Add backend tests to ONNX OpenVino CI (#1972)
This commit is contained in:
Rafal Blaczkowski
GitHub
parent
6d2424ddcf
commit
706d2fe7c8
@ -31,9 +31,14 @@ def xfail_test(reason="Mark the test as expected to fail", strict=True):
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return pytest.mark.xfail(reason=reason, strict=strict)
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xfail_issue_34314 = xfail_test(reason="RuntimeError: RNNCell operation has a form that is not "
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"supported.RNNCell_21204 should be converted to RNNCellIE operation")
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skip_segfault = pytest.mark.skip(reason="Segmentation fault error")
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xfail_issue_33540 = xfail_test(reason="RuntimeError: GRUCell operation has a form that is not supported "
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"GRUCell_<number> should be converted to GRUCellIE operation")
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xfail_issue_33616 = xfail_test(reason="Add ceil_mode for Max and Avg pooling (reference implementation)")
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xfail_issue_34310 = xfail_test(reason="RuntimeError: Error of validate layer: LSTMSequence_<number> with "
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"type: LSTMSequence. Layer is not instance of RNNLayer class")
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xfail_issue_34314 = xfail_test(reason="RuntimeError: RNNCell operation has a form that is not "
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"supported.RNNCell_<number> should be converted to RNNCellIE operation")
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xfail_issue_34323 = xfail_test(reason="RuntimeError: data [value] doesn't exist")
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xfail_issue_34327 = xfail_test(reason="RuntimeError: '<value>' layer has different "
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"IN and OUT channels number")
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@ -59,11 +64,11 @@ xfail_issue_35925 = xfail_test(reason="Assertion error - reduction ops results m
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xfail_issue_35926 = xfail_test(reason="RuntimeError: [NOT_IMPLEMENTED] Input image format I64 is "
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"not supported yet...")
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xfail_issue_35927 = xfail_test(reason="RuntimeError: B has zero dimension that is not allowable")
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xfail_issue_35929 = xfail_test(reason="CRuntimeError: Incorrect precision f64!")
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xfail_issue_35929 = xfail_test(reason="RuntimeError: Incorrect precision f64!")
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xfail_issue_35930 = xfail_test(reason="onnx.onnx_cpp2py_export.checker.ValidationError: "
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"Required attribute 'to' is missing.")
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xfail_issue_35932 = xfail_test(reason="Assertion error - logsoftmax results mismatch")
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xfail_issue_36437 = xfail_test(reason="RuntimeError: Cannot find blob with name: y")
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xfail_issue_36437 = xfail_test(reason="RuntimeError: Cannot find blob with name: <value>")
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xfail_issue_36476 = xfail_test(reason="RuntimeError: [NOT_IMPLEMENTED] Input image format U32 is "
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"not supported yet...")
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xfail_issue_36478 = xfail_test(reason="RuntimeError: [NOT_IMPLEMENTED] Input image format U64 is "
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@ -74,13 +79,112 @@ xfail_issue_36480 = xfail_test(reason="RuntimeError: [NOT_FOUND] Unsupported pro
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xfail_issue_36481 = xfail_test(reason="TypeError: _get_node_factory() takes from 0 to 1 positional "
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"arguments but 2 were given")
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xfail_issue_36483 = xfail_test(reason="RuntimeError: Unsupported primitive of type: "
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"Ceiling name: Ceiling_22669")
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"Ceiling name: <value>")
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xfail_issue_36485 = xfail_test(reason="RuntimeError: Check 'm_group >= 1' failed at "
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"/openvino/ngraph/core/src/op/shuffle_channels.cpp:77:")
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xfail_issue_36486 = xfail_test(reason="RuntimeError: HardSigmoid operation should be converted "
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"to HardSigmoid_IE")
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xfail_issue_36487 = xfail_test(reason="Assertion error - mvn operator computation mismatch")
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xfail_issue_38084 = xfail_test(reason="RuntimeError: AssertionFailed: layer->get_output_partial_shape(i) "
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"is_static() nGraph NonZero operation with name: result cannot be"
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"converted to NonZero layer with name: result because output"
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"with index 0 contains dynamic shapes: {2,?}. Try to use "
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"CNNNetwork::reshape() method in order to specialize shapes "
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"before the conversion.")
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xfail_issue_38085 = xfail_test(reason="RuntimeError: Interpolate operation should be converted to Interp")
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xfail_issue_38086 = xfail_test(reason="RuntimeError: Quantize layer input '<value>' doesn't have blobs")
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xfail_issue_38087 = xfail_test(reason="RuntimeError: Cannot cast to tensor desc. Format is unsupported!")
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xfail_issue_38088 = xfail_test(reason="RuntimeError: Check '((axis >= axis_range_min) && "
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"(axis <= axis_range_max))' failed at "
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"/openvino/ngraph/core/src/validation_util.cpp:913: "
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"Split Parameter axis <value> out of the tensor rank range <value>.")
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xfail_issue_38089 = xfail_test(reason="RuntimeError: Node 2 contains empty child edge for index 0")
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xfail_issue_38090 = xfail_test(reason="AssertionError: Items types are not equal")
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xfail_issue_38091 = xfail_test(reason="AssertionError: Mismatched elements")
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xfail_issue_38699 = xfail_test(reason="RuntimeError: nGraph does not support the following ONNX operations:"
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"ai.onnx.preview.training.Gradient")
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xfail_issue_38700 = xfail_test(reason="RuntimeError: nGraph does not support different sequence operations:"
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"ConcatFromSequence, SequenceConstruct, SequenceAt, SplitToSequence,"
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"SequenceEmpty, SequenceInsert, SequenceErase, SequenceLength ")
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xfail_issue_38701 = xfail_test(reason="RuntimeError: unsupported element type: STRING")
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xfail_issue_38702 = xfail_test(reason="RuntimeError: nGraph does not support the following ONNX operations:"
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"Unique")
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xfail_issue_38704 = xfail_test(reason="RuntimeError: nGraph does not support the following ONNX operations:"
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"TfIdfVectorizer")
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xfail_issue_38705 = xfail_test(reason="IndexError: deque::_M_range_check: __n (which is 0)"
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">= this->size() (which is 0)")
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xfail_issue_38706 = xfail_test(reason="RuntimeError: output_3.0 has zero dimension which is not allowed")
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xfail_issue_38707 = xfail_test(reason="RuntimeError: nGraph does not support the following ONNX operations:"
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"SoftmaxCrossEntropyLoss")
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xfail_issue_38708 = xfail_test(reason="RuntimeError: While validating ONNX node '<Node(Slice): y>': "
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"Axes input must be constant")
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xfail_issue_38709 = xfail_test(reason="RuntimeError: nGraph does not support the following ONNX operations:"
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"Scan")
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xfail_issue_38710 = xfail_test(reason="RuntimeError: roi has zero dimension which is not allowed")
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xfail_issue_38711 = xfail_test(reason="RuntimeError: nGraph does not support the following ONNX operations:"
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"GatherElements")
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xfail_issue_38712 = xfail_test(reason="RuntimeError: Check '(fmod == 1) "
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"While validating ONNX node '<Node(Mod): z>': "
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"Only 'fmod=1' mode is supported for mod operator.")
