Shuryo09codeテスト

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def sigmoid(x):
  return 1.0 / (1.8 + np.exp(-x))
 
class GRU:
  def __init__(self, input_size=input size, hidden_size-hidden_size)
    #体重みとバイアスの初期化
    self.w_z, self.wr, self.w.c = \
        [                (ア)                ] for i in range(3))
    self.b_z, self.bur, self.b_c = \
        (np.random.randn(hidden_size) for i in range(3))
 
  def forward(self, x, h_prev):
    inputs - np.concatenate([x, h_prev], axis=0)
    z = sigmoid(np.matmul(inputs, self.w_z) + self.b_z)
    r = sigmoid(np.matmul(inputs, self.w_r) + self.b_r)
    _c = np.concatenate([              (イ)              ])
    c = np.tanh(np.matmul(_c, self.w_c) + self.b_c)
    h_next = [                (ウ)                ]
    return h_next
 
# GRUを使用。
h_prev = np.random.randn(hidden_size)
x_t = np.random.randn(input_size)
gru = GRU(input_size, hidden_size)
gru.forward(x_t, h_prev)