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,
  ) -> None:
      # function attr dict
      T.func_attr(
          {
              "global_symbol": "tvmgen_default_fused_nn_conv2d_add_fixed_point_multiply_clip_cast_cast_1",
              "tir.noalias": True,
          }
      )
      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, [360000], dtype="int16")
      # body
      PaddedInput_1 = T.decl_buffer([379456], "int16")
      for i0_i1_fused_1, i2_1, i3_1 in T.grid(77, 77, 64):
          PaddedInput_1[
              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 = T.decl_buffer([64], "int32")
          for ff_1 in T.serial(0, 64):
              Conv2dOutput_1[ff_1] = 0
              for ry, rx, rc_1 in T.grid(3, 3, 64):
                  Conv2dOutput_1[ff_1] = Conv2dOutput_1[ff_1] + T.cast(
                      PaddedInput_1[
                          T.floordiv(ax0_ax1_fused_ax2_fused_1, 75)
                          * 4928
                          + ry * 4928
                          + rx * 64
                          + T.floormod(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[ax3_inner_2]
                                  + placeholder_15[ax3_inner_2],
                                  1608879842,
                                  31,
                                  -7,
                                  dtype="int32",
                              ),
                              255,
                          ),
                          0,
                      ),
                      "uint8",
                  ),
                  "int16",
              )
  
imports: import pytest
  import tvm
  from tvm import tir, script
  from tvm.script import tir
  from tvm.tir import stmt_functor
  from tvm.tir.usmp import utils
  from tvm.target import Target
  from tvm import WorkspacePoolInfo, PoolInfoProperties
label_desc: Use image node_id 2 for calling the ResnetStructure 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) without return types