Merge pull request #88 from azavea/lf/sgd

Add stuff from last week of competition

src/experiments/tagging/7_16_17/densenet/generate_experiments.py

@@ -0,0 +1,41 @@
+from os.path import join
+from copy import deepcopy
+
+from rastervision.experiment_generator import (
+    ExperimentGenerator, get_parent_dir)
+
+
+class TestExperimentGenerator(ExperimentGenerator):
+    def generate_experiments(self):
+        base_exp = {
+            'batch_size': 8,
+            'problem_type': 'tagging',
+            'dataset_name': 'planet_kaggle',
+            'generator_name': 'jpg',
+            'active_input_inds': [0, 1, 2],
+            'use_pretraining': True,
+            'optimizer': 'adam',
+            'lr_schedule': [[0, 0.0001], [10, 0.00001]],
+            'model_type': 'densenet121',
+            'train_ratio': 0.99,
+            'epochs': 15,
+            'nb_eval_plot_samples': 100,
+            'validation_steps': 8,
+            'run_name': 'tagging/7_16_17/densenet',
+            'steps_per_epoch': 2400,
+            'augment_methods': ['hflip', 'vflip', 'rotate90']
+        }
+
+        exps = []
+        nb_exps = 5
+        for exp_ind in range(nb_exps):
+            exp = deepcopy(base_exp)
+            exp['run_name'] = join(exp['run_name'], str(exp_ind))
+            exps.append(exp)
+
+        return exps
+
+
+if __name__ == '__main__':
+    path = get_parent_dir(__file__)
+    gen = TestExperimentGenerator().run(path)

src/experiments/tagging/7_16_17/resnet/generate_experiments.py

@@ -0,0 +1,44 @@
+from os.path import join
+from copy import deepcopy
+
+from rastervision.experiment_generator import (
+    ExperimentGenerator, get_parent_dir)
+
+
+class TestExperimentGenerator(ExperimentGenerator):
+    def generate_experiments(self):
+        base_exp = {
+            'batch_size': 32,
+            'git_commit': '7f79ca',
+            'problem_type': 'tagging',
+            'dataset_name': 'planet_kaggle',
+            'generator_name': 'jpg',
+            'active_input_inds': [0, 1, 2],
+            'use_pretraining': True,
+            'optimizer': 'sgd',
+            'lr_schedule': [[0, 1e-2], [10, 1e-3]],
+            'nesterov': True,
+            'momentum': 0.9,
+            'train_ratio': 0.99,
+            'nb_eval_plot_samples': 100,
+            'epochs': 20,
+            'validation_steps': 8,
+            'run_name': 'tagging/7_16_17/resnet',
+            'steps_per_epoch': 600,
+            'augment_methods': ['hflip', 'vflip', 'rotate90'],
+            'model_type': 'baseline_resnet'
+        }
+        exps = []
+        exp_count = 0
+        for run_ind in range(5):
+            exp = deepcopy(base_exp)
+            exp['run_name'] = join(exp['run_name'], str(exp_count))
+            exps.append(exp)
+            exp_count += 1
+
+        return exps
+
+
+if __name__ == '__main__':
+    path = get_parent_dir(__file__)
+    gen = TestExperimentGenerator().run(path)

src/experiments/tagging/7_17_17/densenet_transform/generate_experiments.py

@@ -0,0 +1,42 @@
+from os.path import join
+from copy import deepcopy
+
+from rastervision.experiment_generator import (
+    ExperimentGenerator, get_parent_dir)
+
+
+class TestExperimentGenerator(ExperimentGenerator):
+    def generate_experiments(self):
+        base_exp = {
+            'batch_size': 8,
+            'problem_type': 'tagging',
+            'dataset_name': 'planet_kaggle',
+            'generator_name': 'jpg',
+            'active_input_inds': [0, 1, 2],
+            'use_pretraining': True,
+            'optimizer': 'adam',
+            'lr_schedule': [[0, 0.0001], [10, 0.00001]],
+            'model_type': 'densenet121',
+            'train_ratio': 0.99,
+            'epochs': 15,
+            'nb_eval_plot_samples': 100,
+            'validation_steps': 8,
+            'run_name': 'tagging/7_17_17/densenet_transform',
+            'steps_per_epoch': 2400,
+            'augment_methods': ['hflip', 'vflip', 'rotate', 'zoom',
+                                'translate']
+        }
+
+        exps = []
+        nb_exps = 5
+        for exp_ind in range(nb_exps):
+            exp = deepcopy(base_exp)
+            exp['run_name'] = join(exp['run_name'], str(exp_ind))
+            exps.append(exp)
+
+        return exps
+
+
+if __name__ == '__main__':
+    path = get_parent_dir(__file__)
+    gen = TestExperimentGenerator().run(path)

