Partial debugging progress (bbdc4ea2) · Commits · 钟慕尧 / deepchem

deepchem/nn/copy.py

+3 −5

Original line number	Diff line number	Diff line
		@@ -66,8 +66,6 @@ class Layer(object):
		if not hasattr(self, 'uses_learning_phase'):
		self.uses_learning_phase = False

		if not hasattr(self, '_non_trainable_weights'):
		self._non_trainable_weights = []
		if not hasattr(self, 'losses'):
		self.losses = []

		@@ -133,8 +131,9 @@ class Layer(object):
		----------
		x: Can be a tensor or list/tuple of tensors.
		"""
		outputs = to_list(self.call(x))
		return outputs
		return self.call(x)
		#outputs = to_list(self.call(x))
		#return outputs

		class InputLayer(Layer):
		"""Layer to be used as an entry point into a graph.
		@@ -154,7 +153,6 @@ class InputLayer(Layer):
		input_dtype=None, name=None):
		self.uses_learning_phase = False
		self.trainable = False
		self._non_trainable_weights = []

		if not name:
		prefix = 'input'

+14 −13

Original line number	Diff line number	Diff line
		@@ -488,19 +488,6 @@ class AttnLSTMEmbedding(Layer):
		self.n_test = n_test
		self.n_support = n_support

		def build(self, input_shape):
		"""Initializes trainable weights."""
		x_input_shape, xp_input_shape = input_shape #Unpack

		n_feat = xp_input_shape[1]

		self.lstm = LSTMStep(n_feat)
		self.q_init = model_ops.zeros([self.n_test, n_feat])
		self.r_init = model_ops.zeros([self.n_test, n_feat])
		self.states_init = self.lstm.get_initial_states([self.n_test, n_feat])

		self.trainable_weights = [self.q_init, self.r_init]

		def get_output_shape_for(self, input_shape):
		"""Returns the output shape. Same as input_shape.

		@@ -538,6 +525,20 @@ class AttnLSTMEmbedding(Layer):
		# x is test set, xp is support set.
		x, xp = x_xp

		## Initializes trainable weights.
		#n_feat = xp_input_shape[1]
		n_feat = xp.get_shape()[1]

		self.lstm = LSTMStep(n_feat)
		self.q_init = model_ops.zeros([self.n_test, n_feat])
		self.r_init = model_ops.zeros([self.n_test, n_feat])
		self.states_init = self.lstm.get_initial_states([self.n_test, n_feat])

		self.trainable_weights = [self.q_init, self.r_init]


		### Performs computations

		# Get initializations
		q = self.q_init
		#r = self.r_init

+4 −0

Original line number	Diff line number	Diff line
		@@ -69,6 +69,10 @@ class TestLayers(test_util.TensorFlowTestCase):

		X = graph_topology.get_input_placeholders()
		out = graph_gather_layer(X)
		##################################################### DEBUG
		print("out")
		print(out)
		##################################################### DEBUG
		# Output should be of shape (batch_size, n_feat)
		assert out.get_shape() == (batch_size, n_feat)