glenn-jocher commited on
Commit
5a9c5c1
·
1 Parent(s): f1c63e2

add mosaic and warmup to hyperparameters (#931)

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Files changed (1) hide show
  1. utils/general.py +2 -2
utils/general.py CHANGED
@@ -1210,13 +1210,13 @@ def plot_evolution(yaml_file='data/hyp.finetune.yaml'): # from utils.general im
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  x = np.loadtxt('evolve.txt', ndmin=2)
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  f = fitness(x)
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  # weights = (f - f.min()) ** 2 # for weighted results
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- plt.figure(figsize=(10, 10), tight_layout=True)
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  matplotlib.rc('font', **{'size': 8})
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  for i, (k, v) in enumerate(hyp.items()):
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  y = x[:, i + 7]
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  # mu = (y * weights).sum() / weights.sum() # best weighted result
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  mu = y[f.argmax()] # best single result
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- plt.subplot(5, 5, i + 1)
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  plt.scatter(y, f, c=hist2d(y, f, 20), cmap='viridis', alpha=.8, edgecolors='none')
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  plt.plot(mu, f.max(), 'k+', markersize=15)
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  plt.title('%s = %.3g' % (k, mu), fontdict={'size': 9}) # limit to 40 characters
 
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  x = np.loadtxt('evolve.txt', ndmin=2)
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  f = fitness(x)
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  # weights = (f - f.min()) ** 2 # for weighted results
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+ plt.figure(figsize=(10, 12), tight_layout=True)
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  matplotlib.rc('font', **{'size': 8})
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  for i, (k, v) in enumerate(hyp.items()):
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  y = x[:, i + 7]
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  # mu = (y * weights).sum() / weights.sum() # best weighted result
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  mu = y[f.argmax()] # best single result
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+ plt.subplot(6, 5, i + 1)
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  plt.scatter(y, f, c=hist2d(y, f, 20), cmap='viridis', alpha=.8, edgecolors='none')
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  plt.plot(mu, f.max(), 'k+', markersize=15)
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  plt.title('%s = %.3g' % (k, mu), fontdict={'size': 9}) # limit to 40 characters