tf_agents.specs.BoundedArraySpec

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An ArraySpec that specifies minimum and maximum values.

Inherits From: ArraySpec

tf_agents.specs.BoundedArraySpec(
    shape, dtype, minimum=None, maximum=None, name=None
)

Used in the notebooks

Used in the tutorials

Example usage:

# Specifying the same minimum and maximum for every element.
spec = BoundedArraySpec((3, 4), np.float64, minimum=0.0, maximum=1.0)

# Specifying a different minimum and maximum for each element.
spec = BoundedArraySpec(
    (2,), np.float64, minimum=[0.1, 0.2], maximum=[0.9, 0.9])

# Specifying the same minimum and a different maximum for each element.
spec = BoundedArraySpec(
    (3,), np.float64, minimum=-10.0, maximum=[4.0, 5.0, 3.0])

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

spec = BoundedArraySpec((3, 4), np.int, minimum=0, maximum=2)

shape An iterable specifying the array shape.
dtype numpy dtype or string specifying the array dtype.
minimum Number or sequence specifying the maximum 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.

ValueError If minimum or maximum are not broadcastable to shape or if the limits are outside of the range of the specified dtype.
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.
maximum Returns a NumPy array specifying the maximum bounds (inclusive).
minimum Returns a NumPy array specifying the minimum bounds (inclusive).
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 true if the given array conforms to the spec.

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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@classmethod
from_spec(
    spec, name=None
)

Construct a spec from the given spec.

__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.