Here is the DAG in my case. ```python ========== Task 1 (workload key: ["33a10bb123ba1d747c97e5296eee59ed", 256, 1, 256, 1, 16, 16, 256, 1, 1, 256]) ========== compile_engine_const() = 0 placeholder = PLACEHOLDER [256, 1] T_repeat(ax0, ax1) = placeholder[ax0, floordiv(ax1, 2)] T_take(ax0) = T_repeat[ax0, (((compile_engine_const[] % 2) + 2) % 2)] compile_engine_const() = 1 T_take(ax0) = T_repeat[ax0, (((compile_engine_const[] % 2) + 2) % 2)] T_reshape(ax0, ax1) = T_take[floormod((ax0 + ax1), 256)] T_subtract(ax0, ax1) = (T_take[ax1] - T_reshape[ax0, 0]) compile_engine_const() = 0.0625f T_less(ax0, ax1) = (T_subtract[ax0, ax1] < compile_engine_const[]) T_cast(ax0, ax1) = T_less[ax0, ax1] compile_engine_const() = -0.0625f T_greater(ax0, ax1) = (T_subtract[ax0, ax1] > compile_engine_const[]) T_cast(ax0, ax1) = T_greater[ax0, ax1] T_logical_and(ax0, ax1) = (T_cast[ax0, ax1] && T_cast[ax0, ax1]) T_cast(ax0, ax1) = T_logical_and[ax0, ax1] compile_engine_const() = 0 placeholder = PLACEHOLDER [256, 1] T_repeat(ax0, ax1) = placeholder[ax0, floordiv(ax1, 2)] T_take(ax0) = T_repeat[ax0, (((compile_engine_const[] % 2) + 2) % 2)] compile_engine_const() = 1 T_take(ax0) = T_repeat[ax0, (((compile_engine_const[] % 2) + 2) % 2)] T_reshape(ax0, ax1) = T_take[floormod((ax0 + ax1), 256)] T_subtract(ax0, ax1) = (T_take[ax1] - T_reshape[ax0, 0]) compile_engine_const() = 0.0625f T_less(ax0, ax1) = (T_subtract[ax0, ax1] < compile_engine_const[]) T_cast(ax0, ax1) = T_less[ax0, ax1] T_logical_and(ax0, ax1) = (T_cast[ax0, ax1] && T_cast[ax0, ax1]) T_cast(ax0, ax1) = T_logical_and[ax0, ax1] compile_engine_const() = -0.0625f T_greater(ax0, ax1) = (T_subtract[ax0, ax1] > compile_engine_const[]) T_cast(ax0, ax1) = T_greater[ax0, ax1] T_logical_and(ax0, ax1) = (T_cast[ax0, ax1] && T_cast[ax0, ax1]) T_cast(ax0, ax1) = T_logical_and[ax0, ax1] placeholder = PLACEHOLDER [16, 16] T_cast(ax0, ax1) = float32(placeholder[ax0, ax1]) T_reshape(ax0, ax1) = T_cast[floormod(floordiv((ax0 + ax1), 16), 16), floormod((ax0 + ax1), 16)] T_repeat(ax0, ax1) = T_reshape[ax0, floordiv(ax1, 256)] T_cast(ax0, ax1) = bool(T_repeat[ax0, ax1]) T_reshape(ax0, ax1) = T_cast[floormod(floordiv(((ax0*256) + ax1), 16), 16), floormod(((ax0*256) + ax1), 16)] T_repeat(ax0, ax1) = T_reshape[floordiv(ax0, 256), ax1] T_cast(ax0, ax1) = bool(T_repeat[ax0, ax1]) T_logical_and(ax0, ax1) = (T_cast[ax0, ax1] && T_cast[ax0, ax1]) T_cast(ax0, ax1) = T_logical_and[ax0, ax1] T_logical_and(ax0, ax1) = (T_cast[ax0, ax1] && T_cast[ax0, ax1]) placeholder = PLACEHOLDER [256, 1] T_repeat(ax0, ax1) = placeholder[ax0, floordiv(ax1, 256)] placeholder = PLACEHOLDER [1] T_where(ax0, ax1) = select((int32(T_logical_and[ax0, ax1]) != 0), T_repeat[ax0, ax1], placeholder[0]) T_where_red_temp(ax0).v0 select((argmax_lhs_1 >= argmax_rhs_1), argmax_lhs_0, argmax_rhs_0)= (k1,T_where[ax0, k1]) T_where_red_temp(ax0).v1 select((argmax_lhs_1 >= argmax_rhs_1), argmax_lhs_1, argmax_rhs_1)= (k1,T_where[ax0, k1]) T_where_red(ax0) = T_where_red_temp.v0[ax0] ``` I excluded this task from the tuning task to continue my tuning work at last. I think it would be more make sense to skip the task than to block in the loop if auto-Schedule cannot search for a valid schedule.
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