` import tensorflow as tf
from clearml import Model
from clearml.model import InputModel

def get_model_id(model_name,tags = None):
print("Model name: ", model_name)
print("Model tags: ", tags)
response = Model.query_models(model_name=model_name,
tags=tags)
if not response:
raise ValueError('your model name and tags result in empty query')
model_data= None
for model_obj in response:
if model_obj.name == model_name:
model_data = model_obj
break
return model_data

def get_keras_model(model_name, model_tags, generate_model=True):
"""
Load model from clearml, transform it as a InputModel
then, converts to Keras model
"""

model_obj = get_model_id(model_name,
                        model_tags)
task_input_model = InputModel(model_obj.id)
if generate_model:
    # Construct Keras model
    model = tf.keras.models.model_from_config(task_input_model.config_dict)
    model.load_weights(task_input_model.get_local_copy())

    return task_input_model, model
else:
    return task_input_model

Call

_, model = get_keras_model(task_params['model_name'], task_params['model_tags']) `

VictoriousPenguin97 , can you please try with the latest version? 1.1.3 🙂

Thank you :)

My code are attached above. The version of Clearml is 1.0.5.

Example of filename: patch_ver3_dense_image_model_2 - srr_b4v2-large - step2 - patch_ver3_dense_image_model_2 - srr_b4v2-large - step1 - patch_ver3_dense_image_model_2_weights.03-1.31_weights.15-0.26_weights.10-0.18.h5

VictoriousPenguin97 , Hi 🙂

Can you provide a snippet of how you tried to download the file? Also what version of clearml are you using? Also can you please give an example of the filename you have on s3?

VictoriousPenguin97 , I managed to reproduce the issue with 1.1.3 as well. It should be fixed in the next version 🙂

Meanwhile as a workaround please try using shorter file name. The file name you provided is almost 200 characters long.

Keeping it under 150 characters will still work (I made sure to test it).