diff --git a/api/internal_services/neo4j.py b/api/internal_services/neo4j.py
index f7b4c86b461b0690050473af9c5f25428b8329ea..df4179524a86de63851a8611916b31502d4174b3 100644
--- a/api/internal_services/neo4j.py
+++ b/api/internal_services/neo4j.py
@@ -3,8 +3,7 @@ import os
from neo4j import GraphDatabase
from api.internal_services.logger import logger
-
-uri = os.getenv('NEO4J_URL', "bolt://ala-neo4j:7687")
+uri = os.getenv('NEO4J_URL', "bolt://localhost:7687")
username = os.getenv('NEO4J_USERNAME', "neo4j")
password = os.getenv('NEO4J_PASSWORD', "password")
@@ -49,6 +48,16 @@ def create_concept_node(tx, concept, id, origin):
concept=concept, id=id, origin=origin)
+def create_sentence_node(tx, id):
+ tx.run('''
+ CREATE (
+ n:Sentence {
+ id: $id
+ }
+ )''',
+ id=id)
+
+
def create_next_word_relation(tx, idFrom, idTo):
tx.run('''
MATCH
@@ -96,16 +105,15 @@ def create_constituent_relation(tx, idFrom, idTo):
idFrom=idFrom, idTo=idTo
)
-
-def create_relation(tx, idFrom, idTo, id, type):
+def create_sub_relation(tx, idFrom, idTo):
tx.run('''
MATCH
- (a:Concept),
- (b:Concept)
- WHERE a.id = $idFrom AND b.id = $idTo
- CREATE (a)-[r:RELATION {id: $id, type: $type}]->(b)
+ (w:Word),
+ (s:Sentence)
+ WHERE w.id = $idFrom AND s.id = $idTo
+ CREATE (w)-[r:SUB]->(s)
''',
- idFrom=idFrom, idTo=idTo, id=id, type=type
+ idFrom=idFrom, idTo=idTo
)
@@ -120,7 +128,8 @@ def get_filtered_annotation(sentence_id, concept, annotation):
words_ids = get_id_single_tokens(annotation, sentence_id)
if len(words_ids) == 0:
- logger.warn(f"Cannot find the following annotation '{annotation}' in the sentence id {sentence_id}. This error is a hallucination of large language models.")
+ logger.warn(
+ f"Cannot find the following annotation '{annotation}' in the sentence id {sentence_id}. This error is a hallucination of large language models.")
return set()
filtered_annotation = set()
@@ -150,8 +159,9 @@ def get_id_multi_tokens(annotation, sentence_id):
'''
WITH $array AS words
MATCH path = (start:Word)-[:NEXT*]->(end:Word)
+ MATCH (start)--(s:Sentence)
where size(words) - 1 = size(relationships(path))
- and start.id starts with $sentence_id
+ and s.id = $sentence_id
and all(
idx IN range(0, size(words)-2)
WHERE (toLower(words[idx]) = toLower((nodes(path)[idx]).text)
@@ -164,7 +174,7 @@ def get_id_multi_tokens(annotation, sentence_id):
return collect(results.id) as liste
''',
array=annotation,
- sentence_id=f"{sentence_id}."
+ sentence_id=sentence_id
)
return list_multi_token.records[0][0]
@@ -172,14 +182,14 @@ def get_id_multi_tokens(annotation, sentence_id):
def get_id_single_tokens(annotation, sentence_id):
list_single_token = driver.execute_query(
'''
- match (w:Word)
+ match (s:Sentence)--(w:Word)
where toLower(w.text) = $annotation
- and w.id starts with $sentence_id
+ and s.id = $sentence_id
with distinct w as results
return collect(results.id) as liste
''',
annotation=annotation,
- sentence_id=f"{sentence_id}."
