357 lines
13 KiB
Python
357 lines
13 KiB
Python
import pytest
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import torch
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from copy import copy
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from transformers import AutoTokenizer
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from text_generation_server.pb import generate_pb2
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from text_generation_server.models.causal_lm import CausalLMBatch
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from text_generation_server.utils import weight_hub_files, download_weights
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from text_generation_server.models.bloom import BloomCausalLMBatch, BLOOMSharded
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@pytest.fixture(scope="session")
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def default_bloom():
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model_id = "bigscience/bloom-560m"
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revision = "main"
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filenames = weight_hub_files(model_id, revision, ".safetensors")
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download_weights(filenames, model_id, revision)
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return BLOOMSharded(model_id)
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@pytest.fixture(scope="session")
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def bloom_560m_tokenizer():
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return AutoTokenizer.from_pretrained("bigscience/bloom-560m", padding_side="left")
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@pytest.fixture
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def default_pb_request(default_pb_parameters, default_pb_stop_parameters):
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return generate_pb2.Request(
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id=0,
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inputs="Test",
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prefill_logprobs=True,
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truncate=100,
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parameters=default_pb_parameters,
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stopping_parameters=default_pb_stop_parameters,
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)
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@pytest.fixture
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def default_pb_batch(default_pb_request):
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return generate_pb2.Batch(id=0, requests=[default_pb_request], size=1)
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@pytest.fixture
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def default_bloom_batch(default_pb_batch, bloom_560m_tokenizer):
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return BloomCausalLMBatch.from_pb(
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default_pb_batch, bloom_560m_tokenizer, torch.float32, torch.device("cpu")
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)
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@pytest.fixture
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def default_multi_requests_bloom_batch(default_pb_request, bloom_560m_tokenizer):
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req_0 = copy(default_pb_request)
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req_0.id = 1
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req_1 = default_pb_request
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req_1.id = 2
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req_1.stopping_parameters.max_new_tokens = 5
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batch_pb = generate_pb2.Batch(id=0, requests=[req_0, req_1], size=2)
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return BloomCausalLMBatch.from_pb(
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batch_pb, bloom_560m_tokenizer, torch.float32, torch.device("cpu")
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)
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def test_batch_from_pb(default_pb_batch, default_bloom_batch):
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batch = default_bloom_batch
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assert batch.batch_id == default_pb_batch.id
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assert batch.requests == default_pb_batch.requests
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assert len(batch.input_ids) == default_pb_batch.size
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assert batch.input_ids[0][-1] == 10264
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assert torch.all(batch.input_ids[0][:-1] == 3)
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assert batch.attention_mask[0][0] == 1
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assert torch.all(batch.attention_mask[0][1:] == 0)
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assert batch.past_key_values is None
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assert all(
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[
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torch.equal(input_ids, all_input_ids[:, 0])
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for input_ids, all_input_ids in zip(batch.input_ids, batch.all_input_ids)
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]
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)
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assert batch.input_lengths == [1]
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assert len(batch) == default_pb_batch.size
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assert len(batch.next_token_choosers) == len(batch.stopping_criterias) == len(batch)
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assert batch.max_input_length == batch.input_lengths[0]
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def test_batch_concatenate_no_prefill(default_bloom_batch):
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with pytest.raises(ValueError):
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BloomCausalLMBatch.concatenate([default_bloom_batch, default_bloom_batch])
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def test_causal_lm_batch_type(default_bloom):
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assert default_bloom.batch_type == BloomCausalLMBatch
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def test_causal_lm_generate_token(default_bloom, default_bloom_batch):
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sequence_length = len(default_bloom_batch.all_input_ids[0])
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generations, next_batch, _ = default_bloom.generate_token(default_bloom_batch)
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assert len(generations) == len(default_bloom_batch)
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assert isinstance(next_batch, CausalLMBatch)
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assert not next_batch.keys_head_dim_last
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assert len(next_batch.all_input_ids) == len(next_batch)
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assert len(next_batch.all_input_ids[0]) == sequence_length + 1
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assert len(next_batch.attention_mask[0]) == 11
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assert torch.all(next_batch.all_input_ids[0][-2:] == 10264)
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assert torch.all(next_batch.all_input_ids[0][:-2] == 3)
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assert torch.all(next_batch.attention_mask[0][:2] == 1)
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assert torch.all(next_batch.attention_mask[0][2:] == 0)
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assert next_batch.input_ids.shape == (len(next_batch), 1)
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assert next_batch.input_ids[0, 0] == 10264
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assert next_batch.input_lengths == [2]
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assert next_batch.max_input_length == next_batch.input_lengths[0]
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assert next_batch.past_key_values is not None
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assert all(
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[p[0].shape == (16, 64, sequence_length) for p in next_batch.past_key_values]
