[passes] Optimize ConvertConv3dToConv2d for special case#518
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llFreetimell wants to merge 3 commits intoSamsung:mainfrom
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[passes] Optimize ConvertConv3dToConv2d for special case#518llFreetimell wants to merge 3 commits intoSamsung:mainfrom
llFreetimell wants to merge 3 commits intoSamsung:mainfrom
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This commit optimizes `ConvertConv3dToConv2d` pass for special case. TICO-DCO-1.0-Signed-off-by: Seok Namkoong <seok9311@naver.com>
dayo09
reviewed
Feb 26, 2026
| return (torch.randn(5, 3, 2, 16, 16),), {} | ||
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| class ConvertConv3dPerfectFitKernelTest(SinglePassValueTest): |
Contributor
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(optional) How about adding it to op test too? test/modules/op/conv3d.py
Contributor
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@llFreetimell style failure 😢 |
dayo09
reviewed
Feb 26, 2026
Comment on lines
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| conv2d = create_node( | ||
| graph, | ||
| torch.ops.aten.conv2d.default, | ||
| args=( | ||
| input_reshape, | ||
| weight_reshape, | ||
| bias, | ||
| [1, 1], # stride | ||
| [0, 0], # padding | ||
| [1, 1], # dilation | ||
| groups, | ||
| ), | ||
| origin=node, | ||
| ) |
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@llFreetimell We have considered Linear vs Conv2d for TRIV optimization, so, in the end, is Conv2d better?
seockho-kim
reviewed
Feb 26, 2026
| N, C_in, T_in, H_in, W_in = input_shape | ||
| C_out, C_in_weight, kT, kH, kW = weight_shape | ||
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| if T_in == kT and H_in == kH and W_in == kW and groups == 1: |
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Does this pass work when input shape(T,H,W) is same with kernel's?
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This commit optimizes
ConvertConv3dToConv2dpass for special case.TICO-DCO-1.0-Signed-off-by: Seok Namkoong seok9311@naver.com
For #475
Draft #517