final tweaks to scripts, halfway run now!

Signed-off-by: vsoch <vsochat@stanford.edu>
vsoch · Jan 4, 2021 · 9fe74b1 · 9fe74b1
1 parent ca94522
commit 9fe74b1
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Showing 21 changed files with 31 additions and 33 deletions.
diff --git a/caliper.yaml b/caliper.yaml
@@ -11,7 +11,6 @@ analysis:
     - tensorflow_v0.11/1_Introduction/helloworld.py
     - tensorflow_v0.11/4_Utils/tensorboard_advanced.py
     - tensorflow_v0.11/4_Utils/tensorboard_basic.py
-    - tensorflow_v0.11/4_Utils/save_restore_model.py
     - tensorflow_v0.11/2_BasicModels/logistic_regression.py
     - tensorflow_v0.11/2_BasicModels/linear_regression.py
     - tensorflow_v0.11/2_BasicModels/nearest_neighbor.py
@@ -27,7 +26,6 @@ analysis:
     - tensorflow_v1/1_Introduction/helloworld.py
     - tensorflow_v1/4_Utils/tensorboard_advanced.py
     - tensorflow_v1/4_Utils/tensorboard_basic.py
-    - tensorflow_v1/4_Utils/save_restore_model.py
     - tensorflow_v1/5_DataManagement/build_an_image_dataset.py
     - tensorflow_v1/5_DataManagement/tensorflow_dataset_api.py
     - tensorflow_v1/2_BasicModels/random_forest.py

diff --git a/tensorflow_v0.11/3_NeuralNetworks/autoencoder.py b/tensorflow_v0.11/3_NeuralNetworks/autoencoder.py
@@ -28,10 +28,10 @@
 
 # Parameters
 learning_rate = 0.01
-training_epochs = 2
+training_epochs = 1
 batch_size = 256
 display_step = 1
-examples_to_show = 10
+examples_to_show = 2
 
 
 # Network Parameters

diff --git a/tensorflow_v0.11/3_NeuralNetworks/bidirectional_rnn.py b/tensorflow_v0.11/3_NeuralNetworks/bidirectional_rnn.py
@@ -33,9 +33,9 @@
 
 # Parameters
 learning_rate = 0.001
-training_iters = 100
+training_iters = 10
 batch_size = 128
-display_step = 10
+display_step = 1
 
 # Network Parameters
 n_input = 28  # MNIST data input (img shape: 28*28)

diff --git a/tensorflow_v0.11/3_NeuralNetworks/convolutional_network.py b/tensorflow_v0.11/3_NeuralNetworks/convolutional_network.py
@@ -24,7 +24,7 @@
 
 # Parameters
 learning_rate = 0.001
-training_iters = 10
+training_iters = 2
 batch_size = 128
 display_step = 10
 

diff --git a/tensorflow_v0.11/3_NeuralNetworks/dynamic_rnn.py b/tensorflow_v0.11/3_NeuralNetworks/dynamic_rnn.py
@@ -91,9 +91,9 @@ def next(self, batch_size):
 
 # Parameters
 learning_rate = 0.01
-training_iters = 100
+training_iters = 10
 batch_size = 128
-display_step = 10
+display_step = 1
 
 # Network Parameters
 seq_max_len = 20  # Sequence max length

diff --git a/tensorflow_v0.11/3_NeuralNetworks/multilayer_perceptron.py b/tensorflow_v0.11/3_NeuralNetworks/multilayer_perceptron.py
@@ -24,7 +24,7 @@
 
 # Parameters
 learning_rate = 0.001
-training_epochs = 2
+training_epochs = 1
 batch_size = 300
 display_step = 1
 

diff --git a/tensorflow_v0.11/3_NeuralNetworks/recurrent_network.py b/tensorflow_v0.11/3_NeuralNetworks/recurrent_network.py
@@ -31,9 +31,9 @@
 
 # Parameters
 learning_rate = 0.001
-training_iters = 100
+training_iters = 10
 batch_size = 256
-display_step = 100
+display_step = 1
 
 # Network Parameters
 n_input = 28  # MNIST data input (img shape: 28*28)

diff --git a/tensorflow_v0.11/4_Utils/tensorboard_advanced.py b/tensorflow_v0.11/4_Utils/tensorboard_advanced.py
@@ -23,7 +23,7 @@
 mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
 
 learning_rate = 0.01
-training_epochs = 2
+training_epochs = 1
 batch_size = 500
 display_step = 1
 logs_path = "/tmp/tensorflow_logs/example/"

diff --git a/tensorflow_v0.11/4_Utils/tensorboard_basic.py b/tensorflow_v0.11/4_Utils/tensorboard_basic.py
@@ -24,7 +24,7 @@
 
 # Parameters
 learning_rate = 0.01
-training_epochs = 2
+training_epochs = 1
 batch_size = 300
 display_epoch = 1
 logs_path = "/tmp/tensorflow_logs/example/"

diff --git a/tensorflow_v1/2_BasicModels/kmeans.py b/tensorflow_v1/2_BasicModels/kmeans.py
@@ -35,7 +35,7 @@
 full_data_x = mnist.train.images
 
