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42 行
713 B
42 行
713 B
import time
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import torch
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import numpy as np
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a = torch.tensor([2., 2.])
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batch_size = 32
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print(a.shape[0])
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t0 = time.time()
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for i in range(1000):
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b = a.expand(batch_size, -1)
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t1 = time.time()
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print(t0 - t1)
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t0 = time.time()
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for i in range(1000):
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b = a * torch.ones(batch_size, a.shape[0])
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t1 = time.time()
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print(t0 - t1)
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t0 = time.time()
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for i in range(1000):
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b = torch.cat([a for _ in range(batch_size)], axis=0)
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t1 = time.time()
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print(t0 - t1)
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t0 = time.time()
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for i in range(1000):
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b = torch.cat([a] * batch_size, axis=0)
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t1 = time.time()
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print(t0 - t1)
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t0 = time.time()
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for i in range(1000):
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b = a * torch.tensor(np.ones((batch_size, a.shape[0])))
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t1 = time.time()
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print(t0 - t1)
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