def test_parse_from_sequence_example_missing_framei_exception(self):
missing_frame_proto = text_format.Parse(
"""
feature_lists {
feature_list {
key: "utility"
value {
feature { float_list { value: 0.0 } }
feature { }
}
}
}
""", example_pb2.SequenceExample())
features = data_lib.parse_from_sequence_example(
ops.convert_to_tensor([missing_frame_proto.SerializeToString()]),
list_size=2,
context_feature_spec=None,
example_feature_spec={"utility": EXAMPLE_FEATURE_SPEC["utility"]})
with session.Session() as sess:
sess.run(variables.local_variables_initializer())
queue_runner.start_queue_runners()
with self.assertRaisesRegexp(
errors.InvalidArgumentError,
r"Unexpected number of elements in feature utility"):
sess.run(features)
def _make_sequence_example(self):
example = example_pb2.SequenceExample()
example.context.feature['int_ctx'].int64_list.value.extend([5])
example.context.feature['float_ctx'].float_list.value.extend([123.6])
for val in range(0, 10, 2):
feat = feature_pb2.Feature()
feat.int64_list.value.extend([val] * val)
example.feature_lists.feature_list['int_list'].feature.extend([feat])
for val in range(1, 11, 2):
feat = feature_pb2.Feature()
feat.bytes_list.value.extend([tf.compat.as_bytes(str(val))] * val)
example.feature_lists.feature_list['str_list'].feature.extend([feat])
return example
def _make_sequence_example():
example = example_pb2.SequenceExample()
return text_format.Parse(_SEQ_EX_PROTO, example)
def testSingleTriggerAndStats(self):
event_trigger = text_format.Parse(
"""
event_time { value_us: 1420102800000000 }
""", google_extensions_pb2.EventTrigger())
event_trigger_labels = (event_trigger, list())
event_trigger_labels_list = (event_trigger_labels,)
bundle = text_format.Parse(
"""
entry { resource { patient {
id { value: "14" }
birth_date { value_us: 8640000000000 }
} } }
entry { resource { medication_request {
id { value: "1" }
subject { patient_id { value: "14" } }
contained {
medication {
id { value: "med" }
code { coding {
system { value:
"http://hl7.org/fhir/sid/ndc"
}
code { value: "123" }
} }
}
}
authored_on {
value_us: 1420095600000000 # "2015-01-01T07:00:00+00:00"
}
medication { reference {
medication_id { value: "med" }
} }
} } }
""", resources_pb2.Bundle())
expected_seqex = text_format.Parse(
"""
context: {
feature {
key: "currentEncounterId"
value { int64_list { value: 1420095600 } }
}
feature {
key: "patientId"
value { bytes_list { value: "14" } }
}
feature {
key: "Patient.birthDate"
value { int64_list { value: 8640000 } }
}
feature {
key: "sequenceLength"
value { int64_list { value: 1 } }
}
feature {
key: "timestamp"
value { int64_list { value: 1420102800 } }
} }
feature_lists: {
feature_list {
key: "MedicationRequest.contained.medication.code.ndc"
value { feature { bytes_list { value: "123" } } }
}
feature_list {
key: "MedicationRequest.meta.lastUpdated"
value { feature { int64_list { value: 1420095600 } } }
}
feature_list {
key: "MedicationRequest.authoredOn"
value { feature { int64_list { value: 1420095600 } } }
}
feature_list {
key: "eventId"
value { feature { int64_list { value: 1420095600 } } }
}
feature_list {
key: "MedicationRequest.contained.medication.code"
value { feature { bytes_list { value: "ndc:123" } } }
}
feature_list {
key: "encounterId"
value { feature { int64_list { value: 1420095600 } } }
}
}
""", example_pb2.SequenceExample())
got_stats = self._runTest(
"Patient/14", bundle, event_trigger_labels_list,
(("Patient/14:0-1@1420102800", expected_seqex, 1),))
