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Replace pluggable components to create a proper Configurable hierarchy.

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Summary:
This large diff rewrites a significant portion of Implicitron's config hierarchy. The new hierarchy, and some of the default implementation classes, are as follows:
```
Experiment
    data_source: ImplicitronDataSource
        dataset_map_provider
        data_loader_map_provider
    model_factory: ImplicitronModelFactory
        model: GenericModel
    optimizer_factory: ImplicitronOptimizerFactory
    training_loop: ImplicitronTrainingLoop
        evaluator: ImplicitronEvaluator
```

1) Experiment (used to be ExperimentConfig) is now a top-level Configurable and contains as members mainly (mostly new) high-level factory Configurables.
2) Experiment's job is to run factories, do some accelerate setup and then pass the results to the main training loop.
3) ImplicitronOptimizerFactory and ImplicitronModelFactory are new high-level factories that create the optimizer, scheduler, model, and stats objects.
4) TrainingLoop is a new configurable that runs the main training loop and the inner train-validate step.
5) Evaluator is a new configurable that TrainingLoop uses to run validation/test steps.
6) GenericModel is not the only model choice anymore. Instead, ImplicitronModelBase (by default instantiated with GenericModel) is a member of Experiment and can be easily replaced by a custom implementation by the user.

All the new Configurables are children of ReplaceableBase, and can be easily replaced with custom implementations.

In addition, I added support for the exponential LR schedule, updated the config files and the test, as well as added a config file that reproduces NERF results and a test to run the repro experiment.

Reviewed By: bottler

Differential Revision: D37723227

fbshipit-source-id: b36bee880d6aa53efdd2abfaae4489d8ab1e8a27
This commit is contained in:
Krzysztof Chalupka
2022-07-29 17:32:51 -07:00
committed by Facebook GitHub Bot
parent 6b481595f0
commit 1b0584f7bd
42 changed files with 2045 additions and 1478 deletions
Download Patch File Download Diff File Expand all files Collapse all files

