saymrwulf/onnxruntime
1
0
Fork 0
mirror of https://github.com/saymrwulf/onnxruntime.git synced 2026-07-30 20:18:08 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

Exclude a few python tests for the DML EP (#5135)

Browse source
This commit is contained in:
Hariharan Seshadri 2020-09-11 16:40:02 -07:00 committed by GitHub
parent 698eccf15e
commit 849bb8653f
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
2 changed files with 42 additions and 14 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

20
onnxruntime/test/python/onnx_backend_test_series.py
View file

@ -87,6 +87,26 @@ def create_backend_test(testname=None):
'^test_softmax_cross_entropy'
]
# Skip these tests for a "pure" DML onnxruntime python wheel. We keep these tests enabled for instances where both DML and CUDA
# EPs are available (Windows GPU CI pipeline has this config) - these test will pass because CUDA has higher precendence than DML
# and the nodes are assigned to only the CUDA EP (which supports these tests)
if c2.supports_device('DML') and not c2.supports_device('GPU'):
current_failing_tests += [
'^test_negative_log_likelihood_loss_input_shape_is_NCd1d2d3_none_no_weight_negative_ignore_index_cpu',
'^test_negative_log_likelihood_loss_input_shape_is_NCd1d2d3_none_no_weight_negative_ignore_index_expanded_cpu',
'^test_softmax_cross_entropy_input_shape_is_NCd1d2d3_none_no_weight_negative_ignore_index_cpu',
'^test_softmax_cross_entropy_input_shape_is_NCd1d2d3_none_no_weight_negative_ignore_index_expanded_cpu',
'^test_softmax_cross_entropy_input_shape_is_NCd1d2d3_none_no_weight_negative_ignore_index_log_prob_cpu',
'^test_softmax_cross_entropy_input_shape_is_NCd1d2d3_none_no_weight_negative_ignore_index_log_prob_expanded_cpu',
'^test_asin_example_cpu',
'^test_dynamicquantizelinear_expanded_cpu',
'^test_resize_downsample_scales_linear_cpu',
'^test_resize_downsample_sizes_linear_pytorch_half_pixel_cpu',
'^test_resize_downsample_sizes_nearest_cpu',
'^test_resize_upsample_sizes_nearest_cpu',
'^test_roialign_cpu'
]
filters = current_failing_tests + \
filters['tests_with_pre_opset7_dependencies'] + \
filters['unsupported_usages'] + \

36
onnxruntime/test/python/onnxruntime_test_python.py
View file

@ -278,20 +278,28 @@ class TestInferenceSession(unittest.TestCase):
np.testing.assert_allclose(output_expected, rescontiguous[0], rtol=1e-05, atol=1e-08)
def testRunModelMultipleThreads(self):
so = onnxrt.SessionOptions()
so.log_verbosity_level = 1
so.logid = "MultiThreadsTest"
sess = onnxrt.InferenceSession(get_name("mul_1.onnx"), sess_options=so)
ro1 = onnxrt.RunOptions()
ro1.logid = "thread1"
t1 = threading.Thread(target=self.run_model, args=(sess, ro1))
ro2 = onnxrt.RunOptions()
ro2.logid = "thread2"
t2 = threading.Thread(target=self.run_model, args=(sess, ro2))
t1.start()
t2.start()
t1.join()
t2.join()
available_providers = onnxrt.get_available_providers()
# Skip this test for a "pure" DML onnxruntime python wheel. We keep this test enabled for instances where both DML and CUDA
# EPs are available (Windows GPU CI pipeline has this config) - this test will pass because CUDA has higher precendence than DML
# and the nodes are assigned to only the CUDA EP (which supports this test)
if ('DmlExecutionProvider' in available_providers and not 'CUDAExecutionProvider' in available_providers):
print("Skipping testRunModelMultipleThreads as the DML EP does not support calling Run() on different threads using the same session object ")
else:
so = onnxrt.SessionOptions()
so.log_verbosity_level = 1
so.logid = "MultiThreadsTest"
sess = onnxrt.InferenceSession(get_name("mul_1.onnx"), sess_options=so)
ro1 = onnxrt.RunOptions()
ro1.logid = "thread1"
t1 = threading.Thread(target=self.run_model, args=(sess, ro1))
ro2 = onnxrt.RunOptions()
ro2.logid = "thread2"
t2 = threading.Thread(target=self.run_model, args=(sess, ro2))
t1.start()
t2.start()
t1.join()
t2.join()
def testListAsInput(self):
sess = onnxrt.InferenceSession(get_name("mul_1.onnx"))