Test the difference between Dense and TimeDistributedDense in Keras

time_dist.py

from __future__ import print_function
import numpy as np
np.random.seed(1337)
import sys

from keras.utils.test_utils import get_test_data
from keras.models import Sequential
from keras.layers.core import Dense, TimeDistributedDense
from keras.layers.recurrent import GRU

(X_train, y_train), (X_test, y_test) = get_test_data(nb_train=1000, nb_test=200, input_shape=(5, 10), output_shape=(5, 10), classification=False)

print('X_train:', X_train.shape)
print('X_test:', X_test.shape)
print('y_train:', y_train.shape)
print('y_test:', y_test.shape)

DLAYER = Dense if sys.argv[1] == 'DENSE' else TimeDistributedDense
dee = DLAYER(X_train.shape[-1] + 1, y_train.shape[-1])

model = Sequential()
model.add(GRU(X_train.shape[-1], X_train.shape[-1] + 1, return_sequences=True))
model.add(dee)
model.compile(loss='hinge', optimizer='rmsprop')
history = model.fit(X_train, y_train, nb_epoch=5, batch_size=16, validation_data=(X_test, y_test), verbose=2)

print(dee.get_weights())