Add transfer shaders for buffer storage tensors #3684
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/3684
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit f4a3a6a with merge base ce751fc ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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Summary: ## Context Add transfer shaders for tensors that use buffer storage, in preparation for quantization support. Differential Revision: D57577019
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This pull request was exported from Phabricator. Differential Revision: D57577019 |
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Summary: ## Context Add transfer shaders for tensors that use buffer storage, in preparation for quantization support. Differential Revision: D57577019
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This pull request was exported from Phabricator. Differential Revision: D57577019 |
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Summary: ## Context Add transfer shaders for tensors that use buffer storage, in preparation for quantization support. Differential Revision: D57577019
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This pull request was exported from Phabricator. Differential Revision: D57577019 |
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Summary: ## Context Add transfer shaders for tensors that use buffer storage, in preparation for quantization support. Differential Revision: D57577019
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This pull request was exported from Phabricator. Differential Revision: D57577019 |
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This pull request was exported from Phabricator. Differential Revision: D57577019 |
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May 21, 2024
Summary: Pull Request resolved: pytorch#3684 ## Context Add support for tensors that use buffer storage, in preparation for quantization support. For more context, the initial versions of quantized operators will target buffer based tensors. This is because the primary use-case is LLMs, which may contain tensors that may exceed the texture limits. Differential Revision: D57577019
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This pull request was exported from Phabricator. Differential Revision: D57577019 |
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May 22, 2024
Summary: Pull Request resolved: pytorch#3684 ## Context Add support for tensors that use buffer storage, in preparation for quantization support. For more context, the initial versions of quantized operators will target buffer based tensors. This is because the primary use-case is LLMs, which may contain tensors that may exceed the texture limits. Differential Revision: D57577019
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This pull request was exported from Phabricator. Differential Revision: D57577019 |
SS-JIA
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May 22, 2024
Summary: Pull Request resolved: pytorch#3684 ## Context Add support for tensors that use buffer storage, in preparation for quantization support. For more context, the initial versions of quantized operators will target buffer based tensors. This is because the primary use-case is LLMs, which may contain tensors that may exceed the texture limits. Differential Revision: D57577019
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This pull request was exported from Phabricator. Differential Revision: D57577019 |
SS-JIA
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May 22, 2024
Summary: Pull Request resolved: pytorch#3684 ## Context Add support for tensors that use buffer storage, in preparation for quantization support. For more context, the initial versions of quantized operators will target buffer based tensors. This is because the primary use-case is LLMs, which may contain tensors that may exceed the texture limits. Differential Revision: D57577019
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This pull request was exported from Phabricator. Differential Revision: D57577019 |
SS-JIA
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May 22, 2024
Summary: Pull Request resolved: pytorch#3684 ## Context Add support for tensors that use buffer storage, in preparation for quantization support. For more context, the initial versions of quantized operators will target buffer based tensors. This is because the primary use-case is LLMs, which may contain tensors that may exceed the texture limits. Differential Revision: D57577019
yipjustin
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May 22, 2024
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This pull request was exported from Phabricator. Differential Revision: D57577019 |
SS-JIA
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Summary: Pull Request resolved: pytorch#3684 ## Context Add support for tensors that use buffer storage, in preparation for quantization support. For more context, the initial versions of quantized operators will target buffer based tensors. This is because the primary use-case is LLMs, which may contain tensors that may exceed the texture limits. Differential Revision: D57577019
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This pull request was exported from Phabricator. Differential Revision: D57577019 |
SS-JIA
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May 22, 2024
Summary: Pull Request resolved: pytorch#3684 ## Context Add support for tensors that use buffer storage, in preparation for quantization support. For more context, the initial versions of quantized operators will target buffer based tensors. This is because the primary use-case is LLMs, which may contain tensors that may exceed the texture limits. Reviewed By: yipjustin Differential Revision: D57577019
Summary: Pull Request resolved: pytorch#3684 ## Context Add support for tensors that use buffer storage, in preparation for quantization support. For more context, the initial versions of quantized operators will target buffer based tensors. This is because the primary use-case is LLMs, which may contain tensors that may exceed the texture limits. Reviewed By: yipjustin Differential Revision: D57577019
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This pull request was exported from Phabricator. Differential Revision: D57577019 |
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This pull request has been merged in 2d48cdc. |
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Summary:
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Add transfer shaders for tensors that use buffer storage, in preparation for quantization support.
Differential Revision: D57577019