Fix (examples/ptq): fix arguments typing and names

src/brevitas_examples/imagenet_classification/ptq/ptq_evaluate.py

@@ -2,6 +2,7 @@
 # SPDX-License-Identifier: BSD-3-Clause
 
 import argparse
+from functools import partial
 import os
 import random
 import warnings
@@ -38,6 +39,14 @@
 # Ignore warnings about __torch_function__
 warnings.filterwarnings("ignore")
 
+
+def parse_type(v, default_type):
+    if v == 'None':
+        return None
+    else:
+        return default_type(v)
+
+
 model_names = sorted(
     name for name in torchvision.models.__dict__ if name.islower() and not name.startswith("__") and
     callable(torchvision.models.__dict__[name]) and not name.startswith("get_"))
@@ -96,7 +105,7 @@
 parser.add_argument(
     '--bias-bit-width',
     default=32,
-    type=int,
+    type=partial(parse_type, default_type=int),
     choices=[32, 16, None],
     help='Bias bit width (default: 32)')
 parser.add_argument(
@@ -234,7 +243,7 @@
 add_bool_arg(parser, 'calibrate-bn', default=False, help='Calibrate BN (default: disabled)')
 add_bool_arg(
     parser,
-    'split-input',
+    'channel-splitting-split-input',
     default=False,
     help='Input Channels Splitting for channel splitting (default: disabled)')
 add_bool_arg(
@@ -311,7 +320,7 @@ def main():
         f"Weight quant calibration type: {args.weight_quant_calibration_type} - "
         f"Calibrate BN: {args.calibrate_bn} - "
         f"Channel Splitting Ratio: {args.channel_splitting_ratio} - "
-        f"Split Input: {args.split_input} - "
+        f"Split Input: {args.channel_splitting_split_input} - "
         f"Merge BN: {args.merge_bn}")
 
     # Get model-specific configurations about input shapes and normalization
@@ -358,7 +367,7 @@ def main():
             equalize_merge_bias=args.graph_eq_merge_bias,
             merge_bn=args.merge_bn,
             channel_splitting_ratio=args.channel_splitting_ratio,
-            channel_splitting_split_input=args.split_input)
+            channel_splitting_split_input=args.channel_splitting_split_input)
     else:
         raise RuntimeError(f"{args.target_backend} backend not supported.")