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author | Manjunath Kudlur <keveman@gmail.com> | 2015-11-06 16:27:58 -0800 |
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committer | Manjunath Kudlur <keveman@gmail.com> | 2015-11-06 16:27:58 -0800 |
commit | f41959ccb2d9d4c722fe8fc3351401d53bcf4900 (patch) | |
tree | ef0ca22cb2a5ac4bdec9d080d8e0788a53ed496d /tensorflow/core/kernels/listdiff_op.cc |
TensorFlow: Initial commit of TensorFlow library.
TensorFlow is an open source software library for numerical computation
using data flow graphs.
Base CL: 107276108
Diffstat (limited to 'tensorflow/core/kernels/listdiff_op.cc')
-rw-r--r-- | tensorflow/core/kernels/listdiff_op.cc | 75 |
1 files changed, 75 insertions, 0 deletions
diff --git a/tensorflow/core/kernels/listdiff_op.cc b/tensorflow/core/kernels/listdiff_op.cc new file mode 100644 index 0000000000..f490f5ddd3 --- /dev/null +++ b/tensorflow/core/kernels/listdiff_op.cc @@ -0,0 +1,75 @@ +#include <unordered_set> +#include <utility> + +#include "tensorflow/core/framework/op_kernel.h" +#include "tensorflow/core/framework/register_types.h" +#include "tensorflow/core/public/tensor_shape.h" +#include "tensorflow/core/public/tensor.h" +#include "tensorflow/core/public/status.h" + +namespace tensorflow { +template <typename T> +class ListDiffOp : public OpKernel { + public: + explicit ListDiffOp(OpKernelConstruction* context) : OpKernel(context) { + const DataType dt = DataTypeToEnum<T>::v(); + OP_REQUIRES_OK(context, context->MatchSignature({dt, dt}, {dt, DT_INT32})); + } + + void Compute(OpKernelContext* context) override { + const Tensor& x = context->input(0); + const Tensor& y = context->input(1); + + OP_REQUIRES(context, TensorShapeUtils::IsVector(x.shape()), + errors::InvalidArgument("x should be a 1D vector.")); + + OP_REQUIRES(context, TensorShapeUtils::IsVector(y.shape()), + errors::InvalidArgument("y should be a 1D vector.")); + + std::unordered_set<T> y_set; + const auto Ty = y.vec<T>(); + const int y_size = Ty.size(); + y_set.reserve(y_size); + for (int i = 0; i < y_size; ++i) { + y_set.insert(Ty(i)); + } + + // Compute the size of the output. + const auto Tx = x.vec<T>(); + const int x_size = Tx.size(); + + int out_size = 0; + for (int i = 0; i < x_size; ++i) { + if (y_set.count(Tx(i)) == 0) { + ++out_size; + } + } + + // Allocate and populate outputs. + Tensor* out = nullptr; + OP_REQUIRES_OK(context, context->allocate_output(0, {out_size}, &out)); + auto Tout = out->vec<T>(); + + Tensor* indices = nullptr; + OP_REQUIRES_OK(context, context->allocate_output(1, {out_size}, &indices)); + auto Tindices = indices->vec<int32>(); + + for (int i = 0, p = 0; i < x_size; ++i) { + if (y_set.count(Tx(i)) == 0) { + Tout(p) = Tx(i); + Tindices(p) = i; + p++; + } + } + } +}; + +#define REGISTER_LISTDIFF(type) \ + REGISTER_KERNEL_BUILDER( \ + Name("ListDiff").Device(DEVICE_CPU).TypeConstraint<type>("T"), \ + ListDiffOp<type>) + +TF_CALL_REAL_NUMBER_TYPES(REGISTER_LISTDIFF); +#undef REGISTER_LISTDIFF + +} // namespace tensorflow |