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operators/tokenizer/blingfire_sentencebreaker.cc

95lines · modecode

1// Copyright (c) Microsoft Corporation. All rights reserved.
2// Licensed under the MIT License.
3
4#include "blingfire_sentencebreaker.hpp"
5#include "string_tensor.h"
6#include <vector>
7#include <locale>
8#include <codecvt>
9#include <algorithm>
10#include <memory>
11
12KernelBlingFireSentenceBreaker::KernelBlingFireSentenceBreaker(OrtApi api, const OrtKernelInfo* info) : BaseKernel(api, info), max_sentence(-1) {
13 model_data_ = ort_.KernelInfoGetAttribute<std::string>(info, "model");
14 if (model_data_.empty()) {
15 ORT_CXX_API_THROW("vocabulary shouldn't be empty.", ORT_INVALID_ARGUMENT);
16 }
17
18 void* model_ptr = SetModel(reinterpret_cast<unsigned char*>(model_data_.data()), model_data_.size());
19
20 if (model_ptr == nullptr) {
21 ORT_CXX_API_THROW("Invalid model", ORT_INVALID_ARGUMENT);
22 }
23
24 model_ = std::shared_ptr<void>(model_ptr, FreeModel);
25
26 if (HasAttribute("max_sentence")) {
27 max_sentence = ort_.KernelInfoGetAttribute<int64_t>(info, "max_sentence");
28 }
29}
30
31void KernelBlingFireSentenceBreaker::Compute(OrtKernelContext* context) {
32 // Setup inputs
33 const OrtValue* input = ort_.KernelContext_GetInput(context, 0);
34 OrtTensorDimensions dimensions(ort_, input);
35
36 // TODO: fix this scalar check.
37 if (dimensions.Size() != 1 && dimensions[0] != 1) {
38 ORT_CXX_API_THROW("We only support string scalar.", ORT_INVALID_ARGUMENT);
39 }
40
41 std::vector<std::string> input_data;
42 GetTensorMutableDataString(api_, ort_, context, input, input_data);
43
44 std::string& input_string = input_data[0];
45 int max_length = 2 * input_string.size() + 1;
46 std::unique_ptr<char[]> output_str = std::make_unique<char[]>(max_length);
47
48 int output_length = TextToSentencesWithOffsetsWithModel(input_string.data(), input_string.size(), output_str.get(), nullptr, nullptr, max_length, model_.get());
49 if (output_length < 0) {
50 ORT_CXX_API_THROW(MakeString("splitting input:\"", input_string, "\" failed"), ORT_INVALID_ARGUMENT);
51 }
52
53 // inline split output_str by newline '\n'
54 std::vector<char*> output_sentences;
55 bool head_flag = true;
56 for (int i = 0; i < output_length; i++) {
57 if (head_flag) {
58 output_sentences.push_back(&output_str[i]);
59 head_flag = false;
60 }
61
62 if (output_str[i] == '\n') {
63 head_flag = true;
64 output_str[i] = '\0';
65 }
66 }
67
68 std::vector<int64_t> output_dimensions(1);
69 output_dimensions[0] = output_sentences.size();
70
71 OrtValue* output = ort_.KernelContext_GetOutput(context, 0, output_dimensions.data(), output_dimensions.size());
72 Ort::ThrowOnError(api_, api_.FillStringTensor(output, output_sentences.data(), output_sentences.size()));
73}
74
75void* CustomOpBlingFireSentenceBreaker::CreateKernel(OrtApi api, const OrtKernelInfo* info) const {
76 return new KernelBlingFireSentenceBreaker(api, info);
77};
78
79const char* CustomOpBlingFireSentenceBreaker::GetName() const { return "BlingFireSentenceBreaker"; };
80
81size_t CustomOpBlingFireSentenceBreaker::GetInputTypeCount() const {
82 return 1;
83};
84
85ONNXTensorElementDataType CustomOpBlingFireSentenceBreaker::GetInputType(size_t /*index*/) const {
86 return ONNX_TENSOR_ELEMENT_DATA_TYPE_STRING;
87};
88
89size_t CustomOpBlingFireSentenceBreaker::GetOutputTypeCount() const {
90 return 1;
91};
92
93ONNXTensorElementDataType CustomOpBlingFireSentenceBreaker::GetOutputType(size_t /*index*/) const {
94 return ONNX_TENSOR_ELEMENT_DATA_TYPE_STRING;
95};
96