[quant][fx] Remove is_output_quantized from QuantizeHandler #74843
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Summary: is_output_quantized is used to check if we should quantize the op based on the dtype configuration in qconfig and what is supported by the backend, we'll skip inserting observer if the dtype configuration is not supported by the backend, this is now supported by backend_config_dict, and we can remove this function now. Also we previously supported fp16 static quantization for some ops for one of our internal use case, and now it is not required, so we can remove them Test Plan: python test/test_quantization.py TestQuantizeFx python test/test_quantization.py TestQuantizeFxOps Reviewers: Subscribers: Tasks: Tags: [ghstack-poisoned]
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jerryzh168
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Mar 28, 2022
Summary: is_output_quantized is used to check if we should quantize the op based on the dtype configuration in qconfig and what is supported by the backend, we'll skip inserting observer if the dtype configuration is not supported by the backend, this is now supported by backend_config_dict, and we can remove this function now. Also we previously supported fp16 static quantization for some ops for one of our internal use case, and now it is not required, so we can remove them Test Plan: python test/test_quantization.py TestQuantizeFx python test/test_quantization.py TestQuantizeFxOps Reviewers: Subscribers: Tasks: Tags: ghstack-source-id: 2d9ac63 Pull Request resolved: #74843
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@jerryzh168 has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
andrewor14
approved these changes
Mar 28, 2022
Summary: is_output_quantized is used to check if we should quantize the op based on the dtype configuration in qconfig and what is supported by the backend, we'll skip inserting observer if the dtype configuration is not supported by the backend, this is now supported by backend_config_dict, and we can remove this function now. Also we previously supported fp16 static quantization for some ops for one of our internal use case, and now it is not required, so we can remove them Test Plan: python test/test_quantization.py TestQuantizeFx python test/test_quantization.py TestQuantizeFxOps Reviewers: Subscribers: Tasks: Tags: Differential Revision: [D35190541](https://our.internmc.facebook.com/intern/diff/D35190541) [ghstack-poisoned]
Summary: is_output_quantized is used to check if we should quantize the op based on the dtype configuration in qconfig and what is supported by the backend, we'll skip inserting observer if the dtype configuration is not supported by the backend, this is now supported by backend_config_dict, and we can remove this function now. Also we previously supported fp16 static quantization for some ops for one of our internal use case, and now it is not required, so we can remove them Test Plan: python test/test_quantization.py TestQuantizeFx python test/test_quantization.py TestQuantizeFxOps Reviewers: Subscribers: Tasks: Tags: Differential Revision: [D35190541](https://our.internmc.facebook.com/intern/diff/D35190541) [ghstack-poisoned]
jerryzh168
added a commit
that referenced
this pull request
Mar 28, 2022
Summary: is_output_quantized is used to check if we should quantize the op based on the dtype configuration in qconfig and what is supported by the backend, we'll skip inserting observer if the dtype configuration is not supported by the backend, this is now supported by backend_config_dict, and we can remove this function now. Also we previously supported fp16 static quantization for some ops for one of our internal use case, and now it is not required, so we can remove them Test Plan: python test/test_quantization.py TestQuantizeFx python test/test_quantization.py TestQuantizeFxOps Reviewers: Subscribers: Tasks: Tags: ghstack-source-id: e584d83 Pull Request resolved: #74843
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@jerryzh168 has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
This was referenced Mar 29, 2022
Summary: is_output_quantized is used to check if we should quantize the op based on the dtype configuration in qconfig and what is supported by the backend, we'll skip inserting observer if the dtype configuration is not supported by the backend, this is now supported by backend_config_dict, and we can remove this function now. Also we previously supported fp16 static quantization for some ops for one of our internal use case, and now it is not required, so we can remove them Test Plan: python test/test_quantization.py TestQuantizeFx python test/test_quantization.py TestQuantizeFxOps Reviewers: Subscribers: Tasks: Tags: Differential Revision: [D35190541](https://our.internmc.facebook.com/intern/diff/D35190541) [ghstack-poisoned]
