Fixed testing errors (4e7d5adb) · Commits · 钟慕尧 / deepchem

deepchem/models/tensorgraph/tensor_graph.py

+3 −2

Original line number	Diff line number	Diff line
		@@ -974,11 +974,11 @@ class TensorGraph(Model):

		def get_layer_variables(self, layer):
		"""Get the list of trainable variables in a layer of the graph."""
		if tfe.in_eager_mode():
		return layer.variables
		if not self.built:
		self.build()
		with self._get_tf("Graph").as_default():
		if tfe.in_eager_mode():
		return layer.variables
		if layer.variable_scope == '':
		return []
		return tf.get_collection(
		@@ -988,6 +988,7 @@ class TensorGraph(Model):
		"""Get the variable values associated with a given layer """

		layer_variables = self.get_layer_variables(layer)
		with self._get_tf("Graph").as_default():
		if tfe.in_eager_mode():
		return [v.numpy() for v in layer_variables]
		if len(layer_variables) == 0:

+5 −4

Original line number	Diff line number	Diff line
		@@ -585,7 +585,7 @@ class TestTensorGraph(unittest.TestCase):
		tg.add_output(var)
		expected = [10.0, 12.0]
		obtained = tg.get_layer_variable_values(var)[0]
		np.testing.assert_array_almost_equal(expected, obtained)
		np.testing.assert_array_equal(expected, obtained)

		# Test for shapes (normal mode)
		tg = dc.models.TensorGraph()
		@@ -596,22 +596,23 @@ class TestTensorGraph(unittest.TestCase):
		obtained_shape = tg.get_layer_variable_values(output)[0].shape
		assert expected_shape == obtained_shape

		def test_get_layer_variable_values_eager(self):
		"""Tests to get variable values associated with a layer in eager mode"""

		with context.eager_mode():
		# Test for correct value return (eager mode)
		tg = dc.models.TensorGraph()
		var = Variable([10.0, 12.0])
		tg.add_output(var)
		tg.build()
		expected = [10.0, 12.0]
		obtained = tg.get_layer_variable_values(var)[0]
		np.testing.assert_array_almost_equal(expected, obtained)
		np.testing.assert_array_equal(expected, obtained)

		# Test for shape (eager mode)
		tg = dc.models.TensorGraph()
		input_tensor = Input(shape=(10, 100))
		output = Dense(out_channels=20, in_layers=[input_tensor])
		tg.add_output(output)
		tg.build()
		expected_shape = (100, 20)
		obtained_shape = tg.get_layer_variable_values(output)[0].shape
		assert expected_shape == obtained_shape