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Open source the XRTTpuDeviceAccessor and register XRTStateOps on TPU on the open source XRT side.

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PiperOrigin-RevId: 345582775
Change-Id: Ie97bae4e37b16ba8bce411c016e80b50f7a26ff1
This commit is contained in:
A. Unique TensorFlower 2020-12-03 18:59:28 -08:00 committed by TensorFlower Gardener
parent 1943e58d29
commit 293bd7502b
8 changed files with 0 additions and 202 deletions
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4
tensorflow/compiler/xrt/BUILD
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@ -41,7 +41,6 @@ cc_library(
"xrt_memory_manager.cc",
"xrt_metrics.cc",
"xrt_state.cc",
"xrt_tpu_device.cc",
"xrt_util.cc",
],
hdrs = [
@ -51,7 +50,6 @@ cc_library(
"xrt_metrics.h",
"xrt_refptr.h",
"xrt_state.h",
"xrt_tpu_device.h",
"xrt_util.h",
],
visibility = ["//visibility:public"],
@ -78,10 +76,8 @@ cc_library(
"//tensorflow/core:lib_internal",
"//tensorflow/core/platform:regexp",
"//tensorflow/core/profiler/lib:traceme",
"//tensorflow/core/tpu:tpu_configuration",
"//tensorflow/stream_executor",
"//tensorflow/stream_executor:device_memory_allocator",
"//tensorflow/stream_executor/tpu:tpu_node_context",
"@com_google_absl//absl/memory",
"@com_google_absl//absl/synchronization",
],

1
tensorflow/compiler/xrt/kernels/BUILD
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@ -73,7 +73,6 @@ cc_library(
"//tensorflow/core:lib",
"//tensorflow/core:lib_internal",
"//tensorflow/core:protos_all_cc",
"//tensorflow/core/tpu:tpu_defs",
"//tensorflow/stream_executor:stream_executor_headers",
"@com_google_absl//absl/strings",
],

