diff --git a/.github/actions/free-up-disk-space/action.yml b/.github/actions/free-up-disk-space/action.yml new file mode 100644 index 000000000..a0c980ab3 --- /dev/null +++ b/.github/actions/free-up-disk-space/action.yml @@ -0,0 +1,46 @@ +name: "Free up disk space" +description: "Removes non-essential tools, libraries and cached files from GitHub action runner node" + +runs: + using: "composite" + steps: + - name: "Remove non-essential tools and libraries" + shell: bash + run: | + # https://github.com/actions/runner-images/issues/2840#issuecomment-790492173 + echo "Disk usage before cleanup:" + df -h + echo "Removing non-essential tools and libraries ..." + sudo rm -rf /opt/ghc + sudo rm -rf /usr/local/.ghcup + sudo rm -rf /usr/share/dotnet + # sudo rm -rf /usr/local/share/boost + echo "Deleting libraries for Android (12G), CodeQL (5.3G), PowerShell (1.3G), Swift (1.7G) ..." + sudo rm -rf /usr/local/lib/android + sudo rm -rf "${AGENT_TOOLSDIRECTORY}/CodeQL" + sudo rm -rf /usr/local/share/powershell + sudo rm -rf /usr/share/swift + # ref: https://github.com/jlumbroso/free-disk-space/blob/main/action.yml + echo "Deleting some larger apt packages:" + sudo apt-get remove -y '^aspnetcore-.*' || echo "::warning::The command [sudo apt-get remove -y '^aspnetcore-.*'] failed to complete successfully. Proceeding..." + sudo apt-get remove -y '^dotnet-.*' --fix-missing || echo "::warning::The command [sudo apt-get remove -y '^dotnet-.*' --fix-missing] failed to complete successfully. Proceeding..." + sudo apt-get remove -y '^llvm-.*' --fix-missing || echo "::warning::The command [sudo apt-get remove -y '^llvm-.*' --fix-missing] failed to complete successfully. Proceeding..." + sudo apt-get remove -y 'php.*' --fix-missing || echo "::warning::The command [sudo apt-get remove -y 'php.*' --fix-missing] failed to complete successfully. Proceeding..." + sudo apt-get remove -y '^mongodb-.*' --fix-missing || echo "::warning::The command [sudo apt-get remove -y '^mongodb-.*' --fix-missing] failed to complete successfully. Proceeding..." + sudo apt-get remove -y '^mysql-.*' --fix-missing || echo "::warning::The command [sudo apt-get remove -y '^mysql-.*' --fix-missing] failed to complete successfully. Proceeding..." + sudo apt-get remove -y azure-cli google-chrome-stable firefox powershell mono-devel libgl1-mesa-dri --fix-missing || echo "::warning::The command [sudo apt-get remove -y azure-cli google-chrome-stable firefox powershell mono-devel libgl1-mesa-dri --fix-missing] failed to complete successfully. Proceeding..." + sudo apt-get remove -y google-cloud-sdk --fix-missing || echo "::debug::The command [sudo apt-get remove -y google-cloud-sdk --fix-missing] failed to complete successfully. Proceeding..." + sudo apt-get remove -y google-cloud-cli --fix-missing || echo "::debug::The command [sudo apt-get remove -y google-cloud-cli --fix-missing] failed to complete successfully. Proceeding..." + sudo apt-get autoremove -y || echo "::warning::The command [sudo apt-get autoremove -y] failed to complete successfully. Proceeding..." + sudo apt-get clean || echo "::warning::The command [sudo apt-get clean] failed to complete successfully. Proceeding..." + echo "Disk usage after cleanup:" + df -h + + - name: "Prune docker images" + shell: bash + run: | + echo "Pruning docker images ..." + docker image prune -a -f + docker system df + echo "Disk usage after pruning docker images:" + df -h \ No newline at end of file diff --git a/.github/workflows/build_docker.yml b/.github/workflows/build_docker.yml index a0750d0bb..81b6d3927 100644 --- a/.github/workflows/build_docker.yml +++ b/.github/workflows/build_docker.yml @@ -43,6 +43,9 @@ jobs: with: fetch-depth: 0 + - name: "Free up disk space" + uses: ./.github/actions/free-up-disk-space + - name: "Set up QEMU" uses: docker/setup-qemu-action@v3 diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 