327 lines
12 KiB
Python
327 lines
12 KiB
Python
import pytest
|
|
import torch
|
|
|
|
from copy import copy
|
|
|
|
from transformers import AutoTokenizer
|
|
|
|
from text_generation_server.pb import generate_pb2
|
|
from text_generation_server.models.seq2seq_lm import Seq2SeqLM, Seq2SeqLMBatch
|
|
|
|
|
|
@pytest.fixture(scope="session")
|
|
def mt0_small_tokenizer():
|
|
tokenizer = AutoTokenizer.from_pretrained(
|
|
"bigscience/mt0-small", padding_side="left"
|
|
)
|
|
tokenizer.bos_token_id = 0
|
|
return tokenizer
|
|
|
|
|
|
@pytest.fixture(scope="session")
|
|
def default_seq2seq_lm():
|
|
return Seq2SeqLM("bigscience/mt0-small")
|
|
|
|
|
|
@pytest.fixture
|
|
def default_pb_request(default_pb_parameters, default_pb_stop_parameters):
|
|
return generate_pb2.Request(
|
|
id=0,
|
|
inputs="Test",
|
|
truncate=100,
|
|
parameters=default_pb_parameters,
|
|
stopping_parameters=default_pb_stop_parameters,
|
|
)
|
|
|
|
|
|
@pytest.fixture
|
|
def default_pb_batch(default_pb_request):
|
|
return generate_pb2.Batch(id=0, requests=[default_pb_request], size=1)
|
|
|
|
|
|
@pytest.fixture
|
|
def default_seq2seq_lm_batch(default_pb_batch, mt0_small_tokenizer):
|
|
return Seq2SeqLMBatch.from_pb(
|
|
default_pb_batch, mt0_small_tokenizer, torch.device("cpu")
|
|
)
|
|
|
|
|
|
@pytest.fixture
|
|
def default_multi_requests_seq2seq_lm_batch(default_pb_request, mt0_small_tokenizer):
|
|
req_0 = copy(default_pb_request)
|
|
req_1 = default_pb_request
|
|
req_1.id = 1
|
|
req_1.stopping_parameters.max_new_tokens = 5
|
|
|
|
batch_pb = generate_pb2.Batch(id=0, requests=[req_0, req_1], size=2)
|
|
return Seq2SeqLMBatch.from_pb(batch_pb, mt0_small_tokenizer, torch.device("cpu"))
|
|
|
|
|
|
def test_batch_from_pb(default_pb_batch, default_seq2seq_lm_batch):
|
|
batch = default_seq2seq_lm_batch
|
|
sequence_length = len(default_seq2seq_lm_batch.input_ids[0])
|
|
|
|
assert batch.batch_id == default_pb_batch.id
|
|
assert batch.requests == default_pb_batch.requests
|
|
|
|
assert batch.input_ids.shape == (default_pb_batch.size, sequence_length)
|
|
assert batch.input_ids[0][-2] == 4268
|
|
assert batch.input_ids[0][-1] == 1
|
|
assert torch.all(batch.input_ids[0][:-2] == 0)
|
|
|
|
assert torch.all(batch.attention_mask[0][-2:] == 1)
|
|
assert torch.all(batch.attention_mask[0][:-2] == 0)
|
|
|
|
assert batch.decoder_input_ids.shape == (default_pb_batch.size, 1)
|
|
assert batch.decoder_attention_mask is None
|
|
assert batch.encoder_last_hidden_state is None
|
|
|
|
assert batch.past_key_values is None
|
|
|
|
assert batch.input_lengths == [2]
|
|
assert batch.decoder_input_lengths == [1]
|
|
|
|
assert batch.size == default_pb_batch.size
|
|
assert len(batch.next_token_choosers) == len(batch.stopping_criterias) == batch.size
|
|
|
|
assert batch.max_input_length == batch.input_lengths[0]
|
|
assert batch.max_decoder_input_length == batch.decoder_input_lengths[0]
|
|
|
|
|
|
def test_batch_concatenate_no_prefill(default_seq2seq_lm_batch):
