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#ifndef CAFFE_OPERATORS_ONE_HOT_OPS_H_
#define CAFFE_OPERATORS_ONE_HOT_OPS_H_
#include "caffe2/core/context.h"
#include "caffe2/core/export_caffe2_op_to_c10.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/operator.h"
#include "caffe2/utils/math.h"
C10_DECLARE_EXPORT_CAFFE2_OP_TO_C10(BatchBucketOneHot);
namespace caffe2 {
template <class Context>
class OneHotOp final : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
template <class... Args>
explicit OneHotOp(Args&&... args)
: Operator<Context>(std::forward<Args>(args)...) {}
bool RunOnDevice() override {
auto& indices = Input(0);
CAFFE_ENFORCE_EQ(
indices.dim(),
1,
"indices input must be 1D tensor of data type int64_t");
// Index size input must be in CPU context
auto& index_size_tensor = this->template Input<Tensor>(1, CPU);
CAFFE_ENFORCE_EQ(
index_size_tensor.numel(),
1,
"index_size_tensor input must be scalar of data type int64_t");
auto batch_size = indices.numel();
auto index_size = *index_size_tensor.template data<int64_t>();
auto one_hots = Output(0);
one_hots->Resize(batch_size, index_size);
auto output_size = one_hots->numel();
if (output_size == 0) {
return true;
}
DoOneHotOp(batch_size, index_size, indices, one_hots);
return true;
}
protected:
void DoOneHotOp(
int64_t batch_size,
int64_t index_size,
const Tensor& indices,
Tensor* output);
};
template <class Context>
class BatchOneHotOp final : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
template <class... Args>
explicit BatchOneHotOp(Args&&... args)
: Operator<Context>(std::forward<Args>(args)...) {}
bool RunOnDevice() override {
return DispatchHelper<TensorTypes<int32_t, int64_t>>::call(this, Input(X));
}
template <typename T>
bool DoRunWithType();
INPUT_TAGS(X, LENS, VALS);
protected:
OUTPUT_TAGS(ONE_HOT);
private:
// allows for fast random access to a given dict and is re-used across runs
std::vector<int64_t> valsOffsets_;
};
template <class Context>
class BatchBucketOneHotOp final : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
template <class... Args>
explicit BatchBucketOneHotOp(Args&&... args)
: Operator<Context>(std::forward<Args>(args)...) {}
bool RunOnDevice() override;
protected:
INPUT_TAGS(X, LENS, BOUNDARIES);
OUTPUT_TAGS(ONE_HOT);
};
} // namespace caffe2
#endif // CAFFE_OPERATORS_ONE_HOT_OPS_H_
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