0be63c9f8..3f0ac0d79 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -79,6 +79,7 @@ jobs: markers: "precompilation and not quantized" flags: "--timeout=300" include: + # Lower bound support - vllm_version: name: "vLLM:lowest" repo: "git+https://github.com/vllm-project/vllm --tag v0.10.2" @@ -90,6 +91,19 @@ jobs: hf_model_2_rev: "cf74d8acd4f198de950bf004b262e6accfed5d2c" os: "ubuntu-latest" python_version: "3.12" + # Intermediate versions of vllm to check basic support for as well + - vllm_version: + name: "vLLM:0.11.0" + repo: "git+https://github.com/vllm-project/vllm --tag v0.11.0" + test_suite: + name: "backward compat" + markers: "compat or (cpu and basic)" + flags: "--timeout=300" + hf_model_2: "sentence-transformers/all-roberta-large-v1" + hf_model_2_rev: "cf74d8acd4f198de950bf004b262e6accfed5d2c" + os: "ubuntu-latest" + python_version: "3.12" + # Exclude vLLM:main if PR does NOT have "ready" label AND auto-merge is not enabled exclude: >- ${{ diff --git a/pyproject.toml b/pyproject.toml index f8a7d7c11..3db5b7370 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -11,9 +11,9 @@ description = "vLLM plugin for Spyre hardware support" readme = "README.md" license = {text = "Apache 2"} dependencies = [ - "fms-model-optimizer[fp8]>=0.6.0", + "fms-model-optimizer[fp8]>=0.8.0", "ibm-fms>=1.5.0,<2.0", - "vllm>=0.10.2,<=0.11.0", + "vllm>=0.10.2,<=0.11.1", "pytest-mock>=3.15.0", ] requires-python = ">=3.11" @@ -50,6 +50,7 @@ override-dependencies = [ "torchaudio; sys_platform == 'never'", "torchvision; sys_platform == 'never'", "triton; sys_platform == 'never'", + "intel-extension-for-pytorch; sys_platform == 'never'", # Skip packages on s390x and ppc64le, expected to be pre-installed "vllm ; platform_machine not in 's390x, ppc64le'", @@ -62,6 +63,9 @@ environments = [ "python_version > '3.9'" ] +[tool.uv.sources] +vllm = { git = "https://github.com/vllm-project/vllm", rev = "v0.11.1" } + [tool.ruff] # Allow lines to be as long as 80. line-length = 80 diff --git a/tests/e2e/test_chunked_prefill_tkv_steps.py b/tests/e2e/test_chunked_prefill_tkv_steps.py index 412519b98..6f9ea3b06 100644 --- a/tests/e2e/test_chunked_prefill_tkv_steps.py +++ b/tests/e2e/test_chunked_prefill_tkv_steps.py @@ -20,6 +20,7 @@ from vllm_spyre.platform import SpyrePlatform from vllm_spyre.v1.worker.spyre_model_runner import SpyreModelRunner +from vllm_spyre.v1.worker.spyre_worker import _get_extra_args ########## Assuming that we have: @@ -107,6 +108,7 @@ def make_scheduler_output( if finished_req_ids is None: finished_req_ids = set() + extra_args = _get_extra_args() return SchedulerOutput(scheduled_new_reqs=scheduled_new_reqs, scheduled_cached_reqs=scheduled_cached_reqs, num_scheduled_tokens=num_scheduled_tokens, @@ -115,10 +117,8 @@ def make_scheduler_output( scheduled_encoder_inputs={}, num_common_prefix_blocks=[], finished_req_ids=finished_req_ids, - free_encoder_mm_hashes=[], - structured_output_request_ids={}, - grammar_bitmask=None, - kv_connector_metadata=None) + kv_connector_metadata=None, + **extra_args) def make_new_request_data(req_id, prompt_len): diff --git a/tests/e2e/test_spyre_cb.py b/tests/e2e/test_spyre_cb.py index ee326c51a..acf88bf07 100644 --- a/tests/e2e/test_spyre_cb.py +++ b/tests/e2e/test_spyre_cb.py @@ -37,7 +37,10 @@ def test_cb_max_tokens(model: ModelInfo, backend: str, max_model_len: int, ignore_eos=True, logprobs=0) - with pytest.raises(ValueError, match="max model context length"): + # The text of the error raised by vllm changed from 0.11.0 to 0.11.1 + with pytest.raises( + ValueError, + match="(max model context length|maximum model length)"): generate_spyre_vllm_output( model=model, prompts=overflow_prompt, diff --git a/tests/llm_cache.py b/tests/llm_cache.py index bba57027f..a3f2ff623 100644 --- a/tests/llm_cache.py +++ b/tests/llm_cache.py @@ -234,7 +234,7 @@ def get_engine( # Set scheduler configs for max_model_len and max_num_seqs to the # original values. They were changed for more robust compilation only. - engine_core.scheduler.scheduler_config.max_model_len = max_model_len + engine_core.scheduler.model_config.max_model_len = max_model_len engine_core.scheduler.scheduler_config.max_num_seqs = max_num_seqs if available_blocks is not None: diff --git a/tests/spyre_util.py b/tests/spyre_util.py index 31b759684..8d2e93711 100644 --- a/tests/spyre_util.py +++ b/tests/spyre_util.py @@ -14,7 +14,15 @@ from transformers import AutoTokenizer from vllm import SamplingParams from vllm.entrypoints.openai.cli_args import make_arg_parser -from vllm.utils import FlexibleArgumentParser, get_open_port + +try: + # old + from vllm.utils import FlexibleArgumentParser, get_open_port +except ImportError: + # new + from vllm.utils.argparse_utils import FlexibleArgumentParser + from vllm.utils.network_utils import get_open_port + from vllm.v1.request import Request EmbeddingWarmupShapes = list[tuple[int, int]] diff --git a/tests/utils/test_upstream_compatibility.py b/tests/utils/test_upstream_compatibility.py index 63f9ec0ee..260018b24 100644 --- a/tests/utils/test_upstream_compatibility.py +++ b/tests/utils/test_upstream_compatibility.py @@ -1,7 +1,7 @@ import os import pytest -from vllm.v1.core.sched.output import NewRequestData +from vllm.v1.core.sched.output import NewRequestData, SchedulerOutput from vllm.v1.kv_cache_interface import FullAttentionSpec from vllm_spyre.compat_utils import dataclass_fields @@ -33,3 +33,40 @@ def test_use_mla(): if VLLM_VERSION == "vLLM:lowest": # Can remove backwards compatibility for use_mla assert "use_mla" in dataclass_fields(FullAttentionSpec) + + +def test_pin_memory_available(): + if VLLM_VERSION == "vLLM:lowest": + try: + from vllm.utils import is_pin_memory_available # # noqa + from vllm.utils import make_tensor_with_pad # # noqa + except ImportError as e: + raise AssertionError("remove backwards compatibility imports for " + "is_pin_memory_available and " + "make_tensor_with_pad") from e + + +def test_multi_modal_cache_stats(): + if VLLM_VERSION == "vLLM:lowest": + # If this import succeeds then remove the backwards compatibility type + # def for MultiModalCacheStats + with pytest.raises(ImportError): + from vllm.v1.metrics.stats import MultiModalCacheStats # # noqa + + +def test_v0_worker_base(): + if VLLM_VERSION == "vLLM:lowest": + try: + from vllm.worker.worker_base import WorkerBase # # noqa + except ImportError as e: + raise AssertionError( + "remove the backwards compatibility code from " + "the SpyreWorker initializer") from e + + +def test_structured_output_request_ids(): + if VLLM_VERSION == "vLLM:lowest": + # Can remove "structured_output_request_ids" and "grammar_bitmask" + # from backwards compat + assert 'structured_output_request_ids' in dataclass_fields( + SchedulerOutput) diff --git a/tests/v1/worker/test_spyre_input_batch.py b/tests/v1/worker/test_spyre_input_batch.py index a3b621ee9..c4e8f476f 100644 --- a/tests/v1/worker/test_spyre_input_batch.py +++ b/tests/v1/worker/test_spyre_input_batch.py @@ -6,7 +6,13 @@ import pytest import torch from vllm.sampling_params import SamplingParams -from vllm.utils import is_pin_memory_available, make_tensor_with_pad + +try: + from vllm.utils import is_pin_memory_available, make_tensor_with_pad +except ImportError: + from vllm.utils.platform_utils import is_pin_memory_available + from vllm.utils.torch_utils import make_tensor_with_pad + from vllm.v1.sample.logits_processor import LogitsProcessors from vllm.v1.sample.metadata import SamplingMetadata diff --git a/uv.lock b/uv.lock index 06207da1a..8b0a112cc 100644 --- a/uv.lock +++ b/uv.lock @@ -1,15 +1,24 @@ version = 1 -revision = 3 +revision = 2 requires-python = ">=3.11" resolution-markers = [ - "python_full_version >= '3.12'", - "python_full_version < '3.12'", + "python_full_version >= '3.12' and platform_machine != 'aarch64' and sys_platform == 'darwin'", + "python_full_version >= '3.12' and platform_machine != 'aarch64' and sys_platform != 'darwin'", + "python_full_version >= '3.12' and platform_machine == 'aarch64' and sys_platform == 'darwin'", + "python_full_version >= '3.12' and platform_machine == 'aarch64' and sys_platform == 'linux'", + "python_full_version >= '3.12' and platform_machine == 'aarch64' and sys_platform != 'darwin' and sys_platform != 'linux'", + "python_full_version < '3.12' and platform_machine != 'aarch64' and sys_platform == 'darwin'", + "python_full_version < '3.12' and platform_machine != 'aarch64' and sys_platform != 'darwin'", + "python_full_version < '3.12' and platform_machine == 'aarch64' and sys_platform == 'darwin'", + "python_full_version < '3.12' and platform_machine == 'aarch64' and sys_platform == 'linux'", + "python_full_version < '3.12' and platform_machine == 'aarch64' and sys_platform != 'darwin' and sys_platform != 'linux'", ] supported-markers = [ ] [manifest] overrides = [ + { name = "intel-extension-for-pytorch", marker = 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a/vllm_spyre/model_executor/model_loader/spyre.py b/vllm_spyre/model_executor/model_loader/spyre.py index c5d8b4e6a..d44f7ab53 100644 --- a/vllm_spyre/model_executor/model_loader/spyre.py +++ b/vllm_spyre/model_executor/model_loader/spyre.py @@ -316,7 +316,7 @@ def __init__( rank: int, ) -> None: BLOCK_SIZE = SpyrePlatform.get_block_size() - max_model_len = vllm_config.scheduler_config.max_model_len + max_model_len = vllm_config.model_config.max_model_len # edge case: prompt fills model length: can produce 1 token with prefill max_prompt_length = max_model_len @@ -363,6 +363,12 @@ def __init__( self.current_scale: Optional[list[tuple]] = None def set_past_key_value_states(self, num_blocks) -> None: + + print("\n\n\n\n\t\tNUM BLOCKS:", num_blocks) + print("\t\tBLOCK SIZE:", self.kv_cache_specs['block_size']) + print("\t\tNUM KV HEADS:", self.kv_cache_specs['num_kv_heads']) + print("\t\tHEAD DIM:", self.kv_cache_specs['head_dim']) + # List[layers] of Tuple[k,v] of # Tensor[num_blocks, block_size, num_kv_heads, head_dim] if not self.model_config.quantization: diff --git a/vllm_spyre/platform.py b/vllm_spyre/platform.py index fa244bbd7..950d4aed3 100644 --- a/vllm_spyre/platform.py +++ b/vllm_spyre/platform.py @@ -19,14 +19,18 @@ from transformers.models.granite import GraniteConfig from vllm.inputs import ProcessorInputs, PromptType from vllm.logger import init_logger -from vllm.pooling_params import PoolingParams -from vllm.sampling_params import SamplingParams if TYPE_CHECKING: + # NB: We can't eagerly import many things from vllm since vllm.config + # will import this file. These would lead to circular imports from vllm.config import ModelConfig, VllmConfig + from vllm.pooling_params import PoolingParams + from vllm.sampling_params import SamplingParams else: ModelConfig = None VllmConfig = None + SamplingParams = None + PoolingParams = None from vllm.platforms import Platform, PlatformEnum import vllm_spyre.envs as envs_spyre @@ -346,6 +350,10 @@ def validate_request( processed_inputs: ProcessorInputs | None = None, ) -> None: """Raises if this request is unsupported on this platform""" + + # The PoolingParams import is lazy here because it imports vllm.config, + # which will in turn import this file again. + from vllm.pooling_params import PoolingParams if isinstance(params, PoolingParams): # Only validating generation requests for now return None @@ -379,13 +387,13 @@ def validate_request( prompt_padding_len = math.ceil( prompt_len / cls._block_size) * cls._block_size if (prompt_padding_len + max_tokens - > cls._config.scheduler_config.max_model_len): + > cls._config.model_config.max_model_len): raise