What is the shape of output of the below model?

I am working on a deep learning architecture with training data something like below

X shape is (80, 260,380,3,1)

y shape is (80, 260,380,1)

input_shape1 = (None, 260,380,3,1)

The model:

model = Sequential()
model.add(TimeDistributed(Conv2D(filters=6, kernel_size=(3,3), strides=(1,1), activation ="relu", padding = "same", input_shape=input_shape1)))
model.add(TimeDistributed(MaxPooling2D(pool_size=(3,3), strides=(1,1), padding = "same")))
model.add(TimeDistributed(Flatten()))
model.add(TimeDistributed(Dense(units=380, activation = "relu")))
model.add(Bidirectional(SimpleRNN(380, activation = "relu", return_sequences=True)))
model.add(TimeDistributed(Dense(380, activation ="relu")))
model.add(TimeDistributed(Dense(380, activation ="sigmoid")))
model.compile(loss = "binary_crossentropy", optimizer = "adam")

I am getting output with shape (1,260)

I am looking for (1,260,380)

I am not sure on the RNN part, please check and advise