zpYXlDfDdVta1HFgePHUdJ7amxmsJfthUs9Qbd9Qfd9QfJVA0V9yxzZ+aBrv02OSPeuOOF/50qQaILocx8NprvoaHf/0L+vSBX/wCrr8eUlK8Vtfl2LVrFykpKWRlZVnzp7+hoYGYmMjuCBXuGIwxlJSUsGvXLoYMGRK27SqKoihKV+CLL77gyiuvpKioCBFh3rx5zJs3j8WLF/Pggw823ZLzZz/7GRdccIHHahVFaS/aABFh1NfXt72QMfDii3D33fDWW9C/Pyxd6htgsnv3kGtsi4BisJyOxFBdXW1V4wP4/kxHOuGOQURIT0/XkdZDSH18vNcS/LCpZqk37qg/7qg/SqB4mSvdunXj/vvvZ9y4cRw6dIjx48dzyimnAPD973+fW265xTNtjdh2LMXH2KXHJn/UG3e88EcbICKMY5xbaLVIQwM8+6yv4eH99+HYY+EPf4C5cyEhIVwS28Q1hgihozHY1PgA9unpCF7EEA2+2cwxBw+2vVAYsalmqTfuqD/uqD9KoHiZK5mZmWQ645KlpKSQnZ3N3r17PdPTErYdSwfr7NJjkz/qjTte+BPZfa+7IFVVVUfPrK+Hxx+H0aNh5kw4dAiWL4ePPoLvfMeqxgdoJYYII1JjiI2NJS8vj5ycHL7+9a833c89mEyePJkO3Z7R4dlnn2Xbtm0BL9/Q0ADAqlWrWLJkieuye/bsYdasWR3WpoSHqt69vZbgh03Hu3rjjvrjjvqjBIotubJz507ef/99cnNzAfjd737H6NGjufrqqyktLfVMly3+NNI7zi49Nvmj3rjjhT9dogEiGrqZN5KcnOy7xGL3bt9dLJYsgexsuPxy3/zHHoPt2+Fb3wKPB8hrjeTkZK8ldJpIjSExMZGCggK2bNlCWloaf/zjH72WdFQXXLcGiLq6uqPmNQ5MlZ+fz6JFi1y31b9/f5566qkOKlXCRfLu3V5L8MOm4129cUf9cUf9UQLFhlwpLy9n5syZLF26lP79+3P99dfzySefUFBQQGZmJj/4wQ8802aDP83ZXWOXHpv8UW/c8cKfLtEA0Yi0Oli8xZSXw9tvw4MPwo030nDGGdC7NwwcCOef77uNZkoKPPUUbN7sa4joZveVNWVlZV5L6DTREMPXvvY1du3aBcAnn3zC1KlTGT9+PKeddhoffPBB0/yTTjqJ3NxcbrvttqYfi2vXruWiiy5qWteCBQt4+OGHj9rG9ddfz4QJExg1ahR33HFH0/ysrCxuvfVWxo0bx5NPPtk0/4033mDVqlUsXLiQvLw8PvnkEyZPnsxNN93EhAkT+M1vfsP//d//MWnSJMaOHcvZZ5/Nnj17AHj44YdZsGABAHPnzuXGG2/k5JNP5rjjjmtqdNi5cyc5OTlNy8+YMYOpU6cybNgwfvjDHzbp+POf/8zw4cOZOHEi1113XdN6lfBQdtxxXkvww6bjXb1xR/1xR/1RAsXrXKmtrWXmzJl84xvfYMaMGZSVldG3b19iY2OJiYnhuuuu45133vFMn9f+HMlxiXbpsckf9cYdL/yx+59qV6K+Hj75xNeIsGmT77F5s29eI8nJxOXmwqxZvsstRo+GnBxPbqXZGdLS0ryW0Gk6HcNNN0FBQTCkfEVenm+w0QCor69n9erVXHPNNQDMmzePP/7xjwwbNoy3336b+fPn89prr/G9732P733ve1x22WUd6i1xzz33kJaWRn19PVOmTGHTpk2MHj0agPT0dDZs2OC3/Mknn0x+fj4XXXSR36UShw8fbrqso7S0lLfeegsR4aGHHuJXv/oV999//1HbLiwsZN26dXzwwQfk5+e3eOlFQUEB77//PvHx8YwYMYIbbriB2NhYfvrTn7JhwwZSUlI466yzGDNmTLtjVzpO2ocfei3BD5tqlnrjjvrjjvqjBIqXuWKM4ZprriE7O5ubb77ZpyctjcLCwqaxIZ555pmmEwpeYNux9GGlXXps8ke9cccLf7QBwguKi79qaGh83roVGq+FjImBYcNg3Di46qqvGhuOPZbikpKm2w9FKsXFxRqDR1RVVZGXl8fu3bvJzs5m8uTJlJeX88YbbzB79uym5WqcexS/+eabPPvsswBcfvnl7R55+oknnuCBBx6grq6OwsJCtm3b1tQAcckllwS8nubL7tq1i0suuYTCwkIOHz5MVlZWi5+5+OKLiYmJYeTIkRQVFbW4zJQpU0hNTQVg5MiRfP755+zbt48zzjij6Yfx7Nmz2bFjR8Balc5TnJtLxubNXstowqbjXb1xR/1xR/1RAsXLXHn99df5y1/+Qm5uLnl5eQDceuutvPjiixQUFCAiZGVl8ac//ckTfWDfsZSbnMvmcnv02OSPeuOOF/5oA0Qoqa72jcdwZGPDl19+tUyfPr7Ghe98x/ecmwsjR0JiYourjIYvao2BgHsqBJvGMSAqKys577zzeOCBB5g7dy49e/akoB09Mrp169Y0+CP4bjF6JJ999hn33Xcf7777Lr169WLu3Ll+yyUlJQW8vebL3nDDDdx8883k5+ezdu1aFi9e3OJn4pvd5qi1cWCaLxMbG9viGBNK+LHpixnsqlnqjTvqjzvqjxIoXubKqaee2uL39mWXXeaBmpax7Viy6Q822OWPeuOOF/5oA0QwMAY+//zohoYdO3yXVgDEx8OoUTB1qq+RobGxoW/fdm0qGs4WaAze0717d5YtW8bFF1/M/PnzGTJkCE8++SSzZ8/GGMOmTZsYM2YMJ510Ek8//TSXXHIJK1eubPr8sccey7Zt26ipqaGqqorVq1dz6qmn+m3j4MGDJCUlkZqaSlFREf/4xz+YPHlym9pSUlI4dOhQq++XlZUxYMAAAFasWBH0QWZPPPFEbrrpJkpLS0lJSeHpp59uGn1bCQ+2nR2w6XhXb9xRf9xRf5RACWeuyJ1tj9EWyFlac0f4Bp237VjSs/yto964oz0gQoQhiAWprMzXwNC8sWHzZmh+T9chQ3yNCzNnftXYMHRoUAaHjIYvao3BDsaOHcvo0aN5/PHHeeyxx7j++uu5++67qa2t5dJLL2XMmDEsXbqUK664gnvuuYepU6c2Xa4waNAg5syZQ05ODkOGDGHs2LFHrX/MmDGMHTuWE044gUGDBnHKKacEpOvSSy/luuuuY9myZS3esWLx4sXMnj2bXr16cdZZZ/HZZ591zogjGDBgAD/+8Y+ZOHEiaWlpnHDCCU1xK+HBpi9msOt4V2/cUX/cUX+UQLEtV2z6AwnqT1vY5I96444X/kgk3qJywoQJpnFAukB4YusTXPLUJWydv5WRGSPbt7HCQvjPf+Df//Y9tmzx9XgASE39qidD4zgNo0ZBjx7t20Y7KCkpIT09PWTrDwddNYbt27eTnZ0dIkUdo66ujm4uDWOVlZUkJiYiIqxcuZLHH3+c5557LowK26atGDpCeXk5ycnJ1NXVMX36dK6++mqmT5/ut0xL+1NE3jPGTAiqGEtpbx1uQto+01WSnU369u3uC4XxuyusNasNf9Qbd9Qfd7qKP1qL28CyXAmkB0R2UjbbK9z1BK0HhPrThiB7/FFv2pDjoT9udbhL9IAIGGPgs898DQ2NjQ4ff+x7LykJTj4ZZs/2DQ45erTvVpgBJFow6RVhd7xoCY3BHmJjY13ff++991iwYAHGGHr27Mny5cvDpCxw2oqhIyxevJhXX32V6upqzj33XC6++OKgb0NpnV6WDfpp0/Gu3rij/rij/iiBYluu7KiwS4/6445N/qg37njhjzZAALz5Jixb5mt02L3bNy8tDU491Tc45Omn+25xGBfnqUzwXVffs2dPr2V0Co3BHurr6117D5x22mls3LgxjIraT1sxdIT77rsvqOtT2sfBrCx6Nr8FscfYdLyrN+6oP+6oP0qg2JYrWYlZfFJljx71xx2b/FFv3PHCH22A+PRTOP98X+PC2WfDaaf5GhxGjvTdDtMy2nPnAFvRGOwhxsIcby/REIPiT1JhodcS/LDpeFdv3FF/3FF/lECxLVcKa+zSo/64Y5M/6o07XvjTtRsgqqt9l1SIwDvv+AaPtJzq6mriLOiJ0Rk0BnuIxDFgjiQaYlD8qU5LI66y0msZTdh0vKs37qg/7qg/SqDYlitpcWlU1tijR/1xxyZ/1Bt3vPCnSzRAtPoH5eabYcMGeO65iGh8AKLii1pjsAcJ8xgmoSAaYlD8iauo8FqCHzYd7+qNO+qPO+qPEii25UpFvV161B93bPJHvXHHC3+6VN9lodkflT//Gf7wB1i4EPLzvRPVThoaGryW0Gk0BnuIht4D0RCD4k9DkMf06Cw2He/qjTvqjzvqjxIotuVKN7FLj/rjjk3+qDfueOFPl2qAaOKFF+Db34bzzoN77vFaTbuIhj9bGoN3xMbGkpeX1/TYuXNnuz6/dOlSKlvpNub2nhu33347r776qusyq1atYsmSJe1etxKZmBDc2aQz2HS8qzfuqD/uqD9KoNiWK7Filx71xx2b/FFv3PHCH7uaYMLBO+/AnDm+u1o89ZQVd7ZoD8Ee7d8LNAbvSExMpKCgoOl1e88+LV26lCuuuILu3bu36736+vpWb5d51113tbnd/Px88lvpqaSXYEQf3aqqvJbgh03Hu3rjjvrjjvqjBIptuVLVYJce9ccdm/xRb9zxwp+u1QOipgamT4e+fX29IJKTvVbUbmpqaryW0Gk0Bns4dOgQU6ZMYdy4ceTm5vLcc88BUFFRwYUXXsiYMWPIycnhb3/7G8uWLWPPnj2ceeaZnHnmmX7raem95ORkfvCDHzBmzBjefPNN7rrrLk488URycnKYN29e05mvuXPn8tRTTwGQlZXFHXfc0aTngw8+AODhhx9mwYIFTcvfeOONnHzyyRx33HFNn21oaGD+/PmccMIJnHPOOVxwwQVN7ymRRU1qqtcS/LDpeFdv3FF/3FF/lECxLVdSu9mlR/1xxyZ/1Bt3vPCnazU9x8fDI4/AoEG+RogIpKWzy5GGxgA3vXQTBV8WBEeMQ16/PJZOXeq6TFVVFXl5eQAMGTKEJ554gmeeeYYePXqwb98+TjrpJPLz83nppZfo378/L7zwAgBlZWWkpqbyq1/9ijVr1tC7d2+/9d54441HvVdRUcGkSZO4//77ARg5ciS33347AN/85jd5/vnn+frXv36Uxt69e7NhwwZ+//vfc9999/HQQw8dtUxhYSHr1q3jgw8+ID8/nzlz5vD3v/+dnTt3sm3bNvbu3Ut2djZXX311uzxU7KD73r1eS/DDppql3rij/rij/iiBYluu7D1slx71xx2b/FFv3PHCny7RAyI1IZVRvUcR3y0epkyB4cO9ltRhDh065LWETqMxeEfjJRgFBQU888wz1NXV8eMf/5jRo0dz9tlns3v3boqKisjNzeWVV17h1ltv5T//+Q+pHWitjY2NZebMmU2v16xZw6RJk8jNzeW1115j69atLX5uxowZAIwfP77VMSouvvhiYmJiGDlyJEVFRQCsW7eO2bNnExMTQ79+/Y7qpaFEDocGDfJagh82He/qjTvqjzvqjxIotuXKoAS79Kg/7tjkj3rjjhf+dIkeEFOHTuW848+LimvFe/bs6bWETqMx0GZPhXCxcuVKiouLee+994iLiyMrK4vq6mqGDx/Ohg0bePHFF7ntttuYMmVKU++FQElISGga96G6upr58+ezfv16Bg0axOLFi6murm7xc/Hx8YCvAaOurs51GdBBzKKRnh9/7LUEP2yqWeqNO+qPO+qPEii25crHlXbpUX/csckf9cYdL/zpEj0gAEpKSryWEBSiIQ6NwR5KS0vp06cPcXFxrFmzhs8//xyAPXv20L17d6644goWLlzIhg0bAEhJSWn1jJXbe42NDb1796a8vDwkYzOccsopPP300zQ0NFBUVMTatWuDvg0lPJSMGuW1BD9sOt7VG3fUH3fUHyVQbMuVUcl26VF/3LHJH/XGHS/86TINEEdesx6pREMcGoM9XHnllaxfv57c3FweeeQRTjjhBAA2b97MxIkTycvL48477+S2224DYN68eUydOrXFyxvc3uvZsyfXXXcdOTk5nHfeeZx44olBj2XmzJkMHDiQkSNHcsUVVzBu3LgOXTqieE/vLVu8luCHTce7euOO+uNOOP25+uqr6dOnDzk5OU3z9u/fzznnnMOwYcM455xz/O6OtHbtWvLy8hg1ahRnnHFG2HQqLWPbsbSl3C496o87Nvmj3rjjhT8Sid2XJ0yYYNavX9+uzxQXF5ORkREiReEjGuLoqjFs376d7OzsECnqGLW1tcRF2K1oj6R5DOXl5SQnJ1NSUsLEiRN5/fXX6devX0i229L+FJH3jDETQrJBy+hIHQYggEvhinNyyGjrCzqE31319fVMmDCBAQMG8Pzzzzcd7zfeeCPLly+nvLw8ZNtuyx+vvfn1r3/NQw89hIiQm5vLvffey44dO1i4cCENDQ0kJyfz8MMPM3To0OBv3PLcOdKb//f//h8vvPAC99xzT+i9Aev8+fe//01ycjJXXnklW5xt/vCHPyQtLY1FixaxZMkSdu/ezW9/+1sOHDjAySefzEsvvcTgwYPZu3cvffr06fC2tRa3gWW5Ine2rScnOafNP0rmjiAd2+pPG4Ls8Ue9aUOOh/641eEu0wMi0v/wNhINcWgM9hDpjQ/gH8NFF11EXl4ep512Gv/zP/8TssYHJbS0+cUcYn7zm9/4NS5lZGSwfv16SktLPVTlaPHQm927d7Ns2TLWr1/Pli1bqK+vZ/Xq1Vx//fU89thjFBQUcPnll3P33Xd7ptErf1ryZuXKlfzoRz+yxhsIrz+nn346aWlpfvOee+45rrrqKgCuuuoqXn75ZQD++te/MmPGDAYPHgzQqcYHJTh4XYePxLaz2OqPOzb5o96444U/XaYBYt++fV5LCArREIfGYA+1tbVeS+g0zWNYu3YtBQUFbNu2jblz53onSukU+5p12Q43u3bt4oUXXuDaa69tmldUVMTChQu59957PdPViJfeANTV1VFVVUVdXR2VlZUkJSUhIhw8eBDw3bK3f//+nunz0p8jvenfvz8NDQ3WeAPe509RURGZmZkA9OvXjy+//BKAHTt2UFpayuTJkxk/fjyPPPKIlzIVvM+VI8lJtkuP+uOOTf6oN+544U+XuAsGQHp6utcSgkI0xKEx2EO3bpFfAqIhBsWf9FZu0RoObrrpJu69916/AVUff/xx8vPzm/44eYmX3gwYMIBbbrmFwYMHk5iYyLnnnsusWbPo168fF1xwAYmJifTo0YO33nrLM41e+dOSN+eeey7Lly+3xhvwNn+ORESIifGdB6urq+O9995j9erVVFVV8bWvfY2TTjqJ4RF82/RIx6ZcAdhabpce9ccdm/xRb9zxwp8u0wPiwIEDXksICtEQR1eOwbYxV+rr672W0Gm8iMG2/RhtHAjVNfJt8Pzzz9OnTx/Gjx/fNG/Pnj2sXLmSG264wRNNR+KVN+C7a85zzz3HZ599xp49e6ioqOCBBx7g17/+NS+++CK7du3iW9/6FjfffLNnGr3ypyVvHn30UX75y19a4w14mz8Affv2pbCwEIDCwsKmQToHDhzIeeedR1JSEr179+b0009n48aNXkrt8nidK0cytLtdetQfd2zyR71xxwt/ukwDREpKitcSgkI0xNFVY0hISKCkpMSqP6/NRyCPVMIdgzGGkpISEhISwrrdrkTKF194st3XX3+dVatWkZWVxaWXXsprr73GqFGj2LlzJ0OHDiUrK4vKysrQDSIYAF55A/Dqq68yZMgQMjIyiIuLY8aMGWzYsIGNGzcyadIkAC655BLeeOMNzzR65U9L3rz++uts27bNGm/A2/wByM/PZ8WKFQCsWLGCadOmATBt2jTWrVvXdPnK22+/bd2gzV0Nr3PlSL6otkuP+uOOTf6oN+544U+X6btcWVlJjx49vJbRaaIhjq4aw8CBA9m1axfFxcUhUtV+GhoamrrARipexJCQkMDAgQPDus2uRGWfPvT473/Dvt2f//zn/PznPwd844ncd999PP/88xw8eLDpeE9OTubjjz8Ou7ZGvPIGYPDgwbz11ltUVlaSmJjI6tWrycnJ4emnn2bHjh0MHz6cV155xdM/jl7505I3EyZM4IknnrDGGwivP5dddhlr165l3759DBw4