HongChuang/ultralytics-ascend
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions 3

ultralytics 8.1.30 add advanced HUB train arguments (#9110)

Browse source 
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
This commit is contained in:
Kalen Michael 2024-03-20 23:53:00 +01:00 • committed by GitHub
parent a62cdab53a
commit 8617fcf32d
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
3 changed files with 18 additions and 19 deletions
Download patch file Download diff file Expand all files Collapse all files

33
ultralytics/hub/session.py
View file

@ -170,10 +170,19 @@ class HUBTrainingSession:
return api_key, model_id, filename
def _set_train_args(self, **kwargs):
"""Initializes training arguments and creates a model entry on the Ultralytics HUB."""
def _set_train_args(self):
"""
Initializes training arguments and creates a model entry on the Ultralytics HUB.
This method sets up training arguments based on the model's state and updates them with any additional
arguments provided. It handles different states of the model, such as whether it's resumable, pretrained,
or requires specific file setup.
Raises:
ValueError: If the model is already trained, if required dataset information is missing, or if there are
issues with the provided training arguments.
"""
if self.model.is_trained():
# Model is already trained
raise ValueError(emojis(f"Model is already trained and uploaded to {self.model_url} 🚀"))
if self.model.is_resumable():
@ -182,26 +191,16 @@ class HUBTrainingSession:
self.model_file = self.model.get_weights_url("last")
else:
# Model has no saved weights
def get_train_args(config):
"""Parses an identifier to extract API key, model ID, and filename if applicable."""
return {
"batch": config["batchSize"],
"epochs": config["epochs"],
"imgsz": config["imageSize"],
"patience": config["patience"],
"device": config["device"],
"cache": config["cache"],
"data": self.model.get_dataset_url(),
}
self.train_args = self.model.data.get("train_args") # new response
self.train_args = get_train_args(self.model.data.get("config"))
# Set the model file as either a *.pt or *.yaml file
self.model_file = (
self.model.get_weights_url("parent") if self.model.is_pretrained() else self.model.get_architecture()
)
if not self.train_args.get("data"):
raise ValueError("Dataset may still be processing. Please wait a minute and try again.") # RF fix
if "data" not in self.train_args:
# RF bug - datasets are sometimes not exported
raise ValueError("Dataset may still be processing. Please wait a minute and try again.")
self.model_file = checks.check_yolov5u_filename(self.model_file, verbose=False) # YOLOv5->YOLOv5u
self.model_id = self.model.id