 # Parameters
-num_steps = 3  # Total steps to train
+num_steps = 2  # Total steps to train
 batch_size = 1024  # The number of samples per batch
 k = 25  # The number of clusters
 num_classes = 10  # The 10 digits

diff --git a/tensorflow_v1/2_BasicModels/random_forest.py b/tensorflow_v1/2_BasicModels/random_forest.py
@@ -31,7 +31,7 @@
 mnist = input_data.read_data_sets("/tmp/data/", one_hot=False)
 
 # Parameters
-num_steps = 100  # Total steps to train
+num_steps = 10  # Total steps to train
 batch_size = 1024  # The number of samples per batch
 num_classes = 10  # The 10 digits
 num_features = 784  # Each image is 28x28 pixels

diff --git a/tensorflow_v1/2_BasicModels/word2vec.py b/tensorflow_v1/2_BasicModels/word2vec.py
@@ -34,9 +34,9 @@
 # Training Parameters
 learning_rate = 0.1
 batch_size = 128
-num_steps = 1000
-display_step = 100
-eval_step = 2000
+num_steps = 10
+display_step = 1
+eval_step = 1
 
 # Evaluation Parameters
 eval_words = ["five", "of", "going", "hardware", "american", "britain"]

diff --git a/tensorflow_v1/3_NeuralNetworks/autoencoder.py b/tensorflow_v1/3_NeuralNetworks/autoencoder.py
@@ -33,11 +33,11 @@
 
 # Training Parameters
 learning_rate = 0.01
-num_steps = 2  # reduced from 30000 to make faster
+num_steps = 1  # reduced from 30000 to make faster
 batch_size = 256
 
 display_step = 1
-examples_to_show = 10
+examples_to_show = 2
 
 # Network Parameters
 num_hidden_1 = 256  # 1st layer num features

diff --git a/tensorflow_v1/3_NeuralNetworks/bidirectional_rnn.py b/tensorflow_v1/3_NeuralNetworks/bidirectional_rnn.py
@@ -36,9 +36,9 @@
 
 # Training Parameters
 learning_rate = 0.001
-training_steps = 100
+training_steps = 10
 batch_size = 128
-display_step = 10
+display_step = 1
 
 # Network Parameters
 num_input = 28  # MNIST data input (img shape: 28*28)

diff --git a/tensorflow_v1/3_NeuralNetworks/convolutional_network.py b/tensorflow_v1/3_NeuralNetworks/convolutional_network.py
@@ -26,7 +26,7 @@
 
 # Training Parameters
 learning_rate = 0.001
-num_steps = 10
+num_steps = 2
 batch_size = 128
 
 # Network Parameters

diff --git a/tensorflow_v1/3_NeuralNetworks/dynamic_rnn.py b/tensorflow_v1/3_NeuralNetworks/dynamic_rnn.py
@@ -93,9 +93,9 @@ def next(self, batch_size):
 
 # Parameters
 learning_rate = 0.01
-training_steps = 100
+training_steps = 10
 batch_size = 128
-display_step = 10
+display_step = 1
 
 # Network Parameters
 seq_max_len = 20  # Sequence max length

diff --git a/tensorflow_v1/3_NeuralNetworks/multilayer_perceptron.py b/tensorflow_v1/3_NeuralNetworks/multilayer_perceptron.py
@@ -35,7 +35,7 @@
 
 # Parameters
 learning_rate = 0.001
-training_epochs = 2
+training_epochs = 1
 batch_size = 300
 display_step = 1
 

diff --git a/tensorflow_v1/3_NeuralNetworks/recurrent_network.py b/tensorflow_v1/3_NeuralNetworks/recurrent_network.py
@@ -34,9 +34,9 @@
 
 # Training Parameters
 learning_rate = 0.001
-training_steps = 100
+training_steps = 10
 batch_size = 256
-display_step = 200
+display_step = 1
 
 
 # Network Parameters

diff --git a/tensorflow_v1/4_Utils/tensorboard_advanced.py b/tensorflow_v1/4_Utils/tensorboard_advanced.py
@@ -23,7 +23,7 @@
 
 # Parameters
 learning_rate = 0.01
-training_epochs = 2
+training_epochs = 1
 batch_size = 500
 display_step = 1
 logs_path = "/tmp/tensorflow_logs/example/"

diff --git a/tensorflow_v1/4_Utils/tensorboard_basic.py b/tensorflow_v1/4_Utils/tensorboard_basic.py
@@ -23,7 +23,7 @@
 
 # Parameters
 learning_rate = 0.01
-training_epochs = 2
+training_epochs = 1
 batch_size = 300
 display_epoch = 1
 logs_path = "/tmp/tensorflow_logs/example/"

diff --git a/tensorflow_v1/5_DataManagement/tensorflow_dataset_api.py b/tensorflow_v1/5_DataManagement/tensorflow_dataset_api.py
@@ -23,9 +23,9 @@
 
 # Parameters
 learning_rate = 0.001
-num_steps = 100
+num_steps = 10
 batch_size = 128
-display_step = 100
+display_step = 10
 
 # Network Parameters
 n_input = 784  # MNIST data input (img shape: 28*28)