tf.keras.layers.Bidirectional: Please initialize `Bidirectional` layer with a `tf.keras.layers.Layer` instance

Getting some strange error when using bidirectional LSTM in tf.keras. I have followed documentation of bidriectional, but getting the error.

Here is the code:

 rl = Reshape((-1, int(cnn_SE_featureMap.shape[2]) * int(cnn_SE_featureMap.shape[3])))(
        input) ####(type_spec=TensorSpec(shape=(None, 24, 9))
# lstm_l6 = tf.keras.layers.LSTM(128, activation='tanh', recurrent_initializer=tf.keras.initializers.Orthogonal(seed=1), dropout=0.5, recurrent_dropout=0.25)(lstm_l5)
lstm_l5 = tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(128, activation='tanh',
                               recurrent_initializer=tf.keras.initializers.Orthogonal(), dropout=0.5,
                               recurrent_dropout=0.5, return_sequences=True)(rl)) 

Error: Traceback (most recent call last):

File "/home/anafees/.local/lib/python3.9/site-packages/IPython/core/interactiveshell.py", line 3251, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-11-721b57a9dbb6>", line 1, in <module>
    lstm_l5 = tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(128, activation='tanh',
  File "/home/anafees/.local/lib/python3.9/site-packages/keras/layers/wrappers.py", line 453, in __init__
    raise ValueError(
ValueError: Please initialize `Bidirectional` layer with a `tf.keras.layers.Layer` instance. Received: KerasTensor(type_spec=TensorSpec(shape=(None, 128), dtype=tf.float32, name=None), name='lstm_5/strided_slice_3:0', description="created by layer 'lstm_5'")

[FrameMuse]

Ok, I found solution in this answer on stackoverflow, Simply change tensorflow.keras to keras.

Reference from stackoverflow: You are mixing imports between the keras and tf.keras libraries, these are not the same library, and doing this is not supported.

You need to make all imports from one of the libraries:

from keras.layers import Input, LSTM, Dense, TimeDistributed, Activation, BatchNormalization, Dropout, Bidirectional
from keras.models import Sequential
from keras.utils import Sequence
from keras.layers import CuDNNLSTM

[Nafees-060]

@FrameMuse Might be. But now tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(64,dropout=0.5))(rl) is working for me