import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
from torch.cuda import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
reinterpret_tensor = torch._C._dynamo.guards._reinterpret_tensor


@triton.jit
def triton_poi_fused_convolution_0(in_out_ptr0, in_ptr0, xnumel, XBLOCK: tl
    .constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = xindex // 4096 % 16
    tmp0 = tl.load(in_out_ptr0 + x3, None)
    tmp1 = tl.load(in_ptr0 + x1, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tl.store(in_out_ptr0 + x3, tmp2, None)


@triton.jit
def triton_red_fused__native_batch_norm_legit_1(in_ptr0, out_ptr0, out_ptr1,
    out_ptr2, xnumel, rnumel, XBLOCK: tl.constexpr, RBLOCK: tl.constexpr):
    xnumel = 32
    rnumel = 8192
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
    xmask = xindex < xnumel
    rbase = tl.arange(0, RBLOCK)[None, :]
    x0 = xindex % 16
    x1 = xindex // 16
    tmp2_mean = tl.zeros([XBLOCK, RBLOCK], tl.float32)
    tmp2_m2 = tl.zeros([XBLOCK, RBLOCK], tl.float32)
    tmp2_weight = tl.zeros([XBLOCK, RBLOCK], tl.float32)
    x3 = xindex
    for roffset in range(0, rnumel, RBLOCK):
        rindex = roffset + rbase
        rmask = rindex < rnumel
        r2 = rindex
        tmp0 = tl.load(in_ptr0 + (4096 * x0 + 65536 * (r2 // 4096) + 131072 *
            x1 + r2 % 4096), rmask & xmask, eviction_policy='evict_first',
            other=0.0)
        tmp1 = tl.broadcast_to(tmp0, [XBLOCK, RBLOCK])
        tmp2_mean_next, tmp2_m2_next, tmp2_weight_next = (triton_helpers.
            welford_reduce(tmp1, tmp2_mean, tmp2_m2, tmp2_weight, roffset == 0)
            )
        tmp2_mean = tl.where(rmask & xmask, tmp2_mean_next, tmp2_mean)
        tmp2_m2 = tl.where(rmask & xmask, tmp2_m2_next, tmp2_m2)
        tmp2_weight = tl.where(rmask & xmask, tmp2_weight_next, tmp2_weight)
    tmp2_tmp, tmp3_tmp, tmp4_tmp = triton_helpers.welford(tmp2_mean,
        tmp2_m2, tmp2_weight, 1)
    tmp2 = tmp2_tmp[:, None]
    tmp3 = tmp3_tmp[:, None]
    tmp4 = tmp4_tmp[:, None]
    tl.store(out_ptr0 + x3, tmp2, xmask)
    tl.store(out_ptr1 + x3, tmp3, xmask)
    tl.store(out_ptr2 + x3, tmp4, xmask)


@triton.jit
def triton_per_fused__native_batch_norm_legit_2(in_ptr0, in_ptr1, in_ptr2,
    out_ptr0, out_ptr1, out_ptr2, xnumel, rnumel, XBLOCK: tl.constexpr):
    xnumel = 16
    RBLOCK: tl.constexpr = 2
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
    xmask = xindex < xnumel
    rindex = tl.arange(0, RBLOCK)[None, :]
    tl.full([XBLOCK, RBLOCK], True, tl.int1)
    r1 = rindex
    x0 = xindex
    tmp0 = tl.load(in_ptr0 + (x0 + 16 * r1), xmask, other=0.0)
    tmp1 = tl.load(in_ptr1 + (x0 + 16 * r1), xmask, other=0.0)
    tmp2 = tl.load(in_ptr2 + (x0 + 16 * r1), xmask, other=0.0)
    tmp3 = tl.broadcast_to(tmp0, [XBLOCK, RBLOCK])
    tmp4 = tl.broadcast_to(tmp1, [XBLOCK, RBLOCK])
    tmp5 = tl.broadcast_to(tmp2, [XBLOCK, RBLOCK])
    tmp7 = tl.where(xmask, tmp3, 0)
    tmp8 = tl.where(xmask, tmp4, 0)
    tmp9 = tl.where(xmask, tmp5, 0)
    tmp10, tmp11, tmp12 = triton_helpers.welford(tmp7, tmp8, tmp9, 1)
    tmp13 = tmp10[:, None]
    tmp14 = tmp11[:, None]
    tmp12[:, None]
    tmp16 = 16384.0
    tmp17 = tmp14 / tmp16
    tmp18 = 1e-05
    tmp19 = tmp17 + tmp18
    tmp20 = libdevice.rsqrt(tmp19)
    tl.store(out_ptr2 + x0, tmp20, xmask)
    tl.store(out_ptr0 + x0, tmp13, xmask)
    tl.store(out_ptr1 + x0, tmp14, xmask)


