Fix docstrings

graphnet-team · Sep 2, 2024 · d6e7bed · d6e7bed
1 parent 9b6e568
commit d6e7bed
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Showing 2 changed files with 42 additions and 59 deletions.
diff --git a/src/graphnet/data/datamodule.py b/src/graphnet/data/datamodule.py
@@ -285,7 +285,8 @@ def _create_dataloader(
         if "batch_sampler" in dataloader_args.keys():
             if "sampler" not in dataloader_args.keys():
                 raise KeyError(
-                    "When specifying a `batch_sampler`, you must also provide `sampler`."
+                    "When specifying a `batch_sampler`,"
+                    "you must also provide `sampler`."
                 )
             # If there were no kwargs provided, set it to empty dict
             if "batch_sampler_kwargs" not in dataloader_args.keys():

diff --git a/src/graphnet/data/dataset/samplers.py b/src/graphnet/data/dataset/samplers.py
@@ -1,4 +1,29 @@
-"""`Sampler` and `BatchSampler` objects for `graphnet`."""
+"""`Sampler` and `BatchSampler` objects for `graphnet`.
+
+MIT License
+
+Copyright (c) 2023 DrHB
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+_____________________
+"""
+
 from typing import (
     Any,
     List,
@@ -21,30 +46,8 @@
 class RandomChunkSampler(Sampler[int]):
     """A `Sampler` that randomly selects chunks.
 
-    MIT License
-
-    Copyright (c) 2023 DrHB
-
-    Permission is hereby granted, free of charge, to any person obtaining a copy
-    of this software and associated documentation files (the "Software"), to deal
-    in the Software without restriction, including without limitation the rights
-    to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-    copies of the Software, and to permit persons to whom the Software is
-    furnished to do so, subject to the following conditions:
-
-    The above copyright notice and this permission notice shall be included in all
-    copies or substantial portions of the Software.
-
-    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-    IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-    FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-    AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-    LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-    OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-    SOFTWARE.
-    _____________________
-
-    Original implementation: https://github.com/DrHB/icecube-2nd-place/blob/main/src/dataset.py
+    Original implementation:
+    https://github.com/DrHB/icecube-2nd-place/blob/main/src/dataset.py
     """
 
     def __init__(
@@ -157,30 +160,8 @@ def gather_len_matched_buckets(
 class LenMatchBatchSampler(BatchSampler, Logger):
     """A `BatchSampler` that batches similar length events.
 
-    MIT License
-
-    Copyright (c) 2023 DrHB
-
-    Permission is hereby granted, free of charge, to any person obtaining a copy
-    of this software and associated documentation files (the "Software"), to deal
-    in the Software without restriction, including without limitation the rights
-    to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-    copies of the Software, and to permit persons to whom the Software is
-    furnished to do so, subject to the following conditions:
-
-    The above copyright notice and this permission notice shall be included in all
-    copies or substantial portions of the Software.
-
-    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-    IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-    FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-    AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-    LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-    OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-    SOFTWARE.
-    _____________________
-
-    Original implementation: https://github.com/DrHB/icecube-2nd-place/blob/main/src/dataset.py
+    Original implementation:
+    https://github.com/DrHB/icecube-2nd-place/blob/main/src/dataset.py
     """
 
     def __init__(
@@ -195,20 +176,21 @@ def __init__(
     ) -> None:
         """Construct `LenMatchBatchSampler`.
 
-        This `BatchSampler` groups data with similar lengths to be more efficient
-        in operations like masking for MultiHeadAttention. Since batch samplers
-        run on the main process and can result in a CPU bottleneck, `num_workers`
-        can be specified to use multiprocessing for creating the batches. The
-        `bucket_width` argument specifies how wide the bins are for grouping batches.
-        For example, with `bucket_width=16`, data with length [1, 16] are grouped into
-        a bucket, data with length [17, 32] into another, etc.
+        This `BatchSampler` groups data with similar lengths to be more
+        efficient in operations like masking for MultiHeadAttention. Since
+        batch samplers run on the main process and can result in a CPU
+        bottleneck, `num_workers` can be specified to use multiprocessing for
+        creating the batches. The `bucket_width` argument specifies how wide
+        the bins are for grouping batches. For example, with `bucket_width=16`,
+        data with length [1, 16] are grouped into a bucket, data with length
+        [17, 32] into another, etc.
 
         Args:
             sampler: A `Sampler` object that selects/draws data in some way.
             batch_size: Batch size.
             num_workers: Number of workers to spawn to create batches.
             bucket_width: Size of length buckets for grouping data.
-            chunks_per_segment: Number of chunks to group together for processing.
+            chunks_per_segment: Number of chunks to group together.
             multiprocessing_context: Start method for multiprocessing.
             drop_last: (Optional) Drop the last incomplete batch.
         """
@@ -237,7 +219,7 @@ def __iter__(self) -> Iterator[List[int]]:
             n_chunks = len(self.sampler.chunks)
             n_segments = n_chunks // self._chunks_per_segment
 
-            # Split indices into nearly equal-sized segments amongst the workers
+            # Split indices into nearly equal-sized segments amongst workers
             segments = [
                 range(
                     sum(self.sampler.chunks[: i * self._chunks_per_segment]),