kDvvvJNFixYxZ84c/vznP3Psscfy0EMPAZCdnc3UqVMZPXo0MTExXHvttX6371TCj5e1piX6HNOH/1bbo0f9cccmf9Qbd7zwp8s0QMTHx3stIShEQxxdNYa4uDiGDBkSAjUdp6amJuL3RzTEYAsiMhX4DRALPGSMWeKFjviyMi822yo25ZeX3kyaNIlZs2Yxbtw4unXrxtixY/n2t7/N0KFDmTlzJjExMfTq1Yvly5d7ptErf1ryZt68efTt29cabyC8/jz++OMtzl+9enXTdE1NTdP0woULWbhwYch12Y7W4ZYpq7NLj/rjjk3+qDfueOFPl2mAqKurs+pHZEeJhjg0BnuIhjiiIQYbEJFY4H+Bc4BdwLsissoYsy3cWuoSEz3/gp48eTKTJ0/26WmWY+Xl5R6q8t6bO++8kzvvvLPpdUVFBdOnT2f69OmeaWqOl/4c6Q3AhRdeyJw5czzR0xJe58+RaP32R+tw6yTGJFKGPXrUH3ds8ke9cccLf7pMA4SIeC0hKERDHBqDPURDHNEQgyVMBD42xnwKICIrgWlA2H/4imWDo9qUY+H0Ru5sO+6MuAyKa90vKzN3hG/cG/XHnUjzJ5zeWILW4VaoN3bpUX/csckf9cYdL/zpMg0QkX6deyPREIfGYA/REEc0xGAJA4DmIxHtAiZ5ISSmri5s2wrkT1Kvbr0orSt1XSZcf5TC6U0g1Bm79Kg/7qg/1tMl63Ag2JYr6o87Nvmj3rjjhT9i04j8gSIixcDn7fxYb2BfCOSEm2iIQ2Owh2iIw6YYjjXGZHgtoiOIyCxgqjHmWuf1N4FJxpgFzZaZB8xzXo4APgyRHJv2KdilxyYtoHraQvW4Eyo9EVmLA6nDzvxw1OKukisdRfW4Y5Mem7RA19HTah2OyB4QHflSEZH1xpgJodATTqIhDo3BHqIhjmiIwRJ2A4OavR7ozGvCGPMA8ECohdi2T23SY5MWUD1toXrcsU2PBbRZhyE8tdi2faN63FE9rWOTFlA9ANp3WVEURQF4FxgmIkNE5BjgUmCVx5oURVG6ElqHFUWJeiKyB4SiKIoSXIwxdSKyAPgnvtu/LTfGbPVYlqIoSpdB67CiKF2BrtQAEfJuw2EiGuLQGOwhGuKIhhiswBjzIvCi1zqwb5/apMcmLaB62kL1uGObHs/ROtwqqscd1dM6NmkB1ROZg1AqiqIoiqIoiqIoihJZ6BgQiqIoiqIoiqIoiqKEnC7RACEiU0XkQxH5WEQWea3nSERkp4hsFpECEVnvzEsTkVdE5CPnuZczX0RkmRPLJhEZ12w9VznLfyQiV4VY83IR2SsiW5rNC5pmERnvePKx81kJYxyLRWS3sz8KROSCZu/9yNH0oYic12x+iznmDCT1tjP/b86gUsGOYZCIrBGRbSKyVUS+58yPmP3hEkNE7QvFnbZqsYgMdvLgfSc329zfodARTi3t0SUix4rIakfPWhEZ2Oy9oNX/AP0Ji5b26GpNk4jkicibTm3ZJCKXhEpDuHS0V5fb/nLe7yEiu0Tkd6HUEU4tSutoLe6crnDUP63DndMRTi3t0RWO+hcRddgYE9UPfIP4fAIcBxwDbARGeq3rCI07gd5HzLsXWORMLwJ+4UxfAPwDEOAk4G1nfhrwqfPcy5nuFULNpwPjgC2h0Ay84ywrzmfPD2Mci4FbWlh2pJM/8cAQJ69i3XIMeAK41Jn+I3B9CGLIBMY50ynADkdrxOwPlxgial/ow3Uft1mL8V2HeH2zfbzTbX+HSke4tHTAnyeBq5zps4C/ONNBq//t8CfkWoLoz3BgmDPdHygEenrgTVB0BNObZu//Bvgr8LtQ6giXFn10Ol+0FntYi4NQa6K2DgfJn6itxZ31Jlg62np0hR4QE4GPjTGfGmMOAyuBaR5rCoRpwApnegVwcbP5jxgfbwE9RSQTOA94xRiz3xhTCrwCTA2VOGPMv4H9odDsvNfDGPOW8R0FjzRbVzjiaI1pwEpjTI0x5jPgY3z51WKOiYjgO6ifcj7f3JOgYYwpNMZscKYPAduBAUTQ/nCJoTWs3BeKK4HUYgP0cKZTgT3OdGv7O1Q6wqWlvbpGAq8502uavR/M+h+oP+HQ0l5dLWoyxuwwxnzkTO8B9gIZIdIQDh0d0dXa/kJExgN9gZfDoCNcWpTW0VrceV2hrn9ahzuvI1xa2qsr1PUvIupwV2iAGAB80ez1Ltz/2HiBAV4WkfdEZJ4zr68xptCZ/hJfIkDr8dgQZ7A0D3Cmj5wfThY43ZKWi3PpAu2PIx04YIypO2J+yBCRLGAs8DYRuj+OiAEidF8oRxFIjVoMXCEiu/CNAn9DOz4bTB3h0tJeXRuBGc70dCBFRNKDrCnQdYVDS3t1taapCRGZiO+s0Cch0hAOHR3R1aImEYkB7gduCZOOcGlRWkdrced1hbr+aR3uvI5waWmvrlDXv4iow12hASISONUYMw44H/iuiJze/E3nrLPxRFkHiUTNzfgDcDyQh69b1v2eqgkQEUkGngZuMsYcbP5epOyPFmKIyH2hdJjLgIeNMQPxXSr0F+fLsKtraeQW4AwReR84A9gN1KuWJlw1Ob25/gJ8yxjT0AV0BKJpPvCiMWaX24ejWIvSMjbVP5u0NGJL/bNFR3Nsqn82aWlLU7jrn6c6uoVy5ZawGxjU7PVAZ541GGN2O897ReQZfN1nikQk0xhT6Bwge53FW4tnNzD5iPlrQyz9SIKlebczfeTyYcEYU9Q4LSIPAs87L91yqaX5Jfgub+jmnHkPWRwiEofvj/tjxpi/O7Mjan+0FEMk7gulVQKpxdfgdBM1xrwpIglA7wA/G0wd4dLSLl1OV9EZ0NRYN9MYc0BEgln/A4ovTFrapas1Tc7rHsALwE+cS89CoiFMOtqty2V/fQ04TUTmA8nAMSJSbozpyIDdnc2dYGpRWkdrcSd1haH+aR3upI4wammXrjDUv8iowyYEA0vY9MDXyPIpvgFqGgfjGOW1rmb6koCUZtNv4Cu0v8R/AMF7nekL8R9A8B1nfhrwGb7BZno502kh1p6F/+CNQdPM0YMeXhDGODKbTX8f3zWGAKPwH/DoU3yDvbSaY/gGeWk+8OH8EOgXfOMyLD1ifsTsD5cYImpf6MN1H7dZi53cmutMZ+O71lda29+h0hEuLR3wpzcQ40zfA9zlTAet/rfDn5BrCaI/xwCr8fWsCqmGcOgIpjdHLDOXzg1C2Sl/gqlFH53OF63FHtbiINSaqK3DQfInamtxZ70Jlo42dYZipbY98HXZ2oHv+p6feK3nCG3HOcmxEdjaqA/fNeurgY+AV/nqj6AA/+vEshmY0GxdV+MbhOdjfN2JQqn7cXxd4mvxXV90TTA1AxOALc5nfgdIGOP4i6NzE7AK/z/BP3E0fUizO0G0lmPO/n3Hie9JID4EMZyK7/KKTUCB87ggkvaHSwwRtS/00eZ+PmrfAHcB+c70SOB1fPWwADi3rf0dLB1eaWmnP7Oc43kH8FDzHG7t2A2hP2HREgx/gCvw1fiCZo+8cHsTTB3BzJ1m65hLJ39sdjZ3gqlFH53KF63FHtfizh5LwdIRLG8Icv3rjD/B1hKs3Gm2jrl0rjHY+joszgYURVEURVEURVEURVFChteDuCiKoiiKoiiKoiiK0gXQBghFURRFURRFURRFUUKONkAoiqIoiqIoiqIoihJytAFCURRFURRFURRFUZSQow0QiqIoiqIoiqIoiqKEHG2AUBRFURRFURRFURQl5GgDhKIoiqJ0AUQkS0S2BGE9k0Xk5GBoCgci8rCIzHKmHxKRkV5rUhSla6J1WOuwAt28FqAooUBEkoAngIFALPBT4GPgV0AysA+Ya4wpFJGhwB+BDKAemA1UAn8DeuA7Tq43xvwn3HEoiqJYyGSgHHjDYx3txhhzrdcaFEVRgsBktA4rEYr2gFCilanAHmPMGGNMDvAS8FtgljFmPLAcuMdZ9jHgf40xY4CTgULgcuCfxpg8YAxQEF75iqIoIaGbiDwmIttF5CkR6Q4gIuNF5F8i8p6I/FNEMp35N4rINhHZJCIrRSQL+A7wfREpEJHTmq9cRBaLyAoR+Y+IfC4iM0TkXhHZLCIviUhcG9u7TkTeFZGNIvJ0M30Pi8gyEXlDRD5tPJPWEuLjdyLyoYi8CvRp9t5aEZngTE8VkQ3OtlY785JEZLmIvCMi74vItOBZryiKAmgd1jrcxdEGCCVa2QycIyK/cArzICAHeEVECoDbgIEikgIMMMY8A2CMqTbGVALvAt8SkcVArjHmkBdBKIqiBJkRwO+NMdnAQWC+82O0tQbaRcBYY8xo4DvGmJ34eoz92hiT10rPsOOBs4B84FFgjTEmF6gCLmxje383xpzoNAhvB65ptt5M4FTgImCJS4zTnThHAlfia1j2Q0QygAeBmc62Zjtv/QR4zRgzETgT+KX4etQpiqIEC63DaB3uyuglGEpUYozZISLjgAuAu4HXgK3GmK81X85pgGjp8/8WkdOBC4GHReRXxphHQq1bURQlxHxhjHndmX4UuBFfD7HGBlrwXbZW6CyzCXhMRJ4Fng1wG/8wxtSKyGZnXS858zcDWfh+lLa2vRwRuRvoie9yuX82W++zxpgGYJuI9HXZ/unA48aYemCPiLzWwjInAf82xnwGYIzZ78w/F8gXkVuc1wnAYHw/whVFUYKB1mEfWoe7KNoAoUQlItIf2G+MeVREDgDzgQwR+Zox5k2n5Xe4MWariOwSkYuNMc+KSDy+IpwB7DLGPOjMGwdoA4SiKJGOaeG10EIDrcOF+H5Ifh34iYjkBrCNGgBjTIOI1BpjGrfZgO93h9v2HgYuNsZsFJG5+K5z9luvgwSgoyMIvrNxH4Zo/YqiKFqH3dE6HOXoJRhKtJILvONcbnEHcDswC/iFiGzEN6ZDY3ewbwI3isgmfIP59MNXbDeKyPvAJcBvwileURQlRAwWkcYfnJcD64APcRpoAUQkTkRGiUgMMMgYswa4FUjFdzbsENBi77EAaXF7znspQKHTSPyNDq7/38AlIhLrXNN8ZgvLvAWcLiJDHA1pzvx/AjeIc0pQRMZ2UIOiKEpraB32oXW4i6I9IJSoxBjzT/y7jDVyegvLfoTvOrnmfAqsCIE0RVEUL/kQ+K6ILAe2AX8wxhx2BhNbJiKp+H4bLAV2AI868wRYZow5ICL/BzzlDAx2Q3vvEOSyva3A/wBvA8XOc0d+YD+Dr6ZvA/4LvNmChmIRmQf83fmBvxc4B98dk5YCm5z5n+G71llRFCVYaB1G63BXRr7qkaMoiqIoiqIoiqIoihIa9BIMRVEURVEURVEURVFCjl6CoSiKoihKxOEMxPaXI2bXGGMmeaFHURSlq6F1WOkIegmGoiiKoiiKoiiKoighRy/BUBRFURRFURRFURQl5GgDhKIoiqIoiqIoiqIoIUcbIBRFURRFURRFURRFCTnaAKEoiqIoiqIoiqIoSsjRBghFURRFURRFURRFUULO/wdy8uN7dgMKAQAAAABJRU5ErkJggg==\n", 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" ] @@ -1032,7 +1036,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "[1](#fn1-back) Acknowledgement: This usage is inspired by [Conditional with statement in Python](https://stackoverflow.com/a/68682614) by [Lucas Vasquez](https://stackoverflow.com/users/10712525/lucas-vazquez), used with adaptations under [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/), accessed June 14, 2022." + "[1](#fn1-back) Acknowledgement: This usage is inspired by [Conditional with statement in Python](https://stackoverflow.com/a/68682614) by [Lucas Vasquez](https://stackoverflow.com/users/10712525/lucas-vazquez), used with adaptations under [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/), accessed June 14, 2022." ] } ],

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XvYJOh-RC*>VLXshxR-y&;MxBI#hEjA literal 0 HcmV?d00001 diff --git a/acceleration/fast_training_tutorial.ipynb b/acceleration/fast_training_tutorial.ipynb index b3c0191254..e99db05566 100644 --- a/acceleration/fast_training_tutorial.ipynb +++ b/acceleration/fast_training_tutorial.ipynb @@ -41,7 +41,7 @@ "To support profiling, the following lines have been commented out. \n", "\n", "- To verify that you have key packages installed, uncomment the middle section (3 lines).\n", - "- If you are not interested in profiling, uncomment the last line." + "- If you are not interested in profiling (i.e., you will run this as a Jupyter notebook), uncomment the last line." ] }, { @@ -187,21 +187,13 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": null, "metadata": { "vscode": { "languageId": "python" } }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "root dir is: /tmp/tmp6rnyagom\n" - ] - } - ], + "outputs": [], "source": [ "directory = os.environ.get(\"MONAI_DATA_DIRECTORY\")\n", "root_dir = tempfile.mkdtemp() if directory is None else directory\n", @@ -215,8 +207,8 @@ "By default, outputs will go to `outputs/`. \n", "\n", "You can run this tutorial twice, once with profiling and once without, and the outputs will not conflict with each other. \n", - "- When profiling, the output is `outputs/output_base.nsys-rep`, which you can then visualize using the GUI of Nsight systems (more details below).\n", - "- When not profiling, the outputs are `outputs/loss_dice_comparison.png`, `outputs/metric_time_epochs`, and `outputs/total_epoch_time_comparison.png`.\n", + "- When profiling, the output is `outputs/output_base.nsys-rep`, which you can then visualize using the GUI of Nsight systems (a brief guide is provided in the \"Profiling visualization\" section below).