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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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: e02cdf5 Pull Request resolved: #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
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: e02cdf5 Pull Request resolved: #16
dbyoung18
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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: e02cdf5 Pull Request resolved: pytorch#16
jerryzh168
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that referenced
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Sep 4, 2024
* initial flow for autoround Signed-off-by: yiliu30 <yi4.liu@intel.com> * update flow Signed-off-by: yiliu30 <yi4.liu@intel.com> * use int4 kernel Signed-off-by: yiliu30 <yi4.liu@intel.com> * remove debug code Signed-off-by: yiliu30 <yi4.liu@intel.com> * update the forward Signed-off-by: yiliu30 <yi4.liu@intel.com> * clean code Signed-off-by: yiliu30 <yi4.liu@intel.com> * e2e example Signed-off-by: yiliu30 <yi4.liu@intel.com> * refine code Signed-off-by: yiliu30 <yi4.liu@intel.com> * add requirements for test Signed-off-by: yiliu30 <yi4.liu@intel.com> * update test Signed-off-by: yiliu30 <yi4.liu@intel.com> * update the readme Signed-off-by: yiliu30 <yi4.liu@intel.com> * add readme Signed-off-by: yiliu30 <yi4.liu@intel.com> * update the filenames Signed-off-by: yiliu30 <yi4.liu@intel.com> * update the np version Signed-off-by: yiliu30 <yi4.liu@intel.com> * add demo Signed-off-by: yiliu30 <yi4.liu@intel.com> * format Signed-off-by: yiliu30 <yi4.liu@intel.com> * add more docs Signed-off-by: yiliu30 <yi4.liu@intel.com> * format Signed-off-by: yiliu30 <yi4.liu@intel.com> * add doc Signed-off-by: yiliu30 <yi4.liu@intel.com> * use `AffineQuantizedTensor` Signed-off-by: yiliu30 <yi4.liu@intel.com> * impl ar using multensors Signed-off-by: yiliu30 <yi4.liu@intel.com> * clean code Signed-off-by: yiliu30 <yi4.liu@intel.com> * use hook + multensors Signed-off-by: yiliu30 <yi4.liu@intel.com> * separate mul_tensors into a new file Signed-off-by: yiliu30 <yi4.liu@intel.com> * fix typos Signed-off-by: yiliu30 <yi4.liu@intel.com> * rename mul_tensor to multi_tensor Signed-off-by: yiliu30 <yi4.liu@intel.com> * enable amp Signed-off-by: yiliu30 <yi4.liu@intel.com> * eval model Signed-off-by: yiliu30 <yi4.liu@intel.com> * add gen examples Signed-off-by: yiliu30 <yi4.liu@intel.com> * add warmup to benchmark Signed-off-by: yiliu30 <yi4.liu@intel.com> * add benchmark Signed-off-by: yiliu30 <yi4.liu@intel.com> * clean code Signed-off-by: yiliu30 <yi4.liu@intel.com> * format code Signed-off-by: yiliu30 <yi4.liu@intel.com> * use tiny kernel Signed-off-by: yiliu30 <yi4.liu@intel.com> * add more note Signed-off-by: yiliu30 <yi4.liu@intel.com> * format Signed-off-by: yiliu30 <yi4.liu@intel.com> * correct typos Signed-off-by: yiliu30 <yi4.liu@intel.com> * remove hard code Signed-off-by: yiliu30 <yi4.liu@intel.com> * use intx Signed-off-by: yiliu30 <yi4.liu@intel.com> * enable offload for multitensor Signed-off-by: yiliu30 <yi4.liu@intel.com> * update the default config Signed-off-by: yiliu30 <yi4.liu@intel.com> * refine note Signed-off-by: yiliu30 <yi4.liu@intel.com> * update the version check Signed-off-by: yiliu30 <yi4.liu@intel.com> * format Signed-off-by: yiliu30 <yi4.liu@intel.com> * update Signed-off-by: yiliu30 <yi4.liu@intel.com> * add ut Signed-off-by: yiliu30 <yi4.liu@intel.com> * format Signed-off-by: yiliu30 <yi4.liu@intel.com> * add scripts Signed-off-by: yiliu30 <yi4.liu@intel.com> * format code Signed-off-by: yiliu30 <yi4.liu@intel.com> * format Signed-off-by: yiliu30 <yi4.liu@intel.com> * update Signed-off-by: yiliu30 <yi4.liu@intel.com> * fix typo Signed-off-by: yiliu30 <yi4.liu@intel.com> * refine bench code Signed-off-by: yiliu30 <yi4.liu@intel.com> * Enable `use_optimized_layer_output` and AO' llama (#12) Signed-off-by: yiliu30 <yi4.liu@intel.com> * Refine the Doc (#14) --------- Signed-off-by: yiliu30 <yi4.liu@intel.com> * add more docstring Signed-off-by: yiliu30 <yi4.liu@intel.com> * add paper link Signed-off-by: yiliu30 <yi4.liu@intel.com> * correct some note Signed-off-by: yiliu30 <yi4.liu@intel.com> * add cmd Signed-off-by: yiliu30 <yi4.liu@intel.com> * udpdate the scripts Signed-off-by: yiliu30 <yi4.liu@intel.com> * revert some change Signed-off-by: yiliu30 <yi4.liu@intel.com> * Add a lightweight configuration for quick benchmarking (#15) Signed-off-by: yiliu30 <yi4.liu@intel.com> * update quant method name Signed-off-by: yiliu30 <yi4.liu@intel.com> * 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 <yi4.liu@intel.com> --------- Signed-off-by: yiliu30 <yi4.liu@intel.com>
