Internal MediaPipe Tasks change.
PiperOrigin-RevId: 514002859
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					@ -25,6 +25,7 @@ limitations under the License.
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namespace mediapipe {
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					namespace mediapipe {
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namespace tasks {
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					namespace tasks {
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namespace core {
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					namespace core {
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					// TODO: Use separate builtin op-resolvers.
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MediaPipeBuiltinOpResolver::MediaPipeBuiltinOpResolver() {
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					MediaPipeBuiltinOpResolver::MediaPipeBuiltinOpResolver() {
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  AddCustom("MaxPoolingWithArgmax2D",
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					  AddCustom("MaxPoolingWithArgmax2D",
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            mediapipe::tflite_operations::RegisterMaxPoolingWithArgmax2D());
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					            mediapipe::tflite_operations::RegisterMaxPoolingWithArgmax2D());
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					@ -1,40 +0,0 @@
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/* Copyright 2022 The MediaPipe Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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    http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include "mediapipe/tasks/cc/text/text_embedder/text_embedder_test_utils.h"
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#include "absl/memory/memory.h"
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#include "tensorflow/lite/core/shims/cc/kernels/register.h"
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namespace tflite::ops::custom {
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TfLiteRegistration* Register_SENTENCEPIECE_TOKENIZER();
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TfLiteRegistration* Register_RAGGED_TENSOR_TO_TENSOR();
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}  // namespace tflite::ops::custom
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namespace mediapipe::tasks::text::text_embedder {
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std::unique_ptr<tflite::OpResolver> CreateUSEOpResolver() {
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  auto resolver =
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      absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>();
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  resolver->AddCustom(
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      "TFSentencepieceTokenizeOp",
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      ::tflite::ops::custom::Register_SENTENCEPIECE_TOKENIZER());
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  resolver->AddCustom(
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      "RaggedTensorToTensor",
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      ::tflite::ops::custom::Register_RAGGED_TENSOR_TO_TENSOR());
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  return resolver;
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}
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}  // namespace mediapipe::tasks::text::text_embedder
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					@ -1,32 +0,0 @@
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/* Copyright 2022 The MediaPipe Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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    http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#ifndef MEDIAPIPE_TASKS_CC_TEXT_TEXT_EMBEDDER_TEXT_EMBEDDER_TEST_UTILS_H_
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#define MEDIAPIPE_TASKS_CC_TEXT_TEXT_EMBEDDER_TEXT_EMBEDDER_TEST_UTILS_H_
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#include <memory>
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#include "tensorflow/lite/core/api/op_resolver.h"
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namespace mediapipe::tasks::text::text_embedder {
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// Creates a custom OpResolver containing the additional SENTENCEPIECE_TOKENIZER
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// and RAGGED_TENSOR_TO_TENSOR ops needed by universal sentence encoder-based
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// models.
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std::unique_ptr<tflite::OpResolver> CreateUSEOpResolver();
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}  // namespace mediapipe::tasks::text::text_embedder
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#endif  // MEDIAPIPE_TASKS_CC_TEXT_TEXT_EMBEDDER_TEXT_EMBEDDER_TEST_UTILS_H_
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