old_contents: # encoding: utf-8
  """Test seya.layers.recurrent module"""
  
  from __future__ import print_function
  
  import unittest
  import numpy as np
  import theano
  
  from numpy.testing import assert_allclose
  
  from keras import backend as K
  from keras.layers.core import Layer, Dense
  from keras.models import Sequential
  floatX = K.common._FLOATX
  
  
  class TestCall(unittest.TestCase):
      """Test __call__ methods"""
  
      def test_layer_call(self):
          """Test keras.layers.core.Layer.__call__"""
          nb_samples, input_dim = 3, 10
          layer = Layer()
          X = K.placeholder(ndim=2)
          Y = layer(X)
          F = K.function([X], Y)
  
          x = np.random.randn(nb_samples, input_dim).astype(floatX)
          y = F([x, ])
          assert_allclose(x, y)
  
      def test_sequential_call(self):
          """Test keras.models.Sequential.__call__"""
          nb_samples, input_dim, output_dim = 3, 10, 5
          model = Sequential()
          model.add(Dense(output_dim=output_dim, input_dim=input_dim))
          model.compile('sgd', 'mse')
  
          X = K.placeholder(ndim=2)
          Y = model(X)
          F = K.function([X], Y)
  
          x = np.random.randn(nb_samples, input_dim).astype(floatX)
          y1 = F([x, ])
          y2 = model.predict(x)
          # results of __call__ should match model.predict
          assert_allclose(y1, y2)
  
  
  if __name__ == '__main__':
      theano.config.exception_verbosity = 'high'
      unittest.main(verbosity=2)
  
new_contents: # encoding: utf-8
  """Test seya.layers.recurrent module"""
  
  from __future__ import print_function
  
  import unittest
  import numpy as np
  
  from numpy.testing import assert_allclose
  
  from keras import backend as K
  from keras.layers.core import Dense
  from keras.models import Sequential
  floatX = K.common._FLOATX
  
  
  class TestCall(unittest.TestCase):
      """Test __call__ methods"""
  
      def test_layer_call(self):
          """Test keras.layers.core.Layer.__call__"""
          nb_samples, input_dim, output_dim = 3, 10, 5
          layer = Dense(output_dim, input_dim=input_dim)
          W = np.asarray(K.eval(layer.W))
          X = K.placeholder(ndim=2)
          Y = layer(X)
          F = K.function([X], [Y])
  
          x = np.random.randn(nb_samples, input_dim).astype(floatX)
          y = F([x])[0]
          assert_allclose(np.dot(x, W), y)
  
      def test_sequential_call(self):
          """Test keras.models.Sequential.__call__"""
          nb_samples, input_dim, output_dim = 3, 10, 5
          model = Sequential()
          model.add(Dense(output_dim=output_dim, input_dim=input_dim))
          model.compile('sgd', 'mse')
  
          X = K.placeholder(ndim=2)
          Y = model(X)
          F = K.function([X], [Y])
  
          x = np.random.randn(nb_samples, input_dim).astype(floatX)
          y1 = F([x])[0]
          y2 = model.predict(x)
          # results of __call__ should match model.predict
          assert_allclose(y1, y2)
  
  
  if __name__ == '__main__':
      unittest.main(verbosity=2)
  
subject: Fix tensorflow test