# We only spot check a few counters here. The main goal is to make sure
# we get the counters back from c++ land.
self.assertEqual(1, got_stats.get("num-examples"))
def testMultipleTriggersAndExamples(self):
event_trigger1 = text_format.Parse(
"""
event_time { value_us: 1417424400000000 }
source { encounter_id { value: "1" } }
""", google_extensions_pb2.EventTrigger())
event_trigger2 = text_format.Parse(
"""
event_time { value_us: 1420102800000000 }
source { encounter_id { value: "2" } }
""", google_extensions_pb2.EventTrigger())
event_trigger_labels1 = (
event_trigger1,
list(),
)
event_trigger_labels2 = (
event_trigger2,
list(),
)
event_trigger_labels_list = (
event_trigger_labels1,
event_trigger_labels2,
)
bundle = text_format.Parse(
"""
entry { resource { patient {
id { value: "14" }
} } }
entry {
resource { encounter {
id { value: "1" }
subject { patient_id { value: "14" } }
class_value {
system { value: "http://hl7.org/fhir/v3/ActCode" }
code { value: "IMP" }
}
reason {
coding {
system { value: "http://hl7.org/fhir/sid/icd-9-cm/diagnosis" }
code { value: "V410.9" }
display { value: "Standard issue" }
}
}
period {
start {
value_us: 1417420800000000 # "2014-12-01T08:00:00+00:00"
}
end {
value_us: 1417424400000000 # "2014-12-01T09:00:00+00:00"
}
}
} }
}
entry {
resource { encounter {
id { value: "2" }
subject { patient_id { value: "14" } }
class_value {
system { value: "http://hl7.org/fhir/v3/ActCode" }
code { value: "IMP" }
}
reason {
coding {
system { value: "http://hl7.org/fhir/sid/icd-9-cm/diagnosis" }
code { value: "191.4" }
display { value: "Malignant neoplasm of occipital lobe" }
}
}
period {
start {
value_us: 1420099200000000 # "2015-01-01T08:00:00+00:00"
}
end {
value_us: 1420102800000000 # "2015-01-01T09:00:00+00:00"
}
}
} }
}
""", resources_pb2.Bundle())
# pylint: disable=line-too-long
expected_seqex1 = text_format.Parse(
"""
context: {
feature {
key: "currentEncounterId"
value { int64_list { value: 1417420800 } }
}
feature {
key: "patientId"
value { bytes_list { value: "14" } }
}
feature {
key: "sequenceLength"
value { int64_list { value: 2 } }
}
feature {
key: "timestamp"
value { int64_list { value: 1417424400 } } }
}
feature_lists: {
feature_list {
key: "Encounter.class"
value { feature { bytes_list { value: "actcode:IMP" } } feature { bytes_list { value: "actcode:IMP" } } }
}
feature_list {
key: "Encounter.meta.lastUpdated"
value { feature { int64_list { value: 1417420800 } } feature { int64_list { value: 1417424400 } } }
}
feature_list {
key: "Encounter.period.start"
value { feature { int64_list { value: 1417420800 } } feature { int64_list { value: 1417420800 } } }
}
feature_list {
key: "Encounter.period.end"
value { feature { int64_list { } } feature { int64_list { value: 1417424400 } } }
}
feature_list {
key: "Encounter.reason"
value { feature { bytes_list { } } feature { bytes_list { value: "icd9:V410.9" } } }
}
feature_list {
key: "Encounter.reason.icd9"
value { feature { bytes_list { } } feature { bytes_list { value: "V410.9" } } }
}
feature_list {
key: "Encounter.reason.icd9.display.tokenized"
value { feature { bytes_list { } } feature { bytes_list { value: "standard" value: "issue" } } }
}
feature_list {
key: "encounterId"
value { feature { int64_list { value: 1417420800 } } feature { int64_list { value: 1417420800 } } }
}
feature_list {
key: "eventId"
value { feature { int64_list { value: 1417420800 } } feature { int64_list { value: 1417424400 } } }
}
}
""", example_pb2.SequenceExample())
expected_seqex2 = text_format.Parse(
"""
context: {
feature {
key: "currentEncounterId"
value { int64_list { value: 1420099200 } }
}
feature {
key: "patientId"
value { bytes_list { value: "14" } }
}
feature {
key: "sequenceLength"
value { int64_list { value: 4 } }
}
feature {
key: "timestamp"
value { int64_list { value: 1420102800 } } }
}
feature_lists: {
feature_list {
key: "Encounter.class"
value {
feature { bytes_list { value: "actcode:IMP" } } feature { bytes_list { value: "actcode:IMP" } } feature { bytes_list { value: "actcode:IMP" } } feature { bytes_list { value: "actcode:IMP" } }
}
}
feature_list {
key: "Encounter.meta.lastUpdated"
value { feature { int64_list { value: 1417420800 } } feature { int64_list { value: 1417424400 } } feature { int64_list { value: 1420099200 } } feature { int64_list { value: 1420102800 } } }