650
projects/implicitron_trainer/tests/experiment.yaml
View File

@@ -1,296 +1,14 @@
generic_model_args:
mask_images: true
mask_depths: true
render_image_width: 400
render_image_height: 400
mask_threshold: 0.5
output_rasterized_mc: false
bg_color:
- 0.0
- 0.0
- 0.0
num_passes: 1
chunk_size_grid: 4096
render_features_dimensions: 3
tqdm_trigger_threshold: 16
n_train_target_views: 1
sampling_mode_training: mask_sample
sampling_mode_evaluation: full_grid
global_encoder_class_type: null
raysampler_class_type: AdaptiveRaySampler
renderer_class_type: MultiPassEmissionAbsorptionRenderer
image_feature_extractor_class_type: null
view_pooler_enabled: false
implicit_function_class_type: NeuralRadianceFieldImplicitFunction
view_metrics_class_type: ViewMetrics
regularization_metrics_class_type: RegularizationMetrics
loss_weights:
loss_rgb_mse: 1.0
loss_prev_stage_rgb_mse: 1.0
loss_mask_bce: 0.0
loss_prev_stage_mask_bce: 0.0
log_vars:
- loss_rgb_psnr_fg
- loss_rgb_psnr
- loss_rgb_mse
- loss_rgb_huber
- loss_depth_abs
- loss_depth_abs_fg
- loss_mask_neg_iou
- loss_mask_bce
- loss_mask_beta_prior
- loss_eikonal
- loss_density_tv
- loss_depth_neg_penalty
- loss_autodecoder_norm
- loss_prev_stage_rgb_mse
- loss_prev_stage_rgb_psnr_fg
- loss_prev_stage_rgb_psnr
- loss_prev_stage_mask_bce
- objective
- epoch
- sec/it
global_encoder_HarmonicTimeEncoder_args:
n_harmonic_functions: 10
append_input: true
time_divisor: 1.0
global_encoder_SequenceAutodecoder_args:
autodecoder_args:
encoding_dim: 0
n_instances: 0
init_scale: 1.0
ignore_input: false
raysampler_AdaptiveRaySampler_args:
image_width: 400
image_height: 400
sampling_mode_training: mask_sample
sampling_mode_evaluation: full_grid
n_pts_per_ray_training: 64
n_pts_per_ray_evaluation: 64
n_rays_per_image_sampled_from_mask: 1024
stratified_point_sampling_training: true
stratified_point_sampling_evaluation: false
scene_extent: 8.0
scene_center:
- 0.0
- 0.0
- 0.0
raysampler_NearFarRaySampler_args:
image_width: 400
image_height: 400
sampling_mode_training: mask_sample
sampling_mode_evaluation: full_grid
n_pts_per_ray_training: 64
n_pts_per_ray_evaluation: 64
n_rays_per_image_sampled_from_mask: 1024
stratified_point_sampling_training: true
stratified_point_sampling_evaluation: false
min_depth: 0.1
max_depth: 8.0
renderer_LSTMRenderer_args:
num_raymarch_steps: 10
init_depth: 17.0
init_depth_noise_std: 0.0005
hidden_size: 16
n_feature_channels: 256
bg_color: null
verbose: false
renderer_MultiPassEmissionAbsorptionRenderer_args:
raymarcher_class_type: EmissionAbsorptionRaymarcher
n_pts_per_ray_fine_training: 64
n_pts_per_ray_fine_evaluation: 64
stratified_sampling_coarse_training: true
stratified_sampling_coarse_evaluation: false
append_coarse_samples_to_fine: true
density_noise_std_train: 0.0
return_weights: false
raymarcher_CumsumRaymarcher_args:
surface_thickness: 1
bg_color:
- 0.0
background_opacity: 0.0
density_relu: true
blend_output: false
raymarcher_EmissionAbsorptionRaymarcher_args:
surface_thickness: 1
bg_color:
- 0.0
background_opacity: 10000000000.0
