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Adding tests for save/load support #16
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Summary: we are able to save a model quantized with a tensor subclass, save the state dict, then later, load model as meta tensor (i.e. only load tensor metadata not actually parameters) apply quantization api, and then load the quantized model state dict. We change the dtype of the subclass to match the dtype of the dequantized form, both to align with subclass design guidelines and to make this work Test Plan: python test/test.py Reviewers: Subscribers: Tasks: Tags: [ghstack-poisoned]
HDCharles
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that referenced
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Nov 28, 2023
Summary: we are able to save a model quantized with a tensor subclass, save the state dict, then later, load model as meta tensor (i.e. only load tensor metadata not actually parameters) apply quantization api, and then load the quantized model state dict. We change the dtype of the subclass to match the dtype of the dequantized form, both to align with subclass design guidelines and to make this work Test Plan: python test/test.py Reviewers: Subscribers: Tasks: Tags: ghstack-source-id: e02cdf5cd182c06241ddba73d579189e4ff3ba69 Pull Request resolved: #16
Summary: we are able to save a model quantized with a tensor subclass, save the state dict, then later, load model as meta tensor (i.e. only load tensor metadata not actually parameters) apply quantization api, and then load the quantized model state dict. We change the dtype of the subclass to match the dtype of the dequantized form, both to align with subclass design guidelines and to make this work Test Plan: python test/test.py Reviewers: Subscribers: Tasks: Tags: [ghstack-poisoned]
HDCharles
added a commit
that referenced
this pull request
Nov 28, 2023
Summary: we are able to save a model quantized with a tensor subclass, save the state dict, then later, load model as meta tensor (i.e. only load tensor metadata not actually parameters) apply quantization api, and then load the quantized model state dict. We change the dtype of the subclass to match the dtype of the dequantized form, both to align with subclass design guidelines and to make this work Test Plan: python test/test.py Reviewers: Subscribers: Tasks: Tags: ghstack-source-id: e02cdf5cd182c06241ddba73d579189e4ff3ba69 Pull Request resolved: #16
dbyoung18
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to dbyoung18/ao
that referenced
this pull request
Jul 31, 2024
Summary: we are able to save a model quantized with a tensor subclass, save the state dict, then later, load model as meta tensor (i.e. only load tensor metadata not actually parameters) apply quantization api, and then load the quantized model state dict. We change the dtype of the subclass to match the dtype of the dequantized form, both to align with subclass design guidelines and to make this work Test Plan: python test/test.py Reviewers: Subscribers: Tasks: Tags: ghstack-source-id: e02cdf5cd182c06241ddba73d579189e4ff3ba69 Pull Request resolved: pytorch#16
jerryzh168
pushed a commit
that referenced
this pull request
Sep 4, 2024
* initial flow for autoround Signed-off-by: yiliu30 <[email protected]> * update flow Signed-off-by: yiliu30 <[email protected]> * use int4 kernel Signed-off-by: yiliu30 <[email protected]> * remove debug code Signed-off-by: yiliu30 <[email protected]> * update the forward Signed-off-by: yiliu30 <[email protected]> * clean code Signed-off-by: yiliu30 <[email protected]> * e2e example Signed-off-by: yiliu30 <[email protected]> * refine code Signed-off-by: yiliu30 <[email protected]> * add requirements for test Signed-off-by: yiliu30 <[email protected]> * update test Signed-off-by: yiliu30 <[email protected]> * update the readme Signed-off-by: yiliu30 <[email protected]> * add readme Signed-off-by: yiliu30 <[email protected]> * update the filenames Signed-off-by: yiliu30 <[email protected]> * update the np version Signed-off-by: yiliu30 <[email