102 lines
3.4 KiB
C++
102 lines
3.4 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 <array>
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#include "tensorflow/compiler/tf2xla/xla_helpers.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 "tensorflow/compiler/xla/client/lib/matrix.h"
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#include "tensorflow/compiler/xla/client/xla_builder.h"
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#include "tensorflow/core/framework/op_kernel.h"
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namespace tensorflow {
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namespace {
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constexpr std::array<DataType, 7> kEinsumTypes = {
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{DT_INT32, DT_HALF, DT_BFLOAT16, DT_FLOAT, DT_DOUBLE, DT_COMPLEX64,
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DT_COMPLEX128}};
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// Kernel which compiles XlaEinsum, an einsum op accepting two inputs.
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class XlaEinsumOp : public XlaOpKernel {
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public:
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explicit XlaEinsumOp(OpKernelConstruction* ctx) : XlaOpKernel(ctx) {
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OP_REQUIRES_OK(ctx, ctx->GetAttr("equation", &equation_));
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}
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~XlaEinsumOp() override = default;
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void Compile(XlaOpKernelContext* ctx) override {
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xla::XlaOp lhs = ctx->Input(0);
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if (equation_.find(",") == equation_.npos) {
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ctx->SetOutput(0, xla::Einsum(lhs, equation_));
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} else {
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xla::XlaOp rhs = ctx->Input(1);
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ctx->SetOutput(0, xla::Einsum(lhs, rhs, equation_));
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}
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}
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private:
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string equation_;
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TF_DISALLOW_COPY_AND_ASSIGN(XlaEinsumOp);
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};
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// Kernel which compiles Einsum, an einsum op accepting a list of inputs.
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class EinsumOp : public XlaOpKernel {
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public:
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explicit EinsumOp(OpKernelConstruction* ctx) : XlaOpKernel(ctx) {
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OP_REQUIRES_OK(ctx, ctx->GetAttr("equation", &equation_));
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}
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~EinsumOp() override = default;
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void Compile(XlaOpKernelContext* ctx) override {
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std::vector<xla::XlaOp> input_handles;
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std::vector<TensorShape> input_shapes;
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OP_REQUIRES_OK(ctx,
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ctx->InputList("inputs", &input_handles, &input_shapes));
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if (equation_.find(",") == equation_.npos) {
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OP_REQUIRES(
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ctx, input_handles.size() == 1,
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errors::InvalidArgument(
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"Einsum Op has ", input_handles.size(), " inputs ",
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" but expected 1 input since there is no ',' in equation: ",
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equation_));
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ctx->SetOutput(0, xla::Einsum(input_handles[0], equation_));
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} else {
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OP_REQUIRES(
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ctx, input_handles.size() == 2,
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errors::InvalidArgument(
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"Einsum Op has ", input_handles.size(), " inputs ",
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" but expected 2 inputs since there is a ',' in equation: ",
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equation_));
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ctx->SetOutput(
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0, xla::Einsum(input_handles[0], input_handles[1], equation_));
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}
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}
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private:
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string equation_;
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TF_DISALLOW_COPY_AND_ASSIGN(EinsumOp);
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};
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REGISTER_XLA_OP(Name("XlaEinsum").TypeConstraint("T", kEinsumTypes),
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XlaEinsumOp);
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REGISTER_XLA_OP(Name("Einsum").TypeConstraint("T", kEinsumTypes), EinsumOp);
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} // namespace
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} // namespace tensorflow
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