density_relu: true
blend_output: false
renderer_SignedDistanceFunctionRenderer_args:
render_features_dimensions: 3
ray_tracer_args:
object_bounding_sphere: 1.0
sdf_threshold: 5.0e-05
line_search_step: 0.5
line_step_iters: 1
sphere_tracing_iters: 10
n_steps: 100
n_secant_steps: 8
ray_normal_coloring_network_args:
feature_vector_size: 3
mode: idr
d_in: 9
d_out: 3
dims:
- 512
- 512
- 512
- 512
weight_norm: true
n_harmonic_functions_dir: 0
pooled_feature_dim: 0
bg_color:
- 0.0
soft_mask_alpha: 50.0
image_feature_extractor_ResNetFeatureExtractor_args:
name: resnet34
pretrained: true
stages:
- 1
- 2
- 3
- 4
normalize_image: true
image_rescale: 0.16
first_max_pool: true
proj_dim: 32
l2_norm: true
add_masks: true
add_images: true
global_average_pool: false
feature_rescale: 1.0
view_pooler_args:
feature_aggregator_class_type: AngleWeightedReductionFeatureAggregator
view_sampler_args:
masked_sampling: false
sampling_mode: bilinear
feature_aggregator_AngleWeightedIdentityFeatureAggregator_args:
exclude_target_view: true
exclude_target_view_mask_features: true
concatenate_output: true
weight_by_ray_angle_gamma: 1.0
min_ray_angle_weight: 0.1
feature_aggregator_AngleWeightedReductionFeatureAggregator_args:
exclude_target_view: true
exclude_target_view_mask_features: true
concatenate_output: true
reduction_functions:
- AVG
- STD
weight_by_ray_angle_gamma: 1.0
min_ray_angle_weight: 0.1
feature_aggregator_IdentityFeatureAggregator_args:
exclude_target_view: true
exclude_target_view_mask_features: true
concatenate_output: true
feature_aggregator_ReductionFeatureAggregator_args:
exclude_target_view: true
exclude_target_view_mask_features: true
concatenate_output: true
reduction_functions:
- AVG
- STD
implicit_function_IdrFeatureField_args:
feature_vector_size: 3
d_in: 3
d_out: 1
dims:
- 512
- 512
- 512
- 512
- 512
- 512
- 512
- 512
geometric_init: true
bias: 1.0
skip_in: []
weight_norm: true
n_harmonic_functions_xyz: 0
pooled_feature_dim: 0
encoding_dim: 0
implicit_function_NeRFormerImplicitFunction_args:
n_harmonic_functions_xyz: 10
n_harmonic_functions_dir: 4
n_hidden_neurons_dir: 128
latent_dim: 0
input_xyz: true
xyz_ray_dir_in_camera_coords: false
color_dim: 3
transformer_dim_down_factor: 2.0
n_hidden_neurons_xyz: 80
n_layers_xyz: 2
append_xyz:
- 1
implicit_function_NeuralRadianceFieldImplicitFunction_args:
n_harmonic_functions_xyz: 10
n_harmonic_functions_dir: 4
n_hidden_neurons_dir: 128
latent_dim: 0
input_xyz: true
xyz_ray_dir_in_camera_coords: false
color_dim: 3
transformer_dim_down_factor: 1.0
n_hidden_neurons_xyz: 256
n_layers_xyz: 8
append_xyz:
- 5
implicit_function_SRNHyperNetImplicitFunction_args:
hypernet_args:
n_harmonic_functions: 3
n_hidden_units: 256
n_layers: 2
n_hidden_units_hypernet: 256
n_layers_hypernet: 1
in_features: 3
out_features: 256
latent_dim_hypernet: 0
latent_dim: 0
xyz_in_camera_coords: false
pixel_generator_args:
n_harmonic_functions: 4
n_hidden_units: 256
n_hidden_units_color: 128
n_layers: 2
in_features: 256
out_features: 3
ray_dir_in_camera_coords: false
