Intelegentny_Pszczelarz/.venv/Lib/site-packages/tensorflow/core/function/polymorphism/function_cache.py
2023-06-19 00:49:18 +02:00

108 lines
4.0 KiB
Python

# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Cache to manage concrete functions and their signatures."""
import collections
from typing import Any, NamedTuple, Optional
from tensorflow.core.function import trace_type
from tensorflow.core.function.polymorphism import function_type as function_type_lib
from tensorflow.core.function.polymorphism import type_dispatch
# TODO(b/182990542): Enable and remove flag when stable.
DELETE_WITH_WEAKREF = False
class FunctionContext(NamedTuple):
"""Contains information regarding tf.function execution context."""
context: Any
class FunctionCache:
"""A container for managing concrete functions."""
__slots__ = ["_primary", "_dispatch_dict", "_garbage_collectors"]
def __init__(self):
# Maps (FunctionContext, FunctionType) to a concrete function.
self._primary = collections.OrderedDict()
# Maps FunctionContext to a TypeDispatchTable containing FunctionTypes of
# that particular context.
self._dispatch_dict = {}
def lookup(self, context: FunctionContext,
function_type: function_type_lib.FunctionType) -> Optional[Any]:
"""Looks up a concrete function based on the context and type."""
if context in self._dispatch_dict:
dispatch_type = self._dispatch_dict[context].dispatch(function_type)
if dispatch_type:
return self._primary[(context, dispatch_type)]
return None
def delete(self, context: FunctionContext,
function_type: function_type_lib.FunctionType) -> bool:
"""Deletes a concrete function given the context and type."""
if (context, function_type) not in self._primary:
return False
del self._primary[(context, function_type)]
self._dispatch_dict[context].delete(function_type)
return True
def add(self, context: FunctionContext,
function_type: function_type_lib.FunctionType,
deletion_observer: trace_type.WeakrefDeletionObserver,
concrete_fn: Any):
"""Adds a new concrete function alongside its key.
Args:
context: A FunctionContext representing the current context.
function_type: A FunctionType representing concrete_fn signature.
deletion_observer: A WeakrefDeletionObserver for the concrete_fn validity.
concrete_fn: The concrete function to be added to the cache.
"""
self._primary[(context, function_type)] = concrete_fn
if context not in self._dispatch_dict:
self._dispatch_dict[context] = type_dispatch.TypeDispatchTable()
self._dispatch_dict[context].add_target(function_type)
listener_fn = (lambda: self.delete(context, function_type)
) if DELETE_WITH_WEAKREF else lambda: None
deletion_observer.add_listener(listener_fn)
def generalize(
self, context: FunctionContext,
function_type: function_type_lib.FunctionType
) -> function_type_lib.FunctionType:
"""Try to generalize a FunctionType within a FunctionContext."""
if context in self._dispatch_dict:
return self._dispatch_dict[context].try_generalizing_function_type(
function_type)
else:
return function_type
# TODO(b/205971333): Remove this function.
def clear(self):
"""Removes all concrete functions from the cache."""
self._primary.clear()
self._dispatch_dict.clear()
def values(self):
"""Returns a list of all `ConcreteFunction` instances held by this cache."""
return list(self._primary.values())