+ sentence_id=sentence_id
)
return list_single_token.records[0][0]
@@ -329,3 +339,73 @@ def reference(words_ids):
array=list(words_ids)
)
return set([record[0] for record in nodes.records])
+
+def get_sentences_for_train():
+ nodes = driver.execute_query(
+ '''
+ match (s:Sentence)--(:Word)--(c:Concept)
+ where c.origin <> "BERT"
+ return s.id as sentence, collect( distinct c.id) as concepts
+ '''
+ )
+ return [(record[0],record[1]) for record in nodes.records]
+
+def get_full_sentence_by_id(sentence_id):
+ nodes = driver.execute_query(
+ '''
+ MATCH (s:Sentence{id:$sentence_id})--(w1:Word)
+ MATCH (s:Sentence{id:$sentence_id})--(w2:Word)
+ WHERE NOT EXISTS {
+ MATCH (:Word)-[:NEXT]->(w1)
+ }
+ and not exists {
+ match (w2)-[:NEXT]->(:Word)
+ }
+ WITH w1 AS startNode, w2 as endNode
+ MATCH path = (startNode)-[:NEXT*]->(endNode)
+ WITH nodes(path) AS nodelist
+ WITH [node IN nodelist | node.text] AS texts
+ WITH reduce(acc = "", t IN texts | acc + " " + t) AS concatenated_text
+ RETURN concatenated_text
+ LIMIT 1
+ ''',
+ sentence_id=sentence_id
+ )
+ return [record[0] for record in nodes.records]
+
+def get_concept_text_by_id(concept_id):
+ nodes = driver.execute_query('''
+ match (c:Concept{id:$concept_id})--(w:Word)
+ with collect(w) as word_list
+ match (startNode:Word)
+ match (endNode:Word)
+ where startNode in word_list
+ and endNode in word_list
+ and not exists {
+ match (w1:Word)-[:NEXT]->(startNode)
+ where w1 in word_list
+ }
+ and not exists {
+ match (endNode)-[:NEXT]->(w2:Word)
+ where w2 in word_list
+ }
+ with startNode, endNode
+ MATCH path = (startNode)-[:NEXT*]->(endNode)
+ WITH nodes(path) AS nodelist
+ WITH [node IN nodelist | node.text] AS texts
+ WITH reduce(acc = "", t IN texts | acc + " " + t) AS concatenated_text
+ RETURN concatenated_text
+ LIMIT 1
+ ''',
+ concept_id=concept_id
+ )
+ return [record[0] for record in nodes.records]
+
+def get_concept_type_by_id(concept_id):
+ nodes = driver.execute_query('''
+ match (c:Concept{id:$concept_id})
+ return toLower(c.type)
+ ''',
+ concept_id=concept_id
+ )
+ return [record[0] for record in nodes.records]
\ No newline at end of file
diff --git a/api/internal_services/spacy.py b/api/internal_services/spacy.py
index 43f9b649be3cf9e5f32cf2d78699ea0f7350105d..c308c9f3286eff50dda29f45e5dcdc0d78e7b41b 100644
--- a/api/internal_services/spacy.py
+++ b/api/internal_services/spacy.py
@@ -1,3 +1,5 @@
+import uuid
+
import benepar, spacy
import warnings
@@ -8,7 +10,7 @@ warnings.filterwarnings("ignore")
from api.internal_services.database import get_last_sentence_index, update_last_sentence_index
from api.internal_services.neo4j import create_constituent_node, driver, create_constituent_relation, create_word_node, \
- create_next_word_relation, create_deprel_relation
+ create_next_word_relation, create_deprel_relation, create_sentence_node, create_sub_relation
benepar.download('benepar_fr2')
nlp = spacy.load('fr_dep_news_trf')
@@ -17,14 +19,21 @@ nlp.add_pipe('benepar', config={'model': 'benepar_fr2'})
def parsing_and_load_in_neo4j(job):
sentence = job.job_data['sentence']
- last_index = get_last_sentence_index()
- last_index = update_last_sentence_index(last_index + 1)
+ last_index = update_last_sentence_index(get_last_sentence_index() + 1)
with (driver.session() as session):
doc = nlp(sentence)
for i, sentence in enumerate(doc.sents):
+ sentence_uuid = str(uuid.uuid4())
+
+ #Création du noeud sentence
+ session.execute_write(
+ create_sentence_node,
+ sentence_uuid
+ )
+