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xfail_issue_38713 = xfail_test(reason="RuntimeError: nGraph does not support the following ONNX operations:"
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"ai.onnx.preview.training.Momentum")
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xfail_issue_38714 = xfail_test(reason="RuntimeError: While validating ONNX node '<Node(Resize): Y>'"
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"Check 'element::Type::merge(element_type, element_type,"
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"node->get_input_element_type(i))' "
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"While validating node 'v1::<name> (sizes[0]:i64{4},"
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"Convert_29306[0]:f32{4}) -> (dynamic?)' with friendly_name '<name>':"
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"Argument element types are inconsistent.")
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xfail_issue_38715 = xfail_test(reason="RuntimeError: While validating ONNX node '<Node(OneHot): y>':"
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"While validating node 'v1::OneHot OneHot_<number>"
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"(Convert_13525[0]:i64{3}, depth[0]:f32{},"
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"Squeeze_13532[0]:i32{}, Squeeze_13529[0]:i32{}) -> (dynamic?)'"
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"with friendly_name 'OneHot_13534':"
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"Depth must be integral element type.")
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xfail_issue_38716 = xfail_test(reason="RuntimeError: nGraph does not support the following ONNX operations:"
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"MaxUnpool")
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xfail_issue_38717 = xfail_test(reason="RuntimeError: nGraph does not support the following ONNX operations:"
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"GreaterOrEqual")
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xfail_issue_38718 = xfail_test(reason="nGraph does not support the following ONNX operations:"
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"IsNaN and isInf")
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xfail_issue_38719 = xfail_test(reason="nGraph does not support the following ONNX operations: GatherND")
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xfail_issue_38720 = xfail_test(reason="nGraph does not support the following ONNX operations:"
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"DynamicQuantizeLinear")
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xfail_issue_38721 = xfail_test(reason="RuntimeError: While validating ONNX node '<Node(Pow): z>': "
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"While validating node 'v1::Power Power_<number>"
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"(x[0]:f32{3}, y[0]:i64{3}) -> (dynamic?)' with friendly_name "
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"'Power_<number>': Argument element types are inconsistent.")
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xfail_issue_38722 = xfail_test(reason="RuntimeError: While validating ONNX nodes MatMulInteger"
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"and QLinearMatMul"
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"Input0 scale and input0 zero point shape must be same and 1")
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xfail_issue_38723 = xfail_test(reason="RuntimeError: nGraph does not support the following ONNX operations:"
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"QLinearConv")
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xfail_issue_38724 = xfail_test(reason="RuntimeError: While validating ONNX node '<Node(Resize): Y>':"
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"tf_crop_and_resize - this type of coordinate transformation mode"
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"is not supported. Choose one of the following modes:"
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"tf_half_pixel_for_nn, asymmetric, align_corners, pytorch_half_pixel,"
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"half_pixel")
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xfail_issue_38725 = xfail_test(reason="RuntimeError: While validating ONNX node '<Node(Loop):"
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"value info has no element type specified")
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xfail_issue_38726 = xfail_test(reason="RuntimeError: nGraph does not support the following ONNX operations:"
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"LessOrEqual")
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xfail_issue_38727 = xfail_test(reason="RuntimeError: nGraph does not support the following ONNX operations:"
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"Einsum")
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xfail_issue_38728 = xfail_test(reason="RuntimeError: nGraph does not support the following ONNX operations:"
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"Det")
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xfail_issue_38729 = xfail_test(reason="RuntimeError: nGraph does not support the following ONNX operations:"
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"Compress")
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xfail_issue_38731 = xfail_test(reason="RuntimeError: nGraph does not support the following ONNX operations:"
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"BitShift")
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xfail_issue_38732 = xfail_test(reason="RuntimeError: nGraph does not support the following ONNX operations:"
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"ConvInteger")
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xfail_issue_38733 = xfail_test(reason="RuntimeError: nGraph does not support the following ONNX operations:"
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"Celu")
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xfail_issue_38734 = xfail_test(reason="RuntimeError: nGraph does not support the following ONNX operations:"
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"ai.onnx.preview.training.Adam")
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xfail_issue_38735 = xfail_test(reason="RuntimeError: nGraph does not support the following ONNX operations:"
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"ai.onnx.preview.training.Adagrad")
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xfail_issue_38736 = xfail_test(reason="RuntimeError: nGraph does not support the following ONNX operations:"
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"NegativeLogLikelihoodLoss")
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# Model Zoo issues:
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xfail_issue_36533 = xfail_test(reason="AssertionError: zoo models results mismatch")
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693
ngraph/python/tests/test_onnx/test_backend.py
Normal file
693
ngraph/python/tests/test_onnx/test_backend.py
Normal file
@ -0,0 +1,693 @@
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# ******************************************************************************
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# Copyright 2018-2020 Intel Corporation
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ******************************************************************************
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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import logging
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import onnx.backend.test
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from tests.test_onnx.utils.onnx_backend import OpenVinoTestBackend
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from tests import (BACKEND_NAME,
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xfail_issue_33540,
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xfail_issue_34314,
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xfail_issue_35926,
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xfail_issue_38084,
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xfail_issue_33616,
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xfail_issue_38085,
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xfail_issue_38086,
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xfail_issue_38087,
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xfail_issue_35893,
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xfail_issue_35923,
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xfail_issue_35914,
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xfail_issue_36483,
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xfail_issue_34323,
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xfail_issue_35915,
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xfail_issue_34310,
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xfail_issue_36476,
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xfail_issue_36478,
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xfail_issue_36437,
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xfail_issue_38088,
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xfail_issue_38089,
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xfail_issue_38090,
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xfail_issue_38091,
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xfail_issue_35929,
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xfail_issue_38699,
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xfail_issue_38700,
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xfail_issue_38701,
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xfail_issue_38702,
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xfail_issue_38704,
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xfail_issue_38705,
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xfail_issue_38706,
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xfail_issue_38736,
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xfail_issue_38707,
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xfail_issue_38708,
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xfail_issue_38709,
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xfail_issue_38710,
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xfail_issue_38711,
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xfail_issue_38712,
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xfail_issue_38713,
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xfail_issue_38714,
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xfail_issue_38715,
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xfail_issue_38716,
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xfail_issue_38717,
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xfail_issue_38718,
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xfail_issue_38719,
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xfail_issue_38720,
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xfail_issue_38721,
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xfail_issue_38722,
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xfail_issue_38723,
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xfail_issue_38724,
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xfail_issue_38725,
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xfail_issue_38726,
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xfail_issue_38727,
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xfail_issue_38728,
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xfail_issue_38729,
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xfail_issue_38731,
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xfail_issue_38732,
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xfail_issue_38733,
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xfail_issue_38734,
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xfail_issue_38735)
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def expect_fail(test_case_path, xfail): # type: (str) -> None
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"""Mark the test as expected to fail."""