|
|
with pytest.raises(ValueError):
|
|
Seq2SeqLMBatch.concatenate([default_seq2seq_lm_batch, default_seq2seq_lm_batch])
|
|
|
|
|
|
def test_seq2seq_lm_batch_type(default_seq2seq_lm):
|
|
assert default_seq2seq_lm.batch_type == Seq2SeqLMBatch
|
|
|
|
|
|
def test_seq2seq_lm_generate_token(default_seq2seq_lm, default_seq2seq_lm_batch):
|
|
sequence_length = len(default_seq2seq_lm_batch.input_ids[0])
|
|
generations, next_batch = default_seq2seq_lm.generate_token(
|
|
default_seq2seq_lm_batch
|
|
)
|
|
|
|
assert len(generations) == len(next_batch)
|
|
assert isinstance(next_batch, Seq2SeqLMBatch)
|
|
|
|
assert next_batch.input_ids is None
|
|
assert torch.equal(
|
|
next_batch.attention_mask, default_seq2seq_lm_batch.attention_mask
|
|
)
|
|
assert next_batch.input_lengths == default_seq2seq_lm_batch.input_lengths
|
|
assert next_batch.max_input_length == default_seq2seq_lm_batch.max_input_length
|
|
assert (
|
|
next_batch.next_token_choosers == default_seq2seq_lm_batch.next_token_choosers
|
|
)
|
|
assert next_batch.stopping_criterias == default_seq2seq_lm_batch.stopping_criterias
|
|
|
|
assert next_batch.decoder_input_ids.shape == (next_batch.size, 2)
|
|
assert next_batch.decoder_input_ids[0, 0] == 0
|
|
assert next_batch.decoder_input_ids[0, 1] == 259
|
|
assert next_batch.decoder_attention_mask is None
|
|
assert next_batch.encoder_last_hidden_state.shape == (1, sequence_length, 512)
|
|
|
|
assert next_batch.decoder_input_lengths == [2]
|
|
assert next_batch.max_decoder_input_length == 2
|
|
|
|
assert next_batch.past_key_values is not None
|
|
assert all(
|
|
[p[0].shape == (next_batch.size, 6, 1, 64) for p in next_batch.past_key_values]
|
|
)
|
|
assert all(
|
|
[p[1].shape == (next_batch.size, 6, 1, 64) for p in next_batch.past_key_values]
|
|
)
|
|
assert all(
|
|
[
|
|
p[2].shape == (next_batch.size, 6, sequence_length, 64)
|
|
for p in next_batch.past_key_values
|
|
]
|
|
)
|
|
assert all(
|
|
[
|
|
p[3].shape == (next_batch.size, 6, sequence_length, 64)
|
|
for p in next_batch.past_key_values
|
|
]
|
|
)
|
|
assert all([generation.generated_text is None for generation in generations])
|
|
assert all([len(generation.prefill_tokens) == 1 for generation in generations])
|
|
assert all([generation.token_id.item() == 259 for generation in generations])
|
|
assert all([generation.token_text == "" for generation in generations])
|
|
assert generations[0].request_id == 0
|
|
|
|
|
|
def test_seq2seq_lm_generate_token_completion(
|
|
default_seq2seq_lm, default_seq2seq_lm_batch
|
|
):
|
|
next_batch = default_seq2seq_lm_batch
|
|
for _ in range(6):
|
|
generations, next_batch = default_seq2seq_lm.generate_token(next_batch)
|
|
assert len(generations) == len(next_batch)
|
|
|
|
generations, next_batch = default_seq2seq_lm.generate_token(next_batch)
|
|
assert next_batch is None
|
|
|
|
assert len(generations) == 1
|
|
assert generations[0].generated_text.text == "a few weeks"
|
|
assert generations[0].request_id == default_seq2seq_lm_batch.requests[0].id