}
feature_list {
key: "Encounter.period.start"
value {
feature { int64_list { value: 1417420800 } } feature { int64_list { value: 1417420800 } } feature { int64_list { value: 1420099200 } } feature { int64_list { value: 1420099200 } }
}
}
feature_list {
key: "Encounter.period.end"
value {
feature { int64_list { } } feature { int64_list { value: 1417424400 } } feature { int64_list { } } feature { int64_list { value: 1420102800 } }
}
}
feature_list {
key: "Encounter.reason"
value {
feature { bytes_list { } } feature { bytes_list { value: "icd9:V410.9" } } feature { bytes_list { } } feature { bytes_list { value: "icd9:191.4" } }
}
}
feature_list {
key: "Encounter.reason.icd9"
value {
feature { bytes_list { } } feature { bytes_list { value: "V410.9" } } feature { bytes_list { } } feature { bytes_list { value: "191.4" } }
}
}
feature_list {
key: "Encounter.reason.icd9.display.tokenized"
value {
feature { bytes_list { } } feature { bytes_list { value: "standard" value: "issue" } } feature { bytes_list { } } feature { bytes_list { value: "malignant" value: "neoplasm" value: "of" value: "occipital" value: "lobe" } }
}
}
feature_list {
key: "encounterId"
value {
feature { int64_list { value: 1417420800 } } feature { int64_list { value: 1417420800 } } feature { int64_list { value: 1420099200 } } feature { int64_list { value: 1420099200 } }
}
}
feature_list {
key: "eventId"
value {
feature { int64_list { value: 1417420800 } } feature { int64_list { value: 1417424400 } } feature { int64_list { value: 1420099200 } } feature { int64_list { value: 1420102800 } }
}
}
}
""", example_pb2.SequenceExample())
# pylint: enable=line-too-long
_ = self._runTest("Patient/14", bundle, event_trigger_labels_list, (
("Patient/14:0-2@1417424400:Encounter/1", expected_seqex1, 2),
("Patient/14:0-4@1420102800:Encounter/2", expected_seqex2, 4),
))
def testSingleTriggerAndLabel(self):
event_trigger = text_format.Parse(
"""
event_time { value_us: 1420102800000000 }
source { encounter_id { value: "1" } }
""", google_extensions_pb2.EventTrigger())
event_label = text_format.Parse(
"""
patient { patient_id { value: "14" } }
type { code { value: "test1" }}
event_time { value_us: 1420102800000000 }
label {
class_name {
system { value: "urn:test:label"
}
code { value: "red" }
}
}
""", google_extensions_pb2.EventLabel())
event_trigger_labels = (
event_trigger,
(event_label,),
)
event_trigger_labels_list = (event_trigger_labels,)
bundle = text_format.Parse(
"""
entry { resource { patient {
id { value: "14" }
} } }
entry { resource { condition {
id { value: "1" }
subject { patient_id { value: "14" } }
code { coding {
system { value: "http://hl7.org/fhir/sid/icd-9-cm/diagnosis" }
code { value: "bar" }
} }
asserted_date {
value_us: 1417392000000000 # "2014-12-01T00:00:00+00:00"
}
} } }
entry { resource { condition {
id { value: "2" }
subject { patient_id { value: "14" } }
code { coding {
system { value: "http://hl7.org/fhir/sid/icd-9-cm/diagnosis" }
code { value: "baz" }
} }
asserted_date {
value_us: 1420099200000000 # "2015-01-01T08:00:00+00:00"
}
} } }
entry { resource { composition {
id { value: "1" }
subject { patient_id { value: "14" } }
encounter { encounter_id { value: "1" } }
section { text { div { value: "test text" } } }
date {
value_us: 1420102800000000
timezone: "UTC"
precision: SECOND
}
} } }
entry { resource { encounter {
id { value: "1" }
subject { patient_id { value: "14" } }
class_value {
system { value: "http://hl7.org/fhir/v3/ActCode" }
code { value: "IMP" }
}
reason {
coding {
system { value: "http://hl7.org/fhir/sid/icd-9-cm/diagnosis" }
code { value: "191.4" }
display { value: "Malignant neoplasm of occipital lobe" }
}
}
period {
start {
value_us: 1420099200000000 # "2015-01-01T08:00:00+00:00"
}
end {
value_us: 1420102800000000 # "2015-01-01T09:00:00+00:00"
}
}
} } }
""", resources_pb2.Bundle())
# pylint: disable=line-too-long
expected_seqex = text_format.Parse(
"""
context: {
feature {
key: "currentEncounterId"
value { int64_list { value: 1420099200 } }
}
feature {
key: "label.test1.class"
value { bytes_list { value: "red" } }
}
feature {
key: "label.test1.timestamp_secs"
value { int64_list { value: 1420102800 } }
