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.allocate([379456], "int16", "global")
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.allocate([64], "int32", "global")
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")
def tvmgen_default_fused_nn_conv2d_add_fixed_point_multiply_clip_cast(
placeholder_62: T.handle, placeholder_63: T.handle,
placeholder_64: T.handle, T_cast_20: T.handle) -> None:
# function attr dict
T.func_attr({
"global_symbol":
"tvmgen_default_fused_nn_conv2d_add_fixed_point_multiply_clip_cast",
"tir.noalias": True
})
placeholder_65 = T.match_buffer(placeholder_62, [1, 224, 224, 3],
dtype="int16",
elem_offset=0,
align=128,
offset_factor=1)
placeholder_66 = T.match_buffer(placeholder_63, [7, 7, 3, 64],
dtype="int16",
elem_offset=0,
align=128,
offset_factor=1)
placeholder_67 = T.match_buffer(placeholder_64, [1, 1, 1, 64],
dtype="int32",
elem_offset=0,
align=128,
offset_factor=1)
T_cast_21 = T.match_buffer(T_cast_20, [1, 112, 112, 64],
dtype="uint8",
elem_offset=0,
align=128,
offset_factor=1)
# body
PaddedInput_7 = T.allocate([157323], "int16", "global")
for i0_i1_fused_7 in T.serial(0, 229):
for i2_7, i3_7 in T.grid(229, 3):
T.store(
PaddedInput_7,
(((i0_i1_fused_7 * 687) + (i2_7 * 3)) + i3_7),
T.if_then_else(
((((2 <= i0_i1_fused_7) and (i0_i1_fused_7 < 226)) and
(2 <= i2_7)) and (i2_7 < 226)),
T.load("int16", placeholder_65.data,
((((i0_i1_fused_7 * 672) +
(i2_7 * 3)) + i3_7) - 1350)),
T.int16(0),
dtype="int16"), True)
for ax0_ax1_fused_ax2_fused_7 in T.serial(0, 12544):
Conv2dOutput_7 = T.allocate([64], "int32", "global")
for ff_3 in T.serial(0, 64):
T.store(Conv2dOutput_7, ff_3, 0, True)
for ry_2, rx_2, rc_7 in T.grid(7, 7, 3):
T.store(
Conv2dOutput_7, ff_3,
(T.load("int32", Conv2dOutput_7, ff_3) + (T.cast(
T.load("int16", PaddedInput_7, ((
(((T.floordiv(ax0_ax1_fused_ax2_fused_7, 112) *
1374) + (ry_2 * 687)) +
(T.floormod(ax0_ax1_fused_ax2_fused_7, 112) *
6)) +
(rx_2 * 3)) + rc_7)), "int32") * T.cast(
T.load("int16", placeholder_66.data,
((((ry_2 * 1344) + (rx_2 * 192)) +
(rc_7 * 64)) + ff_3)), "int32"))),
True)
for ax3_inner_7 in T.serial(0, 64):
T.store(
T_cast_21.data,
((ax0_ax1_fused_ax2_fused_7 * 64) + ax3_inner_7),
T.cast(
T.max(
T.min(
T.q_multiply_shift(
(T.load("int32", Conv2dOutput_7,
ax3_inner_7) +
T.load("int32", placeholder_67.data,
ax3_inner_7)),
1939887962,
31,
-9,
dtype="int32"), 255), 0), "uint8"), True)
def primfunc_global_allocates(placeholder_144: T.handle,
placeholder_145: T.handle,
placeholder_146: T.handle,
T_cast_48: T.handle) -> None:
# function attr dict
T.func_attr({
"global_symbol":
"fused_nn_conv2d_add_cast_fixed_point_multiply_clip_cast_cast_13",
"tir.noalias": True
