def _two_phases_preprocessing_fn(inputs):
x = inputs['x']
x_mean = analyzers.mean(x)
x_square_deviations = tf.square(x - x_mean)
x_var = analyzers.mean(x_square_deviations + analyzers.mean(inputs['y']))
x_normalized = (x - x_mean) / tf.sqrt(x_var)
return {
'x_normalized': x_normalized,
's_id': mappers.compute_and_apply_vocabulary(inputs['s'])
}
def test_create_phases_with_table(self):
# Create a graph with table that can only be run after the first analyzer
# has run. Note converting an integerized string into a float doesn't make
# much sense, but is a legal tensorflow computation.
string_placeholder = tf.placeholder(tf.string, shape=(None,))
integerized = mappers.compute_and_apply_vocabulary(string_placeholder)
integerized = tf.to_float(integerized)
integerized / analyzers.max(integerized) # pylint: disable=expression-not-assigned
phases = impl_helper.create_phases({'x': string_placeholder})
self.assertEqual(len(phases), 2)
self.assertEqual(len(phases[0].analyzer_infos), 1)
self.assertEqual(len(phases[1].analyzer_infos), 1)
self.assertEqual(len(phases[0].table_initializers), 0)
self.assertEqual(len(phases[1].table_initializers), 1)
