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[ONNX] WA for I64 images (#2411)

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This commit is contained in:
Jan Iwaszkiewicz 2020-10-22 14:06:23 +02:00 committed by GitHub
parent 3dfec639f0
commit 77794535ab
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GPG Key ID: 4AEE18F83AFDEB23
6 changed files with 87 additions and 45 deletions
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24
ngraph/python/tests/__init__.py
View File

@ -45,6 +45,8 @@ xfail_issue_33535 = xfail_test(reason="nGraph does not support the following ONN
"DynamicQuantizeLinear")
xfail_issue_33538 = xfail_test(reason="RuntimeError: nGraph does not support the following ONNX operations:"
"Scan")
skip_issue_38084 = pytest.mark.skip(reason="Aborted (core dumped) Assertion "
"`(layer->get_output_partial_shape(i).is_static())' failed.")
xfail_issue_33540 = xfail_test(reason="RuntimeError: GRUCell operation has a form that is not supported "
"GRUCell_<number> should be converted to GRUCellIE operation")
xfail_issue_33589 = xfail_test(reason="nGraph does not support the following ONNX operations:"
@ -85,8 +87,6 @@ xfail_issue_35921 = xfail_test(reason="ValueError - shapes mismatch in gemm")
xfail_issue_35923 = xfail_test(reason="RuntimeError: PReLU without weights is not supported")
xfail_issue_35924 = xfail_test(reason="Assertion error - elu results mismatch")
xfail_issue_35925 = xfail_test(reason="Assertion error - reduction ops results mismatch")
xfail_issue_35926 = xfail_test(reason="RuntimeError: [NOT_IMPLEMENTED] Input image format I64 is "
"not supported yet...")
xfail_issue_35927 = xfail_test(reason="RuntimeError: B has zero dimension that is not allowable")
xfail_issue_35929 = xfail_test(reason="RuntimeError: Incorrect precision f64!")
xfail_issue_35930 = xfail_test(reason="onnx.onnx_cpp2py_export.checker.ValidationError: "
@ -200,3 +200,23 @@ xfail_issue_37957 = xfail_test(reason="RuntimeError: nGraph does not support the
"com.microsoft.CropAndResize, com.microsoft.GatherND,"
"com.microsoft.Pad, com.microsoft.Range")
xfail_issue_39669 = xfail_test(reason="AssertionError: This model has no test data")
xfail_issue_36534 = xfail_test(reason="RuntimeError: node input index is out of range")
xfail_issue_36535 = xfail_test(reason="RuntimeError: get_shape was called on a descriptor::Tensor "
"with dynamic shape")
xfail_issue_36536 = xfail_test(reason="RuntimeError: can't protect")
xfail_issue_36537 = xfail_test(reason="ngraph.exceptions.UserInputError: (Provided tensor's shape: "
"<value> does not match the expected: <value>")
xfail_issue_36538 = xfail_test(reason="RuntimeError: Check 'PartialShape::broadcast_merge_into( pshape, "
"node->get_input_partial_shape(i), autob)' failed at "
"/openvino/ngraph/src/ngraph/op/util/elementwise_args.cpp:48:")
xfail_issue_39656 = xfail_test(reason="RuntimeError: Reshape reshaped has dynamic second input!")
xfail_issue_39658 = xfail_test(reason="RuntimeError: Tile operation has a form that is not supported."
" z should be converted to TileIE operation.")
xfail_issue_39659 = xfail_test(reason="RuntimeError: Broadcast operation has a form that is not supported."
" y should be converted to Tile operation.")
xfail_issue_39661 = xfail_test(reason="RuntimeError: NonMaxSuppression operation has a form that is not "
"supported. selected_indices should be converted to "
"NonMaxSuppressionIE operation.")
xfail_issue_39662 = xfail_test(reason="RuntimeError: 'ScatterElementsUpdate' layer with name 'y' have "
"indices value that points to non-existing output tensor element")
xfail_issue_39663 = xfail_test(reason="RuntimeError: Unsupported primitive of type: ROIAlign name: Y")

