ENTER THE CODE YOU WANT TO TRAIN IN YOUR MODEL : tensorflow tf.keras tf.keras.layers LSTM
==== TRAINING START ====
2022-01-08 18:24:14.308919: W tensorflow/core/platform/profile_utils/cpu_utils.cc:128] Failed to get CPU frequency: 0 Hz
Epoch 1/100
3/3 [==============================] - 1s 59ms/step - loss: 4.7865 - acc: 0.0532
Epoch 2/100
3/3 [==============================] - 0s 62ms/step - loss: 3.9297 - acc: 0.2872
Epoch 3/100
3/3 [==============================] - 0s 58ms/step - loss: 2.9941 - acc: 0.5532
...
Epoch 31/100
3/3 [==============================] - 0s 75ms/step - loss: 0.2747 - acc: 0.8617
Epoch 32/100
3/3 [==============================] - 0s 65ms/step - loss: 0.2700 - acc: 0.8298
==== TRAINING DONE ====
Now, Load the best weights on your model.

ENTER THE UNCOMPLETED CODE YOU WANT TO COMPLETE : t tf te l la li k ke tf.kera tf.keras.l
t  - best recommendation : tensorflow
		 - all recommendations :  ['tensorflow']
tf  - best recommendation : tf.keras
		 - all recommendations :  ['tfkeras', 'tf.keras']
te  - best recommendation : tensorflow
		 - all recommendations :  ['tensorflow']
l  - best recommendation : list
		 - all recommendations :  ['list', 'layers']
la  - best recommendation : lange
		 - all recommendations :  ['layers', 'lange']
li  - best recommendation : list
		 - all recommendations :  ['list']
k  - best recommendation : keras
		 - all recommendations :  ['keras']
ke  - best recommendation : keras
		 - all recommendations :  ['keras']
tf.kera  - best recommendation : tf.keras
		 - all recommendations :  []
tf.keras.l  - best recommendation : tf.keras.layers
		 - all recommendations :  ['tf.keras.layers']

Do you want to check only the recommendations? (y/n) : y
['tensorflow'], 
['tfkeras', 'tf.keras'], 
['tensorflow'], 
['list', 'layers'], 
['layers', 'lange'], 
['list'], 
['keras'], 
['keras'], 
[], 
['tf.keras.layers']

samp_model = auto_coding(new_code=samp_text,
                      # verbose=0,
                       batch_size=100,
                       epochs=200,
                       patience=10,
                       model_summary=True,
                       model_save=True,
                       model_name='samp_test', # samp_test/samp_test.h5
                       model_load=True,
                       data_split=True,
                       data_split_num=3 # the number into which users want to split the data
                      )

t  - best match : tf
	 - all recommendations :  ['tensorflow', 'tf']
tup  - best match : tuple
	 - all recommendations :  []
p  - best match : pd
	 - all recommendations :  ['plt', 'pd', 'pandas']
li  - best match : list
	 - all recommendations :  []
d  - best match : dataset
	 - all recommendations :  ['dic', 'dataset']
I  - best match : Import
	 - all recommendations :  []
so  - best match : sort
	 - all recommendations :  ['sort']
m  - best match : matplotlib.pyplot
	 - all recommendations :  []
Accuracy for Best:  0.875
Accuracy for Recommendations :  1.0