fix cache_file_name docstring to make it explicit that it is a path

src/datasets/arrow_dataset.py

@@ -1163,7 +1163,7 @@ def map(
             keep_in_memory (`bool`, defaults to `False`): Keep the dataset in memory instead of writing it to a cache file.
             load_from_cache_file (`bool`, defaults to `True`): If a cache file storing the current computation from `function`
                 can be identified, use it instead of recomputing.
-            cache_file_name (`Optional[str]`, defaults to `None`): Provide the name of a cache file to use to store the
+            cache_file_name (`Optional[str]`, defaults to `None`): Provide the name of a path for the cache file. It is used to store the
                 results of the computation instead of the automatically generated cache file name.
             writer_batch_size (`int`, defaults to `1000`): Number of rows per write operation for the cache file writer.
                 Higher value gives smaller cache files, lower value consume less temporary memory while running `.map()`.
@@ -1369,7 +1369,7 @@ def _map_single(
             keep_in_memory (`bool`, defaults to `False`): Keep the dataset in memory instead of writing it to a cache file.
             load_from_cache_file (`bool`, defaults to `True`): If a cache file storing the current computation from `function`
                 can be identified, use it instead of recomputing.
-            cache_file_name (`Optional[str]`, defaults to `None`): Provide the name of a cache file to use to store the
+            cache_file_name (`Optional[str]`, defaults to `None`): Provide the name of a path for the cache file. It is used to store the
                 results of the computation instead of the automatically generated cache file name.
             writer_batch_size (`int`, defaults to `1000`): Number of rows per write operation for the cache file writer.
                 Higher value gives smaller cache files, lower value consume less temporary memory while running `.map()`.
@@ -1590,7 +1590,7 @@ def filter(
             keep_in_memory (`bool`, defaults to `False`): Keep the dataset in memory instead of writing it to a cache file.
             load_from_cache_file (`bool`, defaults to `True`): If a cache file storing the current computation from `function`
                 can be identified, use it instead of recomputing.
-            cache_file_name (`Optional[str]`, defaults to `None`): Provide the name of a cache file to use to store the
+            cache_file_name (`Optional[str]`, defaults to `None`): Provide the name of a path for the cache file. It is used to store the
                 results of the computation instead of the automatically generated cache file name.
             writer_batch_size (`int`, defaults to `1000`): Number of rows per write operation for the cache file writer.
                 Higher value gives smaller cache files, lower value consume less temporary memory while running `.map()`.
@@ -1660,7 +1660,7 @@ def flatten_indices(
 
         Args:
             keep_in_memory (`bool`, default: `False`): Keep the dataset in memory instead of writing it to a cache file.
-            cache_file_name (`Optional[str]`, defaults to `None`): Provide the name of a cache file to use to store the
+            cache_file_name (`Optional[str]`, defaults to `None`): Provide the name of a path for the cache file. It is used to store the
                 results of the computation instead of the automatically generated cache file name.
             writer_batch_size (`int`, defaults to `1000`): Number of rows per write operation for the cache file writer.
                 Higher value gives smaller cache files, lower value consume less temporary memory while running `.map()`.
@@ -1736,7 +1736,7 @@ def select(
         Args:
             `indices` (sequence, iterable, ndarray or Series): List or 1D-array of integer indices for indexing.
             `keep_in_memory` (`bool`, default: `False`): Keep the indices mapping in memory instead of writing it to a cache file.
-            `indices_cache_file_name` (`Optional[str]`, default: `None`): Provide the name of a cache file to use to store the
+            `indices_cache_file_name` (`Optional[str]`, default: `None`): Provide the name of a path for the cache file. It is used to store the
                 indices mapping instead of the automatically generated cache file name.
             `writer_batch_size` (`int`, default: `1000`): Number of rows per write operation for the cache file writer.
                 Higher value gives smaller cache files, lower value consume less temporary memory while running `.map()`.
@@ -1830,7 +1830,7 @@ def sort(
             keep_in_memory (`bool`, defaults to `False`): Keep the sorted indices in memory instead of writing it to a cache file.
             load_from_cache_file (`bool`, defaults to `True`): If a cache file storing the sorted indices
                 can be identified, use it instead of recomputing.
-            indices_cache_file_name (`Optional[str]`, defaults to `None`): Provide the name of a cache file to use to store the
+            indices_cache_file_name (`Optional[str]`, defaults to `None`): Provide the name of a path for the cache file. It is used to store the
                 sorted indices instead of the automatically generated cache file name.
             writer_batch_size (`int`, defaults to `1000`): Number of rows per write operation for the cache file writer.
                 Higher value gives smaller cache files, lower value consume less temporary memory.
@@ -1906,7 +1906,7 @@ def shuffle(
             keep_in_memory (`bool`, defaults to `False`): Keep the shuffled indices in memory instead of writing it to a cache file.
             load_from_cache_file (`bool`, defaults to `True`): If a cache file storing the shuffled indices
                 can be identified, use it instead of recomputing.
-            indices_cache_file_name (`Optional[str]`, defaults to `None`): Provide the name of a cache file to use to store the
+            indices_cache_file_name (`Optional[str]`, defaults to `None`): Provide the name of a path for the cache file. It is used to store the
                 shuffled indices instead of the automatically generated cache file name.
             writer_batch_size (`int`, defaults to `1000`): Number of rows per write operation for the cache file writer.
                 Higher value gives smaller cache files, lower value consume less temporary memory while running `.map()`.
@@ -1998,9 +1998,9 @@ def train_test_split(
             keep_in_memory (`bool`, defaults to `False`): Keep the splits indices in memory instead of writing it to a cache file.
             load_from_cache_file (`bool`, defaults to `True`): If a cache file storing the splits indices
                 can be identified, use it instead of recomputing.
-            train_cache_file_name (`Optional[str]`, defaults to `None`): Provide the name of a cache file to use to store the
+            train_cache_file_name (`Optional[str]`, defaults to `None`): Provide the name of a path for the cache file. It is used to store the
                 train split indices instead of the automatically generated cache file name.
-            test_cache_file_name (`Optional[str]`, defaults to `None`): Provide the name of a cache file to use to store the
+            test_cache_file_name (`Optional[str]`, defaults to `None`): Provide the name of a path for the cache file. It is used to store the
                 test split indices instead of the automatically generated cache file name.
             writer_batch_size (`int`, defaults to `1000`): Number of rows per write operation for the cache file writer.
                 Higher value gives smaller cache files, lower value consume less temporary memory while running `.map()`.
@@ -2183,7 +2183,7 @@ def shard(
             keep_in_memory (`bool`, defaults to `False`): Keep the dataset in memory instead of writing it to a cache file.
             load_from_cache_file (`bool`, defaults to `True`): If a cache file storing the current computation from `function`
                 can be identified, use it instead of recomputing.
-            indices_cache_file_name (`Optional[str]`, defaults to `None`): Provide the name of a cache file to use to store the
+            indices_cache_file_name (`Optional[str]`, defaults to `None`): Provide the name of a path for the cache file. It is used to store the
                 indices of each shard instead of the automatically generated cache file name.
             writer_batch_size (`int`, defaults to `1000`): Number of rows per write operation for the cache file writer.
                 Higher value gives smaller cache files, lower value consume less temporary memory while running `.map()`.

