“Could not interpret optimizer identifier” error in Keras

Question

I got this error when I tried to modify the learning rate parameter of SGD optimizer in Keras. Did I miss something in my codes or my Keras was not installed properly?

Answer 1

from tensorflow.keras.optimizers import SGD

This works well.

Since Tensorflow 2.0, there is a new API available directly via tensorflow:

• https://www.pyimagesearch.com/2019/10/21/keras-vs-tf-keras-whats-the-difference-in-tensorflow-2-0/

Solution works for tensorflow==2.2.0rc2, Keras==2.2.4 (on Win10)

Please also note that the version above uses learning_rate as parameter and no longer lr.

Answer 2

For some libraries (e.g. keras_radam) you'll need to set up an environment variable before the import:

import os
os.environ['TF_KERAS'] = '1'

import tensorflow
import your_library

Answer 3

I have misplaced parenthesis and got this error,

Initially it was

x=Conv2D(filters[0],(3,3),use_bias=False,padding="same",kernel_regularizer=l2(reg),x))

The corrected version was

x=Conv2D(filters[0],(3,3),use_bias=False,padding="same",kernel_regularizer=l2(reg))(x)

Answer 4

Try changing your import lines to

from keras.models import Sequential
from keras.layers import Dense, ...

Your imports seem a little strange to me. Maybe you could elaborate more on that.

Answer 5

Use one style in one kernel, try not to mix

from keras.optimizers import sth

with

from tensorflow.keras.optimizers import sth

Answer 6

use

from tensorflow.keras import optimizers

instead of

from keras import optimizers