ValueError( "Could not add request: prompt length is " f"{prompt_len} tokens, which gets padded to " f"{prompt_padding_len} tokens, maximum number of output " f"tokens is {max_tokens} tokens, but max model context " - f"length is {cls._config.scheduler_config.max_model_len}.") + f"length is {cls._config.model_config.max_model_len}.") else: # For non-continuous batching, check if the request matches a warmup # shape @@ -545,7 +553,7 @@ def get_max_output_tokens(self, prompt_len: int) -> int: # ceil division to pad to next block boundary padded_prompt_len = math.ceil( prompt_len / self._block_size) * self._block_size - max_new_tokens = (self._config.scheduler_config.max_model_len - + max_new_tokens = (self._config.model_config.max_model_len - padded_prompt_len) return max_new_tokens diff --git a/vllm_spyre/v1/core/scheduler.py b/vllm_spyre/v1/core/scheduler.py index 71fd5047c..e69cd2ae2 100644 --- a/vllm_spyre/v1/core/scheduler.py +++ b/vllm_spyre/v1/core/scheduler.py @@ -33,6 +33,7 @@ class SpyreScheduler(Scheduler): def __init__(self, *args, **kwargs) -> None: # Initialize vLLM scheduler super().__init__(*args, **kwargs) + self.model_config = self.vllm_config.model_config class StaticBatchingSpyreScheduler(SpyreScheduler): @@ -222,7 +223,7 @@ def schedule(self) -> "SchedulerOutput": def can_schedule(self, request) -> bool: max_prompt_batch_size = 1 - max_context_len = self.scheduler_config.max_model_len + max_context_len = self.model_config.max_model_len # running and waiting queues are both empty -> start a new batch # which can always be scheduled @@ -629,7 +630,7 @@ def _satisfies_last_chunk_constraints(self, request: Request) -> bool: decoding_requests = [ r for r in self.running if r not in self.ongoing_prefills ] - max_context_len = self.scheduler_config.max_model_len + max_context_len = self.model_config.max_model_len # check that there is space in the current decode batch num_running = len(decoding_requests) diff --git a/vllm_spyre/v1/metrics/stats_logger.py b/vllm_spyre/v1/metrics/stats_logger.py index 6504976e6..a70528dad 100644 --- a/vllm_spyre/v1/metrics/stats_logger.py +++ b/vllm_spyre/v1/metrics/stats_logger.py @@ -15,6 +15,14 @@ from vllm_spyre import envs as envs_spyre +try: + from vllm.v1.metrics.stats import MultiModalCacheStats +except ImportError: + # compatibility for vllm pre 0.11.1 + class MultiModalCacheStats: # type: ignore + pass + + logger = init_logger(__name__) @@ -88,6 +96,7 @@ def __del__(self): def record(self, scheduler_stats: Optional[SchedulerStats], iteration_stats: Optional[IterationStats], + mm_cache_stats: MultiModalCacheStats | None = None, engine_idx: int = 0): if not self.enabled or engine_idx != 0: # Only log from rank 0 diff --git a/vllm_spyre/v1/worker/spyre_model_runner.py b/vllm_spyre/v1/worker/spyre_model_runner.py index ab73c0797..1e6bdac87 100644 --- a/vllm_spyre/v1/worker/spyre_model_runner.py +++ b/vllm_spyre/v1/worker/spyre_model_runner.py @@ -6,6 +6,7 @@ from logging import DEBUG from typing import TYPE_CHECKING, Any, Generic, Optional, TypeVar, Union, cast +import numpy import torch from torch import nn from transformers import (AutoModel, AutoModelForSequenceClassification, @@ -15,7 +16,13 @@ from vllm.logger import init_logger from vllm.model_executor.layers.pooler import ClassifierPooler, Pooler from vllm.sampling_params import SamplingType -from vllm.utils import is_pin_memory_available + +try: + # pre 0.11.1 compatibility + from vllm.utils import is_pin_memory_available +except ImportError: + from vllm.utils.platform_utils import is_pin_memory_available + from vllm.v1.core.block_pool import BlockPool from vllm.v1.core.kv_cache_utils import KVCacheBlock from vllm.v1.core.sched.output import CachedRequestData @@ -286,6 +293,23 @@ def execute_model( ) -> ModelRunnerOutput: raise NotImplementedError + def _make_compatible_sampled_token_ids( + self, sampled_token_ids: torch.Tensor + ) -> list[list[int]] | list[numpy.ndarray]: + """Some versions of vllm required a list of numpy arrays as output. + This was ultimately rejected, see: + https://github.com/vllm-project/vllm/pull/29121 + + This can be removed once the *lower bound* of the vllm dependency is + >= 0.12.0 + """ + if ModelRunnerOutput.