Add support for multicoil autodiff in absence of Smaps #175
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alineyyy
reviewed
Aug 5, 2024
| @@ -43,11 +43,11 @@ def backward(ctx, dy): | |||
| for size in im_size | |||
| ] | |||
| grid_r = torch.meshgrid(*r, indexing="ij") | |||
| grid_r = torch.stack(grid_r, dim=0).type_as(x)[None, ...] | |||
| grid_r = torch.stack(grid_r, dim=0).type_as(x)[:, None] | |||
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That's really efficient in multiplying each coil with the grid! ( I thought we need to use some for loop before...
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Haha, always use vectors :P
alineyyy
reviewed
Aug 5, 2024
| ).reshape(img_data.shape) | ||
| adj_data_ndft = torch.matmul( | ||
| ndft_matrix(operator).conj().T, ksp_data.T | ||
| ).T.reshape(img_data.shape) |
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To be honest, I am a little bit confused why @ has been replaced by the torch.matmul... Does torch.matmul cost less time or memory?
alineyyy
approved these changes
Aug 5, 2024
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In the past we didnt work on this as we didnt anticipate it to be useful. But @alineyyy needs it so worked on it now.
Adding @alineyyy for review and comments.