def testEval(self):
"""Tests that eval produces correct metrics.
"""
def input_fn():
return {
'age': tf.constant([[1], [2]]),
'language': tf.SparseTensor(values=['greek', 'chinese'],
indices=[[0, 0], [1, 0]],
shape=[2, 1]),
}, tf.constant([[1], [0]])
language = tf.contrib.layers.sparse_column_with_hash_bucket('language', 100)
age = tf.contrib.layers.real_valued_column('age')
classifier = tf.contrib.learn.LinearClassifier(
feature_columns=[age, language])
# Evaluate on trained mdoel
classifier.fit(input_fn=input_fn, steps=100)
classifier.evaluate(input_fn=input_fn, steps=1)
# TODO(ispir): Enable accuracy check after resolving the randomness issue.
# self.assertLess(evaluated_values['loss/mean'], 0.3)
# self.assertGreater(evaluated_values['accuracy/mean'], .95)
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