\n", + "- When not profiling, the outputs are `outputs/loss_dice_comparison.png`, `outputs/metric_time_epochs.png`, and `outputs/total_epoch_time_comparison.png`.\n", "\n", "We set up the tutorial such that figures are only generated when not profiling, but that does not have to be the case. In general, the figures make more sense when training is run for a higher number of epochs (e.g., hundreds), which is usually not the case when profiling." ] @@ -236,7 +228,7 @@ "out_dir = \"outputs/\"\n", "\n", "if not os.path.exists(out_dir):\n", - " os.makedirs(out_dir, exist_ok=True)" + " os.makedirs(out_dir)" ] }, { @@ -265,14 +257,14 @@ " \n", " 2) Set `profiling = True`;\n", " \n", - " 3) Make sure all lines in \"Setup environment\" (first code cell in this tutorial above) are commented out;\n", + " 3) Make sure all lines in \"Setup environment\" (first code cell in this tutorial, above) are commented out;\n", " \n", " 4) Save this notebook;\n", " \n", " 5) Open the terminal and ensure that you are in the directory of this notebook, then run this command:\n", " `jupyter nbconvert fast_training_tutorial.ipynb --to python && nsys profile --output ./outputs/output_base --force-overwrite true --trace-fork-before-exec true python3 fast_training_tutorial.py ; rm fast_training_tutorial.py`\n", " \n", - " This command converts the notebook to a Python script locally and runs nsys. The output file is outputs/output_base.nsys-rep, but you can modify --output to specify the desired location." + " This command converts the notebook to a Python script locally and runs `nsys`. The output file is `outputs/output_base.nsys-rep`, but you can modify `--output` to specify the desired location." ] }, { @@ -293,20 +285,13 @@ "max_epochs = 6 if profiling else 600\n", "\n", "# to improve readability\n", - "range_func_named = lambda x, y: Range(x)(y) if profiling else y\n", - "range_func = lambda y: Range()(y) if profiling else y\n", - "no_profiling = contextlib.nullcontext()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Here we give a brief overview of key observations from the `nsys-rep` output file when opened in Nsight systems (2022.2.1).\n", "\n", - "In the GUI, select File -> Open -> output_base.nsys-rep. Here is a sample of the display:\n", "\n", - "![png](Figures/nsys-all.PNG)" + "def range_func_named(x, y): return Range(x)(y) if profiling else y\n", + "def range_func(y): return Range()(y) if profiling else y\n", + "\n", + "\n", + "no_profiling = contextlib.nullcontext()" ] }, { @@ -320,43 +305,13 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": null, "metadata": { "vscode": { "languageId": "python" } }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Task09_Spleen.tar: 1.50GB [00:41, 39.1MB/s] " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2022-06-21 21:48:22,519 - INFO - Downloaded: /tmp/tmp6rnyagom/Task09_Spleen.tar\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2022-06-21 21:48:25,920 - INFO - Verified 'Task09_Spleen.tar', md5: 410d4a301da4e5b2f6f86ec3ddba524e.\n", - "2022-06-21 21:48:25,921 - INFO - Writing into directory: /tmp/tmp6rnyagom.\n" - ] - } - ], + "outputs": [], "source": [ "resource = \"https://msd-for-monai.s3-us-west-2.amazonaws.com/Task09_Spleen.tar\"\n", "md5 = \"410d4a301da4e5b2f6f86ec3ddba524e\"\n", @@ -416,10 +371,10 @@ " range_func(AddChanneld(keys=[\"image\", \"label\"])),\n", " range_func(Orientationd(keys=[\"image\", \"label\"], axcodes=\"RAS\")),\n", " range_func_named(\"Spacing\", Spacingd(\n", - " keys=[\"image\", \"label\"],\n", - " pixdim=(1.5, 1.5, 2.0),\n", - " mode=(\"bilinear\", \"nearest\"),\n", - " )),\n", + " keys=[\"image\", \"label\"],\n", + " pixdim=(1.5, 1.5, 2.0),\n", + " mode=(\"bilinear\", \"nearest\"),\n", + " )),\n", " range_func(\n", " ScaleIntensityRanged(\n", " keys=[\"image\"],\n", @@ -433,11 +388,11 @@ " # pre-compute foreground and background indexes\n", " # and cache them to accelerate training\n", " range_func_named(\"Indexing\", FgBgToIndicesd(\n", - " keys=\"label\",\n", - " fg_postfix=\"_fg\",\n", - " bg_postfix=\"_bg\",\n", - " image_key=\"image\",\n", - " )),\n", + " keys=\"label\",\n", + " fg_postfix=\"_fg\",\n", + " bg_postfix=\"_bg\",\n", + " image_key=\"image\",\n", + " )),\n", " # change