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122 lines
4.3 KiB
Python
122 lines
4.3 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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import dataclasses
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from collections.abc import Callable
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from typing import Any
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import torch.fx as fx
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import vllm.envs as envs
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from vllm.compilation.backends import VllmBackend
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from vllm.compilation.monitor import end_monitoring_torch_compile
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from vllm.config import VllmConfig
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from vllm.logger import init_logger
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logger = init_logger(__name__)
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@dataclasses.dataclass
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class ConcreteSizeEntry:
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runtime_shape: int
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compiled: bool = False
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runnable: Callable = None # type: ignore
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class PiecewiseBackend:
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def __init__(
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self,
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graph: fx.GraphModule,
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vllm_config: VllmConfig,
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piecewise_compile_index: int,
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total_piecewise_compiles: int,
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sym_shape_indices: list[int],
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compiled_graph_for_general_shape: Callable,
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vllm_backend: VllmBackend,
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):
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"""
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The backend for piecewise compilation.
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It mainly handles the compilation of static shapes and
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dispatching based on runtime shape.
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We will compile `self.graph` once for the general shape,
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and then compile for different shapes specified in
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`compilation_config.compile_sizes`.
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"""
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self.graph = graph
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self.vllm_config = vllm_config
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self.compilation_config = vllm_config.compilation_config
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self.piecewise_compile_index = piecewise_compile_index
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self.total_piecewise_compiles = total_piecewise_compiles
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self.vllm_backend = vllm_backend
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self.is_first_graph = piecewise_compile_index == 0
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self.is_last_graph = piecewise_compile_index == total_piecewise_compiles - 1
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self.is_full_graph = total_piecewise_compiles == 1
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self.compile_sizes: set[int] = set(self.compilation_config.compile_sizes)
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self.first_run_finished = False
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self.compiled_graph_for_general_shape = compiled_graph_for_general_shape # noqa
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self.sym_shape_indices = sym_shape_indices
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self.is_debugging_mode = envs.VLLM_LOGGING_LEVEL == "DEBUG"
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# the entries for different shapes that we need to compile
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self.concrete_size_entries: dict[int, ConcreteSizeEntry] = {}
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# to_be_compiled_sizes tracks the remaining sizes to compile,
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# and updates during the compilation process, so we need to copy it
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self.to_be_compiled_sizes: set[int] = self.compile_sizes.copy()
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# We only keep compilation management inside this class directly.
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for shape in self.compile_sizes:
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self.concrete_size_entries[shape] = ConcreteSizeEntry(
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runtime_shape=shape,
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runnable=self.compiled_graph_for_general_shape,
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)
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def check_for_ending_compilation(self):
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if self.is_last_graph and not self.to_be_compiled_sizes:
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# no specific sizes to compile
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# save the hash of the inductor graph for the next run
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self.vllm_backend.compiler_manager.save_to_file()
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end_monitoring_torch_compile(self.vllm_config)
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def __call__(self, *args) -> Any:
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if not self.first_run_finished:
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self.first_run_finished = True
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self.check_for_ending_compilation()
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return self.compiled_graph_for_general_shape(*args)
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runtime_shape = args[self.sym_shape_indices[0]]
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if runtime_shape not in self.concrete_size_entries:
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# we don't need to do anything for this shape
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return self.compiled_graph_for_general_shape(*args)
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entry = self.concrete_size_entries[runtime_shape]
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if not entry.compiled:
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entry.compiled = True
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self.to_be_compiled_sizes.remove(runtime_shape)
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# args are real arguments
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entry.runnable = self.vllm_backend.compiler_manager.compile(
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self.graph,
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args,
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self.vllm_backend.inductor_config,
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self.compilation_config,
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graph_index=self.piecewise_compile_index,
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num_graphs=self.total_piecewise_compiles,
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runtime_shape=runtime_shape,
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)
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# finished compilations for all required shapes
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if self.is_last_graph and not self.to_be_compiled_sizes:
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self.check_for_ending_compilation()
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return entry.runnable(*args)
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