lileidev commented on issue #13634:
URL: https://github.com/apache/tvm/issues/13634#issuecomment-1471387682
Initialize z_data to zeros. After gm.run(), z_data elements updated to
expected value. gm.get_output(0) get wrong number.
`x_data = torch.rand((1, 10))
y_data = torch.rand((1, 10))
z_data = torch.zeros((1, 10))
z_torch = x_data + y_data
print("z_data: ", z_data)
# first run
assert not np.allclose(z_data.numpy(), z_torch.numpy())
gm.set_input_zero_copy("x", tvm.nd.from_dlpack(x_data))
gm.set_input_zero_copy("y", tvm.nd.from_dlpack(y_data))
gm.set_output_zero_copy(0, tvm.nd.from_dlpack(z_data))
gm.run()
print("output: ", gm.get_output(0).numpy())
print("z_data: ", z_data)
print("z_torch: ", z_torch.numpy())
testing.assert_allclose(z_data.numpy(), z_torch.numpy())
testing.assert_allclose(gm.get_output(0).numpy(), z_torch.numpy())`
Output:
z_data: tensor([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]])
output: [[1.093013e-43 0.000000e+00 3.222986e-44 0.000000e+00 1.121039e-44
0.000000e+00 0.000000e+00 0.000000e+00 4.958032e+12 3.073468e-41]]
z_data: tensor([[1.7693, 0.9101, 1.1325, 0.7544, 0.8513, 1.2013, 1.4561,
1.1772, 0.7521,
1.4009]])
z_torch: [[1.7692755 0.910111 1.1324804 0.7543799 0.8513221 1.2012794
1.4561145 1.177244 0.75213444 1.4009231 ]]
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