@triton.jit
def triton_poi_fused__native_batch_norm_legit_relu_3(in_ptr0, in_ptr1,
    in_ptr2, in_ptr3, in_ptr4, out_ptr0, xnumel, XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = xindex // 4096 % 16
    tmp0 = tl.load(in_ptr0 + x3, None)
    tmp1 = tl.load(in_ptr1 + x1, None, eviction_policy='evict_last')
    tmp3 = tl.load(in_ptr2 + x1, None, eviction_policy='evict_last')
    tmp10 = tl.load(in_ptr3 + x1, None, eviction_policy='evict_last')
    tmp12 = tl.load(in_ptr4 + x1, None, eviction_policy='evict_last')
    tmp2 = tmp0 - tmp1
    tmp4 = 16384.0
    tmp5 = tmp3 / tmp4
    tmp6 = 1e-05
    tmp7 = tmp5 + tmp6
    tmp8 = libdevice.rsqrt(tmp7)
    tmp9 = tmp2 * tmp8
    tmp11 = tmp9 * tmp10
    tmp13 = tmp11 + tmp12
    tmp14 = tl.full([1], 0, tl.int32)
    tmp15 = triton_helpers.maximum(tmp14, tmp13)
    tl.store(out_ptr0 + x3, tmp15, None)


@triton.jit
def triton_poi_fused_max_pool2d_with_indices_4(in_ptr0, out_ptr0, out_ptr1,
    xnumel, XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x0 = xindex % 32
    x1 = xindex // 32
    x2 = xindex
    tmp0 = tl.load(in_ptr0 + (2 * x0 + 128 * x1), None, eviction_policy=
        'evict_last')
    tmp1 = tl.load(in_ptr0 + (1 + 2 * x0 + 128 * x1), None, eviction_policy
        ='evict_last')
    tmp3 = tl.load(in_ptr0 + (64 + 2 * x0 + 128 * x1), None,
        eviction_policy='evict_last')
    tmp5 = tl.load(in_ptr0 + (65 + 2 * x0 + 128 * x1), None,
        eviction_policy='evict_last')
    tmp2 = triton_helpers.maximum(tmp1, tmp0)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tmp6 = triton_helpers.maximum(tmp5, tmp4)
    tmp7 = tmp1 > tmp0
    tmp8 = tl.full([1], 1, tl.int8)
    tmp9 = tl.full([1], 0, tl.int8)
    tmp10 = tl.where(tmp7, tmp8, tmp9)
    tmp11 = tmp3 > tmp2
    tmp12 = tl.full([1], 2, tl.int8)
    tmp13 = tl.where(tmp11, tmp12, tmp10)
    tmp14 = tmp5 > tmp4
    tmp15 = tl.full([1], 3, tl.int8)
    tmp16 = tl.where(tmp14, tmp15, tmp13)
    tl.store(out_ptr0 + x2, tmp6, None)
    tl.store(out_ptr1 + x2, tmp16, None)


@triton.jit
def triton_poi_fused_convolution_5(in_out_ptr0, in_ptr0, xnumel, XBLOCK: tl
    .constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = xindex // 1024 % 32
    tmp0 = tl.load(in_out_ptr0 + x3, None)
    tmp1 = tl.load(in_ptr0 + x1, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tl.store(in_out_ptr0 + x3, tmp2, None)


@triton.jit
def triton_red_fused__native_batch_norm_legit_6(in_ptr0, out_ptr0, out_ptr1,
    out_ptr2, xnumel, rnumel, XBLOCK: tl.constexpr, RBLOCK: tl.constexpr):
    xnumel = 32
    rnumel = 4096
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
    xmask = xindex < xnumel
    rbase = tl.arange(0, RBLOCK)[None, :]
    x0 = xindex
    tmp2_mean = tl.zeros([XBLOCK, RBLOCK], tl.float32)
    tmp2_m2 = tl.zeros([XBLOCK, RBLOCK], tl.float32)
    tmp2_weight = tl.zeros([XBLOCK, RBLOCK], tl.float32)
    for roffset in range(0, rnumel, RBLOCK):
        rindex = roffset + rbase
        rmask = rindex < rnumel
        r1 = rindex % 1024
        r2 = rindex // 1024
        tmp0 = tl.load(in_ptr0 + (r1 + 1024 * x0 + 32768 * r2), rmask &
            xmask, eviction_policy='evict_first', other=0.0)
        tmp1 = tl.broadcast_to(tmp0, [XBLOCK, RBLOCK])
        tmp2_mean_next, tmp2_m2_next, tmp2_weight_next = (triton_helpers.
            welford_reduce(tmp1, tmp2_mean, tmp2_m2, tmp2_weight, roffset == 0)
            )
        tmp2_mean = tl.where(rmask & xmask, tmp2_mean_next, tmp2_mean)
        tmp2_m2 = tl.where(rmask & xmask, tmp2_m2_next, tmp2_m2)
        tmp2_weight = tl.where(rmask & xmask, tmp2_weight_next, tmp2_weight)
    tmp2_tmp, tmp3_tmp, tmp4_tmp = triton_helpers.welford(tmp2_mean,
        tmp2_m2, tmp2_weight, 1)
    tmp2 = tmp2_tmp[:, None]
    tmp3 = tmp3_tmp[:, None]
    tmp4_tmp[:, None]
    tl.store(out_ptr0 + x0, tmp2, xmask)
    tl.store(out_ptr1 + x0, tmp3, xmask)
    tmp5 = 4096.0
    tmp6 = tmp3 / tmp5
    tmp7 = 1e-05
    tmp8 = tmp6 + tmp7
    tmp9 = libdevice.rsqrt(tmp8)
    tl.store(out_ptr2 + x0, tmp9, xmask)


