mirror of
https://github.com/pytorch/pytorch.git
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4014672b30
This PR replaces "guard_serialization_mode" into `save_guards`. All cases where we care about whether or not we're *loading* guards can be inferred automatically from the existing inputs. The only case that's special here is whether or not to check guards. We don't want to check guards on guard load in CheckFnManager, because these guards have already been checked on save. Therefore, we put the setting in OutputGraphGuardsState, so that when we save, we bypass the guards check. Because of this change, it is *technically* possible to do a load and a save in the *same* CheckFunctionManager.__init__() by passing all the necessary parts, and also passing `save_guards=True`. This should just work out of the box, but so far no callsites need it, so not super important. Next up, we'll work on removing save_guards from GuardBuilder, and putting it into its own phase. Pull Request resolved: https://github.com/pytorch/pytorch/pull/160531 Approved by: https://github.com/zhxchen17
930 lines
34 KiB
Python
930 lines
34 KiB
Python
"""
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This module provides the infrastructure for creating and managing compile package
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for torch.compile. We mainly have two abstractions here:
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- CompilePackage: Overarching data structure for store and lookup a list of compiled codes.
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- CodeCacheEntry: Data structure for a single code being compiled by torch.compile.
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The caching behavior is always under user control explicitly so that a stronger guarantee can
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be provided about cache hit for a specific compiled model. Users can load the compile package
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from a different process or host.
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"""
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import abc
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import ast
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import contextlib
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import dataclasses
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import functools
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import hashlib
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import importlib
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import inspect
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import logging
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import os
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import pickle
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import platform
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import shutil
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import sys
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import types
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from collections.abc import Generator, Iterator
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from typing import Any, Callable, NewType, Optional
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from typing_extensions import Never
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import torch
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import torch._inductor.package
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from torch._dynamo.exc import PackageError
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from torch._dynamo.precompile_context import PrecompileCacheArtifact, PrecompileContext
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from torch._inductor.runtime.cache_dir_utils import cache_dir
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from torch.compiler._cache import CacheArtifactFactory
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from .bytecode_transformation import get_code_keys
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from .utils import dynamo_timed, increment_frame
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logger = logging.getLogger(__name__)
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@dataclasses.dataclass(frozen=True)
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class SerializedCode:
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co_argcount: int
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co_posonlyargcount: int
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co_kwonlyargcount: int
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co_nlocals: int
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co_stacksize: int
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co_flags: int
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co_code: bytes
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co_consts: tuple[Any, ...]
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co_names: tuple[str, ...]
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co_varnames: tuple[str, ...]
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co_filename: str
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co_name: str
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co_firstlineno: int
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co_cellvars: tuple[str, ...]
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co_freevars: tuple[str, ...]
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co_linetable: Optional[bytes] = None
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co_qualname: Optional[str] = None
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co_exceptiontable: Optional[bytes] = None
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co_lnotab: Optional[str] = None
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@classmethod
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@functools.cache
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def from_code_object(cls, code: types.CodeType) -> "SerializedCode":
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kwargs = {key: getattr(code, key) for key in get_code_keys()}
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kwargs["co_consts"] = tuple(
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cls.from_code_object(c) if isinstance(c, types.CodeType) else c
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for c in kwargs["co_consts"]
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)
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return cls(**kwargs)
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@classmethod
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@functools.cache
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def to_code_object(cls, serialized_code: "SerializedCode") -> types.CodeType:
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kwargs = {key: getattr(serialized_code, key) for key in get_code_keys()}
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kwargs["co_consts"] = tuple(
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cls.to_code_object(c) if isinstance(c, SerializedCode) else c
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for c in kwargs["co_consts"]
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)
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return types.CodeType(
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*kwargs.values(),
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)
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@dataclasses.dataclass
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class _GuardedCodeCacheEntry:
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"""
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Contains the serializable information associated with a single compilation in dynamo.
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To restore an execution of compiled code, we will need to serialize the following data:
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- Dynamo bytecode for mapping Python inputs/outputs.
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- Dynamo guards.
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"""
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guards_state: bytes
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dynamo_code: SerializedCode
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_BackendId = NewType("_BackendId", str) # __compiled_fn
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_FunctionId = NewType("_FunctionId", str) # __resume_at
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@dataclasses.dataclass(frozen=True)
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class InlinedSource:
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module: str
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firstlineno: int
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lastlineno: int
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checksum: str
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@dataclasses.dataclass
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class DynamoCaptureOutput:
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"""
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Core information generated from Dynamo for fullgraph=True.