implicit_function_SRNImplicitFunction_args:
raymarch_function_args:
n_harmonic_functions: 3
n_hidden_units: 256
n_layers: 2
in_features: 3
out_features: 256
latent_dim: 0
xyz_in_camera_coords: false
raymarch_function: null
pixel_generator_args:
n_harmonic_functions: 4
n_hidden_units: 256
n_hidden_units_color: 128
n_layers: 2
in_features: 256
out_features: 3
ray_dir_in_camera_coords: false
view_metrics_ViewMetrics_args: {}
regularization_metrics_RegularizationMetrics_args: {}
solver_args:
breed: adam
weight_decay: 0.0
lr_policy: multistep
lr: 0.0005
gamma: 0.1
momentum: 0.9
betas:
- 0.9
- 0.999
milestones: []
max_epochs: 1000
data_source_args:
data_source_class_type: ImplicitronDataSource
model_factory_class_type: ImplicitronModelFactory
optimizer_factory_class_type: ImplicitronOptimizerFactory
training_loop_class_type: ImplicitronTrainingLoop
detect_anomaly: false
exp_dir: ./data/default_experiment/
hydra:
run:
dir: .
output_subdir: null
data_source_ImplicitronDataSource_args:
dataset_map_provider_class_type: ???
data_loader_map_provider_class_type: SequenceDataLoaderMapProvider
dataset_map_provider_BlenderDatasetMapProvider_args:
@@ -396,30 +114,322 @@ data_source_args:
sample_consecutive_frames: false
consecutive_frames_max_gap: 0
consecutive_frames_max_gap_seconds: 0.1
architecture: generic
detect_anomaly: false
eval_only: false
exp_dir: ./data/default_experiment/
exp_idx: 0
gpu_idx: 0
metric_print_interval: 5
resume: true
resume_epoch: -1
seed: 0
store_checkpoints: true
store_checkpoints_purge: 1
test_interval: -1
test_when_finished: false
validation_interval: 1
visdom_env: ''
visdom_port: 8097
visdom_server: http://127.0.0.1
visualize_interval: 1000
clip_grad: 0.0
camera_difficulty_bin_breaks:
- 0.97
- 0.98
hydra:
run:
dir: .
output_subdir: null
model_factory_ImplicitronModelFactory_args:
force_load: false
model_class_type: GenericModel
resume: false
resume_epoch: -1
visdom_env: ''
visdom_port: 8097
visdom_server: http://127.0.0.1
model_GenericModel_args:
mask_images: true
mask_depths: true
render_image_width: 400
render_image_height: 400
mask_threshold: 0.5
output_rasterized_mc: false
bg_color:
- 0.0
- 0.0
- 0.0
num_passes: 1
chunk_size_grid: 4096
render_features_dimensions: 3
tqdm_trigger_threshold: 16
n_train_target_views: 1
sampling_mode_training: mask_sample
sampling_mode_evaluation: full_grid
global_encoder_class_type: null
raysampler_class_type: AdaptiveRaySampler
renderer_class_type: MultiPassEmissionAbsorptionRenderer
image_feature_extractor_class_type: null
view_pooler_enabled: false
implicit_function_class_type: NeuralRadianceFieldImplicitFunction
view_metrics_class_type: ViewMetrics
regularization_metrics_class_type: RegularizationMetrics
loss_weights:
loss_rgb_mse: 1.0
loss_prev_stage_rgb_mse: 1.0
loss_mask_bce: 0.0
loss_prev_stage_mask_bce: 0.0
log_vars:
- loss_rgb_psnr_fg
- loss_rgb_psnr
- loss_rgb_mse
- loss_rgb_huber
- loss_depth_abs
- loss_depth_abs_fg
- loss_mask_neg_iou
- loss_mask_bce
- loss_mask_beta_prior
- loss_eikonal
- loss_density_tv