9
ngraph/python/tests/runtime.py
View File

@ -23,6 +23,7 @@ from openvino.inference_engine import IECore, IENetwork
from ngraph.exceptions import UserInputError
from ngraph.impl import Function, Node, PartialShape
from ngraph.utils.types import NumericData, get_shape
import tests
log = logging.getLogger(__name__)
@ -38,6 +39,12 @@ def get_runtime():
return runtime(backend_name=tests.BACKEND_NAME)
def convert_i64_to_i32(cnn_network: IENetwork) -> None:
for cnn_input in cnn_network.input_info:
if cnn_network.input_info[cnn_input].precision == "I64":
cnn_network.input_info[cnn_input].precision = "I32"
class Runtime(object):
"""Represents an nGraph runtime environment."""
@ -98,6 +105,8 @@ class Computation(object):
cnn_network = IENetwork(capsule)
if self.function.is_dynamic():
cnn_network.reshape(dict(zip(param_names, input_shapes)))
# Convert inputs of the network from I64 to I32
convert_i64_to_i32(cnn_network)
self.network_cache[str(input_shapes)] = cnn_network
else:
cnn_network = self.network_cache[str(input_shapes)]

3
ngraph/python/tests/test_ngraph/test_basic.py
View File

@ -28,7 +28,6 @@ from tests.runtime import get_runtime
from tests.test_ngraph.util import run_op_node
from tests import (xfail_issue_34323,
xfail_issue_35929,
xfail_issue_35926,
xfail_issue_36476,
xfail_issue_36478,
xfail_issue_36479,
@ -69,7 +68,7 @@ def test_ngraph_function_api():
pytest.param(np.int8, marks=xfail_issue_36479),
np.int16,
np.int32,
pytest.param(np.int64, marks=xfail_issue_35926),
np.int64,
pytest.param(np.uint8, marks=xfail_issue_36479),
np.uint16,
pytest.param(np.uint32, marks=xfail_issue_36476),

4
ngraph/python/tests/test_ngraph/test_sequence_processing.py
View File

@ -18,7 +18,7 @@ import numpy as np
import ngraph as ng
from tests.runtime import get_runtime
from tests.test_ngraph.util import run_op_node
from tests import xfail_issue_36478, xfail_issue_35926
from tests import xfail_issue_36478, skip_issue_38084
def test_onehot():
@ -46,7 +46,7 @@ def test_one_hot():
assert np.allclose(result, excepted)
@xfail_issue_35926
@skip_issue_38084
def test_range():
start = 5
stop = 35

