add new model of MGP-STR (#21418)
* add new model of MGP-STR * fix the check failings * remove torch and numpy from mgp_tokenization * remove unused import from modeling_mgp_str * add test_processing_mgp_str * rm test_processing_mgp_str.py * add test_processing_mgp_str * add test_processing_mgp_str * add test_processing_mgp_str * rm test_processing_mgp_str and add softmax outs to model * rm test_processing_mgp_str and add softmax outs to model * rewrite the code of mgp-str according to PR suggestions * rewrite the code of mgp-str according to PR suggestions * add new model of MGP-STR * fix the check failings * remove torch and numpy from mgp_tokenization * remove unused import from modeling_mgp_str * add test_processing_mgp_str * rm test_processing_mgp_str.py * add test_processing_mgp_str * add test_processing_mgp_str * add test_processing_mgp_str * rm test_processing_mgp_str and add softmax outs to model * rewrite the code of mgp-str according to PR suggestions * rewrite the code of mgp-str according to PR suggestions * remove representation_size from MGPSTRConfig * reformat configuration_mgp_str.py * format test_processor_mgp_str.py * add test for tokenizer and complete model/processer test and model file * rm Unnecessary tupple in modeling_mgp_str * reduce hidden_size/layers/label_size in test_model * add integration tests and change MGPSTR to Mgpstr * add test for logit values * reformat test model file --------- Co-authored-by: yue kun <yuekun.wp@alibaba-inc.com>
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@@ -95,6 +95,7 @@ IGNORE_NON_TESTED = PRIVATE_MODELS.copy() + [
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"M2M100Encoder", # Building part of bigger (tested) model.
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"M2M100Decoder", # Building part of bigger (tested) model.
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"MCTCTEncoder", # Building part of bigger (tested) model.
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"MgpstrModel", # Building part of bigger (tested) model.
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"Speech2TextEncoder", # Building part of bigger (tested) model.
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"Speech2TextDecoder", # Building part of bigger (tested) model.
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"LEDEncoder", # Building part of bigger (tested) model.
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@@ -269,6 +270,7 @@ IGNORE_NON_AUTO_CONFIGURED = PRIVATE_MODELS.copy() + [
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"LukeForEntityClassification",
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"LukeForEntityPairClassification",
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"LukeForEntitySpanClassification",
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"MgpstrModel",
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"OpenAIGPTDoubleHeadsModel",
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"OwlViTTextModel",
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"OwlViTVisionModel",
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