keras/src/layers/rnn/conv_lstm.py/ConvLSTMCell/input_conv
class ConvLSTMCell:    def input_conv(self, x, w, b=None, padding="valid"):
        conv_out = ops.conv(
            x,
            w,
            strides=self.strides,
            padding=padding,
            data_format=self.data_format,
            dilation_rate=self.dilation_rate,
        )
        if b is not None:
            if self.data_format == "channels_last":
                bias_shape = (1,) * (self.rank + 1) + (self.filters,)
            else:
                bias_shape = (1, self.filters) + (1,) * self.rank
            bias = ops.reshape(b, bias_shape)
            conv_out += bias
        return conv_out