78
ngraph/python/tests/test_onnx/test_backend.py
View File

@ -25,12 +25,17 @@ import onnx.backend.test
from tests.test_onnx.utils.onnx_backend import OpenVinoTestBackend
from tests import (BACKEND_NAME,
skip_issue_38084,
xfail_issue_36535,
xfail_issue_39656,
xfail_issue_39658,
xfail_issue_39659,
xfail_issue_39661,
xfail_issue_39662,
xfail_issue_39663,
xfail_issue_33540,
xfail_issue_34314,
xfail_issue_35926,
xfail_issue_38084,
xfail_issue_33616,
xfail_issue_38085,
xfail_issue_38086,
xfail_issue_38087,
xfail_issue_35923,
@ -127,6 +132,21 @@ OnnxBackendPyTorchConvertedModelTest = None
globals().update(backend_test.enable_report().test_cases)
tests_expected_to_fail = [
(skip_issue_38084,
"OnnxBackendNodeModelTest.test_expand_dim_changed_cpu",
"OnnxBackendNodeModelTest.test_expand_dim_unchanged_cpu",
"OnnxBackendSimpleModelTest.test_expand_shape_model1_cpu",
"OnnxBackendSimpleModelTest.test_expand_shape_model2_cpu",
"OnnxBackendSimpleModelTest.test_expand_shape_model3_cpu",
"OnnxBackendSimpleModelTest.test_expand_shape_model4_cpu",
"OnnxBackendNodeModelTest.test_slice_default_axes_cpu",
"OnnxBackendNodeModelTest.test_top_k_cpu",
"OnnxBackendNodeModelTest.test_top_k_negative_axis_cpu",
"OnnxBackendNodeModelTest.test_top_k_smallest_cpu",
"OnnxBackendNodeModelTest.test_nonzero_example_cpu",
"OnnxBackendNodeModelTest.test_range_int32_type_negative_delta_cpu",
"OnnxBackendNodeModelTest.test_range_float_type_positive_delta_cpu",
"OnnxBackendNodeModelTest.test_upsample_nearest_cpu"),
(xfail_issue_34314,
"OnnxBackendNodeModelTest.test_rnn_seq_length_cpu",
"OnnxBackendNodeModelTest.test_simple_rnn_defaults_cpu",
@ -135,13 +155,11 @@ tests_expected_to_fail = [
"OnnxBackendNodeModelTest.test_gru_defaults_cpu",
"OnnxBackendNodeModelTest.test_gru_seq_length_cpu",
"OnnxBackendNodeModelTest.test_gru_with_initial_bias_cpu"),
(xfail_issue_35926,
"OnnxBackendNodeModelTest.test_expand_dim_changed_cpu",
"OnnxBackendNodeModelTest.test_expand_dim_unchanged_cpu",
"OnnxBackendSimpleModelTest.test_expand_shape_model1_cpu",
"OnnxBackendSimpleModelTest.test_expand_shape_model2_cpu",
"OnnxBackendSimpleModelTest.test_expand_shape_model3_cpu",
"OnnxBackendSimpleModelTest.test_expand_shape_model4_cpu",
(xfail_issue_36535,
"OnnxBackendNodeModelTest.test_constant_pad_cpu",
"OnnxBackendNodeModelTest.test_edge_pad_cpu",
"OnnxBackendNodeModelTest.test_reflect_pad_cpu"),
(xfail_issue_39656,
"OnnxBackendNodeModelTest.test_reshape_extended_dims_cpu",
"OnnxBackendNodeModelTest.test_reshape_negative_dim_cpu",
"OnnxBackendNodeModelTest.test_reshape_one_dim_cpu",
@ -150,13 +168,15 @@ tests_expected_to_fail = [
"OnnxBackendNodeModelTest.test_reshape_reordered_all_dims_cpu",
"OnnxBackendNodeModelTest.test_reshape_reordered_last_dims_cpu",
"OnnxBackendNodeModelTest.test_reshape_zero_and_negative_dim_cpu",
"OnnxBackendNodeModelTest.test_reshape_zero_dim_cpu",
"OnnxBackendNodeModelTest.test_reshape_zero_dim_cpu"),
(xfail_issue_39658,
"OnnxBackendNodeModelTest.test_tile_cpu",
"OnnxBackendNodeModelTest.test_tile_precomputed_cpu",
"OnnxBackendNodeModelTest.test_tile_precomputed_cpu"),
(xfail_issue_39659,
"OnnxBackendNodeModelTest.test_constantofshape_float_ones_cpu",
"OnnxBackendNodeModelTest.test_constantofshape_int_zeros_cpu",
"OnnxBackendNodeModelTest.test_scatter_with_axis_cpu",
"OnnxBackendNodeModelTest.test_scatter_without_axis_cpu",
"OnnxBackendNodeModelTest.test_constantofshape_int_shape_zero_cpu"),
(xfail_issue_39661,
"OnnxBackendNodeModelTest.test_nonmaxsuppression_center_point_box_format_cpu",
"OnnxBackendNodeModelTest.test_nonmaxsuppression_flipped_coordinates_cpu",
"OnnxBackendNodeModelTest.test_nonmaxsuppression_identical_boxes_cpu",
@ -165,12 +185,14 @@ tests_expected_to_fail = [
"OnnxBackendNodeModelTest.test_nonmaxsuppression_suppress_by_IOU_and_scores_cpu",
