137 lines
5.0 KiB
Python
137 lines
5.0 KiB
Python
# SPDX-License-Identifier: Apache-2.0
|
|
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
|
|
|
|
import pytest
|
|
import torch
|
|
|
|
from vllm.model_executor.layers.sampler import SamplerOutput
|
|
from vllm.sequence import (CompletionSequenceGroupOutput, IntermediateTensors,
|
|
SequenceData, SequenceOutput)
|
|
|
|
from .core.utils import create_dummy_prompt
|
|
|
|
|
|
@pytest.fixture
|
|
def sample_outputs():
|
|
return [
|
|
CompletionSequenceGroupOutput(samples=[
|
|
SequenceOutput(parent_seq_id=0, output_token=i, logprobs={})
|
|
],
|
|
prompt_logprobs=None) for i in range(5)
|
|
]
|
|
|
|
|
|
@pytest.fixture
|
|
def sampler_output(sample_outputs):
|
|
return SamplerOutput(outputs=sample_outputs)
|
|
|
|
|
|
def test_sampler_output_initialization(sampler_output, sample_outputs):
|
|
assert len(sampler_output) == len(sample_outputs)
|
|
assert sampler_output.sampled_token_probs is None
|
|
assert sampler_output.sampled_token_ids is None
|
|
|
|
|
|
def test_sampler_output_getitem(sampler_output, sample_outputs):
|
|
assert sampler_output[2] == sample_outputs[2]
|
|
|
|
|
|
def test_sampler_output_setitem(sampler_output):
|
|
new_output = CompletionSequenceGroupOutput(samples=[
|
|
SequenceOutput(parent_seq_id=0, output_token=99, logprobs={})
|
|
],
|
|
prompt_logprobs=None)
|
|
sampler_output[2] = new_output
|
|
assert sampler_output[2] == new_output
|
|
|
|
|
|
def test_sampler_output_len(sampler_output, sample_outputs):
|
|
assert len(sampler_output) == len(sample_outputs)
|
|
|
|
|
|
def test_sampler_output_eq(sample_outputs):
|
|
sampler_output1 = SamplerOutput(outputs=sample_outputs)
|
|
sampler_output2 = SamplerOutput(outputs=sample_outputs.copy())
|
|
sampler_output3 = SamplerOutput(outputs=sample_outputs[:-1])
|
|
assert sampler_output1 == sampler_output2
|
|
assert sampler_output1 != sampler_output3
|
|
|
|
|
|
def test_sequence_data_prefill():
|
|
seq_data = SequenceData.from_seqs([1, 2, 3, 4])
|
|
assert seq_data.get_num_uncomputed_tokens() == 4
|
|
assert seq_data.get_num_computed_tokens() == 0
|
|
# advance by 2
|
|
seq_data.update_num_computed_tokens(2)
|
|
assert seq_data.get_num_uncomputed_tokens() == 2
|
|
assert seq_data.get_num_computed_tokens() == 2
|
|
|
|
# advance by 1
|
|
seq_data.update_num_computed_tokens(1)
|
|
assert seq_data.get_num_uncomputed_tokens() == 1
|
|
assert seq_data.get_num_computed_tokens() == 3
|
|
|
|
# append tokens and reset, simulating recompute
|
|
seq_data.append_token_id(1, logprob=0.0)
|
|
seq_data.reset_state_for_recompute()
|
|
assert seq_data.get_num_uncomputed_tokens() == 5
|
|
assert seq_data.get_num_computed_tokens() == 0
|
|
|
|
|
|
def test_sequence_group_stage():
|
|
_, seq_group = create_dummy_prompt("1", 12)
|
|
assert seq_group.is_prefill() is True
|
|
seq_group.update_num_computed_tokens(6)
|
|
assert seq_group.is_prefill() is True
|
|
seq_group.update_num_computed_tokens(5)
|
|
assert seq_group.is_prefill() is True
|
|
seq_group.update_num_computed_tokens(1)
|
|
assert seq_group.is_prefill() is False
|
|
seqs = seq_group.get_seqs()
|
|
assert len(seqs) == 1
|
|
seqs[0].data.append_token_id(1, logprob=0.0)
|
|
for seq in seq_group.get_seqs():
|
|
seq.reset_state_for_recompute()
|
|
assert seq_group.is_prefill() is True
|
|
seq_group.update_num_computed_tokens(5)
|
|
assert seq_group.is_prefill() is True
|
|
seq_group.update_num_computed_tokens(7)
|
|
assert seq_group.is_prefill() is True
|
|
seq_group.update_num_computed_tokens(1)
|
|
assert seq_group.is_prefill() is False
|
|
|
|
|
|
def test_sequence_intermediate_tensors_equal():
|
|
|
|
class AnotherIntermediateTensors(IntermediateTensors):
|
|
pass
|
|
|
|
intermediate_tensors = IntermediateTensors({})
|
|
another_intermediate_tensors = AnotherIntermediateTensors({})
|
|
assert intermediate_tensors != another_intermediate_tensors
|
|
|
|
empty_intermediate_tensors_1 = IntermediateTensors({})
|
|
empty_intermediate_tensors_2 = IntermediateTensors({})
|
|
assert empty_intermediate_tensors_1 == empty_intermediate_tensors_2
|
|
|
|
different_key_intermediate_tensors_1 = IntermediateTensors(
|
|
{"1": torch.zeros([2, 4], dtype=torch.int32)})
|
|
difference_key_intermediate_tensors_2 = IntermediateTensors(
|
|
{"2": torch.zeros([2, 4], dtype=torch.int32)})
|
|
assert (different_key_intermediate_tensors_1
|
|
!= difference_key_intermediate_tensors_2)
|
|
|
|
same_key_different_value_intermediate_tensors_1 = IntermediateTensors(
|
|
{"1": torch.zeros([2, 4], dtype=torch.int32)})
|
|
same_key_different_value_intermediate_tensors_2 = IntermediateTensors(
|
|
{"1": torch.zeros([2, 5], dtype=torch.int32)})
|
|
assert (same_key_different_value_intermediate_tensors_1
|
|
!= same_key_different_value_intermediate_tensors_2)
|
|
|
|
same_key_same_value_intermediate_tensors_1 = IntermediateTensors(
|
|
{"1": torch.zeros([2, 4], dtype=torch.int32)})
|
|
same_key_same_value_intermediate_tensors_2 = IntermediateTensors(
|
|
{"1": torch.zeros([2, 4], dtype=torch.int32)})
|
|
assert (same_key_same_value_intermediate_tensors_1 ==
|
|
same_key_same_value_intermediate_tensors_2)
|