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[ONNX] Switched to ONNX 1.15.0 (#20929)

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* [ONNX] Switched to ONNX 1.15.0

* Updated usage of ONNX serialization API

* Updated xfailed lists

* Updated xfailed lists

* Added xfailed ML-operators

* Added xfailed float8 cases

* Fixing mo tests

* Reverted legacy tests

* Sets default opset version in layer tests

* Skipped test which breaks moving on 1.15

* Updated xfailed list

* Fixed typo and added more tests to skipped

* Added xfailed tests

* Reduced opset due to need to work on onnx 1.13

* Removed unnecessary xfails

* Skipped misaligned tests

* WA for old compiler build
This commit is contained in:
Georgy Krivoruchko 2023-12-19 10:55:32 -08:00 committed by GitHub
parent 224eb79ab6
commit 27c9ca749d
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GPG Key ID: 4AEE18F83AFDEB23
80 changed files with 478 additions and 201 deletions
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2
conan.lock
View File

@ -10,7 +10,7 @@
"opencl-icd-loader/2023.04.17#5f73dd9f0c023d416a7f162e320b9c77%1692732261.088",
"opencl-headers/2023.04.17#3d98f2d12a67c2400de6f11d5335b5a6%1683936272.16",
"opencl-clhpp-headers/2023.04.17#7c62fcc7ac2559d4839150d2ebaac5c8%1685450803.672",
"onnx/1.14.1#d95f4e64bedf3dc6898253847ac69005%1693130309.828",
"onnx/1.15.0#54b6d944e6995300bc7bcdd3a3206d74%1698840505.336",
"onetbb/2021.10.0#cbb2fc43088070b48f6e4339bc8fa0e1%1693812561.235",
"ittapi/3.24.0#9246125f13e7686dee2b0c992b71db94%1682969872.743",
"hwloc/2.9.2#1c63e2eccac57048ae226e6c946ebf0e%1688677682.002",

2
conanfile.txt
View File

@ -8,7 +8,7 @@ opencl-icd-loader/[>=2023.04.17]
rapidjson/[>=1.1.0]
xbyak/[>=6.62]
snappy/[>=1.1.7]
onnx/1.14.1
onnx/1.15.0
pybind11/[>=2.10.1]
flatbuffers/[>=22.9.24]

2
src/bindings/python/constraints.txt
View File

@ -21,4 +21,4 @@ paddlepaddle==2.5.2
tensorflow>=1.15.5,<2.15.0
six~=1.16.0
protobuf>=3.18.1,<4.0.0
onnx==1.14.1
onnx==1.15.0

16
src/bindings/python/tests_compatibility/__init__.py
View File

@ -157,13 +157,14 @@ xfail_issue_82039 = xfail_test(reason="Unsupported data type Optional, RuntimeEr
xfail_issue_90649 = xfail_test(reason="RuntimeError: OV does not support the following ONNX operations:"
"BlackmanWindow, DFT, HammingWindow, HannWindow, LayerNormalization, "
"MelWeightMatrix, SequenceMap, STFT")
xfail_issue_91151 = xfail_test(reason="RuntimeError: model input (shape={3,4}) and blob (shape=(1)) are incompatible")
skip_issue_91151 = pytest.mark.skip(reason="RuntimeError: model input (shape={3,4}) and blob (shape=(1)) are incompatible") # Need to enable after bumping to 1.15
xfail_issue_91490 = xfail_test(reason="y has zero dimension which is not allowed")
xfail_issue_101965 = xfail_test(reason="Mismatch with numpy-based expected results.")
xfail_issue_113506 = xfail_test(reason="Unsupported operation of type: LSTMSequence Node expects 7 inputs. Actual: 8")
skip_dynamic_model = pytest.mark.skip(reason="CPU plug-in can't load a model with dynamic output shapes via legacy API")
# ONNX 1.14
xfail_issue_119896 = xfail_test(reason="Unsupported element type: FLOAT8")
xfail_issue_119900 = xfail_test(reason="While validating ONNX node '<Node(Resize): Y>': "
"half_pixel_symmetric - this type of coordinate transformation mode "
@ -176,3 +177,16 @@ xfail_issue_119919 = xfail_test(reason="While validating ONNX node '<Node(Pad):
xfail_issue_119922 = xfail_test(reason="ai.onnx.ml operators domain isn't supported")
xfail_issue_119925 = xfail_test(reason="AveragePool AssertionError: Not equal to tolerance rtol=0.001, atol=1e-07")
xfail_issue_119926 = xfail_test(reason="ROIAlign AssertionError: Not equal to tolerance rtol=0.001, atol=1e-07")
# ONNX 1.15
xfail_issue_125485 = xfail_test(reason="AffineGrid operation is not supported")
xfail_issue_125486 = xfail_test(reason="Gelu operation is not supported")
xfail_issue_125488 = xfail_test(reason="ImageDecoder operation is not supported")
xfail_issue_125487 = xfail_test(reason="GridSample doesn't support cubic and linear modes, and 4D tensor")
skip_issue_125489 = pytest.mark.skip(reason="IsInf changed behavior since opset-20") # Need to enable after opset-20 will be released
xfail_issue_125491 = xfail_test(reason="AveragePool mismatch with differences in shapes")
xfail_issue_125492 = xfail_test(reason="DFT mismatch")
xfail_issue_125493 = xfail_test(reason="Reduce* mismatch")
xfail_issue_125495 = xfail_test(reason="ReduceMin/Max doesn't support boolean")
xfail_issue_127812 = xfail_test(reason="Reduce* doesn't support zero dimensions")
skip_misalignment = pytest.mark.skip(reason="Misalignment between onnx versions") # Need to enable after bumping to 1.15

