Python pywrap_tensorflow.TryFindKernelClass方法代碼示例

本文整理匯總了Python中tensorflow.python.pywrap_tensorflow.TryFindKernelClass方法的典型用法代碼示例。如果您正苦於以下問題：Python pywrap_tensorflow.TryFindKernelClass方法的具體用法？Python pywrap_tensorflow.TryFindKernelClass怎麽用？Python pywrap_tensorflow.TryFindKernelClass使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類tensorflow.python.pywrap_tensorflow的用法示例。

在下文中一共展示了pywrap_tensorflow.TryFindKernelClass方法的3個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。

示例1: get_ops_and_kernels

# 需要導入模塊: from tensorflow.python import pywrap_tensorflow [as 別名]
# 或者: from tensorflow.python.pywrap_tensorflow import TryFindKernelClass [as 別名]
def get_ops_and_kernels(proto_fileformat, proto_files, default_ops_str):
  """Gets the ops and kernels needed from the model files."""
  ops = set()

  for proto_file in proto_files:
    tf_logging.info('Loading proto file %s', proto_file)
    # Load GraphDef.
    file_data = gfile.GFile(proto_file, 'rb').read()
    if proto_fileformat == 'rawproto':
      graph_def = graph_pb2.GraphDef.FromString(file_data)
    else:
      assert proto_fileformat == 'textproto'
      graph_def = text_format.Parse(file_data, graph_pb2.GraphDef())

    # Find all ops and kernels used by the graph.
    for node_def in graph_def.node:
      if not node_def.device:
        node_def.device = '/cpu:0'
      kernel_class = pywrap_tensorflow.TryFindKernelClass(
          node_def.SerializeToString())
      if kernel_class:
        op_and_kernel = (str(node_def.op), kernel_class.decode('utf-8'))
        if op_and_kernel not in ops:
          ops.add(op_and_kernel)
      else:
        print(
            'Warning: no kernel found for op %s' % node_def.op, file=sys.stderr)

  # Add default ops.
  if default_ops_str and default_ops_str != 'all':
    for s in default_ops_str.split(','):
      op, kernel = s.split(':')
      op_and_kernel = (op, kernel)
      if op_and_kernel not in ops:
        ops.add(op_and_kernel)

  return list(sorted(ops))

開發者ID:ryfeus，項目名稱:lambda-packs，代碼行數:39，代碼來源:selective_registration_header_lib.py

示例2: get_ops_and_kernels

# 需要導入模塊: from tensorflow.python import pywrap_tensorflow [as 別名]
# 或者: from tensorflow.python.pywrap_tensorflow import TryFindKernelClass [as 別名]
def get_ops_and_kernels(proto_fileformat, proto_files, default_ops_str):
  """Gets the ops and kernels needed from the model files."""
  ops = set()

  for proto_file in proto_files:
    tf_logging.info('Loading proto file %s', proto_file)
    # Load GraphDef.
    file_data = gfile.GFile(proto_file).read()
    if proto_fileformat == 'rawproto':
      graph_def = graph_pb2.GraphDef.FromString(file_data)
    else:
      assert proto_fileformat == 'textproto'
      graph_def = text_format.Parse(file_data, graph_pb2.GraphDef())

    # Find all ops and kernels used by the graph.
    for node_def in graph_def.node:
      if not node_def.device:
        node_def.device = '/cpu:0'
      kernel_class = pywrap_tensorflow.TryFindKernelClass(
          node_def.SerializeToString())
      if kernel_class:
        op_and_kernel = (str(node_def.op), kernel_class.decode('utf-8'))
        if op_and_kernel not in ops:
          ops.add(op_and_kernel)
      else:
        print(
            'Warning: no kernel found for op %s' % node_def.op, file=sys.stderr)

  # Add default ops.
  if default_ops_str != 'all':
    for s in default_ops_str.split(','):
      op, kernel = s.split(':')
      op_and_kernel = (op, kernel)
      if op_and_kernel not in ops:
        ops.add(op_and_kernel)

  return list(sorted(ops))

開發者ID:abhisuri97，項目名稱:auto-alt-text-lambda-api，代碼行數:39，代碼來源:print_selective_registration_header.py

示例3: get_ops_and_kernels

# 需要導入模塊: from tensorflow.python import pywrap_tensorflow [as 別名]
# 或者: from tensorflow.python.pywrap_tensorflow import TryFindKernelClass [as 別名]
def get_ops_and_kernels(proto_fileformat, proto_files, default_ops_str):
  """Gets the ops and kernels needed from the model files."""
  ops = set()

  for proto_file in proto_files:
    tf.logging.info('Loading proto file %s', proto_file)
    # Load GraphDef.
    file_data = tf.gfile.GFile(proto_file).read()
    if proto_fileformat == 'rawproto':
      graph_def = graph_pb2.GraphDef.FromString(file_data)
    else:
      assert proto_fileformat == 'textproto'
      graph_def = text_format.Parse(file_data, graph_pb2.GraphDef())

    # Find all ops and kernels used by the graph.
    for node_def in graph_def.node:
      if not node_def.device:
        node_def.device = '/cpu:0'
      kernel_class = pywrap_tensorflow.TryFindKernelClass(
          node_def.SerializeToString())
      if kernel_class:
        op_and_kernel = (str(node_def.op), kernel_class.decode('utf-8'))
        if op_and_kernel not in ops:
          ops.add(op_and_kernel)
      else:
        print(
            'Warning: no kernel found for op %s' % node_def.op, file=sys.stderr)

  # Add default ops.
  if default_ops_str != 'all':
    for s in default_ops_str.split(','):
      op, kernel = s.split(':')
      op_and_kernel = (op, kernel)
      if op_and_kernel not in ops:
        ops.add(op_and_kernel)

  return list(sorted(ops))

開發者ID:tobegit3hub，項目名稱:deep_image_model，代碼行數:39，代碼來源:print_selective_registration_header.py

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