__dataclass_fields__[ + "sampled_token_ids"].type == list[numpy.ndarray]: + sampled_token_ids = [x for x in sampled_token_ids.numpy()] + else: + sampled_token_ids = sampled_token_ids.tolist() + return sampled_token_ids + class SpyreModelRunner(BaseSpyreModelRunner[SamplingInputBatch, SamplingRequestState, @@ -572,10 +596,13 @@ def execute_model( if not self.is_driver_worker: return EMPTY_MODEL_RUNNER_OUTPUT + sampled_token_ids = self._make_compatible_sampled_token_ids( + output.sampled_token_ids) + model_output = ModelRunnerOutput( req_ids=list(req_id_to_index.keys()), req_id_to_index=req_id_to_index, - sampled_token_ids=output.sampled_token_ids.tolist(), + sampled_token_ids=sampled_token_ids, logprobs=(output.logprobs_tensors.tolists() if output.logprobs_tensors else None), prompt_logprobs_dict=prompt_logprobs_dicts, @@ -898,7 +925,7 @@ def get_total_spyre_blocks(self) -> int: cache_config.num_gpu_blocks_override """ max_batch_size = self.scheduler_config.max_num_seqs - max_model_len = self.scheduler_config.max_model_len + max_model_len = self.model_config.max_model_len block_size = SpyrePlatform.get_block_size() min_req_num_blocks = max_model_len // block_size @@ -2347,10 +2374,13 @@ def execute_model( if not self.is_driver_worker: return self.get_empty_output() + sampled_token_ids = self._make_compatible_sampled_token_ids( + output.sampled_token_ids) + model_output = CPSpyreModelRunnerOutput( req_ids=list(req_id_to_index.keys()), req_id_to_index=req_id_to_index, - sampled_token_ids=output.sampled_token_ids.tolist(), + sampled_token_ids=sampled_token_ids, logprobs=(output.logprobs_tensors.tolists() if output.logprobs_tensors else None), prompt_logprobs_dict=prompt_logprobs_dicts, diff --git a/vllm_spyre/v1/worker/spyre_worker.py b/vllm_spyre/v1/worker/spyre_worker.py index 3d92376d7..0ea41f8d5 100644 --- a/vllm_spyre/v1/worker/spyre_worker.py +++ b/vllm_spyre/v1/worker/spyre_worker.py @@ -26,8 +26,7 @@ SchedulerOutput) from vllm.v1.kv_cache_interface import KVCacheConfig, KVCacheSpec from vllm.v1.outputs import ModelRunnerOutput -from vllm.v1.worker.worker_base import WorkerBase as WorkerBaseV1 -from vllm.worker.worker_base import WorkerBase +from vllm.v1.worker.worker_base import WorkerBase import vllm_spyre.envs as envs_spyre import vllm_spyre.perf_metrics as perf_metrics @@ -114,7 +113,7 @@ def use_torch_fx_backed_size_oblivious(): config.backed_size_oblivious = False -class SpyreWorker(WorkerBaseV1): +class SpyreWorker(WorkerBase): """A worker class that executes the model on a group of Spyre cores. """ @@ -205,8 +204,7 @@ def determine_available_memory(self) -> int: """ # The fake kv_cache config specified by the model runner sets 4 bytes # per token. - accurate_fake_kv_cache_size = (4 * - self.scheduler_config.max_model_len * + accurate_fake_kv_cache_size = (4 * self.model_config.max_model_len * self.scheduler_config.max_num_seqs) # The vLLM scheduler reserves a null block in its kv-cache, so we need @@ -231,11 +229,21 @@ def __init__( distributed_init_method: str, is_driver_worker: bool = False, ) -> None: - WorkerBase.__init__(self, vllm_config=vllm_config) - self.local_rank = local_rank - self.rank = rank - self.distributed_init_method = distributed_init_method - self.is_driver_worker = is_driver_worker + try: + # pre 0.11.1 compatibility with old worker base class + from vllm.worker.worker_base import WorkerBase as LegacyWorkerBase + LegacyWorkerBase.