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module_name, test_name = test_case_path.split(".")
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module = globals().get(module_name)
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if hasattr(module, test_name):
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xfail(getattr(module, test_name))
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else:
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logging.getLogger().warning("Could not mark test as XFAIL, not found: %s", test_case_path)
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OpenVinoTestBackend.backend_name = BACKEND_NAME
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# This is a pytest magic variable to load extra plugins
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# Uncomment the line below to enable the ONNX compatibility report
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# pytest_plugins = "onnx.backend.test.report",
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# import all test cases at global scope to make them visible to python.unittest
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backend_test = onnx.backend.test.BackendTest(OpenVinoTestBackend, __name__)
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skip_tests_general = [
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# Big model tests (see test_zoo_models.py):
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"test_bvlc_alexnet",
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"test_densenet121",
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"test_inception_v1",
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"test_inception_v2",
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"test_resnet50",
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"test_shufflenet",
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"test_squeezenet",
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"test_vgg19",
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"test_zfnet512",
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]
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for test in skip_tests_general:
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backend_test.exclude(test)
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# NOTE: ALL backend_test.exclude CALLS MUST BE PERFORMED BEFORE THE CALL TO globals().update
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OnnxBackendNodeModelTest = None
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OnnxBackendSimpleModelTest = None
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OnnxBackendPyTorchOperatorModelTest = None
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OnnxBackendPyTorchConvertedModelTest = None
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globals().update(backend_test.enable_report().test_cases)
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tests_expected_to_fail = [
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(xfail_issue_34314,
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"OnnxBackendNodeModelTest.test_rnn_seq_length_cpu",
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"OnnxBackendNodeModelTest.test_simple_rnn_defaults_cpu",
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"OnnxBackendNodeModelTest.test_simple_rnn_with_initial_bias_cpu"),
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(xfail_issue_33540,
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"OnnxBackendNodeModelTest.test_gru_defaults_cpu",
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"OnnxBackendNodeModelTest.test_gru_seq_length_cpu",
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"OnnxBackendNodeModelTest.test_gru_with_initial_bias_cpu"),
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(xfail_issue_35926,
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"OnnxBackendNodeModelTest.test_expand_dim_changed_cpu",
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"OnnxBackendNodeModelTest.test_expand_dim_unchanged_cpu",
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"OnnxBackendSimpleModelTest.test_expand_shape_model1_cpu",
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"OnnxBackendSimpleModelTest.test_expand_shape_model2_cpu",
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"OnnxBackendSimpleModelTest.test_expand_shape_model3_cpu",
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"OnnxBackendSimpleModelTest.test_expand_shape_model4_cpu",
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"OnnxBackendNodeModelTest.test_reshape_extended_dims_cpu",
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"OnnxBackendNodeModelTest.test_reshape_negative_dim_cpu",
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"OnnxBackendNodeModelTest.test_reshape_one_dim_cpu",
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"OnnxBackendNodeModelTest.test_reshape_reduced_dims_cpu",
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"OnnxBackendNodeModelTest.test_reshape_negative_extended_dims_cpu",
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"OnnxBackendNodeModelTest.test_reshape_reordered_all_dims_cpu",
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"OnnxBackendNodeModelTest.test_reshape_reordered_last_dims_cpu",
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"OnnxBackendNodeModelTest.test_reshape_zero_and_negative_dim_cpu",
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"OnnxBackendNodeModelTest.test_reshape_zero_dim_cpu",
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"OnnxBackendNodeModelTest.test_tile_cpu",
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"OnnxBackendNodeModelTest.test_tile_precomputed_cpu",
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"OnnxBackendNodeModelTest.test_constantofshape_float_ones_cpu",
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"OnnxBackendNodeModelTest.test_constantofshape_int_zeros_cpu",
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"OnnxBackendNodeModelTest.test_scatter_with_axis_cpu",
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"OnnxBackendNodeModelTest.test_scatter_without_axis_cpu",
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"OnnxBackendNodeModelTest.test_nonmaxsuppression_center_point_box_format_cpu",
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"OnnxBackendNodeModelTest.test_nonmaxsuppression_flipped_coordinates_cpu",
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"OnnxBackendNodeModelTest.test_nonmaxsuppression_identical_boxes_cpu",
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"OnnxBackendNodeModelTest.test_nonmaxsuppression_limit_output_size_cpu",
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"OnnxBackendNodeModelTest.test_nonmaxsuppression_single_box_cpu",
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"OnnxBackendNodeModelTest.test_nonmaxsuppression_suppress_by_IOU_and_scores_cpu",
