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Commit c516fb49 authored by A. Unique TensorFlower's avatar A. Unique TensorFlower
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Fix comments in wmt_dataloader to match the actual behavior. 

PiperOrigin-RevId: 359357110
parent 81419766
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official/nlp/data/wmt_dataloader.py
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...@@ -14,7 +14,7 @@ ...@@ -14,7 +14,7 @@
# ============================================================================== # ==============================================================================
"""Input pipeline for the transformer model to read, filter, and batch examples. """Input pipeline for the transformer model to read, filter, and batch examples.
1. Batching scheme Batching scheme
Prior to batching, elements in the dataset are grouped by length (max between Prior to batching, elements in the dataset are grouped by length (max between
'inputs' and 'targets' length). Each group is then batched such that: 'inputs' and 'targets' length). Each group is then batched such that:
...@@ -60,8 +60,8 @@ def _create_min_max_boundaries(max_length, ...@@ -60,8 +60,8 @@ def _create_min_max_boundaries(max_length,
For example, when max_length=24, min_boundary=4 and boundary_scale=2, the For example, when max_length=24, min_boundary=4 and boundary_scale=2, the
returned values will be: returned values will be:
buckets_min = [0, 4, 8, 16, 24] buckets_min = [0, 4, 8, 16]
buckets_max = [4, 8, 16, 24, 25] buckets_max = [4, 8, 16, 25]
Args: Args:
max_length: The maximum length of example in dataset. max_length: The maximum length of example in dataset.
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