129
src/bindings/python/tests_compatibility/test_onnx/test_backend.py
View File

@ -44,7 +44,7 @@ from tests_compatibility import (
xfail_issue_82038,
xfail_issue_82039,
xfail_issue_90649,
xfail_issue_91151,
skip_issue_91151,
xfail_issue_91490,
xfail_issue_101965,
skip_bitwise_ui64,
@ -73,6 +73,17 @@ from tests_compatibility import (
xfail_issue_119922,
xfail_issue_119925,
xfail_issue_119926,
xfail_issue_125485,
xfail_issue_125486,
xfail_issue_125488,
xfail_issue_125487,
skip_issue_125489,
xfail_issue_125491,
xfail_issue_125492,
xfail_issue_125493,
xfail_issue_125495,
xfail_issue_127812,
skip_misalignment,
)
from tests_compatibility.test_onnx.utils.onnx_backend import OpenVinoTestBackend
@ -186,6 +197,20 @@ tests_expected_to_fail = [
"OnnxBackendNodeModelTest.test_castlike_STRING_to_FLOAT_expanded_cpu",
"OnnxBackendNodeModelTest.test_equal_string_broadcast_cpu",
"OnnxBackendNodeModelTest.test_equal_string_cpu",
"OnnxBackendNodeModelTest.test_regex_full_match_basic_cpu",
"OnnxBackendNodeModelTest.test_regex_full_match_email_domain_cpu",
"OnnxBackendNodeModelTest.test_regex_full_match_empty_cpu",
"OnnxBackendNodeModelTest.test_string_concat_broadcasting_cpu",
"OnnxBackendNodeModelTest.test_string_concat_cpu",
"OnnxBackendNodeModelTest.test_string_concat_empty_string_cpu",
"OnnxBackendNodeModelTest.test_string_concat_utf8_cpu",
"OnnxBackendNodeModelTest.test_string_concat_zero_dimensional_cpu",
"OnnxBackendNodeModelTest.test_string_split_basic_cpu",
"OnnxBackendNodeModelTest.test_string_split_consecutive_delimiters_cpu",
"OnnxBackendNodeModelTest.test_string_split_empty_string_delimiter_cpu",
"OnnxBackendNodeModelTest.test_string_split_empty_tensor_cpu",
"OnnxBackendNodeModelTest.test_string_split_maxsplit_cpu",
"OnnxBackendNodeModelTest.test_string_split_no_delimiter_cpu",
),
(
xfail_issue_33595,
@ -485,7 +510,7 @@ tests_expected_to_fail = [
"OnnxBackendNodeModelTest.test_stft_with_window_cpu",
),
(
xfail_issue_91151,
skip_issue_91151,
"OnnxBackendNodeModelTest.test_castlike_BFLOAT16_to_FLOAT_cpu",
"OnnxBackendNodeModelTest.test_castlike_FLOAT_to_BFLOAT16_cpu",
),
@ -765,6 +790,8 @@ tests_expected_to_fail = [
"OnnxBackendNodeModelTest.test_dequantizelinear_e5m2_cpu",
"OnnxBackendNodeModelTest.test_quantizelinear_e4m3fn_cpu",
"OnnxBackendNodeModelTest.test_quantizelinear_e5m2_cpu",
"OnnxBackendNodeModelTest.test_dequantizelinear_e4m3fn_float16_cpu",
"OnnxBackendNodeModelTest.test_dequantizelinear_e4m3fn_zero_point_cpu",
),
(
xfail_issue_119900,
@ -797,6 +824,10 @@ tests_expected_to_fail = [
xfail_issue_119922,
"OnnxBackendNodeModelTest.test_ai_onnx_ml_array_feature_extractor_cpu",
"OnnxBackendNodeModelTest.test_ai_onnx_ml_binarizer_cpu",
"OnnxBackendNodeModelTest.test_ai_onnx_ml_label_encoder_string_int_cpu",
"OnnxBackendNodeModelTest.test_ai_onnx_ml_label_encoder_string_int_no_default_cpu",
"OnnxBackendNodeModelTest.test_ai_onnx_ml_label_encoder_tensor_mapping_cpu",
"OnnxBackendNodeModelTest.test_ai_onnx_ml_label_encoder_tensor_value_only_mapping_cpu",
),
(
xfail_issue_119925,
@ -806,6 +837,100 @@ tests_expected_to_fail = [
xfail_issue_119926,
"OnnxBackendNodeModelTest.test_roialign_mode_max_cpu",
),
(
xfail_issue_125485,
"OnnxBackendNodeModelTest.test_affine_grid_2d_align_corners_cpu",
"OnnxBackendNodeModelTest.test_affine_grid_2d_align_corners_expanded_cpu",
"OnnxBackendNodeModelTest.test_affine_grid_2d_cpu",
"OnnxBackendNodeModelTest.test_affine_grid_2d_expanded_cpu",
"OnnxBackendNodeModelTest.test_affine_grid_3d_align_corners_cpu",
"OnnxBackendNodeModelTest.test_affine_grid_3d_align_corners_expanded_cpu",
"OnnxBackendNodeModelTest.test_affine_grid_3d_cpu",
"OnnxBackendNodeModelTest.test_affine_grid_3d_expanded_cpu",
),
(
xfail_issue_125486,
"OnnxBackendNodeModelTest.test_gelu_default_1_cpu",
"OnnxBackendNodeModelTest.test_gelu_default_2_cpu",
"OnnxBackendNodeModelTest.test_gelu_tanh_1_cpu",
"OnnxBackendNodeModelTest.test_gelu_tanh_2_cpu",
),
(
xfail_issue_125488,
"OnnxBackendNodeModelTest.test_image_decoder_decode_bmp_rgb_cpu",
"OnnxBackendNodeModelTest.test_image_decoder_decode_jpeg2k_rgb_cpu",
"OnnxBackendNodeModelTest.test_image_decoder_decode_jpeg_bgr_cpu",
"OnnxBackendNodeModelTest.test_image_decoder_decode_jpeg_grayscale_cpu",
"OnnxBackendNodeModelTest.test_image_decoder_decode_jpeg_rgb_cpu",
"OnnxBackendNodeModelTest.test_image_decoder_decode_png_rgb_cpu",
"OnnxBackendNodeModelTest.test_image_decoder_decode_pnm_rgb_cpu",
"OnnxBackendNodeModelTest.test_image_decoder_decode_tiff_rgb_cpu",
"OnnxBackendNodeModelTest.test_image_decoder_decode_webp_rgb_cpu",
),
(
xfail_issue_125487,
"OnnxBackendNodeModelTest.test_gridsample_aligncorners_true_cpu",
"OnnxBackendNodeModelTest.test_gridsample_bicubic_align_corners_0_additional_1_cpu",
"OnnxBackendNodeModelTest.test_gridsample_bicubic_align_corners_1_additional_1_cpu",
"OnnxBackendNodeModelTest.test_gridsample_bicubic_cpu",
"OnnxBackendNodeModelTest.test_gridsample_bilinear_align_corners_0_additional_1_cpu",
"OnnxBackendNodeModelTest.test_gridsample_bilinear_align_corners_1_additional_1_cpu",
"OnnxBackendNodeModelTest.test_gridsample_bilinear_cpu",
"OnnxBackendNodeModelTest.test_gridsample_cpu",
"OnnxBackendNodeModelTest.test_gridsample_volumetric_bilinear_align_corners_0_cpu",
"OnnxBackendNodeModelTest.test_gridsample_volumetric_bilinear_align_corners_1_cpu",
"OnnxBackendNodeModelTest.test_gridsample_volumetric_nearest_align_corners_0_cpu",
"OnnxBackendNodeModelTest.test_gridsample_volumetric_nearest_align_corners_1_cpu",
),
(
skip_issue_125489,
"OnnxBackendNodeModelTest.test_isinf_float16_cpu",
),
(
xfail_issue_125491,
"OnnxBackendNodeModelTest.test_averagepool_3d_dilations_large_count_include_pad_is_0_ceil_mode_is_False_cpu",
"OnnxBackendNodeModelTest.test_averagepool_3d_dilations_large_count_include_pad_is_0_ceil_mode_is_True_cpu",
"OnnxBackendNodeModelTest.test_averagepool_3d_dilations_large_count_include_pad_is_1_ceil_mode_is_False_cpu",
"OnnxBackendNodeModelTest.test_averagepool_3d_dilations_large_count_include_pad_is_1_ceil_mode_is_True_cpu",
"OnnxBackendNodeModelTest.test_averagepool_3d_dilations_small_cpu",
),
(
xfail_issue_125492,
"OnnxBackendNodeModelTest.test_dft_axis_opset19_cpu",
"OnnxBackendNodeModelTest.test_dft_inverse_opset19_cpu",
"OnnxBackendNodeModelTest.test_dft_opset19_cpu",
),
(
xfail_issue_125493,
"OnnxBackendNodeModelTest.test_reduce_l1_empty_set_cpu",
"OnnxBackendNodeModelTest.test_reduce_l2_empty_set_cpu",
"OnnxBackendNodeModelTest.test_reduce_log_sum_empty_set_cpu",
"OnnxBackendNodeModelTest.test_reduce_log_sum_exp_empty_set_cpu",
"OnnxBackendNodeModelTest.test_reduce_min_empty_set_cpu",
"OnnxBackendNodeModelTest.test_reduce_prod_empty_set_cpu",
"OnnxBackendNodeModelTest.test_reduce_sum_square_empty_set_cpu",
),
(
xfail_issue_125495,
"OnnxBackendNodeModelTest.test_reduce_max_bool_inputs_cpu",
"OnnxBackendNodeModelTest.test_reduce_min_bool_inputs_cpu",
),
(
xfail_issue_127812,
"OnnxBackendNodeModelTest.test_reduce_l1_empty_set_expanded_cpu",
"OnnxBackendNodeModelTest.test_reduce_l2_empty_set_expanded_cpu",
"OnnxBackendNodeModelTest.test_reduce_log_sum_empty_set_cpu",
"OnnxBackendNodeModelTest.test_reduce_log_sum_exp_empty_set_cpu",
"OnnxBackendNodeModelTest.test_reduce_sum_empty_set_cpu",
"OnnxBackendNodeModelTest.test_reduce_sum_empty_set_non_reduced_axis_zero_cpu",
"OnnxBackendNodeModelTest.test_reduce_sum_square_empty_set_expanded_cpu",
),
(
skip_misalignment,
"OnnxBackendNodeModelTest.test_gelu_default_2_expanded_cpu",
"OnnxBackendNodeModelTest.test_reduce_log_sum_empty_set_expanded_cpu",
"OnnxBackendNodeModelTest.test_reduce_log_sum_exp_empty_set_expanded_cpu",
),
]
for test_group in tests_expected_to_fail:

