Alex-grovety commented on issue #8717:
URL: https://github.com/apache/tvm/issues/8717#issuecomment-915870297
2.) We can use `compute_at` for DepthwiseConv2d and get:
```
PrimFunc([placeholder, placeholder, placeholder, placeholder, T_cast])
attrs={"from_legacy_te_schedule": (bool)1, "global_symbol":
"tvmgen_default_fused_nn_conv2d_subtract_add_fixed_point_multiply_clip_cast_10",
"tir.noalias": (bool)1} {
allocate DepthwiseConv2d[int32 * 1], storage_scope = global
for (ax0.ax1.fused.ax2.fused.ax3.fused, 0, 401408) {
DepthwiseConv2d[0] = 0
for (di, 0, 3) {
for (dj, 0, 3) {
DepthwiseConv2d[0] = (DepthwiseConv2d[0] +
(int32(placeholder[((((floordiv(ax0.ax1.fused.ax2.fused.ax3.fused, 7168)*7424)
+ (di*7424)) + (dj*128)) + floormod(ax0.ax1.fused.ax2.fused.ax3.fused,
7168))])*int32(placeholder[(((di*384) + (dj*128)) +
floormod(ax0.ax1.fused.ax2.fused.ax3.fused, 128))])))
}
}
T_cast[ax0.ax1.fused.ax2.fused.ax3.fused] =
uint8(max(min(tir.q_multiply_shift(((DepthwiseConv2d[0] +
placeholder[floormod(ax0.ax1.fused.ax2.fused.ax3.fused, 128)]) -
placeholder[ax0.ax1.fused.ax2.fused.ax3.fused]), 2080045879, 31, -4), 255), 0))
}
}
```
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