diff --git a/.buildkite/test-amd.yaml b/.buildkite/test-amd.yaml index 2e02d1b404..61f33d74ee 100644 --- a/.buildkite/test-amd.yaml +++ b/.buildkite/test-amd.yaml @@ -586,7 +586,7 @@ steps: - tests/utils.py - tests/models/test_vision.py commands: - - case "$$BUILDKITE_PARALLEL_JOB" in 0) TARGET_TEST_SUITE=MI300 pytest basic_correctness/ -v -s -m 'distributed(num_gpus=2)' && HIP_VISIBLE_DEVICES=0,1 pytest -v -s model_executor/model_loader/test_sharded_state_loader.py -m '(not slow_test)' ;; 1) pytest models/transformers/test_backend.py -v -s -m 'distributed(num_gpus=2)' && pytest models/language -v -s -m 'distributed(num_gpus=2)' && VLLM_ROCM_USE_AITER=1 pytest -v -s models/test_hyv4_rocm.py -m 'distributed(num_gpus=2)' ;; 2) pytest models/multimodal -v -s -m 'distributed(num_gpus=2)' --ignore models/multimodal/generation/test_whisper.py --ignore models/multimodal/generation/test_phi4siglip.py && pytest models/multimodal/generation/test_phi4siglip.py -v -s -m 'distributed(num_gpus=2)' && VLLM_WORKER_MULTIPROC_METHOD=spawn pytest models/multimodal/generation/test_whisper.py -v -s -m 'distributed(num_gpus=2)' && pytest -v -s models/test_vision.py -m 'distributed(num_gpus=2)' ;; *) exit 2 ;; esac + - case "$$BUILDKITE_PARALLEL_JOB" in 0) TARGET_TEST_SUITE=MI300 pytest basic_correctness/ -v -s -m 'distributed(num_gpus=2)' && HIP_VISIBLE_DEVICES=0,1 pytest -v -s model_executor/model_loader/test_sharded_state_loader.py -m '(not slow_test)' ;; 1) pytest models/transformers/test_backend.py -v -s -m 'distributed(num_gpus=2)' && pytest models/language -v -s -m 'distributed(num_gpus=2)' && VLLM_ROCM_USE_AITER=1 pytest -v -s models/test_hyv4_rocm.py -m 'distributed(num_gpus=2)' ;; 2) pytest models/multimodal -v -s -m 'distributed(num_gpus=2)' --ignore models/multimodal/generation/test_whisper.py && VLLM_WORKER_MULTIPROC_METHOD=spawn pytest models/multimodal/generation/test_whisper.py -v -s -m 'distributed(num_gpus=2)' && pytest -v -s models/test_vision.py -m 'distributed(num_gpus=2)' ;; *) exit 2 ;; esac #---------------------------------------------------------- mi300 ยท compile ----------------------------------------------------------# diff --git a/.buildkite/test_areas/models_distributed.yaml b/.buildkite/test_areas/models_distributed.yaml index a054c00db8..9ab75cfc6e 100644 --- a/.buildkite/test_areas/models_distributed.yaml +++ b/.buildkite/test_areas/models_distributed.yaml @@ -26,8 +26,7 @@ steps: pytest models/language -v -s -m 'distributed(num_gpus=2)' ;; 2) - pytest models/multimodal/generation/test_phi4siglip.py -v -s -m 'distributed(num_gpus=2)' - pytest models/multimodal -v -s -m 'distributed(num_gpus=2)' --ignore models/multimodal/generation/test_whisper.py --ignore models/multimodal/generation/test_phi4siglip.py + pytest models/multimodal -v -s -m 'distributed(num_gpus=2)' --ignore models/multimodal/generation/test_whisper.py VLLM_WORKER_MULTIPROC_METHOD=spawn pytest models/multimodal/generation/test_whisper.py -v -s -m 'distributed(num_gpus=2)' ;; *) exit 2 ;; @@ -72,8 +71,7 @@ steps: VLLM_ROCM_USE_AITER=1 pytest -v -s models/test_hyv4_rocm.py -m 'distributed(num_gpus=2)' ;; 2) - pytest models/multimodal -v -s -m 'distributed(num_gpus=2)' --ignore models/multimodal/generation/test_whisper.py --ignore models/multimodal/generation/test_phi4siglip.py && - pytest