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Source code for pypose.basics.ops

import torch


[docs]def bmv(input, vec, *, out=None): r''' Performs batched matrix-vector product. Args: input (:obj:`Tensor`): matrices to be multiplied. vec (:obj:`Tensor`): vectors to be multiplied. Return: out (:obj:`Tensor`): the output tensor. Note: The ``input`` has to be a (:math:`\cdots\times n \times m`) tensor, the ``vec`` has to be a (:math:`\cdots\times m`) tensor, and ``out`` will be a (:math:`\cdots\times n`) tensor. Different from ``torch.mv``, which is not broadcast, this function is broadcast and supports batched product. Example: >>> matrix = torch.randn(2, 1, 3, 2) >>> vec = torch.randn(1, 2, 2) >>> out = pp.bmv(matrix, vec) >>> out.shape torch.Size([2, 2, 3]) ''' assert input.ndim >= 2 and vec.ndim >= 1, 'Input arguments invalid' assert input.shape[-1] == vec.shape[-1], 'matrix-vector shape invalid' return torch.matmul(input, vec.unsqueeze(-1), out=out).squeeze(-1)

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