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[Dygraph qat] Add more ops to calculate output scales #32036

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Merged
juncaipeng merged 1 commit into from
Apr 2, 2021
Merged

[Dygraph qat] Add more ops to calculate output scales #32036

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2 changes: 1 addition & 1 deletion python/paddle/fluid/contrib/slim/quantization/imperative/qat.py
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Original file line number Diff line number Diff line change
Expand Up @@ -468,7 +468,7 @@ def _is_target_layer(self, layer):
"""
Whether the layer needs to calculate output scales.
"""
return isinstance(layer, tuple(utils.quant_output_layers_map.values())) \
return isinstance(layer, utils.quant_output_layers) \
or ('quantized' in layer.full_name() and \
'quantized_noweight' not in layer.full_name())

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34 changes: 12 additions & 22 deletions python/paddle/fluid/contrib/slim/quantization/imperative/utils.py
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Expand Up @@ -43,28 +43,18 @@
"fake_quantize_dequantize_moving_average_abs_max"
]

quant_output_layers_map = {
'Conv2D': paddle.nn.Conv2D,
'Conv2DTranspose': paddle.nn.Conv2DTranspose,
'Linear': paddle.nn.Linear,
'AdaptiveAvgPool2D': paddle.nn.AdaptiveAvgPool2D,
'AdaptiveMaxPool2D': paddle.nn.AdaptiveMaxPool2D,
'AvgPool2D': paddle.nn.AvgPool2D,
'MaxPool2D': paddle.nn.MaxPool2D,
'BatchNorm': paddle.nn.BatchNorm,
'BatchNorm2D': paddle.nn.BatchNorm2D,
'SyncBatchNorm': paddle.nn.SyncBatchNorm,
'ELU': paddle.nn.ELU,
'GELU': paddle.nn.GELU,
'LeakyReLU': paddle.nn.LeakyReLU,
'PReLU': paddle.nn.PReLU,
'ReLU': paddle.nn.ReLU,
'ReLU6': paddle.nn.ReLU6,
'Sigmoid': paddle.nn.Sigmoid,
'Softmax': paddle.nn.Softmax,
'Tanh': paddle.nn.Tanh,
'Swish': paddle.nn.Swish,
}
quant_output_layers = (
paddle.nn.Conv2D, paddle.nn.Conv2DTranspose, paddle.nn.Linear,
paddle.nn.AdaptiveAvgPool2D, paddle.nn.AdaptiveMaxPool2D,
paddle.nn.AvgPool2D, paddle.nn.MaxPool2D, paddle.nn.BatchNorm,
paddle.nn.BatchNorm2D, paddle.nn.LayerNorm, paddle.nn.SyncBatchNorm,
paddle.nn.ELU, paddle.nn.GELU, paddle.nn.Hardshrink, paddle.nn.Hardsigmoid,
paddle.nn.Hardswish, paddle.nn.Hardtanh, paddle.nn.LeakyReLU,
paddle.nn.LogSigmoid, paddle.nn.LogSoftmax, paddle.nn.Maxout,
paddle.nn.PReLU, paddle.nn.ReLU, paddle.nn.ReLU6, paddle.nn.SELU,
paddle.nn.Sigmoid, paddle.nn.Softmax, paddle.nn.Softplus,
paddle.nn.Softshrink, paddle.nn.Softsign, paddle.nn.Swish, paddle.nn.Tanh,
paddle.nn.Tanhshrink, paddle.nn.ThresholdedReLU, paddle.nn.Upsample)

weight_op_types = [
"conv2d", "depthwise_conv2d", "matmul", "conv2d_transpose",
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