tf.reshape (API r1.3)

末蓝、 2023-02-22 15:54 81阅读 0赞

#  tf.reshape (API r1.3) #

[https://github.com/tensorflow/docs/tree/r1.3/site/en/api\_docs/api\_docs/python/tf][https_github.com_tensorflow_docs_tree_r1.3_site_en_api_docs_api_docs_python_tf]  
`site/en/api_docs/api_docs/python/tf/reshape.md`

reshape(
        tensor,
        shape,
        name=None
    )

Defined in `tensorflow/python/ops/gen_array_ops.py`.  
See the guide: Tensor Transformations > Shapes and Shaping

Reshapes a tensor.  
重塑张量。

Given tensor, this operation returns a tensor that has the same values as tensor with shape shape.  
给定 tensor，这个操作返回一个张量，它与带有形状 shape 的 tensor 具有相同的值。

If one component of `shape` is the special value -1, the size of that dimension is computed so that the total size remains constant. In particular, a `shape` of `[-1]` flattens into 1-D. At most one component of `shape` can be -1.  
如果 `shape` 的一个分量是特殊值 -1，则计算该维度的大小，以使总大小保持不变。特别地情况为，一个 \[-1\] 维的 `shape` 整个矩阵平铺成 1 维。至多能有一个 `shape` 的分量可以是 -1。

If `shape` is 1-D or higher, then the operation returns a tensor with shape `shape` filled with the values of `tensor`. In this case, the number of elements implied by `shape` must be the same as the number of elements in `tensor`.  
如果 `shape` 是 1-D 或更高，则操作返回形状为 `shape` 的张量，其填充为 `tensor` 的值。在这种情况下，隐含的 `shape` 元素数量必须与 `tensor` 元素数量相同。

## 1. Args ##

tensor: A Tensor.  
shape: A Tensor. Must be one of the following types: int32, int64. Defines the shape of the output tensor. (用于定义输出张量的形状。)  
name: A name for the operation (optional). (操作的名称 (可选)。)

## 2. Returns ##

A Tensor. Has the same type as tensor.  
该操作返回一个 Tensor。与 tensor 具有相同的类型。

shape 是一个张量，其中的一个元素可以是 -1。-1 表示不指定这一维度的大小，函数自动计算，但列表中只能存在一个 -1。

reshape 变换矩阵按照最简单的理解就是：  
reshape(M, shape) == reshape(M, \[-1\]) => reshape(M, shape)  
先将矩阵 M 变为一维矩阵，然后再对一维矩阵的形式根据 shape 进行构造。

## 3. Example ##

#!/usr/bin/env python
    # -*- coding: utf-8 -*-
    
    from __future__ import absolute_import
    from __future__ import print_function
    from __future__ import division
    
    import os
    import sys
    import numpy as np
    import tensorflow as tf
    
    sys.path.append(os.path.dirname(os.path.abspath(__file__)))
    current_directory = os.path.dirname(os.path.abspath(__file__))
    
    print(16 * "++--")
    print("current_directory:", current_directory)
    print(16 * "++--")
    
    x = tf.constant([[[0, 1],
                      [2, 3],
                      [4, 5],
                      [6, 7],
                      [8, 9],
                      [10, 11]]], dtype=np.float32)
    
    y_reshape = tf.reshape(x, [12])
    y_reshape_slice = tf.reshape(x, [12])[0:3]
    
    with tf.Session() as sess:
        input_x = sess.run(x)
        print("input_x.shape:", input_x.shape)
        print('\n')
    
        output_reshape = sess.run(y_reshape)
        print("output_reshape.shape:", output_reshape.shape)
        print("output_reshape:", output_reshape)
        print('\n')
    
        output_reshape_slice = sess.run(y_reshape_slice)
        print("output_reshape_slice.shape:", output_reshape_slice.shape)
        print("output_reshape_slice:", output_reshape_slice)

/usr/bin/python2.7 /home/strong/tensorflow_work/R2CNN_Faster-RCNN_Tensorflow/yongqiang.py
    ++--++--++--++--++--++--++--++--++--++--++--++--++--++--++--++--
    current_directory: /home/strong/tensorflow_work/R2CNN_Faster-RCNN_Tensorflow
    ++--++--++--++--++--++--++--++--++--++--++--++--++--++--++--++--
    2019-08-15 19:09:35.722959: I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA
    2019-08-15 19:09:35.804714: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:892] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
    2019-08-15 19:09:35.804993: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1030] Found device 0 with properties: 
    name: GeForce GTX 1080 major: 6 minor: 1 memoryClockRate(GHz): 1.7335
    pciBusID: 0000:01:00.0
    totalMemory: 7.92GiB freeMemory: 7.43GiB
    2019-08-15 19:09:35.805004: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1120] Creating TensorFlow device (/device:GPU:0) -> (device: 0, name: GeForce GTX 1080, pci bus id: 0000:01:00.0, compute capability: 6.1)
    input_x.shape: (1, 6, 2)
    
    
    output_reshape.shape: (12,)
    output_reshape: [ 0.  1.  2.  3.  4.  5.  6.  7.  8.  9. 10. 11.]
    
    
    output_reshape_slice.shape: (3,)
    output_reshape_slice: [0. 1. 2.]
    
    Process finished with exit code 0

[https_github.com_tensorflow_docs_tree_r1.3_site_en_api_docs_api_docs_python_tf]: https://github.com/tensorflow/docs/tree/r1.3/site/en/api_docs/api_docs/python/tf