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

model = Sequential()
model.add(Embedding(input_dim=10000, output_dim=50, input_length=50)) # input_length=50 is the length of input sequences
model.add(SimpleRNN(32)) # 32 units in the RNN
model.add(Dense(1, activation=’sigmoid’)) # Output layer for binary classification

model.compile(loss=’binary_crossentropy’, optimizer=’adam’, metrics=[‘accuracy’])

this is the code snippet I am using, I am not able to figure out why the params are coming as zero and the output shape as “?”
enter image description here

I even tried to change the code snippet to this, still got the same output.

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

LAYERS = [
Embedding(input_dim=10000, output_dim=50, input_length=50, name=”embeddingLayer”), # input_length=50 is the length of input sequences
SimpleRNN(32, name=”simpleRNNLayer”), # 32 units in the RNN
Dense(1, activation=’sigmoid’, name=”outputLayer”) # Output layer for binary classification]
model = Sequential(LAYERS)
model.compile(loss=’binary_crossentropy’, optimizer=’adam’, metrics=[‘accuracy’])

model.summary()enter image description here

there shuould be some value for params and outputshape.