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)
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assert all(
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[p[1].shape == (16, sequence_length, 64) for p in next_batch.past_key_values]
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)
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assert all([generation.generated_text is None for generation in generations])
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assert all([len(generation.prefill_tokens) == 1 for generation in generations])
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assert all(
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[
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token_id.item() == 10264
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for generation in generations
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for token_id in generation.tokens.token_ids
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]
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)
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assert all(
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[
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token_text == "Test"
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for generation in generations
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for token_text in generation.tokens.texts
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]
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)
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assert generations[0].request_id == 0
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def test_causal_lm_generate_token_completion(default_bloom, default_bloom_batch):
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next_batch = default_bloom_batch
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for _ in range(default_bloom_batch.stopping_criterias[0].max_new_tokens - 1):
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generations, next_batch, _ = default_bloom.generate_token(next_batch)
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assert len(generations) == len(default_bloom_batch)
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generations, next_batch, _ = default_bloom.generate_token(next_batch)
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assert next_batch is None
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assert len(generations) == 1
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assert (
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generations[0].generated_text.text == "TestTestTestTestTestTestTestTestTestTest"
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)
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assert generations[0].request_id == default_bloom_batch.requests[0].id
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assert (
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generations[0].generated_text.generated_tokens
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== default_bloom_batch.stopping_criterias[0].max_new_tokens
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)
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def test_causal_lm_generate_token_completion_multi(
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default_bloom, default_multi_requests_bloom_batch
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):
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next_batch = default_multi_requests_bloom_batch
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for i in range(
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default_multi_requests_bloom_batch.stopping_criterias[1].max_new_tokens - 1
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):
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generations, next_batch, _ = default_bloom.generate_token(next_batch)
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assert len(generations) == len(default_multi_requests_bloom_batch)
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generations, next_batch, _ = default_bloom.generate_token(next_batch)
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assert next_batch is not None
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assert len(generations) == 2
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assert generations[1].generated_text.text == "TestTestTestTestTest"
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assert (
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generations[1].request_id == default_multi_requests_bloom_batch.requests[1].id
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)
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assert (
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generations[1].generated_text.generated_tokens
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== default_multi_requests_bloom_batch.stopping_criterias[1].max_new_tokens
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)
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# Copy stopping_criterias before filtering
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stopping_criterias = default_multi_requests_bloom_batch.stopping_criterias.copy()
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next_batch = next_batch.filter([next_batch.requests[0].id])
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for _ in range(
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stopping_criterias[0].max_new_tokens - stopping_criterias[1].max_new_tokens - 1
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):
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generations, next_batch, _ = default_bloom.generate_token(next_batch)
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assert len(generations) == len(next_batch)
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generations, next_batch, _ = default_bloom.generate_token(next_batch)
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assert next_batch is None
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assert len(generations) == 1
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assert (
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generations[0].generated_text.text == "TestTestTestTestTestTestTestTestTestTest"
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)
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assert (
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generations[0].request_id == default_multi_requests_bloom_batch.requests[0].id
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)
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assert (
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generations[0].generated_text.generated_tokens
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== default_multi_requests_bloom_batch.stopping_criterias[0].max_new_tokens
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)
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def test_batch_concatenate(
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default_bloom, default_bloom_batch, default_multi_requests_bloom_batch
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):
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next_batch_0 = default_bloom_batch
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_, next_batch_0, _ = default_bloom.generate_token(next_batch_0)
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_, next_batch_0, _ = default_bloom.generate_token(next_batch_0)
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next_batch_1 = default_multi_requests_bloom_batch
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_, next_batch_1, _ = default_bloom.generate_token(next_batch_1)
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# Clone past_key_values before concatenating to compare after,
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# because they are removed from the concatenated batches
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next_batch_0_past_key_values = [
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(k.clone(), v.clone()) for (k, v) in next_batch_0.past_key_values
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]
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next_batch_1_past_key_values = [
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(k.clone(), v.clone()) for (k, v) in next_batch_1.past_key_values
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]
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next_batch = BloomCausalLMBatch.concatenate([next_batch_0, next_batch_1])
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assert torch.equal(next_batch.all_input_ids[0], next_batch_0.all_input_ids[0])