18
src/frontends/onnx/tests/__init__.py
View File

@ -42,7 +42,7 @@ xfail_issue_33651 = xfail_test(reason="RuntimeError: OV does not support the fol
xfail_issue_33581 = xfail_test(reason="RuntimeError: OV does not support the following ONNX operations: "
"GatherElements")
xfail_issue_90649 = xfail_test(reason="RuntimeError: OV does not support the following ONNX operations:"
"BlackmanWindow, DFT, HammingWindow, HannWindow, LayerNormalization, "
"DFT, LayerNormalization, "
"MelWeightMatrix, SequenceMap, STFT")
xfail_issue_35923 = xfail_test(reason="RuntimeError: PReLU without weights is not supported")
xfail_issue_38091 = xfail_test(reason="AssertionError: Mismatched elements")
@ -147,12 +147,13 @@ xfail_issue_82039 = xfail_test(reason="Unsupported data type Optional, RuntimeEr
"CPU plugin: Input image format UNSPECIFIED is not supported yet...")
xfail_issue_86911 = xfail_test(reason="LSTM_Seq_len_unpacked - AssertionError: zoo models results mismatch")
xfail_issue_91151 = xfail_test(reason="RuntimeError: model input (shape={3,4}) and blob (shape=(1)) are incompatible")
skip_issue_91151 = pytest.mark.skip(reason="RuntimeError: model input (shape={3,4}) and blob (shape=(1)) are incompatible") # Need to enable after bumping to 1.15
xfail_issue_101965 = xfail_test(reason="Mismatch with numpy-based expected results.")
xfail_issue_113506 = xfail_test(reason="Unsupported operation of type: LSTMSequence Node expects 7 inputs. Actual: 8")
skip_dynamic_model = pytest.mark.skip(reason="CPU plug-in can't load a model with dynamic output shapes via legacy API")
# ONNX 1.14
xfail_issue_119896 = xfail_test(reason="Unsupported element type: FLOAT8")
xfail_issue_119900 = xfail_test(reason="While validating ONNX node '<Node(Resize): Y>': "
"half_pixel_symmetric - this type of coordinate transformation mode "
@ -165,11 +166,22 @@ xfail_issue_119919 = xfail_test(reason="While validating ONNX node '<Node(Pad):
xfail_issue_119922 = xfail_test(reason="ai.onnx.ml operators domain isn't supported")
xfail_issue_119925 = xfail_test(reason="AveragePool AssertionError: Not equal to tolerance rtol=0.001, atol=1e-07")
xfail_issue_119926 = xfail_test(reason="ROIAlign AssertionError: Not equal to tolerance rtol=0.001, atol=1e-07")
# ONNX 1.15
xfail_issue_125485 = xfail_test(reason="AffineGrid operation is not supported")
xfail_issue_125486 = xfail_test(reason="Gelu operation is not supported")
xfail_issue_125488 = xfail_test(reason="ImageDecoder operation is not supported")
skip_issue_125487 = pytest.mark.skip(reason="GridSample doesn't support cubic and linear modes, and 4D tensor") # Need to enable after bumping to 1.15
skip_issue_125489 = pytest.mark.skip(reason="IsInf changed behavior since opset-20") # Need to enable after opset-20 will be released
xfail_issue_125491 = xfail_test(reason="AveragePool mismatch with differences in shapes")
xfail_issue_125492 = xfail_test(reason="DFT mismatch")
xfail_issue_125493 = xfail_test(reason="Reduce* mismatch")
xfail_issue_125495 = xfail_test(reason="ReduceMin/Max doesn't support boolean")
xfail_issue_122776 = xfail_test(reason="test_mish_expanded_cpu - "
"Not equal to tolerance")
xfail_issue_122775 = xfail_test(reason="test_resize_downsample_scales_linear_cpu - "
"Not equal to tolerance")
skip_misalignment = pytest.mark.skip(reason="Misalignment between onnx versions") # Need to enable after bumping to 1.15
skip_issue_127649 = pytest.mark.skip(reason="Not equal to tolerance rtol=0.001, atol=1e-07 - "
"Mismatched elements: 1 / 1000 (0.1%)")

4
src/frontends/onnx/tests/onnx_prototxt_converter.py
View File

@ -58,12 +58,12 @@ def _get_output_file_path(path, extension):
def save_model(proto, f, format=None, save_as_external_data=False, all_tensors_to_one_file=True, location=None, size_threshold=1024, convert_attribute=False):
if isinstance(proto, bytes):
proto = onnx._deserialize(proto, onnx.ModelProto())
proto = onnx.serialization.registry.get("protobuf").serialize_proto(proto, onnx.ModelProto())
if save_as_external_data:
convert_model_to_external_data(proto, all_tensors_to_one_file, location, size_threshold, convert_attribute)
s = onnx._serialize(proto)
s = onnx.serialization.registry.get("protobuf").serialize_proto(proto)
onnx._save_bytes(s, f)

