tensorflow/models · error
Unsupported converted_model: %s
Error message
Unsupported converted_model: %s
What it means
Error "Unsupported converted_model: %s" thrown in tensorflow/models.
Source
Thrown at official/nlp/tools/tf2_albert_encoder_checkpoint_converter.py:145
# Create a temporary V1 name-converted checkpoint in the output directory.
temporary_checkpoint_dir = os.path.join(output_dir, "temp_v1")
temporary_checkpoint = os.path.join(temporary_checkpoint_dir, "ckpt")
tf1_bert_checkpoint_converter_lib.convert(
checkpoint_from_path=v1_checkpoint,
checkpoint_to_path=temporary_checkpoint,
num_heads=bert_config.num_attention_heads,
name_replacements=ALBERT_NAME_REPLACEMENTS,
permutations=tf1_bert_checkpoint_converter_lib.BERT_V2_PERMUTATIONS,
exclude_patterns=["adam", "Adam"])
# Create a V2 checkpoint from the temporary checkpoint.
if converted_model == "encoder":
model = _create_albert_model(bert_config)
elif converted_model == "pretrainer":
model = _create_pretrainer_model(bert_config)
else:
raise ValueError("Unsupported converted_model: %s" % converted_model)
tf1_bert_checkpoint_converter_lib.create_v2_checkpoint(
model, temporary_checkpoint, output_path, checkpoint_model_name)
# Clean up the temporary checkpoint, if it exists.
try:
tf.io.gfile.rmtree(temporary_checkpoint_dir)
except tf.errors.OpError:
# If it doesn't exist, we don't need to clean it up; continue.
pass
def main(_):
output_path = FLAGS.converted_checkpoint_path
v1_checkpoint = FLAGS.checkpoint_to_convert
checkpoint_model_name = FLAGS.checkpoint_model_name
converted_model = FLAGS.converted_model
albert_config = configs.AlbertConfig.from_json_file(FLAGS.albert_config_file)View on GitHub (pinned to e006f5f0d5)
When it happens
Trigger: Thrown at official/nlp/tools/tf2_albert_encoder_checkpoint_converter.py:145 when the library encounters an invalid state.
Common situations: See trigger scenarios.
AI-assisted analysis of tensorflow/models@e006f5f0d5 (2026-08-24).
Data as JSON: /api/errors/190578f8fc75baf0.
Report an issue: GitHub.