@triton.jit
def triton_poi_fused__native_batch_norm_legit_relu_7(in_ptr0, in_ptr1,
    in_ptr2, in_ptr3, in_ptr4, out_ptr0, xnumel, XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = xindex // 1024 % 32
    tmp0 = tl.load(in_ptr0 + x3, None)
    tmp1 = tl.load(in_ptr1 + x1, None, eviction_policy='evict_last')
    tmp3 = tl.load(in_ptr2 + x1, None, eviction_policy='evict_last')
    tmp10 = tl.load(in_ptr3 + x1, None, eviction_policy='evict_last')
    tmp12 = tl.load(in_ptr4 + x1, None, eviction_policy='evict_last')
    tmp2 = tmp0 - tmp1
    tmp4 = 4096.0
    tmp5 = tmp3 / tmp4
    tmp6 = 1e-05
    tmp7 = tmp5 + tmp6
    tmp8 = libdevice.rsqrt(tmp7)
    tmp9 = tmp2 * tmp8
    tmp11 = tmp9 * tmp10
    tmp13 = tmp11 + tmp12
    tmp14 = tl.full([1], 0, tl.int32)
    tmp15 = triton_helpers.maximum(tmp14, tmp13)
    tl.store(out_ptr0 + x3, tmp15, None)


@triton.jit
def triton_poi_fused_max_pool2d_with_indices_8(in_ptr0, out_ptr0, out_ptr1,
    xnumel, XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x0 = xindex % 16
    x1 = xindex // 16
    x2 = xindex
    tmp0 = tl.load(in_ptr0 + (2 * x0 + 64 * x1), None, eviction_policy=
        'evict_last')
    tmp1 = tl.load(in_ptr0 + (1 + 2 * x0 + 64 * x1), None, eviction_policy=
        'evict_last')
    tmp3 = tl.load(in_ptr0 + (32 + 2 * x0 + 64 * x1), None, eviction_policy
        ='evict_last')
    tmp5 = tl.load(in_ptr0 + (33 + 2 * x0 + 64 * x1), None, eviction_policy
        ='evict_last')
    tmp2 = triton_helpers.maximum(tmp1, tmp0)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tmp6 = triton_helpers.maximum(tmp5, tmp4)
    tmp7 = tmp1 > tmp0
    tmp8 = tl.full([1], 1, tl.int8)
    tmp9 = tl.full([1], 0, tl.int8)
    tmp10 = tl.where(tmp7, tmp8, tmp9)
    tmp11 = tmp3 > tmp2
    tmp12 = tl.full([1], 2, tl.int8)
    tmp13 = tl.where(tmp11, tmp12, tmp10)
    tmp14 = tmp5 > tmp4
    tmp15 = tl.full([1], 3, tl.int8)
    tmp16 = tl.where(tmp14, tmp15, tmp13)
    tl.store(out_ptr0 + x2, tmp6, None)
    tl.store(out_ptr1 + x2, tmp16, None)


@triton.jit
def triton_poi_fused_convolution_9(in_out_ptr0, in_ptr0, xnumel, XBLOCK: tl
    .constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = xindex // 256 % 64
    tmp0 = tl.load(in_out_ptr0 + x3, None)
    tmp1 = tl.load(in_ptr0 + x1, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tl.store(in_out_ptr0 + x3, tmp2, None)


@triton.jit
def triton_per_fused__native_batch_norm_legit_10(in_ptr0, out_ptr0,
    out_ptr1, out_ptr2, xnumel, rnumel):
    XBLOCK: tl.constexpr = 1
    RBLOCK: tl.constexpr = 1024
    xoffset = tl.program_id(0) * XBLOCK
    xindex = tl.full([1], xoffset, tl.int32)
    tl.full([RBLOCK], True, tl.int1)
    rindex = tl.arange(0, RBLOCK)[:]
    tl.full([RBLOCK], True, tl.int1)
    r1 = rindex % 256
    r2 = rindex // 256
    x0 = xindex
    tmp0 = tl.load(in_ptr0 + (r1 + 256 * x0 + 16384 * r2), None)
    tmp1 = tl.broadcast_to(tmp0, [RBLOCK])
    tmp3 = tl.broadcast_to(tmp1, [RBLOCK])
    tmp5 = triton_helpers.promote_to_tensor(tl.sum(tmp3, 0))
    tmp6 = tl.full([1], 1024, tl.int32)
    tmp7 = tmp6.to(tl.float32)
    tmp8 = tmp5 / tmp7
    tmp9 = tmp1 - tmp8
    tmp10 = tmp9 * tmp9
    tmp11 = tl.broadcast_to(tmp10, [RBLOCK])
    tmp13 = triton_helpers.promote_to_tensor(tl.sum(tmp11, 0))
    tmp14 = 1024.0
    tmp15 = tmp13 / tmp14
    tmp16 = 1e-05
    tmp17 = tmp15 + tmp16
    tmp18 = libdevice.rsqrt(tmp17)
    tl.store(out_ptr2 + x0, tmp18, None)
    tl.store(out_ptr0 + x0, tmp8, None)
    tl.store(out_ptr1 + x0, tmp13, None)


