Updating cbn_sample_size to 250_000

* Updating cbn_sample_size

* Set cbn_sample_size default for the ACTGAN class in actgan_wrapper

* Update Docstrings

* changing None to 0

GitOrigin-RevId: 81b83d2f91fc794147a78c37474f8d53c62057eb

src/gretel_synthetics/actgan/actgan.py

@@ -206,8 +206,8 @@ class ACTGANSynthesizer(BaseSynthesizer):
             be replaced by a random value that is a known mode for a given column.
         cbn_sample_size:
             Number of rows to sample from each column for identifying clusters for the cluster-based normalizer.
-            This only applies to float columns. By default, no sampling is done and all values are considered,
-            which may be very slow.
+            This only applies to float columns. If set to ``0``, no sampling is done and all values are considered,
+            which may be very slow. Defaults to 250_000.
         log_frequency:
             Whether to use log frequency of categorical levels in conditional
             sampling. Defaults to ``True``.
@@ -239,7 +239,7 @@ def __init__(
         discriminator_steps: int = 1,
         binary_encoder_cutoff: int = 500,
         binary_encoder_nan_handler: Optional[str] = None,
-        cbn_sample_size: Optional[int] = None,
+        cbn_sample_size: Optional[int] = 250_000,
         log_frequency: bool = True,
         verbose: bool = False,
         epochs: int = 300,

src/gretel_synthetics/actgan/actgan_wrapper.py

@@ -279,8 +279,8 @@ class ACTGAN(_ACTGANModel):
             be replaced by a random value that is a known mode for a given column.
         cbn_sample_size:
             Number of rows to sample from each column for identifying clusters for the cluster-based normalizer.
-            This only applies to float columns. By default, no sampling is done and all values are considered,
-            which may be very slow.
+            This only applies to float columns. If set to ``0``, no sampling is done and all values are considered,
+            which may be very slow. Defaults to 250_000.
         log_frequency:
             Whether to use log frequency of categorical levels in conditional
             sampling. Defaults to ``True``.
@@ -331,7 +331,7 @@ def __init__(
         discriminator_steps: int = 1,
         binary_encoder_cutoff: int = 500,
         binary_encoder_nan_handler: Optional[str] = None,
-        cbn_sample_size: Optional[int] = None,
+        cbn_sample_size: Optional[int] = 250_000,
         log_frequency: bool = True,
         verbose: bool = False,
         epochs: int = 300,