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Add shuffling in Nanotron for subsequent epochs when data is repeated #247

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Add shuffling in Nanotron for subsequent epochs when data is repeated #247

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eab4770
Add shuffling for subsequent epochs when data is repeated
Lauler Nov 24, 2024
f060414
Simplify random seed in epoch data for reproducibility
Lauler Nov 28, 2024
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26 changes: 18 additions & 8 deletions src/nanotron/data/nanoset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -111,14 +111,24 @@ def build_nanoset_index(self) -> np.ndarray:
dataset_index, dataset_sample_index = build_nanoset_index_helper(
n_samples=samples_per_epoch, weights=self.dataset_weights, dataset_sizes=self.dataset_lengths
)
# Shuffle the indexes the same way
numpy_random_state = np.random.RandomState(self.random_seed)
numpy_random_state.shuffle(dataset_index)
numpy_random_state = np.random.RandomState(self.random_seed)
numpy_random_state.shuffle(dataset_sample_index)
# Concatenate num_epochs the shuffled indexes
dataset_index = np.concatenate([dataset_index for _ in range(num_epochs)])
dataset_sample_index = np.concatenate([dataset_sample_index for _ in range(num_epochs)])

# Shuffle indices in each epoch with different random seeds and concatenate them
dataset_indices = []
dataset_sample_indices = []
for num_epoch in range(num_epochs):
# Shuffle the sample and dataset indices in epoch with a given seed
numpy_random_state = np.random.RandomState(self.random_seed + num_epoch)
numpy_random_state.shuffle(dataset_index)
numpy_random_state = np.random.RandomState(self.random_seed + num_epoch)
numpy_random_state.shuffle(dataset_sample_index)

dataset_indices.append(dataset_index)
dataset_sample_indices.append(dataset_sample_index)

# Concatenate the within-epoch shuffled indices
dataset_index = np.concatenate(dataset_indices)
dataset_sample_index = np.concatenate(dataset_sample_indices)

# Just keep the necessary samples
dataset_index = dataset_index[: self.train_split_num_samples]
dataset_sample_index = dataset_sample_index[: self.train_split_num_samples]
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