def test_dataset_from_dicts_qa_inference(caplog=None): if caplog: caplog.set_level(logging.CRITICAL) models = [ "deepset/roberta-base-squad2", "deepset/bert-base-cased-squad2", "deepset/xlm-roberta-large-squad2", "deepset/minilm-uncased-squad2", "deepset/electra-base-squad2", ] sample_types = [ "answer-wrong", "answer-offset-wrong", "noanswer", "vanilla" ] for model in models: tokenizer = Tokenizer.load(pretrained_model_name_or_path=model, use_fast=True) processor = SquadProcessor(tokenizer, max_seq_len=256, data_dir=None) for sample_type in sample_types: dicts = processor.file_to_dicts(f"samples/qa/{sample_type}.json") dataset, tensor_names, problematic_sample_ids, baskets = processor.dataset_from_dicts( dicts, indices=[1], return_baskets=True) assert tensor_names == [ 'input_ids', 'padding_mask', 'segment_ids', 'passage_start_t', 'start_of_word', 'labels', 'id', 'seq_2_start_t', 'span_mask' ], f"Processing for {model} has changed." assert len(problematic_sample_ids ) == 0, f"Processing for {model} has changed." assert baskets[ 0].id_external == '5ad3d560604f3c001a3ff2c8', f"Processing for {model} has changed." assert baskets[ 0].id_internal == '1-0', f"Processing for {model} has changed." # roberta if model == "deepset/roberta-base-squad2": assert len(baskets[0].samples[0].tokenized["passage_tokens"] ) == 6, f"Processing for {model} has changed." assert len(baskets[0].samples[0].tokenized["question_tokens"] ) == 7, f"Processing for {model} has changed." if sample_type == "noanswer": assert baskets[0].samples[0].features[0]["input_ids"][:13] == \ [0, 6179, 171, 82, 697, 11, 2201, 116, 2, 2, 26795, 2614, 34], \ f"Processing for {model} and {sample_type}-testsample has changed." else: assert baskets[0].samples[0].features[0]["input_ids"][:13] == \ [0, 6179, 171, 82, 697, 11, 5459, 116, 2, 2, 26795, 2614, 34], \ f"Processing for {model} and {sample_type}-testsample has changed." # bert if model == "deepset/bert-base-cased-squad2": assert len(baskets[0].samples[0].tokenized["passage_tokens"] ) == 5, f"Processing for {model} has changed." assert len(baskets[0].samples[0].tokenized["question_tokens"] ) == 7, f"Processing for {model} has changed." if sample_type == "noanswer": assert baskets[0].samples[0].features[0]["input_ids"][:10] == \ [101, 1731, 1242, 1234, 1686, 1107, 2123, 136, 102, 3206], \ f"Processing for {model} and {sample_type}-testsample has changed." else: assert baskets[0].samples[0].features[0]["input_ids"][:10] == \ [101, 1731, 1242, 1234, 1686, 1107, 3206, 136, 102, 3206], \ f"Processing for {model} and {sample_type}-testsample has changed." # xlm-roberta if model == "deepset/xlm-roberta-large-squad2": assert len(baskets[0].samples[0].tokenized["passage_tokens"] ) == 7, f"Processing for {model} has changed." assert len(baskets[0].samples[0].tokenized["question_tokens"] ) == 7, f"Processing for {model} has changed." if sample_type == "noanswer": assert baskets[0].samples[0].features[0]["input_ids"][:12] == \ [0, 11249, 5941, 3395, 6867, 23, 7270, 32, 2, 2, 10271, 1556], \ f"Processing for {model} and {sample_type}-testsample has changed." else: assert baskets[0].samples[0].features[0]["input_ids"][:12] == \ [0, 11249, 5941, 3395, 6867, 23, 10271, 32, 2, 2, 10271, 1556], \ f"Processing for {model} and {sample_type}-testsample has changed." # minilm and electra have same vocab + tokenizer if model == "deepset/minilm-uncased-squad2" or model == "deepset/electra-base-squad2": assert len(baskets[0].samples[0].tokenized["passage_tokens"] ) == 5, f"Processing for {model} has changed." assert len(baskets[0].samples[0].tokenized["question_tokens"] ) == 7, f"Processing for {model} has changed." if sample_type == "noanswer": assert baskets[0].samples[0].features[0]["input_ids"][:10] == \ [101, 2129, 2116, 2111, 2444, 1999, 3000, 1029, 102, 4068], \ f"Processing for {model} and {sample_type}-testsample has changed." else: assert baskets[0].samples[0].features[0]["input_ids"][:10] == \ [101, 2129, 2116, 2111, 2444, 1999, 4068, 1029, 102, 4068], \ f"Processing for {model} and {sample_type}-testsample has changed."
def test_dataset_from_dicts_qa_labelconversion(caplog=None): if caplog: caplog.set_level(logging.CRITICAL) models = [ "deepset/roberta-base-squad2", "deepset/bert-base-cased-squad2", "deepset/xlm-roberta-large-squad2", "deepset/minilm-uncased-squad2", "deepset/electra-base-squad2", ] sample_types = [ "answer-wrong", "answer-offset-wrong", "noanswer", "vanilla" ] for model in models: tokenizer = Tokenizer.load(pretrained_model_name_or_path=model, use_fast=True) processor = SquadProcessor(tokenizer, max_seq_len=256, data_dir=None) for sample_type in sample_types: dicts = processor.file_to_dicts(f"samples/qa/{sample_type}.json") dataset, tensor_names, problematic_sample_ids = processor.dataset_from_dicts( dicts, indices=[1], return_baskets=False) if sample_type == "answer-wrong" or sample_type == "answer-offset-wrong": assert len( problematic_sample_ids ) == 1, f"Processing labels for {model} has changed." if sample_type == "noanswer": assert list(dataset.tensors[tensor_names.index( "labels")].numpy()[0, 0, :]) == [ 0, 0 ], f"Processing labels for {model} has changed." assert list(dataset.tensors[ tensor_names.index("labels")].numpy()[0, 1, :]) == [ -1, -1 ], f"Processing labels for {model} has changed." if sample_type == "vanilla": # roberta if model == "deepset/roberta-base-squad2": assert list(dataset.tensors[ tensor_names.index("labels")].numpy()[0, 0, :]) == [ 13, 13 ], f"Processing labels for {model} has changed." assert list(dataset.tensors[ tensor_names.index("labels")].numpy()[0, 1, :]) == [ 13, 14 ], f"Processing labels for {model} has changed." # bert, minilm, electra if model == "deepset/bert-base-cased-squad2" or model == "deepset/minilm-uncased-squad2" or model == "deepset/electra-base-squad2": assert list(dataset.tensors[ tensor_names.index("labels")].numpy()[0, 0, :]) == [ 11, 11 ], f"Processing labels for {model} has changed." # xlm-roberta if model == "deepset/xlm-roberta-large-squad2": assert list(dataset.tensors[ tensor_names.index("labels")].numpy()[0, 0, :]) == [ 12, 12 ], f"Processing labels for {model} has changed."