128
src/frontends/onnx/tests/tests_python/test_backend.py
View File

@ -45,7 +45,6 @@ from tests import (
xfail_issue_82038,
xfail_issue_82039,
xfail_issue_90649,
xfail_issue_91151,
skip_bitwise_ui64,
xfail_issue_99949,
xfail_issue_99950,
@ -62,6 +61,7 @@ from tests import (
xfail_issue_99970,
xfail_issue_99972,
xfail_issue_99973,
skip_issue_91151,
xfail_issue_101965,
xfail_issue_113506,
skip_dynamic_model,
@ -73,8 +73,18 @@ from tests import (
xfail_issue_119922,
xfail_issue_119925,
xfail_issue_119926,
xfail_issue_125485,
xfail_issue_125486,
xfail_issue_125488,
skip_issue_125487,
skip_issue_125489,
xfail_issue_125491,
xfail_issue_125492,
xfail_issue_125493,
xfail_issue_125495,
xfail_issue_122775,
xfail_issue_122776
xfail_issue_122776,
skip_misalignment,
)
from tests.tests_python.utils.onnx_backend import OpenVinoTestBackend
@ -195,6 +205,20 @@ tests_expected_to_fail = [
"OnnxBackendNodeModelTest.test_castlike_STRING_to_FLOAT_expanded_cpu",
"OnnxBackendNodeModelTest.test_equal_string_broadcast_cpu",
"OnnxBackendNodeModelTest.test_equal_string_cpu",
"OnnxBackendNodeModelTest.test_regex_full_match_basic_cpu",
"OnnxBackendNodeModelTest.test_regex_full_match_email_domain_cpu",
"OnnxBackendNodeModelTest.test_regex_full_match_empty_cpu",
"OnnxBackendNodeModelTest.test_string_concat_broadcasting_cpu",
"OnnxBackendNodeModelTest.test_string_concat_cpu",
"OnnxBackendNodeModelTest.test_string_concat_empty_string_cpu",
"OnnxBackendNodeModelTest.test_string_concat_utf8_cpu",
"OnnxBackendNodeModelTest.test_string_concat_zero_dimensional_cpu",
"OnnxBackendNodeModelTest.test_string_split_basic_cpu",
"OnnxBackendNodeModelTest.test_string_split_consecutive_delimiters_cpu",
"OnnxBackendNodeModelTest.test_string_split_empty_string_delimiter_cpu",
"OnnxBackendNodeModelTest.test_string_split_empty_tensor_cpu",
"OnnxBackendNodeModelTest.test_string_split_maxsplit_cpu",
"OnnxBackendNodeModelTest.test_string_split_no_delimiter_cpu",
),
(
xfail_issue_33651,
@ -385,11 +409,6 @@ tests_expected_to_fail = [
"OnnxBackendNodeModelTest.test_stft_cpu",
"OnnxBackendNodeModelTest.test_stft_with_window_cpu",
),
(
xfail_issue_91151,
"OnnxBackendNodeModelTest.test_castlike_BFLOAT16_to_FLOAT_cpu",
"OnnxBackendNodeModelTest.test_castlike_FLOAT_to_BFLOAT16_cpu",
),
(
skip_bitwise_ui64,
"OnnxBackendNodeModelTest.test_bitwise_and_ui64_bcast_3v1d_cpu",
@ -573,6 +592,11 @@ tests_expected_to_fail = [
"OnnxBackendNodeModelTest.test_split_1d_uneven_split_opset18_cpu",
"OnnxBackendNodeModelTest.test_split_2d_uneven_split_opset18_cpu",
),
(
skip_issue_91151,
"OnnxBackendNodeModelTest.test_castlike_BFLOAT16_to_FLOAT_cpu",
"OnnxBackendNodeModelTest.test_castlike_FLOAT_to_BFLOAT16_cpu",
),
(
xfail_issue_101965,
"OnnxBackendNodeModelTest.test_dft_axis_cpu",
@ -629,6 +653,8 @@ tests_expected_to_fail = [
"OnnxBackendNodeModelTest.test_dequantizelinear_e5m2_cpu",
"OnnxBackendNodeModelTest.test_quantizelinear_e4m3fn_cpu",
"OnnxBackendNodeModelTest.test_quantizelinear_e5m2_cpu",
"OnnxBackendNodeModelTest.test_dequantizelinear_e4m3fn_float16_cpu",
"OnnxBackendNodeModelTest.test_dequantizelinear_e4m3fn_zero_point_cpu",
),
(
xfail_issue_119900,
@ -661,6 +687,10 @@ tests_expected_to_fail = [
xfail_issue_119922,
"OnnxBackendNodeModelTest.test_ai_onnx_ml_array_feature_extractor_cpu",
"OnnxBackendNodeModelTest.test_ai_onnx_ml_binarizer_cpu",
"OnnxBackendNodeModelTest.test_ai_onnx_ml_label_encoder_string_int_cpu",
"OnnxBackendNodeModelTest.test_ai_onnx_ml_label_encoder_string_int_no_default_cpu",
"OnnxBackendNodeModelTest.test_ai_onnx_ml_label_encoder_tensor_mapping_cpu",
"OnnxBackendNodeModelTest.test_ai_onnx_ml_label_encoder_tensor_value_only_mapping_cpu",
),
(
xfail_issue_119925,
@ -670,6 +700,90 @@ tests_expected_to_fail = [
xfail_issue_119926,
"OnnxBackendNodeModelTest.test_roialign_mode_max_cpu",
),
(
xfail_issue_125485,
"OnnxBackendNodeModelTest.test_affine_grid_2d_align_corners_cpu",
"OnnxBackendNodeModelTest.test_affine_grid_2d_align_corners_expanded_cpu",
"OnnxBackendNodeModelTest.test_affine_grid_2d_cpu",
"OnnxBackendNodeModelTest.test_affine_grid_2d_expanded_cpu",
"OnnxBackendNodeModelTest.test_affine_grid_3d_align_corners_cpu",
"OnnxBackendNodeModelTest.test_affine_grid_3d_align_corners_expanded_cpu",
"OnnxBackendNodeModelTest.test_affine_grid_3d_cpu",
"OnnxBackendNodeModelTest.test_affine_grid_3d_expanded_cpu",
),
(
xfail_issue_125486,
"OnnxBackendNodeModelTest.test_gelu_default_1_cpu",
"OnnxBackendNodeModelTest.test_gelu_default_2_cpu",
"OnnxBackendNodeModelTest.test_gelu_tanh_1_cpu",
"OnnxBackendNodeModelTest.test_gelu_tanh_2_cpu",
),
(
xfail_issue_125488,
"OnnxBackendNodeModelTest.test_image_decoder_decode_bmp_rgb_cpu",
"OnnxBackendNodeModelTest.test_image_decoder_decode_jpeg2k_rgb_cpu",
"OnnxBackendNodeModelTest.test_image_decoder_decode_jpeg_bgr_cpu",
"OnnxBackendNodeModelTest.test_image_decoder_decode_jpeg_grayscale_cpu",
"OnnxBackendNodeModelTest.test_image_decoder_decode_jpeg_rgb_cpu",
"OnnxBackendNodeModelTest.test_image_decoder_decode_png_rgb_cpu",
"OnnxBackendNodeModelTest.test_image_decoder_decode_pnm_rgb_cpu",
"OnnxBackendNodeModelTest.test_image_decoder_decode_tiff_rgb_cpu",
"OnnxBackendNodeModelTest.test_image_decoder_decode_webp_rgb_cpu",
),
(
skip_issue_125487,
"OnnxBackendNodeModelTest.test_gridsample_aligncorners_true_cpu",
"OnnxBackendNodeModelTest.test_gridsample_bicubic_align_corners_0_additional_1_cpu",
"OnnxBackendNodeModelTest.test_gridsample_bicubic_align_corners_1_additional_1_cpu",
"OnnxBackendNodeModelTest.test_gridsample_bicubic_cpu",
"OnnxBackendNodeModelTest.test_gridsample_bilinear_align_corners_0_additional_1_cpu",
"OnnxBackendNodeModelTest.test_gridsample_bilinear_align_corners_1_additional_1_cpu",
"OnnxBackendNodeModelTest.test_gridsample_bilinear_cpu",
"OnnxBackendNodeModelTest.test_gridsample_cpu",
"OnnxBackendNodeModelTest.test_gridsample_volumetric_bilinear_align_corners_0_cpu",
"OnnxBackendNodeModelTest.test_gridsample_volumetric_bilinear_align_corners_1_cpu",
"OnnxBackendNodeModelTest.test_gridsample_volumetric_nearest_align_corners_0_cpu",
"OnnxBackendNodeModelTest.test_gridsample_volumetric_nearest_align_corners_1_cpu",
),
(
skip_issue_125489,
"OnnxBackendNodeModelTest.test_isinf_float16_cpu",
),
(
xfail_issue_125491,
"OnnxBackendNodeModelTest.test_averagepool_3d_dilations_large_count_include_pad_is_0_ceil_mode_is_False_cpu",
"OnnxBackendNodeModelTest.test_averagepool_3d_dilations_large_count_include_pad_is_0_ceil_mode_is_True_cpu",
"OnnxBackendNodeModelTest.test_averagepool_3d_dilations_large_count_include_pad_is_1_ceil_mode_is_False_cpu",
"OnnxBackendNodeModelTest.test_averagepool_3d_dilations_large_count_include_pad_is_1_ceil_mode_is_True_cpu",
"OnnxBackendNodeModelTest.test_averagepool_3d_dilations_small_cpu",
),
(
xfail_issue_125492,
"OnnxBackendNodeModelTest.test_dft_axis_opset19_cpu",
"OnnxBackendNodeModelTest.test_dft_inverse_opset19_cpu",
"OnnxBackendNodeModelTest.test_dft_opset19_cpu",
),
(
xfail_issue_125493,
"OnnxBackendNodeModelTest.test_reduce_l1_empty_set_cpu",
"OnnxBackendNodeModelTest.test_reduce_l2_empty_set_cpu",
"OnnxBackendNodeModelTest.test_reduce_log_sum_empty_set_cpu",
"OnnxBackendNodeModelTest.test_reduce_log_sum_exp_empty_set_cpu",
"OnnxBackendNodeModelTest.test_reduce_min_empty_set_cpu",
"OnnxBackendNodeModelTest.test_reduce_prod_empty_set_cpu",
"OnnxBackendNodeModelTest.test_reduce_sum_square_empty_set_cpu",
),
(
xfail_issue_125495,
"OnnxBackendNodeModelTest.test_reduce_max_bool_inputs_cpu",
"OnnxBackendNodeModelTest.test_reduce_min_bool_inputs_cpu",
),
(
skip_misalignment,
"OnnxBackendNodeModelTest.test_gelu_default_2_expanded_cpu",
"OnnxBackendNodeModelTest.test_reduce_log_sum_empty_set_expanded_cpu",
"OnnxBackendNodeModelTest.test_reduce_log_sum_exp_empty_set_expanded_cpu",
),
]
if platform.system() == 'Darwin':

