def testEmptyRnnInput(self):
observation_values = tf.SparseTensor(
indices=tf.reshape(tf.constant([], dtype=tf.int64), shape=[0, 3]),
values=tf.constant([], dtype=tf.float32),
dense_shape=[2, 0, 1])
observation_code_ids = tf.SparseTensor(
indices=observation_values.indices,
values=tf.constant([], dtype=tf.string),
dense_shape=observation_values.dense_shape)
delta_time, obs_values, indicator = osm.construct_input(
{
'Observation.code':
observation_code_ids,
'Observation.valueQuantity.value':
observation_values,
'deltaTime':
tf.reshape(tf.constant([[], []], dtype=tf.int64), [2, 0, 1])
}, ['loinc:1', 'loinc:2', 'MISSING'],
'Observation.code',
'Observation.valueQuantity.value',
mode=tf.estimator.ModeKeys.TRAIN,
normalize=False,
momentum=0.9,
min_value=-10000000,
max_value=10000000,
input_keep_prob=1.0)
result = tf.concat([delta_time, indicator, obs_values], axis=2)
with self.test_session() as sess:
sess.run(tf.tables_initializer())
actual_result, = sess.run([tf.shape(result)])
self.assertAllClose([2, 0, 7], actual_result)
def testRnnInput(self):
observation_values = tf.SparseTensor(
indices=[[0, 0, 0], [0, 1, 0], [0, 2, 0], [1, 0, 0], [1, 1, 0],
[1, 2, 0]],
values=[100.0, 2.3, 9999999.0, 0.5, 0.0, 4.0],
dense_shape=[2, 3, 1])
observation_code_ids = tf.SparseTensor(
indices=observation_values.indices,
values=[
'loinc:2', 'loinc:1', 'loinc:2', 'loinc:1', 'MISSING',
'loinc:1'
],
dense_shape=observation_values.dense_shape)
delta_time, obs_values, indicator = osm.construct_input(
{
'Observation.code':
observation_code_ids,
'Observation.valueQuantity.value':
observation_values,
'deltaTime':
tf.constant([[[2 * 60 * 60], [3 * 60 * 60], [0]],
[[1 * 60 * 60], [3 * 60 * 60], [6 * 60 * 60]]],
dtype=tf.int64)
}, ['loinc:1', 'loinc:2', 'MISSING'],
'Observation.code',
'Observation.valueQuantity.value',
mode=tf.estimator.ModeKeys.TRAIN,
normalize=False,
momentum=0.9,
min_value=-10000000,
max_value=10000000,
input_keep_prob=1.0)
result = tf.concat([delta_time, indicator, obs_values], axis=2)
expected_result = [
[
[0, 0, 1, 0, 0, 100, 0],
[-1, 1, 0, 0, 2.3, 0, 0],
# value 9999999.0 was filtered.
[3, 0, 0, 0, 0, 0, 0]
],
[[0, 1, 0, 0, 0.5, 0, 0], [-2, 0, 0, 1, 0, 0, 0],
[-3, 1, 0, 0, 4.0, 0, 0]]
]
with self.test_session() as sess:
sess.run(tf.tables_initializer())
actual_result = sess.run(result)
print(actual_result)
self.assertAllClose(expected_result, actual_result, atol=0.01)