# 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 array_ops
from tensorflow.python.ops import random_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("var/slot", slot.op.name)
      self.assertEqual([2], slot.get_shape().as_list())
      self.assertEqual(dtypes.float32, slot.dtype.base_dtype)
      self.assertAllEqual([1.0, 2.5], slot.eval())

  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("const/slot", slot.op.name)
      self.assertEqual([2], slot.get_shape().as_list())
      self.assertEqual(dtypes.float32, slot.dtype.base_dtype)
      self.assertAllEqual([2.0, 5.0], slot.eval())

  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("var/slot", slot.op.name)
      self.assertEqual([2], slot.get_shape().as_list())
      self.assertEqual(dtypes.float64, slot.dtype.base_dtype)
      self.assertAllEqual([0.0, 0.0], slot.eval())

  def testCreateZerosSlotFromDynamicShapedVariable(self):
    with self.test_session():
      dyn_shape = constant_op.constant([2], dtype=dtypes.int32)
      dyn_shape = array_ops.placeholder_with_default(dyn_shape,
                                                     shape=[None])
      v = variable_scope.get_variable(
          "var",
          initializer=random_ops.random_uniform(dyn_shape,
                                                dtype=dtypes.float64),
          validate_shape=False)
      with ops.control_dependencies(None):
        slot = slot_creator.create_zeros_slot(
            v, name="slot", dtype=dtypes.float64)

      variables.global_variables_initializer().run()

      self.assertEqual("var/slot", slot.op.name)
      self.assertEqual([2], array_ops.shape(slot).eval())
      self.assertEqual(dtypes.float64, slot.dtype.base_dtype)
      self.assertAllEqual([0.0, 0.0], slot.eval())

  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("const/slot", slot.op.name)
      self.assertEqual([2], slot.get_shape().as_list())
      self.assertEqual(dtypes.float32, slot.dtype.base_dtype)
      self.assertAllEqual([0.0, 0.0], slot.eval())

  def testCreateZerosSlotFromDynamicShapedTensor(self):
    with self.test_session():
      v = random_ops.random_uniform([2], dtype=dtypes.float64)
      v = array_ops.placeholder_with_default(v, shape=[None], name="const")
      with ops.control_dependencies(None):
        slot = slot_creator.create_zeros_slot(
            v, name="slot", dtype=dtypes.float64)

      variables.global_variables_initializer().run()

      self.assertEqual("const/slot", slot.op.name)
      self.assertEqual([2], array_ops.shape(slot).eval())
      self.assertEqual(dtypes.float64, slot.dtype.base_dtype)
      self.assertAllEqual([0.0, 0.0], slot.eval())

  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("scope/scope/var/slot", slot.op.name)


if __name__ == "__main__":
  test.main()