7
tests/layer_tests/common/onnx_layer_test_class.py
View File

@ -33,7 +33,6 @@ class OnnxRuntimeInfer(BaseInfer):
return result
class OnnxRuntimeLayerTest(CommonLayerTest):
def produce_model_path(self, framework_model, save_path):
return save_to_onnx(framework_model, save_path)
@ -42,3 +41,9 @@ class OnnxRuntimeLayerTest(CommonLayerTest):
ort = OnnxRuntimeInfer(net=model_path)
res = ort.infer(input_data=inputs_dict)
return res
def onnx_make_model(graph_def, **args):
from onnx import helper
if not 'opset_imports' in args:
args['opset_imports'] = [helper.make_opsetid("", 18)] # Last released opset
return helper.make_model(graph_def, **args)

6
tests/layer_tests/onnx_tests/test_abs.py
View File

@ -3,7 +3,7 @@
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -43,7 +43,7 @@ class TestAbs(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net
@ -126,7 +126,7 @@ class TestAbs(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_add_sub_mul_div.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
class TestOperations(OnnxRuntimeLayerTest):
@ -67,7 +67,7 @@ class TestOperations(OnnxRuntimeLayerTest):
args = dict(producer_name='test_model')
if opset:
args['opset_imports'] = [helper.make_opsetid("", opset)]
onnx_net = helper.make_model(graph_def, **args)
onnx_net = onnx_make_model(graph_def, **args)
# Create reference IR net
if op == 'Div':
@ -159,7 +159,7 @@ class TestOperations(OnnxRuntimeLayerTest):
args = dict(producer_name='test_model')
if opset:
args['opset_imports'] = [helper.make_opsetid("", opset)]
onnx_net = helper.make_model(graph_def, **args)
onnx_net = onnx_make_model(graph_def, **args)
# Create reference IR net
if op == 'Add':

8
tests/layer_tests/onnx_tests/test_and.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -48,7 +48,7 @@ class TestAnd(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
# Create reference IR net
@ -119,7 +119,7 @@ class TestAnd(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
# Create reference IR net
@ -216,7 +216,7 @@ class TestAnd(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
# Create reference IR net
constant_calculated = np.logical_and(const1, const2)

4
tests/layer_tests/onnx_tests/test_argmax.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -68,7 +68,7 @@ class TestArgMax(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

4
tests/layer_tests/onnx_tests/test_bn.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
class TestBatchNormalization(OnnxRuntimeLayerTest):
@ -100,7 +100,7 @@ class TestBatchNormalization(OnnxRuntimeLayerTest):
args = dict(producer_name='test_model')
if opset:
args['opset_imports'] = [helper.make_opsetid("", opset)]
onnx_net = helper.make_model(graph_def, **args)
onnx_net = onnx_make_model(graph_def, **args)
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_ceil.py
View File

@ -3,7 +3,7 @@
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -43,7 +43,7 @@ class TestCeil(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net
@ -128,7 +128,7 @@ class TestCeil(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

4
tests/layer_tests/onnx_tests/test_clip.py
View File

@ -3,7 +3,7 @@
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -93,7 +93,7 @@ class TestClip(OnnxRuntimeLayerTest):
args = dict(producer_name='test_model')
if opset:
args['opset_imports'] = [helper.make_opsetid("", opset)]
onnx_net = helper.make_model(graph_def, **args)
onnx_net = onnx_make_model(graph_def, **args)
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_concat.py
View File

@ -3,7 +3,7 @@
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -87,7 +87,7 @@ class TestConcat(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_split_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_split_model')
#
# Create reference IR net
@ -159,7 +159,7 @@ class TestConcat(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_concat_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_concat_model')
ref_net = None

4
tests/layer_tests/onnx_tests/test_conv.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -102,7 +102,7 @@ class TestConv(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

4
tests/layer_tests/onnx_tests/test_conv_transpose.py
View File

@ -3,7 +3,7 @@
import numpy as np
import pytest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
class TestConvTranspose(OnnxRuntimeLayerTest):
@ -106,7 +106,7 @@ class TestConvTranspose(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_conv_transpose_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_conv_transpose_model')
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_cumsum.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -79,7 +79,7 @@ class TestCumSum(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
onnx.checker.check_model(onnx_net)
#
@ -202,7 +202,7 @@ class TestCumSum(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
onnx.checker.check_model(onnx_net)
#

