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ValueError: Unrecognized keyword arguments: ['input_dtype'] #34
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HI @RakeshPardeshi. Not sure, but errors like this usually mean that some environment dependencies are incorrect. Some things to check:
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Hi @nikicc, Thank you for your reply. I tried to install the packages as per the version s specified. However, while installing h5py, I am getting following error (last few lines are copied): creating build\temp.win-amd64-cpython-39\Release\Users\DELL\AppData\Local\Temp\pip-install-37o7nv9m\h5py_0f53c4d0f2c943db9d15b7a23cb8aa15\h5py note: This error originates from a subprocess, and is likely not a problem with pip. × Encountered error while trying to install package. note: This is an issue with the package mentioned above, not pip. |
I'm not sure what is causing this issue 🤔 |
Hello :) But the problem was here : I couldn't return to the past and I have many errors. and the final is here : Exception encountered: Unrecognized keyword arguments: ['input_dtype']` Do I need to uninstall python 3 and reinstall it without tensorflow ? (and just unistall python will be feasible ?) Thank you for your help :) |
I don't think you need to uninstall Python 3. If you only uninstall the dependencies, and then reinstall the right versions back, you should be good to go. |
I tryied to uninstall and reinstall. But the numpy version seems to have problems to install : × python setup.py egg_info did not run successfully.
note: This error originates from a subprocess, and is likely not a problem with pip. × Encountered error while generating package metadata. note: This is an issue with the package mentioned above, not pip. But this one is installed without problem : |
I am getting an error while using below code from the python library. Please can anyone help to resolve it?
model = EmotionPredictor(classification='ekman', setting='mc')
model.predict_probabilities(FJ_FP['Cleaned'])
ValueError Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_1676\1528171436.py in
----> 1 model = EmotionPredictor(classification='ekman', setting='mc')
2 model.predict_probabilities(FJ_FP['Cleaned'])
~\Documents\DSA_Task\AbhishekPoddar\Code\emotion_predictor.py in init(self, classification, setting, use_unison_model)
28 self.setting = setting
29 self.use_unison_model = use_unison_model
---> 30 self.model = self._get_model()
31 self.embeddings_model = self._get_embeddings_model()
32 self.char_to_ind = self._get_char_mapping()
~\Documents\DSA_Task\AbhishekPoddar\Code\emotion_predictor.py in _get_model(self)
40 self.setting,
41 )
---> 42 return load_model(self._loaded_model_filename)
43
44 def _get_embeddings_model(self):
~\anaconda3\lib\site-packages\keras\utils\traceback_utils.py in error_handler(*args, **kwargs)
68 # To get the full stack trace, call:
69 #
tf.debugging.disable_traceback_filtering()
---> 70 raise e.with_traceback(filtered_tb) from None
71 finally:
72 del filtered_tb
~\anaconda3\lib\site-packages\keras\engine\input_layer.py in init(self, input_shape, batch_size, dtype, input_tensor, sparse, name, ragged, type_spec, **kwargs)
150 input_shape = batch_input_shape[1:]
151 if kwargs:
--> 152 raise ValueError(
153 f"Unrecognized keyword arguments: {list(kwargs.keys())}"
154 )
ValueError: Unrecognized keyword arguments: ['input_dtype']
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