the-algorithm/twml/libtwml/src/ops/batch_prediction_response_writer.cpp
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83 lines
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C++

#include "tensorflow/core/framework/op.h"
#include "tensorflow/core/framework/shape_inference.h"
#include "tensorflow/core/framework/op_kernel.h"
#include <twml.h>
#include "tensorflow_utils.h"
using namespace tensorflow;
REGISTER_OP("BatchPredictionResponseWriter")
.Attr("T: {float, double}")
.Input("keys: int64")
.Input("values: T")
.Output("result: uint8")
.SetShapeFn([](::tensorflow::shape_inference::InferenceContext* c) {
return Status::OK();
}).Doc(R"doc(
A tensorflow OP that packages keys and values into a BatchPredictionResponse.
values: input feature value. (float/double)
keys: feature ids from the original BatchPredictionRequest. (int64)
Outputs
bytes: output BatchPredictionRequest serialized using Thrift into a uint8 tensor.
)doc");
template<typename T>
class BatchPredictionResponseWriter : public OpKernel {
public:
explicit BatchPredictionResponseWriter(OpKernelConstruction* context)
: OpKernel(context) {}
void Compute(OpKernelContext* context) override {
const Tensor& keys = context->input(0);
const Tensor& values = context->input(1);
try {
// Ensure the inner dimension matches.
if (values.dim_size(values.dims() - 1) != keys.dim_size(keys.dims() - 1)) {
throw std::runtime_error("The sizes of keys and values need to match");
}
// set inputs as twml::Tensor
const twml::Tensor in_keys_ = TFTensor_to_twml_tensor(keys);
const twml::Tensor in_values_ = TFTensor_to_twml_tensor(values);
// no tensors in this op
const twml::Tensor dummy_dense_keys_;
const std::vector<twml::RawTensor> dummy_dense_values_;
// call constructor BatchPredictionResponse
twml::BatchPredictionResponse tempResult(
in_keys_, in_values_, dummy_dense_keys_, dummy_dense_values_);
// determine the length of the result
int len = tempResult.encodedSize();
TensorShape result_shape = {1, len};
// Create an output tensor, the size is determined by the content of input.
Tensor* result = nullptr;
OP_REQUIRES_OK(context, context->allocate_output(0, result_shape,
&result));
twml::Tensor out_result = TFTensor_to_twml_tensor(*result);
// Call writer of BatchPredictionResponse
tempResult.write(out_result);
} catch(const std::exception &e) {
context->CtxFailureWithWarning(errors::InvalidArgument(e.what()));
}
}
};
#define REGISTER(Type) \
\
REGISTER_KERNEL_BUILDER( \
Name("BatchPredictionResponseWriter") \
.Device(DEVICE_CPU) \
.TypeConstraint<Type>("T"), \
BatchPredictionResponseWriter<Type>); \
REGISTER(float);
REGISTER(double);