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 { }