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Raise error for unknown parameters in class ModelConfig(BaseModel) #196

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Raise error for unknown parameters in class ModelConfig(BaseModel) #196

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7df0a05
Update config.py
Ahmed-Samir11 May 4, 2025
a676f06
refactor: Update deprecated methods and use base class for inheritance
nok May 26, 2025
69a3565
Merge pull request #1 from nok/patch-1
Ahmed-Samir11 May 26, 2025
8c0abcf
Merge branch 'develop' into patch-1
Ahmed-Samir11 Sep 23, 2025
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37 changes: 32 additions & 5 deletions rfdetr/config.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,12 +5,36 @@
# ------------------------------------------------------------------------


from pydantic import BaseModel
from typing import List, Optional, Literal, Type
from typing import List, Optional, Literal
from pydantic import BaseModel, ConfigDict, model_validator
import torch

DEVICE = "cuda" if torch.cuda.is_available() else "mps" if torch.backends.mps.is_available() else "cpu"

class ModelConfig(BaseModel):

class BaseConfig(BaseModel):
"""
Base configuration class that validates input parameters against the defined model schema.
If any unknown fields are provided, a ValueError is raised listing the unknown and available parameters.
"""
model_config = ConfigDict(extra='ignore')

@model_validator(mode="before")
def catch_typo_kwargs(cls, values):
allowed_params = set(cls.model_json_schema().get('properties').keys())
provided_params = set(values)
unknown_params = provided_params - allowed_params
if unknown_params:
unknown_params_list = ", ".join(f"'{param}'" for param in sorted(unknown_params))
allowed_params_list = ", ".join(sorted(allowed_params))
raise ValueError(
f"Unknown parameter(s): {unknown_params_list}. "
f"Available parameter(s): {allowed_params_list}."
)
return values


class ModelConfig(BaseConfig):
encoder: Literal["dinov2_windowed_small", "dinov2_windowed_base"]
out_feature_indexes: List[int]
dec_layers: int
Expand Down Expand Up @@ -78,6 +102,7 @@ class RFDETRNanoConfig(RFDETRBaseConfig):
positional_encoding_size: int = 24
pretrain_weights: Optional[str] = "rf-detr-nano.pth"


class RFDETRSmallConfig(RFDETRBaseConfig):
"""
The configuration for an RF-DETR Small model.
Expand All @@ -90,6 +115,7 @@ class RFDETRSmallConfig(RFDETRBaseConfig):
positional_encoding_size: int = 32
pretrain_weights: Optional[str] = "rf-detr-small.pth"


class RFDETRMediumConfig(RFDETRBaseConfig):
"""
The configuration for an RF-DETR Medium model.
Expand All @@ -102,7 +128,8 @@ class RFDETRMediumConfig(RFDETRBaseConfig):
positional_encoding_size: int = 36
pretrain_weights: Optional[str] = "rf-detr-medium.pth"

class TrainConfig(BaseModel):

class TrainConfig(BaseConfig):
lr: float = 1e-4
lr_encoder: float = 1.5e-4
batch_size: int = 4
Expand Down Expand Up @@ -139,4 +166,4 @@ class TrainConfig(BaseModel):
project: Optional[str] = None
run: Optional[str] = None
class_names: List[str] = None
run_test: bool = True
run_test: bool = True