tf.contrib.framework.BoundedTensorSpec

A TensorSpec that specifies minimum and maximum values.

Inherits From: TensorSpec

tf.contrib.framework.BoundedTensorSpec(
    shape, dtype, minimum, maximum, name=None
)

Example usage:

spec = tensor_spec.BoundedTensorSpec((1, 2, 3), tf.float32, 0, (5, 5, 5))
tf_minimum = tf.convert_to_tensor(spec.minimum, dtype=spec.dtype)
tf_maximum = tf.convert_to_tensor(spec.maximum, dtype=spec.dtype)

Bounds are meant to be inclusive. This is especially important for integer types. The following spec will be satisfied by tensors with values in the set {0, 1, 2}:

spec = tensor_spec.BoundedTensorSpec((3, 5), tf.int32, 0, 2)

Args
shape	Value convertible to tf.TensorShape. The shape of the tensor.
dtype	Value convertible to tf.DType. The type of the tensor values.
minimum	Number or sequence specifying the minimum element bounds (inclusive). Must be broadcastable to shape.
maximum	Number or sequence specifying the maximum element bounds (inclusive). Must be broadcastable to shape.
name	Optional string containing a semantic name for the corresponding array. Defaults to None.

Raises
ValueError	If minimum or maximum are not provided or not broadcastable to shape.
TypeError	If the shape is not an iterable or if the dtype is an invalid numpy dtype.

Attributes
dtype	Returns the dtype of elements in the tensor.
maximum	Returns a NumPy array specifying the maximum bounds (inclusive).
minimum	Returns a NumPy array specifying the minimum bounds (inclusive).
name	Returns the (optionally provided) name of the described tensor.
shape	Returns the TensorShape that represents the shape of the tensor.
value_type

Methods

from_spec

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@classmethod
from_spec(
    spec
)

from_tensor

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@classmethod
from_tensor(
    tensor, name=None
)

is_compatible_with

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is_compatible_with(
    spec_or_tensor
)

Returns True if spec_or_tensor is compatible with this TensorSpec.

Two tensors are considered compatible if they have the same dtype and their shapes are compatible (see tf.TensorShape.is_compatible_with).

Args
spec_or_tensor	A tf.TensorSpec or a tf.Tensor

Returns
True if spec_or_tensor is compatible with self.

most_specific_compatible_type

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most_specific_compatible_type(
    other
)

Returns the most specific TypeSpec compatible with self and other.

Args
other	A TypeSpec.

Raises
ValueError	If there is no TypeSpec that is compatible with both self and other.

__eq__

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__eq__(
    other
)

Return self==value.

__ne__

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__ne__(
    other
)

Return self!=value.