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GPTNeoForQuestionAnswering (#23057)

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* first draft - gives index error in question_answering.py

* maturing

* no labels

* pipeline should know about QA

* fixing checks

* formatting

* fixed docstring

* initial commit

* formatting

* adding the class to many places

* towards less unhappy checks

* nearly there

* Update src/transformers/models/gpt_neo/modeling_gpt_neo.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* avoid error

* moving to device of star/end_logits

---------

Co-authored-by: Prof. Peter Schneider-Kamp <jps@ordbogen.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
This commit is contained in:
peter-sk
2023-05-03 21:59:19 +02:00
committed by GitHub
parent b6933d76d2
commit 78b7debf56
9 changed files with 146 additions and 4 deletions
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25
tests/models/gpt_neo/test_modeling_gpt_neo.py
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@@ -34,6 +34,7 @@ if is_torch_available():
GPT_NEO_PRETRAINED_MODEL_ARCHIVE_LIST,
GPT2Tokenizer,
GPTNeoForCausalLM,
GPTNeoForQuestionAnswering,
GPTNeoForSequenceClassification,
GPTNeoForTokenClassification,
GPTNeoModel,
@@ -325,6 +326,17 @@ class GPTNeoModelTester:
self.parent.assertEqual(result.loss.shape, ())
self.parent.assertEqual(result.logits.shape, (self.batch_size, self.seq_length, self.vocab_size))
def create_and_check_gpt_neo_for_question_answering(
self, config, input_ids, input_mask, head_mask, token_type_ids, mc_token_ids, sequence_labels, *args
):
config.num_labels = self.num_labels
model = GPTNeoForQuestionAnswering(config)
model.to(torch_device)
model.eval()
result = model(input_ids, attention_mask=input_mask, token_type_ids=token_type_ids)
self.parent.assertEqual(result.start_logits.shape, (self.batch_size, self.seq_length))
self.parent.assertEqual(result.end_logits.shape, (self.batch_size, self.seq_length))
def create_and_check_gpt_neo_for_sequence_classification(
self, config, input_ids, input_mask, head_mask, token_type_ids, mc_token_ids, sequence_labels, *args
):
@@ -385,7 +397,13 @@ class GPTNeoModelTester:
@require_torch
class GPTNeoModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin, unittest.TestCase):
all_model_classes = (
(GPTNeoModel, GPTNeoForCausalLM, GPTNeoForSequenceClassification, GPTNeoForTokenClassification)
(
GPTNeoModel,
GPTNeoForCausalLM,
GPTNeoForQuestionAnswering,
GPTNeoForSequenceClassification,
GPTNeoForTokenClassification,
)
if is_torch_available()
else ()
)
@@ -393,6 +411,7 @@ class GPTNeoModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMix
pipeline_model_mapping = (
{
"feature-extraction": GPTNeoModel,
"question-answering": GPTNeoForQuestionAnswering,
"text-classification": GPTNeoForSequenceClassification,
"token-classification": GPTNeoForTokenClassification,
"text-generation": GPTNeoForCausalLM,
@@ -438,6 +457,10 @@ class GPTNeoModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMix
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_lm_head_model(*config_and_inputs)
def test_gpt_neo_question_answering_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_gpt_neo_for_question_answering(*config_and_inputs)
def test_gpt_neo_sequence_classification_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_gpt_neo_for_sequence_classification(*config_and_inputs)