Python tensorflow.python.pywrap_tensorflow.EqualGraphDefWrapper() Examples

The following are 5 code examples of tensorflow.python.pywrap_tensorflow.EqualGraphDefWrapper(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module tensorflow.python.pywrap_tensorflow , or try the search function .
Example #1
Source File: test_util.py    From deep_image_model with Apache License 2.0 6 votes vote down vote up 
def assert_equal_graph_def(actual, expected):
  """Asserts that two `GraphDef`s are (mostly) the same.

  Compares two `GraphDef` protos for equality, ignoring versions and ordering of
  nodes, attrs, and control inputs.  Node names are used to match up nodes
  between the graphs, so the naming of nodes must be consistent.

  Args:
    actual: The `GraphDef` we have.
    expected: The `GraphDef` we expected.

  Raises:
    AssertionError: If the `GraphDef`s do not match.
    TypeError: If either argument is not a `GraphDef`.
  """
  if not isinstance(actual, graph_pb2.GraphDef):
    raise TypeError("Expected tf.GraphDef for actual, got %s" %
                    type(actual).__name__)
  if not isinstance(expected, graph_pb2.GraphDef):
    raise TypeError("Expected tf.GraphDef for expected, got %s" %
                    type(expected).__name__)
  diff = pywrap_tensorflow.EqualGraphDefWrapper(actual.SerializeToString(),
                                                expected.SerializeToString())
  if diff:
    raise AssertionError(compat.as_str(diff))
Example #2
Source File: test_util.py    From lambda-packs with MIT License 5 votes vote down vote up 
def assert_equal_graph_def(actual, expected, checkpoint_v2=False):
  """Asserts that two `GraphDef`s are (mostly) the same.

  Compares two `GraphDef` protos for equality, ignoring versions and ordering of
  nodes, attrs, and control inputs.  Node names are used to match up nodes
  between the graphs, so the naming of nodes must be consistent.

  Args:
    actual: The `GraphDef` we have.
    expected: The `GraphDef` we expected.
    checkpoint_v2: boolean determining whether to ignore randomized attribute
        values that appear in V2 checkpoints.

  Raises:
    AssertionError: If the `GraphDef`s do not match.
    TypeError: If either argument is not a `GraphDef`.
  """
  if not isinstance(actual, graph_pb2.GraphDef):
    raise TypeError("Expected tf.GraphDef for actual, got %s" %
                    type(actual).__name__)
  if not isinstance(expected, graph_pb2.GraphDef):
    raise TypeError("Expected tf.GraphDef for expected, got %s" %
                    type(expected).__name__)

  if checkpoint_v2:
    _strip_checkpoint_v2_randomized(actual)
    _strip_checkpoint_v2_randomized(expected)

  diff = pywrap_tensorflow.EqualGraphDefWrapper(actual.SerializeToString(),
                                                expected.SerializeToString())
  if diff:
    raise AssertionError(compat.as_str(diff))
Example #3
Source File: test_util.py    From auto-alt-text-lambda-api with MIT License 5 votes vote down vote up 
def assert_equal_graph_def(actual, expected, checkpoint_v2=False):
  """Asserts that two `GraphDef`s are (mostly) the same.

  Compares two `GraphDef` protos for equality, ignoring versions and ordering of
  nodes, attrs, and control inputs.  Node names are used to match up nodes
  between the graphs, so the naming of nodes must be consistent.

  Args:
    actual: The `GraphDef` we have.
    expected: The `GraphDef` we expected.
    checkpoint_v2: boolean determining whether to ignore randomized attribute
        values that appear in V2 checkpoints.

  Raises:
    AssertionError: If the `GraphDef`s do not match.
    TypeError: If either argument is not a `GraphDef`.
  """
  if not isinstance(actual, graph_pb2.GraphDef):
    raise TypeError("Expected tf.GraphDef for actual, got %s" %
                    type(actual).__name__)
  if not isinstance(expected, graph_pb2.GraphDef):
    raise TypeError("Expected tf.GraphDef for expected, got %s" %
                    type(expected).__name__)

  if checkpoint_v2:
    _strip_checkpoint_v2_randomized(actual)
    _strip_checkpoint_v2_randomized(expected)

  diff = pywrap_tensorflow.EqualGraphDefWrapper(actual.SerializeToString(),
                                                expected.SerializeToString())
  if diff:
    raise AssertionError(compat.as_str(diff))


# Matches attributes named via _SHARDED_SUFFIX in
# tensorflow/python/training/saver.py
Example #4
Source File: test_util.py    From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License 5 votes vote down vote up 
def assert_equal_graph_def(actual, expected, checkpoint_v2=False):
  """Asserts that two `GraphDef`s are (mostly) the same.

  Compares two `GraphDef` protos for equality, ignoring versions and ordering of
  nodes, attrs, and control inputs.  Node names are used to match up nodes
  between the graphs, so the naming of nodes must be consistent.

  Args:
    actual: The `GraphDef` we have.
    expected: The `GraphDef` we expected.
    checkpoint_v2: boolean determining whether to ignore randomized attribute
        values that appear in V2 checkpoints.

  Raises:
    AssertionError: If the `GraphDef`s do not match.
    TypeError: If either argument is not a `GraphDef`.
  """
  if not isinstance(actual, graph_pb2.GraphDef):
    raise TypeError("Expected tf.GraphDef for actual, got %s" %
                    type(actual).__name__)
  if not isinstance(expected, graph_pb2.GraphDef):
    raise TypeError("Expected tf.GraphDef for expected, got %s" %
                    type(expected).__name__)

  if checkpoint_v2:
    _strip_checkpoint_v2_randomized(actual)
    _strip_checkpoint_v2_randomized(expected)

  diff = pywrap_tensorflow.EqualGraphDefWrapper(actual.SerializeToString(),
                                                expected.SerializeToString())
  if diff:
    raise AssertionError(compat.as_str(diff))
Example #5
Source File: test_util.py    From keras-lambda with MIT License 5 votes vote down vote up 
def assert_equal_graph_def(actual, expected, checkpoint_v2=False):
  """Asserts that two `GraphDef`s are (mostly) the same.

  Compares two `GraphDef` protos for equality, ignoring versions and ordering of
  nodes, attrs, and control inputs.  Node names are used to match up nodes
  between the graphs, so the naming of nodes must be consistent.

  Args:
    actual: The `GraphDef` we have.
    expected: The `GraphDef` we expected.
    checkpoint_v2: boolean determining whether to ignore randomized attribute
        values that appear in V2 checkpoints.

  Raises:
    AssertionError: If the `GraphDef`s do not match.
    TypeError: If either argument is not a `GraphDef`.
  """
  if not isinstance(actual, graph_pb2.GraphDef):
    raise TypeError("Expected tf.GraphDef for actual, got %s" %
                    type(actual).__name__)
  if not isinstance(expected, graph_pb2.GraphDef):
    raise TypeError("Expected tf.GraphDef for expected, got %s" %
                    type(expected).__name__)

  if checkpoint_v2:
    _strip_checkpoint_v2_randomized(actual)
    _strip_checkpoint_v2_randomized(expected)

  diff = pywrap_tensorflow.EqualGraphDefWrapper(actual.SerializeToString(),
                                                expected.SerializeToString())
  if diff:
    raise AssertionError(compat.as_str(diff))


# Matches attributes named via _SHARDED_SUFFIX in
# tensorflow/python/training/saver.py