code: def tvmgen_default_fused_nn_conv2d_add_fixed_point_multiply_clip_cast_cast_1(
      placeholder_10: T.handle,
      placeholder_11: T.handle,
      placeholder_12: T.handle,
      T_cast_4: T.handle,
      global_workspace_3_var: T.handle("uint8"),
  ) -> None:
      placeholder_13 = T.match_buffer(
          placeholder_10, [360000], dtype="int16"
      )
      placeholder_14 = T.match_buffer(
          placeholder_11, [36864], dtype="int16"
      )
      placeholder_15 = T.match_buffer(
          placeholder_12, [64], dtype="int32"
      )
      T_cast_5 = T.match_buffer(T_cast_4, [215], dtype="int16")
      global_workspace_3_buffer_var = T.match_buffer(
          global_workspace_3_var,
          [7920256],
          dtype="uint8",
          strides=[1],
          elem_offset=0,
          align=16,
      )
      # body
      PaddedInput_1_let = T.Buffer([379456], "int16")
      with T.LetStmt(
          T.address_of(
              global_workspace_3_buffer_var[0], dtype="handle"
          ),
          var=PaddedInput_1_let.data,
      ):
          for i0_i1_fused_1, i2_1, i3_1 in T.grid(77, 77, 64):
              PaddedInput_1_let[
                  i0_i1_fused_1 * 4928 + i2_1 * 64 + i3_1
              ] = T.if_then_else(
                  1 <= i0_i1_fused_1
                  and i0_i1_fused_1 < 76
                  and 1 <= i2_1
                  and i2_1 < 76,
                  placeholder_13[
                      i0_i1_fused_1 * 4800 + i2_1 * 64 + i3_1 - 4864
                  ],
                  T.int16(0),
                  dtype="int16",
              )
          for ax0_ax1_fused_ax2_fused_1 in T.serial(0, 5625):
              Conv2dOutput_1_let = T.Buffer([64], "int32")
              with T.LetStmt(
                  T.address_of(
                      global_workspace_3_buffer_var[7200000],
                      dtype="handle",
                  ),
                  var=Conv2dOutput_1_let.data,
              ):
                  for ff_1 in T.serial(0, 64):
                      Conv2dOutput_1_let[ff_1] = 0
                      for ry, rx, rc_1 in T.grid(3, 3, 64):
                          Conv2dOutput_1_let[ff_1] = Conv2dOutput_1_let[
                              ff_1
                          ] + T.cast(
                              PaddedInput_1_let[
                                  ax0_ax1_fused_ax2_fused_1 // 75 * 4928
                                  + ry * 4928
                                  + rx * 64
                                  + ax0_ax1_fused_ax2_fused_1 % 75 * 64
                                  + rc_1
                              ],
                              "int32",
                          ) * T.cast(
                              placeholder_14[
                                  ry * 12288
                                  + rx * 4096
                                  + rc_1 * 64
                                  + ff_1
                              ],
                              "int32",
                          )
                  for ax3_inner_2 in T.serial(0, 64):
                      T_cast_5[
                          ax0_ax1_fused_ax2_fused_1 * 64 + ax3_inner_2
                      ] = T.cast(
                          T.cast(
                              T.max(
                                  T.min(
                                      T.q_multiply_shift(
                                          Conv2dOutput_1_let[
                                              ax3_inner_2
                                          ]
                                          + placeholder_15[ax3_inner_2],
                                          1608879842,
                                          31,
                                          -7,
                                          dtype="int32",
                                      ),
                                      255,
                                  ),
                                  0,
                              ),
                              "uint8",
                          ),
                          "int16",
                      )
  
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 5 for calling the ResnetStructurePlanned obj's underlying member method code with example usage: obj.tvmgen_default_fused_nn_conv2d_add_fixed_point_multiply_clip_cast_cast_1(placeholder_10, placeholder_11, placeholder_12, T_cast_4, global_workspace_3_var) without return types