An overview of the differences between pytorch and Numpy and how to convert them to each other.

# -*- coding: utf-8 -*-
# @Time  : 2018/1/17 16:37
# @Author : Zhiwei Zhong
# @Site  : 
# @File  : Numpy_Pytorch.py
# @Software: PyCharm

import torch
import numpy as np

np_data = (6).reshape((2, 3))

# numpy to pytorch format

torch_data = torch.from_numpy(np_data)
print(
  '\n numpy', np_data,
  '\n torch', torch_data,
)
'''
 numpy [[0 1 2]
 [3 4 5]] 
 torch 
 0 1 2
 3 4 5
[ of size 2x3]
'''
# torch to numpy
tensor2array = torch_data.numpy()
print(tensor2array)
"""
[[0 1 2]
 [3 4 5]]
"""
# Operators
# abs, add, similar to numpy
data = [[1, 2], [3, 4]]
tensor = (data)    # Convert to 32-bit floating point, torch accepts all in the form of Tensor, so convert to Tensor before operation
print(
  '\n numpy', (data, data),
  '\n torch', (tensor, tensor)    # () is a dot product
)
'''
 numpy [[ 7 10]
 [15 22]] 
 torch 
 7 10
 15 22
[ of size 2x2]
'''