[Bug]: How to set max epochs parameter ?

[shanmugamani1023]

Describe the bug

from anomalib.data import Folder

i tried to train model using custom dataset using following code and

Create the datamodule

datamodule = Folder(
name="bottle",
root="datasets/bottle",
normal_dir="good",
abnormal_dir="bad",
task="classification",
image_size=(512,512)
)

Setup the datamodule

datamodule.setup()

and

i used efficientad model for transfer learning ,
from anomalib.models import EfficientAd
from anomalib.engine import Engine

Create the model and engine

model = EfficientAd()
engine = Engine(task="classification")
engine.train(datamodule=datamodule, model=model)

but , i dont know how to set my custom epoch value , if i give that max_epochs parameter in anomalib\configs\model\efficient_ad.yaml ,it didnt work, how to change that?

Dataset

Other (please specify in the text field below)

Model

Other (please specify in the field below)

Steps to reproduce the behavior

from anomalib.data import Folder

i tried to train model using custom dataset using following code and

Create the datamodule

datamodule = Folder(
name="bottle",
root="datasets/bottle",
normal_dir="good",
abnormal_dir="bad",
task="classification",
image_size=(512,512)
)

Setup the datamodule

datamodule.setup()

and

i used efficientad model for transfer learning ,
from anomalib.models import EfficientAd
from anomalib.engine import Engine

Create the model and engine

model = EfficientAd()
engine = Engine(task="classification")
engine.train(datamodule=datamodule, model=model)

but , i dont know how to set my custom epoch value , if i give that max_epochs parameter in anomalib\configs\model\efficient_ad.yaml ,it didnt work, how to change that?

OS information

OS information:

• OS: [e.g. Ubuntu 20.04]
• Python version: [e.g. 3.10.0]
• Anomalib version: [e.g. 0.3.6]
• PyTorch version: [e.g. 1.9.0]
• CUDA/cuDNN version: [e.g. 11.1]
• GPU models and configuration: [e.g. 2x GeForce RTX 3090]
• Any other relevant information: [e.g. I'm using a custom dataset]

Expected behavior

null

Screenshots

Pip/GitHub

pip

What version/branch did you use?

No response

Configuration YAML

null

Logs

null

Code of Conduct

• I agree to follow this project's Code of Conduct

[samet-akcay]

You could set it when you instantiate Engine

model = EfficientAd()
engine = Engine(task="classification", max_epochs=1000)
engine.train(datamodule=datamodule, model=model)

but , i dont know how to set my custom epoch value , if i give that max_epochs parameter in anomalib\configs\model\efficient_ad.yaml ,it didnt work, how to change that?

[shanmugamani1023]

i tried that in Patchcore ,
# Import the model and engine
from anomalib.models import Patchcore
from anomalib.engine import Engine

Create the model and engine

model = Patchcore()
engine = Engine(task="classification",max_epochs=2)

Train a Patchcore model on the given datamodule

engine.train(datamodule=datamodule, model=model)
but it epoch runs only one time?

[blaz-r]

Patchcore isn't trained using backpropagation, so it runs only a single epoch in all cases. This is expected. If you want to learn more, check the Patchcore readme.

[shanmugamani1023]

thank you.