parameters: (dtype, shape, name=None)
return_statement: return gen_tpu_ops.infeed_dequeue(dtype, shape, name=name)
docstring: A placeholder op for a value that will be fed into the computation.
  
    Args:
      dtype: A `tf.DType`. The type of elements in the tensor.
      shape: A `tf.TensorShape` or list of `ints`. The shape of the tensor.
      name: A name for the operation (optional).
  
    Returns:
      A `Tensor` of type `dtype`.
      A tensor that will be provided using the infeed mechanism.
  
    Raises:
      TypeError: If 'dtype` is not a supported infeed type.
docstring_summary: A placeholder op for a value that will be fed into the computation.
docstring_tokens: A placeholder op for a value that will be fed into the computation .
function: def infeed_dequeue(dtype, shape, name=None):
    """A placeholder op for a value that will be fed into the computation.
  
    Args:
      dtype: A `tf.DType`. The type of elements in the tensor.
      shape: A `tf.TensorShape` or list of `ints`. The shape of the tensor.
      name: A name for the operation (optional).
  
    Returns:
      A `Tensor` of type `dtype`.
      A tensor that will be provided using the infeed mechanism.
  
    Raises:
      TypeError: If 'dtype` is not a supported infeed type.
    """
    if dtype not in _SUPPORTED_INFEED_DTYPES:
      raise TypeError(
          "Operation '{}' has type {} which is not a supported TPU infeed type. "
          "Supported types are: {}".format(name, dtype,
                                           list(_SUPPORTED_INFEED_DTYPES)))
  
    return gen_tpu_ops.infeed_dequeue(dtype, shape, name=name)
function_tokens: def infeed_dequeue ( dtype , shape , name = None ) : if dtype not in _SUPPORTED_INFEED_DTYPES : raise TypeError ( "Operation '{}' has type {} which is not a supported TPU infeed type. " "Supported types are: {}" . format ( name , dtype , list ( _SUPPORTED_INFEED_DTYPES ) ) ) return gen_tpu_ops . infeed_dequeue ( dtype , shape , name = name )