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Questions and Answers
Which convention is commonly used to save PyTorch checkpoints?
Which convention is commonly used to save PyTorch checkpoints?
What should be done before running inference to ensure consistent results?
What should be done before running inference to ensure consistent results?
When is it helpful to warmstart the training process using trained parameters?
When is it helpful to warmstart the training process using trained parameters?
Which function in PyTorch is used to access the learnable parameters of a model?
Which function in PyTorch is used to access the learnable parameters of a model?
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Which type of layers have entries in the model's state_dict?
Which type of layers have entries in the model's state_dict?
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What is the purpose of the optimizer's state_dict in PyTorch?
What is the purpose of the optimizer's state_dict in PyTorch?
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Which method is recommended for saving models in PyTorch?
Which method is recommended for saving models in PyTorch?
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What should be done before running inference with dropout and batch normalization layers?
What should be done before running inference with dropout and batch normalization layers?
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Which format is recommended for scaled inference and deployment in PyTorch?
Which format is recommended for scaled inference and deployment in PyTorch?
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What should be saved when creating a general checkpoint for inference and/or resuming training?
What should be saved when creating a general checkpoint for inference and/or resuming training?
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