4
tests/layer_tests/onnx_tests/test_dequantize_linear.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -89,7 +89,7 @@ class TestDequantizeLinear(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model',
onnx_net = onnx_make_model(graph_def, producer_name='test_model',
opset_imports=[helper.make_opsetid("", opset)])
onnx.checker.check_model(onnx_net)

6
tests/layer_tests/onnx_tests/test_dropout.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
class TestDropout(OnnxRuntimeLayerTest):
@ -56,7 +56,7 @@ class TestDropout(OnnxRuntimeLayerTest):
args = dict(producer_name='test_model')
if opset:
args['opset_imports'] = [helper.make_opsetid("", opset)]
onnx_net = helper.make_model(graph_def, **args)
onnx_net = onnx_make_model(graph_def, **args)
#
# Create reference IR net
@ -129,7 +129,7 @@ class TestDropout(OnnxRuntimeLayerTest):
args = dict(producer_name='test_model')
if opset:
args['opset_imports'] = [helper.make_opsetid("", opset)]
onnx_net = helper.make_model(graph_def, **args)
onnx_net = onnx_make_model(graph_def, **args)
ref_net = None

6
tests/layer_tests/onnx_tests/test_elu.py
View File

@ -3,7 +3,7 @@
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -44,7 +44,7 @@ class TestElu(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net
@ -132,7 +132,7 @@ class TestElu(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_flatten.py
View File

@ -3,7 +3,7 @@
import pytest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
class TestFlatten(OnnxRuntimeLayerTest):
@ -46,7 +46,7 @@ class TestFlatten(OnnxRuntimeLayerTest):
args = dict(producer_name='test_model')
if opset:
args['opset_imports'] = [helper.make_opsetid("", opset)]
onnx_net = helper.make_model(graph_def, **args)
onnx_net = onnx_make_model(graph_def, **args)
#
# Create reference IR net
@ -124,7 +124,7 @@ class TestFlatten(OnnxRuntimeLayerTest):
args = dict(producer_name='test_model')
if opset:
args['opset_imports'] = [helper.make_opsetid("", opset)]
onnx_net = helper.make_model(graph_def, **args)
onnx_net = onnx_make_model(graph_def, **args)
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_floor.py
View File

@ -3,7 +3,7 @@
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -43,7 +43,7 @@ class TestFloor(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net
@ -128,7 +128,7 @@ class TestFloor(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

4
tests/layer_tests/onnx_tests/test_fusedgemm.py
View File

@ -3,7 +3,7 @@
import numpy as np
import pytest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
class TestFusedGemm(OnnxRuntimeLayerTest):
@ -113,7 +113,7 @@ class TestFusedGemm(OnnxRuntimeLayerTest):
args = dict(producer_name='test_model')
if opset:
args['opset_imports'] = [helper.make_opsetid("", opset)]
onnx_net = helper.make_model(graph_def, **args)
onnx_net = onnx_make_model(graph_def, **args)
ref_net = None

6
tests/layer_tests/onnx_tests/test_gather.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -64,7 +64,7 @@ class TestGather(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net
@ -179,7 +179,7 @@ class TestGather(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_gemm.py
View File

@ -7,7 +7,7 @@ import numpy as np
import pytest
import torch
from common.layer_test_class import CommonLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
class TestGemm(OnnxRuntimeLayerTest):
@ -107,7 +107,7 @@ class TestGemm(OnnxRuntimeLayerTest):
args = dict(producer_name='test_model')
if opset:
args['opset_imports'] = [helper.make_opsetid("", opset)]
onnx_net = helper.make_model(graph_def, **args)
onnx_net = onnx_make_model(graph_def, **args)
#
# Create reference IR net
@ -201,7 +201,7 @@ class TestGemm(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
if precision == 'FP16':
const = const.astype(np.float16)

6
tests/layer_tests/onnx_tests/test_hard_sigmoid.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -55,7 +55,7 @@ class TestHardSigmoid(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net
@ -161,7 +161,7 @@ class TestHardSigmoid(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_identity.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -49,7 +49,7 @@ class TestIdentity(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net
@ -132,7 +132,7 @@ class TestIdentity(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_image_scaler.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
class TestImageScaler(OnnxRuntimeLayerTest):
@ -46,7 +46,7 @@ class TestImageScaler(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net
@ -118,7 +118,7 @@ class TestImageScaler(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

4
tests/layer_tests/onnx_tests/test_instance_normalization.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
class TestInstanceNormalization(OnnxRuntimeLayerTest):
@ -71,7 +71,7 @@ class TestInstanceNormalization(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_leaky_relu.py
View File

@ -3,7 +3,7 @@
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -44,7 +44,7 @@ class TestLeakyRelu(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net
@ -136,7 +136,7 @@ class TestLeakyRelu(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_log.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -49,7 +49,7 @@ class TestLog(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net
@ -130,7 +130,7 @@ class TestLog(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

4
tests/layer_tests/onnx_tests/test_logsoftmax.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from openvino.tools.mo.front.common.partial_infer.utils import int64_array
from unit_tests.utils.graph import build_graph
@ -75,7 +75,7 @@ class TestLog(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_loop.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
class TestLoop(OnnxRuntimeLayerTest):
@ -139,7 +139,7 @@ class TestLoop(OnnxRuntimeLayerTest):
[res]
)
onnx_net = helper.make_model(graph_def, producer_name='test_loop_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_loop_model')
# We do not create reference graph, as it's too complicated to construct it
# So we return None to skip IR comparision
return onnx_net, None
@ -265,7 +265,7 @@ class TestLoop(OnnxRuntimeLayerTest):
[res],
)
onnx_net = helper.make_model(graph_def, producer_name='test_loop_in_loop_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_loop_in_loop_model')
# We do not create reference graph, as it's too complicated to construct it
# So we return None to skip IR comparision

4
tests/layer_tests/onnx_tests/test_lrn.py
View File

@ -3,7 +3,7 @@
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -51,7 +51,7 @@ class TestLRN(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
# Create reference IR net
if not alpha:

4
tests/layer_tests/onnx_tests/test_lstm.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
class TestLSTM(OnnxRuntimeLayerTest):
@ -131,7 +131,7 @@ class TestLSTM(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_{}_model'.format(cell_type))
onnx_net = onnx_make_model(graph_def, producer_name='test_{}_model'.format(cell_type))
# We do not create reference graph, as it's too complicated to construct it
# Moreover, IR reader do not support TensorIterator layers

6
tests/layer_tests/onnx_tests/test_matmul.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
class TestMatMul(OnnxRuntimeLayerTest):
@ -73,7 +73,7 @@ class TestMatMul(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net
@ -127,7 +127,7 @@ class TestMatMul(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

4
tests/layer_tests/onnx_tests/test_mean_variance_normalization.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
class TestMeanVarianceNormalization(OnnxRuntimeLayerTest):
@ -47,7 +47,7 @@ class TestMeanVarianceNormalization(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

4
tests/layer_tests/onnx_tests/test_neg.py
View File

@ -3,7 +3,7 @@
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -43,7 +43,7 @@ class TestNeg(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_neg_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_neg_model')
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_non_zero.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -44,7 +44,7 @@ class TestNonZero(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net
@ -126,7 +126,7 @@ class TestNonZero(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_not.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -49,7 +49,7 @@ class TestNot(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net
@ -132,7 +132,7 @@ class TestNot(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

