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nesting n_known_frames_for_test

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Summary: Use generator.permutation instead of choice so that different options for n_known_frames_for_test are nested.

Reviewed By: davnov134

Differential Revision: D37210906

fbshipit-source-id: fd0d34ce62260417c3f63354a3f750aae9998b0d
This commit is contained in:
Jeremy Reizenstein 2022-06-20 13:47:47 -07:00 committed by Facebook GitHub Bot
parent cba26506b6
commit 28c1afaa9d
1 changed files with 5 additions and 3 deletions
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8
pytorch3d/implicitron/dataset/single_sequence_dataset.py
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@ -116,9 +116,11 @@ class SingleSceneDatasetMapProviderBase(DatasetMapProviderBase):
if set_eval_batches: if set_eval_batches:
generator = np.random.default_rng(seed=0) generator = np.random.default_rng(seed=0)
for batch in eval_batches: for batch in eval_batches:
to_add = generator.choice( # using permutation so that changes to n_known_frames_for_test
len(train_split), self.n_known_frames_for_test # result in consistent batches.
) to_add = generator.permutation(len(train_split))[
: self.n_known_frames_for_test
]
batch.extend((to_add + len(split)).tolist()) batch.extend((to_add + len(split)).tolist())
split = np.concatenate([split, train_split]) split = np.concatenate([split, train_split])
frame_types.extend([DATASET_TYPE_KNOWN] * len(train_split)) frame_types.extend([DATASET_TYPE_KNOWN] * len(train_split))