(self)
| 410 | self._init_params() |
| 411 | |
| 412 | def _init_params(self): |
| 413 | init_weights = WeightInitializer(str(self.act_fn_V), mode=self.init) |
| 414 | |
| 415 | b_in = np.zeros((1, self.n_in)) |
| 416 | b_out = np.zeros((1, self.n_out)) |
| 417 | W = init_weights((self.n_in, self.n_out)) |
| 418 | |
| 419 | self.parameters = {"W": W, "b_in": b_in, "b_out": b_out} |
| 420 | |
| 421 | self.gradients = { |
| 422 | "W": np.zeros_like(W), |
| 423 | "b_in": np.zeros_like(b_in), |
| 424 | "b_out": np.zeros_like(b_out), |
| 425 | } |
| 426 | |
| 427 | self.derived_variables = { |
| 428 | "V": None, |
| 429 | "p_H": None, |
| 430 | "p_V_prime": None, |
| 431 | "p_H_prime": None, |
| 432 | "positive_grad": None, |
| 433 | "negative_grad": None, |
| 434 | } |
| 435 | self.is_initialized = True |
| 436 | |
| 437 | @property |
| 438 | def hyperparameters(self): |
no test coverage detected