8
tests/layer_tests/onnx_tests/test_or.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -48,7 +48,7 @@ class TestOr(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
# Create reference IR net
@ -119,7 +119,7 @@ class TestOr(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
# Create reference IR net
@ -216,7 +216,7 @@ class TestOr(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
# Create reference IR net
constant_calculated = np.logical_or(const1, const2)

4
tests/layer_tests/onnx_tests/test_pad.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -104,7 +104,7 @@ class TestPad(OnnxRuntimeLayerTest):
args = dict(producer_name='test_model')
if opset:
args['opset_imports'] = [helper.make_opsetid("", opset)]
onnx_net = helper.make_model(graph_def, **args)
onnx_net = onnx_make_model(graph_def, **args)
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_pooling.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -115,7 +115,7 @@ class TestPooling(OnnxRuntimeLayerTest):
args = dict(producer_name='test_model')
if opset:
args['opset_imports'] = [helper.make_opsetid("", opset)]
onnx_net = helper.make_model(graph_def, **args)
onnx_net = onnx_make_model(graph_def, **args)
#
# Create reference IR net
@ -202,7 +202,7 @@ class TestPooling(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

4
tests/layer_tests/onnx_tests/test_prelu.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -61,7 +61,7 @@ class TestPRelu(OnnxRuntimeLayerTest):
args = dict(producer_name='test_model')
if opset:
args['opset_imports'] = [helper.make_opsetid("", opset)]
onnx_net = helper.make_model(graph_def, **args)
onnx_net = onnx_make_model(graph_def, **args)
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_reciprocal.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
class TestReciprocal(OnnxRuntimeLayerTest):
@ -59,7 +59,7 @@ class TestReciprocal(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
# Create reference IR net
@ -124,7 +124,7 @@ class TestReciprocal(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
# Create reference IR net

4
tests/layer_tests/onnx_tests/test_reduce.py
View File

@ -3,7 +3,7 @@
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -61,7 +61,7 @@ class TestReduce(OnnxRuntimeLayerTest):
onnx_opset.version = 11
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model', opset_imports=[onnx_opset])
onnx_net = onnx_make_model(graph_def, producer_name='test_model', opset_imports=[onnx_opset])
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_reduce_lp.py
View File

@ -6,7 +6,7 @@ import platform
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -64,7 +64,7 @@ class TestReduceL1L2(OnnxRuntimeLayerTest):
onnx_opset.version = 11
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model', opset_imports=[onnx_opset])
onnx_net = onnx_make_model(graph_def, producer_name='test_model', opset_imports=[onnx_opset])
#
# Create reference IR net
@ -176,7 +176,7 @@ class TestReduceL1L2(OnnxRuntimeLayerTest):
onnx_opset.version = 11
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model', opset_imports=[onnx_opset])
onnx_net = onnx_make_model(graph_def, producer_name='test_model', opset_imports=[onnx_opset])
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_relu.py
View File

@ -3,7 +3,7 @@
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -43,7 +43,7 @@ class TestRelu(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net
@ -130,7 +130,7 @@ class TestRelu(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_reshape.py
View File

@ -3,7 +3,7 @@
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -55,7 +55,7 @@ class TestReshape(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_reshape_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_reshape_model')
#
# Create reference IR net
@ -164,7 +164,7 @@ class TestReshape(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_reshape_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_reshape_model')
#
# Create reference IR net

4
tests/layer_tests/onnx_tests/test_resize.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from openvino.tools.mo.front.common.partial_infer.utils import int64_array
from openvino.tools.mo.middle.passes.convert_data_type import data_type_str_to_np, \
@ -96,7 +96,7 @@ class TestResize(OnnxRuntimeLayerTest):
graph_def = onnx.helper.make_graph(nodes_list, 'test_model', [x], [y])
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
onnx.checker.check_model(onnx_net)
#

4
tests/layer_tests/onnx_tests/test_roi_align.py
View File

@ -6,7 +6,7 @@ import platform
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -68,7 +68,7 @@ class TestROIAlign(OnnxRuntimeLayerTest):
operatorsetid.domain = ""
operatorsetid.version = onnx_version
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model', opset_imports=[operatorsetid])
onnx_net = onnx_make_model(graph_def, producer_name='test_model', opset_imports=[operatorsetid])
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_scale.py
View File

@ -3,7 +3,7 @@
import pytest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
class TestScale(OnnxRuntimeLayerTest):
@ -42,7 +42,7 @@ class TestScale(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net
@ -113,7 +113,7 @@ class TestScale(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

4
tests/layer_tests/onnx_tests/test_scatter.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -51,7 +51,7 @@ class TestScatters(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_sigmoid.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -49,7 +49,7 @@ class TestSigmoid(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net
@ -136,7 +136,7 @@ class TestSigmoid(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_sign.py
View File

@ -3,7 +3,7 @@
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -43,7 +43,7 @@ class TestSign(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net
@ -128,7 +128,7 @@ class TestSign(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_slice.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
class TestSlice(OnnxRuntimeLayerTest):
@ -125,7 +125,7 @@ class TestSlice(OnnxRuntimeLayerTest):
args = dict(producer_name='test_model')
if opset:
args['opset_imports'] = [helper.make_opsetid("", opset)]
onnx_net = helper.make_model(graph_def, **args)
onnx_net = onnx_make_model(graph_def, **args)
#
# Create reference IR net
@ -274,7 +274,7 @@ class TestSlice(OnnxRuntimeLayerTest):
args = dict(producer_name='test_model')
if opset:
args['opset_imports'] = [helper.make_opsetid("", opset)]
onnx_net = helper.make_model(graph_def, **args)
onnx_net = onnx_make_model(graph_def, **args)
#
# Create reference IR net

4
tests/layer_tests/onnx_tests/test_softmax.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from openvino.tools.mo.front.common.partial_infer.utils import int64_array
from unit_tests.utils.graph import build_graph
@ -75,7 +75,7 @@ class TestSoftmax(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_softplus.py
View File

@ -3,7 +3,7 @@
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -43,7 +43,7 @@ class TestSoftplus(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net
@ -128,7 +128,7 @@ class TestSoftplus(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_softsign.py
View File

@ -3,7 +3,7 @@
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -43,7 +43,7 @@ class TestSoftsign(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net
@ -130,7 +130,7 @@ class TestSoftsign(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

14
tests/layer_tests/onnx_tests/test_split_concat.py
View File

@ -3,7 +3,7 @@
import pytest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
test_data_3D = [
dict(input_shape=[1, 50, 50], output_shapes=[[1, 50, 25], [1, 50, 25]], axis=2),
@ -155,7 +155,7 @@ class TestSplitConcat(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_split_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_split_model')
#
# Create reference IR net
@ -247,7 +247,7 @@ class TestSplitConcat(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_split_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_split_model')
#
# Create reference IR net
@ -356,7 +356,7 @@ class TestSplit(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_split_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_split_model')
#
# Create reference IR net
@ -405,7 +405,7 @@ class TestSplit(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_split_model_outputs_order')
onnx_net = onnx_make_model(graph_def, producer_name='test_split_model_outputs_order')
ref_net = None
@ -478,7 +478,7 @@ class TestSplit(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_split_model_outputs_order')
onnx_net = onnx_make_model(graph_def, producer_name='test_split_model_outputs_order')
ref_net = None
@ -541,7 +541,7 @@ class TestSplit(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_split_model_outputs_order')
onnx_net = onnx_make_model(graph_def, producer_name='test_split_model_outputs_order')
ref_net = None