}
feature {
key: "patientId"
value { bytes_list { value: "14" } }
}
feature {
key: "sequenceLength"
value { int64_list { value: 5 } }
}
feature {
key: "timestamp"
value { int64_list { value: 1420102800 } }
}
}
feature_lists: {
feature_list {
key: "Composition.meta.lastUpdated"
value { feature { int64_list { } } feature { int64_list { } } feature { int64_list { } } feature { int64_list { value: 1420102800 } } feature { int64_list { } } }
}
feature_list {
key: "Composition.date"
value { feature { int64_list { } } feature { int64_list { } } feature { int64_list { } } feature { int64_list { value: 1420102800 } } feature { int64_list { } } }
}
feature_list {
key: "Composition.section.text.div.tokenized"
value { feature { bytes_list { } } feature { bytes_list { } } feature { bytes_list { } } feature { bytes_list { value: "test" value: "text" } } feature { bytes_list { } } }
}
feature_list {
key: "Condition.meta.lastUpdated"
value { feature { int64_list { value: 1417392000 } } feature { int64_list { value: 1420099200 } } feature { int64_list { } } feature { int64_list { } } feature { int64_list { } } }
}
feature_list {
key: "Condition.code"
value { feature { bytes_list { value: "icd9:bar" } } feature { bytes_list { value: "icd9:baz" } } feature { bytes_list { } } feature { bytes_list { } } feature { bytes_list { } } }
}
feature_list {
key: "Condition.code.icd9"
value { feature { bytes_list { value: "bar" } } feature { bytes_list { value: "baz" } } feature { bytes_list { } } feature { bytes_list { } } feature { bytes_list { } } }
}
feature_list {
key: "Condition.assertedDate"
value { feature { int64_list { value: 1417392000 } } feature { int64_list { value: 1420099200 } } feature { int64_list { } } feature { int64_list { } } feature { int64_list { } } }
}
feature_list {
key: "Encounter.class"
value { feature { bytes_list { } } feature { bytes_list { } } feature { bytes_list { value: "actcode:IMP" } } feature { bytes_list { } } feature { bytes_list { value: "actcode:IMP" } } }
}
feature_list {
key: "Encounter.meta.lastUpdated"
value { feature { int64_list { } } feature { int64_list { } } feature { int64_list { value: 1420099200 } } feature { int64_list { } } feature { int64_list { value: 1420102800 } } }
}
feature_list {
key: "Encounter.period.start"
value { feature { int64_list { } } feature { int64_list { } } feature { int64_list { value: 1420099200 } } feature { int64_list { } } feature { int64_list { value: 1420099200 } } }
}
feature_list {
key: "Encounter.period.end"
value { feature { int64_list { } } feature { int64_list { } } feature { int64_list { } } feature { int64_list { } } feature { int64_list { value: 1420102800 } } }
}
feature_list {
key: "Encounter.reason"
value { feature { bytes_list { } } feature { bytes_list { } } feature { bytes_list { } } feature { bytes_list { } } feature { bytes_list { value: "icd9:191.4" } } }
}
feature_list {
key: "Encounter.reason.icd9"
value { feature { bytes_list { } } feature { bytes_list { } } feature { bytes_list { } } feature { bytes_list { } } feature { bytes_list { value: "191.4" } } }
}
feature_list {
key: "Encounter.reason.icd9.display.tokenized"
value { feature { bytes_list { } } feature { bytes_list { } } feature { bytes_list { } } feature { bytes_list { } } feature { bytes_list { value: "malignant" value: "neoplasm" value: "of" value: "occipital" value: "lobe" } } }
}
feature_list {
key: "encounterId"
value { feature { int64_list { value: 1417392000 } } feature { int64_list { value: 1420099200 } } feature { int64_list { value: 1420099200 } } feature { int64_list { value: 1420099200 } } feature { int64_list { value: 1420099200 } } }
}
feature_list {
key: "eventId"
value { feature { int64_list { value: 1417392000 } } feature { int64_list { value: 1420099200 } } feature { int64_list { value: 1420099200 } } feature { int64_list { value: 1420102800 } } feature { int64_list { value: 1420102800 } } }
}
}
""", example_pb2.SequenceExample())
# pylint: enable=line-too-long
_ = self._runTest(
"Patient/14", bundle, event_trigger_labels_list,
(("Patient/14:0-5@1420102800:Encounter/1", expected_seqex, 5),))
def testDecodeJpegImageAndBoundingBox(self):
"""Test if the decoder can correctly decode the image and bounding box.
