Converted many @DataClass assignments to field()s for python 3.11 com…

…patibility

nerfstudio/configs/base_config.py

@@ -17,7 +17,7 @@
 
 from __future__ import annotations
 
-from dataclasses import dataclass
+from dataclasses import dataclass, field
 from pathlib import Path
 from typing import Any, List, Literal, Optional, Tuple, Type
 
@@ -113,7 +113,7 @@ class LoggingConfig(PrintableConfig):
     max_buffer_size: int = 20
     """maximum history size to keep for computing running averages of stats.
      e.g. if 20, averages will be computed over past 20 occurrences."""
-    local_writer: LocalWriterConfig = LocalWriterConfig(enable=True)
+    local_writer: LocalWriterConfig = field(default_factory=lambda: LocalWriterConfig(enable=True))
     """if provided, will print stats locally. if None, will disable printing"""
     profiler: Literal["none", "basic", "pytorch"] = "basic"
     """how to profile the code;

nerfstudio/configs/experiment_config.py

@@ -16,7 +16,7 @@
 
 from __future__ import annotations
 
-from dataclasses import dataclass
+from dataclasses import dataclass, field
 from datetime import datetime
 from pathlib import Path
 from typing import Any, Dict, Literal, Optional
@@ -51,13 +51,13 @@ class ExperimentConfig(InstantiateConfig):
     """Project name."""
     timestamp: str = "{timestamp}"
     """Experiment timestamp."""
-    machine: MachineConfig = MachineConfig()
+    machine: MachineConfig = field(default_factory=lambda: MachineConfig())
     """Machine configuration"""
-    logging: LoggingConfig = LoggingConfig()
+    logging: LoggingConfig = field(default_factory=lambda: LoggingConfig())
     """Logging configuration"""
-    viewer: ViewerConfig = ViewerConfig()
+    viewer: ViewerConfig = field(default_factory=lambda: ViewerConfig())
     """Viewer configuration"""
-    pipeline: VanillaPipelineConfig = VanillaPipelineConfig()
+    pipeline: VanillaPipelineConfig = field(default_factory=lambda: VanillaPipelineConfig())
     """Pipeline configuration"""
     optimizers: Dict[str, Any] = to_immutable_dict(
         {

nerfstudio/data/datamanagers/base_datamanager.py

@@ -317,7 +317,7 @@ class VanillaDataManagerConfig(DataManagerConfig):
 
     _target: Type = field(default_factory=lambda: VanillaDataManager)
     """Target class to instantiate."""
-    dataparser: AnnotatedDataParserUnion = BlenderDataParserConfig()
+    dataparser: AnnotatedDataParserUnion = field(default_factory=lambda: BlenderDataParserConfig())
     """Specifies the dataparser used to unpack the data."""
     train_num_rays_per_batch: int = 1024
     """Number of rays per batch to use per training iteration."""
@@ -345,7 +345,7 @@ class VanillaDataManagerConfig(DataManagerConfig):
     """Size of patch to sample from. If > 1, patch-based sampling will be used."""
     camera_optimizer: Optional[CameraOptimizerConfig] = field(default=None)
     """Deprecated, has been moved to the model config."""
-    pixel_sampler: PixelSamplerConfig = PixelSamplerConfig()
+    pixel_sampler: PixelSamplerConfig = field(default_factory=lambda: PixelSamplerConfig())
     """Specifies the pixel sampler used to sample pixels from images."""
 
     def __post_init__(self):

nerfstudio/data/dataparsers/base_dataparser.py

@@ -57,7 +57,7 @@ class DataparserOutputs:
     """Camera object storing collection of camera information in dataset."""
     alpha_color: Optional[Float[Tensor, "3"]] = None
     """Color of dataset background."""
-    scene_box: SceneBox = SceneBox(aabb=torch.tensor([[-1, -1, -1], [1, 1, 1]]))
+    scene_box: SceneBox = field(default_factory=lambda: SceneBox(aabb=torch.tensor([[-1, -1, -1], [1, 1, 1]])))
     """Scene box of dataset. Used to bound the scene or provide the scene scale depending on model."""
     mask_filenames: Optional[List[Path]] = None
     """Filenames for any masks that are required"""

nerfstudio/models/base_surface_model.py

@@ -79,7 +79,7 @@ class SurfaceModelConfig(ModelConfig):
     """Monocular normal consistency loss multiplier."""
     mono_depth_loss_mult: float = 0.0
     """Monocular depth consistency loss multiplier."""
-    sdf_field: SDFFieldConfig = SDFFieldConfig()
+    sdf_field: SDFFieldConfig = field(default_factory=lambda: SDFFieldConfig())
     """Config for SDF Field"""
     background_model: Literal["grid", "mlp", "none"] = "mlp"
     """background models"""

nerfstudio/models/nerfacto.py

@@ -127,7 +127,7 @@ class NerfactoModelConfig(ModelConfig):
     """Which implementation to use for the model."""
     appearance_embed_dim: int = 32
     """Dimension of the appearance embedding."""
-    camera_optimizer: CameraOptimizerConfig = CameraOptimizerConfig(mode="SO3xR3")
+    camera_optimizer: CameraOptimizerConfig = field(default_factory=lambda: CameraOptimizerConfig(mode="SO3xR3"))
     """Config of the camera optimizer to use"""
 
 

nerfstudio/models/tensorf.py

@@ -90,7 +90,7 @@ class TensoRFModelConfig(ModelConfig):
     tensorf_encoding: Literal["triplane", "vm", "cp"] = "vm"
     regularization: Literal["none", "l1", "tv"] = "l1"
     """Regularization method used in tensorf paper"""
-    camera_optimizer: CameraOptimizerConfig = CameraOptimizerConfig(mode="SO3xR3")
+    camera_optimizer: CameraOptimizerConfig = field(default_factory=lambda: CameraOptimizerConfig(mode="SO3xR3"))
     """Config of the camera optimizer to use"""
     use_gradient_scaling: bool = False
     """Use gradient scaler where the gradients are lower for points closer to the camera."""

nerfstudio/pipelines/base_pipeline.py

@@ -224,9 +224,9 @@ class VanillaPipelineConfig(cfg.InstantiateConfig):
 
     _target: Type = field(default_factory=lambda: VanillaPipeline)
     """target class to instantiate"""
-    datamanager: DataManagerConfig = DataManagerConfig()
+    datamanager: DataManagerConfig = field(default_factory=lambda: DataManagerConfig())
     """specifies the datamanager config"""
-    model: ModelConfig = ModelConfig()
+    model: ModelConfig = field(default_factory=lambda: ModelConfig())
     """specifies the model config"""