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Update locustfile.py #13047

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Update locustfile.py #13047

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47 changes: 22 additions & 25 deletions machine-learning/locustfile.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,63 +9,57 @@

byte_image = BytesIO()


@events.init_command_line_parser.add_listener
def _(parser: ArgumentParser) -> None:
parser.add_argument("--clip-model", type=str, default="ViT-B-32::openai")
parser.add_argument("--face-model", type=str, default="buffalo_l")
parser.add_argument(
"--tag-min-score",
type=int,
default=0.0,
help="Returns all tags at or above this score. The default returns all tags.",
)
parser.add_argument(
"--face-min-score",
type=int,
default=0.034,
help=(
"Returns all faces at or above this score. The default returns 1 face per request; "
"setting this to 0 blows up the number of faces to the thousands."
),
)
parser.add_argument("--tag-min-score", type=float, default=0.0,
help="Returns all tags at or above this score.")
parser.add_argument("--face-min-score", type=float, default=0.034,
help="Returns faces at or above this score.")
parser.add_argument("--image-size", type=int, default=1000)


@events.test_start.add_listener
def on_test_start(environment: Environment, **kwargs: Any) -> None:
global byte_image
assert environment.parsed_options is not None
image = Image.new("RGB", (environment.parsed_options.image_size, environment.parsed_options.image_size))
image.save(byte_image, format="jpeg")

@events.request_failure.add_listener
def on_request_failure(request_type, name, response_time, response_length, exception, **kwargs):
print(f"Request failed: {request_type} {name}, Exception: {exception}")

class InferenceLoadTest(HttpUser):
abstract: bool = True
host = "http://127.0.0.1:3003"
data: bytes

# re-use the image across all instances in a process
def on_start(self) -> None:
self.data = byte_image.getvalue()


class CLIPTextFormDataLoadTest(InferenceLoadTest):
@task
def encode_text(self) -> None:
request = {"clip": {"textual": {"modelName": self.environment.parsed_options.clip_model}}}
data = [("entries", json.dumps(request)), ("text", "test search query")]
self.client.post("/predict", data=data)

try:
response = self.client.post("/predict", data=data)
response.raise_for_status()
except Exception as e:
print(f"Error in encode_text: {e}")

class CLIPVisionFormDataLoadTest(InferenceLoadTest):
@task
def encode_image(self) -> None:
request = {"clip": {"visual": {"modelName": self.environment.parsed_options.clip_model, "options": {}}}}
data = [("entries", json.dumps(request))]
files = {"image": self.data}
self.client.post("/predict", data=data, files=files)

try:
response = self.client.post("/predict", data=data, files=files)
response.raise_for_status()
except Exception as e:
print(f"Error in encode_image: {e}")

class RecognitionFormDataLoadTest(InferenceLoadTest):
@task
Expand All @@ -83,5 +77,8 @@ def recognize(self) -> None:
}
data = [("entries", json.dumps(request))]
files = {"image": self.data}

self.client.post("/predict", data=data, files=files)
try:
response = self.client.post("/predict", data=data, files=files)
response.raise_for_status()
except Exception as e:
print(f"Error in recognize: {e}")
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