Merge pull request #824 from lilleswing/MaxPool2D (d1e9575a) · Commits · 钟慕尧 / deepchem

deepchem/models/tensorgraph/layers.py

+2 −2

Original line number	Diff line number	Diff line
		@@ -1302,7 +1302,7 @@ class Conv3D(Layer):
		return out_tensor


		class MaxPool(Layer):
		class MaxPool2D(Layer):

		def __init__(self,
		ksize=[1, 2, 2, 1],
		@@ -1312,7 +1312,7 @@ class MaxPool(Layer):
		self.ksize = ksize
		self.strides = strides
		self.padding = padding
		super(MaxPool, self).__init__(**kwargs)
		super(MaxPool2D, self).__init__(**kwargs)
		try:
		parent_shape = self.in_layers[0].shape
		self._shape = tuple(None if p is None else p // s

deepchem/models/tensorgraph/tests/test_layers.py

+34 −44

Original line number	Diff line number	Diff line
		import unittest

		import numpy as np
		import os
		import rdkit
		import tensorflow as tf
		from nose.tools import assert_true
		from tensorflow.python.framework import test_util
		from deepchem.feat.mol_graphs import ConvMol
		from deepchem.feat.mol_graphs import MultiConvMol

		from deepchem.feat.graph_features import ConvMolFeaturizer
		from deepchem.feat.mol_graphs import ConvMol
		from deepchem.models.tensorgraph.layers import Add, Conv3D, MaxPool2D, MaxPool3D
		from deepchem.models.tensorgraph.layers import AlphaShareLayer
		from deepchem.models.tensorgraph.layers import AttnLSTMEmbedding
		from deepchem.models.tensorgraph.layers import BatchNorm
		from deepchem.models.tensorgraph.layers import BetaShare
		from deepchem.models.tensorgraph.layers import CombineMeanStd
		from deepchem.models.tensorgraph.layers import Concat
		from deepchem.models.tensorgraph.layers import Constant
		from deepchem.models.tensorgraph.layers import Conv1D, Squeeze
		from deepchem.models.tensorgraph.layers import Conv2D
		from deepchem.models.tensorgraph.layers import Dense
		from deepchem.models.tensorgraph.layers import Flatten
		from deepchem.models.tensorgraph.layers import Reshape
		from deepchem.models.tensorgraph.layers import Transpose
		from deepchem.models.tensorgraph.layers import CombineMeanStd
		from deepchem.models.tensorgraph.layers import Repeat
		from deepchem.models.tensorgraph.layers import Gather
		from deepchem.models.tensorgraph.layers import GRU
		from deepchem.models.tensorgraph.layers import TimeSeriesDense
		from deepchem.models.tensorgraph.layers import Gather
		from deepchem.models.tensorgraph.layers import GraphConv
		from deepchem.models.tensorgraph.layers import GraphGather
		from deepchem.models.tensorgraph.layers import Input
		from deepchem.models.tensorgraph.layers import InputFifoQueue
		from deepchem.models.tensorgraph.layers import InteratomicL2Distances
		from deepchem.models.tensorgraph.layers import IterRefLSTMEmbedding
		from deepchem.models.tensorgraph.layers import L2Loss
		from deepchem.models.tensorgraph.layers import Concat
		from deepchem.models.tensorgraph.layers import Constant
		from deepchem.models.tensorgraph.layers import Variable
		from deepchem.models.tensorgraph.layers import Add
		from deepchem.models.tensorgraph.layers import Multiply
		from deepchem.models.tensorgraph.layers import LSTMStep
		from deepchem.models.tensorgraph.layers import LayerSplitter
		from deepchem.models.tensorgraph.layers import Log
		from deepchem.models.tensorgraph.layers import InteratomicL2Distances
		from deepchem.models.tensorgraph.layers import SoftMaxCrossEntropy
		from deepchem.models.tensorgraph.layers import Multiply
		from deepchem.models.tensorgraph.layers import ReduceMean
		from deepchem.models.tensorgraph.layers import ToFloat
		from deepchem.models.tensorgraph.layers import ReduceSum
		from deepchem.models.tensorgraph.layers import ReduceSquareDifference
		from deepchem.models.tensorgraph.layers import Conv2D
		from deepchem.models.tensorgraph.layers import Conv3D
		from deepchem.models.tensorgraph.layers import MaxPool
		from deepchem.models.tensorgraph.layers import MaxPool3D
		from deepchem.models.tensorgraph.layers import InputFifoQueue
		from deepchem.models.tensorgraph.layers import GraphConv
		from deepchem.models.tensorgraph.layers import GraphPool
		from deepchem.models.tensorgraph.layers import GraphGather
		from deepchem.models.tensorgraph.layers import BatchNorm
		from deepchem.models.tensorgraph.layers import ReduceSum
		from deepchem.models.tensorgraph.layers import Repeat
		from deepchem.models.tensorgraph.layers import Reshape
		from deepchem.models.tensorgraph.layers import SluiceLoss
		from deepchem.models.tensorgraph.layers import SoftMax
		from deepchem.models.tensorgraph.layers import WeightedError
		from deepchem.models.tensorgraph.layers import SoftMaxCrossEntropy
		from deepchem.models.tensorgraph.layers import TensorWrapper
		from deepchem.models.tensorgraph.layers import TimeSeriesDense
		from deepchem.models.tensorgraph.layers import ToFloat
		from deepchem.models.tensorgraph.layers import Transpose
		from deepchem.models.tensorgraph.layers import Variable
		from deepchem.models.tensorgraph.layers import VinaFreeEnergy
		from deepchem.models.tensorgraph.layers import WeightedError
		from deepchem.models.tensorgraph.layers import WeightedLinearCombo
		from deepchem.models.tensorgraph.layers import TensorWrapper
		from deepchem.models.tensorgraph.layers import LSTMStep
		from deepchem.models.tensorgraph.layers import AttnLSTMEmbedding
		from deepchem.models.tensorgraph.layers import IterRefLSTMEmbedding
		from deepchem.models.tensorgraph.layers import AlphaShareLayer
		from deepchem.models.tensorgraph.layers import BetaShare
		from deepchem.models.tensorgraph.layers import LayerSplitter
		from deepchem.models.tensorgraph.layers import SluiceLoss

