mirror of
https://github.com/facebookresearch/pytorch3d.git
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test runner for experiment.py
Summary: Add simple interactive testrunner for experiment.py Reviewed By: shapovalov Differential Revision: D35316221 fbshipit-source-id: d424bcba632eef89eefb56e18e536edb58ec6f85
This commit is contained in:
parent
fbd3c679ac
commit
c31bf85a23
@ -705,8 +705,9 @@ class ExperimentConfig:
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)
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cs = hydra.core.config_store.ConfigStore.instance()
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cs.store(name="default_config", node=ExperimentConfig)
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if __name__ == "__main__":
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cs = hydra.core.config_store.ConfigStore.instance()
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cs.store(name="default_config", node=ExperimentConfig)
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@hydra.main(config_path="./configs/", config_name="default_config")
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5
projects/implicitron_trainer/tests/__init__.py
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5
projects/implicitron_trainer/tests/__init__.py
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@ -0,0 +1,5 @@
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the BSD-style license found in the
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# LICENSE file in the root directory of this source tree.
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340
projects/implicitron_trainer/tests/experiment.yaml
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340
projects/implicitron_trainer/tests/experiment.yaml
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@ -0,0 +1,340 @@
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generic_model_args:
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mask_images: true
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mask_depths: true
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render_image_width: 400
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render_image_height: 400
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mask_threshold: 0.5
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output_rasterized_mc: false
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bg_color:
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- 0.0
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- 0.0
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- 0.0
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num_passes: 1
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chunk_size_grid: 4096
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render_features_dimensions: 3
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tqdm_trigger_threshold: 16
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n_train_target_views: 1
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sampling_mode_training: mask_sample
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sampling_mode_evaluation: full_grid
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raysampler_class_type: AdaptiveRaySampler
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renderer_class_type: MultiPassEmissionAbsorptionRenderer
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image_feature_extractor_class_type: null
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view_pooler_enabled: false
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implicit_function_class_type: NeuralRadianceFieldImplicitFunction
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loss_weights:
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loss_rgb_mse: 1.0
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loss_prev_stage_rgb_mse: 1.0
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loss_mask_bce: 0.0
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loss_prev_stage_mask_bce: 0.0
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log_vars:
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- loss_rgb_psnr_fg
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- loss_rgb_psnr
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- loss_rgb_mse
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- loss_rgb_huber
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- loss_depth_abs
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- loss_depth_abs_fg
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- loss_mask_neg_iou
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- loss_mask_bce
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- loss_mask_beta_prior
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- loss_eikonal
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- loss_density_tv
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- loss_depth_neg_penalty
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- loss_autodecoder_norm
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- loss_prev_stage_rgb_mse
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- loss_prev_stage_rgb_psnr_fg
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- loss_prev_stage_rgb_psnr
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- loss_prev_stage_mask_bce
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- objective
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- epoch
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- sec/it
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sequence_autodecoder_args:
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encoding_dim: 0
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n_instances: 0
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init_scale: 1.0
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ignore_input: false
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raysampler_AdaptiveRaySampler_args:
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image_width: 400
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image_height: 400
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sampling_mode_training: mask_sample
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sampling_mode_evaluation: full_grid
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n_pts_per_ray_training: 64
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n_pts_per_ray_evaluation: 64
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n_rays_per_image_sampled_from_mask: 1024
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stratified_point_sampling_training: true
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stratified_point_sampling_evaluation: false
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scene_extent: 8.0
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scene_center:
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- 0.0
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- 0.0
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- 0.0
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raysampler_NearFarRaySampler_args:
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image_width: 400
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image_height: 400
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sampling_mode_training: mask_sample
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sampling_mode_evaluation: full_grid
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n_pts_per_ray_training: 64
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n_pts_per_ray_evaluation: 64
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n_rays_per_image_sampled_from_mask: 1024
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stratified_point_sampling_training: true
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stratified_point_sampling_evaluation: false
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min_depth: 0.1
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max_depth: 8.0
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renderer_LSTMRenderer_args:
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num_raymarch_steps: 10
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init_depth: 17.0
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init_depth_noise_std: 0.0005
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hidden_size: 16
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n_feature_channels: 256
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verbose: false
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renderer_MultiPassEmissionAbsorptionRenderer_args:
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raymarcher_class_type: EmissionAbsorptionRaymarcher
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n_pts_per_ray_fine_training: 64
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n_pts_per_ray_fine_evaluation: 64
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stratified_sampling_coarse_training: true
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stratified_sampling_coarse_evaluation: false
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append_coarse_samples_to_fine: true
