[ET-VK][qconv] Fix depthwise weight_sums sum dimension#17504
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[ET-VK][qconv] Fix depthwise weight_sums sum dimension#17504meta-codesync[bot] merged 3 commits intogh/SS-JIA/432/basefrom
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The weight_sums tensor stores per-output-channel sums of quantized weight values, used to apply activation zero point correction during integer accumulation. For depthwise convolutions, the weight tensor is reshaped to (H, W, OC), but the sum was unconditionally computed along dim=1 (the W dimension). This produced a tensor of shape (H, OC) instead of (OC,), causing incorrect zero point correction and corrupted depthwise conv output. Fix by branching on is_depthwise_conv to sum over dims (0, 1) for the (H, W, OC) layout. Differential Revision: [D93511635](https://our.internmc.facebook.com/intern/diff/D93511635/) [ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/17504
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The weight_sums tensor stores per-output-channel sums of quantized weight values, used to apply activation zero point correction during integer accumulation. For depthwise convolutions, the weight tensor is reshaped to (H, W, OC), but the sum was unconditionally computed along dim=1 (the W dimension). This produced a tensor of shape (H, OC) instead of (OC,), causing incorrect zero point correction and corrupted depthwise conv output. Fix by branching on is_depthwise_conv to sum over dims (0, 1) for the (H, W, OC) layout. Differential Revision: [D93511635](https://our.internmc.facebook.com/intern/diff/D93511635/) [ghstack-poisoned]
The weight_sums tensor stores per-output-channel sums of quantized weight values, used to apply activation zero point correction during integer accumulation. For depthwise convolutions, the weight tensor is reshaped to (H, W, OC), but the sum was unconditionally computed along dim=1 (the W dimension). This produced a tensor of shape (H, OC) instead of (OC,), causing incorrect zero point correction and corrupted depthwise conv output. Fix by branching on is_depthwise_conv to sum over dims (0, 1) for the (H, W, OC) layout. Differential Revision: [D93511635](https://our.internmc.facebook.com/intern/diff/D93511635/) [ghstack-poisoned]
This was referenced Feb 19, 2026
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Pull Request resolved: #17504 The weight_sums tensor stores per-output-channel sums of quantized weight values, used to apply activation zero point correction during integer accumulation. For depthwise convolutions, the weight tensor is reshaped to (H, W, OC), but the sum was unconditionally computed along dim=1 (the W dimension). This produced a tensor of shape (H, OC) instead of (OC,), causing incorrect zero point correction and corrupted depthwise conv output. Fix by branching on is_depthwise_conv to sum over dims (0, 1) for the (H, W, OC) layout. ghstack-source-id: 342806069 @exported-using-ghexport Differential Revision: [D93511635](https://our.internmc.facebook.com/intern/diff/D93511635/)
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Stack from ghstack (oldest at bottom):
The weight_sums tensor stores per-output-channel sums of quantized weight values, used to apply activation zero point correction during integer accumulation. For depthwise convolutions, the weight tensor is reshaped to (H, W, OC), but the sum was unconditionally computed along dim=1 (the W dimension). This produced a tensor of shape (H, OC) instead of (OC,), causing incorrect zero point correction and corrupted depthwise conv output.
Fix by branching on is_depthwise_conv to sum over dims (0, 1) for the (H, W, OC) layout.
Differential Revision: D93511635