protected]> * add demo Signed-off-by: yiliu30 <[email protected]> * format Signed-off-by: yiliu30 <[email protected]> * add more docs Signed-off-by: yiliu30 <[email protected]> * format Signed-off-by: yiliu30 <[email protected]> * add doc Signed-off-by: yiliu30 <[email protected]> * use `AffineQuantizedTensor` Signed-off-by: yiliu30 <[email protected]> * impl ar using multensors Signed-off-by: yiliu30 <[email protected]> * clean code Signed-off-by: yiliu30 <[email protected]> * use hook + multensors Signed-off-by: yiliu30 <[email protected]> * separate mul_tensors into a new file Signed-off-by: yiliu30 <[email protected]> * fix typos Signed-off-by: yiliu30 <[email protected]> * rename mul_tensor to multi_tensor Signed-off-by: yiliu30 <[email protected]> * enable amp Signed-off-by: yiliu30 <[email protected]> * eval model Signed-off-by: yiliu30 <[email protected]> * add gen examples Signed-off-by: yiliu30 <[email protected]> * add warmup to benchmark Signed-off-by: yiliu30 <[email protected]> * add benchmark Signed-off-by: yiliu30 <[email protected]> * clean code Signed-off-by: yiliu30 <[email protected]> * format code Signed-off-by: yiliu30 <[email protected]> * use tiny kernel Signed-off-by: yiliu30 <[email protected]> * add more note Signed-off-by: yiliu30 <[email protected]> * format Signed-off-by: yiliu30 <[email protected]> * correct typos Signed-off-by: yiliu30 <[email protected]> * remove hard code Signed-off-by: yiliu30 <[email protected]> * use intx Signed-off-by: yiliu30 <[email protected]> * enable offload for multitensor Signed-off-by: yiliu30 <[email protected]> * update the default config Signed-off-by: yiliu30 <[email protected]> * refine note Signed-off-by: yiliu30 <[email protected]> * update the version check Signed-off-by: yiliu30 <[email protected]> * format Signed-off-by: yiliu30 <[email protected]> * update Signed-off-by: yiliu30 <[email protected]> * add ut Signed-off-by: yiliu30 <[email protected]> * format Signed-off-by: yiliu30 <[email protected]> * add scripts Signed-off-by: yiliu30 <[email protected]> * format code Signed-off-by: yiliu30 <[email protected]> * format Signed-off-by: yiliu30 <[email protected]> * update Signed-off-by: yiliu30 <[email protected]> * fix typo Signed-off-by: yiliu30 <[email protected]> * refine bench code Signed-off-by: yiliu30 <[email protected]> * Enable `use_optimized_layer_output` and AO' llama (#12) Signed-off-by: yiliu30 <[email protected]> * Refine the Doc (#14) --------- Signed-off-by: yiliu30 <[email protected]> * add more docstring Signed-off-by: yiliu30 <[email protected]> * add paper link Signed-off-by: yiliu30 <[email protected]> * correct some note Signed-off-by: yiliu30 <[email protected]> * add cmd Signed-off-by: yiliu30 <[email protected]> * udpdate the scripts Signed-off-by: yiliu30 <[email protected]> * revert some change Signed-off-by: yiliu30 <[email protected]> * Add a lightweight configuration for quick benchmarking (#15) Signed-off-by: yiliu30 <[email protected]> * update quant method name Signed-off-by: yiliu30 <[email protected]> * Wrap model's buffers and params to `MultiTensor` & update the results (#16) * wrap model's buffers and params to `MultiTensor` and update the results Signed-off-by: yiliu30 <[email protected]> --------- Signed-off-by: yiliu30 <[email protected]>
jerryzh168
pushed a commit
to jerryzh168/ao
that referenced
this pull request
Sep 4, 2024
* initial flow for autoround Signed-off-by: yiliu30 <[email protected]> * update flow Signed-off-by: yiliu30 <[email protected]> * use int4 kernel Signed-off-by: yiliu30 <[email protected]> * remove debug code Signed-off-by: yiliu30 <[email protected]> * update the forward Signed-off-by: yiliu30 <[email protected]> * clean code Signed-off-by: yiliu30 <[email protected]> * e2e example Signed-off-by: yiliu30 <[email protected]> * refine code Signed-off-by: yiliu30 <[email protected]> * add requirements for test Signed-off-by: yiliu30 <[email protected]> * update test Signed-off-by: yiliu30 <[email protected]> * update the readme Signed-off-by: yiliu30 <[email protected]> * add