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"""
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guarded_codes: list[_GuardedCodeCacheEntry]
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backend_ids: list[_BackendId]
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@dataclasses.dataclass
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class _DynamoCodeCacheEntry(DynamoCaptureOutput):
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"""
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Contains the serializable information associated with a single code object
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in dynamo. To restore an execution of compiled code, we will need the following
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ingredients:
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1. The "original" code object, which serves as the entry point for eager
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execution, i.e. the code only executed when there's no cache entry hit.
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2. The python module name this code object belongs to, for identifying the
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enclosing global scope to inject compiled and resume functions.
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3. A list of function names that pointing to this code object. There could be
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multiple function objects pointing to the same code such as recursive functions.
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4. A list of guarded code that eval frame dispatches to.
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5. A list of imported module objects unioned from all compiled branches.
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6. A list of "backends" (compiled fx graph) unioned from all compield branches.
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7. A string path used to access the original code object users defined.
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A code object can be accessed by "{python_module}.{function_name}.{code_source}" .
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8. A boolean flag indicating whether the function is installed to global scope.
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9. A boolean flag indicating whether the function has a compile id.
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"""
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python_code: SerializedCode
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python_module: str
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function_names: list[_FunctionId]
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import_sources: dict[str, str]
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code_source: Optional[str]
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install_to_global: bool
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has_compile_id: bool = False
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def _lookup_code(entry: _DynamoCodeCacheEntry) -> types.CodeType:
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assert len(entry.function_names) == 1
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fn: Any = sys.modules[entry.python_module]
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parts = entry.function_names[0].split(".")
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for part in parts:
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fn = getattr(fn, part)
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if entry.code_source:
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parts = entry.code_source.split(".")
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for part in parts:
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if part.endswith("]"):
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index_begin = part.rfind("[")
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assert isinstance(index_begin, int) and index_begin >= 0
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attr = getattr(fn, part[:index_begin], None)
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if attr is None:
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raise PackageError(f"Cannot find source for code entry {entry}")
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fn = attr[ast.literal_eval(part[index_begin + 1 : -1])]
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else:
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fn = getattr(fn, part)
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else:
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raise PackageError(f"Cannot find source for code entry {entry}")
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assert isinstance(fn, types.CodeType)
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return fn
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def _raise_resolution_error(code: types.CodeType, scope: Any) -> Never:
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raise PackageError(
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f"Cannot resolve a fully qualified name for {code}. Lookup scope: {scope}"
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)
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def _get_code_source(code: types.CodeType) -> tuple[str, str]:
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"""
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Given a code object, return a fully qualified name which will be used as
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a serialized handle to access the code object from the new process.
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This is normally a straightforward process, but there are some corner cases:
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1. When a function is defined with decorator, then this function will be captured
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inside a closure with the wrapper object.
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2. When a function is defined as a nested function, then the code object will be
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stored on the co_consts field of the parent code object by Python compiler.
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This function handles all of the corner cases above.
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"""
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module = inspect.getmodule(code)
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if module is None:
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raise PackageError(f"Cannot find module for code {code}")
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toplevel: Any = module
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if sys.version_info >= (3, 11):
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parts = code.co_qualname.split(".")
