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Hi, trying to solve a binary classification problem with these movinets and was wondering how I would go about creating a MoVinet with some augmentation with the aim of reducing the TFLOPS required and decreasing the inference time
The text was updated successfully, but these errors were encountered:
Hi, using (2+1)D convolution can reduce computation compared with 3D convolution. But I think the stream model should be well designed to decrease the inference time. Also, the stream buffer is returned by the model and sent back to the model in TF version, but that is stored inside the model in this PyTorch implementation. Maybe TF version is a good choice?!
Hi, trying to solve a binary classification problem with these movinets and was wondering how I would go about creating a MoVinet with some augmentation with the aim of reducing the TFLOPS required and decreasing the inference time
The text was updated successfully, but these errors were encountered: