added checks for layers to transforms and layer pattern in lora

src/peft/tuners/adalora/config.py

@@ -68,10 +68,13 @@ def __post_init__(self):
         if isinstance(self.target_modules, str) and self.layers_to_transform is not None:
             raise ValueError("`layers_to_transform` cannot be used when `target_modules` is a str.")
 
-        # if target_modules is a regex expression, then layers_pattern should be None
-        if isinstance(self.target_modules, str) and self.layers_pattern is not None:
-            raise ValueError("`layers_pattern` cannot be used when `target_modules` is a str.")
+        # check for layers_to_transform and layers_pattern
+        if (self.layers_pattern is not None) and (self.layers_to_transform is None):
+            raise ValueError("When `layers_pattern` is specified, `layers_to_transform` must also be specified. ")
 
+        # check for layers_to_transform and layers_pattern
+        if (self.layers_to_transform is not None) and (self.layers_pattern is None):
+            raise ValueError("When `layers_to_transform` is specified, `layers_pattern` must also be specified.")
         # Check if 'r' has been set to a non-default value
         if self.r != 8:  # 8 is the default value for 'r' in LoraConfig
             warnings.warn(

src/peft/tuners/boft/config.py

@@ -144,6 +144,9 @@ def __post_init__(self):
         self.exclude_modules = (
             set(self.exclude_modules) if isinstance(self.exclude_modules, list) else self.exclude_modules
         )
+        # check for layers_to_transform and layers_pattern
+        if (self.layers_pattern is not None) and (self.layers_to_transform is None):
+            raise ValueError("When `layers_pattern` is specified, `layers_to_transform` must also be specified. ")
         if self.boft_block_size == 0 and self.boft_block_num == 0:
             raise ValueError(
                 f"Either `boft_block_size` or `boft_block_num` must be non-zero. Currently, boft_block_size = {self.boft_block_size} and boft_block_num = {self.boft_block_num}."

src/peft/tuners/fourierft/config.py

@@ -197,3 +197,6 @@ def __post_init__(self):
         # if target_modules is a regex expression, then layers_pattern should be None
         if isinstance(self.target_modules, str) and self.layers_pattern is not None:
             raise ValueError("`layers_pattern` cannot be used when `target_modules` is a str.")
+        # check for layers_to_transform and layers_pattern
+        if (self.layers_pattern is not None) and (self.layers_to_transform is None):
+            raise ValueError("When `layers_pattern` is specified, `layers_to_transform` must also be specified. ")

src/peft/tuners/hra/config.py

@@ -127,3 +127,7 @@ def __post_init__(self):
         # if target_modules is a regex expression, then layers_pattern should be None
         if isinstance(self.target_modules, str) and self.layers_pattern is not None:
             raise ValueError("`layers_pattern` cannot be used when `target_modules` is a str.")
+
+        # check for layers_to_transform and layers_pattern
+        if (self.layers_pattern is not None) and (self.layers_to_transform is None):
+            raise ValueError("When `layers_pattern` is specified, `layers_to_transform` must also be specified. ")

src/peft/tuners/loha/config.py

@@ -131,3 +131,6 @@ def __post_init__(self):
         self.exclude_modules = (
             set(self.exclude_modules) if isinstance(self.exclude_modules, list) else self.exclude_modules
         )
+        # check for layers_to_transform and layers_pattern
+        if (self.layers_pattern is not None) and (self.layers_to_transform is None):
+            raise ValueError("When `layers_pattern` is specified, `layers_to_transform` must also be specified. ")

src/peft/tuners/lokr/config.py

@@ -140,3 +140,6 @@ def __post_init__(self):
         self.exclude_modules = (
             set(self.exclude_modules) if isinstance(self.exclude_modules, list) else self.exclude_modules
         )
+        # check for layers_to_transform and layers_pattern
+        if (self.layers_pattern is not None) and (self.layers_to_transform is None):
+            raise ValueError("When `layers_pattern` is specified, `layers_to_transform` must also be specified. ")

src/peft/tuners/lora/config.py

@@ -338,6 +338,7 @@ def __post_init__(self):
         self.exclude_modules = (
             set(self.exclude_modules) if isinstance(self.exclude_modules, list) else self.exclude_modules
         )
+
         # if target_modules is a regex expression, then layers_to_transform should be None
         if isinstance(self.target_modules, str) and self.layers_to_transform is not None:
             raise ValueError("`layers_to_transform` cannot be used when `target_modules` is a str.")
@@ -346,6 +347,10 @@ def __post_init__(self):
         if isinstance(self.target_modules, str) and self.layers_pattern is not None:
             raise ValueError("`layers_pattern` cannot be used when `target_modules` is a str.")
 