@triton.jit
def triton_poi_fused__native_batch_norm_legit_relu_11(in_ptr0, in_ptr1,
    in_ptr2, in_ptr3, in_ptr4, out_ptr0, xnumel, XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = xindex // 256 % 64
    tmp0 = tl.load(in_ptr0 + x3, None)
    tmp1 = tl.load(in_ptr1 + x1, None, eviction_policy='evict_last')
    tmp3 = tl.load(in_ptr2 + x1, None, eviction_policy='evict_last')
    tmp10 = tl.load(in_ptr3 + x1, None, eviction_policy='evict_last')
    tmp12 = tl.load(in_ptr4 + x1, None, eviction_policy='evict_last')
    tmp2 = tmp0 - tmp1
    tmp4 = 1024.0
    tmp5 = tmp3 / tmp4
    tmp6 = 1e-05
    tmp7 = tmp5 + tmp6
    tmp8 = libdevice.rsqrt(tmp7)
    tmp9 = tmp2 * tmp8
    tmp11 = tmp9 * tmp10
    tmp13 = tmp11 + tmp12
    tmp14 = tl.full([1], 0, tl.int32)
    tmp15 = triton_helpers.maximum(tmp14, tmp13)
    tl.store(out_ptr0 + x3, tmp15, None)


@triton.jit
def triton_poi_fused_max_pool2d_with_indices_12(in_ptr0, out_ptr0, out_ptr1,
    xnumel, XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x0 = xindex % 8
    x1 = xindex // 8
    x2 = xindex
    tmp0 = tl.load(in_ptr0 + (2 * x0 + 32 * x1), None, eviction_policy=
        'evict_last')
    tmp1 = tl.load(in_ptr0 + (1 + 2 * x0 + 32 * x1), None, eviction_policy=
        'evict_last')
    tmp3 = tl.load(in_ptr0 + (16 + 2 * x0 + 32 * x1), None, eviction_policy
        ='evict_last')
    tmp5 = tl.load(in_ptr0 + (17 + 2 * x0 + 32 * x1), None, eviction_policy
        ='evict_last')
    tmp2 = triton_helpers.maximum(tmp1, tmp0)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tmp6 = triton_helpers.maximum(tmp5, tmp4)
    tmp7 = tmp1 > tmp0
    tmp8 = tl.full([1], 1, tl.int8)
    tmp9 = tl.full([1], 0, tl.int8)
    tmp10 = tl.where(tmp7, tmp8, tmp9)
    tmp11 = tmp3 > tmp2
    tmp12 = tl.full([1], 2, tl.int8)
    tmp13 = tl.where(tmp11, tmp12, tmp10)
    tmp14 = tmp5 > tmp4
    tmp15 = tl.full([1], 3, tl.int8)
    tmp16 = tl.where(tmp14, tmp15, tmp13)
    tl.store(out_ptr0 + x2, tmp6, None)
    tl.store(out_ptr1 + x2, tmp16, None)


@triton.jit
def triton_poi_fused_convolution_13(in_out_ptr0, in_ptr0, xnumel, XBLOCK:
    tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = xindex // 64 % 128
    tmp0 = tl.load(in_out_ptr0 + x3, None)
    tmp1 = tl.load(in_ptr0 + x1, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tl.store(in_out_ptr0 + x3, tmp2, None)


@triton.jit
def triton_per_fused__native_batch_norm_legit_14(in_ptr0, out_ptr0,
    out_ptr1, out_ptr2, xnumel, rnumel):
    XBLOCK: tl.constexpr = 1
    RBLOCK: tl.constexpr = 256
    xoffset = tl.program_id(0) * XBLOCK
    xindex = tl.full([1], xoffset, tl.int32)
    tl.full([RBLOCK], True, tl.int1)
    rindex = tl.arange(0, RBLOCK)[:]
    tl.full([RBLOCK], True, tl.int1)
    r1 = rindex % 64
    r2 = rindex // 64
    x0 = xindex
    tmp0 = tl.load(in_ptr0 + (r1 + 64 * x0 + 8192 * r2), None)
    tmp1 = tl.broadcast_to(tmp0, [RBLOCK])
    tmp3 = tl.broadcast_to(tmp1, [RBLOCK])
    tmp5 = triton_helpers.promote_to_tensor(tl.sum(tmp3, 0))
    tmp6 = tl.full([1], 256, tl.int32)
    tmp7 = tmp6.to(tl.float32)
    tmp8 = tmp5 / tmp7
    tmp9 = tmp1 - tmp8
    tmp10 = tmp9 * tmp9
    tmp11 = tl.broadcast_to(tmp10, [RBLOCK])
    tmp13 = triton_helpers.promote_to_tensor(tl.sum(tmp11, 0))
    tmp14 = 256.0
    tmp15 = tmp13 / tmp14
    tmp16 = 1e-05
    tmp17 = tmp15 + tmp16
    tmp18 = libdevice.rsqrt(tmp17)
    tl.store(out_ptr2 + x0, tmp18, None)
    tl.store(out_ptr0 + x0, tmp8, None)
    tl.store(out_ptr1 + x0, tmp13, None)