A set of random images (represented as an image tensor) is first decoded as
the groundtrue image. Meanwhile, the image tensor will be encoded and pass
through the sequence example, and then decoded as images. The groundtruth
image and the decoded image are expected to be equal. Similar tests are
also applied to labels such as bounding box.
"""
image_tensor = np.random.randint(256,
size=(256, 256, 3)).astype(np.uint8)
encoded_jpeg = self._EncodeImage(image_tensor)
decoded_jpeg = self._DecodeImage(encoded_jpeg)
sequence_example = example_pb2.SequenceExample(
feature_lists=feature_pb2.FeatureLists(
feature_list={
'image/encoded':
feature_pb2.FeatureList(feature=[
feature_pb2.Feature(bytes_list=feature_pb2.BytesList(
value=[encoded_jpeg])),
]),
'bbox/xmin':
feature_pb2.FeatureList(feature=[
feature_pb2.Feature(float_list=feature_pb2.FloatList(
value=[0.0])),
]),
'bbox/xmax':
feature_pb2.FeatureList(feature=[
feature_pb2.Feature(float_list=feature_pb2.FloatList(
value=[1.0]))
]),
'bbox/ymin':
feature_pb2.FeatureList(feature=[
feature_pb2.Feature(float_list=feature_pb2.FloatList(
value=[0.0])),
]),
'bbox/ymax':
feature_pb2.FeatureList(feature=[
feature_pb2.Feature(float_list=feature_pb2.FloatList(
value=[1.0]))
]),
})).SerializeToString()
example_decoder = tf_sequence_example_decoder.TFSequenceExampleDecoder(
)
tensor_dict = example_decoder.decode(
tf.convert_to_tensor(sequence_example))
# Test tensor dict image dimension.
self.assertAllEqual(
(tensor_dict[fields.InputDataFields.image].get_shape().as_list()),
[None, None, None, 3])
with self.test_session() as sess:
tensor_dict[fields.InputDataFields.image] = tf.squeeze(
tensor_dict[fields.InputDataFields.image])
tensor_dict[fields.InputDataFields.groundtruth_boxes] = tf.squeeze(
tensor_dict[fields.InputDataFields.groundtruth_boxes])
tensor_dict = sess.run(tensor_dict)
# Test decoded image.
self.assertAllEqual(decoded_jpeg,
tensor_dict[fields.InputDataFields.image])
# Test decoded bounding box.
self.assertAllEqual(
[0.0, 0.0, 1.0, 1.0],
tensor_dict[fields.InputDataFields.groundtruth_boxes])
def _create_tf_record(self):
path = os.path.join(self.get_temp_dir(), 'tfrecord')
writer = tf.python_io.TFRecordWriter(path)
image_tensor = np.random.randint(255,
size=(16, 16, 3)).astype(np.uint8)
with self.test_session():
encoded_jpeg = tf.image.encode_jpeg(
tf.constant(image_tensor)).eval()
sequence_example = example_pb2.SequenceExample(
context=feature_pb2.Features(
feature={
'image/format':
feature_pb2.Feature(bytes_list=feature_pb2.BytesList(
value=['jpeg'.encode('utf-8')])),
'image/height':
feature_pb2.Feature(int64_list=feature_pb2.Int64List(
value=[16])),
'image/width':
feature_pb2.Feature(int64_list=feature_pb2.Int64List(
value=[16])),
}),
feature_lists=feature_pb2.FeatureLists(
feature_list={
'image/encoded':
feature_pb2.FeatureList(feature=[
feature_pb2.Feature(bytes_list=feature_pb2.BytesList(
value=[encoded_jpeg])),
]),
'image/object/bbox/xmin':
feature_pb2.FeatureList(feature=[
feature_pb2.Feature(float_list=feature_pb2.FloatList(
value=[0.0])),
]),
'image/object/bbox/xmax':
feature_pb2.FeatureList(feature=[
feature_pb2.Feature(float_list=feature_pb2.FloatList(
value=[1.0]))
]),
'image/object/bbox/ymin':
feature_pb2.FeatureList(feature=[
feature_pb2.Feature(float_list=feature_pb2.FloatList(
value=[0.0])),
]),
'image/object/bbox/ymax':
feature_pb2.FeatureList(feature=[
feature_pb2.Feature(float_list=feature_pb2.FloatList(
value=[1.0]))
]),
'image/object/class/label':
feature_pb2.FeatureList(feature=[
