definition.yaml

benchmark:
  DCASE 2020 Task 2 Slide rail:
    AUC: 0.968
description: This is a fully quantized version (asymmetrical int8) of the MicroNet
  Large model developed by Arm, from the MicroNets paper. It is trained on the 'slide
  rail' task from http://dcase.community/challenge2020/task-unsupervised-detection-of-anomalous-sounds.
license:
- Apache-2.0
network:
  file_size_bytes: 442000
  filename: ad_large_int8.tflite
  framework: TensorFlow Lite
  hash:
    algorithm: sha1
    value: 0b7e7776c79fac28c186b2ba00314a05b7faadbf
  provenance: https://arxiv.org/pdf/2010.11267.pdf
network_parameters:
  input_nodes:
  - description: Input is 64 steps of a Log Mel Spectrogram using 64 mels resized
      to 32x32.
    example_input:
      path: models/anomaly_detection/micronet_large/tflite_int8/testing_input/input
    name: input
    shape:
    - 1
    - 32
    - 32
    - 1
  output_nodes:
  - description: Raw logits corresponding to different machine IDs being anomalous
    name: Identity
    shape:
    - 1
    - 8
    test_output_path: models/anomaly_detection/micronet_large/tflite_int8/testing_output/Identity
operators:
  TensorFlow Lite:
  - AVERAGE_POOL_2D
  - CONV_2D
  - DEPTHWISE_CONV_2D
  - RELU6
  - RESHAPE
paper: https://arxiv.org/pdf/2010.11267.pdf