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62bcdc0ac9
See #127836 for details. Pull Request resolved: https://github.com/pytorch/pytorch/pull/127841 Approved by: https://github.com/oulgen
40 lines
1.6 KiB
Python
40 lines
1.6 KiB
Python
# mypy: allow-untyped-defs
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import torch
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from torch import Tensor
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from torch.ao.quantization.experimental.observer import APoTObserver
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from torch.ao.quantization.fake_quantize import FakeQuantizeBase
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from torch.ao.quantization.experimental.fake_quantize_function import fake_quantize_function
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class APoTFakeQuantize(FakeQuantizeBase):
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alpha: Tensor
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gamma: Tensor
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quantization_levels: Tensor
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level_indices: Tensor
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def __init__(self, observer=APoTObserver, **observer_kwargs):
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super().__init__()
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self.activation_post_process = observer(**observer_kwargs)
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self.dtype = self.activation_post_process.dtype
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def calculate_qparams(self, signed=False): # type: ignore[override]
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return self.activation_post_process.calculate_qparams(signed=signed)
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def forward(self, X: torch.Tensor): # type: ignore[override]
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if self.observer_enabled[0] == 1:
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self.activation_post_process.forward(X)
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result = self.activation_post_process.calculate_qparams(signed=False)
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self.alpha = result[0]
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self.gamma = result[1]
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self.quantization_levels = result[2]
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self.level_indices = result[3]
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if self.fake_quant_enabled[0] == 1:
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assert (self.alpha is not None
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and self.gamma is not None
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and self.quantization_levels is not None
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and self.level_indices is not None), "Must set qparams for fake quant"
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X = fake_quantize_function.apply(X, self.alpha, self.gamma, self.quantization_levels, self.level_indices)
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return X
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