src/experiments/tagging/7_17_17/inception/inception_adam.json

@@ -0,0 +1,35 @@
+{
+    "active_input_inds": [
+        0,
+        1,
+        2
+    ],
+    "augment_methods": [
+        "hflip",
+        "vflip",
+        "rotate90"
+    ],
+    "batch_size": 32,
+    "dataset_name": "planet_kaggle",
+    "epochs": 20,
+    "generator_name": "jpg",
+    "lr_schedule": [
+        [
+            0,
+            0.0001
+        ],
+        [
+            10,
+            0.00001
+        ]
+    ],
+    "model_type": "inception_v3",
+    "nb_eval_plot_samples": 100,
+    "optimizer": "adam",
+    "problem_type": "tagging",
+    "run_name": "tagging/7_17_17/inception/inception_adam",
+    "steps_per_epoch": 600,
+    "train_ratio": 0.8,
+    "use_pretraining": true,
+    "validation_steps": 120
+}

src/experiments/tagging/7_17_17/inception/inception_rms.json

@@ -0,0 +1,37 @@
+{
+    "active_input_inds": [
+        0,
+        1,
+        2
+    ],
+    "augment_methods": [
+        "hflip",
+        "vflip",
+        "rotate90"
+    ],
+    "batch_size": 32,
+    "dataset_name": "planet_kaggle",
+    "epochs": 20,
+    "generator_name": "jpg",
+    "lr_schedule": [
+        [
+            0,
+            0.005
+        ],
+        [
+            10,
+            0.0005
+        ]
+    ],
+    "model_type": "inception_v3",
+    "nb_eval_plot_samples": 100,
+    "optimizer": "rms_prop",
+    "rho": 0.9,
+    "epsilon": 1.0,
+    "problem_type": "tagging",
+    "run_name": "tagging/7_17_17/inception/inception_rms",
+    "steps_per_epoch": 600,
+    "train_ratio": 0.8,
+    "use_pretraining": true,
+    "validation_steps": 120
+}

src/experiments/tagging/7_17_17/inception/inception_test.json

@@ -0,0 +1,39 @@
+{
+    "active_input_inds": [
+        0,
+        1,
+        2
+    ],
+    "augment_methods": [
+        "hflip",
+        "vflip",
+        "rotate90"
+    ],
+    "batch_size": 1,
+    "dataset_name": "planet_kaggle",
+    "epochs": 2,
+    "generator_name": "jpg",
+    "lr_schedule": [
+        [
+            0,
+            0.005
+        ],
+        [
+            10,
+            0.0005
+        ]
+    ],
+    "nb_eval_samples": 1,
+    "nb_eval_plot_samples": 1,
+    "model_type": "inception_v3",
+    "nb_eval_plot_samples": 1,
+    "optimizer": "rms_prop",
+    "rho": 0.9,
+    "epsilon": 1.0,
+    "problem_type": "tagging",
+    "run_name": "tagging/7_17_17/inception/inception_test",
+    "steps_per_epoch": 1,
+    "train_ratio": 0.8,
+    "use_pretraining": true,
+    "validation_steps": 1
+}

src/experiments/tagging/7_17_17/resnet_transform/generate_experiments.py

@@ -0,0 +1,45 @@
+from os.path import join
+from copy import deepcopy
+
+from rastervision.experiment_generator import (
+    ExperimentGenerator, get_parent_dir)
+
+
+class TestExperimentGenerator(ExperimentGenerator):
+    def generate_experiments(self):
+        base_exp = {
+            'batch_size': 32,
+            'git_commit': '7f79ca',
+            'problem_type': 'tagging',
+            'dataset_name': 'planet_kaggle',
+            'generator_name': 'jpg',
+            'active_input_inds': [0, 1, 2],
+            'use_pretraining': True,
+            'optimizer': 'sgd',
+            'lr_schedule': [[0, 1e-2], [10, 1e-3]],
+            'nesterov': True,
+            'momentum': 0.9,
+            'train_ratio': 0.99,
+            'nb_eval_plot_samples': 100,
+            'epochs': 20,
+            'validation_steps': 8,
+            'run_name': 'tagging/7_17_17/resnet_transform',
+            'steps_per_epoch': 600,
+            'augment_methods': ['hflip', 'vflip', 'rotate', 'zoom',
+                                'translate'],
+            'model_type': 'baseline_resnet'
+        }
+        exps = []
+        exp_count = 0
+        for run_ind in range(5):
+            exp = deepcopy(base_exp)
+            exp['run_name'] = join(exp['run_name'], str(exp_count))
+            exps.append(exp)
+            exp_count += 1
+
+        return exps
+
+
+if __name__ == '__main__':
+    path = get_parent_dir(__file__)
+    gen = TestExperimentGenerator().run(path)

src/experiments/tagging/7_18_17/80/densenet_transform/generate_experiments.py

@@ -0,0 +1,42 @@
+from os.path import join
+from copy import deepcopy
+
+from rastervision.experiment_generator import (
+    ExperimentGenerator, get_parent_dir)
+
+
+class TestExperimentGenerator(ExperimentGenerator):
+    def generate_experiments(self):
+        base_exp = {
+            'batch_size': 8,
+            'problem_type': 'tagging',
+            'dataset_name': 'planet_kaggle',
+            'generator_name': 'jpg',
+            'active_input_inds': [0, 1, 2],
+            'use_pretraining': True,
+            'optimizer': 'adam',
+            'lr_schedule': [[0, 0.0001], [10, 0.00001]],
+            'model_type': 'densenet121',
+            'train_ratio': 0.8,
+            'epochs': 15,
+            'nb_eval_plot_samples': 100,
+            'validation_steps': 600,
+            'run_name': 'tagging/7_18_17/80/densenet_transform',
+            'steps_per_epoch': 2400,
+            'augment_methods': ['hflip', 'vflip', 'rotate', 'zoom',
+                                'translate']
+        }
+
+        exps = []
+        nb_exps = 2
+        for exp_ind in range(nb_exps):
+            exp = deepcopy(base_exp)
+            exp['run_name'] = join(exp['run_name'], str(exp_ind))
+            exps.append(exp)
+
+        return exps
+
+
+if __name__ == '__main__':
+    path = get_parent_dir(__file__)
+    gen = TestExperimentGenerator().run(path)

src/experiments/tagging/7_18_17/80/inception/generate_experiments.py

@@ -0,0 +1,43 @@
+from os.path import join
+from copy import deepcopy
+
+from rastervision.experiment_generator import (
+    ExperimentGenerator, get_parent_dir)
+
+
+class TestExperimentGenerator(ExperimentGenerator):
+    def generate_experiments(self):
+        base_exp = {
+            'batch_size': 32,
+            'problem_type': 'tagging',
+            'dataset_name': 'planet_kaggle',
+            'generator_name': 'jpg',
+            'active_input_inds': [0, 1, 2],
+            'use_pretraining': True,
+            'optimizer': 'sgd',
+            'lr_schedule': [[0, 1e-2], [15, 1e-3]],
+            'nesterov': True,
+            'momentum': 0.9,
+            'train_ratio': 0.8,
+            'nb_eval_plot_samples': 100,
+            'epochs': 30,
+            'validation_steps': 120,
+            'run_name': 'tagging/7_18_17/80/inception/',
+            'steps_per_epoch': 600,
+            'augment_methods': ['hflip', 'vflip', 'rotate90'],
+            'model_type': 'inception_v3'
+        }
+        exps = []
+        exp_count = 0
+        for run_ind in range(5):
+            exp = deepcopy(base_exp)
+            exp['run_name'] = join(exp['run_name'], str(exp_count))
+            exps.append(exp)
+            exp_count += 1
+
+        return exps
+
+
+if __name__ == '__main__':
+    path = get_parent_dir(__file__)
+    gen = TestExperimentGenerator().run(path)