to execute transforms with Tensor data\n", " EnsureTyped(keys=[\"image\", \"label\"]),\n", " ]\n", @@ -454,15 +409,15 @@ " # the image centers of negative samples\n", " # must be in valid image area\n", " range_func_named(\"RandCrop\", RandCropByPosNegLabeld(\n", - " keys=[\"image\", \"label\"],\n", - " label_key=\"label\",\n", - " spatial_size=(96, 96, 96),\n", - " pos=1,\n", - " neg=1,\n", - " num_samples=4,\n", - " fg_indices_key=\"label_fg\",\n", - " bg_indices_key=\"label_bg\",\n", - " )),\n", + " keys=[\"image\", \"label\"],\n", + " label_key=\"label\",\n", + " spatial_size=(96, 96, 96),\n", + " pos=1,\n", + " neg=1,\n", + " num_samples=4,\n", + " fg_indices_key=\"label_fg\",\n", + " bg_indices_key=\"label_bg\",\n", + " )),\n", " )\n", "\n", " val_transforms = [\n", @@ -834,6 +789,42 @@ ")" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Profiling visualization" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here we give a brief overview of key observations from the `nsys-rep` output file when opened in Nsight systems (2022.2.1).\n", + "\n", + "In the GUI, select File -> Open -> output_base.nsys-rep. Here is a sample of the display:\n", + "\n", + "![png](Figures/nsys-all-annotated.png)\n", + "- To get a better view of details, you can left-click and select a horizontal section, then right-click and \"Zoom into Selection.\" To return, right-click and select \"Reset Zoom.\"\n", + "- Sections B and C show training before and after acceleration (when fast=False and fast=True, accordingly). Clearly, MONAI optimized training is much faster than regular PyTorch training. B and C both contain two rows; the upper row shows per-epoch time, and the lower row shows per-action time (user-defined, like dataloading, forward, backward, etc.).\n", + "- Section A shows GPU utilization, where the height of the blue bars represents utilization rate. Regular PyTorch training shows sporadic and varying levels of GPU utilization, while MONAI optimized training shows consistent and high levels of GPU utilization.\n", + "\n", + "Expanding one more thread in the lower left corner and several more threads below \\[4648\\], we see the following:\n", + "\n", + "![png](Figures/nsys-transforms-annotated.png)\n", + "\n", + "Sections D and E both include information on the transform chain.\n", + "- Section E: In MONAI optimized training, results of all transforms in the chain until the first randomized transform is stored to prevent repeated operations. This explains why E is chronologically before any of the training epochs in the figure.\n", + "- Section D: In regular PyTorch training, CacheDataset is not in use, and the transform chain is performed every epoch on all data used.\n", + "\n", + "Here is the display of the transform chain when zoomed in:\n", + "![png](Figures/nsys-fast-transform.png)\n", + "\n", + "And a display of one training epoch of MONAI optimized training when zoomed in:\n", + "![png](Figures/nsys-epoch-short.png)\n", + "Notice that the per-epoch time is >20 times faster than the regular PyTorch training." + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -1008,6 +999,7 @@ " else:\n", " return None\n", "\n", + "\n", "if not profiling:\n", " plt.figure(\"train\", (18, 6))\n", " plt.subplot(1, 3, 1)\n", From 22d3e29471b22e723d3d63d15b046929238fd9f0 Mon Sep 17 00:00:00 2001 From: Yuchen Xu Date: Thu, 23 Jun 2022 09:09:12 -0700 Subject: [PATCH 06/12] addressed Nic's comments --- acceleration/fast_training_tutorial.ipynb | 97 ++++++++++++++--------- 1 file changed, 58 insertions(+), 39 deletions(-) diff --git a/acceleration/fast_training_tutorial.ipynb b/acceleration/fast_training_tutorial.ipynb index e99db05566..4664b1162b 100644 --- a/acceleration/fast_training_tutorial.ipynb +++ b/acceleration/fast_training_tutorial.ipynb @@ -46,7 +46,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 2, "metadata": { "vscode": { "languageId": "python" @@ -72,13 +72,21 