Added tracing to classification
All checks were successful
continuous-integration/drone/push Build is passing
All checks were successful
continuous-integration/drone/push Build is passing
This commit is contained in:
parent
0245cd7b6a
commit
1acdd6d21c
@ -4,6 +4,7 @@ import tempfile
|
||||
import os
|
||||
import os.path
|
||||
import shutil
|
||||
import opentracing
|
||||
|
||||
import librosa
|
||||
import librosa.display
|
||||
@ -83,10 +84,13 @@ class Classifier(object):
|
||||
|
||||
return predicted_class_name, labeled_predictions
|
||||
|
||||
def predict(self, wav_filename: str) -> Tuple[str, dict]:
|
||||
def predict(self, wav_filename: str, span: opentracing.span.Span) -> Tuple[str, dict]:
|
||||
with opentracing.tracer.start_span('createSpectrogram', child_of=span):
|
||||
directory, _ = self.create_spectrogram(wav_filename)
|
||||
|
||||
with opentracing.tracer.start_span('runPredictor', child_of=span):
|
||||
result = self._run_predictor(directory)
|
||||
|
||||
shutil.rmtree(directory) # The image is no longer needed
|
||||
|
||||
return result
|
||||
|
@ -18,12 +18,14 @@ class MagicDoer:
|
||||
requests_session = SessionTracing(propagate=True)
|
||||
|
||||
@classmethod
|
||||
def run_everything(cls, parameters: dict) -> dict:
|
||||
def run_everything(cls, parameters: dict, span: opentracing.span.Span) -> dict:
|
||||
tag = parameters['tag']
|
||||
sample_file_handle, sample_file_path = tempfile.mkstemp(prefix=f"{tag}_", suffix=".wav", dir="/dev/shm")
|
||||
span.log_kv({'event': 'sampleFileOpened', 'sampleTag': tag})
|
||||
response = None
|
||||
try:
|
||||
|
||||
with opentracing.tracer.start_span('downloadSample', child_of=span):
|
||||
# Download Sample
|
||||
object_path = urljoin(Config.STORAGE_SERVICE_URL, f"object/{tag}")
|
||||
|
||||
@ -34,12 +36,14 @@ class MagicDoer:
|
||||
|
||||
logging.debug(f"Downloaded sample to {sample_file_path}")
|
||||
|
||||
with opentracing.tracer.start_span('loadClassifier', child_of=span):
|
||||
# Get a classifier that uses the default model
|
||||
model_details, classifier = cls.classifier_cache.get_default_classifier()
|
||||
|
||||
with opentracing.tracer.start_span('runClassifier', child_of=span) as child_span:
|
||||
# do the majic
|
||||
classification_start_time = time.time()
|
||||
predicted_class_name, labeled_predictions = classifier.predict(sample_file_path)
|
||||
predicted_class_name, labeled_predictions = classifier.predict(sample_file_path, child_span)
|
||||
classification_duration = time.time() - classification_start_time
|
||||
|
||||
response = {
|
||||
@ -57,6 +61,8 @@ class MagicDoer:
|
||||
except FileNotFoundError:
|
||||
pass
|
||||
|
||||
span.log_kv({'event': 'sampleFileDeleted', 'sampleTag': tag})
|
||||
|
||||
if not response:
|
||||
logging.error("Something went wrong during classification!")
|
||||
else:
|
||||
|
@ -17,13 +17,17 @@ from magic_doer import MagicDoer
|
||||
|
||||
|
||||
def message_callback(channel, method, properties, body):
|
||||
with opentracing.tracer.start_span('messageHandling') as span:
|
||||
try:
|
||||
msg = json.loads(body.decode('utf-8'))
|
||||
except (UnicodeDecodeError, json.JSONDecodeError) as e:
|
||||
logging.warning(f"Invalid message recieved: {e}")
|
||||
return
|
||||
|
||||
results = MagicDoer.run_everything(msg) # <- This is where the magic happens
|
||||
span.log_kv({'event': 'messageParsed', 'sampleTag': msg['tag']})
|
||||
|
||||
with opentracing.tracer.start_span('runAlgorithm', child_of=span) as child_span:
|
||||
results = MagicDoer.run_everything(msg, child_span) # <- This is where the magic happens
|
||||
|
||||
if results:
|
||||
channel.basic_publish(
|
||||
|
Loading…
Reference in New Issue
Block a user