Python tensorflow.contrib.layers.python.layers.utils.get_variable_collections() Examples

The following are 6 code examples of tensorflow.contrib.layers.python.layers.utils.get_variable_collections(). 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.contrib.layers.python.layers.utils , or try the search function .
Example #1
Source File: layers.py    From lambda-packs with MIT License 5 votes vote down vote up 
def _add_variable_to_collections(variable, collections_set, collections_name):
  """Adds variable (or all its parts) to all collections with that name."""
  collections = utils.get_variable_collections(
      collections_set, collections_name) or []
  variables_list = [variable]
  if isinstance(variable, tf_variables.PartitionedVariable):
    variables_list = [v for v in variable]
  for collection in collections:
    for var in variables_list:
      if var not in ops.get_collection(collection):
        ops.add_to_collection(collection, var)
Example #2
Source File: layers.py    From auto-alt-text-lambda-api with MIT License 5 votes vote down vote up 
def _add_variable_to_collections(variable, collections_set, collections_name):
  """Adds variable (or all its parts) to all collections with that name."""
  collections = utils.get_variable_collections(
      collections_set, collections_name) or []
  variables_list = [variable]
  if isinstance(variable, tf_variables.PartitionedVariable):
    variables_list = [v for v in variable]
  for collection in collections:
    for var in variables_list:
      if var not in ops.get_collection(collection):
        ops.add_to_collection(collection, var)
Example #3
Source File: preact_conv.py    From tensorflow-litterbox with Apache License 2.0 5 votes vote down vote up 
def preact_conv2d(
        inputs,
        num_outputs,
        kernel_size,
        stride=1,
        padding='SAME',
        activation_fn=nn.relu,
        normalizer_fn=None,
        normalizer_params=None,
        weights_initializer=initializers.xavier_initializer(),
        weights_regularizer=None,
        reuse=None,
        variables_collections=None,
        outputs_collections=None,
        trainable=True,
        scope=None):
    """Adds a 2D convolution preceded by batch normalization and activation.
    """
    with variable_scope.variable_scope(scope, 'Conv', values=[inputs], reuse=reuse) as sc:
        inputs = ops.convert_to_tensor(inputs)
        dtype = inputs.dtype.base_dtype
        if normalizer_fn:
            normalizer_params = normalizer_params or {}
            inputs = normalizer_fn(inputs, activation_fn=activation_fn, **normalizer_params)
        kernel_h, kernel_w = utils.two_element_tuple(kernel_size)
        stride_h, stride_w = utils.two_element_tuple(stride)
        num_filters_in = utils.last_dimension(inputs.get_shape(), min_rank=4)
        weights_shape = [kernel_h, kernel_w, num_filters_in, num_outputs]
        weights_collections = utils.get_variable_collections(variables_collections, 'weights')
        weights = variables.model_variable('weights',
                                           shape=weights_shape,
                                           dtype=dtype,
                                           initializer=weights_initializer,
                                           regularizer=weights_regularizer,
                                           collections=weights_collections,
                                           trainable=trainable)
        outputs = nn.conv2d(inputs, weights, [1, stride_h, stride_w, 1], padding=padding)
        return utils.collect_named_outputs(outputs_collections, sc.name, outputs)
Example #4
Source File: convolution.py    From tf-imagenet with Apache License 2.0 5 votes vote down vote up 
def _add_variable_to_collections(variable, collections_set, collections_name):
    """Adds variable (or all its parts) to all collections with that name."""
    collections = utils.get_variable_collections(
            collections_set, collections_name) or []
    variables_list = [variable]
    if isinstance(variable, tf_variables.PartitionedVariable):
        variables_list = [v for v in variable]
    for collection in collections:
        for var in variables_list:
            if var not in ops.get_collection(collection):
                ops.add_to_collection(collection, var)
Example #5
Source File: mmnet_utils.py    From MMNet with Apache License 2.0 5 votes vote down vote up 
def _add_variable_to_collections(variable, collections_set, collections_name):
    """Adds variable (or all its parts) to all collections with that name."""
    collections = utils.get_variable_collections(collections_set,
                                                 collections_name) or []
    variables_list = [variable]
    if isinstance(variable, tf_variables.PartitionedVariable):
        variables_list = [v for v in variable]
    for collection in collections:
        for var in variables_list:
            if var not in ops.get_collection(collection):
                ops.add_to_collection(collection, var)
Example #6
Source File: layers.py    From keras-lambda with MIT License 5 votes vote down vote up 
def _add_variable_to_collections(variable, collections_set, collections_name):
  """Adds variable (or all its parts) to all collections with that name."""
  collections = utils.get_variable_collections(
      collections_set, collections_name) or []
  variables_list = [variable]
  if isinstance(variable, tf_variables.PartitionedVariable):
    variables_list = [v for v in variable]
  for collection in collections:
    for var in variables_list:
      if var not in ops.get_collection(collection):
        ops.add_to_collection(collection, var)