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tutorial-contents/201_torch_numpy.py

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