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Method _init_params

numpy_ml/neural_nets/layers/layers.py:3626–3652  ·  view source on GitHub ↗
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3624 self.is_initialized = False
3625
3626 def _init_params(self):
3627 self.X = []
3628 init_weights = WeightInitializer(str(self.act_fn), mode=self.init)
3629
3630 Wax = init_weights((self.n_in, self.n_out))
3631 Waa = init_weights((self.n_out, self.n_out))
3632 ba = np.zeros((self.n_out, 1))
3633 bx = np.zeros((self.n_out, 1))
3634
3635 self.parameters = {"Waa": Waa, "Wax": Wax, "ba": ba, "bx": bx}
3636
3637 self.gradients = {
3638 "Waa": np.zeros_like(Waa),
3639 "Wax": np.zeros_like(Wax),
3640 "ba": np.zeros_like(ba),
3641 "bx": np.zeros_like(bx),
3642 }
3643
3644 self.derived_variables = {
3645 "A": [],
3646 "Z": [],
3647 "n_timesteps": 0,
3648 "current_step": 0,
3649 "dLdA_accumulator": None,
3650 }
3651
3652 self.is_initialized = True
3653
3654 @property
3655 def hyperparameters(self):

Callers 1

forwardMethod · 0.95

Calls 1

WeightInitializerClass · 0.85

Tested by

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