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refactor

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refactor

refactor
This commit is contained in:
Pythonix Huang 2023-04-01 02:50:16 +08:00
parent 53454e187c
commit 6b78039059
1 changed files with 25 additions and 94 deletions
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119
nerfstudio/configs/method_configs.py
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@ -32,13 +32,9 @@ from nerfstudio.data.datamanagers.semantic_datamanager import SemanticDataManage
from nerfstudio.data.dataparsers.blender_dataparser import BlenderDataParserConfig
from nerfstudio.data.dataparsers.dnerf_dataparser import DNeRFDataParserConfig
from nerfstudio.data.dataparsers.dycheck_dataparser import DycheckDataParserConfig
from nerfstudio.data.dataparsers.instant_ngp_dataparser import (
InstantNGPDataParserConfig,
)
from nerfstudio.data.dataparsers.instant_ngp_dataparser import InstantNGPDataParserConfig
from nerfstudio.data.dataparsers.nerfstudio_dataparser import NerfstudioDataParserConfig
from nerfstudio.data.dataparsers.phototourism_dataparser import (
PhototourismDataParserConfig,
)
from nerfstudio.data.dataparsers.phototourism_dataparser import PhototourismDataParserConfig
from nerfstudio.data.dataparsers.sdfstudio_dataparser import SDFStudioDataParserConfig
from nerfstudio.data.dataparsers.sitcoms3d_dataparser import Sitcoms3DDataParserConfig
from nerfstudio.engine.optimizers import AdamOptimizerConfig, RAdamOptimizerConfig
@ -92,8 +88,9 @@ method_configs["nerfacto"] = TrainerConfig(
train_num_rays_per_batch=4096,
eval_num_rays_per_batch=4096,
camera_optimizer=CameraOptimizerConfig(
mode="SO3xR3", optimizer=AdamOptimizerConfig(lr=6e-4, eps=1e-8, weight_decay=1e-2),
scheduler = ExponentialDecaySchedulerConfig(lr_final=6e-6, max_steps=200000)
mode="SO3xR3",
optimizer=AdamOptimizerConfig(lr=6e-4, eps=1e-8, weight_decay=1e-2),
scheduler=ExponentialDecaySchedulerConfig(lr_final=6e-6, max_steps=200000),
),
),
model=NerfactoModelConfig(eval_num_rays_per_chunk=1 << 15),
@ -130,14 +127,8 @@ method_configs["depth-nerfacto"] = TrainerConfig(
model=DepthNerfactoModelConfig(eval_num_rays_per_chunk=1 << 15),
),
optimizers={
"proposal_networks": {
"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15),
"scheduler": None,
},
"fields": {
"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15),
"scheduler": None,
},
"proposal_networks": {"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15), "scheduler": None,},
"fields": {"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15), "scheduler": None,},
},
viewer=ViewerConfig(num_rays_per_chunk=1 << 15),
vis="viewer",
@ -171,14 +162,8 @@ method_configs["volinga"] = TrainerConfig(
),
),
optimizers={
"proposal_networks": {
"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15),
"scheduler": None,
},
"fields": {
"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15),
"scheduler": None,
},
"proposal_networks": {"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15), "scheduler": None,},
"fields": {"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15), "scheduler": None,},
},
viewer=ViewerConfig(num_rays_per_chunk=1 << 15),
vis="viewer",
@ -194,12 +179,7 @@ method_configs["instant-ngp"] = TrainerConfig(
datamanager=VanillaDataManagerConfig(dataparser=NerfstudioDataParserConfig(), train_num_rays_per_batch=8192),
model=InstantNGPModelConfig(eval_num_rays_per_chunk=8192),
),
optimizers={
"fields": {
"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15),
"scheduler": None,
}
},
optimizers={"fields": {"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15), "scheduler": None,}},
viewer=ViewerConfig(num_rays_per_chunk=64000),
vis="viewer",
)
@ -222,12 +202,7 @@ method_configs["instant-ngp-bounded"] = TrainerConfig(
background_color="black",
),
),
optimizers={
"fields": {
"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15),
"scheduler": None,
}
},
optimizers={"fields": {"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15), "scheduler": None,}},
viewer=ViewerConfig(num_rays_per_chunk=64000),
vis="viewer",
)
@ -245,12 +220,7 @@ method_configs["mipnerf"] = TrainerConfig(
