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# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Functional test for slot_creator."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.ops import variable_scope
from tensorflow.python.ops import variables
from tensorflow.python.platform import test
from tensorflow.python.training import slot_creator
class SlotCreatorTest(test.TestCase):
def testCreateSlotFromVariable(self):
with self.test_session():
v = variables.Variable([1.0, 2.5], name="var")
slot = slot_creator.create_slot(v, v.initialized_value(), name="slot")
variables.global_variables_initializer().run()
self.assertEqual(slot.op.name, "var/slot")
self.assertEqual(slot.get_shape().as_list(), [2])
self.assertEqual(slot.dtype.base_dtype, dtypes.float32)
self.assertAllEqual(slot.eval(), [1.0, 2.5])
def testCreateSlotFromTensor(self):
with self.test_session():
v = constant_op.constant([1.0, 2.5], name="const")
slot = slot_creator.create_slot(v, v * 2, name="slot")
variables.global_variables_initializer().run()
self.assertEqual(slot.op.name, "const/slot")
self.assertEqual(slot.get_shape().as_list(), [2])
self.assertEqual(slot.dtype.base_dtype, dtypes.float32)
self.assertAllEqual(slot.eval(), [2.0, 5.0])
def testCreateZerosSlotFromVariable(self):
with self.test_session():
v = variables.Variable([1.0, 2.5], name="var")
with ops.control_dependencies(None):
slot = slot_creator.create_zeros_slot(
v, name="slot", dtype=dtypes.float64)
variables.global_variables_initializer().run()
self.assertEqual(slot.op.name, "var/slot")
self.assertEqual(slot.get_shape().as_list(), [2])
self.assertEqual(slot.dtype.base_dtype, dtypes.float64)
self.assertAllEqual(slot.eval(), [0.0, 0.0])
def testCreateZerosSlotFromTensor(self):
with self.test_session():
v = constant_op.constant([1.0, 2.5], name="const")
with ops.control_dependencies(None):
slot = slot_creator.create_zeros_slot(v, name="slot")
variables.global_variables_initializer().run()
self.assertEqual(slot.op.name, "const/slot")
self.assertEqual(slot.get_shape().as_list(), [2])
self.assertEqual(slot.dtype.base_dtype, dtypes.float32)
self.assertAllEqual(slot.eval(), [0.0, 0.0])
def testCreateSlotFromVariableRespectsScope(self):
# See discussion on #2740.
with self.test_session():
with variable_scope.variable_scope("scope"):
v = variables.Variable([1.0, 2.5], name="var")
slot = slot_creator.create_slot(v, v.initialized_value(), name="slot")
self.assertEqual(slot.op.name, "scope/scope/var/slot")
if __name__ == "__main__":
test.main()