torch.Tensor.permute - 数据重排

ゝ一世哀愁。 2022-10-29 05:27 155阅读 0赞

# **torch.Tensor.permute - 数据重排** #

重新排列维度，不改变维度。

## 1. `torch.Tensor.permute` ##

Python method, in `torch.Tensor`

### 1.1 `permute(*dims)` \-> Tensor ###

Returns a view of the original tensor with its dimensions permuted.  
返回其尺寸已排列的原始张量的视图。

### 1.2 Parameters ###

`*dims (int...)` \- The desired ordering of dimensions.  
期望的维度顺序。

### 1.3 Example ###

(base) yongqiang@yongqiang:~$ conda env list
    # conda environments:
    #
    base                  *  /home/yongqiang/miniconda3
    pt-1.4_py-3.6            /home/yongqiang/miniconda3/envs/pt-1.4_py-3.6
    
    (base) yongqiang@yongqiang:~$ conda activate pt-1.4_py-3.6
    (pt-1.4_py-3.6) yongqiang@yongqiang:~$ python
    Python 3.6.10 |Anaconda, Inc.| (default, May  8 2020, 02:54:21)
    [GCC 7.3.0] on linux
    Type "help", "copyright", "credits" or "license" for more information.
    >>> import torch
    >>> torch.__version__
    '1.4.0'
    >>> exit()
    (pt-1.4_py-3.6) yongqiang@yongqiang:~$

(pt-1.4_py-3.6) yongqiang@yongqiang:~$ python
    Python 3.6.10 |Anaconda, Inc.| (default, May  8 2020, 02:54:21)
    [GCC 7.3.0] on linux
    Type "help", "copyright", "credits" or "license" for more information.
    >>> import torch
    >>>
    >>> x = torch.randn(2, 3, 5)
    >>> x
    tensor([[[ 1.0919, -0.5716, -0.2230, -1.3081, -0.5326],
             [-0.8434,  0.9088,  0.7279, -1.3815, -0.4925],
             [-0.4546, -2.3575,  0.4141,  0.4549, -0.2353]],
    
            [[-1.2896, -0.2758, -0.7352,  0.0897, -0.2647],
             [ 1.4542,  0.3866, -1.9141, -1.2314, -0.4329],
             [-0.6978,  0.8083, -1.2807, -1.8151,  0.2868]]])
    >>> x.size()
    torch.Size([2, 3, 5])
    >>>
    >>> y = x.permute(2, 1, 0)
    >>> y
    tensor([[[ 1.0919, -1.2896],
             [-0.8434,  1.4542],
             [-0.4546, -0.6978]],
    
            [[-0.5716, -0.2758],
             [ 0.9088,  0.3866],
             [-2.3575,  0.8083]],
    
            [[-0.2230, -0.7352],
             [ 0.7279, -1.9141],
             [ 0.4141, -1.2807]],
    
            [[-1.3081,  0.0897],
             [-1.3815, -1.2314],
             [ 0.4549, -1.8151]],
    
            [[-0.5326, -0.2647],
             [-0.4925, -0.4329],
             [-0.2353,  0.2868]]])
    >>>
    >>> y.size()
    torch.Size([5, 3, 2])
    >>>
    >>> exit()
    (pt-1.4_py-3.6) yongqiang@yongqiang:~$

## 2. `permute(0, 3, 2, 1)` ##

#!/usr/bin/env python
    # -*- coding: utf-8 -*-
    # yongqiang cheng
    
    from __future__ import absolute_import
    from __future__ import division
    from __future__ import print_function
    
    import torch
    import numpy as np
    
    np_data = np.array([[[[1, 2, 3],
                          [4, 5, 6],
                          [7, 8, 9],
                          [10, 11, 12]]]])
    
    print("\nnp_data.size():")
    print(np_data.shape)
    
    print("np_data:")
    print(np_data)
    
    src_data = torch.tensor(np_data)
    print("\nsrc_data.size():")
    print(src_data.size())
    
    print("src_data:")
    print(src_data)
    
    dst_data = src_data.permute(0, 3, 2, 1)
    print("\ndst_data.size():")
    print(dst_data.size())
    
    print("dst_data:")
    print(dst_data)

/home/yongqiang/miniconda3/envs/pt-1.4_py-3.6/bin/python /home/yongqiang/pycharm_work/yongqiang.py
    
    np_data.size():
    (1, 1, 4, 3)
    np_data:
    [[[[ 1  2  3]
       [ 4  5  6]
       [ 7  8  9]
       [10 11 12]]]]
    
    src_data.size():
    torch.Size([1, 1, 4, 3])
    src_data:
    tensor([[[[ 1,  2,  3],
              [ 4,  5,  6],
              [ 7,  8,  9],
              [10, 11, 12]]]])
    
    dst_data.size():
    torch.Size([1, 3, 4, 1])
    dst_data:
    tensor([[[[ 1],
              [ 4],
              [ 7],
              [10]],
    
             [[ 2],
              [ 5],
              [ 8],
              [11]],
    
             [[ 3],
              [ 6],
              [ 9],
              [12]]]])
    
    Process finished with exit code 0

## 3. Transpose matrix in C Program ##

//======================================================================================================================
    // Transpose matrix in C Program
    // Yongqiang Cheng
    //======================================================================================================================
    
    #include <iostream>
    
    void transpose(const float *input_data, float *output_data, const int row, const int col) {
    
        for (int i = 0; i < row; ++i) {
            const float *ptr_in = input_data + i * col;
            for (int j = 0; j < col; ++j) {
                output_data[j * row + i] = ptr_in[j];
            }
        }
    }
    
    const int len = 3 * 4;
    
    int main() {
        const float input_data[len] = {1, 1, 1, 1,
                                       2, 2, 2, 2,
                                       3, 3, 3, 3};
        float output_data[len] = {0};
    
        std::cout << "The size of array is " << len << ".\n";
    
        int row = 3, col = 4;
        for (int i = 0; i < 3; ++i) {
            for (int j = 0; j < 4; ++j) {
                printf("%f ", input_data[i * 4 + j]);
            }
            printf("\n");
        }
    
        printf("\n");
    
        transpose(input_data, output_data, row, col);
    
        for (int i = 0; i < 4; ++i) {
            for (int j = 0; j < 3; ++j) {
                printf("%f ", output_data[i * 3 + j]);
            }
            printf("\n");
        }
    
        printf("\n");
    
        std::cout << "Hello, World!" << std::endl;
        return 0;
    }

/home/yongqiang/CLionProjects/hash_table/cmake-build-debug/hash_table
    The size of array is 12.
    1.000000 1.000000 1.000000 1.000000 
    2.000000 2.000000 2.000000 2.000000 
    3.000000 3.000000 3.000000 3.000000 
    
    1.000000 2.000000 3.000000 
    1.000000 2.000000 3.000000 
    1.000000 2.000000 3.000000 
    1.000000 2.000000 3.000000 
    
    Hello, World!
    
    Process finished with exit code 0