"OnnxBackendNodeModelTest.test_nonmaxsuppression_suppress_by_IOU_cpu",
"OnnxBackendNodeModelTest.test_nonmaxsuppression_two_batches_cpu",
"OnnxBackendNodeModelTest.test_nonmaxsuppression_two_classes_cpu"),
(xfail_issue_39663,
"OnnxBackendNodeModelTest.test_roialign_cpu"),
(xfail_issue_39662,
"OnnxBackendNodeModelTest.test_nonmaxsuppression_two_classes_cpu",
"OnnxBackendNodeModelTest.test_slice_default_axes_cpu",
"OnnxBackendNodeModelTest.test_roialign_cpu",
"OnnxBackendNodeModelTest.test_scatter_elements_with_axis_cpu",
"OnnxBackendNodeModelTest.test_scatter_elements_with_negative_indices_cpu",
"OnnxBackendNodeModelTest.test_scatter_elements_without_axis_cpu",
"OnnxBackendNodeModelTest.test_constant_pad_cpu",
"OnnxBackendNodeModelTest.test_edge_pad_cpu",
"OnnxBackendNodeModelTest.test_reflect_pad_cpu",
@ -178,34 +200,19 @@ tests_expected_to_fail = [
"OnnxBackendNodeModelTest.test_top_k_negative_axis_cpu",
"OnnxBackendNodeModelTest.test_top_k_smallest_cpu",
"OnnxBackendNodeModelTest.test_where_long_example_cpu",
"OnnxBackendNodeModelTest.test_gather_0_cpu",
"OnnxBackendNodeModelTest.test_gather_1_cpu",
"OnnxBackendNodeModelTest.test_mod_int64_fmod_cpu",
"OnnxBackendNodeModelTest.test_reversesequence_batch_cpu",
"OnnxBackendNodeModelTest.test_reversesequence_time_cpu",
"OnnxBackendPyTorchOperatorModelTest.test_operator_non_float_params_cpu",
"OnnxBackendPyTorchConvertedModelTest.test_Embedding_cpu",
"OnnxBackendPyTorchConvertedModelTest.test_Embedding_sparse_cpu",
"OnnxBackendNodeModelTest.test_constantofshape_int_shape_zero_cpu",
"OnnxBackendNodeModelTest.test_max_int64_cpu",
"OnnxBackendNodeModelTest.test_pow_types_float32_int64_cpu",
"OnnxBackendNodeModelTest.test_pow_types_float_cpu",
"OnnxBackendNodeModelTest.test_pow_types_int64_float32_cpu",
"OnnxBackendNodeModelTest.test_pow_types_int64_int64_cpu",
"OnnxBackendNodeModelTest.test_pow_types_int_cpu",
"OnnxBackendNodeModelTest.test_min_int64_cpu",
"OnnxBackendNodeModelTest.test_gather_negative_indices_cpu",
"OnnxBackendNodeModelTest.test_scatternd_cpu"),
(xfail_issue_38084,
"OnnxBackendNodeModelTest.test_nonzero_example_cpu",
"OnnxBackendNodeModelTest.test_range_int32_type_negative_delta_cpu",
"OnnxBackendNodeModelTest.test_range_float_type_positive_delta_cpu"),
"OnnxBackendNodeModelTest.test_gather_negative_indices_cpu"),
(xfail_issue_33616,
"OnnxBackendNodeModelTest.test_maxpool_2d_ceil_cpu",
"OnnxBackendNodeModelTest.test_maxpool_2d_dilations_cpu",
"OnnxBackendNodeModelTest.test_averagepool_2d_ceil_cpu"),
(xfail_issue_38085,
"OnnxBackendNodeModelTest.test_upsample_nearest_cpu"),
(xfail_issue_38086,
"OnnxBackendNodeModelTest.test_dynamicquantizelinear_min_adjusted_expanded_cpu",
"OnnxBackendNodeModelTest.test_dynamicquantizelinear_expanded_cpu",
@ -284,6 +291,12 @@ tests_expected_to_fail = [
(xfail_issue_38089,
"OnnxBackendPyTorchConvertedModelTest.test_GLU_dim_cpu"),
(xfail_issue_38090,
"OnnxBackendNodeModelTest.test_where_long_example_cpu",
"OnnxBackendNodeModelTest.test_mod_int64_fmod_cpu",
"OnnxBackendPyTorchOperatorModelTest.test_operator_non_float_params_cpu",
"OnnxBackendNodeModelTest.test_max_int64_cpu",
"OnnxBackendNodeModelTest.test_pow_types_int64_int64_cpu",
"OnnxBackendNodeModelTest.test_min_int64_cpu",
"OnnxBackendNodeModelTest.test_not_2d_cpu",
"OnnxBackendNodeModelTest.test_not_3d_cpu",
"OnnxBackendNodeModelTest.test_not_4d_cpu",
@ -342,6 +355,7 @@ tests_expected_to_fail = [
"OnnxBackendNodeModelTest.test_clip_default_int8_min_cpu",
"OnnxBackendNodeModelTest.test_clip_default_int8_max_cpu"),
(xfail_issue_38091,
"OnnxBackendNodeModelTest.test_gather_negative_indices_cpu",
"OnnxBackendNodeModelTest.test_round_cpu",
"OnnxBackendNodeModelTest.test_mvn_cpu",
"OnnxBackendNodeModelTest.test_elu_example_cpu"),

