156 lines
4.7 KiB
Python
156 lines
4.7 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""
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This test file includes some cases where it is inappropriate to
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only get the `eos_token_id` from the tokenizer as defined by
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`BaseRenderer.get_eos_token_id`.
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"""
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from types import SimpleNamespace
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from typing import cast
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from unittest.mock import MagicMock, patch
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import pytest
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from transformers import PretrainedConfig
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from vllm.config.model import ModelConfig
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from vllm.tokenizers import get_tokenizer
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from vllm.transformers_utils import config as config_module
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from vllm.transformers_utils.config import (
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get_safetensors_params_metadata,
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try_get_generation_config,
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)
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from vllm.transformers_utils.configs.glm5_next import (
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Glm5NextConfig,
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Glm5NextTextConfig,
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Glm5NextVisionConfig,
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)
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def test_glm5_next_accepts_deepseek_sparse_attention_layers():
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layer_types = ["linear_attention", "deepseek_sparse_attention"]
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config = Glm5NextTextConfig(
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num_hidden_layers=len(layer_types), layer_types=layer_types
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)
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assert config.layer_types == layer_types
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assert config.layers_block_type == ["linear_attention", "attention"]
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def test_glm5_next_accepts_prebuilt_subconfigs():
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text_config = Glm5NextTextConfig(hidden_size=1024)
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vision_config = Glm5NextVisionConfig(hidden_size=768)
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config = Glm5NextConfig(
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text_config=text_config,
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vision_config=vision_config,
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)
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assert config.text_config is text_config
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assert config.vision_config is vision_config
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@pytest.mark.parametrize(
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("kwargs", "option"),
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[
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(
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{"index_topk": 2048, "index_dsa_use_layernorm": False},
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"index_dsa_use_layernorm",
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),
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(
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{"index_topk": 2048, "index_kpool_compress": False},
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"index_kpool_compress",
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),
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(
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{"index_topk": 2048, "index_kpool_always_select_tail": False},
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"index_kpool_always_select_tail",
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),
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({"hres_vwnstyle": False}, "hres_vwnstyle"),
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({"mhc_no_norm_weight": True}, "mhc_no_norm_weight"),
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],
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)
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def test_glm5_next_rejects_unimplemented_config_options(kwargs, option):
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with pytest.raises(NotImplementedError, match=option):
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Glm5NextTextConfig(**kwargs)
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def test_get_llama3_eos_token():
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model_name = "meta-llama/Llama-3.2-1B-Instruct"
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tokenizer = get_tokenizer(model_name)
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assert tokenizer.eos_token_id == 128009
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generation_config = try_get_generation_config(model_name, trust_remote_code=False)
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assert generation_config is not None
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assert generation_config.eos_token_id == [128001, 128008, 128009]
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def test_get_blip2_eos_token():
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model_name = "Salesforce/blip2-opt-2.7b"
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tokenizer = get_tokenizer(model_name)
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assert tokenizer.eos_token_id == 2
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generation_config = try_get_generation_config(model_name, trust_remote_code=False)
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assert generation_config is not None
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assert generation_config.eos_token_id == 50118
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def test_model_config_generation_fallback_forwards_code_revision():
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model_config = cast(
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ModelConfig,
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SimpleNamespace(
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generation_config="auto",
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hf_config_path=None,
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model="org/model",
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trust_remote_code=True,
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revision="model-pin",
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code_revision="code-pin",
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config_format="auto",
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hf_token=None,
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),
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)
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with (
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patch.object(
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config_module.GenerationConfig,
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"from_pretrained",
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side_effect=OSError,
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),
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patch.object(
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config_module,
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"get_config",
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return_value=PretrainedConfig(),
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) as get_config,
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):
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ModelConfig.try_get_generation_config(model_config)
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get_config.assert_called_once_with(
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"org/model",
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trust_remote_code=True,
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revision="model-pin",
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code_revision="code-pin",
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config_format="auto",
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token=None,
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)
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def test_safetensors_metadata_of_repo_without_safetensors():
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"""A repo storing its weights in another format is an answer, not a failure,
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so it must not be retried."""
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from huggingface_hub.errors import LocalEntryNotFoundError, NotASafetensorsRepoError
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get_safetensors_metadata = MagicMock(
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side_effect=NotASafetensorsRepoError("not a safetensors repo")
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)
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api = SimpleNamespace(
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get_safetensors_metadata=get_safetensors_metadata,
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snapshot_download=MagicMock(side_effect=LocalEntryNotFoundError("no cache")),
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)
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with patch.object(config_module, "hf_api", lambda: api):
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assert get_safetensors_params_metadata("some/pytorch-only-model") == {}
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get_safetensors_metadata.assert_called_once()
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