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 3, "metadata": { "vscode": { "languageId": "python" } }, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/conda/lib/python3.8/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", + " from .autonotebook import tqdm as notebook_tqdm\n" + ] + }, { "name": "stdout", "output_type": "stream", @@ -187,13 +195,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": { "vscode": { "languageId": "python" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "root dir is: /tmp/tmp87h4yebg\n" + ] + } + ], "source": [ "directory = os.environ.get(\"MONAI_DATA_DIRECTORY\")\n", "root_dir = tempfile.mkdtemp() if directory is None else directory\n", @@ -215,7 +231,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 5, "metadata": { "vscode": { "languageId": "python" @@ -269,7 +285,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 6, "metadata": { "vscode": { "languageId": "python" @@ -277,7 +293,7 @@ }, "outputs": [], "source": [ - "profiling = False\n", + "profiling = True\n", "\n", "# if profiling = True, it is recommended to set max_epochs = 6 for faster prototyping\n", "# to see the trend in training curve and dice results, set max_epochs to be larger (600)\n", @@ -287,8 +303,7 @@ "# to improve readability\n", "\n", "\n", - "def range_func_named(x, y): return Range(x)(y) if profiling else y\n", - "def range_func(y): return Range()(y) if profiling else y\n", + "def range_func(x, y): return Range(x)(y) if profiling else y\n", "\n", "\n", "no_profiling = contextlib.nullcontext()" @@ -331,7 +346,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 9, "metadata": { "vscode": { "languageId": "python" @@ -361,54 +376,52 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ - "def transformations(fast=False):\n", + "def transformations(fast=False, device='cuda:0'):\n", " train_transforms = [\n", - " range_func_named(\"LoadImage\", LoadImaged(keys=[\"image\", \"label\"])),\n", - " range_func(AddChanneld(keys=[\"image\", \"label\"])),\n", - " range_func(Orientationd(keys=[\"image\", \"label\"], axcodes=\"RAS\")),\n", - " range_func_named(\"Spacing\", Spacingd(\n", + " range_func(\"LoadImage\", LoadImaged(keys=[\"image\", \"label\"])),\n", + " range_func(\"AddChannel\", AddChanneld(keys=[\"image\", \"label\"])),\n", + " range_func(\"Orientation\", Orientationd(keys=[\"image\", \"label\"], axcodes=\"RAS\")),\n", + " range_func(\"Spacing\", Spacingd(\n", " keys=[\"image\", \"label\"],\n", " pixdim=(1.5, 1.5, 2.0),\n", " mode=(\"bilinear\", \"nearest\"),\n", " )),\n", - " range_func(\n", - " ScaleIntensityRanged(\n", - " keys=[\"image\"],\n", - " a_min=-57,\n", - " a_max=164,\n", - " b_min=0.0,\n", - " b_max=1.0,\n", - " clip=True,\n", - " )),\n", - " range_func(CropForegroundd(keys=[\"image\", \"label\"], source_key=\"image\")),\n", + " range_func(\"ScaleIntensityRange\",\n", + " ScaleIntensityRanged(\n", + " keys=[\"image\"],\n", + " a_min=-57,\n", + " a_max=164,\n", + " b_min=0.0,\n", + " b_max=1.0,\n", + " clip=True,\n", + " )),\n", + " range_func(\"CropForeground\", CropForegroundd(keys=[\"image\", \"label\"], source_key=\"image\")),\n", " # pre-compute foreground and background indexes\n", " # and cache them to accelerate training\n", - " range_func_named(\"Indexing\", FgBgToIndicesd(\n", + " range_func(\"Indexing\", FgBgToIndicesd(\n", " keys=\"label\",\n", " fg_postfix=\"_fg\",\n", " bg_postfix=\"_bg\",\n", " image_key=\"image\",\n", " )),\n", " # change to execute transforms with Tensor data\n", - " EnsureTyped(keys=[\"image\", \"label\"]),\n", + " range_func(\"EnsureType\", EnsureTyped(keys=[\"image\", \"label\"])),\n", " ]\n", "\n", " if fast:\n", " # move the data to GPU and cache to avoid CPU -> GPU sync in every epoch\n", - " train_transforms.append(\n", - " ToDeviced(keys=[\"image\", \"label\"], device=\"cuda:0\")\n", - " )\n", + " train_transforms.append(range_func(\"ToDevice\", ToDeviced(keys=[\"image\", \"label\"], device=device)))\n", "\n", " train_transforms.append(\n", " # randomly crop out patch samples from big\n", " # image based on pos / neg ratio\n", " # the image centers of negative samples\n", " # must be in valid image area\n", - " range_func_named(\"RandCrop\", RandCropByPosNegLabeld(\n", + " range_func(\"RandCrop\", RandCropByPosNegLabeld(\n", " keys=[\"image\", \"label\"],\n", " label_key=\"label\",\n", " spatial_size=(96, 96, 96),\n", @@ -462,12 +475,14 @@ "3. `ToDeviced` transform: to move data to GPU and cache with `CacheDataset`, then execute random transforms on GPU directly, avoid CPU -> GPU sync in every epoch. Please note that not all the MONAI transforms support GPU operation so far, still working in progress.