14
ngraph/python/tests/test_onnx/test_zoo_models.py
View File

@ -30,7 +30,7 @@ from tests import (
xfail_issue_39683,
xfail_issue_36533,
xfail_issue_39684,
xfail_issue_35926,
xfail_issue_34323,
xfail_issue_36537,
xfail_issue_39685,
xfail_issue_37957,
@ -139,11 +139,11 @@ if len(zoo_models) > 0:
(xfail_issue_36533, "test_onnx_model_zoo_vision_object_detection_segmentation_duc_model_ResNet101_DUC_7_ResNet101_DUC_HDC_ResNet101_DUC_HDC_cpu"),
(xfail_issue_36533, "test_onnx_model_zoo_vision_object_detection_segmentation_retinanet_model_retinanet_9_test_retinanet_resnet101_retinanet_9_cpu"),
(xfail_issue_39684, "test_onnx_model_zoo_vision_object_detection_segmentation_yolov4_model_yolov4_yolov4_yolov4_cpu"),
(xfail_issue_35926, "test_onnx_model_zoo_text_machine_comprehension_bert_squad_model_bertsquad_10_download_sample_10_bertsquad10_cpu"),
(xfail_issue_35926, "test_onnx_model_zoo_text_machine_comprehension_gpt_2_model_gpt2_10_GPT2_model_cpu"),
(xfail_issue_35926, "test_onnx_model_zoo_text_machine_comprehension_roberta_model_roberta_base_11_roberta_base_11_roberta_base_11_cpu"),
(xfail_issue_35926, "test_onnx_model_zoo_text_machine_comprehension_bert_squad_model_bertsquad_8_download_sample_8_bertsquad8_cpu"),
(xfail_issue_35926, "test_onnx_model_zoo_text_machine_comprehension_gpt_2_model_gpt2_lm_head_10_GPT_2_LM_HEAD_model_cpu"),
(xfail_issue_36533, "test_onnx_model_zoo_text_machine_comprehension_gpt_2_model_gpt2_10_GPT2_model_cpu"),
(xfail_issue_36533, "test_onnx_model_zoo_text_machine_comprehension_gpt_2_model_gpt2_lm_head_10_GPT_2_LM_HEAD_model_cpu"),
(xfail_issue_34323, "test_onnx_model_zoo_text_machine_comprehension_bert_squad_model_bertsquad_10_download_sample_10_bertsquad10_cpu"),
(xfail_issue_34323, "test_onnx_model_zoo_text_machine_comprehension_roberta_model_roberta_base_11_roberta_base_11_roberta_base_11_cpu"),
(xfail_issue_34323, "test_onnx_model_zoo_text_machine_comprehension_bert_squad_model_bertsquad_8_download_sample_8_bertsquad8_cpu"),
(xfail_issue_36537, "test_onnx_model_zoo_vision_classification_efficientnet_lite4_model_efficientnet_lite4_11_efficientnet_lite4_efficientnet_lite4_cpu"),
(xfail_issue_39685, "test_onnx_model_zoo_text_machine_comprehension_roberta_model_roberta_sequence_classification_9_roberta_sequence_classification_9_roberta_sequence_classification_9_cpu"),
(xfail_issue_39669, "test_onnx_model_zoo_text_machine_comprehension_t5_model_t5_encoder_12_t5_encoder_cpu"),
@ -186,7 +186,7 @@ if len(zoo_models) > 0:
(xfail_issue_38084, "test_MSFT_opset10_faster_rcnn_faster_rcnn_R_50_FPN_1x_cpu"),
(xfail_issue_39669, "test_MSFT_opset9_cgan_cgan_cpu"),
(xfail_issue_35926, "test_MSFT_opset10_BERT_Squad_bertsquad10_cpu"),
(xfail_issue_34323, "test_MSFT_opset10_BERT_Squad_bertsquad10_cpu"),
]
for test_case in import_xfail_list + execution_xfail_list:
xfail, test_name = test_case