More rigorous shape inference in to_tf_dataset (#4763)

* More rigorous shape inference in to_tf_dataset

* Simplify the new shape inference

* Read length from Sequence features instead of just sampling batches

* make style

* Remove Sequence-specific code

Author: Rocketknight1

src/datasets/arrow_dataset.py

@@ -224,7 +224,7 @@ def _get_output_signature(
         collate_fn_args: dict,
         cols_to_retain: Optional[List[str]] = None,
         batch_size: Optional[int] = None,
-        num_test_batches: int = 10,
+        num_test_batches: int = 200,
     ):
         """Private method used by `to_tf_dataset()` to find the shapes and dtypes of samples from this dataset
            after being passed through the collate_fn. Tensorflow needs an exact signature for tf.numpy_function, so
@@ -253,11 +253,9 @@ def _get_output_signature(
 
         if len(dataset) == 0:
             raise ValueError("Unable to get the output signature because the dataset is empty.")
-        if batch_size is None:
-            test_batch_size = min(len(dataset), 8)
-        else:
+        if batch_size is not None:
             batch_size = min(len(dataset), batch_size)
-            test_batch_size = batch_size
+        test_batch_size = min(len(dataset), 2)
 
         test_batches = []
         for _ in range(num_test_batches):