63 lines
1.7 KiB
Python
63 lines
1.7 KiB
Python
"""
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View more, visit my tutorial page: https://mofanpy.com/tutorials/
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My Youtube Channel: https://www.youtube.com/user/MorvanZhou
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Dependencies:
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torch: 0.1.11
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numpy
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"""
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import torch
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import numpy as np
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# details about math operation in torch can be found in: http://pytorch.org/docs/torch.html#math-operations
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# convert numpy to tensor or vise versa
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np_data = np.arange(6).reshape((2, 3))
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torch_data = torch.from_numpy(np_data)
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tensor2array = torch_data.numpy()
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print(
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'\nnumpy array:', np_data, # [[0 1 2], [3 4 5]]
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'\ntorch tensor:', torch_data, # 0 1 2 \n 3 4 5 [torch.LongTensor of size 2x3]
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'\ntensor to array:', tensor2array, # [[0 1 2], [3 4 5]]
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)
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# abs
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data = [-1, -2, 1, 2]
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tensor = torch.FloatTensor(data) # 32-bit floating point
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print(
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'\nabs',
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'\nnumpy: ', np.abs(data), # [1 2 1 2]
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'\ntorch: ', torch.abs(tensor) # [1 2 1 2]
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)
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# sin
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print(
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'\nsin',
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'\nnumpy: ', np.sin(data), # [-0.84147098 -0.90929743 0.84147098 0.90929743]
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'\ntorch: ', torch.sin(tensor) # [-0.8415 -0.9093 0.8415 0.9093]
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)
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# mean
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print(
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'\nmean',
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'\nnumpy: ', np.mean(data), # 0.0
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'\ntorch: ', torch.mean(tensor) # 0.0
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)
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# matrix multiplication
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data = [[1,2], [3,4]]
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tensor = torch.FloatTensor(data) # 32-bit floating point
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# correct method
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print(
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'\nmatrix multiplication (matmul)',
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'\nnumpy: ', np.matmul(data, data), # [[7, 10], [15, 22]]
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'\ntorch: ', torch.mm(tensor, tensor) # [[7, 10], [15, 22]]
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)
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# incorrect method
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data = np.array(data)
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print(
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'\nmatrix multiplication (dot)',
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'\nnumpy: ', data.dot(data), # [[7, 10], [15, 22]]
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'\ntorch: ', tensor.dot(tensor) # this will convert tensor to [1,2,3,4], you'll get 30.0
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) |