parameters: (tik_instance, input_x, res, input_shape, shape_info)
return_statement: return tik_instance, res
docstring: input_shape is ((32, 4, 56, 56, 16), 'float16', (3, 3), (1, 1))
docstring_summary: input_shape is ((32, 4, 56, 56, 16), 'float16', (3, 3), (1, 1))
docstring_tokens: input_shape is (( 32 4 56 56 16 ) float16 ( 3 3 ) ( 1 1 ))
function: def shape56_0(tik_instance, input_x, res, input_shape, shape_info):
      """input_shape is ((32, 4, 56, 56, 16), 'float16', (3, 3), (1, 1))"""
      stride_w, stride_h, filter_w, filter_h, dilation_filter_w, dilation_filter_h = shape_info
      pad = [1, 1, 1, 1]
      l1_h, l1_w, jump_stride, repeat_mode = 56, 56, 1, 1
      with tik_instance.for_range(0, 32, block_num=32) as block_index:
          input_1_1_local_l1 = tik_instance.Tensor("float16", (200704,), scope=tik.scope_cbuf,
                                                   name="input_1_1_local_l1")
          input_1_1_fractal_l1_local_ub = tik_instance.Tensor("float16", (50176,), scope=tik.scope_ubuf,
                                                              name="input_1_1_fractal_l1_local_ub")
          tik_instance.data_move(input_1_1_local_l1, input_x[block_index, 0, 0, 0, 0], 0, 1, 12544, 0, 0)
          with tik_instance.for_range(0, 9) as eeb0, tik_instance.for_range(0, 4) as eeb1:
              rep = 196
              fetch_filter_w = eeb0 % 3
              fetch_filter_h = eeb0 // 3
              left_top_w, left_top_h = -1, -1
              c1_index = eeb1
              tik_instance.load3dv1(input_1_1_fractal_l1_local_ub, input_1_1_local_l1, pad,
                                    l1_h, l1_w, c1_index, fetch_filter_w, fetch_filter_h, left_top_w,
                                    left_top_h, stride_w, stride_h, filter_w, filter_h, dilation_filter_w,
                                    dilation_filter_h, jump_stride, repeat_mode, rep)
              with tik_instance.for_range(0, rep) as i:
                  tik_instance.data_move(res[eeb1 * 9 + eeb0, i + 196 * block_index, 0, 0],
                                         input_1_1_fractal_l1_local_ub[i * 256], 0, 1, 16, 0, 0)
      return tik_instance, res
function_tokens: def shape56_0 ( tik_instance , input_x , res , input_shape , shape_info ) : stride_w , stride_h , filter_w , filter_h , dilation_filter_w , dilation_filter_h = shape_info pad = [ 1 , 1 , 1 , 1 ] l1_h , l1_w , jump_stride , repeat_mode = 56 , 56 , 1 , 1 with tik_instance . for_range ( 0 , 32 , block_num = 32 ) as block_index : input_1_1_local_l1 = tik_instance . Tensor ( "float16" , ( 200704 , ) , scope = tik . scope_cbuf , name = "input_1_1_local_l1" ) input_1_1_fractal_l1_local_ub = tik_instance . Tensor ( "float16" , ( 50176 , ) , scope = tik . scope_ubuf , name = "input_1_1_fractal_l1_local_ub" ) tik_instance . data_move ( input_1_1_local_l1 , input_x [ block_index , 0 , 0 , 0 , 0 ] , 0 , 1 , 12544 , 0 , 0 ) with tik_instance . for_range ( 0 , 9 ) as eeb0 , tik_instance . for_range ( 0 , 4 ) as eeb1 : rep = 196 fetch_filter_w = eeb0 % 3 fetch_filter_h = eeb0 // 3 left_top_w , left_top_h = - 1 , - 1 c1_index = eeb1 tik_instance . load3dv1 ( input_1_1_fractal_l1_local_ub , input_1_1_local_l1 , pad , l1_h , l1_w , c1_index , fetch_filter_w , fetch_filter_h , left_top_w , left_top_h , stride_w , stride_h , filter_w , filter_h , dilation_filter_w , dilation_filter_h , jump_stride , repeat_mode , rep ) with tik_instance . for_range ( 0 , rep ) as i : tik_instance . data_move ( res [ eeb1 * 9 + eeb0 , i + 196 * block_index , 0 , 0 ] , input_1_1_fractal_l1_local_ub [ i * 256 ] , 0 , 1 , 16 , 0 , 0 ) return tik_instance , res