general:
  project_name: AED_project

dataset:
  name: esc10
  class_names: ['dog', 'chainsaw', 'crackling_fire', 'helicopter', 'rain', 'crying_baby', 'clock_tick', 'sneezing', 'rooster', 'sea_waves']
  audio_path: /opt/ml/processing/input/datasets/ESC-50/audio
  csv_path: /opt/ml/processing/input/datasets/ESC-50/meta/esc50.csv
  file_extension: .wav
  validation_split: 0.1
  test_split: 0.2
  test_path:

pre_processing:
  min_length: 1
  max_length: 10
  target_rate: 16000
  top_db: 60
  frame_length: 3200
  hop_length: 3200
  trim_last_second: False
  lengthen: 'after'

feature_extraction:
  patch_length: 96
  n_mels: 64
  overlap: 0.25
  n_fft: 512
  hop_length: 160
  window_length: 400
  window: hann
  center: False
  pad_mode: constant
  power: 1.0
  fmin: 125
  fmax: 7500
  norm: None
  htk: True
  to_db: False
  include_last_patch: False

model:
  model_type: { name: yamnet, embedding_size: 256 }
  # Shape of a single patch.
  # Input shape must be [mels, frames]
  input_shape: [64, 96]
  expand_last_dim: True
  multi_label: False
  model_path: /opt/ml/processing/input/model/model.tar.gz

quantization:
  quantize: True
  evaluate: True
  quantizer: TFlite_converter
  quantization_type: PTQ
  quantization_input_type: int8
  quantization_output_type: float
  export_dir: quantized_models

stm32ai:
  optimization: balanced
  serie: STM32U5
  IDE: GCC
  footprints_on_target: STM32H747I-DISCO
  path_to_stm32ai: C:\Users\martinlu\work\Xcubeai-7.3.0\windows\stm32ai.exe

mlflow:
  uri: ./mlruns

hydra:
  run:
    dir: /opt/ml/processing/outputs/build