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