signal/tensorflow_core/kernels/stacker_kernel.cc

/* Copyright 2023 The TensorFlow Authors. All Rights Reserved.

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

    http://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.
==============================================================================*/

#include "signal/src/circular_buffer.h"
#include "tensorflow/core/framework/op_kernel.h"

namespace tensorflow {
namespace signal {

class StackerOp : public tensorflow::OpKernel {
 public:
  explicit StackerOp(tensorflow::OpKernelConstruction* context)
      : tensorflow::OpKernel(context) {
    OP_REQUIRES_OK(context, context->GetAttr("num_channels", &num_channels_));
    OP_REQUIRES_OK(context, context->GetAttr("stacker_left_context",
                                             &stacker_left_context_));
    OP_REQUIRES_OK(context, context->GetAttr("stacker_right_context",
                                             &stacker_right_context_));
    OP_REQUIRES_OK(context, context->GetAttr("stacker_step", &stacker_step_));
    buffer_size_ =
        num_channels_ * (stacker_left_context_ + stacker_right_context_ + 1);
    step_size_ = num_channels_ * stacker_step_;
    stacker_has_first_frame_ = false;

    size_t state_size =
        tflite::tflm_signal::CircularBufferGetNeededMemory(buffer_size_);
    OP_REQUIRES_OK(context,
                   context->allocate_temp(
                       DT_INT8, TensorShape({static_cast<int32_t>(state_size)}),
                       &state_tensor_));
    state_ = state_tensor_.flat<int8_t>().data();
    circular_buffer = tflite::tflm_signal::CircularBufferInit(
        buffer_size_, state_, state_size);
  }

  void Compute(tensorflow::OpKernelContext* context) override {
    const tensorflow::Tensor& input_tensor = context->input(0);
    const int16_t* input = input_tensor.flat<int16_t>().data();

    tflite::tflm_signal::CircularBufferWrite(circular_buffer, input,
                                             num_channels_);

    // The first frame is replicated an extra left_context times to pad.
    if (stacker_has_first_frame_ == false) {
      tflite::tflm_signal::CircularBufferExtend(circular_buffer, num_channels_,
                                                stacker_left_context_);
      stacker_has_first_frame_ = true;
    }

    tensorflow::Tensor* output_tensor = nullptr;
    tensorflow::Tensor* output_valid_tensor = nullptr;

    OP_REQUIRES_OK(
        context, context->allocate_output(
                     0, {static_cast<int32_t>(buffer_size_)}, &output_tensor));
    OP_REQUIRES_OK(context,
                   context->allocate_output(1, {}, &output_valid_tensor));

    if (tflite::tflm_signal::CircularBufferAvailable(circular_buffer) >=
        buffer_size_) {
      tflite::tflm_signal::CircularBufferGet(
          circular_buffer, buffer_size_, output_tensor->flat<int16_t>().data());
      tflite::tflm_signal::CircularBufferDiscard(circular_buffer, step_size_);
      *output_valid_tensor->flat<bool>().data() = true;
    } else {
      *output_valid_tensor->flat<bool>().data() = false;
    }
  }

 private:
  int num_channels_;
  int stacker_left_context_;
  int stacker_right_context_;
  int stacker_step_;
  size_t buffer_size_;
  size_t step_size_;
  bool stacker_has_first_frame_;

  int8_t* state_;
  Tensor state_tensor_;
  tflite::tflm_signal::CircularBuffer* circular_buffer;
};

REGISTER_KERNEL_BUILDER(Name("SignalStacker").Device(tensorflow::DEVICE_CPU),
                        StackerOp);

}  // namespace signal
}  // namespace tensorflow