# I am getting error while running the code in my own computer **URL:** \ **Category:** Convolutional Neural Networks\ **Tags:** coursera-platform\ **Created:** [March 1, 2022, 10:17am UTC](https://community.deeplearning.ai/t/i-am-getting-error-while-running-the-code-in-my-own-computer/104309 "2022-03-01T10:17:24Z")\ **Posts on this page:** 5\ **Page:** 1
**Author:** ![Nafisa\_Anjum\_Samia](https://avatars.discourse-cdn.com/v4/letter/n/2bfe46/32.png) [@Nafisa\_Anjum\_Samia](https://community.deeplearning.ai/u/Nafisa_Anjum_Samia)\ **Post date:** [March 1, 2022, 10:17am UTC](https://community.deeplearning.ai/t/i-am-getting-error-while-running-the-code-in-my-own-computer/104309/1 "2022-03-01T10:17:24Z")
Hi, I can run the code perfectly in coursera jupyter notebook, but while running into my computer, I have faced this problem. For the following code: ```auto from tensorflow.keras.models import model_from_json json_file = open('keras-facenet-h5/model.json', 'r') loaded_model_json = json_file.read() json_file.close() model = model_from_json(loaded_model_json) model.load_weights('keras-facenet-h5/model.h5') ``` I am getting this error: ```auto --------------------------------------------------------------------------- ValueError Traceback (most recent call last) C:\Users\NAFISA~1.SAM\AppData\Local\Temp/ipykernel_7476/324912946.py in 4 loaded_model_json = json_file.read() 5 json_file.close() ----> 6 model = model_from_json(loaded_model_json) 7 model.load_weights('keras-facenet-h5/model.h5') ~\anaconda3\lib\site-packages\keras\saving\model_config.py in model_from_json(json_string, custom_objects) 102 config = json_utils.decode(json_string) 103 from keras.layers import deserialize # pylint: disable=g-import-not-at-top --> 104 return deserialize(config, custom_objects=custom_objects) ~\anaconda3\lib\site-packages\keras\layers\serialization.py in deserialize(config, custom_objects) 205 """ 206 populate_deserializable_objects() --> 207 return generic_utils.deserialize_keras_object( 208 config, 209 module_objects=LOCAL.ALL_OBJECTS, ~\anaconda3\lib\site-packages\keras\utils\generic_utils.py in deserialize_keras_object(identifier, module_objects, custom_objects, printable_module_name) 677 678 if 'custom_objects' in arg_spec.args: --> 679 deserialized_obj = cls.from_config( 680 cls_config, 681 custom_objects=dict( ~\anaconda3\lib\site-packages\keras\engine\functional.py in from_config(cls, config, custom_objects) 706 if all(key in config for key in [ 707 'name', 'layers', 'input_layers', 'output_layers']): --> 708 input_tensors, output_tensors, created_layers = reconstruct_from_config( 709 config, custom_objects) 710 model = cls( ~\anaconda3\lib\site-packages\keras\engine\functional.py in reconstruct_from_config(config, custom_objects, created_layers) 1324 # First, we create all layers and enqueue nodes to be processed 1325 for layer_data in config['layers']: -> 1326 process_layer(layer_data) 1327 # Then we process nodes in order of layer depth. 1328 # Nodes that cannot yet be processed (if the inbound node ~\anaconda3\lib\site-packages\keras\engine\functional.py in process_layer(layer_data) 1306 from keras.layers import deserialize as deserialize_layer # pylint: disable=g-import-not-at-top 1307 -> 1308 layer = deserialize_layer(layer_data, custom_objects=custom_objects) 1309 created_layers[layer_name] = layer 1310 ~\anaconda3\lib\site-packages\keras\layers\serialization.py in deserialize(config, custom_objects) 205 """ 206 populate_deserializable_objects() --> 207 return generic_utils.deserialize_keras_object( 208 config, 209 module_objects=LOCAL.ALL_OBJECTS, ~\anaconda3\lib\site-packages\keras\utils\generic_utils.py in deserialize_keras_object(identifier, module_objects, custom_objects, printable_module_name) 677 678 if 'custom_objects' in arg_spec.args: --> 679 deserialized_obj = cls.from_config( 680 cls_config, 681 custom_objects=dict( ~\anaconda3\lib\site-packages\keras\layers\core\lambda_layer.py in from_config(cls, config, custom_objects) 301 def from_config(cls, config, custom_objects=None): 302 config = config.copy() --> 303 function = cls._parse_function_from_config(config, custom_objects, 304 'function', 'module', 305 'function_type') ~\anaconda3\lib\site-packages\keras\layers\core\lambda_layer.py in _parse_function_from_config(cls, config, custom_objects, func_attr_name, module_attr_name, func_type_attr_name) 356 elif function_type == 'lambda': 357 # Unsafe deserialization from bytecode --> 358 function = generic_utils.func_load(config[func_attr_name], globs=globs) 359 elif function_type == 'raw': 360 function = config[func_attr_name] ~\anaconda3\lib\site-packages\keras\utils\generic_utils.py in func_load(code, defaults, closure, globs) 791 except (UnicodeEncodeError, binascii.Error): 792 raw_code = code.encode('raw_unicode_escape') --> 793 code = marshal.loads(raw_code) 794 if globs is None: 795 globs = globals() ValueError: bad marshal data (unknown type code) ``` How can I solve this? ---