feature_pb2.Feature(int64_list=feature_pb2.Int64List(
value=[2]))
]),
}))
writer.write(sequence_example.SerializeToString())
writer.close()
return path
def testBundleAndLabelsToSeqexDoFn(self):
event_trigger1 = text_format.Parse(
"""
event_time { value_us: 1417424400000000 }
source { encounter_id { value: "1" } }
""", google_extensions_pb2.EventTrigger())
event_trigger2 = text_format.Parse(
"""
event_time { value_us: 1420102800000000 }
source { encounter_id { value: "2" } }
""", google_extensions_pb2.EventTrigger())
event_trigger_labels1 = (
event_trigger1,
list(),
)
event_trigger_labels2 = (
event_trigger2,
list(),
)
event_trigger_labels_list = [
event_trigger_labels1,
event_trigger_labels2,
]
bundle = text_format.Parse(
"""
entry { resource { patient {
id { value: "14" }
} } }
entry {
resource { encounter {
id { value: "1" }
subject { patient_id { value: "14" } }
class_value {
system { value: "http://hl7.org/fhir/v3/ActCode" }
code { value: "IMP" }
}
reason {
coding {
system { value: "http://hl7.org/fhir/sid/icd-9-cm/diagnosis" }
code { value: "V410.9" }
display { value: "Standard issue" }
}
}
period {
start {
value_us: 1417420800000000 # "2014-12-01T08:00:00+00:00"
}
end {
value_us: 1417424400000000 # "2014-12-01T09:00:00+00:00"
}
}
} }
}
entry {
resource { encounter {
id { value: "2" }
subject { patient_id { value: "14" } }
class_value {
system { value: "http://hl7.org/fhir/v3/ActCode" }
code { value: "IMP" }
}
reason {
coding {
system { value: "http://hl7.org/fhir/sid/icd-9-cm/diagnosis" }
code { value: "191.4" }
display { value: "Malignant neoplasm of occipital lobe" }
}
}
period {
start {
value_us: 1420099200000000 # "2015-01-01T08:00:00+00:00"
}
end {
value_us: 1420102800000000 # "2015-01-01T09:00:00+00:00"
}
}
} }
}
""", resources_pb2.Bundle())
# pylint: disable=line-too-long
expected_seqex1 = text_format.Parse(
"""
context: {
feature {
key: "currentEncounterId"
value { int64_list { value: 1417420800 } }
}
feature {
key: "patientId"
value { bytes_list { value: "14" } }
}
feature {
key: "sequenceLength"
value { int64_list { value: 2 } }
}
feature {
key: "timestamp"
value { int64_list { value: 1417424400 } } }
}
feature_lists: {
feature_list {
key: "Encounter.class"
value { feature { bytes_list { value: "http-hl7-org-fhir-v3-ActCode:IMP" } } feature { bytes_list { value: "http-hl7-org-fhir-v3-ActCode:IMP" } } }
}
feature_list {
key: "Encounter.meta.lastUpdated"
value { feature { int64_list { value: 1417420800 } } feature { int64_list { value: 1417424400 } } }
}
feature_list {
key: "Encounter.period.start"
value { feature { int64_list { value: 1417420800 } } feature { int64_list { value: 1417420800 } } }
}
feature_list {
key: "Encounter.period.end"
value { feature { int64_list { } } feature { int64_list { value: 1417424400 } } }
}
feature_list {
key: "Encounter.reason.http-hl7-org-fhir-sid-icd-9-cm-diagnosis"
value { feature { bytes_list { } } feature { bytes_list { value: "V410.9" } } }
}
feature_list {
key: "Encounter.reason.http-hl7-org-fhir-sid-icd-9-cm-diagnosis.display.tokenized"
value { feature { bytes_list { } } feature { bytes_list { value: "standard" value: "issue" } } }
}
feature_list {
key: "encounterId"
value { feature { int64_list { value: 1417420800 } } feature { int64_list { value: 1417420800 } } }
}
feature_list {
key: "eventId"
value { feature { int64_list { value: 1417420800 } } feature { int64_list { value: 1417424400 } } }
}
}
""", example_pb2.SequenceExample())
expected_seqex2 = text_format.Parse(
"""
context: {
feature {
