Migrate thnn_conv2d from THC to ATen #63428
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💊 CI failures summary and remediationsAs of commit d525b31 (more details on the Dr. CI page):
🕵️ 3 new failures recognized by patternsThe following CI failures do not appear to be due to upstream breakages:
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This was referenced Aug 18, 2021
peterbell10
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ngimel
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Aug 19, 2021
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| // Allow for empty batch size but not other dimensions | ||
| const bool valid_empty = c10::multiply_integers(in_sizes.slice(1)) != 0; |
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This is not right if ndim is 3 (the you need in_sizes.numel() > 0)? Btw, do we still allow 3d inputs, or is this code path never exercised?
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You're right, _convolution enforce the shape check before this is ever called. Should I just remove all the dim=3 handling code?
| if (weight.defined()) { | ||
| const auto w_sizes = weight.sizes(); | ||
| int64_t nInputPlane = w_sizes[1]; | ||
| if (w_sizes.size() == 2) { |
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can this happen? I though weight shape is checked to have 4 dims before dispatching to slow conv?
| int64_t k_ = 1; | ||
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| // Do GEMM (note: this is a bit confusing because gemm assumes column-major matrices) | ||
| if (bias.defined()) { |
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is it just expanding bias to output size? Should we be able to do the same with .expand() and output_n.copy_, without gemm call and ones?
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Is it alright if I leave algorithmic changes to a follow-up PR?
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sure! Then I only have questions about 3d inputs and 2d weights.
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| // Do Bias: | ||
| if (grad_bias.defined()) { |
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This also should be doable by just a sum call with appropriate dimensions?
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Stack from ghstack:
Closes gh-24644, closes gh-24645
Differential Revision: D30441307