- loss_depth_neg_penalty
- loss_autodecoder_norm
- loss_prev_stage_rgb_mse
- loss_prev_stage_rgb_psnr_fg
- loss_prev_stage_rgb_psnr
- loss_prev_stage_mask_bce
- objective
- epoch
- sec/it
global_encoder_HarmonicTimeEncoder_args:
n_harmonic_functions: 10
append_input: true
time_divisor: 1.0
global_encoder_SequenceAutodecoder_args:
autodecoder_args:
encoding_dim: 0
n_instances: 0
init_scale: 1.0
ignore_input: false
raysampler_AdaptiveRaySampler_args:
image_width: 400
image_height: 400
sampling_mode_training: mask_sample
sampling_mode_evaluation: full_grid
n_pts_per_ray_training: 64
n_pts_per_ray_evaluation: 64
n_rays_per_image_sampled_from_mask: 1024
stratified_point_sampling_training: true
stratified_point_sampling_evaluation: false
scene_extent: 8.0
scene_center:
- 0.0
- 0.0
- 0.0
raysampler_NearFarRaySampler_args:
image_width: 400
image_height: 400
sampling_mode_training: mask_sample
sampling_mode_evaluation: full_grid
n_pts_per_ray_training: 64
n_pts_per_ray_evaluation: 64
n_rays_per_image_sampled_from_mask: 1024
stratified_point_sampling_training: true
stratified_point_sampling_evaluation: false
min_depth: 0.1
max_depth: 8.0
renderer_LSTMRenderer_args:
num_raymarch_steps: 10
init_depth: 17.0
init_depth_noise_std: 0.0005
hidden_size: 16
n_feature_channels: 256
bg_color: null
verbose: false
renderer_MultiPassEmissionAbsorptionRenderer_args:
raymarcher_class_type: EmissionAbsorptionRaymarcher
n_pts_per_ray_fine_training: 64
n_pts_per_ray_fine_evaluation: 64
stratified_sampling_coarse_training: true
stratified_sampling_coarse_evaluation: false
append_coarse_samples_to_fine: true
density_noise_std_train: 0.0
return_weights: false
raymarcher_CumsumRaymarcher_args:
surface_thickness: 1
bg_color:
- 0.0
background_opacity: 0.0
density_relu: true
blend_output: false
raymarcher_EmissionAbsorptionRaymarcher_args:
surface_thickness: 1
bg_color:
- 0.0
background_opacity: 10000000000.0
density_relu: true
blend_output: false
renderer_SignedDistanceFunctionRenderer_args:
render_features_dimensions: 3
ray_tracer_args:
object_bounding_sphere: 1.0
sdf_threshold: 5.0e-05
line_search_step: 0.5
line_step_iters: 1
sphere_tracing_iters: 10
n_steps: 100
n_secant_steps: 8
ray_normal_coloring_network_args:
feature_vector_size: 3
mode: idr
d_in: 9
d_out: 3
dims:
- 512
- 512
- 512
- 512
weight_norm: true
n_harmonic_functions_dir: 0
pooled_feature_dim: 0
bg_color:
- 0.0
soft_mask_alpha: 50.0
image_feature_extractor_ResNetFeatureExtractor_args:
name: resnet34
pretrained: true
stages:
- 1
- 2
- 3
- 4
normalize_image: true
image_rescale: 0.16
first_max_pool: true
proj_dim: 32
l2_norm: true
add_masks: true
add_images: true
global_average_pool: false
feature_rescale: 1.0
view_pooler_args:
feature_aggregator_class_type: AngleWeightedReductionFeatureAggregator
view_sampler_args:
masked_sampling: false
sampling_mode: bilinear
feature_aggregator_AngleWeightedIdentityFeatureAggregator_args:
exclude_target_view: true
exclude_target_view_mask_features: true
concatenate_output: true
weight_by_ray_angle_gamma: 1.0
