LSTMStep pickles (dc8906b8) · Commits · 钟慕尧 / deepchem

deepchem/models/tensorgraph/layers.py

+5 −25

Original line number	Diff line number	Diff line
		@@ -1409,11 +1409,6 @@ class LSTMStep(Layer):
		def build(self):
		init = initializations.get(self.init)
		inner_init = initializations.get(self.inner_init)
		########################################################## DEBUG
		print("build()")
		print("self.input_dim")
		print(self.input_dim)
		########################################################## DEBUG
		self.W = init((self.input_dim, 4 * self.output_dim))
		self.U = inner_init((self.output_dim, 4 * self.output_dim))

		@@ -1424,12 +1419,14 @@ class LSTMStep(Layer):
		self.trainable_weights = [self.W, self.U, self.b]

		def none_tensors(self):
		W, U, b = self.W, self.U, self.b
		W, U, b, out_tensor = self.W, self.U, self.b, self.out_tensor
		trainable_weights = self.trainable_weights
		return W, U, b, trainable_weights
		self.W, self.U, self.b, self.out_tensor = None, None, None, None
		self.trainable_weights = []
		return W, U, b, out_tensor, trainable_weights

		def set_tensors(self, tensor):
		self.W, self.U, self.b, self.trainable_weights = tensor
		self.W, self.U, self.b, self.out_tensor, self.trainable_weights = tensor

		def create_tensor(self, in_layers=None, **kwargs):
		"""Execute this layer on input tensors.
		@@ -1454,12 +1451,6 @@ class LSTMStep(Layer):
		x, h_tm1, c_tm1 = inputs

		# Taken from Keras code [citation needed]
		########################################################## DEBUG
		print("x")
		print(x)
		print("self.W")
		print(self.W)
		########################################################## DEBUG
		z = model_ops.dot(x, self.W) + model_ops.dot(h_tm1, self.U) + self.b

		z0 = z[:, :self.output_dim]
		@@ -1509,9 +1500,6 @@ class AttnLSTMEmbedding(Layer):
		n_support,
		n_feat,
		max_depth,
		init='glorot_uniform',
		activation='linear',
		dropout=None,
		**kwargs):
		"""
		Parameters
		@@ -1524,17 +1512,9 @@ class AttnLSTMEmbedding(Layer):
		Number of features per atom
		max_depth: int
		Number of "processing steps" used by sequence-to-sequence for sets model.
		init: str, optional
		Type of initialization of weights
		activation: str, optional
		Activation for layers.
		dropout: float, optional
		Dropout probability
		"""
		super(AttnLSTMEmbedding, self).__init__(**kwargs)

		self.init = initializations.get(init) # Set weight initialization
		self.activation = activations.get(activation) # Get activations
		self.max_depth = max_depth
		self.n_test = n_test
		self.n_support = n_support

deepchem/models/tensorgraph/tensor_graph.py

+26 −8

Original line number	Diff line number	Diff line
		@@ -389,10 +389,10 @@ class TensorGraph(Model):
		for node in order:
		with tf.name_scope(node):
		node_layer = self.layers[node]
		########################################################### DEBUG
		print("node_layer")
		print(node_layer)
		########################################################### DEBUG
		############################################################ DEBUG
		#print("node_layer")
		#print(node_layer)
		############################################################ DEBUG
		node_layer.create_tensor(training=self._training_placeholder)
		self.rnn_initial_states += node_layer.rnn_initial_states
		self.rnn_final_states += node_layer.rnn_final_states
		@@ -510,10 +510,28 @@ class TensorGraph(Model):

		# Pickle itself
		pickle_name = os.path.join(self.model_dir, "model.pickle")
		######################################################### DEBUG
		print("self")
		print(self)
		######################################################### DEBUG
		########################################################## DEBUG
		#print("self")
		#print(self)

		#def debug_pickle(instance):
		# attribute = None

		# for k, v in instance.__dict__.iteritems():
		# print("checking: %s" % k)
		# print("type(v)")
		# print(type(v))
		# try:
		# pickle.dumps(v)
		# except:
		# attribute = k
		# break

		# return attribute
		#debug_pickle(self)
		##pickle.dumps(self)

		########################################################## DEBUG
		with open(pickle_name, 'wb') as fout:
		try:
		pickle.dump(self, fout)

deepchem/models/tensorgraph/tests/test_layers_pickle.py

+1 −1

Original line number	Diff line number	Diff line
		@@ -445,7 +445,7 @@ def test_MP_pickle():
		def test_LSTMStep_pickle():
		"""Tests that LSTMStep can be pickled."""
		n_feat = 10
		tg = TensorGraph(use_queue=False)
		tg = TensorGraph()
		y = Feature(shape=(None, 2*n_feat))
		state_zero = Feature(shape=(None, n_feat))
		state_one = Feature(shape=(None, n_feat))

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