@triton.jit
def triton_poi_fused__native_batch_norm_legit_relu_15(in_ptr0, in_ptr1,
    in_ptr2, in_ptr3, in_ptr4, out_ptr0, xnumel, XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = xindex // 64 % 128
    tmp0 = tl.load(in_ptr0 + x3, None)
    tmp1 = tl.load(in_ptr1 + x1, None, eviction_policy='evict_last')
    tmp3 = tl.load(in_ptr2 + x1, None, eviction_policy='evict_last')
    tmp10 = tl.load(in_ptr3 + x1, None, eviction_policy='evict_last')
    tmp12 = tl.load(in_ptr4 + x1, None, eviction_policy='evict_last')
    tmp2 = tmp0 - tmp1
    tmp4 = 256.0
    tmp5 = tmp3 / tmp4
    tmp6 = 1e-05
    tmp7 = tmp5 + tmp6
    tmp8 = libdevice.rsqrt(tmp7)
    tmp9 = tmp2 * tmp8
    tmp11 = tmp9 * tmp10
    tmp13 = tmp11 + tmp12
    tmp14 = tl.full([1], 0, tl.int32)
    tmp15 = triton_helpers.maximum(tmp14, tmp13)
    tl.store(out_ptr0 + x3, tmp15, None)


@triton.jit
def triton_poi_fused_max_pool2d_with_indices_16(in_ptr0, out_ptr0, out_ptr1,
    xnumel, XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x0 = xindex % 4
    x1 = xindex // 4
    x2 = xindex
    tmp0 = tl.load(in_ptr0 + (2 * x0 + 16 * x1), None, eviction_policy=
        'evict_last')
    tmp1 = tl.load(in_ptr0 + (1 + 2 * x0 + 16 * x1), None, eviction_policy=
        'evict_last')
    tmp3 = tl.load(in_ptr0 + (8 + 2 * x0 + 16 * x1), None, eviction_policy=
        'evict_last')
    tmp5 = tl.load(in_ptr0 + (9 + 2 * x0 + 16 * x1), None, eviction_policy=
        'evict_last')
    tmp2 = triton_helpers.maximum(tmp1, tmp0)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tmp6 = triton_helpers.maximum(tmp5, tmp4)
    tmp7 = tmp1 > tmp0
    tmp8 = tl.full([1], 1, tl.int8)
    tmp9 = tl.full([1], 0, tl.int8)
    tmp10 = tl.where(tmp7, tmp8, tmp9)
    tmp11 = tmp3 > tmp2
    tmp12 = tl.full([1], 2, tl.int8)
    tmp13 = tl.where(tmp11, tmp12, tmp10)
    tmp14 = tmp5 > tmp4
    tmp15 = tl.full([1], 3, tl.int8)
    tmp16 = tl.where(tmp14, tmp15, tmp13)
    tl.store(out_ptr0 + x2, tmp6, None)
    tl.store(out_ptr1 + x2, tmp16, None)


@triton.jit
def triton_poi_fused_convolution_17(in_out_ptr0, in_ptr0, xnumel, XBLOCK:
    tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = xindex // 16 % 256
    tmp0 = tl.load(in_out_ptr0 + x3, None)
    tmp1 = tl.load(in_ptr0 + x1, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tl.store(in_out_ptr0 + x3, tmp2, None)


@triton.jit
def triton_per_fused__native_batch_norm_legit_18(in_ptr0, out_ptr0,
    out_ptr1, out_ptr2, xnumel, rnumel, XBLOCK: tl.constexpr):
    xnumel = 256
    RBLOCK: tl.constexpr = 64
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
    xmask = xindex < xnumel
    rindex = tl.arange(0, RBLOCK)[None, :]
    tl.full([XBLOCK, RBLOCK], True, tl.int1)
    r1 = rindex % 16
    r2 = rindex // 16
    x0 = xindex
    tmp0 = tl.load(in_ptr0 + (r1 + 16 * x0 + 4096 * r2), xmask, other=0.0)
    tmp1 = tl.broadcast_to(tmp0, [XBLOCK, RBLOCK])
    tl.where(xmask, tmp1, 0)
    tmp4 = tl.broadcast_to(tmp1, [XBLOCK, RBLOCK])
    tmp6 = tl.where(xmask, tmp4, 0)
    tmp7 = tl.sum(tmp6, 1)[:, None]
    tmp8 = tl.full([XBLOCK, 1], 64, tl.int32)
    tmp9 = tmp8.to(tl.float32)
    tmp10 = tmp7 / tmp9
    tmp11 = tmp1 - tmp10
    tmp12 = tmp11 * tmp11
    tmp13 = tl.broadcast_to(tmp12, [XBLOCK, RBLOCK])
    tmp15 = tl.where(xmask, tmp13, 0)
    tmp16 = tl.sum(tmp15, 1)[:, None]
    tmp17 = 64.0
    tmp18 = tmp16 / tmp17
    tmp19 = 1e-05
    tmp20 = tmp18 + tmp19
    tmp21 = libdevice.rsqrt(tmp20)
    tl.store(out_ptr2 + x0, tmp21, xmask)
    tl.store(out_ptr0 + x0, tmp10, xmask)
    tl.store(out_ptr1 + x0, tmp16, xmask)


