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From: "coderabbitai[bot]"
 <136622811+coderabbitai[bot]@users.noreply.github.com>
Date: Sun, 30 Nov 2025 18:29:28 +0000
Subject: [PATCH] =?UTF-8?q?=F0=9F=93=9D=20Add=20docstrings=20to=20`feat/qw?=
 =?UTF-8?q?en3-vl-liger-integration`?=
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Docstrings generation was requested by @thad0ctor.

* https://github.com/axolotl-ai-cloud/axolotl/pull/3285#issuecomment-3593043121

The following files were modified:

* `src/axolotl/integrations/liger/plugin.py`
---
 src/axolotl/integrations/liger/plugin.py | 41 +++++++++++++++++++++++-
 1 file changed, 40 insertions(+), 1 deletion(-)

diff --git a/src/axolotl/integrations/liger/plugin.py b/src/axolotl/integrations/liger/plugin.py
index ac796c2c9..27dbdf9d4 100644
--- a/src/axolotl/integrations/liger/plugin.py
+++ b/src/axolotl/integrations/liger/plugin.py
@@ -23,6 +23,29 @@ class LigerPlugin(BasePlugin):
         return "axolotl.integrations.liger.LigerArgs"
 
     def pre_model_load(self, cfg):
+        """
+        Apply LIGER runtime patches and integrations according to the provided configuration.
+        
+        This hook inspects `cfg` and conditionally applies LIGER kernel patches, replacements, and model-specific integrations (rotary embeddings, normalization, GLU variants, and cross-entropy implementations) for the model type indicated by `cfg.model_config_type`. Behavior is driven entirely by the various `cfg.liger_*` flags; the method logs actions and warnings when support is experimental or unavailable.
+        
+        Parameters:
+            cfg: Configuration object containing LIGER-related flags and model identification. Expected attributes include:
+                - model_config_type (str): Target model config type to determine which patches to apply.
+                - base_model (str): Base model identifier used when probing model modules (used for some model types).
+                - trust_remote_code (bool|None): Passed when loading remote model code (used for some model types).
+                - torch_compile (bool): If true, disable torch.compile optimizations for certain LIGER kernels.
+                - liger_cross_entropy (bool)
+                - liger_fused_linear_cross_entropy (bool)
+                - liger_use_token_scaling (bool)
+                - liger_rope (bool)
+                - liger_rms_norm (bool)
+                - liger_layer_norm (bool)
+                - liger_glu_activation (str|bool): Name or flag for GLU/SwiGLU activation selection.
+                (Other LIGER flags referenced by the code may also be consulted.)
+        
+        Raises:
+            ValueError: If both `cfg.liger_cross_entropy` and `cfg.liger_fused_linear_cross_entropy` are enabled.
+        """
         if cfg.torch_compile:
             # torch compile will unnecessarily attempt to optimize the triton kernel unless explicitly disabled
             import liger_kernel.ops.fused_linear_cross_entropy
@@ -168,6 +191,22 @@ class LigerPlugin(BasePlugin):
                 rms_norm=cfg.liger_rms_norm,
                 layer_norm=cfg.liger_layer_norm,
             )
+        elif cfg.model_config_type == "qwen3_vl":
+            """
+            Apply Liger kernels for Qwen3 Vision-Language models.
+            
+            Note: The parameter 'swiglu' is used instead of 'glu_activation' to match
+            the Liger kernel API for vision-language models.
+            """
+            from liger_kernel.transformers import apply_liger_kernel_to_qwen3_vl
+
+            apply_liger_kernel_to_qwen3_vl(
+                rope=cfg.liger_rope,
+                cross_entropy=cfg.liger_cross_entropy,
+                fused_linear_cross_entropy=cfg.liger_fused_linear_cross_entropy,
+                rms_norm=cfg.liger_rms_norm,
+                swiglu=cfg.liger_glu_activation,  # Note: qwen3_vl uses swiglu parameter name
+            )
         elif cfg.model_config_type == "qwen3_moe":
             from axolotl.integrations.liger.models.qwen3_moe import (
                 apply_liger_kernel_to_qwen3_moe,
@@ -206,4 +245,4 @@ class LigerPlugin(BasePlugin):
         else:
             LOG.warning(
                 f"Unsupported model config type: {cfg.model_config_type}. Liger not applied."
-            )
+            )
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