torch.nn.intrinsic
This module implements the combined (fused) modules conv + relu which can be then quantized.
ConvBn1d
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class torch.nn.intrinsic.ConvBn1d(conv, bn)
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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.
ConvBn2d
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class torch.nn.intrinsic.ConvBn2d(conv, bn)
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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.
ConvBnReLU1d
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class torch.nn.intrinsic.ConvBnReLU1d(conv, bn, relu)
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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.
ConvBnReLU2d
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class torch.nn.intrinsic.ConvBnReLU2d(conv, bn, relu)
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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.
ConvReLU1d
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class torch.nn.intrinsic.ConvReLU1d(conv, relu)
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This is a sequential container which calls the Conv1d and ReLU modules. During quantization this will be replaced with the corresponding fused module.
ConvReLU2d
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class torch.nn.intrinsic.ConvReLU2d(conv, relu)
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This is a sequential container which calls the Conv2d and ReLU modules. During quantization this will be replaced with the corresponding fused module.
© 2019 Torch Contributors
Licensed under the 3-clause BSD License.
https://pytorch.org/docs/1.8.0/torch.nn.intrinsic.html