45a10bc6d708fade197a37bfbc62312caf70e6a7,keras/layers/convolutional_recurrent.py,ConvLSTM2D,get_constants,#ConvLSTM2D#Any#Any#,438

Before Change

        if self.implementation == 0 and 0 < self.dropout < 1:
            input_shape = K.int_shape(inputs)
            input_dim = input_shape[-1]
            ones = K.ones_like(K.reshape(inputs[:, 0, 0], (-1, 1)))
            ones = K.tile(ones, (1, int(input_dim)))

            def dropped_inputs():
                return K.dropout(ones, self.dropout)

After Change

    def get_constants(self, inputs, training=None):
        constants = []
        if self.implementation == 0 and 0 < self.dropout < 1:
            ones = K.zeros_like(inputs)
            ones = K.sum(ones, axis=1)
            ones += 1

            def dropped_inputs():
                return K.dropout(ones, self.dropout)

Instances