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density_noise_std_train: 0.0
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return_weights: false
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raymarcher_EmissionAbsorptionRaymarcher_args:
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surface_thickness: 1
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bg_color:
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- 0.0
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background_opacity: 10000000000.0
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density_relu: true
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blend_output: false
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raymarcher_CumsumRaymarcher_args:
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surface_thickness: 1
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bg_color:
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- 0.0
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background_opacity: 0.0
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density_relu: true
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blend_output: false
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renderer_SignedDistanceFunctionRenderer_args:
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render_features_dimensions: 3
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ray_tracer_args:
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object_bounding_sphere: 1.0
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sdf_threshold: 5.0e-05
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line_search_step: 0.5
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line_step_iters: 1
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sphere_tracing_iters: 10
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n_steps: 100
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n_secant_steps: 8
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ray_normal_coloring_network_args:
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feature_vector_size: 3
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mode: idr
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d_in: 9
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d_out: 3
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dims:
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- 512
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- 512
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- 512
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- 512
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weight_norm: true
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n_harmonic_functions_dir: 0
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pooled_feature_dim: 0
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bg_color:
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- 0.0
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soft_mask_alpha: 50.0
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image_feature_extractor_ResNetFeatureExtractor_args:
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name: resnet34
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pretrained: true
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stages:
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- 1
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- 2
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- 3
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- 4
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normalize_image: true
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image_rescale: 0.16
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first_max_pool: true
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proj_dim: 32
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l2_norm: true
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add_masks: true
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add_images: true
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global_average_pool: false
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feature_rescale: 1.0
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view_pooler_args:
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feature_aggregator_class_type: AngleWeightedReductionFeatureAggregator
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view_sampler_args:
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masked_sampling: false
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sampling_mode: bilinear
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feature_aggregator_IdentityFeatureAggregator_args:
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exclude_target_view: true
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exclude_target_view_mask_features: true
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concatenate_output: true
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feature_aggregator_ReductionFeatureAggregator_args:
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exclude_target_view: true
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exclude_target_view_mask_features: true
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concatenate_output: true
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reduction_functions:
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- AVG
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- STD
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feature_aggregator_AngleWeightedReductionFeatureAggregator_args:
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exclude_target_view: true
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exclude_target_view_mask_features: true
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concatenate_output: true
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reduction_functions:
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- AVG
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- STD
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weight_by_ray_angle_gamma: 1.0
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min_ray_angle_weight: 0.1
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feature_aggregator_AngleWeightedIdentityFeatureAggregator_args:
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exclude_target_view: true
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exclude_target_view_mask_features: true
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concatenate_output: true
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weight_by_ray_angle_gamma: 1.0
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min_ray_angle_weight: 0.1
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implicit_function_IdrFeatureField_args:
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feature_vector_size: 3
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d_in: 3
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d_out: 1
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dims:
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- 512
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- 512
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- 512
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- 512
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- 512
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- 512
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- 512
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- 512
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geometric_init: true
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bias: 1.0
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skip_in: []
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weight_norm: true
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n_harmonic_functions_xyz: 0
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pooled_feature_dim: 0
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encoding_dim: 0
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implicit_function_NeuralRadianceFieldImplicitFunction_args:
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n_harmonic_functions_xyz: 10
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n_harmonic_functions_dir: 4
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n_hidden_neurons_dir: 128
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latent_dim: 0
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input_xyz: true
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xyz_ray_dir_in_camera_coords: false
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color_dim: 3
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transformer_dim_down_factor: 1.0
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n_hidden_neurons_xyz: 256
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n_layers_xyz: 8
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append_xyz:
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- 5
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implicit_function_NeRFormerImplicitFunction_args:
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n_harmonic_functions_xyz: 10
