Extended error messages (#13647)
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464e0aae72
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@ -1022,7 +1022,7 @@ const ov::AnyMap& ov::Model::get_map_from_attr(const ov::Any& info) const {
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std::shared_ptr<ov::Meta> meta = info.as<std::shared_ptr<ov::Meta>>();
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return *info.as<std::shared_ptr<ov::Meta>>();
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}
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throw ov::Exception("Cannot get rt attribute. Keys are incorrect.");
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throw ov::Exception("Cannot get runtime attribute. Path to runtime attribute is incorrect.");
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}
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ov::AnyMap& ov::Model::get_map_from_attr(ov::Any& info) const {
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@ -1038,7 +1038,7 @@ ov::AnyMap& ov::Model::get_map_from_attr(ov::Any& info) const {
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std::shared_ptr<ov::Meta> meta = info.as<std::shared_ptr<ov::Meta>>();
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return *info.as<std::shared_ptr<ov::Meta>>();
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}
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throw ov::Exception("Cannot get rt attribute. Keys are incorrect.");
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throw ov::Exception("Cannot get runtime attribute. Path to runtime attribute is incorrect.");
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}
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const ov::Any& ov::Model::get_attr(const ov::Any& info) const {
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@ -53,7 +53,8 @@ bool evaluate(const HostTensorPtr& arg0,
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arg1->get_shape(),
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arg2->get_shape());
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} else {
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throw ngraph_error("Unexpected type");
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throw ov::Exception(std::string("Unexpected type ") + arg1->get_element_type().c_type_string() +
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" for ScatterNDUpdate evaluate method.");
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}
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return true;
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@ -108,7 +108,8 @@ bool evaluate(const ngraph::HostTensorPtr& arg0,
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axis,
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batch_dims);
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} else {
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throw ov::Exception("Unexpected type");
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throw ov::Exception(std::string("Unexpected type ") + arg1->get_element_type().c_type_string() +
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" for Gather evaluate method.");
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}
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return true;
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@ -239,10 +239,10 @@ public:
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<config value="{ 'compression': { 'algorithms': [ { 'name': 'DefaultQuantization', 'params': { 'num_samples_for_tuning': 2000, 'preset': 'performance', 'stat_subset_size': 300, 'use_layerwise_tuning': false } } ], 'dump_intermediate_model': true, 'target_device': 'ANY' }, 'engine': { 'models': [ { 'name': 'bert-small-uncased-whole-word-masking-squad-0001', 'launchers': [ { 'framework': 'openvino', 'adapter': { 'type': 'bert_question_answering', 'start_token_logits_output': 'output_s', 'end_token_logits_output': 'output_e' }, 'inputs': [ { 'name': 'input_ids', 'type': 'INPUT', 'value': 'input_ids' }, { 'name': 'attention_mask', 'type': 'INPUT', 'value': 'input_mask' }, { 'name': 'token_type_ids', 'type': 'INPUT', 'value': 'segment_ids' } ], 'device': 'cpu' } ], 'datasets': [ { 'name': 'squad_v1_1_msl384_mql64_ds128_lowercase', 'annotation_conversion': { 'converter': 'squad', 'testing_file': 'PATH', 'max_seq_length': 384, 'max_query_length': 64, 'doc_stride': 128, 'lower_case': true, 'vocab_file': 'PATH' }, 'reader': { 'type': 'annotation_features_extractor', 'features': [ 'input_ids', 'input_mask', 'segment_ids' ] }, 'postprocessing': [ { 'type': 'extract_answers_tokens', 'max_answer': 30, 'n_best_size': 20 } ], 'metrics': [ { 'name': 'F1', 'type': 'f1', 'reference': 0.9157 }, { 'name': 'EM', 'type': 'exact_match', 'reference': 0.8504 } ], '_command_line_mapping': { 'testing_file': 'PATH', 'vocab_file': [ 'PATH' ] } } ] } ], 'stat_requests_number': null, 'eval_requests_number': null, 'type': 'accuracy_checker' } }" />
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<version value="invalid version" />
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</optimization>
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<framework>
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<batch value="1"/>
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<chunk_size value="16"/>
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</framework>
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<framework>
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<batch value="1"/>
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<chunk_size value="16"/>
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</framework>
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</rt_info>
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</net>
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)V0G0N";
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