models/multimodal/generation/test_phi4siglip.py -v -s -m 'distributed(num_gpus=2)' && + pytest models/multimodal -v -s -m 'distributed(num_gpus=2)' --ignore models/multimodal/generation/test_whisper.py && VLLM_WORKER_MULTIPROC_METHOD=spawn pytest models/multimodal/generation/test_whisper.py -v -s -m 'distributed(num_gpus=2)' ;; *) exit 2 ;; diff --git a/tests/compile/passes/test_fusion.py b/tests/compile/passes/test_fusion.py index bb15022459..934522a1b9 100644 --- a/tests/compile/passes/test_fusion.py +++ b/tests/compile/passes/test_fusion.py @@ -60,10 +60,6 @@ from vllm.utils.deep_gemm import ( is_deep_gemm_supported, ) -FP8_DTYPE = current_platform.fp8_dtype() - -RMS_ADD_OP = torch.ops._C.fused_add_rms_norm.default - # Kernel and group_shape combinations: (kernel, group_shape) # CUDA kernels CUDA_KERNEL_GROUPSHAPE_COMBINATIONS = [ diff --git a/tests/compile/passes/test_fusion_attn.py b/tests/compile/passes/test_fusion_attn.py index 759970f14d..6c3ca6b832 100644 --- a/tests/compile/passes/test_fusion_attn.py +++ b/tests/compile/passes/test_fusion_attn.py @@ -248,7 +248,6 @@ class TestAttentionNvfp4QuantPatternModel(AttentionQuantPatternModel): PATTERN_TEST_MODELS_FP8: list[tuple[str, type]] = [] PATTERN_TEST_MODELS_FP4: list[tuple[str, type]] = [] HEADS: list[tuple[int, int]] = [] -SPLIT_ATTENTION: list[bool] = [] BACKENDS_FP8: list[AttentionBackendEnum] = [] BACKENDS_FP4: list[AttentionBackendEnum] = [] diff --git a/tests/conftest.py b/tests/conftest.py index 37bfee1f8b..c1380f61cd 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -317,11 +317,6 @@ def example_system_message() -> str: return f.read() -@pytest.fixture -def example_long_prompts() -> list[str]: - return [prompt for filename in _LONG_PROMPTS for prompt in _read_prompts(filename)] - - @pytest.fixture(scope="session") def image_assets() -> ImageTestAssets: return IMAGE_ASSETS diff --git a/tests/entrypoints/conftest.py b/tests/entrypoints/conftest.py index 27383f87ea..097d56cc9d 100644 --- a/tests/entrypoints/conftest.py +++ b/tests/entrypoints/conftest.py @@ -14,16 +14,6 @@ def sample_prompts(): ] -@pytest.fixture -def sample_token_ids(): - return [ - [0], - [0, 1], - [0, 2, 1], - [0, 3, 1, 2], - ] - - @pytest.fixture def sample_regex(): return ( @@ -61,104 +51,6 @@ def sample_json_schema(): } -@pytest.fixture -def sample_complex_json_schema(): - return { - "type": "object", - "properties": { - "score": { - "type": "integer", - "minimum": 0, - "maximum": 100, # Numeric range - }, - "grade": { - "type": "string", - "pattern": "^[A-D]$", # Regex pattern - }, - "email": { - "type": "string", - "pattern": "^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,}$", - }, - "tags": { - "type": "array", - "items": { - "type": "string", - # Combining length and pattern restrictions - "pattern": "^[a-z]{1,10}$", - }, - }, - }, - "required": ["score", "grade", "email", "tags"], - } - - -@pytest.fixture -def sample_definition_json_schema(): - return { - "$defs": { - "Step": { - "properties": { - "explanation": {"title": "Explanation", "type": "string"}, - "output": {"title": "Output", "type": "string"}, - }, - "required": ["explanation", "output"], - "title": "Step", - "type": "object", - } - }, - "properties": { - "steps": { - "items": {"$ref": "#/$defs/Step"}, - "title": "Steps", - "type": "array", - }, - "final_answer": {"title": "Final