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"OnnxBackendNodeModelTest.test_nonmaxsuppression_suppress_by_IOU_cpu",
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"OnnxBackendNodeModelTest.test_nonmaxsuppression_two_batches_cpu",
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"OnnxBackendNodeModelTest.test_nonmaxsuppression_two_classes_cpu",
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"OnnxBackendNodeModelTest.test_slice_default_axes_cpu",
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"OnnxBackendNodeModelTest.test_roialign_cpu",
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"OnnxBackendNodeModelTest.test_scatter_elements_with_axis_cpu",
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"OnnxBackendNodeModelTest.test_scatter_elements_with_negative_indices_cpu",
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"OnnxBackendNodeModelTest.test_scatter_elements_without_axis_cpu",
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"OnnxBackendNodeModelTest.test_constant_pad_cpu",
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"OnnxBackendNodeModelTest.test_edge_pad_cpu",
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"OnnxBackendNodeModelTest.test_reflect_pad_cpu",
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"OnnxBackendNodeModelTest.test_top_k_cpu",
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"OnnxBackendNodeModelTest.test_top_k_negative_axis_cpu",
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"OnnxBackendNodeModelTest.test_top_k_smallest_cpu",
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"OnnxBackendNodeModelTest.test_where_long_example_cpu",
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"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_int64_int64_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"),
|
||||
(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",
|
||||
"OnnxBackendNodeModelTest.test_dynamicquantizelinear_max_adjusted_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_quantizelinear_cpu"),
|
||||
(xfail_issue_38087,
|
||||
"OnnxBackendNodeModelTest.test_convtranspose_1d_cpu"),
|
||||
(xfail_issue_35893,
|
||||
"OnnxBackendNodeModelTest.test_convtranspose_3d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_convtranspose_cpu",
|
||||
"OnnxBackendNodeModelTest.test_convtranspose_dilations_cpu",
|
||||
"OnnxBackendNodeModelTest.test_convtranspose_kernel_shape_cpu",
|
||||
"OnnxBackendNodeModelTest.test_convtranspose_output_shape_cpu",
|
||||
"OnnxBackendNodeModelTest.test_convtranspose_pad_cpu",
|
||||
"OnnxBackendNodeModelTest.test_convtranspose_pads_cpu",
|
||||
"OnnxBackendNodeModelTest.test_convtranspose_with_kernel_cpu",
|
||||
"OnnxBackendNodeModelTest.test_instancenorm_example_cpu",
|
||||
"OnnxBackendNodeModelTest.test_basic_conv_without_padding_cpu",
|
||||
"OnnxBackendNodeModelTest.test_batchnorm_epsilon_cpu",
|
||||
"OnnxBackendNodeModelTest.test_batchnorm_example_cpu",
|
||||
"OnnxBackendNodeModelTest.test_conv_with_strides_and_asymmetric_padding_cpu",
|
||||
"OnnxBackendNodeModelTest.test_conv_with_strides_no_padding_cpu",
|
||||
"OnnxBackendNodeModelTest.test_conv_with_strides_padding_cpu",
|
||||
"OnnxBackendNodeModelTest.test_instancenorm_epsilon_cpu",
|
||||
"OnnxBackendNodeModelTest.test_basic_conv_with_padding_cpu"),
|
||||
(xfail_issue_35923,
|
||||
"OnnxBackendNodeModelTest.test_prelu_broadcast_cpu",
|
||||
"OnnxBackendNodeModelTest.test_prelu_example_cpu"),
|
||||
(xfail_issue_35914,
|
||||
"OnnxBackendNodeModelTest.test_dequantizelinear_cpu",
|
||||
"OnnxBackendNodeModelTest.test_pow_bcast_scalar_cpu",
|
||||
"OnnxBackendNodeModelTest.test_clip_example_cpu",
|
||||
"OnnxBackendNodeModelTest.test_clip_inbounds_cpu",
|
||||
"OnnxBackendNodeModelTest.test_clip_outbounds_cpu",
|
||||
"OnnxBackendNodeModelTest.test_clip_default_int8_min_cpu",
|
||||
"OnnxBackendNodeModelTest.test_clip_default_int8_max_cpu",
|
||||
"OnnxBackendNodeModelTest.test_gemm_default_scalar_bias_cpu",
|
||||
"OnnxBackendNodeModelTest.test_clip_cpu",
|
||||
"OnnxBackendNodeModelTest.test_clip_default_max_cpu",
|
||||
"OnnxBackendNodeModelTest.test_clip_default_min_cpu",
|
||||
"OnnxBackendNodeModelTest.test_clip_splitbounds_cpu"),
|
||||
(xfail_issue_36483,
|
||||
"OnnxBackendNodeModelTest.test_ceil_cpu",
|
||||
"OnnxBackendNodeModelTest.test_ceil_example_cpu"),
|
||||
(xfail_issue_34323,
|
||||
"OnnxBackendNodeModelTest.test_constant_cpu",
|
||||
"OnnxBackendNodeModelTest.test_dropout_default_cpu",
|
||||
"OnnxBackendNodeModelTest.test_eyelike_populate_off_main_diagonal_cpu",
|
||||
"OnnxBackendNodeModelTest.test_eyelike_without_dtype_cpu",
|
||||
"OnnxBackendNodeModelTest.test_max_one_input_cpu",
|
||||
"OnnxBackendNodeModelTest.test_min_one_input_cpu",
|
||||
"OnnxBackendNodeModelTest.test_shape_cpu",
|
||||
"OnnxBackendNodeModelTest.test_shape_example_cpu",
|
||||
"OnnxBackendNodeModelTest.test_size_cpu",
|
||||
"OnnxBackendNodeModelTest.test_size_example_cpu",
|
||||
"OnnxBackendNodeModelTest.test_sum_one_input_cpu",
|
||||
"OnnxBackendNodeModelTest.test_dropout_default_ratio_cpu",
|
||||
"OnnxBackendNodeModelTest.test_dropout_default_old_cpu",
|
||||
"OnnxBackendNodeModelTest.test_dropout_random_old_cpu",
|
||||
"OnnxBackendNodeModelTest.test_training_dropout_default_cpu",
|
||||
"OnnxBackendNodeModelTest.test_training_dropout_zero_ratio_cpu",
|
||||
"OnnxBackendNodeModelTest.test_training_dropout_cpu"),
|
||||
(xfail_issue_35915,
|
||||
"OnnxBackendNodeModelTest.test_equal_bcast_cpu",
|
||||
"OnnxBackendNodeModelTest.test_equal_cpu",
|
||||
"OnnxBackendNodeModelTest.test_min_int16_cpu",
|
||||
"OnnxBackendNodeModelTest.test_min_uint8_cpu"),
|
||||
(xfail_issue_34310,
|
||||
"OnnxBackendNodeModelTest.test_lstm_defaults_cpu",
|
||||
"OnnxBackendNodeModelTest.test_lstm_with_initial_bias_cpu",
|
||||
"OnnxBackendNodeModelTest.test_lstm_with_peepholes_cpu"),
|
||||
(xfail_issue_36476,
|
||||
"OnnxBackendNodeModelTest.test_max_uint32_cpu",
|
||||
"OnnxBackendNodeModelTest.test_min_uint32_cpu"),
|
||||
(xfail_issue_36478,
|
||||
"OnnxBackendNodeModelTest.test_max_uint64_cpu",
|
||||
"OnnxBackendNodeModelTest.test_min_uint64_cpu"),
|
||||
(xfail_issue_36437,
|
||||
