liming-ai / ControlNet_Plus_Plus

Official PyTorch implementation of ECCV 2024 Paper: ControlNet++: Improving Conditional Controls with Efficient Consistency Feedback.
https://liming-ai.github.io/ControlNet_Plus_Plus
Apache License 2.0
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GPU hours of training #7

Closed wangherr closed 3 months ago

wangherr commented 3 months ago

Hi,

I’m interested in knowing the GPU hours used for training the code. Could you please provide this information?

Thank you!

liming-ai commented 3 months ago

Hi,

I’m interested in knowing the GPU hours used for training the code. Could you please provide this information?

Thank you!

The training time is around 7.5 hours for 8 A100 GPUs , when training 5000 iterations with a batch size 256 (4 gradient_accumulation_steps)

wangherr commented 3 months ago

In the paper,there are two stage: Stage 1: "We first fine-tune the pre-trained ControlNet until convergence using a batch size of 256 and a learning rate of 1e-5."

Stage 2: "We then employ the same batch size and learning rate for 5k iterations for reward fine-tuning."

From my understanding, Stage 2 costs about 60 GPU hours, while Stage 1 takes very little time and can be considered negligible. Is this correct?

liming-ai commented 3 months ago

In the paper,there are two stage: Stage 1: "We first fine-tune the pre-trained ControlNet until convergence using a batch size of 256 and a learning rate of 1e-5."

Stage 2: "We then employ the same batch size and learning rate for 5k iterations for reward fine-tuning."

From my understanding, Stage 2 costs about 60 GPU hours, while Stage 1 takes very little time and can be considered negligible. Is this correct?

Yes, you're right.