auto-enable lora kernels where possible (#2589)
* auto-enable lora kernels where possible * test * revert change to example yaml * naming * remove print * slight logic change
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@@ -1315,6 +1315,54 @@ class AxolotlConfigWCapabilities(AxolotlInputConfig):
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)
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return data
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@model_validator(mode="before")
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@classmethod
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def check_auto_enable_lora_kernels(cls, data):
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# Only proceed if using LoRA or QLoRA adapter
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if data.get("adapter") in ["lora", "qlora"]:
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# Skip if already set, using unsloth optimizations, or using 8-bit
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unsloth_fields = ["unsloth_lora_mlp", "unsloth_lora_qkv", "unsloth_lora_o"]
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kernel_fields = ["lora_mlp_kernel", "lora_qkv_kernel", "lora_o_kernel"]
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if (
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any(data.get(k) is not None for k in kernel_fields)
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or any(data.get(k) for k in unsloth_fields)
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or data.get("adapter") == "lora"
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and data.get("load_in_8bit")
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):
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return data
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# Check multi-GPU compatibility
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capabilities = data.get("capabilities")
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is_multi_gpu = capabilities and capabilities.get("n_gpu", 0) > 1
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is_fsdp = data.get("fsdp") is not None
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is_fsdp2 = (
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data.get("fsdp_config") is not None
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and str(data.get("fsdp_config").get("fsdp_version")) == "2"
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)
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if (
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not is_multi_gpu
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or (is_multi_gpu and not is_fsdp)
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or (is_multi_gpu and is_fsdp2)
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):
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# Auto-enable kernels if not explicitly set by user
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if data.get("lora_mlp_kernel") is None:
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data["lora_mlp_kernel"] = True
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if data.get("lora_qkv_kernel") is None:
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data["lora_qkv_kernel"] = True
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if data.get("lora_o_kernel") is None:
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data["lora_o_kernel"] = True
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LOG.warning(
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"Auto-enabling LoRA kernel optimizations for faster training. "
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+ "Please explicitly set `lora_*_kernel` config values to `false` to disable. "
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+ "See https://docs.axolotl.ai/docs/lora_optims.html for more info."
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)
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return data
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@model_validator(mode="before")
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@classmethod
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def check_adopt_torch_version(cls, data):
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