[quant] Add quantized Sigmoid module #45883
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Summary: Test Plan: python test/test_quantization.py TestStaticQuantizedModule.test_sigmoid Reviewers: Subscribers: Tasks: Tags: [ghstack-poisoned]
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@@ Coverage Diff @@
## gh/jerryzh168/454/base #45883 +/- ##
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Coverage 68.33% 68.33%
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Files 410 410
Lines 52997 53008 +11
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+ Hits 36213 36222 +9
- Misses 16784 16786 +2
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| zero_point: quantization zero point of the output tensor | ||
| """ | ||
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| def __init__(self, output_scale: float, output_zero_point: int): |
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Can we have default args? It is safe to assume those for this function
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not sure, it's not likely that user is going to construct quantized model from quantized modules from scratch anyways, what is the benefit of having default args?
Summary: Test Plan: python test/test_quantization.py TestStaticQuantizedModule.test_sigmoid Reviewers: Subscribers: Tasks: Tags: Differential Revision: [D24129116](https://our.internmc.facebook.com/intern/diff/D24129116) [ghstack-poisoned]
Summary: Test Plan: python test/test_quantization.py TestStaticQuantizedModule.test_sigmoid Reviewers: Subscribers: Tasks: Tags: Differential Revision: [D24129116](https://our.internmc.facebook.com/intern/diff/D24129116) [ghstack-poisoned]
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This pull request has been merged in 83d2c9a. |
| @@ -149,3 +149,24 @@ def _get_name(self): | |||
| def from_float(cls, mod): | |||
| scale, zero_point = mod.activation_post_process.calculate_qparams() | |||
| return cls(float(scale), int(zero_point), mod.negative_slope, mod.inplace) | |||
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| class Sigmoid(torch.nn.Sigmoid): | |||
| r"""This is the quantized equivalent of :class:`~torch.nn.LeakyReLU`. | |||
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The docs are off here, can we refer to sigmoid instead of leakyRelu?
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oh sorry, will fix in next PR
Stack from ghstack:
Summary:
Test Plan:
python test/test_quantization.py TestStaticQuantizedModule.test_sigmoid
Reviewers:
Subscribers:
Tasks:
Tags:
Differential Revision: D24129116