66 lines
2.5 KiB
C++
66 lines
2.5 KiB
C++
/* Copyright 2018 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 "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/sorting.h"
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#include "tensorflow/compiler/xla/client/xla_builder.h"
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#include "tensorflow/compiler/xla/literal.h"
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#include "tensorflow/core/framework/kernel_def_builder.h"
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#include "tensorflow/core/framework/types.h"
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namespace tensorflow {
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namespace {
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class TopKOp : public XlaOpKernel {
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public:
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explicit TopKOp(OpKernelConstruction* context) : XlaOpKernel(context) {
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OP_REQUIRES_OK(context, context->GetAttr("sorted", &sorted_));
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}
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void Compile(XlaOpKernelContext* context) override {
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int64 k;
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OP_REQUIRES_OK(context, context->ConstantInputAsIntScalar(1, &k));
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OP_REQUIRES(context, k >= 0,
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errors::InvalidArgument("Need k >= 0, got ", k));
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const TensorShape input_shape = context->InputShape(0);
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OP_REQUIRES(context, input_shape.dims() >= 1,
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errors::InvalidArgument("input must be >= 1-D, got shape ",
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input_shape.DebugString()));
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int last_dim = input_shape.dims() - 1;
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int last_dim_size = input_shape.dim_size(last_dim);
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OP_REQUIRES(
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context, last_dim_size >= k,
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errors::InvalidArgument("input must have at least k columns. Had ",
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last_dim_size, ", needed ", k));
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if (last_dim_size < k) {
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k = last_dim_size;
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}
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xla::XlaOp output_tuple = TopK(context->Input(0), k);
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context->SetOutput(0, xla::GetTupleElement(output_tuple, 0));
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context->SetOutput(1, xla::GetTupleElement(output_tuple, 1));
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}
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private:
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bool sorted_;
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};
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REGISTER_XLA_OP(Name("TopKV2").CompileTimeConstantInput("k").TypeConstraint(
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"T", {DT_UINT32, DT_INT32, DT_FLOAT, DT_BFLOAT16}),
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TopKOp);
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} // namespace
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} // namespace tensorflow
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