code: def tvmgen_default_fused_nn_conv2d_add_fixed_point_multiply_add_clip_cast_cast_subtract_fixed_point_4200876283395191415_(
      placeholder_22: T.handle,
      placeholder_23: T.handle,
      placeholder_24: T.handle,
      placeholder_25: T.handle,
      T_cast_6: T.handle,
      global_workspace_5_var: T.handle("uint8"),
  ) -> None:
      placeholder_29 = T.match_buffer(
          placeholder_22, [360000], dtype="int16"
      )
      placeholder_27 = T.match_buffer(
          placeholder_23, [16384], dtype="int16"
      )
      placeholder_26 = T.match_buffer(
          placeholder_24, [256], dtype="int32"
      )
      placeholder_28 = T.match_buffer(
          placeholder_25, [1440000], dtype="int32"
      )
      T_cast_7 = T.match_buffer(T_cast_6, [407], dtype="uint8")
      global_workspace_5_buffer_var = T.match_buffer(
          global_workspace_5_var,
          [7920256],
          dtype="uint8",
          strides=[1],
          elem_offset=0,
          align=16,
      )
      # body
      PaddedInput_3_let = T.Buffer([360000], "int16")
      with T.LetStmt(
          T.address_of(
              global_workspace_5_buffer_var[6480000], dtype="handle"
          ),
          var=PaddedInput_3_let.data,
      ):
          for i0_i1_fused_3, i2_3, i3_3 in T.grid(75, 75, 64):
              PaddedInput_3_let[
                  i0_i1_fused_3 * 4800 + i2_3 * 64 + i3_3
              ] = placeholder_29[
                  i0_i1_fused_3 * 4800 + i2_3 * 64 + i3_3
              ]
          for ax0_ax1_fused_ax2_fused_3 in T.serial(0, 5625):
              Conv2dOutput_3_let = T.Buffer([64], "int32")
              with T.LetStmt(
                  T.address_of(
                      global_workspace_5_buffer_var[7200000],
                      dtype="handle",
                  ),
                  var=Conv2dOutput_3_let.data,
              ):
                  for ax3_outer_2 in T.serial(0, 4):
                      for ff_3 in T.serial(0, 64):
                          Conv2dOutput_3_let[ff_3] = 0
                          for rc_3 in T.serial(0, 64):
                              Conv2dOutput_3_let[
                                  ff_3
                              ] = Conv2dOutput_3_let[ff_3] + T.cast(
                                  PaddedInput_3_let[
                                      ax0_ax1_fused_ax2_fused_3 * 64
                                      + rc_3
                                  ],
                                  "int32",
                              ) * T.cast(
                                  placeholder_27[
                                      rc_3 * 256
                                      + ax3_outer_2 * 64
                                      + ff_3
                                  ],
                                  "int32",
                              )
                      for ax3_inner_4 in T.serial(0, 64):
                          T_cast_7[
                              ax0_ax1_fused_ax2_fused_3 * 256
                              + ax3_outer_2 * 64
                              + ax3_inner_4
                          ] = T.cast(
                              T.max(
                                  T.min(
                                      T.q_multiply_shift(
                                          T.cast(
                                              T.cast(
                                                  T.max(
                                                      T.min(
                                                          T.q_multiply_shift(
                                                              Conv2dOutput_3_let[
                                                                  ax3_inner_4
                                                              ]
                                                              + placeholder_26[
                                                                  ax3_outer_2
                                                                  * 64
                                                                  + ax3_inner_4
                                                              ],
                                                              1343014664,
                                                              31,
                                                              -8,
                                                              dtype="int32",
                                                          )
                                                          + 136,
                                                          255,
                                                      ),
                                                      0,
                                                  ),
                                                  "uint8",
                                              ),
                                              "int32",
                                          )
                                          - 136,
                                          1073903788,
                                          31,
                                          1,
                                          dtype="int32",
                                      )
                                      + placeholder_28[
                                          ax0_ax1_fused_ax2_fused_3
                                          * 256
                                          + ax3_outer_2 * 64
                                          + ax3_inner_4
                                      ],
                                      255,
                                  ),
                                  0,
                              ),
                              "uint8",
                          )
  
imports: import sys
  import pytest
  import tvm
  from tvm import PoolInfoProperties, WorkspacePoolInfo
  from tvm.script import tir, ir
  from tvm.target import Target
  from tvm.tir import stmt_functor
  from tvm.tir.usmp import utils
label_desc: Use image node_id 2 for calling the ResnetStructurePlanned obj's underlying member method code with example usage: obj.tvmgen_default_fused_nn_conv2d_add_fixed_point_multiply_add_clip_cast_cast_subtract_fixed_point_4200876283395191415_(placeholder_22, placeholder_23, placeholder_24, placeholder_25, T_cast_6, global_workspace_5_var) without return types