83 lines
3.1 KiB
C++
83 lines
3.1 KiB
C++
/* Copyright 2017 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.
|
|
==============================================================================*/
|
|
|
|
// XLA implementation of OneHot operator.
|
|
|
|
#include "tensorflow/compiler/tf2xla/literal_util.h"
|
|
#include "tensorflow/compiler/tf2xla/xla_helpers.h"
|
|
#include "tensorflow/compiler/tf2xla/xla_op_kernel.h"
|
|
#include "tensorflow/compiler/tf2xla/xla_op_registry.h"
|
|
|
|
namespace tensorflow {
|
|
namespace {
|
|
|
|
class OneHotOp : public XlaOpKernel {
|
|
public:
|
|
explicit OneHotOp(OpKernelConstruction* ctx) : XlaOpKernel(ctx) {
|
|
OP_REQUIRES_OK(ctx, ctx->GetAttr("axis", &axis_));
|
|
}
|
|
|
|
void Compile(XlaOpKernelContext* ctx) override {
|
|
const TensorShape indices_shape = ctx->InputShape(0);
|
|
const TensorShape depth_shape = ctx->InputShape(1);
|
|
const TensorShape on_value_shape = ctx->InputShape(2);
|
|
const TensorShape off_value_shape = ctx->InputShape(3);
|
|
|
|
const int indices_dims = indices_shape.dims();
|
|
const int output_dims = indices_dims + 1;
|
|
|
|
// Preliminary validation of sizes.
|
|
OP_REQUIRES(
|
|
ctx, axis_ == -1 || (axis_ >= 0 && axis_ < output_dims),
|
|
errors::InvalidArgument("Expected axis to be -1 or between [0, ",
|
|
output_dims, "). But received: ", axis_));
|
|
OP_REQUIRES(ctx, TensorShapeUtils::IsScalar(depth_shape),
|
|
errors::InvalidArgument("depth must be a scalar, but got: ",
|
|
depth_shape.DebugString()));
|
|
OP_REQUIRES(ctx, TensorShapeUtils::IsScalar(on_value_shape),
|
|
errors::InvalidArgument("on_value must be a scalar, but got: ",
|
|
on_value_shape.DebugString()));
|
|
OP_REQUIRES(ctx, TensorShapeUtils::IsScalar(off_value_shape),
|
|
errors::InvalidArgument("off_value must be a scalar, but got: ",
|
|
off_value_shape.DebugString()));
|
|
|
|
const int axis = (axis_ == -1) ? indices_dims : axis_;
|
|
|
|
// The one-hot dimension.
|
|
int64 depth;
|
|
OP_REQUIRES_OK(ctx, ctx->ConstantInputAsIntScalar(1, &depth));
|
|
OP_REQUIRES(
|
|
ctx, depth >= 0,
|
|
errors::InvalidArgument("depth must be non-negative, got: ", depth));
|
|
|
|
xla::XlaOp one_hot;
|
|
OP_REQUIRES_OK(
|
|
ctx, XlaHelpers::OneHot(ctx->builder(), depth, axis, input_type(0),
|
|
indices_shape, ctx->Input(0), ctx->Input(2),
|
|
ctx->Input(3), &one_hot));
|
|
ctx->SetOutput(0, one_hot);
|
|
}
|
|
|
|
private:
|
|
int32 axis_;
|
|
|
|
TF_DISALLOW_COPY_AND_ASSIGN(OneHotOp);
|
|
};
|
|
|
|
REGISTER_XLA_OP(Name("OneHot").CompileTimeConstantInput("depth"), OneHotOp);
|
|
|
|
} // namespace
|
|
} // namespace tensorflow
|