tf_agents.specs.ArraySpec

Describes a numpy array or scalar shape and dtype.

tf_agents.specs.ArraySpec(
    shape, dtype, name=None
)

An ArraySpec allows an API to describe the arrays that it accepts or returns, before that array exists. The equivalent version describing a tf.Tensor is TensorSpec.

shape An iterable specifying the array shape.
dtype numpy dtype or string specifying the array dtype.
name Optional string containing a semantic name for the corresponding array. Defaults to None.

TypeError If the shape is not an iterable or if the dtype is an invalid numpy dtype.

dtype Returns a numpy dtype specifying the array dtype.
name Returns the name of the ArraySpec.
shape Returns a tuple specifying the array shape.

Methods

check_array

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check_array(
    array
)

Return whether the given NumPy array conforms to the spec.

Args
array A NumPy array or a scalar. Tuples and lists will not be converted to a NumPy array automatically; they will cause this function to return false, even if a conversion to a conforming array is trivial.

Returns
True if the array conforms to the spec, False otherwise.

from_array

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@staticmethod
from_array(
    array, name=None
)

Construct a spec from the given array or number.

from_spec

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@staticmethod
from_spec(
    spec
)

Construct a spec from the given spec.

replace

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replace(
    shape=None, dtype=None, name=None
)

__eq__

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__eq__(
    other
)

Checks if the shape and dtype of two specs are equal.

__ne__

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__ne__(
    other
)

Return self!=value.