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for part in parts:
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if not hasattr(toplevel, part):
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_raise_resolution_error(code, toplevel)
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toplevel = getattr(toplevel, part)
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if inspect.isfunction(toplevel):
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break
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seen = set()
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def _find_code_source(obj: Any) -> Optional[str]:
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nonlocal toplevel
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nonlocal seen
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if obj in seen:
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return None
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seen.add(obj)
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if inspect.iscode(obj):
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if obj is code:
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return ""
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for i, const in enumerate(obj.co_consts):
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if (res := _find_code_source(const)) is not None:
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return f".co_consts[{i}]{res}"
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if inspect.isfunction(obj):
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if (res := _find_code_source(obj.__code__)) is not None:
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toplevel = obj
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return f".__code__{res}"
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if obj.__closure__ is not None:
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for i, cell in enumerate(obj.__closure__):
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try:
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cell_contents = cell.cell_contents
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except ValueError:
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continue
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if not (
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inspect.isfunction(cell_contents)
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or inspect.iscode(cell_contents)
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):
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continue
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if (res := _find_code_source(cell_contents)) is not None:
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toplevel = obj
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return f".__closure__[{i}].cell_contents{res}"
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if sys.version_info < (3, 11):
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if inspect.ismodule(obj):
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for value in obj.__dict__.values():
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if not (inspect.isfunction(value) or inspect.isclass(value)):
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continue
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if (res := _find_code_source(value)) is not None:
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return res
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if inspect.isclass(obj):
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for name, value in obj.__dict__.items():
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value = getattr(obj, name)
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if not (inspect.isfunction(value) or inspect.isclass(value)):
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continue
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if (res := _find_code_source(value)) is not None:
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if value.__name__ != name:
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_raise_resolution_error(code, toplevel)
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return res
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return None
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code_source = _find_code_source(toplevel)
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if code_source is None:
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_raise_resolution_error(code, toplevel)
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return toplevel.__qualname__, code_source.strip(".")
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@dataclasses.dataclass
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class _DynamoCacheEntry:
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codes: list[_DynamoCodeCacheEntry]
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inlined_sources: set[InlinedSource]
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python_version: str = platform.python_version()
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torch_version: str = torch.__version__
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@property
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def backend_ids(self) -> set[_BackendId]:
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return {backend_id for code in self.codes for backend_id in code.backend_ids}
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@CacheArtifactFactory.register
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class _DynamoCacheArtifact(PrecompileCacheArtifact[_DynamoCacheEntry]):
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@staticmethod
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def type() -> str:
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return "precompile_dynamo"
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def after_deserialization(self) -> _DynamoCacheEntry:
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return pickle.loads(self.content)
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def _hash_source(source: str) -> str:
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sha256_hash = hashlib.sha256()
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sha256_hash.update(source.encode())
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return sha256_hash.hexdigest()
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def _get_sourcelines(
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m: types.ModuleType, firstlineno: int, lastlineno: int
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) -> list[str]:
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return inspect.getsourcelines(m)[0][firstlineno - 1 : lastlineno - 1]
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def _hash_sourcelines(m: types.ModuleType, firstlineno: int, lastlineno: int) -> str:
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return _hash_source("".join(_get_sourcelines(m, firstlineno, lastlineno)))
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def _compile_frame_context(
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code: types.CodeType,
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) -> contextlib.AbstractContextManager[None]:
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from torch._dynamo.convert_frame import get_compile_id, log_dynamo_start
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from torch._guards import compile_context, CompileContext
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# Each code represents a new compile frame
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# recompiles on the same frame are all saved
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# under the same cache entry, so we don't have recompile ids
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# i.e. If cold start had 0/0, 0/1, 1/0, 1/1, these would be
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# collapsed into 0/0, 1/0 on warm.
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@contextlib.contextmanager
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def _ctx() -> Iterator[None]:
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increment_frame()
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compile_id = get_compile_id(frame_state={})
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log_dynamo_start(code)
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with (
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compile_context(CompileContext(compile_id)),
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dynamo_timed(
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"_compile.compile_inner",
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phase_name="entire_frame_compile",
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dynamo_compile_column_us="dynamo_cumulative_compile_time_us",
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# TODO: save all relevant compilation metrics
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metadata={
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"frame_key": str(torch._dynamo.utils.curr_frame),
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"co_name": code.co_name,
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"co_filename": code.co_filename,
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"co_firstlineno": code.co_firstlineno,
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},
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),
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):
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yield
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return _ctx()
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class CompilePackage:
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"""
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CompilePackage is considered a low level component and should not be directly exposed to
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end users. It has the following interface:
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1. `CompilePackage.__init__()` which optionally takes previously serialized dynamo states.
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a. when `dynamo` argument is None, it will construct a brand new CompilePackage object.
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b. when `dynamo` argument is not None, it will load a pre-compiled dynamo state.
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2. `package.save()` which dumps the dynamo and backend states to a DynamoCacheEntry object.
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3. `package.install(backends) which will handle all the side-effectful global scope
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updates with compiled functions and resume functions.