@triton.jit
def triton_poi_fused__native_batch_norm_legit_relu_19(in_ptr0, in_ptr1,
    in_ptr2, in_ptr3, in_ptr4, out_ptr0, xnumel, XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = xindex // 16 % 256
    tmp0 = tl.load(in_ptr0 + x3, None)
    tmp1 = tl.load(in_ptr1 + x1, None, eviction_policy='evict_last')
    tmp3 = tl.load(in_ptr2 + x1, None, eviction_policy='evict_last')
    tmp10 = tl.load(in_ptr3 + x1, None, eviction_policy='evict_last')
    tmp12 = tl.load(in_ptr4 + x1, None, eviction_policy='evict_last')
    tmp2 = tmp0 - tmp1
    tmp4 = 64.0
    tmp5 = tmp3 / tmp4
    tmp6 = 1e-05
    tmp7 = tmp5 + tmp6
    tmp8 = libdevice.rsqrt(tmp7)
    tmp9 = tmp2 * tmp8
    tmp11 = tmp9 * tmp10
    tmp13 = tmp11 + tmp12
    tmp14 = tl.full([1], 0, tl.int32)
    tmp15 = triton_helpers.maximum(tmp14, tmp13)
    tl.store(out_ptr0 + x3, tmp15, None)


@triton.jit
def triton_poi_fused__native_batch_norm_legit_relu_threshold_backward_20(
    in_ptr0, in_ptr1, in_ptr2, in_ptr3, in_ptr4, out_ptr0, out_ptr1, xnumel,
    XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = xindex // 16 % 256
    tmp0 = tl.load(in_ptr0 + x3, None)
    tmp1 = tl.load(in_ptr1 + x1, None, eviction_policy='evict_last')
    tmp3 = tl.load(in_ptr2 + x1, None, eviction_policy='evict_last')
    tmp10 = tl.load(in_ptr3 + x1, None, eviction_policy='evict_last')
    tmp12 = tl.load(in_ptr4 + x1, None, eviction_policy='evict_last')
    tmp2 = tmp0 - tmp1
    tmp4 = 64.0
    tmp5 = tmp3 / tmp4
    tmp6 = 1e-05
    tmp7 = tmp5 + tmp6
    tmp8 = libdevice.rsqrt(tmp7)
    tmp9 = tmp2 * tmp8
    tmp11 = tmp9 * tmp10
    tmp13 = tmp11 + tmp12
    tmp14 = tl.full([1], 0, tl.int32)
    tmp15 = triton_helpers.maximum(tmp14, tmp13)
    tmp16 = 0.0
    tmp17 = tmp15 <= tmp16
    tl.store(out_ptr0 + x3, tmp15, None)
    tl.store(out_ptr1 + x3, tmp17, None)


@triton.jit
def triton_poi_fused__to_copy_add_arange_mul_21(out_ptr0, xnumel, XBLOCK:
    tl.constexpr):
    xnumel = 8
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x0 = xindex
    tmp0 = x0
    tmp1 = tmp0.to(tl.float32)
    tmp2 = 0.5
    tmp3 = tmp1 * tmp2
    tmp4 = tmp3.to(tl.int32)
    tl.store(out_ptr0 + x0, tmp4, xmask)


@triton.jit
def triton_poi_fused__unsafe_index_constant_pad_nd_22(in_ptr0, in_ptr1,
    out_ptr0, xnumel, XBLOCK: tl.constexpr):
    xnumel = 82944
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x1 = xindex // 9 % 9
    x0 = xindex % 9
    x2 = xindex // 81
    x4 = xindex
    tmp0 = x1
    tmp1 = tl.full([1], 8, tl.int64)
    tmp2 = tmp0 < tmp1
    tmp3 = x0
    tmp4 = tmp3 < tmp1
    tmp5 = tmp2 & tmp4
    tmp6 = tl.load(in_ptr0 + x1, tmp5 & xmask, eviction_policy='evict_last',
        other=0.0)
    tmp7 = tl.full([XBLOCK], 4, tl.int32)
    tmp8 = tmp6 + tmp7
    tmp9 = tmp6 < 0
    tmp10 = tl.where(tmp9, tmp8, tmp6)
    tmp11 = tl.load(in_ptr0 + x0, tmp5 & xmask, eviction_policy=
        'evict_last', other=0.0)
    tmp12 = tmp11 + tmp7
    tmp13 = tmp11 < 0
    tmp14 = tl.where(tmp13, tmp12, tmp11)
    tmp15 = tl.load(in_ptr1 + (tmp14 + 4 * tmp10 + 16 * x2), tmp5 & xmask,
        eviction_policy='evict_last', other=0.0)
    tl.store(out_ptr0 + x4, tmp15, xmask)


