Changing imports in files (203ac99d) · Commits · 钟慕尧 / deepchem

deepchem/init.py

+0 −1

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		@@ -13,7 +13,6 @@ import deepchem.hyper
		import deepchem.metalearning
		import deepchem.metrics
		import deepchem.models
		import deepchem.nn
		import deepchem.splits
		import deepchem.trans
		import deepchem.utils

+1 −1

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		@@ -12,7 +12,7 @@ import threading
		import collections

		import deepchem as dc
		from deepchem.nn import model_ops
		from deepchem.models.tensorgraph import model_ops
		from deepchem.utils.save import log
		from deepchem.metrics import to_one_hot, from_one_hot
		from deepchem.metrics import to_one_hot

+3 −4

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		@@ -12,10 +12,9 @@ from __future__ import unicode_literals

		import numpy as np
		import tensorflow as tf
		from deepchem.nn import activations
		from deepchem.nn import initializations
		from deepchem.nn import model_ops

		from deepchem.models.tensorgraph import activations
		from deepchem.models.tensorgraph import initializations
		from deepchem.models.tensorgraph import model_ops
		from deepchem.models.tensorgraph.layers import Layer, LayerSplitter
		from deepchem.models.tensorgraph.layers import convert_to_layers

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		@@ -5,7 +5,6 @@ repository. The SequenceDNN class is useful for prediction
		tasks working with genomic data.
		"""
		import tensorflow as tf
		from deepchem.nn.regularizers import l1
		from deepchem.models import Sequential
		from deepchem.models.tensorgraph import layers
		from deepchem.data import NumpyDataset

+5 −6

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		@@ -11,10 +11,9 @@ from __future__ import unicode_literals

		import numpy as np
		import tensorflow as tf
		from deepchem.nn import activations
		from deepchem.nn import initializations
		from deepchem.nn import model_ops

		from deepchem.models.tensorgraph import activations
		from deepchem.models.tensorgraph import initializations
		from deepchem.models.tensorgraph import model_ops
		from deepchem.models.tensorgraph.layers import Layer
		from deepchem.models.tensorgraph.layers import convert_to_layers
		from deepchem.metrics import to_one_hot
		@@ -445,8 +444,8 @@ class AtomicDifferentiatedDense(Layer):
		self.b[i, :])

		mask = 1 - tf.to_float(tf.cast(atom_numbers - atom_case, tf.bool))
		output = tf.reshape(output * tf.expand_dims(mask, 2), (-1, self.max_atoms,
		self.out_channels))
		output = tf.reshape(output * tf.expand_dims(mask, 2),
		(-1, self.max_atoms, self.out_channels))
		outputs.append(output)
		self.out_tensor = tf.add_n(outputs)