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Source code for torch.nn.intrinsic.modules.fused

import torch
from torch.nn import Conv1d, Conv2d, Conv3d, ReLU, Linear, BatchNorm1d, BatchNorm2d, BatchNorm3d

# Used for identifying intrinsic modules used in quantization
class _FusedModule(torch.nn.Sequential):
    pass

[docs]class ConvReLU1d(_FusedModule): r"""This is a sequential container which calls the Conv1d and ReLU modules. During quantization this will be replaced with the corresponding fused module.""" def __init__(self, conv, relu): assert type(conv) == Conv1d and type(relu) == ReLU, \ 'Incorrect types for input modules{}{}'.format( type(conv), type(relu)) super().__init__(conv, relu)
[docs]class ConvReLU2d(_FusedModule): r"""This is a sequential container which calls the Conv2d and ReLU modules. During quantization this will be replaced with the corresponding fused module.""" def __init__(self, conv, relu): assert type(conv) == Conv2d and type(relu) == ReLU, \ 'Incorrect types for input modules{}{}'.format( type(conv), type(relu)) super().__init__(conv, relu)
[docs]class ConvReLU3d(_FusedModule): r"""This is a sequential container which calls the Conv3d and ReLU modules. During quantization this will be replaced with the corresponding fused module.""" def __init__(self, conv, relu): assert type(conv) == Conv3d and type(relu) == ReLU, \ 'Incorrect types for input modules{}{}'.format( type(conv), type(relu)) super().__init__(conv, relu)
[docs]class LinearReLU(_FusedModule): r"""This is a sequential container which calls the Linear and ReLU modules. During quantization this will be replaced with the corresponding fused module.""" def __init__(self, linear, relu): assert type(linear) == Linear and type(relu) == ReLU, \ 'Incorrect types for input modules{}{}'.format( type(linear), type(relu)) super().__init__(linear, relu)
[docs]class ConvBn1d(_FusedModule): r"""This is a sequential container which calls the Conv 1d and Batch Norm 1d modules. During quantization this will be replaced with the corresponding fused module.""" def __init__(self, conv, bn): assert type(conv) == Conv1d and type(bn) == BatchNorm1d, \ 'Incorrect types for input modules{}{}'.format( type(conv), type(bn)) super().__init__(conv, bn)
[docs]class ConvBn2d(_FusedModule): r"""This is a sequential container which calls the Conv 2d and Batch Norm 2d modules. During quantization this will be replaced with the corresponding fused module.""" def __init__(self, conv, bn): assert type(conv) == Conv2d and type(bn) == BatchNorm2d, \ 'Incorrect types for input modules{}{}'.format( type(conv), type(bn)) super(ConvBn2d, self).__init__(conv, bn)
[docs]class ConvBnReLU1d(_FusedModule): r"""This is a sequential container which calls the Conv 1d, Batch Norm 1d, and ReLU modules. During quantization this will be replaced with the corresponding fused module.""" def __init__(self, conv, bn, relu): assert type(conv) == Conv1d and type(bn) == BatchNorm1d and \ type(relu) == ReLU, 'Incorrect types for input modules{}{}{}' \ .format(type(conv), type(bn), type(relu)) super().__init__(conv, bn, relu)
[docs]class ConvBnReLU2d(_FusedModule): r"""This is a sequential container which calls the Conv 2d, Batch Norm 2d, and ReLU modules. During quantization this will be replaced with the corresponding fused module.""" def __init__(self, conv, bn, relu): assert type(conv) == Conv2d and type(bn) == BatchNorm2d and \ type(relu) == ReLU, 'Incorrect types for input modules{}{}{}' \ .format(type(conv), type(bn), type(relu)) super().__init__(conv, bn, relu)
[docs]class ConvBn3d(_FusedModule): r"""This is a sequential container which calls the Conv 3d and Batch Norm 3d modules. During quantization this will be replaced with the corresponding fused module.""" def __init__(self, conv, bn): assert type(conv) == Conv3d and type(bn) == BatchNorm3d, \ 'Incorrect types for input modules{}{}'.format( type(conv), type(bn)) super().__init__(conv, bn)
[docs]class ConvBnReLU3d(_FusedModule): r"""This is a sequential container which calls the Conv 3d, Batch Norm 3d, and ReLU modules. During quantization this will be replaced with the corresponding fused module.""" def __init__(self, conv, bn, relu): assert type(conv) == Conv3d and type(bn) == BatchNorm3d and \ type(relu) == ReLU, 'Incorrect types for input modules{}{}{}' \ .format(type(conv), type(bn), type(relu)) super().__init__(conv, bn, relu)
class BNReLU2d(_FusedModule): r"""This is a sequential container which calls the BatchNorm 2d and ReLU modules. During quantization this will be replaced with the corresponding fused module.""" def __init__(self, batch_norm, relu): assert type(batch_norm) == BatchNorm2d and type(relu) == ReLU, \ 'Incorrect types for input modules{}{}'.format( type(batch_norm), type(relu)) super().__init__(batch_norm, relu)
[docs]class BNReLU3d(_FusedModule): r"""This is a sequential container which calls the BatchNorm 3d and ReLU modules. During quantization this will be replaced with the corresponding fused module.""" def __init__(self, batch_norm, relu): assert type(batch_norm) == BatchNorm3d and type(relu) == ReLU, \ 'Incorrect types for input modules{}{}'.format( type(batch_norm), type(relu)) super().__init__(batch_norm, relu)

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