**Author:** ![paulinpaloalto](https://sea1.discourse-cdn.com/dlai/user_avatar/community.deeplearning.ai/paulinpaloalto/32/187_2.png) [@paulinpaloalto](https://community.deeplearning.ai/u/paulinpaloalto)\ **Post date:** [March 1, 2022, 5:05pm UTC](https://community.deeplearning.ai/t/i-am-getting-error-while-running-the-code-in-my-own-computer/104309/2 "2022-03-01T17:05:54Z")
There are no official instructions for running the assignments locally, but there are some threads with helpful instructions and pointers. Note that the notebooks are not “standalone” entities: they include a whole tree of files with each assignment. It doesn’t work just to bring down the notebook “ipynb” file itself: you need all the other associated files as well. You also need to install the same versions of all the supporting packages that the notebooks use, since there can be “versionitis” problems because everything mutates really quickly in this space. The notebooks are from April 2021 and you can’t just install the very latest version of TF, python and all the zillion packages and expect things to “just work”. [Here’s a thread](https://community.deeplearning.ai/t/downloading-entire-assignment/122407/2) about how to download all the files associated with a given assignment. [Here’s a thread](https://community.deeplearning.ai/t/dls-1-my-own-project-in-pycharm/74781) with some useful instructions about the “versionitis” issues, but, as you’ll quickly see from reading it, this is not a trivial exercise. ---
**Author:** ![Nafisa\_Anjum\_Samia](https://avatars.discourse-cdn.com/v4/letter/n/2bfe46/32.png) [@Nafisa\_Anjum\_Samia](https://community.deeplearning.ai/u/Nafisa_Anjum_Samia)\ **Post date:** [March 1, 2022, 5:29pm UTC](https://community.deeplearning.ai/t/i-am-getting-error-while-running-the-code-in-my-own-computer/104309/3 "2022-03-01T17:29:23Z")
Thank you so much for your reply. I didnt download only ipynb file, but I downloaded the whole folder, and try to explore more the code with different images, that was my target. I installed all the necessary libraries, and successfully import them, but I have no idea about this error and I couldnt solve it even I searched a lot. I will follow your instructions from the thread that you shared. Thanks again. ---
**Author:** ![paulinpaloalto](https://sea1.discourse-cdn.com/dlai/user_avatar/community.deeplearning.ai/paulinpaloalto/32/187_2.png) [@paulinpaloalto](https://community.deeplearning.ai/u/paulinpaloalto)\ **Post date:** [March 1, 2022, 5:40pm UTC](https://community.deeplearning.ai/t/i-am-getting-error-while-running-the-code-in-my-own-computer/104309/4 "2022-03-01T17:40:07Z")
Yes, those error traces are always difficult to decipher. My best guess is that it’s saying it doesn’t like the format of the h5 file. Maybe it’s a “versionitis” problem, but my suggestion would be to try opening and reading the h5 file just as a separate operation and see if you can get that to work. ---
**Author:** ![paulinpaloalto](https://sea1.discourse-cdn.com/dlai/user_avatar/community.deeplearning.ai/paulinpaloalto/32/187_2.png) [@paulinpaloalto](https://community.deeplearning.ai/u/paulinpaloalto)\ **Post date:** [March 1, 2022, 7:17pm UTC](https://community.deeplearning.ai/t/i-am-getting-error-while-running-the-code-in-my-own-computer/104309/5 "2022-03-01T19:17:53Z")
Maybe write the code to dump information about the contents of the h5 file and then run it both locally and in the notebook on the course website and see if the results differ. [Here’s a thread](https://community.deeplearning.ai/t/extra-data-sets-for-week-2/62324/5) which shows how to create an h5 file containing your own images. That may not be directly relevant to what you are doing here (since the h5 file contains the weights of the model, not data samples), but at least it shows you some of the h5 related python APIs.