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n_harmonic_functions_dir: 4
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n_hidden_neurons_dir: 128
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latent_dim: 0
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input_xyz: true
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xyz_ray_dir_in_camera_coords: false
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color_dim: 3
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transformer_dim_down_factor: 2.0
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n_hidden_neurons_xyz: 80
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n_layers_xyz: 2
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append_xyz:
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- 1
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implicit_function_SRNImplicitFunction_args:
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raymarch_function_args:
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n_harmonic_functions: 3
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n_hidden_units: 256
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n_layers: 2
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in_features: 3
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out_features: 256
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latent_dim: 0
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xyz_in_camera_coords: false
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raymarch_function: null
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pixel_generator_args:
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n_harmonic_functions: 4
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n_hidden_units: 256
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n_hidden_units_color: 128
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n_layers: 2
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in_features: 256
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out_features: 3
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ray_dir_in_camera_coords: false
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implicit_function_SRNHyperNetImplicitFunction_args:
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hypernet_args:
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n_harmonic_functions: 3
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n_hidden_units: 256
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n_layers: 2
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n_hidden_units_hypernet: 256
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n_layers_hypernet: 1
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in_features: 3
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out_features: 256
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latent_dim_hypernet: 0
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latent_dim: 0
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xyz_in_camera_coords: false
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pixel_generator_args:
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n_harmonic_functions: 4
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n_hidden_units: 256
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n_hidden_units_color: 128
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n_layers: 2
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in_features: 256
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out_features: 3
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ray_dir_in_camera_coords: false
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solver_args:
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breed: adam
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weight_decay: 0.0
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lr_policy: multistep
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lr: 0.0005
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gamma: 0.1
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momentum: 0.9
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betas:
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- 0.9
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- 0.999
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milestones: []
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max_epochs: 1000
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data_source_args:
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dataset_map_provider_class_type: ???
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data_loader_map_provider_class_type: SequenceDataLoaderMapProvider
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dataset_map_provider_JsonIndexDatasetMapProvider_args:
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category: ???
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task_str: singlesequence
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dataset_root: ''
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limit_to: -1
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limit_sequences_to: -1
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n_frames_per_sequence: -1
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test_on_train: false
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load_point_clouds: false
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mask_images: false
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mask_depths: false
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restrict_sequence_name: []
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test_restrict_sequence_id: -1
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assert_single_seq: false
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only_test_set: false
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aux_dataset_kwargs:
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box_crop: true
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box_crop_context: 0.3
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image_width: 800
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image_height: 800
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remove_empty_masks: true
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path_manager: null
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data_loader_map_provider_SequenceDataLoaderMapProvider_args:
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batch_size: 1
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num_workers: 0
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dataset_len: 1000
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dataset_len_val: 1
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images_per_seq_options:
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- 2
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sample_consecutive_frames: false
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consecutive_frames_max_gap: 0
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consecutive_frames_max_gap_seconds: 0.1
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architecture: generic
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detect_anomaly: false
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eval_only: false
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exp_dir: ./data/default_experiment/
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exp_idx: 0
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gpu_idx: 0
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metric_print_interval: 5
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resume: true
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resume_epoch: -1
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seed: 0
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store_checkpoints: true
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store_checkpoints_purge: 1
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test_interval: -1
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test_when_finished: false
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validation_interval: 1
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visdom_env: ''
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visdom_port: 8097
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visdom_server: http://127.0.0.1
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visualize_interval: 1000
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clip_grad: 0.0
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hydra:
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run:
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dir: .
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output_subdir: null
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103
projects/implicitron_trainer/tests/test_experiment.py
Normal file
103
projects/implicitron_trainer/tests/test_experiment.py
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@ -0,0 +1,103 @@
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the BSD-style license found in the
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# LICENSE file in the root directory of this source tree.
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import logging
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import os
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import unittest
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from pathlib import Path
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import experiment
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import torch
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from iopath.common.file_io import PathManager
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from omegaconf import OmegaConf
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from pytorch3d.implicitron.dataset.json_index_dataset_map_provider import (
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JsonIndexDatasetMapProvider,
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)
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def interactive_testing_requested() -> bool:
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"""
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Certain tests are only useful when run interactively, and so are not regularly run.
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These are activated by this funciton returning True, which the user requests by
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setting the environment variable `PYTORCH3D_INTERACTIVE_TESTING` to 1.
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"""
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return os.environ.get("PYTORCH3D_INTERACTIVE_TESTING", "") == "1"
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DATA_DIR = Path(__file__).resolve().parent
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DEBUG: bool = False
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# TODO:
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# - sort out path_manager config. Here we monkeypatch to avoid
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# the problem.
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# - add enough files to skateboard_first_5 that this works on RE.
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# - share common code with PyTorch3D tests?
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# - deal with the temporary output files this test creates
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def get_path_manager(silence_logs: bool = False) -> PathManager:
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"""
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Returns a path manager which can access manifold internally.
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Args:
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silence_logs: Whether to reduce log output from iopath library.
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"""
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if silence_logs:
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logging.getLogger("iopath.fb.manifold").setLevel(logging.CRITICAL)
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logging.getLogger("iopath.common.file_io").setLevel(logging.CRITICAL)
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if os.environ.get("INSIDE_RE_WORKER", False):
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raise ValueError("Cannot get to manifold from RE")
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path_manager = PathManager()
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if os.environ.get("FB_TEST", False):
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from iopath.fb.manifold import ManifoldPathHandler
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path_manager.register_handler(ManifoldPathHandler())
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return path_manager
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def set_path_manager(self):
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self.path_manager = get_path_manager()
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class TestExperiment(unittest.TestCase):
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def setUp(self):
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self.maxDiff = None
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JsonIndexDatasetMapProvider.__post_init__ = set_path_manager
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def test_from_defaults(self):
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# Test making minimal changes to the dataclass defaults.
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if not interactive_testing_requested():
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return
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cfg = OmegaConf.structured(experiment.ExperimentConfig)
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cfg.data_source_args.dataset_map_provider_class_type = (
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"JsonIndexDatasetMapProvider"
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)
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dataset_args = (
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cfg.data_source_args.dataset_map_provider_JsonIndexDatasetMapProvider_args
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)
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dataloader_args = (
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cfg.data_source_args.data_loader_map_provider_SequenceDataLoaderMapProvider_args
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)
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dataset_args.category = "skateboard"
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dataset_args.test_restrict_sequence_id = 0
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dataset_args.dataset_root = "manifold://co3d/tree/extracted"
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dataset_args.limit_sequences_to = 5
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dataloader_args.dataset_len = 1
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cfg.solver_args.max_epochs = 2
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device = torch.device("cuda:0")
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experiment.run_training(cfg, device)
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def test_yaml_contents(self):
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cfg = OmegaConf.structured(experiment.ExperimentConfig)
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yaml = OmegaConf.to_yaml(cfg, sort_keys=False)
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if DEBUG:
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(DATA_DIR / "experiment.yaml").write_text(yaml)
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self.assertEqual(yaml, (DATA_DIR / "experiment.yaml").read_text())
|
@ -19,9 +19,9 @@ def interactive_testing_requested() -> bool:
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"""
|
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Certain tests are only useful when run interactively, and so are not regularly run.
|
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These are activated by this funciton returning True, which the user requests by
|
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setting the environment variable `PYTORCH3D_INTERACTIVE_TESTING`.
|
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setting the environment variable `PYTORCH3D_INTERACTIVE_TESTING` to 1.
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"""
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return os.environ.get("PYTORCH3D_INTERACTIVE_TESTING", False)
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return os.environ.get("PYTORCH3D_INTERACTIVE_TESTING", "") == "1"
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||||
|
||||
|
||||
def get_tests_dir() -> Path:
|
||||
|
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Reference in New Issue
Block a user