Summary: is_output_quantized is used to check if we should quantize the op based on the dtype configuration in qconfig and what is supported by the backend, we'll skip inserting observer if the dtype configuration is not supported by the backend, this is now supported by backend_config_dict, and we can remove this function now. Also we previously supported fp16 static quantization for some ops for one of our internal use case, and now it is not required, so we can remove them Test Plan: python test/test_quantization.py TestQuantizeFx python test/test_quantization.py TestQuantizeFxOps Reviewers: Subscribers: Tasks: Tags: Differential Revision: [D35190541](https://our.internmc.facebook.com/intern/diff/D35190541) [ghstack-poisoned]
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@jerryzh168 has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
Summary: is_output_quantized is used to check if we should quantize the op based on the dtype configuration in qconfig and what is supported by the backend, we'll skip inserting observer if the dtype configuration is not supported by the backend, this is now supported by backend_config_dict, and we can remove this function now. Also we previously supported fp16 static quantization for some ops for one of our internal use case, and now it is not required, so we can remove them Test Plan: python test/test_quantization.py TestQuantizeFx python test/test_quantization.py TestQuantizeFxOps Reviewers: Subscribers: Tasks: Tags: Differential Revision: [D35190541](https://our.internmc.facebook.com/intern/diff/D35190541) [ghstack-poisoned]
Summary: is_output_quantized is used to check if we should quantize the op based on the dtype configuration in qconfig and what is supported by the backend, we'll skip inserting observer if the dtype configuration is not supported by the backend, this is now supported by backend_config_dict, and we can remove this function now. Also we previously supported fp16 static quantization for some ops for one of our internal use case, and now it is not required, so we can remove them Test Plan: python test/test_quantization.py TestQuantizeFx python test/test_quantization.py TestQuantizeFxOps Reviewers: Subscribers: Tasks: Tags: Differential Revision: [D35190541](https://our.internmc.facebook.com/intern/diff/D35190541) [ghstack-poisoned]
Summary: is_output_quantized is used to check if we should quantize the op based on the dtype configuration in qconfig and what is supported by the backend, we'll skip inserting observer if the dtype configuration is not supported by the backend, this is now supported by backend_config_dict, and we can remove this function now. Also we previously supported fp16 static quantization for some ops for one of our internal use case, and now it is not required, so we can remove them Test Plan: python test/test_quantization.py TestQuantizeFx python test/test_quantization.py TestQuantizeFxOps Reviewers: Subscribers: Tasks: Tags: Differential Revision: [D35190541](https://our.internmc.facebook.com/intern/diff/D35190541) [ghstack-poisoned]
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@jerryzh168 has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
facebook-github-bot
pushed a commit
that referenced
this pull request
Apr 2, 2022
Summary: Pull Request resolved: #74843 is_output_quantized is used to check if we should quantize the op based on the dtype configuration in qconfig and what is supported by the backend, we'll skip inserting observer if the dtype configuration is not supported by the backend, this is now supported by backend_config_dict, and we can remove this function now. Also we previously supported fp16 static quantization for some ops for one of our internal use case, and now it is not required, so we can remove them Test Plan: python test/test_quantization.py TestQuantizeFx python test/test_quantization.py TestQuantizeFxOps Imported from OSS Reviewed By: andrewor14 Differential Revision: D35190541 fbshipit-source-id: 623d961810737ec01e1f8b269ec48a6a99bb284a
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Hey @jerryzh168. |
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Stack from ghstack (oldest at bottom):
Summary:
is_output_quantized is used to check if we should quantize the op based on the dtype configuration in qconfig and what
is supported by the backend, we'll skip inserting observer if the dtype configuration is not supported by the backend,
this is now supported by backend_config_dict, and we can remove this function now.
Also we previously supported fp16 static quantization for some ops for one of our internal use case, and now it is not required, so
we can remove them
Test Plan:
python test/test_quantization.py TestQuantizeFx
python test/test_quantization.py TestQuantizeFxOps
Reviewers:
Subscribers:
Tasks:
Tags:
Differential Revision: D35190541