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"""
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def __init__(
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self,
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fn: Optional[Callable[..., Any]],
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dynamo: Optional[_DynamoCacheEntry] = None,
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ignore_inlined_sources: bool = False,
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) -> None:
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self._innermost_fn = None
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self._codes: dict[types.CodeType, _DynamoCodeCacheEntry] = {}
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self._current_entry: Optional[_DynamoCodeCacheEntry] = None
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self._installed_globals: dict[types.ModuleType, list[str]] = {}
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# For debugging/testing purpose only.
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self._cached_backends: dict[_BackendId, Any] = {}
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self._inlined_sources: set[InlinedSource] = set()
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self._resume_codes: set[types.CodeType] = set()
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self._initialized = False
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if fn is not None:
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self.initialize(fn, dynamo, ignore_inlined_sources)
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self.uninstall()
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self.validate()
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def is_initialized(self) -> bool:
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return self._initialized
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def initialize(
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self,
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fn: Any,
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dynamo: Optional[_DynamoCacheEntry] = None,
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ignore_inlined_sources: bool = False,
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) -> None:
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from .eval_frame import innermost_fn
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assert not self._initialized
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self._inlined_sources = set()
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self._innermost_fn = innermost_fn(fn) # type: ignore[assignment]
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assert self._innermost_fn is not None
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if dynamo is not None:
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assert isinstance(dynamo, _DynamoCacheEntry)
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if dynamo.python_version != platform.python_version():
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raise RuntimeError(
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f"Compile package was created with a different Python version: {dynamo.python_version}"
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)
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if dynamo.torch_version != torch.__version__:
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raise RuntimeError(
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f"Compile package was created with a different PyTorch version: {dynamo.torch_version}"
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)
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if not ignore_inlined_sources:
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for code in dynamo.inlined_sources:
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m = importlib.import_module(code.module)
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checksum = _hash_sourcelines(m, code.firstlineno, code.lastlineno)
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if checksum != code.checksum:
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raise RuntimeError(
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f"Source code changes detected for {code.module} (line {code.firstlineno} - line {code.lastlineno})"
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)
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self._inlined_sources = dynamo.inlined_sources
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main, *codes = dynamo.codes
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self._codes = {self._innermost_fn.__code__: main}
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for code in codes:
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self._codes[SerializedCode.to_code_object(code.python_code)] = code
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else:
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self._add_function(
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self._innermost_fn.__code__, self._innermost_fn.__module__
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)
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self._initialized = True
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def _add_function(
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self,
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python_code: types.CodeType,
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python_module: str,
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function_name: Optional[_FunctionId] = None,
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code_source: Optional[str] = None,
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install_to_global: bool = False,
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) -> None:
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if python_code not in self._codes:
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code = _DynamoCodeCacheEntry(
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python_code=SerializedCode.from_code_object(python_code),
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python_module=python_module,
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function_names=[],
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guarded_codes=[],
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import_sources={},
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backend_ids=[],
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code_source=code_source,
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install_to_global=install_to_global,
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)
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self._codes[python_code] = code
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else:
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code = self._codes[python_code]
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assert code.python_module == python_module
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assert code.install_to_global == install_to_global
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assert code.code_source == code_source
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if function_name is not None:
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code.function_names.append(function_name)
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@property
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def cached_backends(self) -> dict[_BackendId, Any]:
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return self._cached_backends
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@functools.cached_property
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|
def source_id(self) -> str:
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assert self._innermost_fn is not None
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return CompilePackage.source_id_from_fn(self._innermost_fn)
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def _add_user_function(self, code: types.CodeType) -> None:
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function_name, code_source = _get_code_source(code)
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module = inspect.getmodule(code)
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if module is None:
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raise PackageError(f"Cannot find module for code {code}")
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self._add_function(
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code,
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module.__name__,
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function_name=_FunctionId(function_name),
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code_source=code_source,
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)
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@contextlib.contextmanager
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|
def code_context(self, code: types.CodeType) -> Generator[None, None, None]:
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assert self._current_entry is None
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# Sometimes user code cannot be inlined in dynamo resulting in extra user code
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# being compiled. We should record these as when they are actually invoked.
