tf.experimental.numpy.ndarray

Equivalent of numpy.ndarray backed by TensorFlow tensors.

tf.experimental.numpy.ndarray(
    shape, dtype=float, buffer=None
)

This does not support all features of NumPy ndarrays e.g. strides and memory order since, unlike NumPy, the backing storage is not a raw memory buffer.

or if there are any differences in behavior.

Args
shape	The shape of the array. Must be a scalar, an iterable of integers or a TensorShape object.
dtype	Optional. The dtype of the array. Must be a python type, a numpy type or a tensorflow DType object.
buffer	Optional. The backing buffer of the array. Must have shape shape. Must be a ndarray, np.ndarray or a Tensor.

Raises
ValueError	If buffer is specified and its shape does not match shape.

Attributes
T
data	Tensor object containing the array data. This has a few key differences from the Python buffer object used in NumPy arrays. Tensors are immutable. So operations requiring in-place edit, e.g. setitem, are performed by replacing the underlying buffer with a new one. Tensors do not provide access to their raw buffer.
dtype
ndim
shape	Returns a tuple or tf.Tensor of array dimensions.
size	Returns the number of elements in the array.

Methods

astype

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astype(
    dtype
)

clip

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clip(
    a, a_min, a_max
)

TensorFlow variant of NumPy's clip.

Unsupported arguments: out, kwargs.

See the NumPy documentation for numpy.clip.

from_tensor

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@classmethod
from_tensor(
    tensor
)

ravel

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ravel(
    a
)

TensorFlow variant of NumPy's ravel.

Unsupported arguments: order.

See the NumPy documentation for numpy.ravel.

reshape

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reshape(
    a, *newshape, **kwargs
)

tolist

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tolist()

transpose

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transpose(
    a, axes=None
)

TensorFlow variant of NumPy's transpose.

See the NumPy documentation for numpy.transpose.

__abs__

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__abs__(
    x
)

TensorFlow variant of NumPy's absolute.

Unsupported arguments: out, where, casting, order, dtype, subok, signature, extobj.

See the NumPy documentation for numpy.absolute.

__add__

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__add__(
    a, b
)

__bool__

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__bool__()

__eq__

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__eq__(
    a, b
)

__floordiv__

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__floordiv__(
    a, b
)

__ge__

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__ge__(
    a, b
)

__getitem__

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__getitem__(
    slice_spec
)

Implementation of ndarray.getitem.

__gt__

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__gt__(
    a, b
)

__invert__

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__invert__(
    x
)

TensorFlow variant of NumPy's logical_not.

Unsupported arguments: out, where, casting, order, dtype, subok, signature, extobj.

See the NumPy documentation for numpy.logical_not.

__iter__

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__iter__()

__le__

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__le__(
    a, b
)

__len__

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__len__()

__lt__

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__lt__(
    a, b
)

__matmul__

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__matmul__(
    a, b
)

__mod__

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__mod__(
    a, b
)

__mul__

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__mul__(
    a, b
)

__ne__

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__ne__(
    a, b
)

__neg__

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__neg__()

__nonzero__

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__nonzero__()

__pos__

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__pos__()

__pow__

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__pow__(
    a, b
)

__radd__

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__radd__(
    a, b
)

__rfloordiv__

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__rfloordiv__(
    a, b
)

__rmatmul__

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__rmatmul__(
    a, b
)

__rmod__

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__rmod__(
    a, b
)

__rmul__

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__rmul__(
    a, b
)

__rpow__

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__rpow__(
    a, b
)

__rsub__

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__rsub__(
    a, b
)

__rtruediv__

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__rtruediv__(
    a, b
)

__sub__

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__sub__(
    a, b
)

__truediv__

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__truediv__(
    a, b
)