address some comments

python/python/lance/tf/data.py

@@ -25,7 +25,7 @@
 
 import logging
 from pathlib import Path
-from typing import List, Optional, Union
+from typing import Iterable, List, Optional, Union
 
 import lance
 import numpy as np
@@ -61,7 +61,12 @@ def arrow_data_type_to_tf(dt: pa.DataType) -> tf.DType:
         return tf.float32
     elif pa.types.is_float64(dt):
         return tf.float64
-    elif pa.types.is_string(dt) or pa.types.is_binary(dt):
+    elif (
+        pa.types.is_string(dt)
+        or pa.types.is_large_string(dt)
+        or pa.types.is_binary(dt)
+        or pa.types.is_large_binary(dt)
+    ):
         return tf.string
 
     raise TypeError(f"Arrow/Tf conversion: Unsupported arrow data type: {dt}")
@@ -76,7 +81,11 @@ def data_type_to_tensor_spec(dt: pa.DataType) -> tf.TensorSpec:
         or pa.types.is_string(dt)
     ):
         return tf.TensorSpec(shape=(None,), dtype=arrow_data_type_to_tf(dt))
-    elif pa.types.is_list(dt):
+    elif pa.types.is_fixed_size_list(dt):
+        return tf.TensorSpec(
+            shape=(dt.list_size, None), dtype=arrow_data_type_to_tf(dt.value_type)
+        )
+    elif pa.types.is_list(dt) or pa.types.is_large_list(dt):
         return tf.TensorSpec(
             shape=(
                 None,
@@ -103,7 +112,7 @@ def from_lance(
     columns: Optional[List[str]] = None,
     batch_size: int = 256,
     filter: Optional[str] = None,
-    fragments: Union[List[LanceFragment], tf.data.Dataset] = None,
+    fragments: Union[Iterable[LanceFragment], tf.data.Dataset] = None,
 ) -> tf.data.Dataset:
     """Create a ``tf.data.Dataset`` from a Lance dataset.
 
@@ -112,7 +121,8 @@ def from_lance(
     dataset : Union[str, Path, LanceDataset]
         Lance dataset or dataset URI/path.
     columns : Optional[List[str]], optional
-        List of columns to include in the output dataset, by default None
+        List of columns to include in the output dataset.
+        If not set, all columns will be read.
     batch_size : int, optional
         Batch size, by default 256
     filter : Optional[str], optional