285 lines
8.4 KiB
Python
285 lines
8.4 KiB
Python
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# Copyright 2017 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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"""Utilities for using the TensorFlow C API."""
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import contextlib
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from tensorflow.core.framework import api_def_pb2
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from tensorflow.core.framework import op_def_pb2
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from tensorflow.python.client import pywrap_tf_session as c_api
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from tensorflow.python.util import compat
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from tensorflow.python.util import tf_contextlib
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class AlreadyGarbageCollectedError(Exception):
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def __init__(self, name, obj_type):
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super(AlreadyGarbageCollectedError,
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self).__init__(f"{name} of type {obj_type} has already been garbage "
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f"collected and cannot be called.")
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# FIXME(b/235488206): Convert all Scoped objects to the context manager
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# to protect against deletion during use when the object is attached to
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# an attribute.
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class UniquePtr(object):
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"""Wrapper around single-ownership C-API objects that handles deletion."""
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__slots__ = ["_obj", "deleter", "name", "type_name"]
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def __init__(self, name, obj, deleter):
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# '_' prefix marks _obj private, but unclear if it is required also to
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# maintain a special CPython destruction order.
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self._obj = obj
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self.name = name
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# Note: when we're destructing the global context (i.e when the process is
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# terminating) we may have already deleted other modules. By capturing the
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# DeleteGraph function here, we retain the ability to cleanly destroy the
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# graph at shutdown, which satisfies leak checkers.
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self.deleter = deleter
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self.type_name = str(type(obj))
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@contextlib.contextmanager
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def get(self):
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"""Yields the managed C-API Object, guaranteeing aliveness.
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This is a context manager. Inside the context the C-API object is
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guaranteed to be alive.
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Raises:
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AlreadyGarbageCollectedError: if the object is already deleted.
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"""
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# Thread-safety: self.__del__ never runs during the call of this function
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# because there is a reference to self from the argument list.
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if self._obj is None:
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raise AlreadyGarbageCollectedError(self.name, self.type_name)
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yield self._obj
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def __del__(self):
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obj = self._obj
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if obj is not None:
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self._obj = None
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self.deleter(obj)
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class ScopedTFStatus(object):
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"""Wrapper around TF_Status that handles deletion."""
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__slots__ = ["status"]
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def __init__(self):
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self.status = c_api.TF_NewStatus()
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def __del__(self):
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# Note: when we're destructing the global context (i.e when the process is
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# terminating) we can have already deleted other modules.
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if c_api is not None and c_api.TF_DeleteStatus is not None:
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c_api.TF_DeleteStatus(self.status)
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class ScopedTFGraph(UniquePtr):
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"""Wrapper around TF_Graph that handles deletion."""
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def __init__(self, name):
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super(ScopedTFGraph, self).__init__(
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name, obj=c_api.TF_NewGraph(), deleter=c_api.TF_DeleteGraph)
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class ScopedTFImportGraphDefOptions(object):
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"""Wrapper around TF_ImportGraphDefOptions that handles deletion."""
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__slots__ = ["options"]
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def __init__(self):
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self.options = c_api.TF_NewImportGraphDefOptions()
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def __del__(self):
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# Note: when we're destructing the global context (i.e when the process is
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# terminating) we can have already deleted other modules.
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if c_api is not None and c_api.TF_DeleteImportGraphDefOptions is not None:
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c_api.TF_DeleteImportGraphDefOptions(self.options)
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class ScopedTFImportGraphDefResults(object):
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"""Wrapper around TF_ImportGraphDefOptions that handles deletion."""
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__slots__ = ["results"]
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def __init__(self, results):
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self.results = results
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def __del__(self):
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# Note: when we're destructing the global context (i.e when the process is
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# terminating) we can have already deleted other modules.
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if c_api is not None and c_api.TF_DeleteImportGraphDefResults is not None:
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c_api.TF_DeleteImportGraphDefResults(self.results)
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class ScopedTFFunction(UniquePtr):
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"""Wrapper around TF_Function that handles deletion."""
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def __init__(self, func, name):
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super(ScopedTFFunction, self).__init__(
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name=name, obj=func, deleter=c_api.TF_DeleteFunction)
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class ScopedTFBuffer(object):
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"""An internal class to help manage the TF_Buffer lifetime."""
