# 比较与torch.nn.TransformerDecoder的差异 [![查看源文件](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/website-images/master/resource/_static/logo_source.svg)](https://gitee.com/mindspore/docs/blob/master/docs/mindspore/source_zh_cn/note/api_mapping/pytorch_diff/TransformerDecoder.md) ## torch.nn.TransformerDecoder ```python class torch.nn.TransformerDecoder( decoder_layer, num_layers, norm=None )(tgt, memory, tgt_mask=None, memory_mask=None, tgt_key_padding_mask=None, memory_key_padding_mask=None) ``` 更多内容详见[torch.nn.TransformerDecoder](https://pytorch.org/docs/1.8.1/generated/torch.nn.TransformerDecoder.html)。 ## mindspore.nn.TransformerDecoder ```python class mindspore.nn.TransformerDecoder( decoder_layer, num_layers, norm=None )(tgt, memory, tgt_mask=None, memory_mask=None, tgt_key_padding_mask=None, memory_key_padding_mask=None) ``` 更多内容详见[mindspore.nn.TransformerDecoder](https://mindspore.cn/docs/zh-CN/master/api_python/nn/mindspore.nn.TransformerDecoder.html)。 ## 差异对比 `torch.nn.TransformerDecoder` 和 `mindspore.nn.TransformerDecoder` 用法基本一致。 | 分类 | 子类 | PyTorch | MindSpore | 差异 | | ---- |----- |------------------------- |------------- |----------------------------------------------------| | 参数 | 参数1 | decoder_layer | decoder_layer | 功能一致 | | | 参数2 | num_layers | num_layers | 功能一致 | | | 参数3 | norm | norm | 功能一致 | | 输入 | 输入1 | tgt | tgt | 功能一致 | | | 输入2 | memory | memory | 功能一致 | | | 输入3 | tgt_mask | tgt_mask | MindSpore中dtype可设置为float或bool Tensor,PyTorch中dtype可设置为float、byte或bool Tensor | | | 输入4 | memory_mask | memory_mask | MindSpore中dtype可设置为float或bool Tensor,PyTorch中dtype可设置为float、byte或bool Tensor | | | 输入5 | tgt_key_padding_mask | tgt_key_padding_mask | MindSpore中dtype可设置为float或bool Tensor,PyTorch中dtype可设置为byte或bool Tensor | | | 输入6 | memory_key_padding_mask | memory_key_padding_mask | MindSpore中dtype可设置为float或bool Tensor,PyTorch中dtype可设置为byte或bool Tensor | ### 代码示例 ```python # PyTorch import torch from torch import nn decoder_layer = nn.TransformerDecoderLayer(d_model=512, nhead=8) transformer_decoder = nn.TransformerDecoder(decoder_layer, num_layers=6) memory = torch.rand(10, 32, 512) tgt = torch.rand(20, 32, 512) out = transformer_decoder(tgt, memory) print(out.shape) #torch.Size([20, 32, 512]) # MindSpore import mindspore as ms import numpy as np decoder_layer = ms.nn.TransformerDecoderLayer(d_model=512, nhead=8) transformer_decoder = ms.nn.TransformerDecoder(decoder_layer, num_layers=6) memory = ms.Tensor(np.random.rand(10, 32, 512), ms.float32) tgt = ms.Tensor(np.random.rand(20, 32, 512), ms.float32) out = transformer_decoder(tgt, memory) print(out.shape) #(20, 32, 512) ```