def testFromContribEstimatorWithSessionConfig(self):
estimator = testing_common.get_arithmetic_estimator(core=False)
input_fn = testing_common.get_arithmetic_input_fn(core=False)
predictor_factories.from_contrib_estimator(
estimator,
input_fn,
output_alternative_key='sum',
config=config_pb2.ConfigProto())
def testFromContribEstimatorWithCoreEstimatorRaises(self):
estimator = testing_common.get_arithmetic_estimator(core=True)
input_fn = testing_common.get_arithmetic_input_fn(core=True)
with self.assertRaises(TypeError):
predictor_factories.from_contrib_estimator(estimator, input_fn)
def testFromContribEstimator(self):
estimator = testing_common.get_arithmetic_estimator(core=False)
input_fn = testing_common.get_arithmetic_input_fn(core=False)
predictor_factories.from_contrib_estimator(estimator, input_fn,
output_alternative_key='sum')
def testFromContribEstimatorWithSessionConfig(self):
estimator = testing_common.get_arithmetic_estimator(core=False)
input_fn = testing_common.get_arithmetic_input_fn(core=False)
predictor_factories.from_contrib_estimator(
estimator, input_fn, output_alternative_key='sum',
config=config_pb2.ConfigProto())
def prediction_input_fn():
feature_placeholders = {
'wvec': tf.placeholder(tf.float32, [1, 2, 3]),
'dvec': tf.placeholder(tf.float32, [1, 2, 3]),
}
features = {
key: tf.expand_dims(tensor, -1)
for key, tensor in feature_placeholders.items()
}
return tf.contrib.learn.InputFnOps(features, None,
feature_placeholders)
predictor = from_contrib_estimator(estimator=estimator,
prediction_input_fn=prediction_input_fn,
output_alternative_key="g_dvec")
sess = tf.Session()
print(predictor.fetch_tensors)
wvec = [[[1, 2, 3], [4, 5, 6]]]
dvec = [[[2, 3, 4], [5, 6, 7]]]
i = 0
g_wvec = [
[
model.dist(wvec[i][0], wvec[i][1]),
model.dist(dvec[i][0], dvec[i][1])
],
]
g_dvec = [
[