Commenting out many more old classes (0d49f0f4) · Commits · 钟慕尧 / deepchem

deepchem/models/init.py

+0 −3

Original line number	Diff line number	Diff line
		@@ -13,9 +13,6 @@ from deepchem.models.multitask import SingletaskToMultitask
		from deepchem.models.tensorflow_models.fcnet import MultiTaskRegressor
		from deepchem.models.tensorflow_models.fcnet import MultiTaskClassifier
		from deepchem.models.tensorflow_models.fcnet import MultiTaskFitTransformRegressor
		from deepchem.models.tensorflow_models.lr import TensorflowLogisticRegression
		from deepchem.models.tensorflow_models.progressive_multitask import ProgressiveMultitaskRegressor
		from deepchem.models.tensorflow_models.progressive_joint import ProgressiveJointRegressor
		from deepchem.models.tensorflow_models.IRV import TensorflowMultiTaskIRVClassifier
		from deepchem.models.tensorgraph.tensor_graph import TensorGraph
		from deepchem.models.tensorgraph.models.graph_models import WeaveTensorGraph, DTNNTensorGraph, DAGTensorGraph, GraphConvTensorGraph, MPNNTensorGraph

deepchem/models/tensorflow_models/lr.py

+2 −2

Original line number	Diff line number	Diff line
		@@ -11,8 +11,6 @@ import os
		import time

		from deepchem.metrics import from_one_hot
		from deepchem.models.tensorflow_models import TensorflowGraph
		from deepchem.models.tensorflow_models import TensorflowGraphModel
		from deepchem.nn import model_ops
		from deepchem.utils.save import log
		from deepchem.data import pad_features
		@@ -40,6 +38,7 @@ def weight_decay(penalty_type, penalty):
		return cost


		'''
		class TensorflowLogisticRegression(TensorflowGraphModel):
		""" A simple tensorflow based logistic regression model. """

		@@ -246,3 +245,4 @@ class TensorflowLogisticRegression(TensorflowGraphModel):
		outputs = np.array(from_one_hot(np.concatenate(output), axis=-1))

		return np.copy(outputs)
		'''

deepchem/models/tensorflow_models/progressive_joint.py

+2 −5

Original line number	Diff line number	Diff line
		@@ -11,11 +11,7 @@ from deepchem.utils.save import log
		from deepchem.metrics import to_one_hot
		from deepchem.metrics import from_one_hot
		from deepchem.nn import model_ops
		from deepchem.models.tensorflow_models import TensorflowGraph
		from deepchem.models.tensorflow_models.fcnet import TensorflowMultiTaskClassifier
		from deepchem.models.tensorflow_models.fcnet import TensorflowMultiTaskRegressor


		'''
		class ProgressiveJointRegressor(TensorflowMultiTaskRegressor):
		"""Implements a progressive multitask neural network.

		@@ -430,3 +426,4 @@ class ProgressiveJointRegressor(TensorflowMultiTaskRegressor):
		config = tf.ConfigProto(allow_soft_placement=True)
		self.eval_graph.session = tf.Session(config=config)
		return self.eval_graph.session
		'''

deepchem/models/tensorflow_models/robust_multitask.py

+0 −1

Original line number	Diff line number	Diff line
		@@ -7,7 +7,6 @@ import numpy as np
		import tensorflow as tf

		from deepchem.nn import model_ops
		from deepchem.models.tensorflow_models import TensorflowGraph
		'''
		class RobustMultitaskClassifier(MultiTaskClassifier):
		"""Implements a neural network for robust multitasking.

deepchem/models/tests/test_overfit.py

+8 −1

Original line number	Diff line number	Diff line
		@@ -359,6 +359,7 @@ class TestOverfit(test_util.TensorFlowTestCase):
		scores = model.evaluate(dataset, [classification_metric])
		assert scores[classification_metric.name] > .9

		'''
		def test_tf_robust_multitask_classification_overfit(self):
		"""Test tf robust multitask overfits tiny data."""
		n_tasks = 10
		@@ -393,7 +394,8 @@ class TestOverfit(test_util.TensorFlowTestCase):
		# Eval model on train
		scores = model.evaluate(dataset, [classification_metric])
		assert scores[classification_metric.name] > .9

		'''
		'''
		def test_tf_logreg_multitask_classification_overfit(self):
		"""Test tf multitask overfits tiny data."""
		n_tasks = 10
		@@ -425,6 +427,7 @@ class TestOverfit(test_util.TensorFlowTestCase):
		# Eval model on train
		scores = model.evaluate(dataset, [classification_metric])
		assert scores[classification_metric.name] > .9
		'''

		def test_IRV_multitask_classification_overfit(self):
		"""Test IRV classifier overfits tiny data."""
		@@ -522,6 +525,7 @@ class TestOverfit(test_util.TensorFlowTestCase):
		scores = model.evaluate(dataset, [regression_metric])
		assert scores[regression_metric.name] < .1

		'''
		def test_tf_robust_multitask_regression_overfit(self):
		"""Test tf robust multitask overfits tiny data."""
		np.random.seed(123)
		@@ -559,6 +563,7 @@ class TestOverfit(test_util.TensorFlowTestCase):
		# Eval model on train
		scores = model.evaluate(dataset, [regression_metric])
		assert scores[regression_metric.name] < .2
		'''

		def test_tensorgraph_DTNN_multitask_regression_overfit(self):
		"""Test deep tensor neural net overfits tiny data."""
		@@ -905,6 +910,7 @@ class TestOverfit(test_util.TensorFlowTestCase):

		assert scores[regression_metric.name] > .9

		'''
		def test_tf_progressive_regression_overfit(self):
		"""Test tf progressive multitask overfits tiny data."""
		np.random.seed(123)
		@@ -943,3 +949,4 @@ class TestOverfit(test_util.TensorFlowTestCase):
		scores = model.evaluate(dataset, [metric])
		y_pred = model.predict(dataset)
		assert scores[metric.name] < .2
		'''

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