min_ray_angle_weight: 0.1
feature_aggregator_AngleWeightedReductionFeatureAggregator_args:
exclude_target_view: true
exclude_target_view_mask_features: true
concatenate_output: true
reduction_functions:
- AVG
- STD
weight_by_ray_angle_gamma: 1.0
min_ray_angle_weight: 0.1
feature_aggregator_IdentityFeatureAggregator_args:
exclude_target_view: true
exclude_target_view_mask_features: true
concatenate_output: true
feature_aggregator_ReductionFeatureAggregator_args:
exclude_target_view: true
exclude_target_view_mask_features: true
concatenate_output: true
reduction_functions:
- AVG
- STD
implicit_function_IdrFeatureField_args:
feature_vector_size: 3
d_in: 3
d_out: 1
dims:
- 512
- 512
- 512
- 512
- 512
- 512
- 512
- 512
geometric_init: true
bias: 1.0
skip_in: []
weight_norm: true
n_harmonic_functions_xyz: 0
pooled_feature_dim: 0
encoding_dim: 0
implicit_function_NeRFormerImplicitFunction_args:
n_harmonic_functions_xyz: 10
n_harmonic_functions_dir: 4
n_hidden_neurons_dir: 128
latent_dim: 0
input_xyz: true
xyz_ray_dir_in_camera_coords: false
color_dim: 3
transformer_dim_down_factor: 2.0
n_hidden_neurons_xyz: 80
n_layers_xyz: 2
append_xyz:
- 1
implicit_function_NeuralRadianceFieldImplicitFunction_args:
n_harmonic_functions_xyz: 10
n_harmonic_functions_dir: 4
n_hidden_neurons_dir: 128
latent_dim: 0
input_xyz: true
xyz_ray_dir_in_camera_coords: false
color_dim: 3
transformer_dim_down_factor: 1.0
n_hidden_neurons_xyz: 256
n_layers_xyz: 8
append_xyz:
- 5
implicit_function_SRNHyperNetImplicitFunction_args:
hypernet_args:
n_harmonic_functions: 3
n_hidden_units: 256
n_layers: 2
n_hidden_units_hypernet: 256
n_layers_hypernet: 1
in_features: 3
out_features: 256
latent_dim_hypernet: 0
latent_dim: 0
xyz_in_camera_coords: false
pixel_generator_args:
n_harmonic_functions: 4
n_hidden_units: 256
n_hidden_units_color: 128
n_layers: 2
in_features: 256
out_features: 3
ray_dir_in_camera_coords: false
implicit_function_SRNImplicitFunction_args:
raymarch_function_args:
n_harmonic_functions: 3
n_hidden_units: 256
n_layers: 2
in_features: 3
out_features: 256
latent_dim: 0
xyz_in_camera_coords: false
raymarch_function: null
pixel_generator_args:
n_harmonic_functions: 4
n_hidden_units: 256
n_hidden_units_color: 128
n_layers: 2
in_features: 256
out_features: 3
ray_dir_in_camera_coords: false
view_metrics_ViewMetrics_args: {}
regularization_metrics_RegularizationMetrics_args: {}
optimizer_factory_ImplicitronOptimizerFactory_args:
betas:
- 0.9
- 0.999
breed: Adam
exponential_lr_step_size: 250
gamma: 0.1
lr: 0.0005
lr_policy: MultiStepLR
momentum: 0.9
multistep_lr_milestones: []
resume: false
resume_epoch: -1
weight_decay: 0.0
training_loop_ImplicitronTrainingLoop_args:
eval_only: false
evaluator_class_type: ImplicitronEvaluator
max_epochs: 1000
seed: 0
store_checkpoints: true
store_checkpoints_purge: 1
test_interval: -1
test_when_finished: false
validation_interval: 1
clip_grad: 0.0
metric_print_interval: 5
visualize_interval: 1000
evaluator_ImplicitronEvaluator_args:
camera_difficulty_bin_breaks:
- 0.97
- 0.98

