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hub / github.com/YesianRohn/TextSSR / parse_args

Function parse_args

diffusers/examples/controlnet/train_controlnet_sd3.py:261–639  ·  view source on GitHub ↗
(input_args=None)

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259
260
261def parse_args(input_args=None):
262 parser = argparse.ArgumentParser(description="Simple example of a ControlNet training script.")
263 parser.add_argument(
264 "--pretrained_model_name_or_path",
265 type=str,
266 default=None,
267 required=True,
268 help="Path to pretrained model or model identifier from huggingface.co/models.",
269 )
270 parser.add_argument(
271 "--controlnet_model_name_or_path",
272 type=str,
273 default=None,
274 help="Path to pretrained controlnet model or model identifier from huggingface.co/models."
275 " If not specified controlnet weights are initialized from unet.",
276 )
277 parser.add_argument(
278 "--revision",
279 type=str,
280 default=None,
281 required=False,
282 help="Revision of pretrained model identifier from huggingface.co/models.",
283 )
284 parser.add_argument(
285 "--variant",
286 type=str,
287 default=None,
288 help="Variant of the model files of the pretrained model identifier from huggingface.co/models, 'e.g.' fp16",
289 )
290 parser.add_argument(
291 "--output_dir",
292 type=str,
293 default="controlnet-model",
294 help="The output directory where the model predictions and checkpoints will be written.",
295 )
296 parser.add_argument(
297 "--cache_dir",
298 type=str,
299 default=None,
300 help="The directory where the downloaded models and datasets will be stored.",
301 )
302 parser.add_argument("--seed", type=int, default=None, help="A seed for reproducible training.")
303 parser.add_argument(
304 "--resolution",
305 type=int,
306 default=512,
307 help=(
308 "The resolution for input images, all the images in the train/validation dataset will be resized to this"
309 " resolution"
310 ),
311 )
312 parser.add_argument(
313 "--train_batch_size", type=int, default=4, help="Batch size (per device) for the training dataloader."
314 )
315 parser.add_argument("--num_train_epochs", type=int, default=1)
316 parser.add_argument(
317 "--max_train_steps",
318 type=int,

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