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__slots__ = ["buffer"]
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def __init__(self, buf_string):
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self.buffer = c_api.TF_NewBufferFromString(compat.as_bytes(buf_string))
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def __del__(self):
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c_api.TF_DeleteBuffer(self.buffer)
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class ApiDefMap(object):
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"""Wrapper around Tf_ApiDefMap that handles querying and deletion.
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The OpDef protos are also stored in this class so that they could
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be queried by op name.
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"""
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__slots__ = ["_api_def_map", "_op_per_name"]
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def __init__(self):
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op_def_proto = op_def_pb2.OpList()
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buf = c_api.TF_GetAllOpList()
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try:
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op_def_proto.ParseFromString(c_api.TF_GetBuffer(buf))
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self._api_def_map = c_api.TF_NewApiDefMap(buf)
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finally:
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c_api.TF_DeleteBuffer(buf)
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self._op_per_name = {}
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for op in op_def_proto.op:
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self._op_per_name[op.name] = op
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def __del__(self):
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# Note: when we're destructing the global context (i.e when the process is
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# terminating) we can have already deleted other modules.
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if c_api is not None and c_api.TF_DeleteApiDefMap is not None:
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c_api.TF_DeleteApiDefMap(self._api_def_map)
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def put_api_def(self, text):
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c_api.TF_ApiDefMapPut(self._api_def_map, text, len(text))
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def get_api_def(self, op_name):
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api_def_proto = api_def_pb2.ApiDef()
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buf = c_api.TF_ApiDefMapGet(self._api_def_map, op_name, len(op_name))
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try:
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api_def_proto.ParseFromString(c_api.TF_GetBuffer(buf))
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finally:
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c_api.TF_DeleteBuffer(buf)
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return api_def_proto
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def get_op_def(self, op_name):
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if op_name in self._op_per_name:
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return self._op_per_name[op_name]
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raise ValueError(f"No op_def found for op name {op_name}.")
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def op_names(self):
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return self._op_per_name.keys()
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@tf_contextlib.contextmanager
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def tf_buffer(data=None):
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"""Context manager that creates and deletes TF_Buffer.
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Example usage:
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with tf_buffer() as buf:
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# get serialized graph def into buf
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...
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proto_data = c_api.TF_GetBuffer(buf)
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graph_def.ParseFromString(compat.as_bytes(proto_data))
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# buf has been deleted
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with tf_buffer(some_string) as buf:
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c_api.TF_SomeFunction(buf)
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# buf has been deleted
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Args:
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data: An optional `bytes`, `str`, or `unicode` object. If not None, the
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yielded buffer will contain this data.
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Yields:
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Created TF_Buffer
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"""
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if data:
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buf = c_api.TF_NewBufferFromString(compat.as_bytes(data))
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else:
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buf = c_api.TF_NewBuffer()
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try:
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yield buf
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finally:
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c_api.TF_DeleteBuffer(buf)
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def tf_output(c_op, index):
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"""Returns a wrapped TF_Output with specified operation and index.
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Args:
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c_op: wrapped TF_Operation
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index: integer
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Returns:
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Wrapped TF_Output
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"""
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ret = c_api.TF_Output()
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ret.oper = c_op
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ret.index = index
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return ret
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def tf_operations(graph):
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"""Generator that yields every TF_Operation in `graph`.
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Args:
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graph: Graph
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Yields:
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wrapped TF_Operation
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"""
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# pylint: disable=protected-access
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pos = 0
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with graph._c_graph.get() as c_graph:
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c_op, pos = c_api.TF_GraphNextOperation(c_graph, pos)
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while c_op is not None:
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yield c_op
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c_op, pos = c_api.TF_GraphNextOperation(c_graph, pos)
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# pylint: enable=protected-access
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def new_tf_operations(graph):
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"""Generator that yields newly-added TF_Operations in `graph`.
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Specifically, yields TF_Operations that don't have associated Operations in
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`graph`. This is useful for processing nodes added by the C API.
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Args:
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graph: Graph
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Yields:
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wrapped TF_Operation
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"""
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# TODO(b/69679162): do this more efficiently
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for c_op in tf_operations(graph):
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try:
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graph._get_operation_by_tf_operation(c_op) # pylint: disable=protected-access
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except KeyError:
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yield c_op
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