59 lines
1.6 KiB
C++
59 lines
1.6 KiB
C++
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#include "tensorflow/core/framework/op.h"
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#include "tensorflow/core/framework/shape_inference.h"
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#include "tensorflow/core/framework/op_kernel.h"
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#include <twml.h>
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#include "tensorflow_utils.h"
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using namespace tensorflow;
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REGISTER_OP("FeatureId")
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.Attr("feature_names: list(string)")
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.Output("output: int64")
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.SetShapeFn([](::tensorflow::shape_inference::InferenceContext* c) {
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return Status::OK();
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}).Doc(R"doc(
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A tensorflow OP that hashes a list of strings into int64. This is used for feature name hashing.
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Attr
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feature_names: a list of string feature names (list(string)).
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Outputs
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ouput: hashes corresponding to the string feature names (int64).
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)doc");
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class FeatureId : public OpKernel {
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private:
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std::vector<string> input_vector;
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public:
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explicit FeatureId(OpKernelConstruction* context) : OpKernel(context) {
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OP_REQUIRES_OK(context, context->GetAttr("feature_names", &input_vector));
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}
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void Compute(OpKernelContext* context) override {
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// Get size of the input_vector and create TensorShape shape
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const int total_size = static_cast<int>(input_vector.size());
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TensorShape shape = {total_size};
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// Create an output tensor
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Tensor* output_tensor = nullptr;
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OP_REQUIRES_OK(context, context->allocate_output(0, shape,
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&output_tensor));
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auto output_flat = output_tensor->flat<int64>();
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// Transform the input tensor into a int64
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for (int i = 0; i < total_size; i++) {
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output_flat(i) = twml::featureId(input_vector[i]);
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}
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}
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};
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REGISTER_KERNEL_BUILDER(
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Name("FeatureId")
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.Device(DEVICE_CPU),
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FeatureId);
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