eval_num_rays_per_chunk=1024,
),
),
optimizers={
"fields": {
"optimizer": RAdamOptimizerConfig(lr=5e-4, eps=1e-08),
"scheduler": None,
}
},
optimizers={"fields": {"optimizer": RAdamOptimizerConfig(lr=5e-4, eps=1e-08), "scheduler": None,}},
)
method_configs["semantic-nerfw"] = TrainerConfig(
@ -266,14 +236,8 @@ method_configs["semantic-nerfw"] = TrainerConfig(
model=SemanticNerfWModelConfig(eval_num_rays_per_chunk=1 << 16),
),
optimizers={
"proposal_networks": {
"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15),
"scheduler": None,
},
"fields": {
"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15),
"scheduler": None,
},
"proposal_networks": {"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15), "scheduler": None,},
"fields": {"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15), "scheduler": None,},
},
viewer=ViewerConfig(num_rays_per_chunk=1 << 16),
vis="viewer",
@ -282,20 +246,12 @@ method_configs["semantic-nerfw"] = TrainerConfig(
method_configs["vanilla-nerf"] = TrainerConfig(
method_name="vanilla-nerf",
pipeline=VanillaPipelineConfig(
datamanager=VanillaDataManagerConfig(
dataparser=BlenderDataParserConfig(),
),
datamanager=VanillaDataManagerConfig(dataparser=BlenderDataParserConfig(),),
model=VanillaModelConfig(_target=NeRFModel),
),
optimizers={
"fields": {
"optimizer": RAdamOptimizerConfig(lr=5e-4, eps=1e-08),
"scheduler": None,
},
"temporal_distortion": {
"optimizer": RAdamOptimizerConfig(lr=5e-4, eps=1e-08),
"scheduler": None,
},
"fields": {"optimizer": RAdamOptimizerConfig(lr=5e-4, eps=1e-08), "scheduler": None,},
"temporal_distortion": {"optimizer": RAdamOptimizerConfig(lr=5e-4, eps=1e-08), "scheduler": None,},
},
)
@ -307,9 +263,7 @@ method_configs["tensorf"] = TrainerConfig(
mixed_precision=False,
pipeline=VanillaPipelineConfig(
datamanager=VanillaDataManagerConfig(
dataparser=BlenderDataParserConfig(),
train_num_rays_per_batch=4096,
eval_num_rays_per_batch=4096,
dataparser=BlenderDataParserConfig(), train_num_rays_per_batch=4096, eval_num_rays_per_batch=4096,
),
model=TensoRFModelConfig(),
),
@ -338,14 +292,8 @@ method_configs["dnerf"] = TrainerConfig(
),
),
optimizers={
"fields": {
"optimizer": RAdamOptimizerConfig(lr=5e-4, eps=1e-08),
"scheduler": None,
},
"temporal_distortion": {
"optimizer": RAdamOptimizerConfig(lr=5e-4, eps=1e-08),
"scheduler": None,
},
"fields": {"optimizer": RAdamOptimizerConfig(lr=5e-4, eps=1e-08), "scheduler": None,},
"temporal_distortion": {"optimizer": RAdamOptimizerConfig(lr=5e-4, eps=1e-08), "scheduler": None,},
},
)
@ -372,14 +320,8 @@ method_configs["phototourism"] = TrainerConfig(
model=NerfactoModelConfig(eval_num_rays_per_chunk=1 << 15),
),
optimizers={
"proposal_networks": {
"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15),
"scheduler": None,
},
"fields": {
"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15),
"scheduler": None,
},
"proposal_networks": {"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15), "scheduler": None,},
"fields": {"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15), "scheduler": None,},
},
viewer=ViewerConfig(num_rays_per_chunk=1 << 15),
vis="viewer",
@ -403,14 +345,8 @@ method_configs["nerfplayer-nerfacto"] = TrainerConfig(
model=NerfplayerNerfactoModelConfig(eval_num_rays_per_chunk=1 << 15),
),
optimizers={
"proposal_networks": {
"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15),
"scheduler": None,
},
"fields": {
"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15),
"scheduler": None,
},
"proposal_networks": {"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15), "scheduler": None,},
"fields": {"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15), "scheduler": None,},
},
viewer=ViewerConfig(num_rays_per_chunk=1 << 15),
vis="viewer",
@ -432,12 +368,7 @@ method_configs["nerfplayer-ngp"] = TrainerConfig(
near_plane=0.01,
),
),
optimizers={
"fields": {
"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15),
"scheduler": None,
}
},
optimizers={"fields": {"optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15), "scheduler": None,}},
viewer=ViewerConfig(num_rays_per_chunk=64000),
vis="viewer",
)