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uint8 , and numpy.bool . Warning. Writing to a tensor created from a read-only NumPy array is not supported and will result in undefined behavior.


If data is a NumPy array (an ndarray) with the same dtype and device then a ...


Converts obj to a tensor. obj can be one of: a tensor. a NumPy array. a DLPack capsule. an object that implements Python's buffer protocol. a scalar.


Unlike NumPy's flatten, which always copies input's data, this function may return the original object, a view, or copy. If no dimensions are flattened, ...


By default, NaN s are replaced with zero, positive infinity is replaced with the greatest finite value representable by input 's dtype, and negative infinity is ...


This function is based on NumPy's numpy.array_split() . Parameters. input (Tensor) – the tensor to split. indices_or_sections (Tensor, int or list or tuple ...


meshgrid(*tensors) currently has the same behavior as calling numpy.meshgrid(*arrays, indexing='ij') . In the future torch.meshgrid will transition to indexing= ...


Returns a tensor with the same data and number of elements as input , but with the specified shape.


threshold – Total number of array elements which trigger summarization rather than full repr (default = 1000).


Applies the Softmax function to an n-dimensional input Tensor rescaling them so that the elements of the n-dimensional output Tensor lie in the range [0,1] and ...

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