tmp

[zhangjun]

TransformerInputConvertPlugin

[zhangjun]

https://github.com/giampaolo/psutil/blob/1f1074f8fbed46077ddc05dae92af95fecc78a33/psutil/_pslinux.py#L1885

[zhangjun]

  virtual nvinfer1::DimsExprs getOutputDimensions(
      int output_index,
      const nvinfer1::DimsExprs* inputs,
      int nb_inputs,
      nvinfer1::IExprBuilder& expr_builder) TRT_NOEXCEPT = 0;  // NOLINT

  virtual bool supportsFormatCombination(
      int pos,
      const nvinfer1::PluginTensorDesc* in_out,
      int nb_inputs,
      int nb_outputs) TRT_NOEXCEPT = 0;
virtual void configurePlugin(const nvinfer1::DynamicPluginTensorDesc* in,
                               int nb_inputs,
                               const nvinfer1::DynamicPluginTensorDesc* out,
                               int nb_outputs) TRT_NOEXCEPT;

[zhangjun]

Stargazers over time

[zhangjun]

masked softmax

import math
import torch
from torch import nn
from d2l import torch as d2l

def masked_softmax(X, valid_lens):
    """通过在最后一个轴上掩蔽元素来执行softmax操作"""
    # X:3D张量，valid_lens:1D或2D张量
    if valid_lens is None:
        return nn.functional.softmax(X, dim=-1) # dim=-1代表以X的最后一个维度进行softmax，对于多维的X来说dim=-1相当于dim=2，即是对行进行softmax
    else:
        shape = X.shape
        if valid_lens.dim() == 1: 
            valid_lens = torch.repeat_interleave(valid_lens, shape[1]) # 把valid_lens转换成一个mask向量
        else:
            valid_lens = valid_lens.reshape(-1) # .reshape(-1)把张量拉成一维数组

        X = d2l.sequence_mask(X.reshape(-1, shape[-1]), valid_lens,
                              value=-1e6) # # 最后一轴上被掩蔽的元素使用一个非常大的负值替换，从而其softmax输出为0
        return nn.functional.softmax(X.reshape(shape), dim=-1)