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if code not in self._codes:
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self._add_user_function(code)
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entry = self._codes[code]
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self._current_entry = entry
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try:
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yield
|
|
finally:
|
|
entry.has_compile_id = True
|
|
self._current_entry = None
|
|
|
|
def add_guarded_code(
|
|
self,
|
|
guards_state: bytes,
|
|
dynamo_code: types.CodeType,
|
|
) -> None:
|
|
assert self._current_entry is not None
|
|
guarded_code_entry = _GuardedCodeCacheEntry(
|
|
guards_state=guards_state,
|
|
dynamo_code=SerializedCode.from_code_object(dynamo_code),
|
|
)
|
|
self._current_entry.guarded_codes.append(guarded_code_entry)
|
|
|
|
def add_inlined_source(self, sources: list[types.CodeType]) -> None:
|
|
for code in sources:
|
|
if code in self._resume_codes:
|
|
continue
|
|
module = inspect.getmodule(code)
|
|
if module is None:
|
|
continue
|
|
source = inspect.getsource(code)
|
|
lastlineno = code.co_firstlineno + len(inspect.getsourcelines(code)[0])
|
|
assert source == "".join(
|
|
_get_sourcelines(module, code.co_firstlineno, lastlineno)
|
|
)
|
|
self._inlined_sources.add(
|
|
InlinedSource(
|
|
module=module.__name__,
|
|
firstlineno=code.co_firstlineno,
|
|
lastlineno=lastlineno,
|
|
checksum=_hash_source(source),
|
|
)
|
|
)
|
|
|
|
def add_resume_function(
|
|
self,
|
|
python_code: types.CodeType,
|
|
python_module: str,
|
|
function_name: Optional[str],
|
|
) -> None:
|
|
self._add_function(
|
|
python_code,
|
|
python_module,
|
|
function_name=_FunctionId(function_name) if function_name else None,
|
|
install_to_global=True,
|
|
)
|
|
self._resume_codes.add(python_code)
|
|
|
|
def add_import_source(self, alias: str, module_name: str) -> None:
|
|
assert self._current_entry is not None
|
|
self._current_entry.import_sources[alias] = module_name
|
|
|
|
def add_backend_id(self, backend_id: str, backend: Optional[Any] = None) -> None:
|
|
assert self._current_entry is not None
|
|
assert backend_id.startswith("__compiled_fn_") # sanity check
|
|
backend_id = _BackendId(backend_id)
|
|
self._current_entry.backend_ids.append(backend_id)
|
|
if backend is not None:
|
|
self._cached_backends[backend_id] = backend
|
|
|
|
def validate(self) -> None:
|
|
assert self._current_entry is None
|
|
assert self._innermost_fn is not None
|
|
assert self._initialized
|
|
assert next(iter(self._codes)) is self._innermost_fn.__code__
|
|
|
|
def _install_global(self, module: types.ModuleType, name: str, value: Any) -> None:
|
|
module.__dict__[name] = value
|
|
self._installed_globals.setdefault(module, []).append(name)
|
|
|
|
def uninstall(self) -> None:
|
|
from torch._C._dynamo.eval_frame import _reset_precompile_entries
|
|
|
|
assert self._innermost_fn is not None
|
|
for module, names in self._installed_globals.items():
|
|
for name in names:
|
|
module.__dict__.pop(name)
|
|
|
|
self._installed_globals = {}
|
|
|
|
_reset_precompile_entries(self._innermost_fn.__code__)
|
|
|
|
def install(self, backends: dict[_BackendId, Any]) -> None:
|
|
"""
|
|
Sync the package states to the compiled function. This includes the following actions:
|
|
1. Clean up the previously installed states.
|
|
2. Install the compiled functions to global scopes.
|
|
3. Install the precompiled cache entries to ExtraStates on the code object.
|
|
"""
|
|
from torch._C._dynamo.eval_frame import _load_precompile_entry
|
|
|
|
from .output_graph import get_builtins_dict
|
|
|
|
self.uninstall()
|
|
for code, entry in self._codes.items():
|
|
context = (
|
|
_compile_frame_context(code)
|
|
if entry.has_compile_id
|
|
else contextlib.nullcontext()
|
|
)
|
|
with context:
|
|
module = sys.modules[entry.python_module]
|
|
for alias, module_name in entry.import_sources.items():
|
|
self._install_global(
|
|
module, alias, importlib.import_module(module_name)
|
|
)
|
|
target_code = code
|
|
if entry.install_to_global:
|
|
for function_name in entry.function_names:
|
|
fn = types.FunctionType(code, module.__dict__, function_name)
|
|
self._install_global(module, function_name, fn)
|
|
if entry.code_source:
|
|
target_code = _lookup_code(entry)
|
|
|
|
for backend_id in entry.backend_ids:
|
|
if backend_id not in backends:
|
|
raise RuntimeError(
|
|
f"Backend {backend_id} is not found in the given backends"
|
|
)
|
|
with dynamo_timed(
|
|
"after_deserialization", phase_name="backend_compile"
|
|
):
|
|
backend = backends[backend_id].after_deserialization()
|
|
self._install_global(
|
|
module,
|
|
backend_id,
|
|
torch._dynamo.disable(backend),
|
|
)
|
|
|
|
if len(entry.guarded_codes) == 0:
|
|
# Dynamo generates empty graph for trivial functions, should just skip them
|
|
# in these cases.
|
|
torch._dynamo.eval_frame.skip_code(target_code)
|
|
|
|
for guarded_code in entry.guarded_codes:
|
|
guards_state = pickle.loads(guarded_code.guards_state)
|
|
runtime_global_scope = sys.modules[entry.python_module].__dict__
|
|
# The installed builtins dict might be absent from the runtime
|
|
# while loading guards. Populate it if it's missing.
|
|
if (
|
|
builtin_dict_name
|
|
:= guards_state.output_graph.name_of_builtins_dict_key_in_fglobals
|
|
):
|
|
builtins_dict = get_builtins_dict(runtime_global_scope)
|
|
if builtin_dict_name in runtime_global_scope:
|
|
assert (
|
|
runtime_global_scope[builtin_dict_name] is builtins_dict
|
|
)
|
|
else:
|
|
runtime_global_scope[builtin_dict_name] = builtins_dict
|
|
assert isinstance(guards_state, torch._dynamo.guards.GuardsState)
|
|
check_fn_manager = torch._dynamo.guards.CheckFunctionManager(
|
|
target_code,
|
|
guards_state.output_graph,
|
|
shape_code_parts=guards_state.shape_code_parts,
|
|
runtime_global_scope=runtime_global_scope,
|
|
)
|
|
_load_precompile_entry(
|
|
target_code,
|
|
check_fn_manager.guard_manager,
|
|
SerializedCode.to_code_object(guarded_code.dynamo_code),
|
|
)
|
|
|
|
def cache_entry(self) -> _DynamoCacheEntry:
|
|
self.validate()
|
|
return _DynamoCacheEntry(
|
|
codes=list(self._codes.values()), inlined_sources=self._inlined_sources
|
|
)
|
|
|
|
@staticmethod
|
|
def source_id_from_fn(fn: Callable[..., Any]) -> str:
|
|
from .eval_frame import innermost_fn
|
|
|
|
innermost_fn_ = innermost_fn(fn)
|
|
|
|
sha256_hash = hashlib.sha256()
|
|
sha256_hash.update(innermost_fn_.__qualname__.encode())
|
|
sha256_hash.update(str(innermost_fn_.__code__.co_firstlineno).encode())
|
|
return sha256_hash.hexdigest()
|
|
|
|
|
|
@CacheArtifactFactory.register
|
|
class EagerCacheArtifact(PrecompileCacheArtifact[Any]):
|
|
@staticmethod
|
|
def type() -> str:
|
|
return "precompile_eager"
|
|
|
|
def after_deserialization(self) -> Any:
|
|
return pickle.loads(self.content)
|
|
|
|
|
|
_Backends = dict[_BackendId, PrecompileCacheArtifact[Any]]
|
|
|
|
|
|
class DynamoStore(abc.ABC):
|
|
"""
|
|
A DynamoStore tracks active CompilePackages, and provides methods to store and retrieve them.
|
|
|
|
This is an abstract base class for different storage implementations.
|
|
"""
|
|
|
|
def record_package(self, package: CompilePackage) -> None:
|
|
"""
|
|
Records a package to PrecompileContext, so that it can be serialized later.
|
|
"""
|
|
cache_entry = package.cache_entry()
|
|
pickled_result = pickle.dumps(cache_entry)
|
|
PrecompileContext.record_artifact(
|
|
_DynamoCacheArtifact.type(), key=package.source_id, content=pickled_result
|
|
)
|
|
|
|
def record_eager_backend(self, backend_id: _BackendId, backend: Any) -> None:
|
|
"""
|
|
Records eager fx graphs to PrecompileContext for testing purposes.