@triton.jit
def triton_poi_fused_cat_23(in_ptr0, in_ptr1, in_ptr2, out_ptr0, xnumel,
    XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x1 = xindex // 64 % 256
    x0 = xindex % 64
    x2 = xindex // 16384
    x3 = xindex
    tmp0 = x1
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 128, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (x0 + 64 * x1 + 8192 * x2), tmp4, other=0.0)
    tmp6 = tmp0 >= tmp3
    tl.full([1], 256, tl.int64)
    tmp9 = tl.load(in_ptr1 + (x0 + 64 * (-128 + x1) + 8192 * x2), tmp6,
        other=0.0)
    tmp10 = tl.load(in_ptr2 + (-128 + x1), tmp6, eviction_policy=
        'evict_last', other=0.0)
    tmp11 = tmp9 + tmp10
    tmp12 = tl.full(tmp11.shape, 0.0, tmp11.dtype)
    tmp13 = tl.where(tmp6, tmp11, tmp12)
    tmp14 = tl.where(tmp4, tmp5, tmp13)
    tl.store(out_ptr0 + x3, tmp14, None)


@triton.jit
def triton_poi_fused__native_batch_norm_legit_relu_threshold_backward_24(
    in_ptr0, in_ptr1, in_ptr2, in_ptr3, in_ptr4, out_ptr0, out_ptr1, xnumel,
    XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = xindex // 64 % 128
    tmp0 = tl.load(in_ptr0 + x3, None)
    tmp1 = tl.load(in_ptr1 + x1, None, eviction_policy='evict_last')
    tmp3 = tl.load(in_ptr2 + x1, None, eviction_policy='evict_last')
    tmp10 = tl.load(in_ptr3 + x1, None, eviction_policy='evict_last')
    tmp12 = tl.load(in_ptr4 + x1, None, eviction_policy='evict_last')
    tmp2 = tmp0 - tmp1
    tmp4 = 256.0
    tmp5 = tmp3 / tmp4
    tmp6 = 1e-05
    tmp7 = tmp5 + tmp6
    tmp8 = libdevice.rsqrt(tmp7)
    tmp9 = tmp2 * tmp8
    tmp11 = tmp9 * tmp10
    tmp13 = tmp11 + tmp12
    tmp14 = tl.full([1], 0, tl.int32)
    tmp15 = triton_helpers.maximum(tmp14, tmp13)
    tmp16 = 0.0
    tmp17 = tmp15 <= tmp16
    tl.store(out_ptr0 + x3, tmp15, None)
    tl.store(out_ptr1 + x3, tmp17, None)


@triton.jit
def triton_poi_fused__to_copy_add_arange_mul_25(out_ptr0, xnumel, XBLOCK:
    tl.constexpr):
    xnumel = 16
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x0 = xindex
    tmp0 = x0
    tmp1 = tmp0.to(tl.float32)
    tmp2 = 0.5
    tmp3 = tmp1 * tmp2
    tmp4 = tmp3.to(tl.int32)
    tl.store(out_ptr0 + x0, tmp4, xmask)


@triton.jit
def triton_poi_fused__unsafe_index_constant_pad_nd_26(in_ptr0, in_ptr1,
    out_ptr0, xnumel, XBLOCK: tl.constexpr):
    xnumel = 147968
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x1 = xindex // 17 % 17
    x0 = xindex % 17
    x2 = xindex // 289
    x4 = xindex
    tmp0 = x1
    tmp1 = tl.full([1], 16, tl.int64)
    tmp2 = tmp0 < tmp1
    tmp3 = x0
    tmp4 = tmp3 < tmp1
    tmp5 = tmp2 & tmp4
    tmp6 = tl.load(in_ptr0 + x1, tmp5 & xmask, eviction_policy='evict_last',
        other=0.0)
    tmp7 = tl.full([XBLOCK], 8, tl.int32)
    tmp8 = tmp6 + tmp7
    tmp9 = tmp6 < 0
    tmp10 = tl.where(tmp9, tmp8, tmp6)
    tmp11 = tl.load(in_ptr0 + x0, tmp5 & xmask, eviction_policy=
        'evict_last', other=0.0)
    tmp12 = tmp11 + tmp7
    tmp13 = tmp11 < 0
    tmp14 = tl.where(tmp13, tmp12, tmp11)
    tmp15 = tl.load(in_ptr1 + (tmp14 + 8 * tmp10 + 64 * x2), tmp5 & xmask,
        eviction_policy='evict_last', other=0.0)
    tl.store(out_ptr0 + x4, tmp15, xmask)


