93ff2240f329431e77f3e613a8dbfaab911c82e9,keras/layers/recurrent.py,JZS1,__init__,#JZS1#Any#Any#Any#Any#Any#Any#Any#Any#Any#,392

Before Change

        self.b_h = shared_zeros((self.output_dim))

        // P_h used to project X onto different dimension
        P = np.ones((self.input_dim, self.output_dim), dtype=theano.config.floatX)
        P = P / np.linalg.norm(P, axis=0)
        self.Pmat = theano.shared(P, name=None)

        self.params = [
            self.W_z, self.b_z,
            self.W_r, self.U_r, self.b_r,

After Change

        weights=None, truncate_gradient=-1, return_sequences=False):

        super(JZS1,self).__init__()
        self.input_dim = input_dim
        self.output_dim = output_dim
        self.truncate_gradient = truncate_gradient
        self.return_sequences = return_sequences

        self.init = initializations.get(init)
        self.inner_init = initializations.get(inner_init)
        self.activation = activations.get(activation)
        self.inner_activation = activations.get(inner_activation)
        self.input = T.tensor3()

        self.W_z = self.init((self.input_dim, self.output_dim))
        self.b_z = shared_zeros((self.output_dim))

        self.W_r = self.init((self.input_dim, self.output_dim))
        self.U_r = self.inner_init((self.output_dim, self.output_dim))
        self.b_r = shared_zeros((self.output_dim))

        self.U_h = self.inner_init((self.output_dim, self.output_dim))
        self.b_h = shared_zeros((self.output_dim))

        // P_h used to project X onto different dimension, using sparse random projections
        if self.input_dim == self.output_dim:
            self.Pmat = theano.shared(np.identity(self.output_dim), name=None)
        else:
            P = np.random.binomial(1, 0.5, size=(self.input_dim, self.output_dim)) * 2 - 1
            P = 1 / np.sqrt(self.input_dim) * P
            self.Pmat = theano.shared(P, name=None)

        self.params = [
            self.W_z, self.b_z,
            self.W_r, self.U_r, self.b_r,
            self.U_h, self.b_h,

Instances