sigpy.convolve_data_adjoint¶
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sigpy.
convolve_data_adjoint
(output, filt, data_shape, mode='full', strides=None, multi_channel=False)[source]¶ Adjoint convolution operation with respect to data.
Note that the cuDNN version only supports inputs with D=1, 2 or 3.
Parameters: - output (array) – output array of shape \([..., p_1, ..., p_D]\) if multi_channel is False, \([..., c_o, p_1, ..., p_D]\) otherwise.
- filt (array) – filter array of shape \([n_1, ..., n_D]\) if multi_channel is False \([c_o, c_i, n_1, ..., n_D]\) otherwise.
- mode (str) – {‘full’, ‘valid’}.
- strides (None or tuple of ints) – convolution strides of length D.
- multi_channel (bool) – specify if input/output has multiple channels.
- multi_channel – specify if data/output has multiple channels.
- mode – {‘full’, ‘valid’}.
Returns: - data array of shape
\([..., m_1, ..., m_D]\) if multi_channel is False, \([..., c_i, m_1, ..., m_D]\) otherwise.
Return type: array