updates
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@ -22,12 +22,12 @@ def load_classes(path):
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def model_info(model): # Plots a line-by-line description of a PyTorch model
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def model_info(model): # Plots a line-by-line description of a PyTorch model
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n_p = sum(x.numel() for x in model.parameters()) # number parameters
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n_p = sum(x.numel() for x in model.parameters()) # number parameters
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n_g = sum(x.numel() for x in model.parameters() if x.requires_grad) # number gradients
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n_g = sum(x.numel() for x in model.parameters() if x.requires_grad) # number gradients
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print('\n%4s %70s %9s %12s %20s %12s %12s' % ('', 'name', 'gradient', 'parameters', 'shape', 'mu', 'sigma'))
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print('\n%5s %50s %9s %12s %20s %12s %12s' % ('layer', 'name', 'gradient', 'parameters', 'shape', 'mu', 'sigma'))
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for i, (name, p) in enumerate(model.named_parameters()):
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for i, (name, p) in enumerate(model.named_parameters()):
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name = name.replace('module_list.', '')
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name = name.replace('module_list.', '')
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print('%4g %70s %9s %12g %20s %12g %12g' % (
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print('%5g %50s %9s %12g %20s %12g %12g' % (
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i, name, p.requires_grad, p.numel(), list(p.shape), p.mean(), p.std()))
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i, name, p.requires_grad, p.numel(), list(p.shape), p.mean(), p.std()))
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print('\nModel Summary: %g layers, %g parameters, %g gradients\n' % (i + 1, n_p, n_g))
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print('Model Summary: %g layers, %g parameters, %g gradients\n' % (i + 1, n_p, n_g))
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def class_weights(): # frequency of each class in coco train2014
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def class_weights(): # frequency of each class in coco train2014
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