1 /* Copyright 2015 The TensorFlow Authors. All Rights Reserved. 2 3 Licensed under the Apache License, Version 2.0 (the "License"); 4 you may not use this file except in compliance with the License. 5 You may obtain a copy of the License at 6 7 http://www.apache.org/licenses/LICENSE-2.0 8 9 Unless required by applicable law or agreed to in writing, software 10 distributed under the License is distributed on an "AS IS" BASIS, 11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 See the License for the specific language governing permissions and 13 limitations under the License. 14 ==============================================================================*/ 15 16 #include "tensorflow/core/framework/op_kernel.h" 17 #include "tensorflow/core/kernels/variable_ops.h" 18 #include "tensorflow/core/lib/core/errors.h" 19 #include "tensorflow/core/platform/mutex.h" 20 #include "tensorflow/core/platform/types.h" 21 22 namespace tensorflow { 23 24 template <class T> 25 class CountUpToOp : public OpKernel { 26 public: 27 explicit CountUpToOp(OpKernelConstruction* context) : OpKernel(context) { 28 OP_REQUIRES_OK(context, context->GetAttr("limit", &limit_)); 29 } 30 31 void Compute(OpKernelContext* context) override { 32 T before_increment; 33 { 34 mutex_lock l(*context->input_ref_mutex(0)); 35 Tensor tensor = context->mutable_input(0, true); 36 OP_REQUIRES(context, TensorShapeUtils::IsScalar(tensor.shape()), 37 errors::InvalidArgument("input is not a scalar: ", 38 tensor.shape().DebugString())); 39 T* ptr = &tensor.scalar<T>()(); 40 before_increment = *ptr; 41 if (*ptr >= limit_) { 42 context->SetStatus(errors::OutOfRange("Reached limit of ", limit_)); 43 return; 44 } 45 ++*ptr; 46 } 47 // Output if no error. 48 Tensor* out_tensor; 49 OP_REQUIRES_OK(context, context->allocate_output("output", TensorShape({}), 50 &out_tensor)); 51 out_tensor->scalar<T>()() = before_increment; 52 } 53 54 private: 55 T limit_; 56 }; 57 58 template <class T> 59 class ResourceCountUpToOp : public OpKernel { 60 public: 61 explicit ResourceCountUpToOp(OpKernelConstruction* context) 62 : OpKernel(context) { 63 OP_REQUIRES_OK(context, context->GetAttr("limit", &limit_)); 64 OP_REQUIRES_OK(context, context->GetAttr("T", &dtype_)); 65 } 66 67 void Compute(OpKernelContext* context) override { 68 Var* variable = nullptr; 69 OP_REQUIRES_OK( 70 context, 71 LookupResource<Var>(context, HandleFromInput(context, 0), &variable)); 72 core::ScopedUnref s(variable); 73 mutex_lock l(*variable->mu()); 74 Tensor before_increment = *variable->tensor(); 75 OP_REQUIRES( 76 context, TensorShapeUtils::IsScalar(before_increment.shape()), 77 errors::InvalidArgument("input is not a scalar: ", 78 before_increment.shape().DebugString())); 79 if (before_increment.scalar<T>()() >= limit_) { 80 context->SetStatus(errors::OutOfRange("Reached limit of ", limit_)); 81 return; 82 } 83 // Allocate new buffer 84 AllocatorAttributes attr; 85 attr.set_gpu_compatible(true); 86 attr.set_nic_compatible(true); 87 PersistentTensor unused; 88 Tensor* tmp; 89 OP_REQUIRES_OK(context, context->allocate_persistent( 90 dtype_, TensorShape({}), &unused, &tmp, attr)); 91 *variable->tensor() = *tmp; 92 tmp->scalar<T>()() = before_increment.scalar<T>()() + 1; 93 context->set_output(0, before_increment); 94 } 95 96 private: 97 T limit_; 98 DataType dtype_; 99 }; 100 101 #define REGISTER(TYPE) \ 102 REGISTER_KERNEL_BUILDER( \ 103 Name("CountUpTo").TypeConstraint<TYPE>("T").Device(DEVICE_CPU), \ 104 CountUpToOp<TYPE>) \ 105 REGISTER_KERNEL_BUILDER( \ 106 Name("ResourceCountUpTo").TypeConstraint<TYPE>("T").Device(DEVICE_CPU), \ 107 ResourceCountUpToOp<TYPE>) 108 109 REGISTER(int32); 110 REGISTER(int64); 111 112 #undef REGISTER 113 114 } // namespace tensorflow 115
