fix: pydantic warnings about model_ namespace

Modalities · Aug 2, 2024 · a29fe8c · a29fe8c
1 parent 65bf611
commit a29fe8c
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Showing 3 changed files with 19 additions and 3 deletions.
diff --git a/src/modalities/config/config.py b/src/modalities/config/config.py
@@ -5,7 +5,7 @@
 
 import torch
 from omegaconf import OmegaConf
-from pydantic import BaseModel, Field, FilePath, PositiveInt, field_validator, model_validator
+from pydantic import BaseModel, ConfigDict, Field, FilePath, PositiveInt, field_validator, model_validator
 from torch.distributed.fsdp import ShardingStrategy
 from transformers import GPT2TokenizerFast
 from transformers.models.llama.tokenization_llama_fast import LlamaTokenizerFast
@@ -234,6 +234,10 @@ class WeightInitializedModelConfig(BaseModel):
     model: PydanticPytorchModuleType
     model_initializer: PydanticModelInitializationIFType
 
+    # avoid warning about protected namespace 'model_', see
+    # https://docs.pydantic.dev/2.7/api/config/#pydantic.config.ConfigDict.protected_namespaces
+    model_config = ConfigDict(protected_namespaces=())
+
 
 class PreTrainedHFTokenizerConfig(BaseModel):
     pretrained_model_name_or_path: str

diff --git a/src/modalities/config/instantiation_models.py b/src/modalities/config/instantiation_models.py
@@ -2,7 +2,7 @@
 from pathlib import Path
 from typing import Annotated, Dict, List, Optional
 
-from pydantic import BaseModel, Field, FilePath, field_validator
+from pydantic import BaseModel, ConfigDict, Field, FilePath, field_validator
 
 from modalities.config.pydanctic_if_types import (
     PydanticCheckpointSavingIFType,
@@ -82,6 +82,10 @@ class TextGenerationSettings(BaseModel):
         device: PydanticPytorchDeviceType
         referencing_keys: Dict[str, str]
 
+        # avoid warning about protected namespace 'model_', see
+        # https://docs.pydantic.dev/2.7/api/config/#pydantic.config.ConfigDict.protected_namespaces
+        model_config = ConfigDict(protected_namespaces=())
+
         @field_validator("device", mode="before")
         def parse_device(cls, device) -> PydanticPytorchDeviceType:
             return parse_torch_device(device)

diff --git a/src/modalities/nn/model_initialization/composed_initialization.py b/src/modalities/nn/model_initialization/composed_initialization.py
@@ -1,7 +1,7 @@
 from typing import List, Optional
 
 import torch.nn as nn
-from pydantic import BaseModel, Field, model_validator
+from pydantic import BaseModel, ConfigDict, Field, model_validator
 from typing_extensions import Annotated
 
 from modalities.config.pydanctic_if_types import PydanticModelInitializationIFType
@@ -17,6 +17,10 @@
 class ModelInitializerWrapperConfig(BaseModel):
     model_initializers: List[PydanticModelInitializationIFType]
 
+    # avoid warning about protected namespace 'model_', see
+    # https://docs.pydantic.dev/2.7/api/config/#pydantic.config.ConfigDict.protected_namespaces
+    model_config = ConfigDict(protected_namespaces=())
+
 
 class ComposedModelInitializationConfig(BaseModel):
     model_type: SupportWeightInitModels
@@ -27,6 +31,10 @@ class ComposedModelInitializationConfig(BaseModel):
     hidden_dim: Optional[Annotated[int, Field(strict=True, gt=0)]] = None
     num_layers: Optional[Annotated[int, Field(strict=True, gt=0)]] = None
 
+    # avoid warning about protected namespace 'model_', see
+    # https://docs.pydantic.dev/2.7/api/config/#pydantic.config.ConfigDict.protected_namespaces
+    model_config = ConfigDict(protected_namespaces=())
+
     @model_validator(mode="after")
     def _check_values(self):
         # in case of initialization with "auto", we need to specify the hidden_dim