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#ifndef CAFFE2_OPERATORS_INT8_FLATTEN_OP_H_
#define CAFFE2_OPERATORS_INT8_FLATTEN_OP_H_
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/operators/quantized/int8_utils.h"
namespace caffe2 {
namespace int8 {
class Int8FlattenOp : public Operator<CPUContext> {
public:
template <class... Args>
explicit Int8FlattenOp(Args&&... args)
: Operator<CPUContext>(std::forward<Args>(args)...),
axis_(this->template GetSingleArgument<int>("axis", 1)) {}
bool RunOnDevice() override {
const auto& X = Inputs()[0]->Get<Int8TensorCPU>();
auto* Y = Outputs()[0]->GetMutable<Int8TensorCPU>();
int32_t Y_offset = this->template GetSingleArgument<int>("Y_zero_point", 0);
auto Y_scale = this->template GetSingleArgument<float>("Y_scale", 1);
TORCH_CHECK_EQ(Y_offset, X.zero_point);
TORCH_CHECK_EQ(Y_scale, X.scale);
Y->scale = Y_scale;
Y->zero_point = Y_offset;
CAFFE_ENFORCE_GE(
X.t.sizes().size(), axis_, "The rank of the tensor must be >= axis.");
Y->t.Resize(X.t.size_to_dim(axis_), X.t.size_from_dim(axis_));
context_.CopyItemsToCPU(
X.t.dtype(),
X.t.numel(),
X.t.raw_data(),
Y->t.raw_mutable_data(X.t.dtype()));
return true;
}
private:
int axis_;
};
} // namespace int8
} // namespace caffe2
#endif // CAFFE2_OPERATORS_INT8_FLATTEN_OP_H_
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