wehub-resource-sync
77 lines
2.6 KiB
C++
77 lines
2.6 KiB
C++
/* Copyright 2019 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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#include <cstdint>
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#include <optional>
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#include <vector>
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#include "tensorflow/compiler/tf2xla/sharding_util.h"
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#include "tensorflow/compiler/tf2xla/xla_op_kernel.h"
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#include "tensorflow/compiler/tf2xla/xla_op_registry.h"
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#include "xla/hlo/builder/xla_builder.h"
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#include "xla/sharding_op_util.h"
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#include "tensorflow/core/framework/op_kernel.h"
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#include "tensorflow/core/framework/op_requires.h"
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namespace tensorflow {
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namespace {
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class ShardingOp : public XlaOpKernel {
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public:
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explicit ShardingOp(OpKernelConstruction* ctx) : XlaOpKernel(ctx) {
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std::vector<int32_t> unspecified_dims;
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OP_REQUIRES_OK(ctx, ctx->GetAttr("unspecified_dims", &unspecified_dims));
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for (int32_t i32 : unspecified_dims) {
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unspecified_dims_.push_back(i32);
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}
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}
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~ShardingOp() override = default;
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void Compile(XlaOpKernelContext* ctx) override {
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xla::XlaOp input;
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{
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// The builder might create a broadcast from a constant, so we clear
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// sharding for the input.
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xla::XlaScopedShardingAssignment no_sharding(ctx->builder(),
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std::nullopt);
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input = ctx->Input(0);
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}
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auto shape_or = ctx->builder()->GetShape(input);
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OP_REQUIRES_OK(ctx, shape_or.status());
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xla::XlaOp output = xla::CustomCall(
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ctx->builder(), /*call_target_name=*/"Sharding", {input},
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shape_or.value(),
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/*opaque=*/
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xla::sharding_op_util::EncodeAttributes(unspecified_dims_));
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if (ctx->compiler()->options().use_shardy_partitioner) {
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OP_REQUIRES_OK(ctx, addSdyShardingFrontendAttribute(
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ctx->builder(), output, shape_or.value()));
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}
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ctx->SetOutput(0, output);
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}
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private:
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ShardingOp(const ShardingOp&) = delete;
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void operator=(const ShardingOp&) = delete;
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std::vector<int64_t> unspecified_dims_;
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};
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REGISTER_XLA_OP(Name("XlaSharding"), ShardingOp);
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} // namespace
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} // namespace tensorflow
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