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WaqasSultani avatar WaqasSultani commented on July 3, 2024

I think you have different keras ( and backend theano version) compared to what I used in experiments

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bardia-esm avatar bardia-esm commented on July 3, 2024

Hello @WaqasSultani thanks for your great work, so I guess I have to use the older version of keras

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Singapore-mor avatar Singapore-mor commented on July 3, 2024

Hello @WaqasSultani thanks for your great work, so I guess I have to use the older version of keras

Hi BaRdia-eSm i ,
when I try to run Demo.py, i confronted the same problem
Exception has occurred: ValueError
I tried to use the older version of keras, keras 1.10
but it occurs
AttributeError: module 'tensorflow' has no attribute 'python'
I don't know what happened

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libb999 avatar libb999 commented on July 3, 2024

Hello @WaqasSultani thanks for your great work, so I guess I have to use the older version of keras

Hi BaRdia-eSm i ,
when I try to run Demo.py, i confronted the same problem
Exception has occurred: ValueError
I tried to use the older version of keras, keras 1.10
but it occurs
AttributeError: module 'tensorflow' has no attribute 'python'
I don't know what happened

Hi,I meet the same problem: AttributeError: module 'tensorflow' has no attribute 'python'
can you tell me how to solve it?
thank you very much

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iShahad97 avatar iShahad97 commented on July 3, 2024

@libb999 & @Singapore-mor, you have to change the backend from tensorflow to theano, there are two ways:

  1. Configure the file "$ HOME / .keras / keras.json" and set "theano" as back-end:

{
"image_data_format": "channels_last",
"epsilon": 1e-07,
"floatx": "float32",
"backend": "theano"
}
2. Use this code:
def set_keras_backend(backend):

if K.backend() != backend:
os.environ['KERAS_BACKEND'] = backend
importlib.reload(K)
assert K.backend() == backend

set_keras_backend("theano")

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sahilsingh31 avatar sahilsingh31 commented on July 3, 2024

File "/home/sahilsingh/.local/lib/python3.6/site-packages/keras/utils/generic_utils.py", line 129, in deserialize_keras_object
raise ValueError('Improper config format: ' + str(config))

ValueError: Improper config format: {'l2': 0.0010000000474974513, 'name': 'WeightRegularizer', 'l1': 0.0}

how to solve this error, i tried for various solutions over internet but didn't got one

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sanjayroka05 avatar sanjayroka05 commented on July 3, 2024

File "/home/sahilsingh/.local/lib/python3.6/site-packages/keras/utils/generic_utils.py", line 129, in deserialize_keras_object
raise ValueError('Improper config format: ' + str(config))

ValueError: Improper config format: {'l2': 0.0010000000474974513, 'name': 'WeightRegularizer', 'l1': 0.0}

how to solve this error, i tried for various solutions over internet but didn't got one

I'm also having the same errror...

ValueError: Improper config format: {'l2': 0.0010000000474974513, 'name': 'WeightRegularizer', 'l1': 0.0}

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Angel3636 avatar Angel3636 commented on July 3, 2024

File "/home/sahilsingh/.local/lib/python3.6/site-packages/keras/utils/generic_utils.py", line 129, in deserialize_keras_object
raise ValueError('Improper config format: ' + str(config))
ValueError: Improper config format: {'l2': 0.0010000000474974513, 'name': 'WeightRegularizer', 'l1': 0.0}
how to solve this error, i tried for various solutions over internet but didn't got one

I'm also having the same errror...

ValueError: Improper config format: {'l2': 0.0010000000474974513, 'name': 'WeightRegularizer', 'l1': 0.0}

Hello, is anyone got the solution for this?

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jiafeixiaoye avatar jiafeixiaoye commented on July 3, 2024

File "/home/sahilsingh/.local/lib/python3.6/site-packages/keras/utils/generic_utils.py", line 129, in deserialize_keras_object
raise ValueError('Improper config format: ' + str(config))

ValueError: Improper config format: {'l2': 0.0010000000474974513, 'name': 'WeightRegularizer', 'l1': 0.0}

how to solve this error, i tried for various solutions over internet but didn't got one

It seems the official model is written by Keras1 and you installed Keras2. You can modify the model file with Keras2 format.
Here I replace "W_regularizer": {"l2": 0.0010000000474974513, "name": "WeightRegularizer", "l1": 0.0}
with "kernel_regularizer": {"class_name": "L1L2", "config": {"l2": 0.0010000000474974513, "l1": 0.0}}
and it works.

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