key: "currentEncounterId"
value { int64_list { value: 1420099200 } }
}
feature {
key: "patientId"
value { bytes_list { value: "14" } }
}
feature {
key: "sequenceLength"
value { int64_list { value: 4 } }
}
feature {
key: "timestamp"
value { int64_list { value: 1420102800 } } }
}
feature_lists: {
feature_list {
key: "Encounter.class"
value {
feature { bytes_list { value: "http-hl7-org-fhir-v3-ActCode:IMP" } } feature { bytes_list { value: "http-hl7-org-fhir-v3-ActCode:IMP" } } feature { bytes_list { value: "http-hl7-org-fhir-v3-ActCode:IMP" } } feature { bytes_list { value: "http-hl7-org-fhir-v3-ActCode:IMP" } }
}
}
feature_list {
key: "Encounter.meta.lastUpdated"
value { feature { int64_list { value: 1417420800 } } feature { int64_list { value: 1417424400 } } feature { int64_list { value: 1420099200 } } feature { int64_list { value: 1420102800 } } }
}
feature_list {
key: "Encounter.period.start"
value {
feature { int64_list { value: 1417420800 } } feature { int64_list { value: 1417420800 } } feature { int64_list { value: 1420099200 } } feature { int64_list { value: 1420099200 } }
}
}
feature_list {
key: "Encounter.period.end"
value {
feature { int64_list { } } feature { int64_list { value: 1417424400 } } feature { int64_list { } } feature { int64_list { value: 1420102800 } }
}
}
feature_list {
key: "Encounter.reason.http-hl7-org-fhir-sid-icd-9-cm-diagnosis"
value {
feature { bytes_list { } } feature { bytes_list { value: "V410.9" } } feature { bytes_list { } } feature { bytes_list { value: "191.4" } }
}
}
feature_list {
key: "Encounter.reason.http-hl7-org-fhir-sid-icd-9-cm-diagnosis.display.tokenized"
value {
feature { bytes_list { } } feature { bytes_list { value: "standard" value: "issue" } } feature { bytes_list { } } feature { bytes_list { value: "malignant" value: "neoplasm" value: "of" value: "occipital" value: "lobe" } }
}
}
feature_list {
key: "encounterId"
value {
feature { int64_list { value: 1417420800 } } feature { int64_list { value: 1417420800 } } feature { int64_list { value: 1420099200 } } feature { int64_list { value: 1420099200 } }
}
}
feature_list {
key: "eventId"
value {
feature { int64_list { value: 1417420800 } } feature { int64_list { value: 1417424400 } } feature { int64_list { value: 1420099200 } } feature { int64_list { value: 1420102800 } }
}
}
}
""", example_pb2.SequenceExample())
with test_pipeline.TestPipeline() as p:
result = (
p
| beam.Create([(b"Patient/14", (bundle, event_trigger_labels_list))])
| "BundleAndLabelsToSeqex" >> beam.ParDo(
bundle_to_seqex.BundleAndLabelsToSeqexDoFn(
version_config=self._version_config,
enable_attribution=False,
generate_sequence_label=False)))
def check_result(got):
try:
self.assertLen(got, 2, "got: %s" % got)
got_seqex1 = got[0]
got_seqex2 = got[1]
self.assertProtoEqual(expected_seqex1, got_seqex1)
self.assertProtoEqual(expected_seqex2, got_seqex2)
except AssertionError as err:
raise util.BeamAssertException(err)
util.assert_that(result, check_result)
feature_list {
key: "unigrams"
value {
feature { bytes_list { value: "tensorflow" } }
feature { bytes_list { value: ["learning", "to", "rank"] } }
}
}
feature_list {
key: "utility"
value {
feature { float_list { value: 0.0 } }
feature { float_list { value: 1.0 } }
}
}
}
""", example_pb2.SequenceExample())
SEQ_EXAMPLE_PROTO_2 = text_format.Parse(
"""
context {
feature {
key: "query_length"
value { int64_list { value: 2 } }
}
}
feature_lists {
feature_list {
key: "unigrams"
value {
feature { bytes_list { value: "gbdt" } }
feature { }