(self, params)
| 79 | return np.concatenate([self.W1.flatten(), self.b1, self.W2.flatten(), self.b2]) |
| 80 | |
| 81 | def set_params(self, params): |
| 82 | # params is a flat list |
| 83 | # unflatten into individual weights |
| 84 | D, M, K = self.D, self.M, self.K |
| 85 | self.W1 = params[:D * M].reshape(D, M) |
| 86 | self.b1 = params[D * M:D * M + M] |
| 87 | self.W2 = params[D * M + M:D * M + M + M * K].reshape(M, K) |
| 88 | self.b2 = params[-K:] |
| 89 | |
| 90 | |
| 91 | def evolution_strategy( |
no outgoing calls
no test coverage detected