65
tensorflow/compiler/xrt/kernels/xrt_state_ops.cc
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@ -24,7 +24,6 @@ limitations under the License.
#include "tensorflow/compiler/tf2xla/xla_op_registry.h"
#include "tensorflow/compiler/xla/client/local_client.h"
#include "tensorflow/compiler/xrt/xrt_metrics.h"
#include "tensorflow/core/tpu/tpu_defs.h"
namespace tensorflow {
namespace {
@ -68,11 +67,6 @@ REGISTER_KERNEL_BUILDER(Name("XRTAllocate")
.HostMemory("allocation")
.HostMemory("handle"),
XRTAllocateOp<XRTGenericDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTAllocate")
.Device(DEVICE_TPU_NODE)
.HostMemory("allocation")
.HostMemory("handle"),
XRTAllocateOp<XRTTpuDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTAllocateUninitialized")
.Device(DEVICE_XLA_GPU)
@ -82,10 +76,6 @@ REGISTER_KERNEL_BUILDER(Name("XRTAllocateUninitialized")
.Device(DEVICE_XLA_CPU)
.HostMemory("handle"),
XRTAllocateUninitializedOp<XRTGenericDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTAllocateUninitialized")
.Device(DEVICE_TPU_NODE)
.HostMemory("handle"),
XRTAllocateUninitializedOp<XRTTpuDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTAllocateFromTensor")
.Device(DEVICE_XLA_GPU)
@ -97,11 +87,6 @@ REGISTER_KERNEL_BUILDER(Name("XRTAllocateFromTensor")
.HostMemory("inputs")
.HostMemory("handle"),
XRTAllocateFromTensorOp<XRTGenericDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTAllocateFromTensor")
.Device(DEVICE_TPU_NODE)
.HostMemory("inputs")
.HostMemory("handle"),
XRTAllocateFromTensorOp<XRTTpuDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTSubTuple")
.Device(DEVICE_XLA_GPU)
@ -115,12 +100,6 @@ REGISTER_KERNEL_BUILDER(Name("XRTSubTuple")
.HostMemory("shape_index")
.HostMemory("output_handle"),
XRTSubTupleOp<false, XRTGenericDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTSubTuple")
.Device(DEVICE_TPU_NODE)
.HostMemory("base_handle")
.HostMemory("shape_index")
.HostMemory("output_handle"),
XRTSubTupleOp<false, XRTTpuDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTSubTupleAndRelease")
.Device(DEVICE_XLA_GPU)
@ -134,12 +113,6 @@ REGISTER_KERNEL_BUILDER(Name("XRTSubTupleAndRelease")
.HostMemory("shape_index")
.HostMemory("output_handle"),
XRTSubTupleOp<true, XRTGenericDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTSubTupleAndRelease")
.Device(DEVICE_TPU_NODE)
.HostMemory("base_handle")
.HostMemory("shape_index")
.HostMemory("output_handle"),
XRTSubTupleOp<true, XRTTpuDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTMakeTuple")
.Device(DEVICE_XLA_GPU)
@ -153,12 +126,6 @@ REGISTER_KERNEL_BUILDER(Name("XRTMakeTuple")
.HostMemory("input_handles")
.HostMemory("output_handle"),
XRTMakeTupleOp<XRTGenericDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTMakeTuple")
.Device(DEVICE_TPU_NODE)
.HostMemory("tuple_description")
.HostMemory("input_handles")
.HostMemory("output_handle"),
XRTMakeTupleOp<XRTTpuDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTReadLiteral")
.Device(DEVICE_XLA_GPU)
@ -170,11 +137,6 @@ REGISTER_KERNEL_BUILDER(Name("XRTReadLiteral")
.HostMemory("handle")
.HostMemory("literal"),
XRTReadLiteralOp<false, XRTGenericDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTReadLiteral")
.Device(DEVICE_TPU_NODE)
.HostMemory("handle")
.HostMemory("literal"),
XRTReadLiteralOp<false, XRTTpuDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTWriteLiteral")
.Device(DEVICE_XLA_GPU)
@ -188,12 +150,6 @@ REGISTER_KERNEL_BUILDER(Name("XRTWriteLiteral")
.HostMemory("literal")
.HostMemory("output_handle"),
XRTWriteLiteralOp<XRTGenericDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTWriteLiteral")
.Device(DEVICE_TPU_NODE)
.HostMemory("handle")
.HostMemory("literal")
.HostMemory("output_handle"),
XRTWriteLiteralOp<XRTTpuDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTReadLiteralAndRelease")
.Device(DEVICE_XLA_GPU)
@ -205,11 +161,6 @@ REGISTER_KERNEL_BUILDER(Name("XRTReadLiteralAndRelease")
.HostMemory("handle")
.HostMemory("literal"),
XRTReadLiteralOp<true, XRTGenericDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTReadLiteralAndRelease")
.Device(DEVICE_TPU_NODE)
.HostMemory("handle")
.HostMemory("literal"),
XRTReadLiteralOp<true, XRTTpuDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTReadToTensor")
.Device(DEVICE_XLA_GPU)
@ -221,11 +172,6 @@ REGISTER_KERNEL_BUILDER(Name("XRTReadToTensor")
.HostMemory("handles")
.HostMemory("tensors"),
XRTReadToTensorOp<XRTGenericDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTReadToTensor")
.Device(DEVICE_TPU_NODE)
.HostMemory("handles")
.HostMemory("tensors"),
XRTReadToTensorOp<XRTTpuDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTReleaseAllocationHandle")
.Device(DEVICE_XLA_GPU)
@ -235,25 +181,16 @@ REGISTER_KERNEL_BUILDER(Name("XRTReleaseAllocationHandle")
.Device(DEVICE_XLA_CPU)
.HostMemory("handle"),
XRTReleaseAllocationOp<XRTGenericDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTReleaseAllocationHandle")
.Device(DEVICE_TPU_NODE)
.HostMemory("handle"),
XRTReleaseAllocationOp<XRTTpuDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTReleaseAllAllocations").Device(DEVICE_XLA_GPU),
XRTReleaseAllAllocationsOp<XRTGenericDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTReleaseAllAllocations").Device(DEVICE_XLA_CPU),
XRTReleaseAllAllocationsOp<XRTGenericDeviceAccessor>);
REGISTER_KERNEL_BUILDER(
Name("XRTReleaseAllAllocations").Device(DEVICE_TPU_NODE),
XRTReleaseAllAllocationsOp<XRTTpuDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTCompactAllocations").Device(DEVICE_XLA_GPU),
XRTCompactAllocationsOp<XRTGenericDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTCompactAllocations").Device(DEVICE_XLA_CPU),
XRTCompactAllocationsOp<XRTGenericDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTCompactAllocations").Device(DEVICE_TPU_NODE),
XRTCompactAllocationsOp<XRTTpuDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTMetricsCollect").Device(DEVICE_CPU),
XRTMetricsCollectOp);
@ -262,7 +199,5 @@ REGISTER_KERNEL_BUILDER(Name("XRTMemoryInfo").Device(DEVICE_XLA_GPU),
XRTMemoryInfoOp<XRTGenericDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTMemoryInfo").Device(DEVICE_XLA_CPU),
XRTMemoryInfoOp<XRTGenericDeviceAccessor>);
REGISTER_KERNEL_BUILDER(Name("XRTMemoryInfo").Device(DEVICE_TPU_NODE),
XRTMemoryInfoOp<XRTTpuDeviceAccessor>);
} // namespace tensorflow

1
tensorflow/compiler/xrt/kernels/xrt_state_ops.h
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@ -37,7 +37,6 @@ limitations under the License.
#include "tensorflow/compiler/xrt/xrt_memory_manager.h"
#include "tensorflow/compiler/xrt/xrt_metrics.h"
#include "tensorflow/compiler/xrt/xrt_state.h"
#include "tensorflow/compiler/xrt/xrt_tpu_device.h"
#include "tensorflow/core/common_runtime/dma_helper.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/resource_mgr.h"

61
tensorflow/compiler/xrt/xrt_tpu_device.cc
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@ -1,61 +0,0 @@
/* Copyright 2020 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.
==============================================================================*/
#include "tensorflow/compiler/xrt/xrt_tpu_device.h"
#include "tensorflow/compiler/jit/xla_device.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/resource_mgr.h"
#include "tensorflow/core/lib/core/status.h"
#include "tensorflow/core/tpu/tpu_configuration.h"
namespace tensorflow {
/*static*/ Status XRTTpuDeviceAccessor::GetResourceManager(OpKernelContext* ctx,
ResourceMgr** rm) {
// ctx is unused here, but maintained because XRTGenericDeviceAccessor uses
// it in its GetResourceManager.
*rm = GetTPUConfigResourceMgr();
if (*rm == nullptr) {
return errors::Internal("No Tpu resource manager.");
}
return Status::OK();
}
Status XRTTpuDeviceAccessor::ScopedRef::Acquire(int device_ordinal) {
TF_ASSIGN_OR_RETURN(node_context_,
tpu::TpuNodeContext::Create(device_ordinal));
ordinal_ = device_ordinal;
return Status::OK();
}
Status XRTTpuDeviceAccessor::ScopedRef::Acquire(OpKernelContext* ctx) {
const XlaDevice::Metadata* metadata;
TF_RETURN_IF_ERROR(XlaDevice::GetMetadata(ctx, &metadata));
return Acquire(metadata->device_ordinal());
}
/*static*/ Status XRTTpuDeviceAccessor::InitScopedRef(
OpKernelContext* /*unused ctx*/, int device_ordinal,
ScopedRef* scoped_ref) {
return scoped_ref->Acquire(device_ordinal);
}
/*static*/ Status XRTTpuDeviceAccessor::InitScopedRef(OpKernelContext* ctx,
ScopedRef* scoped_ref) {
return scoped_ref->Acquire(ctx);
}
} // namespace tensorflow

68
tensorflow/compiler/xrt/xrt_tpu_device.h
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@ -1,68 +0,0 @@
/* Copyright 2020 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.
==============================================================================*/
// Classes for keeping track of on-device state for TPUs.
#ifndef TENSORFLOW_COMPILER_XRT_XRT_TPU_DEVICE_H_
#define TENSORFLOW_COMPILER_XRT_XRT_TPU_DEVICE_H_
#include "tensorflow/compiler/xla/client/local_client.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/resource_mgr.h"
#include "tensorflow/stream_executor/tpu/tpu_node_context.h"
namespace tensorflow {
// This accessor is used for XLA TPU. It uses the distributed TPU compilation
// cache infrastructure which it accesses via the TPU_SYSTEM resource manager.
class XRTTpuDeviceAccessor {
public:
static Status GetResourceManager(OpKernelContext* ctx, ResourceMgr** rm);
class ScopedRef {
public:
ScopedRef() {}
~ScopedRef() {}
ScopedRef(const ScopedRef&) = delete;
ScopedRef& operator=(const ScopedRef&) = delete;
// Returns the XLA device properties from the TpuNodeContext object
// protected by this ScopedRef.
xla::Backend* backend() { return node_context_->backend(); }
int device_ordinal() { return ordinal_; }
private:
// XRTTpuDeviceAccessor::InitScopedRef is the only way to initialize
// ScopedRef.
friend class XRTTpuDeviceAccessor;
Status Acquire(int device_ordinal);
Status Acquire(OpKernelContext* ctx);
std::unique_ptr<tpu::TpuNodeContext> node_context_;
int ordinal_ = 0;
};
static Status InitScopedRef(OpKernelContext* ctx, int device_ordinal,
ScopedRef* scoped_ref);
static Status InitScopedRef(OpKernelContext* ctx, ScopedRef* scoped_ref);
};
} // namespace tensorflow
#endif // TENSORFLOW_COMPILER_XRT_XRT_TPU_DEVICE_H_

1
tensorflow/core/tpu/BUILD
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@ -9,7 +9,6 @@ load(
package(
default_visibility = [
"//tensorflow/compiler/tf2xla/kernels:__subpackages__",
"//tensorflow/compiler/xrt:__subpackages__",
"//tensorflow/core/tpu:__subpackages__",
"//tensorflow/stream_executor/tpu:__subpackages__",
],

1
tensorflow/stream_executor/tpu/BUILD
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@ -5,7 +5,6 @@ load("//tensorflow/core/platform:rules_cc.bzl", "cc_library")
package(
default_visibility = [
"//learning/brain/experimental/dtensor:__subpackages__",
"//tensorflow/compiler/xrt:__subpackages__",
"//tensorflow/core/tpu:__subpackages__",
],
licenses = ["notice"], # Apache 2.0