Answer", "type": "string"}, - }, - "required": ["steps", "final_answer"], - "title": "MathReasoning", - "type": "object", - } - - -@pytest.fixture -def sample_enum_json_schema(): - return { - "type": "object", - "properties": { - "status": { - "type": "string", - "enum": ["active", "inactive", "pending"], # Literal values using enum - }, - "priority": { - "type": "string", - "enum": ["low", "medium", "high", "critical"], - }, - "category": { - "type": "object", - "properties": { - "type": { - "type": "string", - "enum": ["bug", "feature", "improvement"], - }, - "severity": { - "type": "integer", - "enum": [1, 2, 3, 4, 5], # Enum can also contain numbers - }, - }, - "required": ["type", "severity"], - }, - "flags": { - "type": "array", - "items": { - "type": "string", - "enum": ["urgent", "blocked", "needs_review", "approved"], - }, - }, - }, - "required": ["status", "priority", "category", "flags"], - } - - @pytest.fixture def sample_structured_outputs_choices(): return [ @@ -175,18 +67,6 @@ def sample_structured_outputs_choices(): ] -@pytest.fixture -def sample_sql_statements(): - return """ -start: select_statement -select_statement: "SELECT" column "from" table "where" condition -column: "col_1" | "col_2" -table: "table_1" | "table_2" -condition: column "=" number -number: "1" | "2" -""" - - @pytest.fixture(scope="session") def qwen3_lora_files(): """Download Qwen3 LoRA files once per test session.""" diff --git a/tests/entrypoints/launchers/test_dp_supervisor.py b/tests/entrypoints/launchers/test_dp_supervisor.py index f96b020d10..c10f7ee698 100644 --- a/tests/entrypoints/launchers/test_dp_supervisor.py +++ b/tests/entrypoints/launchers/test_dp_supervisor.py @@ -47,7 +47,6 @@ _SUPERVISOR_PORT = 19256 _CHILD_PORT_BASE = 18000 _N_CHILDREN = 2 _PROBE_INTERVAL = 1.0 -_POLL_INTERVAL = 1.0 # --------------------------------------------------------------------------- diff --git a/tests/entrypoints/openai/responses/test_serving_responses.py b/tests/entrypoints/openai/responses/test_serving_responses.py index 33e5eaa323..d07a89ec9c 100644 --- a/tests/entrypoints/openai/responses/test_serving_responses.py +++ b/tests/entrypoints/openai/responses/test_serving_responses.py @@ -127,14 +127,6 @@ def test_serialize_message_pydantic_model_returns_dict() -> None: assert serialized["message"] == "hello" -@pytest.fixture -def mock_serving_responses(): - """Create a mock OpenAIServingResponses instance.""" - serving_responses = MagicMock(spec=OpenAIServingResponses) - serving_responses.tool_server = MagicMock(spec=ToolServer) - return serving_responses - - @pytest.fixture def mock_context(): """Create a mock conversation context.""" diff --git a/tests/entrypoints/tool_parsers/test_openai_tool_parser.py b/tests/entrypoints/tool_parsers/test_openai_tool_parser.py index de402b435c..f840404111 100644 --- a/tests/entrypoints/tool_parsers/test_openai_tool_parser.py +++ b/tests/entrypoints/tool_parsers/test_openai_tool_parser.py @@ -117,10 +117,7 @@ MESSAGES_INVALID_CALL = [ # Expected outputs FUNC_CALC = "calculator" -FUNC_ARGS_CALC = '{"expression":"123 + 456"}' - FUNC_TIME = "get_time" -FUNC_ARGS_TIME = '{"city": "New York"}' # ========================================================== diff --git a/tests/kernels/attention/test_attention.py