+        # check for layers_to_transform and layers_pattern
+        if (self.layers_pattern is not None) and (self.layers_to_transform is None):
+            raise ValueError("When `layers_pattern` is specified, `layers_to_transform` must also be specified. ")
+
         if self.use_dora and self.megatron_config:
             raise ValueError("DoRA does not support megatron_core, please set `use_dora=False`.")
 

src/peft/tuners/oft/config.py

@@ -174,6 +174,9 @@ def __post_init__(self):
         self.exclude_modules = (
             set(self.exclude_modules) if isinstance(self.exclude_modules, list) else self.exclude_modules
         )
+        # check for layers_to_transform and layers_pattern
+        if (self.layers_pattern is not None) and (self.layers_to_transform is None):
+            raise ValueError("When `layers_pattern` is specified, `layers_to_transform` must also be specified. ")
         if self.r == 0 and self.oft_block_size == 0:
             raise ValueError(
                 f"Either `r` or `oft_block_size` must be non-zero. Currently, r = {self.r} and oft_block_size = {self.oft_block_size}."

src/peft/tuners/vblora/config.py

@@ -188,3 +188,6 @@ def __post_init__(self):
         self.exclude_modules = (
             set(self.exclude_modules) if isinstance(self.exclude_modules, list) else self.exclude_modules
         )
+        # check for layers_to_transform and layers_pattern
+        if (self.layers_pattern is not None) and (self.layers_to_transform is None):
+            raise ValueError("When `layers_pattern` is specified, `layers_to_transform` must also be specified. ")

src/peft/tuners/vera/config.py

@@ -148,7 +148,9 @@ def __post_init__(self):
         self.target_modules = (
             set(self.target_modules) if isinstance(self.target_modules, list) else self.target_modules
         )
-
+        # check for layers_to_transform and layers_pattern
+        if (self.layers_pattern is not None) and (self.layers_to_transform is None):
+            raise ValueError("When `layers_pattern` is specified, `layers_to_transform` must also be specified. ")
         if not self.save_projection:
             warnings.warn(
                 "Specified to not save vera_A and vera_B within the state dictionary, instead they will be restored "

tests/test_config.py

@@ -351,3 +351,30 @@ def test_from_pretrained_sanity_check(self, config_class, tmp_path):
         msg = f"The config that is trying to be loaded is not a valid {config_class.__name__} config"
         with pytest.raises(TypeError, match=msg):
             config_class.from_pretrained(tmp_path)
+
+    def test_lora_config_layers_to_transform_validation(self):
+        """Test that specifying layers_pattern without layers_to_transform raises an error"""
+        with pytest.raises(
+            ValueError, match="When `layers_pattern` is specified, `layers_to_transform` must also be specified."
+        ):
+            LoraConfig(r=8, lora_alpha=16, target_modules=["query", "value"], layers_pattern="model.layers")
+
+        # Test that specifying both layers_to_transform and layers_pattern works fine
+        config = LoraConfig(
+            r=8,
+            lora_alpha=16,
+            target_modules=["query", "value"],
+            layers_to_transform=[0, 1, 2],
+            layers_pattern="model.layers",
+        )
+        assert config.layers_to_transform == [0, 1, 2]
+        assert config.layers_pattern == "model.layers"
+
+        # Test that not specifying either works fine
+        config = LoraConfig(
+            r=8,
+            lora_alpha=16,
+            target_modules=["query", "value"],
+        )
+        assert config.layers_to_transform is None
+        assert config.layers_pattern is None