for constituent in sentence._.constituents:
constituent_id = f"{last_index}.{i}.{constituent.start}-{constituent.end}"
if constituent._.labels and constituent.root.text != constituent.text:
@@ -44,6 +53,16 @@ def parsing_and_load_in_neo4j(job):
)
else:
+ #Création du mot en noeud neo4j
+ session.execute_write(
+ create_word_node,
+ '.'.join(map(str, [last_index, i, constituent.root.i])),
+ constituent.text,
+ None if not hasattr(constituent, 'lemma_') else constituent.lemma_,
+ constituent.root.pos_,
+ True if constituent.root.dep_ == "root" else False
+ )
+
# Créer le mot et le constituant solitaire si nécessaire
if constituent._.labels:
# Créer le consituant
@@ -53,16 +72,6 @@ def parsing_and_load_in_neo4j(job):
constituent._.labels[0]
)
- #Création du mot en noeud neo4j
- session.execute_write(
- create_word_node,
- '.'.join(map(str, [last_index, i, constituent.root.i])),
- constituent.text,
- None if not hasattr(constituent, 'lemma_') else constituent.lemma_,
- constituent.root.pos_,
- True if constituent.root.dep_ == "root" else False
- )
-
session.execute_write(
create_constituent_relation,
f"{last_index}.{i}.{constituent.start}-{constituent.end}",
@@ -76,16 +85,6 @@ def parsing_and_load_in_neo4j(job):
)
else:
- #Création du mot en noeud neo4j
- session.execute_write(
- create_word_node,
- '.'.join(map(str, [last_index, i, constituent.root.i])),
- constituent.text,
- None if not hasattr(constituent, 'lemma_') else constituent.lemma_,
- constituent.root.pos_,
- True if constituent.root.dep_ == "root" else False
- )
-
# parent existe alors on crée le lien
session.execute_write(
create_constituent_relation,
@@ -93,6 +92,12 @@ def parsing_and_load_in_neo4j(job):
'.'.join(map(str, [last_index, i, constituent.root.i])),
)
+ session.execute_write(
+ create_sub_relation,
+ '.'.join(map(str, [last_index, i, constituent.root.i])),
+ sentence_uuid,
+ )
+
for token in sentence:
#Création d'un lien de succession
if token.i != 0:
@@ -108,7 +113,7 @@ def parsing_and_load_in_neo4j(job):
new_job = Job()
new_job.job_id = job.job_id
new_job.job_type = JobType.ANNOTATION
- new_job.job_data = {'sentence': sentence, 'sentence_id': last_index}
+ new_job.job_data = {'sentence': sentence, 'sentence_id': sentence_uuid}
add_job_to_queue(new_job)
diff --git a/api/internal_services/trainer.py b/api/internal_services/trainer.py
index 3a65500c0695e130f0e6aa96a7cfd45b857cb5aa..1f870b9fe62525105fd5ee010aeedd268f08da07 100644
--- a/api/internal_services/trainer.py
+++ b/api/internal_services/trainer.py
@@ -1,13 +1,53 @@
+import json
+
import grpc
+from api.internal_services import neo4j
from api.internal_services.logger import logger
from api.protos.trainer import trainer_pb2_grpc, trainer_pb2
+def find_all_occurrences(text, phrase):
+ start = 0
+ while True:
+ start = text.find(phrase, start)
+ if start == -1: return
+ yield start
+ start += len(phrase)
+
+
def start_training(job):
+ training_data = []
+ training_sentences = neo4j.get_sentences_for_train()
+
+ for tuple in training_sentences:
+ sentence_id = tuple[0]
+ concepts_id = tuple[1]
+ sentence = neo4j.get_full_sentence_by_id(sentence_id)[0].strip()
+ tags = []
+
+ for concept_id in concepts_id:
+ span = neo4j.get_concept_text_by_id(concept_id)[0].strip()
+ type = neo4j.get_concept_type_by_id(concept_id)[0]
+ all_occurrences = list(find_all_occurrences(sentence, span))
+ for start_index in all_occurrences:
+ end_index = start_index + len(span)
+ tags.append({
+ "start": start_index if start_index == 0 else start_index-1,
