i'm trying to import these :
from numpy import array
from keras.preprocessing.text import one_hot
from keras.preprocessing.sequence import pad_sequences
from keras.models import Sequential
from keras.layers.core import Activation, Dropout, Dense
from keras.layers import Flatten, LSTM
from keras.layers import GlobalMaxPooling1D
from keras.models import Model
But i'm getting error as cannot import name 'pad_sequences' from 'keras.preprocessing.sequence'
Can anyone help me here please?
Replace:
from keras.preprocessing.sequence import pad_sequences
With:
from keras_preprocessing.sequence import pad_sequences
you can use this. It is worked for me.
from tensorflow.keras.preprocessing.sequence import pad_sequences
According to the TensorFlow v2.10.0 doc, the correct path to pad_sequences is tf.keras.utils.pad_sequences. So in your script one should write:
from keras.utils import pad_sequences
It has resolved the problem for me.
most likely you are using tf version 2.9 - go back to 2.8 and the same path works
alternatively import it from keras.utils.data_utils import pad_sequences
TF is not so stable with paths - the best way is check their git source corresponding to the version you succeeded to install !! in the case of TF2.9 you can see how it is importedhere
You can use the following;
from tensorflow.keras.preprocessing.sequence import pad_sequences
The correct path to import is keras.io.preprocessing.sequence.pad_sequences. Your path lacks the io.
from keras.io.preprocessing.sequence import pad_sequences
I came across the same problem just now but still don't know what is going on(still waiting for an answer).
I gave up importing pad_sequences and write it in full and it works
keras.preprocessing.sequence.pad_sequences()
In their last update Kiras 2.11.0 they made few changes and improvements to their packages.
Considering your issue you should:
replace this:
from keras.preprocessing.sequence import pad_sequences
with this:
from keras_preprocessing.sequence import pad_sequences
from tensorflow.keras.preprocessing import sequence
worked for me
from keras.utils.data_utils import pad_sequences
use this instead.
Related
Trying to run---
import tensorflow as tf
from tensorflow import keras
from tensorflow.python.keras.models import Sequential
from tensorflow.python.keras.layers import Flatten, Dense
from tensorflow.python.keras.optimizers import SGD, Adam
import numpy as np
print(tf.__version__)
I get this error---
---------------------------------------------------------------------------
ImportError Traceback (most recent call last)
<ipython-input-8-f05f8f753c47> in <module>()
4 from tensorflow.python.keras.models import Sequential
5 from tensorflow.python.keras.layers import Flatten, Dense
----> 6 from tensorflow.python.keras.optimizers import SGD, Adam
7
8 import numpy as np
ImportError: cannot import name 'SGD' from 'tensorflow.python.keras.optimizers' (/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/optimizers.py)
---------------------------------------------------------------------------
NOTE: If your import is failing due to a missing package, you can
manually install dependencies using either !pip or !apt.
---------------------------------------------------------------------------
I'm studying machine learning in Google Colab.
I pasted the example code and run it, and get error message.
I could find similar errors in Google, but I couldn't find anything to solve this problem.
I tried 'from tensorflow.keras.optimizers import SGD, Adam', 'from tf.keras.optimizers import SGD, Adam', and 'from keras.optimizers import SGD, Adam'.
But everything didn't work.
try this:
from tensorflow.python.keras.optimizer_v1 import SGD
You need to mention the exact updated alias name while importing the model(Sequential),layers (Flatten, Dense) and optimizers (SGD, Adam).
Please try again using the below code in new Google Colab notebook.
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras.models import Sequential #removed python from each layer
from tensorflow.keras.layers import Flatten, Dense
from tensorflow.keras.optimizers import SGD, Adam
import numpy as np
print(tf.__version__)
Output:
2.8.2
This is the error I can't figure out.
module 'keras.backend' has no attribute 'unique_object_name'
This is what I'm importing:
import cv2
import os
from keras.models import load_model
import numpy as np
from pygame import mixer
import time
I get the error when I try and run this line:
model = load_model('C:/Users/Henry/Downloads/Drowsiness detection/Drowsiness detection/models/cnnCat2.h5')
Method keras.models.load_model() probably worked properly before Keras become part of Tensorflow.
If you are using newer version of tf you should call this to load model:
tf.keras.models.load_model()
I'm trying to implement learning rate scheduling in my convolutional neural network for which I implemented the ReduceLROnPlateau method but I encounter this error.
My list of imports
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import seaborn as sns
%matplotlib inline
import warnings
warnings.filterwarnings('ignore')
np.random.seed(0)
from sklearn.model_selection import train_test_split
from sklearn.metrics import confusion_matrix
import itertools
from keras.utils.np_utils import to_categorical # convert to one-hot-encoding
from keras.models import Sequential
from keras.layers import Dense, Dropout, Flatten, Conv2D, MaxPool2D
from keras.optimizers import RMSprop
from keras.preprocessing.image import ImageDataGenerator
from keras.callbacks import ReduceLROnPlateau
from keras.activations import selu
The code I'm using to implement it:
reduce_lr = ReduceLROnPlateau(monitor='val_loss', factor=0.2,patience=5, min_lr=0.001)
The full error that I encounter
My code is working without the learning rate scheduler and this is the error I get whenever I try to callback this particular scheduler.
Thank you
Changing
from keras.callbacks import ReduceLROnPlateau to
from tensorflow.keras.callbacks import ReduceLROnPlateau
might resolve your error.
Most probably it is happening because you are mixing tensorflow and keras imports.
I was trying to run a machine learning code based on Keras/TensorFlow. When running in tensorflow environment, I encounter the following error:
from keras_applications.mobilenet import relu6
ImportError: cannot import name 'relu6'
How can I solve it?
See this answer from GitHub.
You need to use a CustomObjectScope to import relu6.
MobileNet was moved to keras-applications
For keras 2.2.4:
from keras.layers import ReLU
from keras.layers import DepthwiseConv2D
You can create your relu6 like this:
relu6 = keras.layers.ReLU(max_value=6, name="ReLU6")
I want to import keras.engine.topology in Tensorflow.
I used to add the word tensorflow at the beginning of every Keras import if I want to use the Tensorflow version of Keras.
For example: instead of writing:
from keras.layers import Dense, Dropout, Input
I just write the following code and it works fine :
from tensorflow.keras.layers import Dense, Dropout, Input
But that's not the case for this specific import:
from tensorflow.keras.engine.topology import Layer, InputSpec
And I m getting the following error message:
No module named 'tensorflow.keras.engine'
You can import Layer and InputSpec from TensorFlow as follows:
from tensorflow.python.keras.layers import Layer, InputSpec
UPDATE: 30/10/2019
from tensorflow.keras.layers import Layer, InputSpec
In the keras_vggface/models.py file, change the import from:
from keras.engine.topology import get_source_inputs
to:
from keras.utils.layer_utils import get_source_inputs
In order to import keras.engine you may try using:
import tensorflow.python.keras.engine
Note: But from tensorflow.python.keras.engine you cannot import topology
I solved this issue by changing the import from from keras.engine.topology import get_source_inputs to from keras.utils.layer_utils import get_source_inputs