parameters: (tik_instance, input_x, res, dtype)
return_statement: return tik_instance, res
docstring: input shape (32, 8, 56, 56, 16)
docstring_summary: input shape (32, 8, 56, 56, 16)
docstring_tokens: input shape ( 32 8 56 56 16 )
function: def shape3(tik_instance, input_x, res, dtype):
      """input shape (32, 8, 56, 56, 16)"""
      zero = tik_instance.Scalar(dtype="float16", init_value=0)
      with tik_instance.for_range(0, 32, block_num=32) as block_idx, tik_instance.for_range(0, 7) as cc1_db, \
              tik_instance.for_range(0, 2, thread_num=2) as db_idx:
          input_1_local_ub = tik_instance.Tensor(dtype, [28672], name="input_1_local_ub",
                                                 scope=tik.scope_ubuf)
          t_transpose_local_ub = tik_instance.Tensor(dtype, [28672], name="t_transpose_local_ub",
                                                     scope=tik.scope_ubuf)
          tik_instance.data_move(input_1_local_ub,
                                 input_x[block_idx * 401408 + cc1_db * 7168 + 3584 * db_idx], 0, 8, 224,
                                 2912, 0)
          with tik_instance.for_range(0, 224) as cc7, tik_instance.for_range(0, 16) as cc8:
              tik_instance.vadds(16, t_transpose_local_ub[cc7 * 128 + cc8 * 16],
                                 input_1_local_ub[3584 * cc8 + cc7 * 16], zero, 1, 1, 1, 0, 0)
          tik_instance.data_move(res[block_idx * 401408 + cc1_db * 57344 + 28672 * db_idx],
                                 t_transpose_local_ub, 0, 1, 1792, 0, 0)
      return tik_instance, res
function_tokens: def shape3 ( tik_instance , input_x , res , dtype ) : zero = tik_instance . Scalar ( dtype = "float16" , init_value = 0 ) with tik_instance . for_range ( 0 , 32 , block_num = 32 ) as block_idx , tik_instance . for_range ( 0 , 7 ) as cc1_db , tik_instance . for_range ( 0 , 2 , thread_num = 2 ) as db_idx : input_1_local_ub = tik_instance . Tensor ( dtype , [ 28672 ] , name = "input_1_local_ub" , scope = tik . scope_ubuf ) t_transpose_local_ub = tik_instance . Tensor ( dtype , [ 28672 ] , name = "t_transpose_local_ub" , scope = tik . scope_ubuf ) tik_instance . data_move ( input_1_local_ub , input_x [ block_idx * 401408 + cc1_db * 7168 + 3584 * db_idx ] , 0 , 8 , 224 , 2912 , 0 ) with tik_instance . for_range ( 0 , 224 ) as cc7 , tik_instance . for_range ( 0 , 16 ) as cc8 : tik_instance . vadds ( 16 , t_transpose_local_ub [ cc7 * 128 + cc8 * 16 ] , input_1_local_ub [ 3584 * cc8 + cc7 * 16 ] , zero , 1 , 1 , 1 , 0 , 0 ) tik_instance . data_move ( res [ block_idx * 401408 + cc1_db * 57344 + 28672 * db_idx ] , t_transpose_local_ub , 0 , 1 , 1792 , 0 , 0 ) return tik_instance , res