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."
