| /* Copyright 2015 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. |
| ==============================================================================*/ |
| |
| // An example Op. |
| |
| #include "tensorflow/core/framework/op.h" |
| #include "tensorflow/core/framework/op_kernel.h" |
| |
| namespace tensorflow { |
| |
| REGISTER_OP("Ackermann") |
| .Output("ackermann: string") |
| .Doc(R"doc( |
| Output a fact about the ackermann function. |
| )doc"); |
| |
| class AckermannOp : public OpKernel { |
| public: |
| explicit AckermannOp(OpKernelConstruction* context) : OpKernel(context) {} |
| |
| void Compute(OpKernelContext* context) override { |
| // Output a scalar string. |
| Tensor* output_tensor = nullptr; |
| OP_REQUIRES_OK(context, |
| context->allocate_output(0, TensorShape(), &output_tensor)); |
| auto output = output_tensor->scalar<tstring>(); |
| |
| output() = "A(m, 0) == A(m-1, 1)"; |
| } |
| }; |
| |
| REGISTER_KERNEL_BUILDER(Name("Ackermann").Device(DEVICE_CPU), AckermannOp); |
| |
| } // namespace tensorflow |