jerryzh168
pushed a commit
to jerryzh168/ao
that referenced
this pull request
Sep 4, 2024
* initial flow for autoround Signed-off-by: yiliu30 <yi4.liu@intel.com> * update flow Signed-off-by: yiliu30 <yi4.liu@intel.com> * use int4 kernel Signed-off-by: yiliu30 <yi4.liu@intel.com> * remove debug code Signed-off-by: yiliu30 <yi4.liu@intel.com> * update the forward Signed-off-by: yiliu30 <yi4.liu@intel.com> * clean code Signed-off-by: yiliu30 <yi4.liu@intel.com> * e2e example Signed-off-by: yiliu30 <yi4.liu@intel.com> * refine code Signed-off-by: yiliu30 <yi4.liu@intel.com> * add requirements for test Signed-off-by: yiliu30 <yi4.liu@intel.com> * update test Signed-off-by: yiliu30 <yi4.liu@intel.com> * update the readme Signed-off-by: yiliu30 <yi4.liu@intel.com> * add readme Signed-off-by: yiliu30 <yi4.liu@intel.com> * update the filenames Signed-off-by: yiliu30 <yi4.liu@intel.com> * update the np version Signed-off-by: yiliu30 <yi4.liu@intel.com> * add demo Signed-off-by: yiliu30 <yi4.liu@intel.com> * format Signed-off-by: yiliu30 <yi4.liu@intel.com> * add more docs Signed-off-by: yiliu30 <yi4.liu@intel.com> * format Signed-off-by: yiliu30 <yi4.liu@intel.com> * add doc Signed-off-by: yiliu30 <yi4.liu@intel.com> * use `AffineQuantizedTensor` Signed-off-by: yiliu30 <yi4.liu@intel.com> * impl ar using multensors Signed-off-by: yiliu30 <yi4.liu@intel.com> * clean code Signed-off-by: yiliu30 <yi4.liu@intel.com> * use hook + multensors Signed-off-by: yiliu30 <yi4.liu@intel.com> * separate mul_tensors into a new file Signed-off-by: yiliu30 <yi4.liu@intel.com> * fix typos Signed-off-by: yiliu30 <yi4.liu@intel.com> * rename mul_tensor to multi_tensor Signed-off-by: yiliu30 <yi4.liu@intel.com> * enable amp Signed-off-by: yiliu30 <yi4.liu@intel.com> * eval model Signed-off-by: yiliu30 <yi4.liu@intel.com> * add gen examples Signed-off-by: yiliu30 <yi4.liu@intel.com> * add warmup to benchmark Signed-off-by: yiliu30 <yi4.liu@intel.com> * add benchmark Signed-off-by: yiliu30 <yi4.liu@intel.com> * clean code Signed-off-by: yiliu30 <yi4.liu@intel.com> * format code Signed-off-by: yiliu30 <yi4.liu@intel.com> * use tiny kernel Signed-off-by: yiliu30 <yi4.liu@intel.com> * add more note Signed-off-by: yiliu30 <yi4.liu@intel.com> * format Signed-off-by: yiliu30 <yi4.liu@intel.com> * correct typos Signed-off-by: yiliu30 <yi4.liu@intel.com> * remove hard code Signed-off-by: yiliu30 <yi4.liu@intel.com> * use intx Signed-off-by: yiliu30 <yi4.liu@intel.com> * enable offload for multitensor Signed-off-by: yiliu30 <yi4.liu@intel.com> * update the default config Signed-off-by: yiliu30 <yi4.liu@intel.com> * refine note Signed-off-by: yiliu30 <yi4.liu@intel.com> * update the version check Signed-off-by: yiliu30 <yi4.liu@intel.com> * format Signed-off-by: yiliu30 <yi4.liu@intel.com> * update Signed-off-by: yiliu30 <yi4.liu@intel.com> * add ut Signed-off-by: yiliu30 <yi4.liu@intel.com> * format Signed-off-by: yiliu30 <yi4.liu@intel.com> * add scripts Signed-off-by: yiliu30 <yi4.liu@intel.com> * format code Signed-off-by: yiliu30 <yi4.liu@intel.com> * format Signed-off-by: yiliu30 <yi4.liu@intel.com> * update Signed-off-by: yiliu30 <yi4.liu@intel.com> * fix typo Signed-off-by: yiliu30 <yi4.liu@intel.com> * refine bench code Signed-off-by: yiliu30 <yi4.liu@intel.com> * Enable `use_optimized_layer_output` and AO' llama (pytorch#12) Signed-off-by: yiliu30 <yi4.liu@intel.com> * Refine the Doc (pytorch#14) --------- Signed-off-by: yiliu30 <yi4.liu@intel.com> * add more docstring Signed-off-by: yiliu30 <yi4.liu@intel.com> * add paper link Signed-off-by: yiliu30 <yi4.liu@intel.com> * correct some note Signed-off-by: yiliu30 <yi4.liu@intel.com> * add cmd Signed-off-by: yiliu30 <yi4.liu@intel.com> * udpdate the scripts Signed-off-by: yiliu30 <yi4.liu@intel.com> * revert some change Signed-off-by: yiliu30 <yi4.liu@intel.com> * Add a lightweight configuration for quick benchmarking (pytorch#15) Signed-off-by: yiliu30 <yi4.liu@intel.com> * update quant method name Signed-off-by: yiliu30 <yi4.liu@intel.com> * 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 <yi4.liu@intel.com> --------- Signed-off-by: yiliu30 <yi4.liu@intel.com>
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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: