- match:
    class: ktransformers.models.modeling_mixtral.MixtralRotaryEmbedding
  replace:
    class: ktransformers.operators.RoPE.RotaryEmbedding
    kwargs:
      generate_device: "cuda"
      prefill_device: "cuda"
- match:
    name: "^model\\.layers\\..*$"
    class: torch.nn.Linear  # only match modules matching name and class simultaneously
  replace:
    class: ktransformers.operators.linear.KTransformersLinear  # optimized Kernel on quantized data types
    kwargs:
      generate_device: "cuda"
      prefill_device: "cuda"
      generate_op: "KLinearMarlin"
      prefill_op: "KLinearTorch"
- match:
    name: "^lm_head"
    class: torch.nn.Linear
  replace:
    class: ktransformers.operators.linear.KTransformersLinear
    kwargs:
      generate_device: "cuda"
      prefill_device: "cuda"
      generate_op: "KLinearMarlin"
      prefill_op: "KLinearTorch"
- match:
    name: "^model\\.layers\\..*\\.block_sparse_moe$"
    class: ktransformers.models.modeling_mixtral.MixtralSparseMoeBlock
  replace: 
    class: ktransformers.operators.experts.KMistralSparseMoEBlock
- match:
    name: "^model\\.layers\\..*\\.block_sparse_moe\\.experts$"
  replace: 
    class: ktransformers.operators.experts.KTransformersExperts
    kwargs:
      prefill_device: "cuda"
      prefill_op: "KExpertsTorch"
      generate_device: "cpu"
      generate_op:  "KExpertsCPU"
      out_device: "cuda"
  recursive: False # don't recursively inject submodules of this module

- match:
    name: "^model.embed_tokens"
  replace:
    class: "default"
    kwargs:
        generate_device: "cpu"
        prefill_device: "cpu"

- match:
    name: "^model\\.layers\\..*\\."
  replace:
    class: "default"
    kwargs:
      generate_device: "cuda"
      prefill_device: "cuda"