6
tests/layer_tests/onnx_tests/test_sqrt.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -49,7 +49,7 @@ class TestSqrt(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net
@ -136,7 +136,7 @@ class TestSqrt(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_squeeze.py
View File

@ -3,7 +3,7 @@
import pytest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
class TestSqueeze(OnnxRuntimeLayerTest):
@ -42,7 +42,7 @@ class TestSqueeze(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_squeeze_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_squeeze_model')
#
# Create reference IR net
@ -117,7 +117,7 @@ class TestSqueeze(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_squeeze_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_squeeze_model')
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_sum.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
class TestSum(OnnxRuntimeLayerTest):
@ -71,7 +71,7 @@ class TestSum(OnnxRuntimeLayerTest):
args = dict(producer_name='test_model')
if opset:
args['opset_imports'] = [helper.make_opsetid("", opset)]
onnx_net = helper.make_model(graph_def, **args)
onnx_net = onnx_make_model(graph_def, **args)
# Create reference IR net
@ -152,7 +152,7 @@ class TestSum(OnnxRuntimeLayerTest):
args = dict(producer_name='test_model')
if opset:
args['opset_imports'] = [helper.make_opsetid("", opset)]
onnx_net = helper.make_model(graph_def, **args)
onnx_net = onnx_make_model(graph_def, **args)
# Create reference IR net

4
tests/layer_tests/onnx_tests/test_topk.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
class TestTopK(OnnxRuntimeLayerTest):
@ -120,7 +120,7 @@ class TestTopK(OnnxRuntimeLayerTest):
args = dict(producer_name='test_model')
if opset:
args['opset_imports'] = [helper.make_opsetid("", opset)]
onnx_net = helper.make_model(graph_def, **args)
onnx_net = onnx_make_model(graph_def, **args)
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_transpose.py
View File

@ -5,7 +5,7 @@ import itertools
import numpy as np
import pytest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
class TestTranspose(OnnxRuntimeLayerTest):
@ -53,7 +53,7 @@ class TestTranspose(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net
@ -129,7 +129,7 @@ class TestTranspose(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_trigonometry.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -45,7 +45,7 @@ class TestTrigonomery(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net
@ -121,7 +121,7 @@ class TestTrigonomery(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
#
# Create reference IR net

6
tests/layer_tests/onnx_tests/test_unsqueeze.py
View File

@ -3,7 +3,7 @@
import pytest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
class TestUnsqueeze(OnnxRuntimeLayerTest):
@ -42,7 +42,7 @@ class TestUnsqueeze(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_squeeze_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_squeeze_model')
#
# Create reference IR net
@ -117,7 +117,7 @@ class TestUnsqueeze(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_unsqueeze_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_unsqueeze_model')
#
# Create reference IR net

4
tests/layer_tests/onnx_tests/test_upsample.py
View File

@ -7,7 +7,7 @@ import os
import pytest
import torch
from common.layer_test_class import CommonLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
class TestUpsample(OnnxRuntimeLayerTest):
@ -72,7 +72,7 @@ class TestUpsample(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def,
onnx_net = onnx_make_model(graph_def,
producer_name='test_model',
opset_imports=[helper.make_opsetid("", opset)])

4
tests/layer_tests/onnx_tests/test_where.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -49,7 +49,7 @@ class TestWhere(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
# Create reference IR net

8
tests/layer_tests/onnx_tests/test_xor.py
View File

@ -4,7 +4,7 @@
import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.onnx_layer_test_class import OnnxRuntimeLayerTest
from common.onnx_layer_test_class import OnnxRuntimeLayerTest, onnx_make_model
from unit_tests.utils.graph import build_graph
@ -48,7 +48,7 @@ class TestXor(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
# Create reference IR net
@ -119,7 +119,7 @@ class TestXor(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
# Create reference IR net
@ -216,7 +216,7 @@ class TestXor(OnnxRuntimeLayerTest):
)
# Create the model (ModelProto)
onnx_net = helper.make_model(graph_def, producer_name='test_model')
onnx_net = onnx_make_model(graph_def, producer_name='test_model')
# Create reference IR net
constant_calculated = np.logical_xor(const1, const2)

2
thirdparty/dependencies.cmake vendored
View File

@ -506,7 +506,7 @@ endif()
#
if(ENABLE_OV_ONNX_FRONTEND)
find_package(ONNX 1.14.0 QUIET COMPONENTS onnx onnx_proto NO_MODULE)
find_package(ONNX 1.15.0 QUIET COMPONENTS onnx onnx_proto NO_MODULE)
if(ONNX_FOUND)
# conan and vcpkg create imported targets 'onnx' and 'onnx_proto'

7
thirdparty/onnx/CMakeLists.txt vendored
View File

@ -53,6 +53,13 @@ if(WIN32)
endif()
endif()
#WA to support old compiler version, removes unused header which may block build
if(CMAKE_COMPILER_IS_GNUCXX AND LINUX AND AARCH64 AND CMAKE_CXX_COMPILER_VERSION VERSION_LESS 7.0)
file(READ onnx/onnx/defs/parser.cc CONTENT)
string(REPLACE "#include <string_view>" "" CONTENT "${CONTENT}")
file(WRITE onnx/onnx/defs/parser.cc "${CONTENT}")
endif()
ov_disable_all_warnings(onnx onnx_proto)
# install

2
thirdparty/onnx/onnx vendored

@ -1 +1 @@
Subproject commit 1014f41f17ecc778d63e760a994579d96ba471ff
Subproject commit b86cc54efce19530fb953e4b21f57e6b3888534c

2
tools/constraints.txt
View File

@ -4,7 +4,7 @@
# tensorflow, numpy
mxnet~=1.2.0; sys_platform == 'win32'
mxnet>=1.7.0.post2,<=1.9.1; sys_platform != 'win32'
onnx>=1.8.1,<=1.14.1
onnx>=1.8.1,<=1.15.0
networkx<=3.1.0
pytest>=5.0,<7.3
protobuf>=3.18.1,<4.0.0

2
tools/mo/unit_tests/mo/front/onnx/priorbox_ext_test.py
View File

@ -14,7 +14,7 @@ from unit_tests.utils.extractors import PB
class TestPriorBoxExt(unittest.TestCase):
@staticmethod
def _create_priorbox_node(aspect_ratio=[], min_size=np.array([]), max_size=np.array([]),
def _create_priorbox_node(aspect_ratio=[], min_size=None, max_size=None,
flip=False, clip=False, variance=None, img_size=0, img_h=0,
img_w=0, step=0, step_h=0, step_w=0, offset=0):
pb = onnx.helper.make_node(

2
tools/mo/unit_tests/mo/front/onnx/unsqueeze_ext_test.py
View File

@ -36,7 +36,7 @@ class TestUnsqueezeONNXExt():
def setUpClass(cls):
Op.registered_ops['Unsqueeze'] = Unsqueeze
@pytest.mark.parametrize("axes",[[0, 1, 2, 3], [1], []])
@pytest.mark.parametrize("axes",[[0, 1, 2, 3], [1]])
def test_unsqueeze_ext(self, axes):
node = self._create_unsqueeze_node(axes)
UnsqueezeFrontExtractor.extract(node)

2
vcpkg.json
View File

@ -81,7 +81,7 @@
"dependencies": [
{
"name": "onnx",
"version>=": "1.14.0"
"version>=": "1.15.0"
},
{
"name": "protobuf",