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https://github.com/zebrajr/pytorch.git
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e94ba742b0
Summary: - ~~Add a unit test for the Dynamic Quantized Linear operator (```torch.fbgemm_linear_quantize_weight```, ```torch.fbgemm_pack_quantized_matrix```, and ```torch.fbgemm_linear_int8_weight```) in ```test_quantized.py```.~~ Move this to D16404027 for a separate review. - Add the Dynamic Quantized Linear module in ```torch/nn/quantized/modules/linear.py```. ~~This is in a rudimentary stage. Will add more functions later~~. - Add the torch.quantize logic (prepare, eval, convert) for dynamic quantization. - Add a unit test for the Dynamic Quantized Linear module in ```test_nn_quantized.py```. - Add a unit test for the Model-level Quantization API Pull Request resolved: https://github.com/pytorch/pytorch/pull/23128 ghstack-source-id: 88257232 Differential Revision: D16258664 fbshipit-source-id: 4be3ac39ee27c088b341c741d3f09f51d5a23ef0
37 lines
1.2 KiB
Python
37 lines
1.2 KiB
Python
from __future__ import absolute_import, division, print_function, unicode_literals
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from .quantize import * # noqa: F401
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from .observer import * # noqa: F401
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from .QConfig import * # noqa: F401
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from .fake_quantize import * # noqa: F401
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from .fuse_modules import fuse_modules # noqa: F401
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def default_eval_fn(model, calib_data):
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r"""
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Default evaluation function takes a torch.utils.data.Dataset or a list of
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input Tensors and run the model on the dataset
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"""
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for data, target in calib_data:
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model(data)
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_all__ = [
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'QuantWrapper', 'QuantStub', 'DeQuantStub', 'DEFAULT_MODULE_MAPPING',
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# Top level API for quantizing a float model
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'quantize',
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# Sub functions called by quantize
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'prepare', 'convert',
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# Sub functions for `prepare` and `swap_module`
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'propagate_qconfig', 'add_quant_dequant', 'add_observer', 'swap_module',
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'default_eval_fn',
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# Observers
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'Observer', 'WeightObserver', 'observer', 'default_observer',
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'default_weight_observer',
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# QConfig
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'QConfig', 'default_qconfig',
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# QAT utilities
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'default_qat_qconfig', 'prepare_qat', 'quantize_qat',
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# module transformations
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'fuse_modules',
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# Dynamic quantization utilities
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'quantize_dynamic',
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]
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