wehub-resource-sync
83 lines
3.2 KiB
C++
83 lines
3.2 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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#include "absl/status/status.h"
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#include "absl/status/statusor.h"
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#include "absl/strings/str_cat.h"
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#include "tensorflow/compiler/tf2xla/lib/broadcast.h"
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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 "xla/hlo/builder/lib/arithmetic.h"
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#include "xla/hlo/builder/lib/constants.h"
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#include "xla/hlo/builder/lib/loops.h"
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#include "xla/hlo/builder/lib/math.h"
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#include "xla/hlo/builder/xla_builder.h"
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#include "xla/status_macros.h"
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namespace tensorflow {
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namespace {
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class BetaincOp : public XlaOpKernel {
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public:
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explicit BetaincOp(OpKernelConstruction* ctx) : XlaOpKernel(ctx) {}
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void Compile(XlaOpKernelContext* ctx) override {
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const TensorShape& a_shape = ctx->InputShape(0);
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const TensorShape& b_shape = ctx->InputShape(1);
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const TensorShape& x_shape = ctx->InputShape(2);
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if (a_shape.dims() > 0 && b_shape.dims() > 0) {
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OP_REQUIRES(ctx, a_shape == b_shape,
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absl::InvalidArgumentError(absl::StrCat(
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"Shapes of a and b are inconsistent: ",
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a_shape.DebugString(), " vs. ", b_shape.DebugString())));
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}
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if (a_shape.dims() > 0 && x_shape.dims() > 0) {
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OP_REQUIRES(ctx, a_shape == x_shape,
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absl::InvalidArgumentError(absl::StrCat(
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"Shapes of a and x are inconsistent: ",
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a_shape.DebugString(), " vs. ", x_shape.DebugString())));
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}
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if (b_shape.dims() > 0 && x_shape.dims() > 0) {
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OP_REQUIRES(ctx, b_shape == x_shape,
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absl::InvalidArgumentError(absl::StrCat(
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"Shapes of b and x are inconsistent: ",
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b_shape.DebugString(), " vs. ", x_shape.DebugString())));
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}
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TensorShape merged_shape(a_shape);
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if (b_shape.dims() > 0) merged_shape = b_shape;
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if (x_shape.dims() > 0) merged_shape = x_shape;
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auto builder = ctx->builder();
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auto result =
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builder->ReportErrorOrReturn([&]() -> absl::StatusOr<xla::XlaOp> {
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TF_ASSIGN_OR_RETURN(
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auto a, BroadcastTo(ctx->Input(0), merged_shape.dim_sizes()));
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TF_ASSIGN_OR_RETURN(
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auto b, BroadcastTo(ctx->Input(1), merged_shape.dim_sizes()));
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TF_ASSIGN_OR_RETURN(
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auto x, BroadcastTo(ctx->Input(2), merged_shape.dim_sizes()));
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return xla::RegularizedIncompleteBeta(a, b, x);
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});
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ctx->SetOutput(0, result);
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}
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};
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REGISTER_XLA_OP(Name("Betainc"), BetaincOp);
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} // namespace
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} // namespace tensorflow
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