})
placeholder_147 = T.match_buffer(placeholder_144, [100352],
dtype="int16",
elem_offset=0,
align=128,
offset_factor=1)
placeholder_148 = T.match_buffer(placeholder_145, [4608],
dtype="int16",
elem_offset=0,
align=128,
offset_factor=1)
placeholder_149 = T.match_buffer(placeholder_146, [512],
dtype="int32",
elem_offset=0,
align=128,
offset_factor=1)
T_cast_49 = T.match_buffer(T_cast_48, [100352],
dtype="int16",
elem_offset=0,
align=128,
offset_factor=1)
# body
PaddedInput_22 = T.allocate([131072], "int16", "global")
DepthwiseConv2d_9 = T.allocate([100352], "int32", "global")
for i1_29, i2_39, i3_40 in T.grid(16, 16, 512):
PaddedInput_22[(((i1_29 * 8192) + (i2_39 * 512)) +
i3_40)] = T.if_then_else(
((((1 <= i1_29) and (i1_29 < 15)) and
(1 <= i2_39)) and (i2_39 < 15)),
placeholder_147[((((i1_29 * 7168) +
(i2_39 * 512)) + i3_40) -
7680)],
T.int16(0),
dtype="int16")
for i_9, j_9, c_9 in T.grid(14, 14, 512):
DepthwiseConv2d_9[(((i_9 * 7168) + (j_9 * 512)) + c_9)] = 0
for di_9, dj_9 in T.grid(3, 3):
DepthwiseConv2d_9[(((i_9 * 7168) + (j_9 * 512)) + c_9)] = (
DepthwiseConv2d_9[(((i_9 * 7168) + (j_9 * 512)) + c_9)] +
(PaddedInput_22[(((((i_9 * 8192) + (di_9 * 8192)) +
(j_9 * 512)) +
(dj_9 * 512)) + c_9)].astype("int32") *
placeholder_148[(((di_9 * 1536) +
(dj_9 * 512)) + c_9)].astype("int32")))
for ax1_27, ax2_28, ax3_30 in T.grid(14, 14, 512):
DepthwiseConv2d_9[(((ax1_27 * 7168) + (ax2_28 * 512)) + ax3_30)] = (
DepthwiseConv2d_9[(((ax1_27 * 7168) + (ax2_28 * 512)) + ax3_30)] +
placeholder_149[ax3_30])
for i1_30, i2_40, i3_41 in T.grid(14, 14, 512):
DepthwiseConv2d_9[(((i1_30 * 7168) + (i2_40 * 512)) +
i3_41)] = T.q_multiply_shift(
DepthwiseConv2d_9[(((i1_30 * 7168) +
(i2_40 * 512)) + i3_41)],
1269068532,
31,
-4,
dtype="int32")
for i1_31, i2_41, i3_42 in T.grid(14, 14, 512):
DepthwiseConv2d_9[(((i1_31 * 7168) + (i2_41 * 512)) + i3_42)] = T.max(
T.max(
DepthwiseConv2d_9[(((i1_31 * 7168) + (i2_41 * 512)) + i3_42)],
255), 0)
for ax1_28, ax2_29, ax3_31 in T.grid(14, 14, 512):
PaddedInput_22[(((ax1_28 * 7168) + (ax2_29 * 512)) +
ax3_31)] = DepthwiseConv2d_9[(((ax1_28 * 7168) +
(ax2_29 * 512)) +
ax3_31)].astype("uint8")
for ax1_29, ax2_30, ax3_32 in T.grid(14, 14, 512):
T_cast_49[(((ax1_29 * 7168) + (ax2_30 * 512)) +
ax3_32)] = PaddedInput_22[(((ax1_29 * 7168) +
(ax2_30 * 512)) +
ax3_32)].astype("int16")
def primfunc_local_allocates(placeholder_162: T.handle,
placeholder_163: T.handle,
placeholder_164: T.handle,
T_cast_76: T.handle) -> None:
# function attr dict
T.func_attr({
"global_symbol":
"fused_nn_conv2d_add_cast_fixed_point_multiply_clip_cast_cast_9",
"tir.noalias": True
})
placeholder_165 = T.match_buffer(placeholder_162, [100352],