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assert torch.equal(next_batch.all_input_ids[1], next_batch_1.all_input_ids[0])
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assert torch.equal(next_batch.all_input_ids[2], next_batch_1.all_input_ids[1])
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assert torch.all(
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next_batch.attention_mask[0, : -next_batch.padding_right_offset] == 1
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)
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assert torch.all(
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next_batch.attention_mask[1:, 1 : -next_batch.padding_right_offset] == 1
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)
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assert torch.all(next_batch.attention_mask[1:, 3:] == 0)
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assert next_batch.batch_id == 0
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assert torch.all(next_batch.input_ids == 10264)
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assert next_batch.input_lengths == [3, 2, 2]
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assert next_batch.max_input_length == 3
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assert next_batch.requests[0] == next_batch_0.requests[0]
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assert next_batch.requests[1:] == next_batch_1.requests
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assert next_batch.next_token_choosers[0] == next_batch_0.next_token_choosers[0]
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assert next_batch.next_token_choosers[1:] == next_batch_1.next_token_choosers
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assert next_batch.stopping_criterias[0] == next_batch_0.stopping_criterias[0]
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assert next_batch.stopping_criterias[1:] == next_batch_1.stopping_criterias
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assert next_batch.past_key_values is not None
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assert all([p[0].shape == (3, 16, 64, 2) for p in next_batch.past_key_values])
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assert all([p[1].shape == (3, 16, 2, 64) for p in next_batch.past_key_values])
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for i, past in enumerate(next_batch.past_key_values):
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assert torch.equal(next_batch_0_past_key_values[i][0][:, :, -2:], past[0][0])
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assert torch.equal(
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next_batch_1_past_key_values[i][0][:, :, -1:],
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past[0][1:, :, :, -1].reshape(-1, 64, 1),
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)
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assert torch.equal(next_batch_0_past_key_values[i][1][:, -2:, :], past[1][0])
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assert torch.equal(
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next_batch_1_past_key_values[i][1][:, -1:, :],
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past[1][1:, :, -1, :].reshape(-1, 1, 64),
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)
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for _ in range(
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default_multi_requests_bloom_batch.stopping_criterias[1].max_new_tokens - 2
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):
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generations, next_batch, _ = default_bloom.generate_token(next_batch)
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assert len(generations) == len(next_batch)
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generations, next_batch, _ = default_bloom.generate_token(next_batch)
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assert next_batch is not None
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assert len(generations) == 3
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assert generations[2].generated_text.text == "TestTestTestTestTest"
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assert (
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generations[2].request_id == default_multi_requests_bloom_batch.requests[1].id
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)
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assert (
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generations[2].generated_text.generated_tokens
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== default_multi_requests_bloom_batch.stopping_criterias[1].max_new_tokens
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)
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next_batch = next_batch.filter(
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[next_batch.requests[0].id, next_batch.requests[1].id]
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)
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for _ in range(
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default_bloom_batch.stopping_criterias[0].max_new_tokens
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- default_multi_requests_bloom_batch.stopping_criterias[1].max_new_tokens
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- 2
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):
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generations, next_batch, _ = default_bloom.generate_token(next_batch)
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assert len(generations) == len(next_batch)
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generations, next_batch, _ = default_bloom.generate_token(next_batch)
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assert next_batch is not None
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assert len(generations) == 2
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assert (
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generations[0].generated_text.text == "TestTestTestTestTestTestTestTestTestTest"
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)
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assert generations[0].request_id == default_bloom_batch.requests[0].id
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assert (
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generations[0].generated_text.generated_tokens
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== default_bloom_batch.stopping_criterias[0].max_new_tokens
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)
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next_batch = next_batch.filter([next_batch.requests[1].id])
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for _ in range(
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default_multi_requests_bloom_batch.stopping_criterias[0].max_new_tokens
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- default_bloom_batch.stopping_criterias[0].max_new_tokens
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- default_multi_requests_bloom_batch.stopping_criterias[1].max_new_tokens
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- 4
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):
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generations, next_batch, _ = default_bloom.generate_token(next_batch)
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assert len(generations) == len(next_batch)
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generations, next_batch, _ = default_bloom.generate_token(next_batch)
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assert next_batch is None
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assert len(generations) == 1
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assert (
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generations[0].generated_text.text == "TestTestTestTestTestTestTestTestTestTest"
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)
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assert (
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generations[0].request_id == default_multi_requests_bloom_batch.requests[0].id
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)
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assert (
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generations[0].generated_text.generated_tokens
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== default_multi_requests_bloom_batch.stopping_criterias[0].max_new_tokens
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)
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