tensorflow 无效参数:In[0] 不是矩阵 [英] tensorflow Invalid argument: In[0] is not a matrix

问题描述

我是 tensorflow C++ API 的新手，正在努力寻找文档在线的.这个短代码执行两个向量的内积W 和 x1，编译正常但有运行时错误，我复制代码和错误日志在这里.非常感谢您的帮助

i am new to tensorflow C++ API and struggling to find documentation online. this short code performs inner product of two vectors W and x1, compile fine but there are run time errors, i copy the code and error logs here. thanks a lot for the help

#include "tensorflow/cc/client/client_session.h"
#include "tensorflow/cc/ops/standard_ops.h"
#include "tensorflow/core/framework/tensor.h"

int main() {

  using namespace tensorflow;
  using namespace tensorflow::ops;

  Tensor W (DT_FLOAT,TensorShape({2})); 
  Tensor x1(DT_FLOAT,TensorShape({2})); 

  auto W_map  = W .tensor<float,1>();
  auto x1_map = x1.tensor<float,1>();

  for(int i=0;i<L;++i) { 
    W_map(i)  = -1; 
    x1_map(i) =  1;  
  }
  std::cout<<"W  \n"<<W .flat<float>()<<"\n debug "<<W .DebugString()<<std::endl;
  std::cout<<"x1 \n"<<x1.flat<float>()<<"\n debug "<<x1.DebugString()<<std::endl; 

  Scope root = Scope::NewRootScope();
  ClientSession session(root);

  // either line of code gives similar run time error
 // auto v1 = MatMul(root.WithOpName("v1"), W, x1,  MatMul::TransposeA(true));
  auto v1 = MatMul(root.WithOpName("v1"), W, x1, MatMul::TransposeB(true));

  std::vector<Tensor> o1; 

  TF_CHECK_OK(session.Run({v1}, &o1));
}

===========================

hweekuans-MacBook-Pro:linear_model hweekuan$ ./linear

W  
-1
-1
 debug Tensor<type: float shape: [2] values: -1 -1>

x1 
1
1
 debug Tensor<type: float shape: [2] values: 1 1>

F tensorflow/cc/20170412/linear_model/linear.cc:37] Check failed:   ::tensorflow::Status::OK() == (session.Run({v1}, &o1)) (OK vs. Invalid argument: In[0] is not a matrix
     [[Node: v1 = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=true, _device="/job:localhost/replica:0/task:0/cpu:0"](Const/Const, Const_1/Const)]])
Abort trap: 6

推荐答案

错误信息给出了问题的线索:W 和 x1 都不是二维的矩阵——事实上，两者都是一维向量——并且 tensorflow::ops::MatMul() 操作要求它的两个参数至少是二维的.它不会自动将向量转换为其矩阵表示，您必须手动执行此操作.

The error message gives a clue to the problem: neither W nor x1 is a 2-D matrix—in fact, both are 1-D vectors—and the tensorflow::ops::MatMul() op requires that both of its arguments are at least 2-dimensional. It does not automatically convert vectors to their matrix representation, and you must do this manually.

为了解决这个问题，在构造W和TensorShape({2, 1})TensorShape({1, 2})> 当你构造 x1 时.对于这些形状，您不应设置 MatMul::TransposeA(false) 和 MatMul::TransposeB(false)，或者您可以省略这些选项，因为它们是默认值.

To solve the problem, specify TensorShape({1, 2}) when you construct W and TensorShape({2, 1}) when you construct x1. With these shapes, you should not set MatMul::TransposeA(false) and MatMul::TransposeB(false), or you can omit these options since they are the default values.

这篇关于tensorflow 无效参数:In[0] 不是矩阵的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！