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e489ad7a21
- **Add SPDX license headers to python source files**
- **Check for SPDX headers using pre-commit**
commit 9d7ef44c3cfb72ca4c32e1c677d99259d10d4745
Author: Russell Bryant <rbryant@redhat.com>
Date: Fri Jan 31 14:18:24 2025 -0500
Add SPDX license headers to python source files
This commit adds SPDX license headers to python source files as
recommended to
the project by the Linux Foundation. These headers provide a concise way
that is
both human and machine readable for communicating license information
for each
source file. It helps avoid any ambiguity about the license of the code
and can
also be easily used by tools to help manage license compliance.
The Linux Foundation runs license scans against the codebase to help
ensure
we are in compliance with the licenses of the code we use, including
dependencies. Having these headers in place helps that tool do its job.
More information can be found on the SPDX site:
- https://spdx.dev/learn/handling-license-info/
Signed-off-by: Russell Bryant <rbryant@redhat.com>
commit 5a1cf1cb3b80759131c73f6a9dddebccac039dea
Author: Russell Bryant <rbryant@redhat.com>
Date: Fri Jan 31 14:36:32 2025 -0500
Check for SPDX headers using pre-commit
Signed-off-by: Russell Bryant <rbryant@redhat.com>
---------
Signed-off-by: Russell Bryant <rbryant@redhat.com>
112 lines
3.7 KiB
Python
112 lines
3.7 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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from typing import List
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import pytest
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import torch
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from vllm.spec_decode.batch_expansion import BatchExpansionTop1Scorer
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from .utils import create_seq_group_metadata_from_prompts, mock_worker
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@pytest.mark.parametrize('num_target_seq_ids', [100])
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@pytest.mark.skip_global_cleanup
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def test_create_target_seq_id_iterator(num_target_seq_ids: int):
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"""Verify all new sequence ids are greater than all input
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seq ids.
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"""
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scorer = BatchExpansionTop1Scorer(mock_worker(), 'cuda:0', 32_000)
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all_seq_ids = [
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[1, 3, 5, 7],
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list(range(100)) + [0],
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[100],
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]
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for seq_ids in all_seq_ids:
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max_seq_id = max(seq_ids)
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iterator = scorer._create_target_seq_id_iterator(seq_ids) # pylint: disable=protected-access
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for _ in range(num_target_seq_ids):
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assert next(iterator) > max_seq_id
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@pytest.mark.parametrize('k', [1, 2, 6])
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@pytest.mark.skip_global_cleanup
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def test_get_token_ids_to_score(k: int):
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"""Verify correct tokens are selected for scoring.
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"""
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proposal_token_ids = torch.tensor(
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list(range(k)),
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dtype=torch.int64,
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device='cuda',
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)
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expected_output: List[List[int]] = [
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[],
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]
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for i in range(proposal_token_ids.shape[0]):
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expected_output.append(proposal_token_ids[:i + 1].tolist())
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scorer = BatchExpansionTop1Scorer(mock_worker(), 'cuda:0', 32_000)
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actual_output = scorer._get_token_ids_to_score(proposal_token_ids.tolist()) # pylint: disable=protected-access
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actual_output = [
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x.tolist() if isinstance(x, torch.Tensor) else x for x in actual_output
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]
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assert actual_output == expected_output
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@pytest.mark.parametrize('k', [1, 2, 6])
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@pytest.mark.skip_global_cleanup
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def test_create_single_target_seq_group_metadata(k: int):
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"""Verify correct creation of a batch-expanded seq group metadata.
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"""
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prompt_tokens = [1, 2, 3]
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prev_output_tokens = [4, 5, 6]
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token_ids = list(range(k))
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num_tokens_processed = len(prompt_tokens) + len(prev_output_tokens) - 1
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final_seq_len = len(prompt_tokens) + len(prev_output_tokens) + len(
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token_ids)
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block_size = 32
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input_seq_group_metadata = create_seq_group_metadata_from_prompts(
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[prompt_tokens], 2048 // block_size, block_size, [final_seq_len],
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[prev_output_tokens], [num_tokens_processed])[0]
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input_seq_id = list(input_seq_group_metadata.seq_data.keys())[0]
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target_seq_id = 100
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scorer = BatchExpansionTop1Scorer(mock_worker(), 'cuda:0', 32_000)
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output = scorer._create_single_target_seq_group_metadata( # pylint: disable=protected-access
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input_seq_group_metadata,
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input_seq_id,
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target_seq_id,
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token_ids,
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input_seq_group_metadata.sampling_params,
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)
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assert output.request_id == input_seq_group_metadata.request_id
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assert output.sampling_params.repetition_penalty == \
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input_seq_group_metadata.sampling_params.repetition_penalty
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assert output.sampling_params.temperature == \
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input_seq_group_metadata.sampling_params.temperature
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assert output.sampling_params.top_p == \
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input_seq_group_metadata.sampling_params.top_p
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assert output.sampling_params.top_k == \
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input_seq_group_metadata.sampling_params.top_k
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assert len(output.seq_data) == 1
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assert output.seq_data[target_seq_id].get_prompt_token_ids() == tuple(
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prompt_tokens)
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assert output.seq_data[target_seq_id].get_output_token_ids() == tuple(
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prev_output_tokens + token_ids)
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assert len(output.block_tables) == 1
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assert output.block_tables[
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target_seq_id] == input_seq_group_metadata.block_tables[input_seq_id]
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