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