A `Concatenate` layer requires inputs with matching shapes except for the concatenation axis. Received: input_shape=[(None, 5), (None, 5, 1)]

The `Concatenate` layer in Keras requires inputs with matching shapes along all axes except for the concatenation axis. In the received input shape [(None, 5), (None, 5, 1)], the first input has a shape of (None, 5) and the second input has a shape of (None, 5, 1).

To resolve this issue and make the shapes compatible for concatenation, you can use a `Reshape` layer to reshape the second input from (None, 5, 1) to (None, 5). Here's an example:

from tensorflow.keras.layers import Concatenate, Reshape
from tensorflow.keras.models import Model
from tensorflow.keras.layers import Input

input1 = Input(shape=(5,))
input2 = Input(shape=(5, 1))
reshaped_input2 = Reshape((5,), name='reshape')(input2)
concatenated_output = Concatenate()([input1, reshaped_input2])

model = Model(inputs=[input1, input2], outputs=concatenated_output)

In this example, the `Reshape` layer is used to reshape the second input from (None, 5, 1) to (None, 5), and then the `Concatenate` layer is used to concatenate the reshaped input with the first input. Now the inputs have matching shapes along all axes, and you can proceed with your model.