99
projects/implicitron_trainer/tests/test_experiment.py
View File

@@ -12,6 +12,7 @@ from hydra import compose, initialize_config_dir
from omegaconf import OmegaConf
from .. import experiment
from .utils import intercept_logs
def interactive_testing_requested() -> bool:
@@ -33,7 +34,10 @@ DEBUG: bool = False
# TODO:
# - add enough files to skateboard_first_5 that this works on RE.
# - share common code with PyTorch3D tests?
# - deal with the temporary output files this test creates
def _parse_float_from_log(line):
return float(line.split()[-1])
class TestExperiment(unittest.TestCase):
@@ -44,15 +48,18 @@ class TestExperiment(unittest.TestCase):
# Test making minimal changes to the dataclass defaults.
if not interactive_testing_requested() or not internal:
return
cfg = OmegaConf.structured(experiment.ExperimentConfig)
cfg.data_source_args.dataset_map_provider_class_type = (
# Manually override config values. Note that this is not necessary out-
# side of the tests!
cfg = OmegaConf.structured(experiment.Experiment)
cfg.data_source_ImplicitronDataSource_args.dataset_map_provider_class_type = (
"JsonIndexDatasetMapProvider"
)
dataset_args = (
cfg.data_source_args.dataset_map_provider_JsonIndexDatasetMapProvider_args
cfg.data_source_ImplicitronDataSource_args.dataset_map_provider_JsonIndexDatasetMapProvider_args
)
dataloader_args = (
cfg.data_source_args.data_loader_map_provider_SequenceDataLoaderMapProvider_args
cfg.data_source_ImplicitronDataSource_args.data_loader_map_provider_SequenceDataLoaderMapProvider_args
)
dataset_args.category = "skateboard"
dataset_args.test_restrict_sequence_id = 0
@@ -62,18 +69,80 @@ class TestExperiment(unittest.TestCase):
dataset_args.dataset_JsonIndexDataset_args.image_width = 80
dataloader_args.dataset_length_train = 1
dataloader_args.dataset_length_val = 1
cfg.solver_args.max_epochs = 2
cfg.training_loop_ImplicitronTrainingLoop_args.max_epochs = 2
cfg.training_loop_ImplicitronTrainingLoop_args.store_checkpoints = False
cfg.optimizer_factory_ImplicitronOptimizerFactory_args.multistep_lr_milestones = [
0,
1,
]
experiment.run_training(cfg)
if DEBUG:
experiment.dump_cfg(cfg)
with intercept_logs(
logger_name="projects.implicitron_trainer.impl.training_loop",
regexp="LR change!",
) as intercepted_logs:
experiment_runner = experiment.Experiment(**cfg)
experiment_runner.run()
# Make sure LR decreased on 0th and 1st epoch 10fold.
self.assertEqual(intercepted_logs[0].split()[-1], "5e-06")
def test_exponential_lr(self):
# Test making minimal changes to the dataclass defaults.
if not interactive_testing_requested():
return
cfg = OmegaConf.structured(experiment.Experiment)
cfg.data_source_ImplicitronDataSource_args.dataset_map_provider_class_type = (
"JsonIndexDatasetMapProvider"
)
dataset_args = (
cfg.data_source_ImplicitronDataSource_args.dataset_map_provider_JsonIndexDatasetMapProvider_args
)
dataloader_args = (
cfg.data_source_ImplicitronDataSource_args.data_loader_map_provider_SequenceDataLoaderMapProvider_args
)
dataset_args.category = "skateboard"
dataset_args.test_restrict_sequence_id = 0
dataset_args.dataset_root = "manifold://co3d/tree/extracted"
dataset_args.dataset_JsonIndexDataset_args.limit_sequences_to = 5
dataset_args.dataset_JsonIndexDataset_args.image_height = 80
dataset_args.dataset_JsonIndexDataset_args.image_width = 80
dataloader_args.dataset_length_train = 1
dataloader_args.dataset_length_val = 1
cfg.training_loop_ImplicitronTrainingLoop_args.max_epochs = 2
cfg.training_loop_ImplicitronTrainingLoop_args.store_checkpoints = False
cfg.optimizer_factory_ImplicitronOptimizerFactory_args.lr_policy = "Exponential"
cfg.optimizer_factory_ImplicitronOptimizerFactory_args.exponential_lr_step_size = (
2
)
if DEBUG:
experiment.dump_cfg(cfg)
with intercept_logs(
logger_name="projects.implicitron_trainer.impl.training_loop",
regexp="LR change!",
) as intercepted_logs:
experiment_runner = experiment.Experiment(**cfg)
experiment_runner.run()
# Make sure we followed the exponential lr schedule with gamma=0.1,
# exponential_lr_step_size=2 -- so after two epochs, should
# decrease lr 10x to 5e-5.
self.assertEqual(intercepted_logs[0].split()[-1], "0.00015811388300841897")
self.assertEqual(intercepted_logs[1].split()[-1], "5e-05")
def test_yaml_contents(self):
cfg = OmegaConf.structured(experiment.ExperimentConfig)
# Check that the default config values, defined by Experiment and its
# members, is what we expect it to be.
cfg = OmegaConf.structured(experiment.Experiment)
yaml = OmegaConf.to_yaml(cfg, sort_keys=False)
if DEBUG:
(DATA_DIR / "experiment.yaml").write_text(yaml)
self.assertEqual(yaml, (DATA_DIR / "experiment.yaml").read_text())
def test_load_configs(self):
# Check that all the pre-prepared configs are valid.
config_files = []
for pattern in ("repro_singleseq*.yaml", "repro_multiseq*.yaml"):
@@ -89,3 +158,17 @@ class TestExperiment(unittest.TestCase):
with self.subTest(file.name):
with initialize_config_dir(config_dir=str(IMPLICITRON_CONFIGS_DIR)):
compose(file.name)
class TestNerfRepro(unittest.TestCase):
@unittest.skip("This test reproduces full NERF training.")
def test_nerf_blender(self):
# Train vanilla NERF.
# Set env vars BLENDER_DATASET_ROOT and BLENDER_SINGLESEQ_CLASS first!
if not interactive_testing_requested():
return
with initialize_config_dir(config_dir=str(IMPLICITRON_CONFIGS_DIR)):
cfg = compose(config_name="repro_singleseq_nerf_blender", overrides=[])
experiment_runner = experiment.Experiment(**cfg)
experiment.dump_cfg(cfg)
experiment_runner.run()

31
projects/implicitron_trainer/tests/utils.py Normal file
View File

@@ -0,0 +1,31 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import contextlib
import logging
import re
from typing import List
@contextlib.contextmanager
def intercept_logs(logger_name: str, regexp: str):
# Intercept logs that match a regexp, from a given logger.
intercepted_messages = []
logger = logging.getLogger(logger_name)
class LoggerInterceptor(logging.Filter):
def filter(self, record):
message = record.getMessage()
if re.search(regexp, message):
intercepted_messages.append(message)
return True
interceptor = LoggerInterceptor()
logger.addFilter(interceptor)
try:
yield intercepted_messages
finally:
logger.removeFilter(interceptor)