|
|
assert generations[0].generated_text.generated_tokens == 7
|
|
|
|
|
|
def test_seq2seq_lm_generate_token_completion_multi(
|
|
default_seq2seq_lm, default_multi_requests_seq2seq_lm_batch
|
|
):
|
|
next_batch = default_multi_requests_seq2seq_lm_batch
|
|
|
|
for i in range(4):
|
|
generations, next_batch = default_seq2seq_lm.generate_token(next_batch)
|
|
assert len(generations) == len(next_batch)
|
|
|
|
generations, next_batch = default_seq2seq_lm.generate_token(next_batch)
|
|
assert next_batch is not None
|
|
|
|
assert len(generations) == 2
|
|
assert generations[1].generated_text.text == "a few "
|
|
assert (
|
|
generations[1].request_id
|
|
== default_multi_requests_seq2seq_lm_batch.requests[1].id
|
|
)
|
|
assert generations[1].generated_text.generated_tokens == 5
|
|
|
|
generations, next_batch = default_seq2seq_lm.generate_token(next_batch)
|
|
assert len(generations) == len(next_batch)
|
|
|
|
generations, next_batch = default_seq2seq_lm.generate_token(next_batch)
|
|
assert next_batch is None
|
|
|
|
assert len(generations) == 1
|
|
assert generations[0].generated_text.text == "a few weeks"
|
|
assert (
|
|
generations[0].request_id
|
|
== default_multi_requests_seq2seq_lm_batch.requests[0].id
|
|
)
|
|
assert generations[0].generated_text.generated_tokens == 7
|
|
|
|
|
|
def test_batch_concatenate(
|
|
default_seq2seq_lm,
|
|
default_seq2seq_lm_batch,
|
|
default_multi_requests_seq2seq_lm_batch,
|
|
):
|
|
next_batch_0 = default_seq2seq_lm_batch
|
|
_, next_batch_0 = default_seq2seq_lm.generate_token(next_batch_0)
|
|
_, next_batch_0 = default_seq2seq_lm.generate_token(next_batch_0)
|
|
|
|
next_batch_1 = default_multi_requests_seq2seq_lm_batch
|
|
_, next_batch_1 = default_seq2seq_lm.generate_token(next_batch_1)
|
|
|
|
next_batch = Seq2SeqLMBatch.concatenate([next_batch_0, next_batch_1])
|
|
|
|
assert next_batch.batch_id == 0
|
|
|
|
assert torch.equal(
|
|
next_batch.decoder_input_ids[0], next_batch_0.decoder_input_ids[0]
|
|
)
|
|
assert torch.all(next_batch.decoder_input_ids[1:, 0] == 0)
|
|
assert torch.equal(
|
|
next_batch.decoder_input_ids[1:, -2:], next_batch_1.decoder_input_ids
|
|
)
|
|
|
|
assert torch.all(next_batch.decoder_attention_mask[0, :3] == 1)
|
|
assert torch.all(next_batch.decoder_attention_mask[0, 3:] == 0)
|
|
assert torch.all(next_batch.decoder_attention_mask[1:, 0] == 0)
|
|
assert torch.all(next_batch.decoder_attention_mask[1:, 1:3] == 1)
|
|
|
|
assert torch.equal(
|
|
next_batch.encoder_last_hidden_state[0],
|
|
next_batch_0.encoder_last_hidden_state[0, -2:],
|
|
)
|
|
assert torch.equal(
|
|
next_batch.encoder_last_hidden_state[1:],
|
|
next_batch_1.encoder_last_hidden_state[:, -2:],
|
|
)
|
|
|
|
assert next_batch.input_lengths == [2, 2, 2]
|
|
assert next_batch.decoder_input_lengths == [3, 2, 2]
|
|
assert next_batch.max_input_length == 2
|
|
assert next_batch.max_decoder_input_length == 3
|
|
|
|
assert next_batch.requests[0] == next_batch_0.requests[0]
