Skip to content

Run ONNX Node Tests on enabled targets #8189

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
masahi merged 1 commit into from
Jun 4, 2021
Merged

Run ONNX Node Tests on enabled targets #8189

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
33 changes: 26 additions & 7 deletions tests/python/frontend/onnx/test_forward.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -4306,8 +4306,25 @@ def verify_eyelike(indata):
]


targets = [tgt for (tgt, _) in tvm.testing.enabled_targets()]

target_skips = {
"cuda": [
"test_mod_mixed_sign_float16/",
"test_qlinearconv/",
"test_resize_upsample_sizes_nearest/",
]
}


@pytest.mark.parametrize("target", targets)
@pytest.mark.parametrize("test", onnx_test_folders)
def test_onnx_nodes(test):
def test_onnx_nodes(test, target):
if target in target_skips:
for failure in target_skips[target]:
if failure in test:
pytest.skip()
break
for failure in unsupported_onnx_tests:
if failure in test:
pytest.skip()
Expand All @@ -4333,12 +4350,14 @@ def test_onnx_nodes(test):
outputs.append(numpy_helper.to_array(new_tensor))
else:
raise ImportError(str(tensor) + " not labeled as an import or an output")
tvm_val = get_tvm_output_with_vm(onnx_model, inputs, "llvm", tvm.cpu(0))
if len(outputs) == 1:
tvm.testing.assert_allclose(outputs[0], tvm_val, rtol=rtol, atol=atol)
else:
for output, val in zip(outputs, tvm_val):
tvm.testing.assert_allclose(output, val, rtol=rtol, atol=atol)

dev = tvm.device(target, 0)
tvm_val = get_tvm_output_with_vm(onnx_model, inputs, target, dev)
if len(outputs) == 1:
tvm.testing.assert_allclose(outputs[0], tvm_val, rtol=rtol, atol=atol)
else:
for output, val in zip(outputs, tvm_val):
tvm.testing.assert_allclose(output, val, rtol=rtol, atol=atol)


def test_wrong_input():
Expand Down