__init__(self, vllm_config=vllm_config) + self.local_rank = local_rank + self.rank = rank + self.distributed_init_method = distributed_init_method + self.is_driver_worker = is_driver_worker + except ImportError: + # From 0.11.1 and on we should only have to call the super init + super().__init__(vllm_config=vllm_config, + local_rank=local_rank, + rank=rank, + distributed_init_method=distributed_init_method, + is_driver_worker=is_driver_worker) # For power-user debugging of spyre logs for tensor parallel ops self.redirect_logs_to_files() @@ -526,8 +534,6 @@ def _warmup_spyre_dynamic_size(self, special_token_ids): scheduled_encoder_inputs={}, num_common_prefix_blocks=0, finished_req_ids=set(), - structured_output_request_ids={}, - grammar_bitmask=None, **_get_extra_args()) logger.info("[WARMUP] Deploying to device...") self.execute_model(scheduler_output) @@ -557,8 +563,6 @@ def _cleanup_model_runner(self, request) -> None: num_common_prefix_blocks=0, # The requests to be removed finished_req_ids=set([r.req_id for r in request]), - structured_output_request_ids={}, - grammar_bitmask=None, **_get_extra_args()) self.execute_model(scheduler_output) # satisfy mypy @@ -618,13 +622,11 @@ def _warmup_spyre_fixed_size(self, prompt_len, num_decode_tokens, new_block_ids.append([req.block_ids]) num_computed_tokens.append(req.num_computed_tokens) - cached_request_data = CachedRequestData( - req_ids=req_ids, - resumed_from_preemption=False, - new_token_ids=new_token_ids, - new_block_ids=new_block_ids, - num_computed_tokens=num_computed_tokens, - ) + cached_request_data = CachedRequestData.make_empty() + cached_request_data.req_ids = req_ids + cached_request_data.new_block_ids = new_block_ids + cached_request_data.new_token_ids = new_token_ids + cached_request_data.num_computed_tokens = num_computed_tokens # Set up scheduler_output for execute_model scheduler_output = SchedulerOutput( @@ -640,8 +642,6 @@ def _warmup_spyre_fixed_size(self, prompt_len, num_decode_tokens, scheduled_encoder_inputs={}, num_common_prefix_blocks=0, finished_req_ids=set(), - structured_output_request_ids={}, - grammar_bitmask=None, **_get_extra_args()) # First full forward pass @@ -705,8 +705,6 @@ def _dynamic_warmup( scheduled_encoder_inputs={}, num_common_prefix_blocks=0, finished_req_ids=set(), - structured_output_request_ids={}, - grammar_bitmask=None, **_get_extra_args()) logger.info("[WARMUP] Prefill [%s/%s]...", idx + 1, req_count) @@ -722,14 +720,15 @@ def _dynamic_warmup( functools.reduce(lambda blocks, req: blocks + req.block_ids, requests, []) - cached_request_data = CachedRequestData( - req_ids=[req.req_id for req in requests], - resumed_from_preemption=False, - new_token_ids=[[valid_token_ids_tensor[random_token_id()]] - for _ in requests], - new_block_ids=block_ids, - num_computed_tokens=[prompt_len for _ in requests], - ) + cached_request_data = CachedRequestData.make_empty() + cached_request_data.req_ids = [req.req_id for req in requests] + cached_request_data.new_block_ids = block_ids + cached_request_data.new_token_ids = [ + [valid_token_ids_tensor[random_token_id()]] for _ in requests + ] + cached_request_data.num_computed_tokens = [ + prompt_len for _ in requests + ] scheduler_output = SchedulerOutput( scheduled_new_reqs=[], @@ -741,8 +740,6 @@ def _dynamic_warmup( scheduled_encoder_inputs={}, num_common_prefix_blocks=0, finished_req_ids=set(), - structured_output_request_ids={}, - grammar_bitmask=None, **_get_extra_args()) logger.info("[WARMUP] Decode...") self.execute_model(scheduler_output) @@ -828,4 +825,10 @@ def _get_extra_args() -> dict: SchedulerOutputs here""" extra_args: dict = {} extra_args.update({"free_encoder_mm_hashes": []}) + + if "structured_output_request_ids" in dataclass_fields(SchedulerOutput): + extra_args["structured_output_request_ids"] = {} + if "grammar_bitmask" in dataclass_fields(SchedulerOutput): + extra_args["grammar_bitmask"] = None + return extra_args