387e650e16a5405691fb18ce05b34bd90239180e,deepchem/metalearning/tests/test_maml.py,TestMAML,test_sine,#TestMAML#,12
Before Change
batch = learner.get_batch()
feed_dict = {}
for j in range(len(batch)):
feed_dict[maml._input_placeholders[j]] = batch[j]
feed_dict[maml._meta_placeholders[j]] = batch[j]
loss1.append(
np.average(
np.sqrt(maml._session.run(maml._loss, feed_dict=feed_dict) )))
loss2.append(
np.average(
np.sqrt(maml._session.run(maml._meta_loss, feed_dict=feed_dict))))
After Change
loss, outputs = maml.predict_on_batch(batch)
loss1.append(np.sqrt(loss))
maml.train_on_current_task()
loss, outputs = maml.predict_on_batch(batch)
loss2.append(np.sqrt(loss))
// Initially the model should do a bad job of fitting the sine function.
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 6
Instances Project Name: deepchem/deepchem
Commit Name: 387e650e16a5405691fb18ce05b34bd90239180e
Time: 2020-01-31
Author: peastman@stanford.edu
File Name: deepchem/metalearning/tests/test_maml.py
Class Name: TestMAML
Method Name: test_sine
Project Name: deepchem/deepchem
Commit Name: de7f5863338af5e1f92257cb29a6ca9a1c52c473
Time: 2019-07-10
Author: peastman@stanford.edu
File Name: deepchem/metalearning/tests/test_maml.py
Class Name: TestMAML
Method Name: test_sine
Project Name: deepchem/deepchem
Commit Name: 387e650e16a5405691fb18ce05b34bd90239180e
Time: 2020-01-31
Author: peastman@stanford.edu
File Name: deepchem/metalearning/tests/test_maml.py
Class Name: TestMAML
Method Name: test_sine
Project Name: deepchem/deepchem
Commit Name: de7f5863338af5e1f92257cb29a6ca9a1c52c473
Time: 2019-07-10
Author: peastman@stanford.edu
File Name: examples/low_data/toxcast_maml.py
Class Name:
Method Name: compute_scores