4d3023ed5db726f6d4bab30e2ff0620472c37966,models_train.py,,,#,12
Before Change
frames_slice = frames_features[j - 8:j + 7]
network_inputs.append(frames_slice)
model = convolutional_model(input_shapes=list(network_inputs[0].shape) + [1],
num_frames=len(network_inputs[0]))
model.compile(optimizer="adam",
loss=deep_speaker_loss,
After Change
loss=deep_speaker_loss,
metrics=["accuracy"])
stub_targets = np.random.uniform(size=(BATCH_SIZE * NUM_FRAMES, 1))
print(model.train_on_batch(network_inputs, stub_targets))
print(model.summary())
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 6
Instances
Project Name: philipperemy/deep-speaker
Commit Name: 4d3023ed5db726f6d4bab30e2ff0620472c37966
Time: 2017-06-12
Author: premy@reactive.co.jp
File Name: models_train.py
Class Name:
Method Name:
Project Name: freelunchtheorem/Conditional_Density_Estimation
Commit Name: 6fbef6a3631d94991ab02a9f7411e3b6fd954dfc
Time: 2019-01-12
Author: jonas.rothfuss@gmx.de
File Name: tests/unittests_estimators.py
Class Name: TestConditionalDensityEstimators_2d_gaussian
Method Name: test_NKDE_with_2d_gaussian
Project Name: philipperemy/deep-speaker
Commit Name: d14ad44d0f425c04be5a6cdca13fc513fba53843
Time: 2017-06-12
Author: premy@reactive.co.jp
File Name: test_models_train.py
Class Name:
Method Name: