Exemple #1
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 def __init__(self,
              in_features: int,
              out_features: int,
              bias: bool = True) -> None:
     super(Bilinear, self).__init__(in_features, out_features, bias)
     self.quant_handle = Q.QuantAndDeQuantGPU()
     self.weight_origin = None
Exemple #2
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 def __init__(self,
              kernel_size,
              stride=None,
              padding=0,
              ceil_mode: bool = False,
              count_include_pad: bool = True) -> None:
     super(AvgPool1d, self).__init__(kernel_size, stride, padding,
                                     ceil_mode, count_include_pad)
     self.quant_handle = Q.QuantAndDeQuantGPU()
Exemple #3
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 def __init__(self,
              norm_type,
              kernel_size,
              stride=None,
              ceil_mode: bool = False) -> None:
     super(LPPool2d, self).__init__(norm_type=norm_type,
                                    kernel_size=kernel_size,
                                    stride=stride,
                                    ceil_mode=ceil_mode)
     self.quant_handle = Q.QuantAndDeQuantGPU()
Exemple #4
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 def __init__(self,
              kernel_size,
              output_size=None,
              output_ratio=None,
              return_indices: bool = False,
              _random_samples=None) -> None:
     super(FractionalMaxPool2d,
           self).__init__(kernel_size, output_ratio, return_indices,
                          _random_samples)
     self.quant_handle = Q.QuantAndDeQuantGPU()
Exemple #5
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 def __init__(self,
              kernel_size,
              stride=None,
              padding=0,
              dilation=1,
              return_indices: bool = False,
              ceil_mode: bool = False) -> None:
     super(MaxPool1d, self).__init__(kernel_size, stride, padding, dilation,
                                     return_indices, ceil_mode)
     self.quant_handle = Q.QuantAndDeQuantGPU()
Exemple #6
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 def __init__(self,
              in_channels: int,
              out_channels: int,
              kernel_size,
              stride=1,
              padding=0,
              dilation=1,
              groups: int = 1,
              bias: bool = True):
     super(Conv2d, self).__init__(in_channels, out_channels, kernel_size,
                                  stride, padding, dilation, groups, bias)
     self.quant_handle = Q.QuantAndDeQuantGPU()
     self.weight_origin = None
     self._bit_width = 8
Exemple #7
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 def __init__(self, output_size, return_indices: bool = False) -> None:
     super(AdaptiveMaxPool3d, self).__init__(output_size=output_size,
                                             return_indices=return_indices)
     self.quant_handle = Q.QuantAndDeQuantGPU()
Exemple #8
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 def __init__(self, kernel_size, stride=None, padding=0) -> None:
     super(MaxUnpool3d, self).__init__(kernel_size, stride, padding)
     self.quant_handle = Q.QuantAndDeQuantGPU()
Exemple #9
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 def __init__(self, output_size) -> None:
     super(AdaptiveAvgPool3d, self).__init__(output_size)
     self.quant_handle = Q.QuantAndDeQuantGPU()