/* Copyright 2015 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/core/framework/op.h"
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#include "tensorflow/core/framework/op_kernel.h"
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using namespace tensorflow; // NOLINT(build/namespaces)
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REGISTER_OP("AddOne")
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.Input("input: int32")
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.Output("output: int32")
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.Doc(R"doc(
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Adds 1 to all elements of the tensor.
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output: A Tensor.
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output = input + 1
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)doc");
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void AddOneKernelLauncher(const int* in, const int N, int* out);
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class AddOneOp : public OpKernel {
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public:
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explicit AddOneOp(OpKernelConstruction* context) : OpKernel(context) {}
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void Compute(OpKernelContext* context) override {
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// Grab the input tensor
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const Tensor& input_tensor = context->input(0);
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auto input = input_tensor.flat<int32>();
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// Create an output tensor
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Tensor* output_tensor = nullptr;
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OP_REQUIRES_OK(context, context->allocate_output(0, input_tensor.shape(),
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&output_tensor));
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auto output = output_tensor->template flat<int32>();
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// Set all but the first element of the output tensor to 0.
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const int N = input.size();
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// Call the cuda kernel launcher
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AddOneKernelLauncher(input.data(), N, output.data());
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}
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};
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REGISTER_KERNEL_BUILDER(Name("AddOne").Device(DEVICE_GPU), AddOneOp);
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