b/tests/kernels/attention/test_attention.py index e78ede88f0..e3c3ac0b24 100644 --- a/tests/kernels/attention/test_attention.py +++ b/tests/kernels/attention/test_attention.py @@ -26,7 +26,6 @@ NUM_BLOCKS = 4321 # Arbitrary values for testing PARTITION_SIZE_ROCM = 256 DTYPES = [torch.bfloat16, torch.float16] NUM_GEN_SEQS = [7] # Arbitrary values for testing -NUM_PREFILL_SEQS = [3] # Arbitrary values for testing NUM_HEADS = [(32, 8), (40, 40), (64, 8)] # Arbitrary values for testing # Head sizes supported by the ROCm paged attention kernel. diff --git a/tests/kernels/moe/utils.py b/tests/kernels/moe/utils.py index 71b28a9375..1536c4cec9 100644 --- a/tests/kernels/moe/utils.py +++ b/tests/kernels/moe/utils.py @@ -7,7 +7,6 @@ import torch import vllm._custom_ops as ops from tests.kernels.quant_utils import per_block_cast_to_int8 from tests.kernels.quantization.nvfp4_utils import FLOAT4_E2M1_MAX, FLOAT8_E4M3_MAX -from vllm.model_executor.layers.activation import SiluAndMul from vllm.model_executor.layers.fused_moe.activation import MoEActivation from vllm.model_executor.layers.fused_moe.all2all_utils import ( maybe_make_prepare_finalize, @@ -552,97 +551,6 @@ class TestMLP(torch.nn.Module): return x -class RealMLP(torch.nn.Module): - def __init__( - self, - hidden_size: int, - intermediate_size: int, - w1: torch.Tensor, - w2: torch.Tensor, - hidden_act: str = "silu", - quant_config=None, - reduce_results: bool = True, - prefix: str = "", - w1_s: torch.Tensor | None = None, - w2_s: torch.Tensor | None = None, - ) -> None: - from vllm.model_executor.layers.linear import ( - MergedColumnParallelLinear, - RowParallelLinear, - ) - - super().__init__() - self.gate_up_proj = MergedColumnParallelLinear( - hidden_size, - [intermediate_size] * 2, - bias=False, - quant_config=quant_config, - prefix=f"{prefix}.gate_up_proj", - ) - self.gate_up_proj.register_parameter( - "weight", torch.nn.Parameter(w1, requires_grad=False) - ) - self.gate_up_proj.register_parameter( - "weight_scale", torch.nn.Parameter(w1_s, requires_grad=False) - ) - self.gate_up_proj.register_parameter( - "input_scale", None - ) # torch.nn.Parameter(None, requires_grad=False)) - self.down_proj = RowParallelLinear( - intermediate_size, - hidden_size, - bias=False, - quant_config=quant_config, - reduce_results=reduce_results, - prefix=f"{prefix}.down_proj", - ) - self.down_proj.register_parameter( - "weight", torch.nn.Parameter(w2, requires_grad=False) - ) - self.down_proj.register_parameter( - "weight_scale", torch.nn.Parameter(w2_s, requires_grad=False) - ) - self.down_proj.register_parameter( - "input_scale", None - ) # torch.nn.Parameter(None, requires_grad=False)) - if hidden_act != "silu": - raise ValueError( - f"Unsupported activation: {hidden_act}. Only silu is supported for now." - ) - self.act_fn = SiluAndMul() - - def forward(self, x): - gate_up, _ = self.gate_up_proj(x) - x = self.act_fn(gate_up) - x, _ = self.down_proj(x) - return x - - -def make_shared_experts_with_weights( - N: int, - K: int, - in_dtype: torch.dtype, - w1: torch.Tensor, - w2: torch.Tensor, - w1_s: torch.Tensor | None = None, - w2_s: torch.Tensor | None = None, - quant_dtype: torch.dtype | str | None = None, -) -> torch.nn.Module: - old_dtype = torch.get_default_dtype() - try: - torch.set_default_dtype(in_dtype) - if quant_dtype == torch.float8_e4m3fn: - from vllm.model_executor.layers.quantization.fp8 import Fp8Config - - quant_config = Fp8Config() - else: - quant_config = None - - return RealMLP(K, N, w1, w2, "silu", quant_config, w1_s=w1_s, w2_s=w2_s) - finally: - torch.set_default_dtype(old_dtype) - - def modular_triton_fused_moe( moe_config: FusedMoEConfig, quant_config: FusedMoEQuantConfig, diff --git a/tests/lora/conftest.py b/tests/lora/conftest.py index f5ca44f174..59690401e5 100644 --- a/tests/lora/conftest.py +++ b/tests/lora/conftest.py @@ -76,18 +76,6 @@ def dist_init(): cleanup_dist_env_and_memory(shutdown_ray=True) -@pytest.fixture -def dist_init_torch_only(): - if torch.distributed.is_initialized(): - return - backend = current_platform.dist_backend - - temp_file = tempfile.mkstemp()[1] - torch.distributed.init_process_group( - world_size=1, rank=0, init_method=f"file://{temp_file}", backend=backend - ) - - class DummyLoRAModel(nn.Sequential, SupportsLoRA): pass @@ -208,12 +196,6 @@ def qwen2vl_lora_files(): return hf_api().snapshot_download(repo_id="jeeejeee/qwen2-vl-lora-pokemon") -@pytest.fixture(scope="session") -def qwen25vl_base_huggingface_id(): - # used as a base model for testing with qwen25vl lora adapter - return "Qwen/Qwen2.5-VL-3B-Instruct" - - @pytest.fixture(scope="session") def qwen25vl_lora_files(): return hf_api().snapshot_download(repo_id="jeeejeee/qwen25-vl-lora-pokemon") diff --git a/tests/models/multimodal/generation/test_phi4siglip.py b/tests/models/multimodal/generation/test_phi4siglip.py deleted file mode 100644 index f80b16c341..0000000000 --- a/tests/models/multimodal/generation/test_phi4siglip.py +++ /dev/null @@ -1,198 +0,0 @@ -# SPDX-License-Identifier: Apache-2.0 -# SPDX-FileCopyrightText: Copyright contributors to the vLLM project - -from collections.abc import Sequence -from importlib.metadata import version - -import pytest -import regex as re -from packaging.version import Version -from transformers import AutoModelForCausalLM, AutoTokenizer - -from vllm.logprobs import SampleLogprobs -from vllm.multimodal.image import rescale_image_size - -from ....conftest import ( - IMAGE_ASSETS, - HfRunner, - PromptImageInput, - VllmRunner, -) -from ....utils import multi_gpu_test -from ...utils import check_logprobs_close - -pytestmark = pytest.mark.skipif( - Version("5.0") <= Version(version("transformers")), - reason=( - "vllm upgraded transformers above v5.4 where HF model custom code uses siglip2 " - "internals (filter_out_non_signature_kwargs) removed by " - "huggingface/transformers#43514" - ), -) - -MODEL_ID = "microsoft/Phi-4-reasoning-vision-15B" - -HF_IMAGE_PROMPTS = IMAGE_ASSETS.prompts( - { - "stop_sign": "<|user|>\n\nWhat's the content of the image?<|end|>\n<|assistant|>\n", # noqa: E501 - "cherry_blossom": "<|user|>\n\nPlease infer the season with reason in details.<|end|>\n<|assistant|>\n", # noqa: E501 - } -) -HF_MULTIIMAGE_IMAGE_PROMPT = ( - "<|user|>\n\n\nDescribe these images.