#movinet Add se_type option in tools/convert_3d_2plus1d.py

PiperOrigin-RevId: 420368239

official/vision/beta/projects/movinet/tools/convert_3d_2plus1d.py

@@ -29,6 +29,8 @@ flags.DEFINE_string(
     'Export path to save the saved_model file.')
 flags.DEFINE_string(
     'model_id', 'a0', 'MoViNet model name.')
+flags.DEFINE_string(
+    'se_type', '2plus3d', 'MoViNet model SE type.')
 flags.DEFINE_bool(
     'causal', True, 'Run the model in causal mode.')
 flags.DEFINE_bool(
@@ -46,6 +48,7 @@ def main(_) -> None:
   backbone_2plus1d = movinet.Movinet(
       model_id=FLAGS.model_id,
       causal=FLAGS.causal,
+      se_type=FLAGS.se_type,
       conv_type='2plus1d',
       use_positional_encoding=FLAGS.use_positional_encoding)
   model_2plus1d = movinet_model.MovinetClassifier(
@@ -56,6 +59,7 @@ def main(_) -> None:
   backbone_3d_2plus1d = movinet.Movinet(
       model_id=FLAGS.model_id,
       causal=FLAGS.causal,
+      se_type=FLAGS.se_type,
       conv_type='3d_2plus1d',
       use_positional_encoding=FLAGS.use_positional_encoding)
   model_3d_2plus1d = movinet_model.MovinetClassifier(

official/vision/beta/projects/movinet/tools/convert_3d_2plus1d_test.py

@@ -36,6 +36,7 @@ class Convert3d2plus1dTest(tf.test.TestCase):
     model_3d_2plus1d = movinet_model.MovinetClassifier(
         backbone=movinet.Movinet(
             model_id='a0',
+            se_type='2plus3d',
             conv_type='3d_2plus1d'),
         num_classes=600)
     model_3d_2plus1d.build([1, 1, 1, 1, 3])