defaults:
  - whisper_baseline
  - _self_
  - override backend: onnxruntime

hydra:
  sweeper:
    params:
      backend.auto_optimization: O1,O2,O3,O4
      backend.auto_quantization: arm64,avx2,avx512,avx512_vnni
      +backend.auto_quantization_config.per_channel: false # blocking decoder quantization
      +backend.auto_quantization_config.operators_to_quantize:
      # when a model is optimized a new set of operators is created in the graph (like fused attention)
        - Gather
        - Transpose
        - EmbedLayerNormalization
        - Attention
        - LSTM
        - ArgMax
        # - Conv # only works for static quantization
        - Gemm
        - MatMul
        - Add
        - Mul
        - Relu
        - Clip
        - LeakyRelu
        - Sigmoid
        - MaxPool
        - GlobalAveragePool
        - Split
        - Pad
        - Reshape
        - Squeeze
        - Unsqueeze
        - Resize
        - AveragePool
        - Concat
        - Softmax
        - Where
        - ConvTranspose
        - InstanceNormalization

experiment_name: whisper_auto_opt(${backend.auto_optimization})+auto_qnt(${backend.auto_quantization})
