Attribute error occur in Lamdacallback

[prateekvyas1996]

I am using the latest version of tensorflow and keras and while running LRfinder class i got an error as shown below

---

AttributeError Traceback (most recent call last)
in
1 from keras_lr_finder.lr_finder import*
2 lr_finder = lf.LRFinder(model_seq)
----> 3 lr_finder.find(input_data, labels, start_lr=0.0001, end_lr=1, epochs=5)

D:\Deep_learning_projects\aryan\keras_lr_finder\lr_finder.py in find(self, x_train, y_train, start_lr, end_lr, batch_size, epochs, **kw_fit)
62 batch_size=batch_size, epochs=epochs,
63 callbacks=[callback],
---> 64 **kw_fit)
65
66 # Restore the weights to the state before model fitting

c:\programdata\anaconda3\envs\deeplearning\lib\site-packages\tensorflow\python\keras\engine\training.py in _method_wrapper(self, *args, **kwargs)
106 def _method_wrapper(self, *args, **kwargs):
107 if not self._in_multi_worker_mode(): # pylint: disable=protected-access
--> 108 return method(self, *args, **kwargs)
109
110 # Running inside run_distribute_coordinator already.

c:\programdata\anaconda3\envs\deeplearning\lib\site-packages\tensorflow\python\keras\engine\training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing)
1072 verbose=verbose,
1073 epochs=epochs,
-> 1074 steps=data_handler.inferred_steps)
1075
1076 self.stop_training = False

c:\programdata\anaconda3\envs\deeplearning\lib\site-packages\tensorflow\python\keras\callbacks.py in init(self, callbacks, add_history, add_progbar, model, **params)
233 # pylint: disable=protected-access
234 self._should_call_train_batch_hooks = any(
--> 235 cb._implements_train_batch_hooks() for cb in self.callbacks)
236 self._should_call_test_batch_hooks = any(
237 cb._implements_test_batch_hooks() for cb in self.callbacks)

c:\programdata\anaconda3\envs\deeplearning\lib\site-packages\tensorflow\python\keras\callbacks.py in (.0)
233 # pylint: disable=protected-access
234 self._should_call_train_batch_hooks = any(
--> 235 cb._implements_train_batch_hooks() for cb in self.callbacks)
236 self._should_call_test_batch_hooks = any(
237 cb._implements_test_batch_hooks() for cb in self.callbacks)

AttributeError: 'LambdaCallback' object has no attribute '_implements_train_batch_hooks'

[arthur-ver]

Try installing keras-lr-finder from git using pip install git+https://github.com/surmenok/keras_lr_finder, instead of pip install keras-lr-finder

I've had a similar error and it worked for me. Hope this helps you too!

[prateekvyas1996]

it works after upgrading keras

…

On Thu, Aug 20, 2020, 8:41 PM Arthur ***@***.***> wrote: Try installing keras-lr-finder from git using pip install git+ https://github.com/surmenok/keras_lr_finder, instead of pip install keras-lr-finder — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub <#31 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AG3OJZER52PFTECMTMIXKK3SBU4K3ANCNFSM4QFBCT7Q> .

[lydiazajiczek]

(This is for Keras/TensorFlow version 2.3.0)

If you are limited to what tensorflow/keras version you can install (because of the CUDA version you have installed, for example) I found that editing the import statements let me run this. Specifically:
import keras.backend as K --> replace all instances of K with tf.compat.v1.keras.backend
e.g. on line 24 of lr_finder.py:
lr = K.get_value(self.model.optimizer.lr) --> lr = tf.compat.v1.keras.backend.get_value(self.model.optimizer.lr)

I also had to change from keras.callbacks import LambdaCallback to from tensorflow.keras.callbacks import LambdaCallback