tf.experimental.numpy.ndarray

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Equivalent of numpy.ndarray backed by TensorFlow tensors.

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.

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.

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

T

data Tensor object containing the array data.

This has a few key differences from the Python buffer object used in NumPy arrays.

  1. Tensors are immutable. So operations requiring in-place edit, e.g. setitem, are performed by replacing the underlying buffer with a new one.
  2. 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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from_tensor

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ravel

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TensorFlow variant of NumPy's ravel.

Unsupported arguments: order.

See the NumPy documentation for numpy.ravel.

reshape

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tolist

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transpose

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TensorFlow variant of NumPy's transpose.

See the NumPy documentation for numpy.transpose.

__abs__

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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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__bool__

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__eq__

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__floordiv__

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__ge__

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__getitem__

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Implementation of ndarray.getitem.

__gt__

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__invert__

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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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__le__

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__len__

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__lt__

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__matmul__

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__mod__

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__mul__

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__ne__

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__neg__

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__nonzero__

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__pos__

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__pow__

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__radd__

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__rfloordiv__

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__rmatmul__

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__rmod__

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__rmul__

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__rpow__

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__rsub__

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__rtruediv__

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__sub__

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__truediv__

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