src/datasets/dataset_dict.py

@@ -267,7 +267,7 @@ def map(
             keep_in_memory (`bool`, defaults to `False`): Keep the dataset in memory instead of writing it to a cache file.
             load_from_cache_file (`bool`, defaults to `True`): If a cache file storing the current computation from `function`
                 can be identified, use it instead of recomputing.
-            cache_file_names (`Optional[Dict[str, str]]`, defaults to `None`): Provide the name of a cache file to use to store the
+            cache_file_names (`Optional[Dict[str, str]]`, defaults to `None`): Provide the name of a path for the cache file. It is used to store the
                 results of the computation instead of the automatically generated cache file name.
                 You have to provide one :obj:`cache_file_name` per dataset in the dataset dictionary.
             writer_batch_size (`int`, defaults to `1000`): Number of rows per write operation for the cache file writer.
@@ -337,7 +337,7 @@ def filter(
             keep_in_memory (`bool`, defaults to `False`): Keep the dataset in memory instead of writing it to a cache file.
             load_from_cache_file (`bool`, defaults to `True`): If a cache file storing the current computation from `function`
                 can be identified, use it instead of recomputing.
-            cache_file_names (`Optional[Dict[str, str]]`, defaults to `None`): Provide the name of a cache file to use to store the
+            cache_file_names (`Optional[Dict[str, str]]`, defaults to `None`): Provide the name of a path for the cache file. It is used to store the
                 results of the computation instead of the automatically generated cache file name.
                 You have to provide one :obj:`cache_file_name` per dataset in the dataset dictionary.
             writer_batch_size (`int`, defaults to `1000`): Number of rows per write operation for the cache file writer.
@@ -394,7 +394,7 @@ def sort(
             keep_in_memory (`bool`, defaults to `False`): Keep the dataset in memory instead of writing it to a cache file.
             load_from_cache_file (`bool`, defaults to `True`): If a cache file storing the current computation from `function`
                 can be identified, use it instead of recomputing.
-            indices_cache_file_names (`Optional[Dict[str, str]]`, defaults to `None`): Provide the name of a cache file to use to store the
+            indices_cache_file_names (`Optional[Dict[str, str]]`, defaults to `None`): Provide the name of a path for the cache file. It is used to store the
                 indices mapping instead of the automatically generated cache file name.
                 You have to provide one :obj:`cache_file_name` per dataset in the dataset dictionary.
             writer_batch_size (`int`, defaults to `1000`): Number of rows per write operation for the cache file writer.
@@ -446,7 +446,7 @@ def shuffle(
             keep_in_memory (`bool`, defaults to `False`): Keep the dataset in memory instead of writing it to a cache file.
             load_from_cache_file (`bool`, defaults to `True`): If a cache file storing the current computation from `function`
                 can be identified, use it instead of recomputing.
-            indices_cache_file_names (`Optional[Dict[str, str]]`, default: `None`): Provide the name of a cache file to use to store the
+            indices_cache_file_names (`Optional[Dict[str, str]]`, default: `None`): Provide the name of a path for the cache file. It is used to store the
                 indices mappings instead of the automatically generated cache file name.
                 You have to provide one :obj:`cache_file_name` per dataset in the dataset dictionary.
             writer_batch_size (`int`, defaults to `1000`): Number of rows per write operation for the cache file writer.