+ "end": end_index,
+ "tag": type,
+ })
+
+ training_data.append({
+ 'id': sentence_id,
+ 'text': sentence,
+ 'tags': tags
+ })
+
+ logger.debug(training_data)
with grpc.insecure_channel(job.job_data['server_url']) as channel:
stub = trainer_pb2_grpc.TrainerStub(channel)
request = trainer_pb2.TrainingInput(
- training_data=[],
+ training_data=json.dumps(training_data),
fondation_model_id=job.job_data['fondation_model_id'],
finetuned_repo_name=job.job_data['finetuned_repo_name'],
huggingface_token=job.job_data['huggingface_token'],
@@ -16,4 +56,6 @@ def start_training(job):
responses = stub.StartTraining(request)
for response in responses:
logger.debug(f"gRPC message : {response.status}")
- logger.debug(f"fin de la connexion gRPC")
\ No newline at end of file
+ logger.debug(f"fin de la connexion gRPC")
+
+ # passer toutes les origines des concepts en BERT
diff --git a/api/protos/trainer/trainer.proto b/api/protos/trainer/trainer.proto
index 6510cc54d6bf98d980eaa7931d88aac05c3970db..c36c1f016771eedf304ad29a63b24dacdae81545 100644
--- a/api/protos/trainer/trainer.proto
+++ b/api/protos/trainer/trainer.proto
@@ -5,24 +5,12 @@ service Trainer {
}
message TrainingInput {
- repeated TrainingData training_data = 1;
+ string training_data = 1;
string fondation_model_id = 2;
string finetuned_repo_name = 3;
string huggingface_token = 4;
}
-message TrainingData {
- string id = 1;
- string text = 2;
- repeated Tag tags = 3;
-}
-
-message Tag {
- int32 start = 1;
- int32 end = 2;
- string tag = 3;
-}
-
message TrainingEvent {
string status = 1;
}
\ No newline at end of file
diff --git a/api/protos/trainer/trainer_pb2.py b/api/protos/trainer/trainer_pb2.py
index 4e4c61cf7a37e411e1e14d66d59f1f0fab5ae210..5a088b5d1f816f47c73b05ebb5590b447c7f818f 100644
--- a/api/protos/trainer/trainer_pb2.py
+++ b/api/protos/trainer/trainer_pb2.py
@@ -14,13 +14,11 @@ _sym_db = _symbol_database.Default()
-DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n api/protos/trainer/trainer.proto\"\x89\x01\n\rTrainingInput\x12$\n\rtraining_data\x18\x01 \x03(\x0b\x32\r.TrainingData\x12\x1a\n\x12\x66ondation_model_id\x18\x02 \x01(\t\x12\x1b\n\x13\x66inetuned_repo_name\x18\x03 \x01(\t\x12\x19\n\x11huggingface_token\x18\x04 \x01(\t\"<\n\x0cTrainingData\x12\n\n\x02id\x18\x01 \x01(\t\x12\x0c\n\x04text\x18\x02 \x01(\t\x12\x12\n\x04tags\x18\x03 \x03(\x0b\x32\x04.Tag\".\n\x03Tag\x12\r\n\x05start\x18\x01 \x01(\x05\x12\x0b\n\x03\x65nd\x18\x02 \x01(\x05\x12\x0b\n\x03tag\x18\x03 \x01(\t\"\x1f\n\rTrainingEvent\x12\x0e\n\x06status\x18\x01 \x01(\t2>\n\x07Trainer\x12\x33\n\rStartTraining\x12\x0e.TrainingInput\x1a\x0e.TrainingEvent\"\x00\x30\x01\x62\x06proto3')
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n api/protos/trainer/trainer.proto\"z\n\rTrainingInput\x12\x15\n\rtraining_data\x18\x01 \x01(\t\x12\x1a\n\x12\x66ondation_model_id\x18\x02 \x01(\t\x12\x1b\n\x13\x66inetuned_repo_name\x18\x03 \x01(\t\x12\x19\n\x11huggingface_token\x18\x04 \x01(\t\"\x1f\n\rTrainingEvent\x12\x0e\n\x06status\x18\x01 \x01(\t2>\n\x07Trainer\x12\x33\n\rStartTraining\x12\x0e.TrainingInput\x1a\x0e.TrainingEvent\"\x00\x30\x01\x62\x06proto3')
_TRAININGINPUT = DESCRIPTOR.message_types_by_name['TrainingInput']
-_TRAININGDATA = DESCRIPTOR.message_types_by_name['TrainingData']
-_TAG = DESCRIPTOR.message_types_by_name['Tag']
_TRAININGEVENT = DESCRIPTOR.message_types_by_name['TrainingEvent']
TrainingInput = _reflection.GeneratedProtocolMessageType('TrainingInput', (_message.Message,), {
'DESCRIPTOR' : _TRAININGINPUT,
