def test_small_no_sequence_gru_random(self):
np.random.seed(1988)
input_dim = 10
input_length = 1
num_channels = 1
# Define a model
model = Sequential()
model.add(GRU(num_channels, input_shape = (input_length, input_dim),
recurrent_activation = 'sigmoid'))
# 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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