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51 lines
1.4 KiB
51 lines
1.4 KiB
import pickle
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import numpy as np
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import megengine as mge
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import torch
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import torch.nn.functional as F
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def manual_pad(x, pady, padx):
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pad = (padx, padx, pady, pady)
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return F.pad(torch.tensor(x), pad, "replicate")
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def test_pad_1_1():
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# Getting back the megengine objects:
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with open('test_data/manual_pad_test1_1.pickle', 'rb') as f:
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right_feature, pady, padx, right_pad = pickle.load(f)
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right_feature = right_feature.numpy()
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right_pad = right_pad.numpy()
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# Test Pytorch
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right_pad_pytorch = manual_pad(right_feature, pady, padx).numpy()
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error = np.mean(right_pad_pytorch-right_pad)
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print(f"test_pad_1_1 - Avg. Error: {error}, \n \
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Orig. shape: {right_feature.shape}, \n \
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Padded shape: {right_pad_pytorch.shape}, Expected shape: {right_pad.shape}")
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def test_pad_0_4():
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# Getting back the megengine objects:
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with open('test_data/manual_pad_test0_4.pickle', 'rb') as f:
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right_feature, pady, padx, right_pad = pickle.load(f)
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right_feature = right_feature.numpy()
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right_pad = right_pad.numpy()
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# Test Pytorch
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right_pad_pytorch = manual_pad(right_feature, pady, padx).numpy()
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error = np.mean(right_pad_pytorch-right_pad)
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print(f"test_pad_0_4 - Avg. Error: {error}, \n \
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Orig. shape: {right_feature.shape}, \n \
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Padded shape: {right_pad_pytorch.shape}, Expected shape: {right_pad.shape}")
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if __name__ == '__main__':
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test_pad_1_1()
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test_pad_0_4() |