@@ -29,20 +27,6 @@ TrainingInput = _reflection.GeneratedProtocolMessageType('TrainingInput', (_mess
})
_sym_db.RegisterMessage(TrainingInput)
-TrainingData = _reflection.GeneratedProtocolMessageType('TrainingData', (_message.Message,), {
- 'DESCRIPTOR' : _TRAININGDATA,
- '__module__' : 'api.protos.trainer.trainer_pb2'
- # @@protoc_insertion_point(class_scope:TrainingData)
- })
-_sym_db.RegisterMessage(TrainingData)
-
-Tag = _reflection.GeneratedProtocolMessageType('Tag', (_message.Message,), {
- 'DESCRIPTOR' : _TAG,
- '__module__' : 'api.protos.trainer.trainer_pb2'
- # @@protoc_insertion_point(class_scope:Tag)
- })
-_sym_db.RegisterMessage(Tag)
-
TrainingEvent = _reflection.GeneratedProtocolMessageType('TrainingEvent', (_message.Message,), {
'DESCRIPTOR' : _TRAININGEVENT,
'__module__' : 'api.protos.trainer.trainer_pb2'
@@ -54,14 +38,10 @@ _TRAINER = DESCRIPTOR.services_by_name['Trainer']
if _descriptor._USE_C_DESCRIPTORS == False:
DESCRIPTOR._options = None
- _TRAININGINPUT._serialized_start=37
- _TRAININGINPUT._serialized_end=174
- _TRAININGDATA._serialized_start=176
- _TRAININGDATA._serialized_end=236
- _TAG._serialized_start=238
- _TAG._serialized_end=284
- _TRAININGEVENT._serialized_start=286
- _TRAININGEVENT._serialized_end=317
- _TRAINER._serialized_start=319
- _TRAINER._serialized_end=381
+ _TRAININGINPUT._serialized_start=36
+ _TRAININGINPUT._serialized_end=158
+ _TRAININGEVENT._serialized_start=160
+ _TRAININGEVENT._serialized_end=191
+ _TRAINER._serialized_start=193
+ _TRAINER._serialized_end=255
# @@protoc_insertion_point(module_scope)
diff --git a/microservices/trainer/trainer.proto b/microservices/trainer/trainer.proto
index 6510cc54d6bf98d980eaa7931d88aac05c3970db..c36c1f016771eedf304ad29a63b24dacdae81545 100644
--- a/microservices/trainer/trainer.proto
+++ b/microservices/trainer/trainer.proto
@@ -5,24 +5,12 @@ service Trainer {
}
message TrainingInput {
- repeated TrainingData training_data = 1;
+ string training_data = 1;
string fondation_model_id = 2;
string finetuned_repo_name = 3;
string huggingface_token = 4;
}
-message TrainingData {
- string id = 1;
- string text = 2;
- repeated Tag tags = 3;
-}
-
-message Tag {
- int32 start = 1;
- int32 end = 2;
- string tag = 3;
-}
-
message TrainingEvent {
string status = 1;
}
\ No newline at end of file
diff --git a/microservices/trainer/trainer.py b/microservices/trainer/trainer.py
index 5a0c31e987e7517dd258956c5184a06ca49f77e7..ad423312cac9e92ac7083418fad68eed9d828b1b 100644
--- a/microservices/trainer/trainer.py
+++ b/microservices/trainer/trainer.py
@@ -1,3 +1,4 @@
+import json
from concurrent import futures
from typing import Optional, Union, Tuple
import grpc
@@ -55,6 +56,8 @@ def serve():
def training_process(training_data, fondation_model_id, finetuned_repo_name, huggingface_token):
+ training_data = json.loads(training_data)
+ print(training_data)
MAX_LENGTH = 256
tag2id = {'action': 1, 'actor': 2, 'artifact': 3, 'condition': 4, 'location': 5, 'modality': 6, 'reference': 7,
'time': 8}
diff --git a/microservices/trainer/trainer_pb2.py b/microservices/trainer/trainer_pb2.py
index 4e4c61cf7a37e411e1e14d66d59f1f0fab5ae210..5a088b5d1f816f47c73b05ebb5590b447c7f818f 100644
--- a/microservices/trainer/trainer_pb2.py
+++ b/microservices/trainer/trainer_pb2.py
@@ -14,13 +14,11 @@ _sym_db = _symbol_database.Default()
-DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n api/protos/trainer/trainer.proto\"\x89\x01\n\rTrainingInput\x12$\n\rtraining_data\x18\x01 \x03(\x0b\x32\r.TrainingData\x12\x1a\n\x12\x66ondation_model_id\x18\x02 \x01(\t\x12\x1b\n\x13\x66inetuned_repo_name\x18\x03 \x01(\t\x12\x19\n\x11huggingface_token\x18\x04 \x01(\t\"<\n\x0cTrainingData\x12\n\n\x02id\x18\x01 \x01(\t\x12\x0c\n\x04text\x18\x02 \x01(\t\x12\x12\n\x04tags\x18\x03 \x03(\x0b\x32\x04.Tag\".\n\x03Tag\x12\r\n\x05start\x18\x01 \x01(\x05\x12\x0b\n\x03\x65nd\x18\x02 \x01(\x05\x12\x0b\n\x03tag\x18\x03 \x01(\t\"\x1f\n\rTrainingEvent\x12\x0e\n\x06status\x18\x01 \x01(\t2>\n\x07Trainer\x12\x33\n\rStartTraining\x12\x0e.TrainingInput\x1a\x0e.TrainingEvent\"\x00\x30\x01\x62\x06proto3')
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n api/protos/trainer/trainer.proto\"z\n\rTrainingInput\x12\x15\n\rtraining_data\x18\x01 \x01(\t\x12\x1a\n\x12\x66ondation_model_id\x18\x02 \x01(\t\x12\x1b\n\x13\x66inetuned_repo_name\x18\x03 \x01(\t\x12\x19\n\x11huggingface_token\x18\x04 \x01(\t\"\x1f\n\rTrainingEvent\x12\x0e\n\x06status\x18\x01 \x01(\t2>\n\x07Trainer\x12\x33\n\rStartTraining\x12\x0e.TrainingInput\x1a\x0e.TrainingEvent\"\x00\x30\x01\x62\x06proto3')
_TRAININGINPUT = DESCRIPTOR.message_types_by_name['TrainingInput']
-_TRAININGDATA = DESCRIPTOR.message_types_by_name['TrainingData']
-_TAG = DESCRIPTOR.message_types_by_name['Tag']
_TRAININGEVENT = DESCRIPTOR.message_types_by_name['TrainingEvent']
TrainingInput = _reflection.GeneratedProtocolMessageType('TrainingInput', (_message.Message,), {
'DESCRIPTOR' : _TRAININGINPUT,
@@ -29,20 +27,6 @@ TrainingInput = _reflection.GeneratedProtocolMessageType('TrainingInput', (_mess
})
_sym_db.RegisterMessage(TrainingInput)
-TrainingData = _reflection.GeneratedProtocolMessageType('TrainingData', (_message.Message,), {
- 'DESCRIPTOR' : _TRAININGDATA,
- '__module__' : 'api.protos.trainer.trainer_pb2'
- # @@protoc_insertion_point(class_scope:TrainingData)
- })
-_sym_db.RegisterMessage(TrainingData)
-
-Tag = _reflection.GeneratedProtocolMessageType('Tag', (_message.Message,), {
- 'DESCRIPTOR' : _TAG,
- '__module__' : 'api.protos.trainer.trainer_pb2'
- # @@protoc_insertion_point(class_scope:Tag)
- })
-_sym_db.RegisterMessage(Tag)
-
TrainingEvent = _reflection.GeneratedProtocolMessageType('TrainingEvent', (_message.Message,), {
'DESCRIPTOR' : _TRAININGEVENT,
'__module__' : 'api.protos.trainer.trainer_pb2'
@@ -54,14 +38,10 @@ _TRAINER = DESCRIPTOR.services_by_name['Trainer']
if _descriptor._USE_C_DESCRIPTORS == False:
DESCRIPTOR._options = None
- _TRAININGINPUT._serialized_start=37
- _TRAININGINPUT._serialized_end=174
- _TRAININGDATA._serialized_start=176
- _TRAININGDATA._serialized_end=236
- _TAG._serialized_start=238
- _TAG._serialized_end=284
- _TRAININGEVENT._serialized_start=286
- _TRAININGEVENT._serialized_end=317
- _TRAINER._serialized_start=319
- _TRAINER._serialized_end=381
+ _TRAININGINPUT._serialized_start=36
+ _TRAININGINPUT._serialized_end=158
+ _TRAININGEVENT._serialized_start=160
+ _TRAININGEVENT._serialized_end=191
+ _TRAINER._serialized_start=193
+ _TRAINER._serialized_end=255
# @@protoc_insertion_point(module_scope)
diff --git a/microservices/trainer/trainer_pb2_grpc.py b/microservices/trainer/trainer_pb2_grpc.py
index ede71aa15bee98983bbbbfdf21125462b25faef2..ca55b8cc9bbbb93e818c21d3e797f954b3d546ee 100644
--- a/microservices/trainer/trainer_pb2_grpc.py
+++ b/microservices/trainer/trainer_pb2_grpc.py
@@ -1,7 +1,6 @@
# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
"""Client and server classes corresponding to protobuf-defined services."""
import grpc
-
import trainer_pb2 as api_dot_protos_dot_trainer_dot_trainer__pb2