PyTorch test output

root@Ryzen1800X:~/pytorch/test# python run_test.py 
Running test_autograd ...
............................................................................................s..................................### HCC STATUS_CHECK Error: HSA_STATUS_ERROR_INVALID_ISA (0x100f) at file:mcwamp_hsa.cpp line:1156
Traceback (most recent call last):
  File "run_test.py", line 391, in <module>
    main()
  File "run_test.py", line 383, in main
    raise RuntimeError(message)
RuntimeError: test_autograd failed! Received signal: SIGIOT
root@Ryzen1800X:~/pytorch/test# python test_torch.py 
.................................EF..............................sss............s...............E..........................ss...................................................s..........................................test_torch.py:2540: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than tensor.new_tensor(sourceTensor).
  res2 = expected.new_tensor(expected)
test_torch.py:2544: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than tensor.new_tensor(sourceTensor).
  res2 = expected.new_tensor(expected, dtype=torch.int)
......E...........s.THCudaCheck FAIL file=/root/pytorch/aten/src/THC/generic/THCTensorMath.cu line=25 error=1011 : hipErrorInvalidValue
E.........F................................................................s.................s..............test_torch.py:2180: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  assertEqual('cpu', lambda: torch.tensor(torch.ones((2, 3), dtype=torch.float32), device='cpu:0'))
test_torch.py:2193: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  assertEqual('cuda:0', lambda: torch.tensor(torch.ones((2, 3), dtype=torch.float32), device='cuda:0'))
.Etest_torch.py:2395: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  res2 = torch.tensor(expected)
test_torch.py:2400: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  res2 = torch.tensor(expected, dtype=torch.int)
.test_torch.py:2424: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  check_copy(torch.tensor(source), True, False)
test_torch.py:2425: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  check_copy(torch.tensor(source, requires_grad=False), True, False)
test_torch.py:2426: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  check_copy(torch.tensor(source, requires_grad=True), True, True)
test_torch.py:2430: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than tensor.new_tensor(sourceTensor).
  check_copy(copy.new_tensor(source), True, False)
test_torch.py:2431: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than tensor.new_tensor(sourceTensor).
  check_copy(copy.new_tensor(source, requires_grad=False), True, False)
test_torch.py:2432: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than tensor.new_tensor(sourceTensor).
  check_copy(copy.new_tensor(source, requires_grad=True), True, True)
......E...........................ss...s.
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ERROR: test_blas_alpha_beta_empty (__main__.TestTorch)
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Traceback (most recent call last):
  File "/root/pytorch/test/common.py", line 111, in wrapper
    fn(*args, **kwargs)
  File "test_torch.py", line 6817, in test_blas_alpha_beta_empty
    torch.addmv(input=input, mat=mat, vec=vec, alpha=alpha, beta=beta))
RuntimeError: cublas runtime error : an invalid numeric value was used as an argument at /root/pytorch/aten/src/THC/THCBlas.cu:146

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ERROR: test_dim_function_empty (__main__.TestTorch)
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Traceback (most recent call last):
  File "/root/pytorch/test/common.py", line 111, in wrapper
    fn(*args, **kwargs)
  File "test_torch.py", line 6657, in test_dim_function_empty
    self.assertEqual([shape, shape], [z.shape for z in torch.sort(x, dim=0)])
RuntimeError: invalid argument 2: out of range at /root/pytorch/aten/src/THC/generic/THCTensor.cpp:380

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ERROR: test_norm_cuda (__main__.TestTorch)
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Traceback (most recent call last):
  File "/root/pytorch/test/common.py", line 111, in wrapper
    fn(*args, **kwargs)
  File "test_torch.py", line 871, in test_norm_cuda
    self._test_norm(self, device='cuda')
  File "test_torch.py", line 858, in _test_norm
    res = x.norm(p).cpu().numpy()
  File "/usr/local/lib/python3.6/dist-packages/torch/tensor.py", line 246, in norm
    return torch.norm(self, p, dim, keepdim)
  File "/usr/local/lib/python3.6/dist-packages/torch/functional.py", line 719, in norm
    torch._C._VariableFunctions.nuclear_norm(input, keepdim=keepdim)
RuntimeError: No CUDA implementation of 'gesdd'. Install MAGMA and rebuild cutorch (http://icl.cs.utk.edu/magma/) at /root/pytorch/aten/src/THC/generic/THCTensorMathMagma.cu:333

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ERROR: test_pairwise_distance_empty (__main__.TestTorch)
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Traceback (most recent call last):
  File "/root/pytorch/test/common.py", line 111, in wrapper
    fn(*args, **kwargs)
  File "test_torch.py", line 1088, in test_pairwise_distance_empty
    self.assertEqual(torch.zeros(0, device=device), torch.pairwise_distance(x, y))
RuntimeError: cuda runtime error (1011) : hipErrorInvalidValue at /root/pytorch/aten/src/THC/generic/THCTensorMath.cu:25

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ERROR: test_tensor_factories_empty (__main__.TestTorch)
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Traceback (most recent call last):
  File "/root/pytorch/test/common.py", line 111, in wrapper
    fn(*args, **kwargs)
  File "test_torch.py", line 2500, in test_tensor_factories_empty
    self.assertEqual(shape, torch.zeros(shape, device=device).shape)
RuntimeError: cuda runtime error (1011) : hipErrorInvalidValue at /root/pytorch/aten/src/THC/generic/THCTensorMath.cu:25

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ERROR: test_tensor_shape_empty (__main__.TestTorch)
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Traceback (most recent call last):
  File "/root/pytorch/test/common.py", line 111, in wrapper
    fn(*args, **kwargs)
  File "test_torch.py", line 6585, in test_tensor_shape_empty
    self.assertEqual((0, 0), torch.diagflat(torch.tensor([], device=device)).shape)
RuntimeError: cuda runtime error (1011) : hipErrorInvalidValue at /root/pytorch/aten/src/THC/generic/THCTensorMath.cu:25

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FAIL: test_blas_empty (__main__.TestTorch)
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Traceback (most recent call last):
  File "/root/pytorch/test/common.py", line 111, in wrapper
    fn(*args, **kwargs)
  File "test_torch.py", line 6748, in test_blas_empty
    self.assertEqual(torch.zeros((5, 6), device=device), fn(torch.mm, (5, 0), (0, 6)))
  File "/root/pytorch/test/common.py", line 374, in assertEqual
    assertTensorsEqual(x, y)
  File "/root/pytorch/test/common.py", line 366, in assertTensorsEqual
    self.assertLessEqual(max_err, prec, message)
AssertionError: tensor(3.1855, device='cuda:0') not less than or equal to 1e-05 : 

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FAIL: test_pin_memory (__main__.TestTorch)
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Traceback (most recent call last):
  File "/root/pytorch/test/common.py", line 111, in wrapper
    fn(*args, **kwargs)
  File "test_torch.py", line 8234, in test_pin_memory
    self.assertTrue(pinned.is_pinned())
AssertionError: False is not true

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Ran 391 tests in 58.126s

FAILED (failures=2, errors=6, skipped=13)