# -*- coding: utf-8 -*-# @Time : 2018/1/17 16:37# @Author : Zhiwei Zhong# @Site : # @File : Numpy_Pytorch.py# @Software: PyCharmimport torchimport numpy as npnp_data = np.arange(6).reshape((2, 3))# numpy 转为 pytorch格式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[torch.LongTensor of size 2x3]'''# torch 转为numpytensor2array = torch_data.numpy()print(tensor2array)"""[[0 1 2] [3 4 5]]"""# 运算符# abs 、 add 、和numpy类似data = [[1, 2], [3, 4]]tensor = torch.FloatTensor(data) # 转为32位浮点数，torch接受的都是Tensor的形式，所以运算前先转化为Tensorprint( '/n numpy', np.matmul(data, data), '/n torch', torch.mm(tensor, tensor) # torch.dot()是点乘)''' numpy [[ 7 10] [15 22]] torch 7 10 15 22[torch.FloatTensor of size 2x2]'''