|
|
"""
|
|
pickled_result = pickle.dumps(backend)
|
|
PrecompileContext.record_artifact(
|
|
EagerCacheArtifact.type(), key=backend_id, content=pickled_result
|
|
)
|
|
|
|
@abc.abstractmethod
|
|
def clear(self) -> None: ...
|
|
|
|
@abc.abstractmethod
|
|
def write(
|
|
self,
|
|
dynamo: _DynamoCacheEntry,
|
|
backends: _Backends,
|
|
path: str,
|
|
) -> None:
|
|
"""
|
|
Abstract method to write dynamo cache entry and backends to storage.
|
|
|
|
Args:
|
|
dynamo: The dynamo cache entry to write
|
|
backends: Dictionary of backend content to write
|
|
path: Path or key to identify where to write the data
|
|
"""
|
|
...
|
|
|
|
def save_cache_entry(self, cache_entry: _DynamoCacheEntry, key: str) -> None:
|
|
"""
|
|
Saves a package to a given path. Grabs backends from PrecompileContext.
|
|
"""
|
|
backend_content: _Backends = {}
|
|
for backend_id in cache_entry.backend_ids:
|
|
serialized_backend = PrecompileContext.serialize_artifact_by_key(backend_id)
|
|
if serialized_backend is None:
|
|
raise RuntimeError(
|
|
f"Backend {backend_id} is not found in the given backends"
|
|
)
|
|
assert isinstance(serialized_backend, PrecompileCacheArtifact)
|
|
backend_content[backend_id] = serialized_backend
|
|
|
|
self.write(cache_entry, backend_content, key)
|
|
|
|
def save_package(self, package: CompilePackage, key: str) -> None:
|
|
"""
|
|
Saves a package to a given path. Grabs backends from PrecompileContext.
|
|
"""
|
|
self.record_package(package)
|
|
cache_entry = package.cache_entry()
|
|
self.save_cache_entry(cache_entry, key)
|
|
|
|
@abc.abstractmethod
|
|
def read(self, path: str) -> tuple[_DynamoCacheEntry, _Backends]:
|
|
"""
|
|
Abstract method to read dynamo cache entry and backends from storage.
|
|
|
|
Args:
|
|
path: Path or key to identify where to read the data from
|
|
|
|
Returns:
|
|
A tuple containing (dynamo_cache_entry, backend_content)
|
|
"""
|
|
...
|
|
|
|
def load_cache_entry(
|
|
self, key: str
|
|
) -> tuple[_DynamoCacheEntry, dict[_BackendId, Any]]:
|
|
cache_entry, backend_content = self.read(key)
|
|
for backend_id, backend in backend_content.items():
|
|
PrecompileContext.record_artifact(
|
|
backend.type(), key=backend.key, content=backend.content
|
|
)
|
|
backend_content[backend_id] = backend
|
|
|
|
return cache_entry, backend_content
|
|
|
|
def load_package(
|
|
self, fn: Any, key: str
|
|
) -> tuple[CompilePackage, dict[_BackendId, Any]]:
|
|
"""
|
|
Loads a package from a given path and returns it plus a list of deserialized backends
|
|
"""
|
|
cache_entry, backend_content = self.load_cache_entry(key)
|
|
package = CompilePackage(fn, cache_entry)
|
|
return package, backend_content
|
|
|
|
|
|
class InMemoryDynamoStore(DynamoStore):
|
|
"""
|
|
A DynamoStore implementation that keeps state about CompilePackages in memory.
|
|
"""
|
|
|
|
def __init__(self) -> None:
|
|
self.packages: dict[str, tuple[_DynamoCacheEntry, _Backends]] = {}
|
|
|
|
def clear(self) -> None:
|
|
self.packages.clear()
|
|
|
|
def write(
|
|
self,
|
|
dynamo: _DynamoCacheEntry,
|
|
backends: _Backends,
|
|
path: str,
|
|
) -> None:
|
|
"""
|
|
Store the dynamo cache entry and backends in memory instead of writing to disk.
|
|
"""
|
|
self.packages[path] = (dynamo, backends)
|
|
|
|
def read(self, path: str) -> tuple[_DynamoCacheEntry, _Backends]:
|
|
"""
|
|
Read dynamo cache entry and backends from memory.