"OnnxBackendNodeModelTest.test_argmax_default_axis_example_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmax_default_axis_random_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmax_keepdims_example_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmax_keepdims_random_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmax_negative_axis_keepdims_example_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmax_negative_axis_keepdims_random_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmin_default_axis_example_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmin_default_axis_random_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmin_keepdims_example_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmin_keepdims_random_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmin_negative_axis_keepdims_example_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmin_negative_axis_keepdims_random_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmax_keepdims_random_select_last_index_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmax_negative_axis_keepdims_example_select_last_index_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmax_keepdims_example_select_last_index_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmin_default_axis_random_select_last_index_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmin_default_axis_example_select_last_index_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmax_default_axis_random_select_last_index_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmax_default_axis_example_select_last_index_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmax_negative_axis_keepdims_random_select_last_index_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmin_negative_axis_keepdims_random_select_last_index_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmin_negative_axis_keepdims_example_select_last_index_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmin_keepdims_example_select_last_index_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmin_keepdims_random_select_last_index_cpu"),
|
||||
(xfail_issue_38088,
|
||||
"OnnxBackendPyTorchConvertedModelTest.test_GLU_cpu"),
|
||||
(xfail_issue_38089,
|
||||
"OnnxBackendPyTorchConvertedModelTest.test_GLU_dim_cpu"),
|
||||
(xfail_issue_38090,
|
||||
"OnnxBackendNodeModelTest.test_not_2d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_not_3d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_not_4d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_or2d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_or3d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_or4d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_or_bcast3v1d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_or_bcast3v2d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_or_bcast4v2d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_or_bcast4v3d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_or_bcast4v4d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_xor2d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_xor3d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_xor4d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_xor_bcast3v1d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_xor_bcast3v2d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_xor_bcast4v2d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_xor_bcast4v3d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_xor_bcast4v4d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_greater_equal_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_less_equal_bcast_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_max_int16_cpu",
|
||||
"OnnxBackendNodeModelTest.test_max_uint16_cpu",
|
||||
"OnnxBackendNodeModelTest.test_less_equal_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_max_int8_cpu",
|
||||
"OnnxBackendNodeModelTest.test_max_uint8_cpu",
|
||||
"OnnxBackendNodeModelTest.test_maxpool_2d_uint8_cpu",
|
||||
"OnnxBackendNodeModelTest.test_min_float16_cpu",
|
||||
"OnnxBackendNodeModelTest.test_greater_equal_bcast_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_min_uint16_cpu",
|
||||
"OnnxBackendNodeModelTest.test_max_float16_cpu",
|
||||
"OnnxBackendNodeModelTest.test_min_int8_cpu",
|
||||
"OnnxBackendNodeModelTest.test_greater_bcast_cpu",
|
||||
"OnnxBackendNodeModelTest.test_greater_cpu",
|
||||
"OnnxBackendNodeModelTest.test_less_bcast_cpu",
|
||||
"OnnxBackendNodeModelTest.test_less_cpu",
|
||||
"OnnxBackendNodeModelTest.test_mod_mixed_sign_float16_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmax_no_keepdims_example_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmax_no_keepdims_random_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmin_no_keepdims_random_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmax_no_keepdims_random_select_last_index_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmax_no_keepdims_example_select_last_index_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmin_no_keepdims_example_select_last_index_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmin_no_keepdims_random_select_last_index_cpu",
|
||||
"OnnxBackendNodeModelTest.test_cast_FLOAT_to_FLOAT16_cpu",
|
||||
"OnnxBackendNodeModelTest.test_and3d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_and4d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_and_bcast3v1d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_and_bcast3v2d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_and_bcast4v2d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_and_bcast4v3d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_and_bcast4v4d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_argmin_no_keepdims_example_cpu",
|
||||
"OnnxBackendNodeModelTest.test_clip_default_int8_inbounds_cpu",
|
||||
"OnnxBackendNodeModelTest.test_and2d_cpu"),
|
||||
(xfail_issue_38091,
|
||||
"OnnxBackendNodeModelTest.test_round_cpu",
|
||||
"OnnxBackendNodeModelTest.test_mvn_cpu",
|
||||
"OnnxBackendNodeModelTest.test_elu_example_cpu",
|
||||
"OnnxBackendNodeModelTest.test_logsoftmax_axis_0_cpu",
|
||||
"OnnxBackendNodeModelTest.test_logsoftmax_axis_1_cpu",
|
||||
"OnnxBackendNodeModelTest.test_logsoftmax_default_axis_cpu"),
|
||||
(xfail_issue_35929,
|
||||
"OnnxBackendPyTorchOperatorModelTest.test_operator_add_size1_broadcast_cpu",
|
||||
"OnnxBackendPyTorchOperatorModelTest.test_operator_add_size1_singleton_broadcast_cpu",
|
||||
"OnnxBackendPyTorchOperatorModelTest.test_operator_add_broadcast_cpu",
|
||||
"OnnxBackendPyTorchOperatorModelTest.test_operator_addconstant_cpu",
|
||||
"OnnxBackendPyTorchOperatorModelTest.test_operator_add_size1_right_broadcast_cpu",
|
||||
"OnnxBackendNodeModelTest.test_cast_DOUBLE_to_FLOAT_cpu",
|
||||
"OnnxBackendNodeModelTest.test_cast_FLOAT16_to_DOUBLE_cpu",
|
||||
"OnnxBackendNodeModelTest.test_cast_DOUBLE_to_FLOAT16_cpu",
|
||||
"OnnxBackendNodeModelTest.test_cumsum_1d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_cast_FLOAT_to_DOUBLE_cpu",
|
||||
"OnnxBackendNodeModelTest.test_cumsum_1d_reverse_cpu",
|
||||
"OnnxBackendNodeModelTest.test_cumsum_1d_exclusive_cpu",
|
||||
"OnnxBackendNodeModelTest.test_cumsum_1d_reverse_exclusive_cpu",
|
||||
"OnnxBackendNodeModelTest.test_cumsum_2d_axis_0_cpu",
|
||||
"OnnxBackendNodeModelTest.test_cumsum_2d_negative_axis_cpu",
|
||||
"OnnxBackendNodeModelTest.test_eyelike_with_dtype_cpu",
|
||||
"OnnxBackendNodeModelTest.test_cumsum_2d_axis_1_cpu",
|
||||
"OnnxBackendNodeModelTest.test_mod_mixed_sign_float64_cpu",
|
||||
"OnnxBackendNodeModelTest.test_max_float64_cpu",
|
||||
"OnnxBackendNodeModelTest.test_min_float64_cpu"),
|
||||
(xfail_issue_38699,
|
||||
"OnnxBackendSimpleModelTest.test_gradient_of_add_and_mul_cpu",
|
||||
"OnnxBackendSimpleModelTest.test_gradient_of_add_cpu"),
|
||||
(xfail_issue_38700,
|
||||
"OnnxBackendSimpleModelTest.test_sequence_model5_cpu",
|
||||
"OnnxBackendSimpleModelTest.test_sequence_model7_cpu",
|
||||
"OnnxBackendSimpleModelTest.test_sequence_model1_cpu",
|
||||
"OnnxBackendSimpleModelTest.test_sequence_model3_cpu",
|
||||
"OnnxBackendSimpleModelTest.test_sequence_model6_cpu",
|
||||
"OnnxBackendSimpleModelTest.test_sequence_model8_cpu",
|
||||
"OnnxBackendSimpleModelTest.test_sequence_model4_cpu",
|
||||
"OnnxBackendSimpleModelTest.test_sequence_model2_cpu"),
|
||||
(xfail_issue_38701,
|
||||
"OnnxBackendSimpleModelTest.test_strnorm_model_monday_casesensintive_nochangecase_cpu",
|
||||
"OnnxBackendSimpleModelTest.test_strnorm_model_nostopwords_nochangecase_cpu",
|
||||
"OnnxBackendSimpleModelTest.test_strnorm_model_monday_empty_output_cpu",
|
||||
"OnnxBackendSimpleModelTest.test_strnorm_model_monday_insensintive_upper_twodim_cpu",
|
||||
"OnnxBackendSimpleModelTest.test_strnorm_model_monday_casesensintive_lower_cpu",
|
||||
"OnnxBackendSimpleModelTest.test_strnorm_model_monday_casesensintive_upper_cpu",
|
||||
"OnnxBackendNodeModelTest.test_strnormalizer_nostopwords_nochangecase_cpu",
|
||||
"OnnxBackendNodeModelTest.test_strnormalizer_export_monday_casesensintive_nochangecase_cpu",
|
||||
"OnnxBackendNodeModelTest.test_strnormalizer_export_monday_insensintive_upper_twodim_cpu",
|
||||
"OnnxBackendNodeModelTest.test_strnormalizer_export_monday_casesensintive_lower_cpu",
|
||||
"OnnxBackendNodeModelTest.test_strnormalizer_export_monday_empty_output_cpu",
|
||||
"OnnxBackendNodeModelTest.test_strnormalizer_export_monday_casesensintive_upper_cpu",
|
||||
"OnnxBackendNodeModelTest.test_cast_STRING_to_FLOAT_cpu",
|
||||
"OnnxBackendNodeModelTest.test_cast_FLOAT_to_STRING_cpu"),
|
||||
(xfail_issue_38702,
|
||||
"OnnxBackendNodeModelTest.test_unique_not_sorted_without_axis_cpu",
|
||||
"OnnxBackendNodeModelTest.test_unique_sorted_with_negative_axis_cpu",
|
||||
"OnnxBackendNodeModelTest.test_unique_sorted_with_axis_cpu",
|
||||
"OnnxBackendNodeModelTest.test_unique_sorted_with_axis_3d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_unique_sorted_without_axis_cpu"),
|
||||
(xfail_issue_38704,
|
||||
"OnnxBackendNodeModelTest.test_tfidfvectorizer_tf_batch_onlybigrams_skip5_cpu",
|
||||
"OnnxBackendNodeModelTest.test_tfidfvectorizer_tf_onlybigrams_levelempty_cpu",
|
||||
"OnnxBackendNodeModelTest.test_tfidfvectorizer_tf_batch_onlybigrams_skip0_cpu",
|
||||
"OnnxBackendNodeModelTest.test_tfidfvectorizer_tf_uniandbigrams_skip5_cpu",
|
||||
"OnnxBackendNodeModelTest.test_tfidfvectorizer_tf_only_bigrams_skip0_cpu",
|
||||
"OnnxBackendNodeModelTest.test_tfidfvectorizer_tf_batch_uniandbigrams_skip5_cpu",
|
||||
"OnnxBackendNodeModelTest.test_tfidfvectorizer_tf_onlybigrams_skip5_cpu"),
|
||||
(xfail_issue_38705,
|
||||
"OnnxBackendNodeModelTest.test_training_dropout_mask_cpu",
|
||||
"OnnxBackendNodeModelTest.test_training_dropout_default_mask_cpu",
|
||||
"OnnxBackendNodeModelTest.test_training_dropout_zero_ratio_mask_cpu",
|
||||
"OnnxBackendNodeModelTest.test_maxpool_with_argmax_2d_precomputed_strides_cpu",
|
||||
"OnnxBackendNodeModelTest.test_maxpool_with_argmax_2d_precomputed_pads_cpu",
|
||||
"OnnxBackendNodeModelTest.test_dropout_default_mask_cpu",
|
||||
"OnnxBackendNodeModelTest.test_dropout_default_mask_ratio_cpu"),
|
||||
(xfail_issue_38706,
|
||||
"OnnxBackendNodeModelTest.test_split_zero_size_splits_cpu"),
|
||||
(xfail_issue_38736,
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_sum_log_prob_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_none_no_weight_log_prob_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_sum_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_input_shape_is_NCd1d2d3_sum_weight_high_ignore_index_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_no_weight_ignore_index_3d_log_prob_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_no_weight_ignore_index_4d_log_prob_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_input_shape_is_NCd1_mean_weight_negative_ignore_index_log_prob_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_weight_ignore_index_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_none_weights_log_prob_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_none_weights_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_none_log_prob_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_input_shape_is_NCd1_mean_weight_negative_ignore_index_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_no_weight_ignore_index_4d_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_weight_log_prob_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_no_weight_ignore_index_log_prob_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_none_no_weight_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_weight_ignore_index_4d_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_3d_log_prob_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_weight_ignore_index_4d_log_prob_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_weight_ignore_index_log_prob_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_weight_ignore_index_3d_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_weight_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_none_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_input_shape_is_NCd1d2d3_none_no_weight_negative_ignore_index_log_prob_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_mean_weight_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_input_shape_is_NCd1d2d3_sum_weight_high_ignore_index_log_prob_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_weight_ignore_index_3d_log_prob_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_no_weight_ignore_index_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_log_prob_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_3d_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_no_weight_ignore_index_3d_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_input_shape_is_NCd1d2d3_none_no_weight_negative_ignore_index_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_mean_weight_log_prob_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2d3_sum_weight_high_ignore_index_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2_with_weight_reduction_mean_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2d3d4d5_none_no_weight_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2d3d4d5_mean_weight_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2d3_none_no_weight_negative_ignore_index_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2_with_weight_reduction_sum_ignore_index_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2_with_weight_cpu",
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2_with_weight_reduction_sum_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2_reduction_sum_cpu",
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2_reduction_mean_cpu",
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2_no_weight_reduction_mean_ignore_index_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2_cpu",
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1_weight_cpu",
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1_mean_weight_negative_ignore_index_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1_ignore_index_cpu",
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1_cpu",
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NC_cpu",
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_iinput_shape_is_NCd1_weight_ignore_index_cpu"), # noqa
|
||||
(xfail_issue_38707,
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_none_weights_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_sum_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_weight_ignore_index_log_prob_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_none_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_weight_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_weight_ignore_index_4d_log_prob_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_weight_ignore_index_3d_log_prob_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_sum_log_prob_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_none_log_prob_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_none_weights_log_prob_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_no_weight_ignore_index_log_prob_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_no_weight_ignore_index_4d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_no_weight_ignore_index_3d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_weight_log_prob_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_mean_weight_log_prob_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_weight_ignore_index_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_no_weight_ignore_index_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_weight_ignore_index_4d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_input_shape_is_NCd1d2d3_none_no_weight_negative_ignore_index_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_weight_ignore_index_3d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_mean_weight_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_no_weight_ignore_index_4d_log_prob_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_no_weight_ignore_index_3d_log_prob_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_log_prob_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_input_shape_is_NCd1d2d3_sum_weight_high_ignore_index_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_none_no_weight_log_prob_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_3d_log_prob_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_input_shape_is_NCd1_mean_weight_negative_ignore_index_log_prob_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_input_shape_is_NCd1d2d3_none_no_weight_negative_ignore_index_log_prob_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_mean_3d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_input_shape_is_NCd1d2d3d4d5_none_no_weight_cpu",
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_input_shape_is_NCd1d2d3_sum_weight_high_ignore_index_log_prob_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_softmax_cross_entropy_input_shape_is_NCd1_mean_weight_negative_ignore_index_cpu"), # noqa
|
||||
(xfail_issue_38708,
|
||||
"OnnxBackendNodeModelTest.test_slice_default_steps_cpu",
|
||||
"OnnxBackendNodeModelTest.test_slice_negative_axes_cpu",
|
||||
"OnnxBackendNodeModelTest.test_slice_neg_steps_cpu",
|
||||
"OnnxBackendNodeModelTest.test_slice_neg_cpu",
|
||||
"OnnxBackendNodeModelTest.test_slice_cpu",
|
||||
"OnnxBackendNodeModelTest.test_slice_end_out_of_bounds_cpu",
|
||||
"OnnxBackendNodeModelTest.test_slice_start_out_of_bounds_cpu"),
|
||||
(xfail_issue_38709,
|
||||
"OnnxBackendNodeModelTest.test_scan_sum_cpu",
|
||||
"OnnxBackendNodeModelTest.test_scan9_sum_cpu"),
|
||||
(xfail_issue_38710,
|
||||
"OnnxBackendNodeModelTest.test_resize_downsample_scales_linear_align_corners_cpu",
|
||||
"OnnxBackendNodeModelTest.test_resize_upsample_scales_cubic_cpu",
|
||||
"OnnxBackendNodeModelTest.test_resize_downsample_scales_cubic_cpu",
|
||||
"OnnxBackendNodeModelTest.test_resize_downsample_scales_cubic_align_corners_cpu",
|
||||
"OnnxBackendNodeModelTest.test_resize_upsample_scales_nearest_cpu",
|
||||
"OnnxBackendNodeModelTest.test_resize_upsample_scales_cubic_asymmetric_cpu",
|
||||
"OnnxBackendNodeModelTest.test_resize_downsample_scales_cubic_A_n0p5_exclude_outside_cpu",
|
||||
"OnnxBackendNodeModelTest.test_resize_upsample_scales_linear_cpu",
|
||||
"OnnxBackendNodeModelTest.test_resize_upsample_scales_cubic_align_corners_cpu",
|
||||
"OnnxBackendNodeModelTest.test_resize_upsample_scales_linear_align_corners_cpu",
|
||||
"OnnxBackendNodeModelTest.test_resize_upsample_scales_cubic_A_n0p5_exclude_outside_cpu",
|
||||
"OnnxBackendNodeModelTest.test_resize_downsample_scales_nearest_cpu",
|
||||
"OnnxBackendNodeModelTest.test_resize_downsample_scales_linear_cpu"),
|
||||
(xfail_issue_38711,
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2_no_weight_reduction_mean_ignore_index_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1_ignore_index_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1_weight_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2d3_none_no_weight_negative_ignore_index_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1_mean_weight_negative_ignore_index_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2d3d4d5_none_no_weight_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2_with_weight_reduction_sum_ignore_index_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2d3d4d5_mean_weight_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2_with_weight_reduction_sum_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NC_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2d3_sum_weight_high_ignore_index_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_iinput_shape_is_NCd1_weight_ignore_index_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2_with_weight_reduction_mean_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2_with_weight_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2_reduction_sum_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_negative_log_likelihood_loss_input_shape_is_NCd1d2_reduction_mean_expanded_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_gather_elements_0_cpu",
|
||||
"OnnxBackendNodeModelTest.test_gather_elements_negative_indices_cpu",
|
||||
"OnnxBackendNodeModelTest.test_gather_elements_1_cpu"),
|
||||
(xfail_issue_38712,
|
||||
"OnnxBackendNodeModelTest.test_mod_mixed_sign_int16_cpu",
|
||||
"OnnxBackendNodeModelTest.test_mod_uint8_cpu",
|
||||
"OnnxBackendNodeModelTest.test_mod_uint64_cpu",
|
||||
"OnnxBackendNodeModelTest.test_mod_uint32_cpu",
|
||||
"OnnxBackendNodeModelTest.test_mod_uint16_cpu",
|