<|end|>\n<|assistant|>\n" # noqa: E501 -) - -DTYPE = "half" -MAX_TOKENS = 128 -NUM_LOGPROBS = 10 - - -def vllm_to_hf_output( - vllm_output: tuple[list[int], str, SampleLogprobs | None], model: str -): - """Sanitize vllm output to be comparable with hf output.""" - _, output_str, out_logprobs = vllm_output - - output_str_without_image = re.sub(r"()+", "", output_str) - if output_str_without_image and output_str_without_image[0] == " ": - output_str_without_image = output_str_without_image[1:] - - hf_output_str = output_str_without_image + "<|end|><|endoftext|>" - - tokenizer = AutoTokenizer.from_pretrained(model, trust_remote_code=True) - hf_output_ids = tokenizer.encode(output_str_without_image) - if hf_output_ids and hf_output_ids[0] == tokenizer.bos_token_id: - hf_output_ids = hf_output_ids[1:] - - return hf_output_ids, hf_output_str, out_logprobs - - -def _build_single_image_inputs( - image_assets, -) -> list[tuple[list[str], PromptImageInput]]: - """Build single-image inputs for all size_factors at once.""" - images = [asset.pil_image for asset in image_assets] - all_inputs: list[tuple[list[str], PromptImageInput]] = [] - for size_factors in [[1.0], [0.25, 0.5, 1.0]]: - for image, prompt in zip(images, HF_IMAGE_PROMPTS): - all_inputs.append( - ( - [prompt for _ in size_factors], - [rescale_image_size(image, f) for f in size_factors], - ) - ) - return all_inputs - - -def _build_multi_image_inputs( - image_assets, -) -> list[tuple[list[str], PromptImageInput]]: - """Build multi-image inputs for all size_factors at once.""" - images = [asset.pil_image for asset in image_assets] - all_inputs: list[tuple[list[str], PromptImageInput]] = [] - for size_factors in [[0.5], [0.15, 0.30]]: - all_inputs.append( - ( - [HF_MULTIIMAGE_IMAGE_PROMPT for _ in size_factors], - [ - [rescale_image_size(image, factor) for image in images] - for factor in size_factors - ], - ) - ) - return all_inputs - - -def _run_and_compare( - hf_runner: type[HfRunner], - vllm_runner: type[VllmRunner], - all_inputs: Sequence[tuple[list[str], PromptImageInput]], - model: str, - max_model_len: int, - max_num_seqs: int, - mm_limit: int, - gpu_memory_utilization: float, -): - """Load each runner once, run all inputs, then compare.""" - # NOTE: run vLLM first, then HF. vLLM needs a fresh process without - # cuda initialization; running HF first would break the multiprocessing - # backend with fork method. - with vllm_runner( - model, - runner="generate", - max_model_len=max_model_len, - max_num_seqs=max_num_seqs, - gpu_memory_utilization=gpu_memory_utilization, - dtype=DTYPE, - limit_mm_per_prompt={"image": mm_limit}, - tensor_parallel_size=2, - trust_remote_code=True, - enforce_eager=True, - ) as vllm_model: - vllm_outputs_per_case = [ - vllm_model.generate_greedy_logprobs( - prompts, - MAX_TOKENS, - num_logprobs=NUM_LOGPROBS, - images=images, - ) - for prompts, images in all_inputs - ] - - hf_model_kwargs = {"_attn_implementation": "sdpa", "device_map": "auto"} - with hf_runner( - model, - dtype=DTYPE, - model_kwargs=hf_model_kwargs, - auto_cls=AutoModelForCausalLM, - trust_remote_code=True, - ) as hf_model: - hf_outputs_per_case = [ - hf_model.generate_greedy_logprobs_limit( - prompts, - MAX_TOKENS, - num_logprobs=NUM_LOGPROBS, - images=images, - ) - for prompts, images in all_inputs - ] - - for hf_outputs, vllm_outputs in zip(hf_outputs_per_case, vllm_outputs_per_case): - check_logprobs_close( - outputs_0_lst=hf_outputs, - outputs_1_lst=vllm_outputs, - name_0="hf", - name_1="vllm", - ) - - -@multi_gpu_test(num_gpus=2) -@pytest.mark.parametrize("model", [MODEL_ID]) -def test_models(hf_runner, vllm_runner, image_assets, model) -> None: - all_inputs = _build_single_image_inputs(image_assets) - _run_and_compare( - hf_runner, - vllm_runner, - all_inputs, - model, - max_model_len=8192, - max_num_seqs=2, - mm_limit=1, - gpu_memory_utilization=0.80, - ) - - -@multi_gpu_test(num_gpus=2) -@pytest.mark.parametrize("model", [MODEL_ID]) -def test_multi_images_models(hf_runner, vllm_runner, image_assets, model) -> None: - all_inputs = _build_multi_image_inputs(image_assets) - _run_and_compare( - hf_runner, - vllm_runner, - all_inputs, - model, - max_model_len=8192, - max_num_seqs=2, - mm_limit=2, - gpu_memory_utilization=0.80, - ) diff --git a/tests/reasoning/test_kimi_k2_reasoning_parser.py b/tests/reasoning/test_kimi_k2_reasoning_parser.py index dc0947fdb2..e9690b2faa 100644 --- a/tests/reasoning/test_kimi_k2_reasoning_parser.py +++ b/tests/reasoning/test_kimi_k2_reasoning_parser.py @@ -1,7 +1,6 @@ # SPDX-License-Identifier: Apache-2.0 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project -from unittest.mock import MagicMock import pytest @@ -13,20 +12,6 @@ from vllm.tokenizers import get_tokenizer REASONING_MODEL_NAME = "moonshotai/Kimi-K2.5" -@pytest.fixture -def mock_kimi_k2_tokenizer(): - tokenizer = MagicMock() - tokenizer.get_vocab.return_value = { - "": 100, - "": 101, - "<|tool_calls_section_begin|>": 200, - "<|tool_calls_section_end|>": 201, - "<|tool_call_begin|>": 202, - "<|tool_call_end|>": 203, - } - return tokenizer - - @pytest.fixture(scope="module") def kimi_k2_tokenizer(): return get_tokenizer(tokenizer_name=REASONING_MODEL_NAME, trust_remote_code=True) diff --git a/tests/tracing/conftest.py b/tests/tracing/conftest.py index 635d4fd257..97b2afa0c8 100644 --- a/tests/tracing/conftest.py +++ b/tests/tracing/conftest.py @@ -142,9 +142,3 @@ def trace_service() -> Generator[FakeTraceService, None, None]: yield service server.stop(grace=None) - - -@pytest.fixture -def trace_server_address() -> str: - """Returns the address of the fake trace server.""" - return FAKE_TRACE_SERVER_ADDRESS diff --git a/tests/v1/engine/conftest.py b/tests/v1/engine/conftest.py index 1cfe671a62..e382b9fdca 100644 --- a/tests/v1/engine/conftest.py +++ b/tests/v1/engine/conftest.py @@ -2,7 +2,6 @@ # SPDX-FileCopyrightText: Copyright contributors to the vLLM project import pytest -import torch from transformers import AutoTokenizer from tests.v1.engine.utils import ( @@ -19,9 +18,6 @@ from vllm.engine.arg_utils import EngineArgs from ...distributed.conftest import publisher_config, random_port # noqa: F401 -EngineCoreSampleLogprobsType = list[tuple[torch.Tensor, torch.Tensor]] -EngineCorePromptLogprobsType = tuple[torch.Tensor, torch.Tensor] - def _build_test_vectors_no_logprobs() -> DummyOutputProcessorTestVectors: """Generate output processor dummy test vectors, without logprobs. diff --git a/tests/v1/engine/test_llm_engine.py b/tests/v1/engine/test_llm_engine.py index e0e6004b0e..c9832f7d8e 100644 --- a/tests/v1/engine/test_llm_engine.py +++ b/tests/v1/engine/test_llm_engine.py @@ -49,13 +49,6 @@ def vllm_model(vllm_runner, request): yield vllm_model -@pytest.fixture(scope="function") -def vllm_model_apc(vllm_runner): - """VllmRunner test fixture with APC.""" - with _vllm_model(True, vllm_runner) as vllm_model: - yield vllm_model - - @pytest.fixture( # Function scope decouples tests & allows # env var adjustment via monkeypatch