readme Signed-off-by: yiliu30 <[email protected]> * update the filenames Signed-off-by: yiliu30 <[email protected]> * update the np version Signed-off-by: yiliu30 <[email protected]> * add demo Signed-off-by: yiliu30 <[email protected]> * format Signed-off-by: yiliu30 <[email protected]> * add more docs Signed-off-by: yiliu30 <[email protected]> * format Signed-off-by: yiliu30 <[email protected]> * add doc Signed-off-by: yiliu30 <[email protected]> * use `AffineQuantizedTensor` Signed-off-by: yiliu30 <[email protected]> * impl ar using multensors Signed-off-by: yiliu30 <[email protected]> * clean code Signed-off-by: yiliu30 <[email protected]> * use hook + multensors Signed-off-by: yiliu30 <[email protected]> * separate mul_tensors into a new file Signed-off-by: yiliu30 <[email protected]> * fix typos Signed-off-by: yiliu30 <[email protected]> * rename mul_tensor to multi_tensor Signed-off-by: yiliu30 <[email protected]> * enable amp Signed-off-by: yiliu30 <[email protected]> * eval model Signed-off-by: yiliu30 <[email protected]> * add gen examples Signed-off-by: yiliu30 <[email protected]> * add warmup to benchmark Signed-off-by: yiliu30 <[email protected]> * add benchmark Signed-off-by: yiliu30 <[email protected]> * clean code Signed-off-by: yiliu30 <[email protected]> * format code Signed-off-by: yiliu30 <[email protected]> * use tiny kernel Signed-off-by: yiliu30 <[email protected]> * add more note Signed-off-by: yiliu30 <[email protected]> * format Signed-off-by: yiliu30 <[email protected]> * correct typos Signed-off-by: yiliu30 <[email protected]> * remove hard code Signed-off-by: yiliu30 <[email protected]> * use intx Signed-off-by: yiliu30 <[email protected]> * enable offload for multitensor Signed-off-by: yiliu30 <[email protected]> * update the default config Signed-off-by: yiliu30 <[email protected]> * refine note Signed-off-by: yiliu30 <[email protected]> * update the version check Signed-off-by: yiliu30 <[email protected]> * format Signed-off-by: yiliu30 <[email protected]> * update Signed-off-by: yiliu30 <[email protected]> * add ut Signed-off-by: yiliu30 <[email protected]> * format Signed-off-by: yiliu30 <[email protected]> * add scripts Signed-off-by: yiliu30 <[email protected]> * format code Signed-off-by: yiliu30 <[email protected]> * format Signed-off-by: yiliu30 <[email protected]> * update Signed-off-by: yiliu30 <[email protected]> * fix typo Signed-off-by: yiliu30 <[email protected]> * refine bench code Signed-off-by: yiliu30 <[email protected]> * Enable `use_optimized_layer_output` and AO' llama (pytorch#12) Signed-off-by: yiliu30 <[email protected]> * Refine the Doc (pytorch#14) --------- Signed-off-by: yiliu30 <[email protected]> * add more docstring Signed-off-by: yiliu30 <[email protected]> * add paper link Signed-off-by: yiliu30 <[email protected]> * correct some note Signed-off-by: yiliu30 <[email protected]> * add cmd Signed-off-by: yiliu30 <[email protected]> * udpdate the scripts Signed-off-by: yiliu30 <[email protected]> * revert some change Signed-off-by: yiliu30 <[email protected]> * Add a lightweight configuration for quick benchmarking (pytorch#15) Signed-off-by: yiliu30 <[email protected]> * update quant method name Signed-off-by: yiliu30 <[email protected]> * Wrap model's buffers and params to `MultiTensor` & update the results (pytorch#16) * wrap model's buffers and params to `MultiTensor` and update the results Signed-off-by: yiliu30 <[email protected]> --------- Signed-off-by: yiliu30 <[email protected]>
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Stack from ghstack (oldest at bottom):
Summary: we are able to save a model quantized with a tensor subclass,
save the state dict, then later, load model as meta tensor (i.e. only
load tensor metadata not actually parameters) apply quantization api,
and then load the quantized model state dict.
We change the dtype of the subclass to match the dtype of the
dequantized form, both to align with subclass design guidelines and to
make this work
Test Plan: python test/test.py
Reviewers:
Subscribers:
Tasks:
Tags: