Arm backend: Add 16A8W support and test for cat operation#13800
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facebook-github-bot merged 8 commits intogh/Ninja91/13/basefrom Sep 11, 2025
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Arm backend: Add 16A8W support and test for cat operation#13800facebook-github-bot merged 8 commits intogh/Ninja91/13/basefrom
facebook-github-bot merged 8 commits intogh/Ninja91/13/basefrom
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Add 16A8W quantization support and test for the cat operation in ExecutorTorch ARM backend. This follows the pattern established for linear, mul, sigmoid, tanh, slice, and view/transpose operations, extending int16 support to cat operations. Changes: - Add test_cat_tensor_16a8w_tosa_INT test function - Enable test_cat.py in test targets configuration The 16A8W configuration uses 16-bit activations with 8-bit weights, enabling higher precision for activations while maintaining weight efficiency. Differential Revision: [D80511455](https://our.internmc.facebook.com/intern/diff/D80511455/) [ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/13800
Note: Links to docs will display an error until the docs builds have been completed. ❌ 4 New Failures, 7 Unrelated FailuresAs of commit 6df79e2 with merge base 1d37845 ( NEW FAILURES - The following jobs have failed:
BROKEN TRUNK - The following jobs failed but were present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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Add 16A8W quantization support and test for the cat operation in ExecutorTorch ARM backend. This follows the pattern established for linear, mul, sigmoid, tanh, slice, and view/transpose operations, extending int16 support to cat operations. Changes: - Add test_cat_tensor_16a8w_tosa_INT test function - Enable test_cat.py in test targets configuration The 16A8W configuration uses 16-bit activations with 8-bit weights, enabling higher precision for activations while maintaining weight efficiency. Differential Revision: [D80511455](https://our.internmc.facebook.com/intern/diff/D80511455/) cc digantdesai freddan80 per zingo oscarandersson8218 [ghstack-poisoned]
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This pull request was exported from Phabricator. Differential Revision: D80511455 |
Add 16A8W quantization support and test for the cat operation in ExecutorTorch ARM backend. This follows the pattern established for linear, mul, sigmoid, tanh, slice, and view/transpose operations, extending int16 support to cat operations. Changes: - Add test_cat_tensor_16a8w_tosa_INT test function - Enable test_cat.py in test targets configuration The 16A8W configuration uses 16-bit activations with 8-bit weights, enabling higher precision for activations while maintaining weight efficiency. Differential Revision: [D80511455](https://our.internmc.facebook.com/intern/diff/D80511455/) cc digantdesai freddan80 per zingo oscarandersson8218 [ghstack-poisoned]
Contributor
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This pull request was exported from Phabricator. Differential Revision: D80511455 |
Add 16A8W quantization support and test for the cat operation in ExecutorTorch ARM backend. This follows the pattern established for linear, mul, sigmoid, tanh, slice, and view/transpose operations, extending int16 support to cat operations. Changes: - Add test_cat_tensor_16a8w_tosa_INT test function - Enable test_cat.py in test targets configuration The 16A8W configuration uses 16-bit activations with 8-bit weights, enabling higher precision for activations while maintaining weight efficiency. Differential Revision: [D80511455](https://our.internmc.facebook.com/intern/diff/D80511455/) cc digantdesai freddan80 per zingo oscarandersson8218 [ghstack-poisoned]
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This pull request was exported from Phabricator. Differential Revision: D80511455 |
Add 16A8W quantization support and test for the cat operation in ExecutorTorch ARM backend. This follows the pattern established for linear, mul, sigmoid, tanh, slice, and view/transpose operations, extending int16 support to cat operations. Changes: - Add test_cat_tensor_16a8w_tosa_INT test function - Enable test_cat.py in test targets configuration The 16A8W configuration uses 16-bit activations with 8-bit weights, enabling higher precision for activations while maintaining weight efficiency. Differential Revision: [D80511455](https://our.internmc.facebook.com/intern/diff/D80511455/) cc digantdesai freddan80 per zingo oscarandersson8218 [ghstack-poisoned]
Contributor
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This pull request was exported from Phabricator. Differential Revision: D80511455 |
Add 16A8W quantization support and test for the cat operation in ExecutorTorch ARM backend. This follows the pattern established for linear, mul, sigmoid, tanh, slice, and view/transpose operations, extending int16 support to cat operations. Changes: - Add test_cat_tensor_16a8w_tosa_INT test function - Enable test_cat.py in test targets configuration The 16A8W configuration uses 16-bit activations with 8-bit weights, enabling higher precision for activations while maintaining weight efficiency. Differential Revision: [D80511455](https://our.internmc.facebook.com/intern/diff/D80511455/) cc digantdesai freddan80 per zingo oscarandersson8218 [ghstack-poisoned]
Contributor
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This pull request was exported from Phabricator. Differential Revision: D80511455 |
Add 16A8W quantization support and test for the cat operation in ExecutorTorch ARM backend. This follows the pattern established for linear, mul, sigmoid, tanh, slice, and view/transpose operations, extending int16 support to cat operations. Changes: - Add test_cat_tensor_16a8w_tosa_INT test function - Enable test_cat.py in test targets configuration The 16A8W configuration uses 16-bit activations with 8-bit weights, enabling higher precision for activations while maintaining weight efficiency. Differential Revision: [D80511455](https://our.internmc.facebook.com/intern/diff/D80511455/) cc digantdesai freddan80 per zingo oscarandersson8218 [ghstack-poisoned]
Contributor
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This pull request was exported from Phabricator. Differential Revision: D80511455 |
Add 16A8W quantization support and test for the cat operation in ExecutorTorch ARM backend. This follows the pattern established for linear, mul, sigmoid, tanh, slice, and view/transpose operations, extending int16 support to cat operations. Changes: - Add test_cat_tensor_16a8w_tosa_INT test function - Enable test_cat.py in test targets configuration The 16A8W configuration uses 16-bit activations with 8-bit weights, enabling higher precision for activations while maintaining weight efficiency. Differential Revision: [D80511455](https://our.internmc.facebook.com/intern/diff/D80511455/) cc digantdesai freddan80 per zingo oscarandersson8218 [ghstack-poisoned]
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This pull request was exported from Phabricator. Differential Revision: D80511455 |
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This PR was created by the merge bot to help merge the original PR into the main branch. ghstack PR number: #13800 by @Ninja91 ^ Please use this as the source of truth for the PR details, comments, and reviews ghstack PR base: https://github.com/pytorch/executorch/tree/gh/Ninja91/13/base ghstack PR head: https://github.com/pytorch/executorch/tree/gh/Ninja91/13/head Merge bot PR base: https://github.com/pytorch/executorch/tree/gh/Ninja91/12/orig Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/Ninja91/13/orig @diff-train-skip-merge --------- Co-authored-by: Nitin Jain <jainnitin@meta.com>
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) This PR was created by the merge bot to help merge the original PR into the main branch. ghstack PR number: pytorch#13800 by @Ninja91 ^ Please use this as the source of truth for the PR details, comments, and reviews ghstack PR base: https://github.com/pytorch/executorch/tree/gh/Ninja91/13/base ghstack PR head: https://github.com/pytorch/executorch/tree/gh/Ninja91/13/head Merge bot PR base: https://github.com/pytorch/executorch/tree/gh/Ninja91/12/orig Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/Ninja91/13/orig @diff-train-skip-merge --------- Co-authored-by: Nitin Jain <jainnitin@meta.com>
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Stack from ghstack (oldest at bottom):
Add 16A8W quantization support and test for the cat operation in ExecutorTorch ARM backend.
This follows the pattern established for linear, mul, sigmoid, tanh, slice, and view/transpose operations, extending int16 support to cat operations.
Changes:
The 16A8W configuration uses 16-bit activations with 8-bit weights, enabling higher precision for activations while maintaining weight efficiency.
Differential Revision: D80511455
cc @digantdesai @freddan80 @per @zingo @oscarandersson8218