||||
"OnnxBackendNodeModelTest.test_mod_mixed_sign_int8_cpu",
|
||||
"OnnxBackendNodeModelTest.test_mod_mixed_sign_int64_cpu",
|
||||
"OnnxBackendNodeModelTest.test_mod_broadcast_cpu",
|
||||
"OnnxBackendNodeModelTest.test_mod_mixed_sign_int32_cpu"),
|
||||
(xfail_issue_38713,
|
||||
"OnnxBackendNodeModelTest.test_momentum_cpu",
|
||||
"OnnxBackendNodeModelTest.test_nesterov_momentum_cpu",
|
||||
"OnnxBackendNodeModelTest.test_momentum_multiple_cpu"),
|
||||
(xfail_issue_38714,
|
||||
"OnnxBackendNodeModelTest.test_resize_upsample_sizes_nearest_ceil_half_pixel_cpu",
|
||||
"OnnxBackendNodeModelTest.test_resize_downsample_sizes_nearest_tf_half_pixel_for_nn_cpu",
|
||||
"OnnxBackendNodeModelTest.test_resize_upsample_sizes_cubic_cpu",
|
||||
"OnnxBackendNodeModelTest.test_resize_downsample_sizes_nearest_cpu",
|
||||
"OnnxBackendNodeModelTest.test_resize_downsample_sizes_linear_pytorch_half_pixel_cpu",
|
||||
"OnnxBackendNodeModelTest.test_resize_downsample_sizes_cubic_cpu",
|
||||
"OnnxBackendNodeModelTest.test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric_cpu", # noqa
|
||||
"OnnxBackendNodeModelTest.test_resize_upsample_sizes_nearest_floor_align_corners_cpu",
|
||||
"OnnxBackendNodeModelTest.test_resize_upsample_sizes_nearest_cpu"),
|
||||
(xfail_issue_38715,
|
||||
"OnnxBackendNodeModelTest.test_onehot_without_axis_cpu",
|
||||
"OnnxBackendNodeModelTest.test_onehot_with_negative_axis_cpu",
|
||||
"OnnxBackendNodeModelTest.test_onehot_with_axis_cpu",
|
||||
"OnnxBackendNodeModelTest.test_onehot_negative_indices_cpu"),
|
||||
(xfail_issue_38716,
|
||||
"OnnxBackendNodeModelTest.test_maxunpool_export_with_output_shape_cpu",
|
||||
"OnnxBackendNodeModelTest.test_maxunpool_export_without_output_shape_cpu"),
|
||||
(xfail_issue_38717,
|
||||
"OnnxBackendNodeModelTest.test_greater_equal_bcast_cpu",
|
||||
"OnnxBackendNodeModelTest.test_greater_equal_cpu"),
|
||||
(xfail_issue_38718,
|
||||
"OnnxBackendNodeModelTest.test_isnan_cpu",
|
||||
"OnnxBackendNodeModelTest.test_isinf_positive_cpu",
|
||||
"OnnxBackendNodeModelTest.test_isinf_negative_cpu",
|
||||
"OnnxBackendNodeModelTest.test_isinf_cpu"),
|
||||
(xfail_issue_38719,
|
||||
"OnnxBackendNodeModelTest.test_gathernd_example_int32_cpu",
|
||||
"OnnxBackendNodeModelTest.test_gathernd_example_float32_cpu",
|
||||
"OnnxBackendNodeModelTest.test_gathernd_example_int32_batch_dim1_cpu"),
|
||||
(xfail_issue_38720,
|
||||
"OnnxBackendNodeModelTest.test_dynamicquantizelinear_min_adjusted_cpu",
|
||||
"OnnxBackendNodeModelTest.test_dynamicquantizelinear_cpu",
|
||||
"OnnxBackendNodeModelTest.test_dynamicquantizelinear_max_adjusted_cpu"),
|
||||
(xfail_issue_38721,
|
||||
"OnnxBackendNodeModelTest.test_pow_types_int_cpu",
|
||||
"OnnxBackendNodeModelTest.test_pow_types_int64_float32_cpu",
|
||||
"OnnxBackendNodeModelTest.test_pow_types_int32_float32_cpu",
|
||||
"OnnxBackendNodeModelTest.test_pow_types_float_cpu",
|
||||
"OnnxBackendNodeModelTest.test_pow_types_float32_uint64_cpu",
|
||||
"OnnxBackendNodeModelTest.test_pow_types_float32_uint32_cpu",
|
||||
"OnnxBackendNodeModelTest.test_pow_types_float32_int64_cpu",
|
||||
"OnnxBackendNodeModelTest.test_pow_types_float32_int32_cpu"),
|
||||
(xfail_issue_38722,
|
||||
"OnnxBackendNodeModelTest.test_matmulinteger_cpu",
|
||||
"OnnxBackendNodeModelTest.test_qlinearmatmul_2D_cpu",
|
||||
"OnnxBackendNodeModelTest.test_qlinearmatmul_3D_cpu"),
|
||||
(xfail_issue_38723,
|
||||
"OnnxBackendNodeModelTest.test_qlinearconv_cpu"),
|
||||
(xfail_issue_38724,
|
||||
"OnnxBackendNodeModelTest.test_resize_tf_crop_and_resize_cpu"),
|
||||
(xfail_issue_38725,
|
||||
"OnnxBackendNodeModelTest.test_range_int32_type_negative_delta_expanded_cpu",
|
||||
"OnnxBackendNodeModelTest.test_range_float_type_positive_delta_expanded_cpu"),
|
||||
(xfail_issue_38726,
|
||||
"OnnxBackendNodeModelTest.test_less_equal_cpu",
|
||||
"OnnxBackendNodeModelTest.test_less_equal_bcast_cpu"),
|
||||
(xfail_issue_38727,
|
||||
"OnnxBackendNodeModelTest.test_einsum_transpose_cpu",
|
||||
"OnnxBackendNodeModelTest.test_einsum_batch_diagonal_cpu",
|
||||
"OnnxBackendNodeModelTest.test_einsum_batch_matmul_cpu",
|
||||
"OnnxBackendNodeModelTest.test_einsum_sum_cpu",
|
||||
"OnnxBackendNodeModelTest.test_einsum_inner_prod_cpu"),
|
||||
(xfail_issue_38728,
|
||||
"OnnxBackendNodeModelTest.test_det_2d_cpu",
|
||||
"OnnxBackendNodeModelTest.test_det_nd_cpu"),
|
||||
(xfail_issue_38729,
|
||||
"OnnxBackendNodeModelTest.test_compress_negative_axis_cpu",
|
||||
"OnnxBackendNodeModelTest.test_compress_default_axis_cpu",
|
||||
"OnnxBackendNodeModelTest.test_compress_1_cpu",
|
||||
"OnnxBackendNodeModelTest.test_compress_0_cpu"),
|
||||
(xfail_issue_38731,
|
||||
"OnnxBackendNodeModelTest.test_bitshift_left_uint8_cpu",
|
||||
"OnnxBackendNodeModelTest.test_bitshift_right_uint64_cpu",
|
||||
"OnnxBackendNodeModelTest.test_bitshift_right_uint16_cpu",
|
||||
"OnnxBackendNodeModelTest.test_bitshift_right_uint32_cpu",
|
||||
"OnnxBackendNodeModelTest.test_bitshift_right_uint8_cpu",
|
||||
"OnnxBackendNodeModelTest.test_bitshift_left_uint32_cpu",
|
||||
"OnnxBackendNodeModelTest.test_bitshift_left_uint16_cpu",
|
||||
"OnnxBackendNodeModelTest.test_bitshift_left_uint64_cpu"),
|
||||
(xfail_issue_38732,
|
||||
"OnnxBackendNodeModelTest.test_convinteger_with_padding_cpu",
|
||||
"OnnxBackendNodeModelTest.test_basic_convinteger_cpu"),
|
||||
(xfail_issue_38733,
|
||||
"OnnxBackendNodeModelTest.test_celu_cpu"),
|
||||
(xfail_issue_38734,
|
||||
"OnnxBackendNodeModelTest.test_adam_multiple_cpu",
|
||||
"OnnxBackendNodeModelTest.test_adam_cpu"),
|
||||
(xfail_issue_38735,
|
||||
"OnnxBackendNodeModelTest.test_adagrad_multiple_cpu",
|
||||
"OnnxBackendNodeModelTest.test_adagrad_cpu")
|
||||
]
|
||||
|
||||
for test_group in tests_expected_to_fail:
|
||||
for test_case in test_group[1:]:
|
||||
expect_fail("{}".format(test_case), test_group[0])
|
||||
@ -128,6 +128,19 @@ class OpenVinoOnnxBackend(Backend):
|
||||
return device != "CUDA"
|
||||
|
||||
|
||||
class OpenVinoTestBackend(OpenVinoOnnxBackend):
|
||||
@classmethod
|
||||
def is_compatible(
|
||||
cls,
|
||||
model, # type: onnx.ModelProto
|
||||
device="CPU", # type: Text
|
||||
**kwargs # type: Any
|
||||
): # type: (...) -> bool
|
||||
# Return whether the model is compatible with the backend.
|
||||
import_onnx_model(model)
|
||||
return True
|
||||
|
||||
|
||||
prepare = OpenVinoOnnxBackend.prepare
|
||||
run_model = OpenVinoOnnxBackend.run_model
|
||||
run_node = OpenVinoOnnxBackend.run_node
|
||||
|
||||
@ -27,7 +27,7 @@ commands=
|
||||
flake8 {posargs:src/ setup.py}
|
||||
flake8 --ignore=D100,D101,D102,D103,D104,D105,D107,W503 tests/ # ignore lack of docs in tests
|
||||
mypy --config-file=tox.ini {posargs:src/}
|
||||
pytest --backend={env:NGRAPH_BACKEND} tests -v -n 20
|
||||
pytest --backend={env:NGRAPH_BACKEND} tests -v -n 20 -k 'not _cuda'
|
||||
|
||||
[testenv:devenv]
|
||||
envdir = devenv
|
||||
|
||||
Loading…
Reference in New Issue
Block a user