Rt1-VIT-bert #14
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Rt1-VIT-bert #14
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sebbyjp
requested changes
Jun 10, 2024
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motion is the correct folder name
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We only need this, vit, tokenizers, and learner
| "cuda" if torch.cuda.is_available() else "cpu" | ||
| ) | ||
| model_name = 'bert-base-uncased' | ||
| self.tokenizer = BertTokenizer.from_pretrained(model_name) |
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dont reinitialize every call
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This call is in the constructor / __init__ method. So its only initialized once when we create the Rt1Agent object
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observation, action, history size, image size should not be hard coded, use the current ones in the file as default values in case the config doesn't specify them.
| from mbodied_agents.types.controls import Motion | ||
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| class MotorAgent(ABC): |
nqyy
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Changed EfficientNet to ViT and Integrated BERT Text Encoder for
rt1Description
This update replaces the existing EfficientNet model with a Vision Transformer (ViT) and integrates a BERT text encoder for
rt1. The current implementation includes a dummy sample to test the network functionality. The training part is not included in this update.Summary:
How Has This Been Tested?
The changes have been verified by running a dummy sample to ensure the network functionality works as expected.
Testing:
Checklist