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hi all, I have tested torch.fft.fftn and mkl_fft.fftn, the performance is below measure in python
import torch import numpy as np from mkl_fft import fftn, fft2 import datetime def numpy_fft(x): for i in range(10): y = fftn(x, axes=(-2,-1)) return y def torch_fft(x): for i in range(10): y = torch.fft.fftn(x, dim=(-2,-1)) return y data = np.random.uniform(0, 10, (1,3,2160, 3840)) torch_data = torch.from_numpy(data) s = datetime.datetime.now() y1 = numpy_fft(data) e = datetime.datetime.now() y2 = torch_fft(torch_data) k = datetime.datetime.now() print(np.max(y2.numpy() - y1)) print(e-s, k-e)
could anyone explains why mkl_fft is slow than torch.fft (almost 10x)?
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hi all, I have tested torch.fft.fftn and mkl_fft.fftn, the performance is below measure in python
could anyone explains why mkl_fft is slow than torch.fft (almost 10x)?
The text was updated successfully, but these errors were encountered: