Fixes a TODO in PJRT. In general, we may have multiple tasks per physical host, so "task_id" is more accurate. PiperOrigin-RevId: 353984838 Change-Id: I59340c15181374a3db488b238ed81836a94003d0
61 lines
2.2 KiB
C++
61 lines
2.2 KiB
C++
/* Copyright 2020 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_PJRT_TPU_CLIENT_H_
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#define TENSORFLOW_COMPILER_XLA_PJRT_TPU_CLIENT_H_
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#include <array>
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#include <memory>
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#include <vector>
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#include "tensorflow/compiler/xla/pjrt/pjrt_stream_executor_client.h"
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#include "tensorflow/compiler/xla/statusor.h"
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#include "tensorflow/stream_executor/tpu/tpu_topology.h"
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namespace xla {
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class PjRtTpuDevice : public PjRtStreamExecutorDevice {
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public:
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PjRtTpuDevice(const tensorflow::tpu::TpuCoreLocationExternal core,
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std::unique_ptr<LocalDeviceState> local_device_state,
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int task_id, const std::array<int, 3>& coords,
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std::string device_kind)
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: PjRtStreamExecutorDevice(core.Id(), std::move(local_device_state),
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std::move(device_kind), task_id),
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core_(core),
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coords_(coords) {}
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const std::array<int, 3>& coords() const { return coords_; }
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int core_on_chip() const { return core_.index(); }
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const tensorflow::tpu::TpuCoreLocationExternal core() const { return core_; }
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std::string DebugString() const override {
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return absl::StrFormat("TPU_%i(host=%i,(%i,%i,%i,%i))", id(), task_id(),
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coords_[0], coords_[1], coords_[2], core_.index());
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}
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private:
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const tensorflow::tpu::TpuCoreLocationExternal core_;
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const std::array<int, 3> coords_;
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};
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StatusOr<std::shared_ptr<PjRtClient>> GetTpuClient(
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bool asynchronous,
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absl::Duration init_retry_timeout = absl::ZeroDuration());
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} // namespace xla
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#endif // TENSORFLOW_COMPILER_XLA_PJRT_TPU_CLIENT_H_
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