torch.nn.intrinsic

This module implements the combined (fused) modules conv + relu which can be then quantized.

ConvBn1d

class torch.nn.intrinsic.ConvBn1d(conv, bn) [source]

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

class torch.nn.intrinsic.ConvBn2d(conv, bn) [source]

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

class torch.nn.intrinsic.ConvBnReLU1d(conv, bn, relu) [source]

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

class torch.nn.intrinsic.ConvBnReLU2d(conv, bn, relu) [source]

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

class torch.nn.intrinsic.ConvReLU1d(conv, relu) [source]

This is a sequential container which calls the Conv1d and ReLU modules. During quantization this will be replaced with the corresponding fused module.

ConvReLU2d

class torch.nn.intrinsic.ConvReLU2d(conv, relu) [source]

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