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Unit test for existing speechllm dataset with llama2 prompt format #10634

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pzelasko merged 1 commit into from
Sep 26, 2024
Merged

Unit test for existing speechllm dataset with llama2 prompt format #10634

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182 changes: 181 additions & 1 deletion tests/collections/multimodal/test_speechllm_dataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -82,7 +82,6 @@ def test_speechllm_dataset(tokenizer, cuts):
)

batch = dataset[cuts]
print(batch)

expected_keys = {
"sample_ids",
Expand Down Expand Up @@ -164,3 +163,184 @@ def test_speechllm_dataset(tokenizer, cuts):
0., 0., 0., 0., 0., 0., 0., 0., 0.]])
)
# fmt: on


@pytest.fixture
def llama_tokenizer(capsys, tmp_path_factory):
TOKENIZER_TRAIN_TEXT = """
a b c d e f g h i j k l m n o p q r s t u v x y z
A B C D E F G H I J K L M N O P Q R S T U V X Y Z
[EOG]
Example system message.
Example user message.
Example assistant message.
TEST
[INST]
[/INST]
<s>
</s>
<<SYS>>
<</SYS>>
User: Assistant:
user model
Instruct Output
\n\n
<start_of_turn> <end_of_turn>
<|
|>
<|en|> <|de|> <|fr|> <|es|> <|transcribe|> <|translate|> <|pnc|> <|nopnc|> <|startoftranscript|> <|endoftext|>
Feel free to add new tokens for your own tests!?
But know that if you do so, you may need to update the token IDs in the existing tests!
So, it might be a good idea to create a new tokenizer instead when adding new prompt formats.
"""
tmpdir = tmp_path_factory.mktemp("bpe_tokenizer")
text_path = tmpdir / "text.txt"
text_path.write_text(TOKENIZER_TRAIN_TEXT)
with capsys.disabled():
create_spt_model(
str(text_path),
vocab_size=512,
sample_size=-1,
do_lower_case=False,
output_dir=str(tmpdir),
bos=True,
eos=True,
user_defined_symbols=["[INST]", "[/INST]", "<<SYS>>", "<</SYS>>", "[EOG]"],
)
return SentencePieceTokenizer(str(tmpdir / "tokenizer.model"))


def test_speechllm_dataset_prompt_template(llama_tokenizer, cuts):
tokenizer = llama_tokenizer
text_processor = TextProcessing(
tokenizer=tokenizer,
prompt_template='[INST]\n<<SYS>>\nPlease answer the following based on the previous speech feature.\n<</SYS>>\n\n{context}[/INST] {answer}',
context_key="context",
answer_key="answer",
add_eos=True,
add_sep=False,
add_bos=False,
separate_prompt_and_response_with_newline=False,
end_string="[EOG]",
)
dataset = LhotseAudioQuestionAnswerDataset(
text_processor=text_processor,
default_context="do this task",
tokens_to_generate=128,
pad_to_max_length=False,
max_seq_length=128,
)

batch = dataset[cuts]
print(batch)

expected_keys = {
"sample_ids",
"audio_signal",
"audio_signal_length",
"audio_ratio",
"metadata",
"tokens",
"tokens_length",
"labels",
"loss_mask",
"position_ids",
"contexts",
"context_lengths",
"max_length",
"answers",
}
missing_keys = expected_keys - set(batch)
unexpected_keys = set(batch) - expected_keys
assert not missing_keys and not unexpected_keys, f"{missing_keys=} {unexpected_keys=}"

assert batch["sample_ids"] == ["ex0"]
assert batch["metadata"] == [{'audio_filepath': 'ex0.wav'}]
torch.testing.assert_close(batch["audio_ratio"], tensor([1.0]))
torch.testing.assert_close(batch["max_length"], tensor([128]))

assert torch.is_tensor(batch["audio_signal"])
assert torch.is_floating_point(batch["audio_signal"])
assert batch["audio_signal"].shape == (1, 80000)
torch.testing.assert_close(batch["audio_signal_length"], tensor([80000], dtype=torch.int32))

# fmt: off
expected = tensor([[ 8, 3, 8, 5, 8, 105, 18, 9, 12, 17, 9, 41, 14, 17,
22, 125, 43, 9, 117, 19, 18, 18, 79, 48, 15, 92, 12, 17,
9, 42, 8, 19, 14, 43, 9, 85, 21, 9, 114, 45, 19, 86,
17, 72, 20, 9, 9, 32, 46, 117, 9, 123, 69, 9, 25, 8,
6, 8, 93, 14, 8, 74, 88, 12, 86, 18, 13, 85, 21, 19,
27, 13, 116, 19, 14, 13, 78, 13, 4, 72, 19, 84, 9, 8,
65, 120, 45, 19, 14, 8, 7, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2]])
torch.testing.assert_close(batch["tokens"], expected)
torch.testing.assert_close(batch["tokens_length"], tensor([91]))
assert tokenizer.ids_to_text(expected[0, :91].tolist()) == "[INST] <<SYS>> Please answer the following based on the previous speech feature. <</SYS>> non default prompt context[/INST] some transcription [EOG]"

expected = tensor([[ 8, 3, 8, 5, 8, 105, 18, 9, 12, 17, 9, 41, 14, 17,
22, 125, 43, 9, 117, 19, 18, 18, 79, 48, 15, 92, 12, 17,
9, 42, 8, 19, 14, 43, 9, 85, 21, 9, 114, 45, 19, 86,
17, 72, 20, 9, 9, 32, 46, 117, 9, 123, 69, 9, 25, 8,
6, 8, 93, 14, 8, 74, 88, 12, 86, 18, 13, 85, 21, 19,
27, 13, 116, 19, 14, 13, 78, 13, 4, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2]])
torch.testing.assert_close(batch["contexts"], expected)
torch.testing.assert_close(batch["context_lengths"], tensor([79]))
assert tokenizer.ids_to_text(expected[0, :79].tolist()) == "[INST] <<SYS>> Please answer the following based on the previous speech feature. <</SYS>> non default prompt context[/INST]"

expected = tensor([[ 72, 19, 84, 9, 8, 65, 120, 45, 19, 14, 8, 7, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2]])
torch.testing.assert_close(batch["answers"], expected)
assert tokenizer.ids_to_text(expected[0, :12].tolist()) == "some transcription [EOG]"

expected = tensor([[ 3, 8, 5, 8, 105, 18, 9, 12, 17, 9, 41, 14, 17, 22,
125, 43, 9, 117, 19, 18, 18, 79, 48, 15, 92, 12, 17, 9,
42, 8, 19, 14, 43, 9, 85, 21, 9, 114, 45, 19, 86, 17,
72, 20, 9, 9, 32, 46, 117, 9, 123, 69, 9, 25, 8, 6,
8, 93, 14, 8, 74, 88, 12, 86, 18, 13, 85, 21, 19, 27,
13, 116, 19, 14, 13, 78, 13, 4, 72, 19, 84, 9, 8, 65,
120, 45, 19, 14, 8, 7, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2]])
torch.testing.assert_close(batch["labels"], expected)
assert tokenizer.ids_to_text(expected[0, :90].tolist()) == "[INST] <<SYS>> Please answer the following based on the previous speech feature. <</SYS>> non default prompt context[/INST] some transcription [EOG]"

torch.testing.assert_close(
batch["position_ids"],
tensor([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,
14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27,
28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41,
42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55,
56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69,
70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83,
84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97,
98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111,
112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125,
126, 127]])
)

torch.testing.assert_close(
batch["loss_mask"],
tensor([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0.]])
)
# fmt: on