mirror of
https://github.com/kvcache-ai/ktransformers.git
synced 2025-09-03 19:20:04 +00:00
91 lines
No EOL
3 KiB
YAML
91 lines
No EOL
3 KiB
YAML
- match:
|
|
class: ktransformers.models.modeling_deepseek_v3.DeepseekV3RotaryEmbedding
|
|
replace:
|
|
class: ktransformers.operators.RoPE.YarnRotaryEmbeddingV3
|
|
kwargs:
|
|
generate_device: "cuda"
|
|
prefill_device: "cuda"
|
|
- match:
|
|
name: "^model\\.layers\\.(?!.*self_attn\\.kv_b_proj).*$" # regular expression
|
|
class: torch.nn.Linear # only match modules matching name and class simultaneously
|
|
replace:
|
|
class: ktransformers.operators.linear.KTransformersLinear # optimized Kernel on quantized data types
|
|
kwargs:
|
|
generate_device: "cuda"
|
|
prefill_device: "cuda"
|
|
generate_op: "KLinearFP8"
|
|
prefill_op: "KLinearTorch"
|
|
- match:
|
|
name: "^model\\.layers\\..*\\.mlp$"
|
|
class: ktransformers.models.modeling_deepseek_v3.DeepseekV3MoE
|
|
replace:
|
|
class: ktransformers.operators.experts.KDeepseekV3MoEV2 # mlp module with custom forward function
|
|
kwargs:
|
|
generate_device: "cuda"
|
|
prefill_device: "cuda"
|
|
- match:
|
|
class: ktransformers.models.modeling_deepseek_v3.MoEGate
|
|
replace:
|
|
class: ktransformers.operators.gate.KMoEGate
|
|
kwargs:
|
|
generate_device: "cuda:0"
|
|
prefill_device: "cuda:0"
|
|
- match:
|
|
name: "^model\\.layers\\..*\\.mlp\\.experts$"
|
|
replace:
|
|
class: ktransformers.operators.experts.KTransformersExpertsV2 # custom MoE Kernel with expert paralleism
|
|
kwargs:
|
|
prefill_device: "cuda"
|
|
prefill_op: "KExpertsTorch"
|
|
generate_device: "cpu"
|
|
generate_op: "KExpertsCPU"
|
|
out_device: "cuda"
|
|
backend: "llamafile"
|
|
recursive: False # don't recursively inject submodules of this module
|
|
- match:
|
|
name: "^model\\.layers\\..*\\.self_attn$"
|
|
replace:
|
|
class: ktransformers.operators.balance_serve_attention.flashinfer_attn # optimized MLA implementation
|
|
kwargs:
|
|
generate_device: "cuda"
|
|
prefill_device: "cuda"
|
|
- match:
|
|
name: "^model$"
|
|
replace:
|
|
class: "ktransformers.operators.models.KDeepseekV2Model"
|
|
kwargs:
|
|
per_layer_prefill_intput_threshold: 0 # 0 is close layer wise prefill
|
|
- match:
|
|
name: "^model.embed_tokens"
|
|
replace:
|
|
class: "default"
|
|
kwargs:
|
|
generate_device: "cpu"
|
|
prefill_device: "cpu"
|
|
|
|
- match:
|
|
class: ktransformers.models.modeling_deepseek_v3.DeepseekV3RMSNorm
|
|
replace:
|
|
class: ktransformers.operators.layernorm.RMSNorm
|
|
kwargs:
|
|
generate_device: "cuda"
|
|
prefill_device: "cuda"
|
|
|
|
- match:
|
|
class: ktransformers.models.modeling_deepseek_v3.DeepseekV3MLP
|
|
replace:
|
|
class: ktransformers.operators.mlp.kDeepseekV3MLP
|
|
kwargs:
|
|
generate_device: "cuda"
|
|
prefill_device: "cuda"
|
|
|
|
- match:
|
|
name: "^lm_head$" # regular expression
|
|
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: "VLinearMarlin"
|
|
prefill_op: "KLinearTorch" |