Fixes to CO3Dv2 provider.

Summary:
1. Random sampling of num batches without replacement not supported.
2.Providers should implement the interface for the training loop to work.

Reviewed By: bottler, davnov134

Differential Revision: D37815388

fbshipit-source-id: 8a2795b524e733f07346ffdb20a9c0eb1a2b8190

Author: shapovalov

projects/implicitron_trainer/tests/experiment.yaml

@@ -335,6 +335,47 @@ data_source_args:
       sort_frames: false
     path_manager_factory_PathManagerFactory_args:
       silence_logs: true
+  dataset_map_provider_JsonIndexDatasetMapProviderV2_args:
+    category: ???
+    subset_name: ???
+    dataset_root: ''
+    test_on_train: false
+    only_test_set: false
+    load_eval_batches: true
+    dataset_class_type: JsonIndexDataset
+    path_manager_factory_class_type: PathManagerFactory
+    dataset_JsonIndexDataset_args:
+      path_manager: null
+      frame_annotations_file: ''
+      sequence_annotations_file: ''
+      subset_lists_file: ''
+      subsets: null
+      limit_to: 0
+      limit_sequences_to: 0
+      pick_sequence: []
+      exclude_sequence: []
+      limit_category_to: []
+      dataset_root: ''
+      load_images: true
+      load_depths: true
+      load_depth_masks: true
+      load_masks: true
+      load_point_clouds: false
+      max_points: 0
+      mask_images: false
+      mask_depths: false
+      image_height: 800
+      image_width: 800
+      box_crop: true
+      box_crop_mask_thr: 0.4
+      box_crop_context: 0.3
+      remove_empty_masks: true
+      n_frames_per_sequence: -1
+      seed: 0
+      sort_frames: false
+      eval_batches: null
+    path_manager_factory_PathManagerFactory_args:
+      silence_logs: true
   dataset_map_provider_LlffDatasetMapProvider_args:
     base_dir: ???
     object_name: ???

pytorch3d/implicitron/dataset/data_loader_map_provider.py

@@ -354,9 +354,13 @@ def _simple_loader(
         """
         if num_batches > 0:
             num_samples = self.batch_size * num_batches
+            replacement = True
         else:
             num_samples = None
-        sampler = RandomSampler(dataset, replacement=False, num_samples=num_samples)
+            replacement = False
+        sampler = RandomSampler(
+            dataset, replacement=replacement, num_samples=num_samples
+        )
         batch_sampler = BatchSampler(sampler, self.batch_size, drop_last=True)
         return DataLoader(
             dataset,

pytorch3d/implicitron/dataset/data_source.py

@@ -17,6 +17,7 @@
 from .data_loader_map_provider import DataLoaderMap, DataLoaderMapProviderBase
 from .dataset_map_provider import DatasetMap, DatasetMapProviderBase, Task
 from .json_index_dataset_map_provider import JsonIndexDatasetMapProvider  # noqa
+from .json_index_dataset_map_provider_v2 import JsonIndexDatasetMapProviderV2  # noqa
 from .llff_dataset_map_provider import LlffDatasetMapProvider  # noqa
 
 

pytorch3d/implicitron/dataset/json_index_dataset_map_provider_v2.py

@@ -9,12 +9,13 @@
 import logging
 import os
 import warnings
-from typing import Dict, List, Type
+from typing import Dict, List, Optional, Type
 
 from pytorch3d.implicitron.dataset.dataset_map_provider import (
     DatasetMap,
     DatasetMapProviderBase,
     PathManagerFactory,
+    Task,
 )
 from pytorch3d.implicitron.dataset.json_index_dataset import JsonIndexDataset
 from pytorch3d.implicitron.tools.config import (
@@ -23,6 +24,8 @@
     run_auto_creation,
 )
 
+from pytorch3d.renderer.cameras import CamerasBase
+
 
 _CO3DV2_DATASET_ROOT: str = os.getenv("CO3DV2_DATASET_ROOT", "")
 
@@ -296,6 +299,18 @@ def get_category_to_subset_name_list(self) -> Dict[str, List[str]]:
         )
         return category_to_subset_name_list
 
+    def get_task(self) -> Task:  # TODO: we plan to get rid of tasks
+        return {
+            "manyview": Task.SINGLE_SEQUENCE,
+            "fewview": Task.MULTI_SEQUENCE,
+        }[self.subset_name.split("_")[0]]
+
+    def get_all_train_cameras(self) -> Optional[CamerasBase]:
+        # pyre-ignore[16]
+        train_dataset = self.dataset_map.train
+        assert isinstance(train_dataset, JsonIndexDataset)
+        return train_dataset.get_all_train_cameras()
+
     def _load_annotation_json(self, json_filename: str):
         full_path = os.path.join(
             self.dataset_root,