Merge pull request #655 from peastman/normalizer (6dd2f1b3) · Commits · 钟慕尧 / deepchem

deepchem/models/tensorgraph/layers.py

+5 −1

Original line number	Diff line number	Diff line
		@@ -767,6 +767,7 @@ class Conv2D(Layer):
		stride=1,
		padding='SAME',
		activation_fn=tf.nn.relu,
		normalizer_fn=None,
		scope_name=None,
		**kwargs):
		"""Create a Conv2D layer.
		@@ -787,12 +788,15 @@ class Conv2D(Layer):
		the padding method to use, either 'SAME' or 'VALID'
		activation_fn: object
		the Tensorflow activation function to apply to the output
		normalizer_fn: object
		the Tensorflow normalizer function to apply to the output
		"""
		self.num_outputs = num_outputs
		self.kernel_size = kernel_size
		self.stride = stride
		self.padding = padding
		self.activation_fn = activation_fn
		self.normalizer_fn = normalizer_fn
		super(Conv2D, self).__init__(**kwargs)
		if scope_name is None:
		scope_name = self.name
		@@ -808,7 +812,7 @@ class Conv2D(Layer):
		stride=self.stride,
		padding=self.padding,
		activation_fn=self.activation_fn,
		normalizer_fn=tf.contrib.layers.batch_norm,
		normalizer_fn=self.normalizer_fn,
		scope=self.scope_name)
		out_tensor = out_tensor
		if set_tensors:

+8 −2

Original line number	Diff line number	Diff line
		@@ -25,10 +25,16 @@ class TestTensorGraphMNIST(unittest.TestCase):
		feature = Feature(shape=(None, 784), name="Feature")
		make_image = Reshape(shape=(-1, 28, 28, 1), in_layers=[feature])

		conv2d_1 = Conv2D(num_outputs=32, in_layers=[make_image])
		conv2d_1 = Conv2D(
		num_outputs=32,
		normalizer_fn=tf.contrib.layers.batch_norm,
		in_layers=[make_image])
		maxpool_1 = MaxPool(in_layers=[conv2d_1])

		conv2d_2 = Conv2D(num_outputs=64, in_layers=[maxpool_1])
		conv2d_2 = Conv2D(
		num_outputs=64,
		normalizer_fn=tf.contrib.layers.batch_norm,
		in_layers=[maxpool_1])
		maxpool_2 = MaxPool(in_layers=[conv2d_2])
		flatten = Flatten(in_layers=[maxpool_2])