dtype="int16",
elem_offset=0,
align=128,
offset_factor=1)
placeholder_166 = T.match_buffer(placeholder_163, [4608],
dtype="int16",
elem_offset=0,
align=128,
offset_factor=1)
placeholder_167 = T.match_buffer(placeholder_164, [512],
dtype="int32",
elem_offset=0,
align=128,
offset_factor=1)
T_cast_77 = T.match_buffer(T_cast_76, [100352],
dtype="int16",
elem_offset=0,
align=128,
offset_factor=1)
# body
PaddedInput_25 = T.allocate([131072], "int16", "global")
for i1_35, i2_46, i3_47 in T.grid(16, 16, 512):
PaddedInput_25[(((i1_35 * 8192) + (i2_46 * 512)) +
i3_47)] = T.if_then_else(
((((1 <= i1_35) and (i1_35 < 15)) and
(1 <= i2_46)) and (i2_46 < 15)),
placeholder_165[((((i1_35 * 7168) +
(i2_46 * 512)) + i3_47) -
7680)],
T.int16(0),
dtype="int16")
T_add_11 = T.allocate([100352], "int32", "global")
with T.allocate([100352], "int32", "global") as DepthwiseConv2d_11:
for i_11, j_11, c_11 in T.grid(14, 14, 512):
DepthwiseConv2d_11[(((i_11 * 7168) + (j_11 * 512)) + c_11)] = 0
for di_11, dj_11 in T.grid(3, 3):
DepthwiseConv2d_11[(((i_11 * 7168) + (j_11 * 512)) + c_11)] = (
DepthwiseConv2d_11[(((i_11 * 7168) +
(j_11 * 512)) + c_11)] +
(PaddedInput_25[(((((i_11 * 8192) + (di_11 * 8192)) +
(j_11 * 512)) +
(dj_11 * 512)) + c_11)].astype("int32") *
placeholder_166[(
((di_11 * 1536) +
(dj_11 * 512)) + c_11)].astype("int32")))
for ax1_44, ax2_45, ax3_47 in T.grid(14, 14, 512):
T_add_11[(((ax1_44 * 7168) + (ax2_45 * 512)) +
ax3_47)] = (DepthwiseConv2d_11[((
(ax1_44 * 7168) + (ax2_45 * 512)) + ax3_47)] +
placeholder_167[ax3_47])
compute_22 = T.allocate([100352], "int32", "global")
with T.allocate([100352], "int32", "global") as T_cast_78:
for ax1_45, ax2_46, ax3_48 in T.grid(14, 14, 512):
T_cast_78[(((ax1_45 * 7168) + (ax2_46 * 512)) +
ax3_48)] = T_add_11[(((ax1_45 * 7168) +
(ax2_46 * 512)) + ax3_48)]
for i1_36, i2_47, i3_48 in T.grid(14, 14, 512):
compute_22[(((i1_36 * 7168) + (i2_47 * 512)) +
i3_48)] = T.q_multiply_shift(
T_cast_78[(((i1_36 * 7168) + (i2_47 * 512)) +
i3_48)],
1948805937,
31,
-5,
dtype="int32")
T_cast_79 = T.allocate([100352], "uint8", "global")
with T.allocate([100352], "int32", "global") as compute_23:
for i1_37, i2_48, i3_49 in T.grid(14, 14, 512):
compute_23[(((i1_37 * 7168) + (i2_48 * 512)) + i3_49)] = T.max(
T.max(compute_22[(((i1_37 * 7168) + (i2_48 * 512)) + i3_49)],
255), 0)
for ax1_46, ax2_47, ax3_49 in T.grid(14, 14, 512):
T_cast_79[(((ax1_46 * 7168) + (ax2_47 * 512)) +
ax3_49)] = compute_23[(((ax1_46 * 7168) +
(ax2_47 * 512)) +
ax3_49)].astype("uint8")
for ax1_47, ax2_48, ax3_50 in T.grid(14, 14, 512):
T_cast_77[(((ax1_47 * 7168) + (ax2_48 * 512)) +
ax3_50)] = T_cast_79[(((ax1_47 * 7168) + (ax2_48 * 512)) +
ax3_50)].astype("int16")