\n", "4. `ThreadDataLoader`: uses multi-threads instead of multi-processing, faster than `DataLoader` in light-weight task as we already cached the results of most computation.\n", "5. `DiceCE` loss function: computes Dice loss and Cross Entropy Loss, returns the weighted sum of these two losses.\n", - "6. Analyzed the training curve and tuned algorithm: Use `SGD` optimizer, different network parameters, etc." + "6. Analyzed the training curve and tuned algorithm: Use `SGD` optimizer, different network parameters, etc.\n", + "\n", + "(A note on code: to improve readability and support the profiling flag, we used the `with nvtx(...) if profiling else no_profiling` context pattern, where `no_profiling` is a null context from Python's native `contextlib` with no effect on the code. An acknowledgement is provided here[1](#fn1).)" ] }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 12, "metadata": { "vscode": { "languageId": "python" @@ -475,19 +490,16 @@ }, "outputs": [], "source": [ - "# reference used from https://stackoverflow.com/questions/27803059/conditional-with-statement-in-python/53088625#53088625\n", - "# accessed June 14, 2022\n", - "\n", "def train_process(fast=False):\n", " learning_rate = 2e-4\n", " val_interval = 5 # do validation for every epoch\n", "\n", " if torch.cuda.is_available():\n", - " device = torch.device(\"cuda:1\")\n", + " device = torch.device(\"cuda:0\")\n", " else:\n", " raise RuntimeError('this tutorial is intended for GPU, but no CUDA device is available')\n", "\n", - " train_trans, val_trans = transformations(fast=fast)\n", + " train_trans, val_trans = transformations(fast=fast, device=device)\n", " # set CacheDataset, ThreadDataLoader and DiceCE loss for MONAI fast training\n", " if fast:\n", " # as `RandCropByPosNegLabeld` crops from the cached content and `deepcopy`\n", @@ -1061,6 +1073,13 @@ "if directory is None:\n", " shutil.rmtree(root_dir)" ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[1](#fn1-back) Acknowledgement: This usage is inspired by [Conditional with statement in Python](https://stackoverflow.com/a/68682614) by [Lucas Vasquez](https://stackoverflow.com/users/10712525/lucas-vazquez), used with adaptations under [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/), accessed June 14, 2022." + ] } ], "metadata": { From bd6ab9033ca69eb725800dc897fc55291d1749b3 Mon Sep 17 00:00:00 2001 From: Yuchen Xu Date: Thu, 23 Jun 2022 21:05:04 -0700 Subject: [PATCH 07/12] fixed typo --- acceleration/fast_training_tutorial.ipynb | 26 ++++++++--------------- 1 file changed, 9 insertions(+), 17 deletions(-) diff --git a/acceleration/fast_training_tutorial.ipynb b/acceleration/fast_training_tutorial.ipynb index 4664b1162b..be47bf6351 100644 --- a/acceleration/fast_training_tutorial.ipynb +++ b/acceleration/fast_training_tutorial.ipynb @@ -377,7 +377,11 @@ { "cell_type": "code", "execution_count": 11, - "metadata": {}, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [], "source": [ "def transformations(fast=False, device='cuda:0'):\n", @@ -456,7 +460,7 @@ " if fast:\n", " # move the data to GPU and cache to avoid CPU -> GPU sync in every epoch\n", " val_transforms.append(\n", - " ToDeviced(keys=[\"image\", \"label\"], device=\"cuda:0\")\n", + " ToDeviced(keys=[\"image\", \"label\"], device=device)\n", " )\n", "\n", " return Compose(train_transforms), Compose(val_transforms)" @@ -855,7 +859,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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