47ed18a3af8be20dce91286a331d4671074ee0ca,keras/layers/recurrent.py,LSTM,build,#LSTM#,398

Before Change

    def build(self):
        input_dim = self.input_shape[2]
        self.input = T.tensor3()

        self.W_i = self.init((input_dim, self.output_dim))
        self.U_i = self.inner_init((self.output_dim, self.output_dim))
        self.b_i = shared_zeros((self.output_dim))

After Change

    def build(self):
        input_shape = self.input_shape
        input_dim = input_shape[2]
        self.input_dim = input_dim
        self.input = K.placeholder(input_shape)

        if self.stateful:
            if not input_shape[0]:
                raise Exception("If a RNN is stateful, a complete " +
                                "input_shape must be provided " +
                                "(including batch size).")
            self.states = [K.zeros(input_shape[0], self.output_dim),
                           K.zeros(input_shape[0], self.output_dim)]
        else:
            // initial states: 2 all-zero tensor of shape (output_dim)
            self.states = [None, None]

        self.W_i = self.init((input_dim, self.output_dim))
        self.U_i = self.inner_init((self.output_dim, self.output_dim))
        self.b_i = K.zeros((self.output_dim))

Instances