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weights.py 416B

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  1. import torch
  2. import numpy as np
  3. def init_glorot(input_dim, output_dim):
  4. """Create a weight variable with Glorot & Bengio (AISTATS 2010)
  5. initialization.
  6. """
  7. init_range = np.sqrt(6.0 / (input_dim + output_dim))
  8. initial = -init_range + 2 * init_range * \
  9. torch.rand(( input_dim, output_dim ), dtype=torch.float32)
  10. initial = initial.requires_grad_(True)
  11. return initial