|
|
assert next_batch.requests[1:] == next_batch_1.requests
|
|
|
|
assert next_batch.next_token_choosers[0] == next_batch_0.next_token_choosers[0]
|
|
assert next_batch.next_token_choosers[1:] == next_batch_1.next_token_choosers
|
|
|
|
assert next_batch.stopping_criterias[0] == next_batch_0.stopping_criterias[0]
|
|
assert next_batch.stopping_criterias[1:] == next_batch_1.stopping_criterias
|
|
|
|
assert next_batch.past_key_values is not None
|
|
assert all(
|
|
[p[0].shape == (next_batch.size, 6, 2, 64) for p in next_batch.past_key_values]
|
|
)
|
|
assert all(
|
|
[p[1].shape == (next_batch.size, 6, 2, 64) for p in next_batch.past_key_values]
|
|
)
|
|
assert all(
|
|
[p[2].shape == (next_batch.size, 6, 2, 64) for p in next_batch.past_key_values]
|
|
)
|
|
assert all(
|
|
[p[3].shape == (next_batch.size, 6, 2, 64) for p in next_batch.past_key_values]
|
|
)
|
|
|
|
for i, past in enumerate(next_batch.past_key_values):
|
|
assert torch.equal(next_batch_0.past_key_values[i][0][0, :, -2:, :], past[0][0])
|
|
assert torch.equal(
|
|
next_batch_1.past_key_values[i][0][:, :, -1:, :], past[0][1:, :, -1:, :]
|
|
)
|
|
|
|
assert torch.equal(next_batch_0.past_key_values[i][1][0, :, -2:, :], past[1][0])
|
|
assert torch.equal(
|
|
next_batch_1.past_key_values[i][1][:, :, -1:, :], past[1][1:, :, -1:, :]
|
|
)
|
|
|
|
assert torch.equal(next_batch_0.past_key_values[i][2][0, :, -2:, :], past[2][0])
|
|
assert torch.equal(
|
|
next_batch_1.past_key_values[i][2][:, :, -2:, :], past[2][1:]
|
|
)
|
|
|
|
assert torch.equal(next_batch_0.past_key_values[i][3][0, :, -2:, :], past[3][0])
|
|
assert torch.equal(
|
|
next_batch_1.past_key_values[i][3][:, :, -2:, :], past[3][1:]
|
|
)
|
|
|
|
for _ in range(3):
|
|
generations, next_batch = default_seq2seq_lm.generate_token(next_batch)
|
|
assert len(generations) == len(next_batch)
|
|
|
|
generations, next_batch = default_seq2seq_lm.generate_token(next_batch)
|
|
assert next_batch is not None
|
|
|
|
assert len(generations) == 3
|
|
assert generations[2].generated_text.text == "a few "
|
|
assert (
|
|
generations[2].request_id
|
|
== default_multi_requests_seq2seq_lm_batch.requests[1].id
|
|
)
|
|
assert generations[2].generated_text.generated_tokens == 5
|
|
|
|
generations, next_batch = default_seq2seq_lm.generate_token(next_batch)
|
|
assert next_batch is not None
|
|
|
|
assert len(generations) == 2
|
|
assert generations[0].generated_text.text == "a few weeks"
|
|
assert generations[0].request_id == default_seq2seq_lm_batch.requests[0].id
|
|
assert generations[0].generated_text.generated_tokens == 7
|
|
|
|
generations, next_batch = default_seq2seq_lm.generate_token(next_batch)
|
|
assert next_batch is None
|
|
|
|
assert len(generations) == 1
|
|
assert generations[0].generated_text.text == "a few weeks"
|
|
assert (
|
|
generations[0].request_id
|
|
== default_multi_requests_seq2seq_lm_batch.requests[0].id
|
|
)
|
|
assert generations[0].generated_text.generated_tokens == 7
|