		import deepchem as dc


		class TestLayers(test_util.TensorFlowTestCase):
		@@ -387,8 +377,8 @@ class TestLayers(test_util.TensorFlowTestCase):
		assert out_tensor.shape == (batch_size, length, width, depth,
		out_channels)

		def test_max_pool(self):
		"""Test that MaxPool can be invoked."""
		def test_maxpool2D(self):
		"""Test that MaxPool2D can be invoked."""
		length = 2
		width = 2
		in_channels = 2
		@@ -396,7 +386,7 @@ class TestLayers(test_util.TensorFlowTestCase):
		in_tensor = np.random.rand(batch_size, length, width, in_channels)
		with self.test_session() as sess:
		in_tensor = tf.convert_to_tensor(in_tensor, dtype=tf.float32)
		out_tensor = MaxPool()(in_tensor)
		out_tensor = MaxPool2D()(in_tensor)
		sess.run(tf.global_variables_initializer())
		out_tensor = out_tensor.eval()
		assert out_tensor.shape == (batch_size, 1, 1, in_channels)

deepchem/models/tensorgraph/tests/test_layers_pickle.py

+3 −3

Original line number	Diff line number	Diff line
		@@ -3,7 +3,7 @@ import tensorflow as tf
		from deepchem.models import TensorGraph
		from deepchem.models.tensorgraph.layers import Feature, Conv1D, Dense, Flatten, Reshape, Squeeze, Transpose, \
		CombineMeanStd, Repeat, Gather, GRU, L2Loss, Concat, SoftMax, Constant, Variable, Add, Multiply, Log, InteratomicL2Distances, \
		SoftMaxCrossEntropy, ReduceMean, ToFloat, ReduceSquareDifference, Conv2D, MaxPool, ReduceSum, GraphConv, GraphPool, \
		SoftMaxCrossEntropy, ReduceMean, ToFloat, ReduceSquareDifference, Conv2D, MaxPool2D, ReduceSum, GraphConv, GraphPool, \
		GraphGather, BatchNorm, WeightedError, \
		Conv3D, MaxPool3D, \
		LSTMStep, AttnLSTMEmbedding, IterRefLSTMEmbedding
		@@ -266,10 +266,10 @@ def test_Conv3D_pickle():
		tg.save()


		def test_MaxPool_pickle():
		def test_MaxPool2D_pickle():
		tg = TensorGraph()
		feature = Feature(shape=(tg.batch_size, 10, 10, 10))
		layer = MaxPool(in_layers=feature)
		layer = MaxPool2D(in_layers=feature)
		tg.add_output(layer)
		tg.set_loss(layer)
		tg.build()

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