|
|
"""
|
|
if path not in self.packages:
|
|
raise RuntimeError(f"No package found with key {path}")
|
|
|
|
return self.packages[path]
|
|
|
|
|
|
class DiskDynamoStore(DynamoStore):
|
|
"""
|
|
A DynamoStore implementation that keeps state about CompilePackages on disk.
|
|
"""
|
|
|
|
def __init__(self, path_prefix: str = ""):
|
|
"""
|
|
Initialize a DiskDynamoStore with a path prefix.
|
|
|
|
Args:
|
|
path_prefix: Prefix directory for where to put CompilePackages on disk
|
|
"""
|
|
self.path_prefix = path_prefix
|
|
|
|
def clear(self) -> None:
|
|
"""
|
|
Clear all CompilePackages from disk.
|
|
"""
|
|
if self.path_prefix:
|
|
shutil.rmtree(self.path_prefix, ignore_errors=True)
|
|
|
|
def write(
|
|
self,
|
|
dynamo: _DynamoCacheEntry,
|
|
backends: _Backends,
|
|
path: str,
|
|
) -> None:
|
|
"""
|
|
Write dynamo cache entry and backends to disk.
|
|
"""
|
|
path = os.path.join(self.path_prefix, path) if self.path_prefix else path
|
|
try:
|
|
os.makedirs(path, exist_ok=True)
|
|
with open(os.path.join(path, "dynamo"), "wb") as dynamo_path:
|
|
pickle.dump(dynamo, dynamo_path)
|
|
with open(os.path.join(path, "backends"), "wb") as backend_path:
|
|
pickle.dump(backends, backend_path)
|
|
except Exception as e:
|
|
raise RuntimeError(f"Failed to save package to {path}: {e}") from e
|
|
|
|
def read(self, path: str) -> tuple[_DynamoCacheEntry, _Backends]:
|
|
"""
|
|
Read dynamo cache entry and backends from disk.
|
|
"""
|
|
path = os.path.join(self.path_prefix, path) if self.path_prefix else path
|
|
try:
|
|
with open(os.path.join(path, "dynamo"), "rb") as dynamo_path:
|
|
cache_entry = pickle.load(dynamo_path)
|
|
with open(os.path.join(path, "backends"), "rb") as backend_path:
|
|
backend_content = pickle.load(backend_path)
|
|
return cache_entry, backend_content
|
|
except Exception as e:
|
|
raise RuntimeError(f"Failed to load package from path {path}: {e}") from e
|
|
|
|
|
|
class DiskDynamoCache(DiskDynamoStore):
|
|
"""
|
|
Special DiskDynamoStore which adds some helper functions for automatically
|
|
tracking paths of packages
|
|
"""
|
|
|
|
def save(self, package: CompilePackage) -> None:
|
|
"""
|
|
Saves a package to a given path. Grabs backends from PrecompileContext.
|
|
"""
|
|
key = package.source_id
|
|
logger.info("Saving CompilePackage for %s", package.source_id)
|
|
super().save_package(package, key)
|
|
|
|
def load(
|
|
self, fn: Callable[..., Any]
|
|
) -> Optional[tuple[_DynamoCacheEntry, dict[_BackendId, Any]]]:
|
|
"""
|
|
Loads a package from a given path and returns it plus a list of deserialized backends
|
|
"""
|
|
key = CompilePackage.source_id_from_fn(fn)
|
|
logger.info("Loading CompilePackage for %s", key)
|
|
path = os.path.join(self.path_prefix, key)
|
|
if os.path.exists(path):
|
|
try:
|
|
result = super().load_cache_entry(key)
|
|
return result
|
|
except Exception as e:
|
|
logger.warning("Failed to load package from path %s: %s", path, str(e))
|
|
return None
|
|
logger.info("No package found for %s", key)
|
|
return None
|
|
|
|
def load_and_install_package(
|
|
self, fn: Callable[..., Any]
|
|
) -> Optional[CompilePackage]:
|
|
"""
|
|
Load directly into a package and install backends
|
|
"""
|
|
results = self.load(fn)
|
|
if results is None:
|
|
return None
|
|
else:
|
|
(entry, backends) = results
|
|
package = CompilePackage(fn, entry)
|
|
package.install(backends)
|
|
return package
|
|
|
|
|
|
DynamoCache = DiskDynamoCache(os.path.join(cache_dir(), "dynamo"))
|