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// Copyright 2020 Google LLC
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
// Shared methods for the text and token encoders.
#ifndef LIBTEXTCLASSIFIER_UTILS_TFLITE_ENCODER_COMMON_H_
#define LIBTEXTCLASSIFIER_UTILS_TFLITE_ENCODER_COMMON_H_
#include <memory>
#include <vector>
#include "tensorflow/lite/model.h"
namespace libtextclassifier3 {
// Input rank for the encoder ops is 2, because the first dimension is
// always considered to be for batching, and during inference is always set to
// 1, and the second dimension indexes the input values (texts or token
// lengths).
constexpr const int kEncoderInputRank = 2;
constexpr const int kEncoderBatchSize = 1;
// Creates a TensorFlow Lite array from an initializer list.
TfLiteIntArray* CreateIntArray(const std::initializer_list<int>& values);
// Copies values associated with the input to the output.
// Typically we have attribute values associated with each item in the input,
// e.g. user id per message in the conversation.
// This aligns and replicates the attribute values with the encoded input, e.g.
// replicates the same user id per token or sentence piece of the input.
// As the input for the whole conversation is concatenated and (potentially)
// trimmed, `encoding_end_offset` indicates where each item ends and
// `start_offset` indicates how many elements at the beginning were dropped.
TfLiteStatus CopyValuesToTensorAndPadOrTruncate(
const TfLiteTensor& in, const std::vector<int>& encoding_end_offsets,
int start_offset, TfLiteContext* context, TfLiteTensor* out);
// Resizes an output tensor to shape {kBatchSize, max_output_length}.
TfLiteStatus ResizeOutputTensor(const int max_output_length,
TfLiteTensor* tensor, TfLiteContext* context);
// Copy a slice of data to output.
// If the size of the data is smaller than `max_output_length` then the output
// is padded with `padding_value`.
// If the size of the data is larger than `max_output_length` then entries at
// the beginning a dropped to fit into the limit.
int CopyDataToTensorAndPadOrTruncate(const int32_t max_output_length,
const std::vector<int32_t>& data,
const int32_t padding_value,
TfLiteTensor* output_tensor);
} // namespace libtextclassifier3
#endif // LIBTEXTCLASSIFIER_UTILS_TFLITE_ENCODER_COMMON_H_