Class TensorSpec

tensorpack/compat/tensor_spec.py:18–106

Describes a tf.Tensor. Metadata for describing the `tf.Tensor` objects accepted or returned by some TensorFlow APIs.

class TensorSpec(object):
  """Describes a tf.Tensor.

  Metadata for describing the `tf.Tensor` objects accepted or returned
  by some TensorFlow APIs.
  """

  __slots__ = ["_shape", "_shape_tuple", "_dtype", "_name"]

  def __init__(self, shape, dtype=dtypes.float32, name=None):
    """Creates a TensorSpec.

    Args:
      shape: Value convertible to `tf.TensorShape`. The shape of the tensor.
      dtype: Value convertible to `tf.DType`. The type of the tensor values.
      name: Optional name for the Tensor.

    Raises:
      TypeError: If shape is not convertible to a `tf.TensorShape`, or dtype is
        not convertible to a `tf.DType`.
    """
    self._shape = tensor_shape.TensorShape(shape)
    try:
      self._shape_tuple = tuple(self.shape.as_list())
    except ValueError:
      self._shape_tuple = None
    self._dtype = dtypes.as_dtype(dtype)
    self._name = name

  @classmethod
  def from_spec(cls, spec, name=None):
    return cls(spec.shape, spec.dtype, name or spec.name)

  @classmethod
  def from_tensor(cls, tensor, name=None):
    if isinstance(tensor, ops.EagerTensor):
      return TensorSpec(tensor.shape, tensor.dtype, name)
    elif isinstance(tensor, ops.Tensor):
      return TensorSpec(tensor.shape, tensor.dtype, name or tensor.op.name)
    else:
      raise ValueError("`tensor` should be a tf.Tensor")

  @property
  def shape(self):
    """Returns the `TensorShape` that represents the shape of the tensor."""
    return self._shape

  @property
  def dtype(self):
    """Returns the `dtype` of elements in the tensor."""
    return self._dtype

  @property
  def name(self):
    """Returns the (optionally provided) name of the described tensor."""
    return self._name

  def is_compatible_with(self, spec_or_tensor):