96 lines
3.5 KiB
C++
96 lines
3.5 KiB
C++
/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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#ifndef TENSORFLOW_COMPILER_XLA_SERVICE_CHANNEL_TRACKER_H_
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#define TENSORFLOW_COMPILER_XLA_SERVICE_CHANNEL_TRACKER_H_
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#include <map>
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#include "absl/container/flat_hash_map.h"
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#include "absl/types/span.h"
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#include "tensorflow/compiler/xla/service/hlo_module.h"
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#include "tensorflow/compiler/xla/status.h"
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#include "tensorflow/compiler/xla/statusor.h"
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#include "tensorflow/compiler/xla/types.h"
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#include "tensorflow/compiler/xla/xla_data.pb.h"
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#include "tensorflow/core/platform/macros.h"
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#include "tensorflow/core/platform/mutex.h"
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#include "tensorflow/core/platform/thread_annotations.h"
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#include "tensorflow/core/platform/types.h"
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namespace xla {
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// Tracks channels between computations in the XLA service. Channels
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// are associated with a unique handle and can be resolved from the handle for
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// later use.
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//
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// TODO(b/34027823): Destruct channels when all the associated computations that
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// communicate via each channel are destructed.
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class ChannelTracker {
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public:
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ChannelTracker();
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// A struct that keeps the current status of each channel. has_sender and
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// receiver_count fields are initialized with false and 0 respectively when
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// the struct is created and are updated by RegisterSend() and RegisterRecev()
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// as Send or Recv instructions using the channel are requested.
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struct Channel {
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bool has_sender;
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int64 receiver_count;
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ChannelHandle::ChannelType type;
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};
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// Creates a new Channel object and returns the corresponding
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// ChannelHandle for it.
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StatusOr<ChannelHandle> NewChannel(ChannelHandle::ChannelType type);
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// Informs that the given channel handle is used for a Send operation.
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// Returns an error status if the handle is already used by another Send.
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Status RegisterSend(const ChannelHandle& handle);
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// Informs that the given channel handle is used for a Recv operation.
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// Returns an error status if the handle is already used by another Recv.
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Status RegisterRecv(const ChannelHandle& handle);
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private:
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// Bumps the next_channel_ number and returns the allocated number
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// wrapped in a ChannelHandle.
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ChannelHandle AllocateHandle(ChannelHandle::ChannelType type)
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TF_EXCLUSIVE_LOCKS_REQUIRED(channel_mutex_);
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Status RegisterSendInternal(const ChannelHandle& handle)
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TF_EXCLUSIVE_LOCKS_REQUIRED(channel_mutex_);
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Status RegisterRecvInternal(const ChannelHandle& handle)
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TF_EXCLUSIVE_LOCKS_REQUIRED(channel_mutex_);
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// Guards the channel mapping.
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tensorflow::mutex channel_mutex_;
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// The next sequence number to assign to a channel.
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int64 next_channel_ TF_GUARDED_BY(channel_mutex_);
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// Mapping from ChannelHandle value to the corresponding registered
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// Channel object.
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absl::flat_hash_map<int64, Channel> opaque_to_channel_
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TF_GUARDED_BY(channel_mutex_);
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TF_DISALLOW_COPY_AND_ASSIGN(ChannelTracker);
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};
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} // namespace xla
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#endif // TENSORFLOW_COMPILER_XLA_SERVICE_CHANNEL_TRACKER_H_
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