Best Python code snippet using pandera_python
test_shape_convert.py
Source:test_shape_convert.py
...18 return x19 x = torch.rand(*shape_nchw)20 output = nchw2nlc2nchw(test_func2, x, arg=100)21 assert output.shape == torch.Size(shape_nchw)22 def test_func3(x):23 assert x.is_contiguous()24 assert x.shape == torch.Size(shape_nlc)25 return x26 x = torch.rand(*shape_nchw)27 output = nchw2nlc2nchw(test_func3, x, contiguous=True)28 assert output.shape == torch.Size(shape_nchw)29 assert output.is_contiguous()30def test_nlc2nchw2nlc():31 # Test nlc2nchw2nlc function32 shape_nchw = (4, 2, 5, 5)33 shape_nlc = (4, 25, 2)34 def test_func(x):35 assert x.shape == torch.Size(shape_nchw)36 return x37 x = torch.rand(*shape_nlc)38 output = nlc2nchw2nlc(test_func, x, shape_nchw[2:])39 assert output.shape == torch.Size(shape_nlc)40 def test_func2(x, arg):41 assert x.shape == torch.Size(shape_nchw)42 assert arg == 10043 return x44 x = torch.rand(*shape_nlc)45 output = nlc2nchw2nlc(test_func2, x, shape_nchw[2:], arg=100)46 assert output.shape == torch.Size(shape_nlc)47 def test_func3(x):48 assert x.is_contiguous()49 assert x.shape == torch.Size(shape_nchw)50 return x51 x = torch.rand(*shape_nlc)52 output = nlc2nchw2nlc(test_func3, x, shape_nchw[2:], contiguous=True)53 assert output.shape == torch.Size(shape_nlc)54 assert output.is_contiguous()55def test_nchw_to_nlc():56 # Test nchw_to_nlc function57 shape_nchw = (4, 2, 5, 5)58 shape_nlc = (4, 25, 2)59 x = torch.rand(*shape_nchw)60 y = nchw_to_nlc(x)61 assert y.shape == torch.Size(shape_nlc)...
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