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7 changes: 3 additions & 4 deletions init2winit/dataset_lib/fineweb_edu_10b_input_pipeline.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,6 @@
https://github.com/mlcommons/algorithmic-efficiency/blob/main/datasets/dataset_setup.py.
"""

# import tensorflow.compat.v2 as tf
import os
from absl import logging
from ml_collections.config_dict import config_dict
Expand All @@ -35,8 +34,7 @@
SHUFFLE_BUFFER_SIZE = 100_000
VOCAB_SIZE = 50_257

PAD_ID = tf.constant(-1, dtype=tf.int64)
# PAD_ID = -1
PAD_ID = -1

AUTOTUNE = tf.data.experimental.AUTOTUNE

Expand All @@ -61,6 +59,8 @@ def batch_with_padding(

# tf.data.Dataset.padded.batch pads elements in the batch so we call it
# again with batch_size=1 to pad each element in original batch.
if isinstance(padding_id, int):
padding_id = tf.constant(padding_id, dtype=tf.int64)
padded_batched_dataset = batched_dataset.padded_batch(
1, padded_shapes=padded_shapes, padding_values=padding_id
)
Expand Down Expand Up @@ -95,7 +95,6 @@ def get_fineweb_edu_dataset(
train_path = os.path.join(DATA_DIR, TRAIN_DIR)
val_path = os.path.join(DATA_DIR, VAL_DIR)

# Load datasets and cast to int32.
train_dataset = tf.data.Dataset.load(train_path)
val_dataset = tf.data.Dataset.load(val_path)

Expand Down
2 changes: 1 addition & 1 deletion init2winit/dataset_lib/test_fineweb_edu_10b_input_pipeline.py
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Expand Up @@ -26,7 +26,7 @@ class FinewebEdu10bInputPipelineTest(absltest.TestCase):

def test_batch_with_padding(self):
"""Test batching with padding."""
arr = np.arange(18, dtype=np.int32)
arr = np.arange(18, dtype=np.int64)
ds = tf.data.Dataset.from_tensor_slices(arr)
ds = ds.batch(
6,
Expand Down
4 changes: 2 additions & 2 deletions init2winit/dataset_lib/test_fineweb_edu_10b_mdlm.py
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Expand Up @@ -133,7 +133,7 @@ def test_eval_batch_padding_applied(self):
self.assertLen(batches, 2)

padded_batch = batches[1]
pad_id = int(input_pipeline.PAD_ID.numpy())
pad_id = input_pipeline.PAD_ID

# The second row of the padded batch should be all PAD_ID.
np.testing.assert_array_equal(padded_batch['inputs'][1], np.full(4, pad_id))
Expand All @@ -157,7 +157,7 @@ def test_eval_batch_padding_not_in_full_batches(self):

batches = list(valid_ds.as_numpy_iterator())
full_batch = batches[0]
pad_id = int(input_pipeline.PAD_ID.numpy())
pad_id = input_pipeline.PAD_ID

# No element in the full batch should be PAD_ID.
self.assertTrue(np.all(full_batch['inputs'] != pad_id))
Expand Down