def test_tiny_seq2seq_rnn_random(self):
np.random.seed(1988)
input_dim = 2
input_length = 4
num_channels = 3
# Define a model
model = Sequential()
model.add(SimpleRNN(num_channels, input_shape=(input_length, input_dim), return_sequences=True))
# Set some random weights
model.set_weights([np.random.rand(*w.shape)*0.2 - 0.1 for w in model.get_weights()])
# Test the keras model
self._test_keras_model(model, input_blob = 'data', output_blob = 'output')
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