@triton.jit
def triton_poi_fused_cat_27(in_ptr0, in_ptr1, in_ptr2, out_ptr0, xnumel,
    XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x1 = xindex // 256 % 128
    x0 = xindex % 256
    x2 = xindex // 32768
    x3 = xindex
    tmp0 = x1
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 64, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (x0 + 256 * x1 + 16384 * x2), tmp4, other=0.0)
    tmp6 = tmp0 >= tmp3
    tl.full([1], 128, tl.int64)
    tmp9 = tl.load(in_ptr1 + (x0 + 256 * (-64 + x1) + 16384 * x2), tmp6,
        other=0.0)
    tmp10 = tl.load(in_ptr2 + (-64 + x1), tmp6, eviction_policy=
        'evict_last', other=0.0)
    tmp11 = tmp9 + tmp10
    tmp12 = tl.full(tmp11.shape, 0.0, tmp11.dtype)
    tmp13 = tl.where(tmp6, tmp11, tmp12)
    tmp14 = tl.where(tmp4, tmp5, tmp13)
    tl.store(out_ptr0 + x3, tmp14, None)


@triton.jit
def triton_poi_fused__native_batch_norm_legit_relu_threshold_backward_28(
    in_ptr0, in_ptr1, in_ptr2, in_ptr3, in_ptr4, out_ptr0, out_ptr1, xnumel,
    XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = xindex // 256 % 64
    tmp0 = tl.load(in_ptr0 + x3, None)
    tmp1 = tl.load(in_ptr1 + x1, None, eviction_policy='evict_last')
    tmp3 = tl.load(in_ptr2 + x1, None, eviction_policy='evict_last')
    tmp10 = tl.load(in_ptr3 + x1, None, eviction_policy='evict_last')
    tmp12 = tl.load(in_ptr4 + x1, None, eviction_policy='evict_last')
    tmp2 = tmp0 - tmp1
    tmp4 = 1024.0
    tmp5 = tmp3 / tmp4
    tmp6 = 1e-05
    tmp7 = tmp5 + tmp6
    tmp8 = libdevice.rsqrt(tmp7)
    tmp9 = tmp2 * tmp8
    tmp11 = tmp9 * tmp10
    tmp13 = tmp11 + tmp12
    tmp14 = tl.full([1], 0, tl.int32)
    tmp15 = triton_helpers.maximum(tmp14, tmp13)
    tmp16 = 0.0
    tmp17 = tmp15 <= tmp16
    tl.store(out_ptr0 + x3, tmp15, None)
    tl.store(out_ptr1 + x3, tmp17, None)


@triton.jit
def triton_poi_fused__to_copy_add_arange_mul_29(out_ptr0, xnumel, XBLOCK:
    tl.constexpr):
    xnumel = 32
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x0 = xindex
    tmp0 = x0
    tmp1 = tmp0.to(tl.float32)
    tmp2 = 0.5
    tmp3 = tmp1 * tmp2
    tmp4 = tmp3.to(tl.int32)
    tl.store(out_ptr0 + x0, tmp4, xmask)


@triton.jit
def triton_poi_fused__unsafe_index_constant_pad_nd_30(in_ptr0, in_ptr1,
    out_ptr0, xnumel, XBLOCK: tl.constexpr):
    xnumel = 278784
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x1 = xindex // 33 % 33
    x0 = xindex % 33
    x2 = xindex // 1089
    x4 = xindex
    tmp0 = x1
    tmp1 = tl.full([1], 32, tl.int64)
    tmp2 = tmp0 < tmp1
    tmp3 = x0
    tmp4 = tmp3 < tmp1
    tmp5 = tmp2 & tmp4
    tmp6 = tl.load(in_ptr0 + x1, tmp5 & xmask, eviction_policy='evict_last',
        other=0.0)
    tmp7 = tl.full([XBLOCK], 16, tl.int32)
    tmp8 = tmp6 + tmp7
    tmp9 = tmp6 < 0
    tmp10 = tl.where(tmp9, tmp8, tmp6)
    tmp11 = tl.load(in_ptr0 + x0, tmp5 & xmask, eviction_policy=
        'evict_last', other=0.0)
    tmp12 = tmp11 + tmp7
    tmp13 = tmp11 < 0
    tmp14 = tl.where(tmp13, tmp12, tmp11)
    tmp15 = tl.load(in_ptr1 + (tmp14 + 16 * tmp10 + 256 * x2), tmp5 & xmask,
        eviction_policy='evict_last', other=0.0)
    tl.store(out_ptr0 + x4, tmp15, xmask)


@triton.jit
def triton_poi_fused_cat_31(in_ptr0, in_ptr1, in_ptr2, out_ptr0, xnumel,
    XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x1 = xindex // 1024 % 64
    x0 = xindex % 1024
    x2 = xindex // 65536
    x3 = xindex
    tmp0 = x1
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 32, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (x0 + 1024 * x1 + 32768 * x2), tmp4, other=0.0)
    tmp6 = tmp0 >= tmp3
    tl.full([1], 64, tl.int64)
    tmp9 = tl.load(in_ptr1 + (x0 + 1024 * (-32 + x1) + 32768 * x2), tmp6,
        other=0.0)
    tmp10 = tl.load(in_ptr2 + (-32 + x1), tmp6, eviction_policy=
        'evict_last', other=0.0)
    tmp11 = tmp9 + tmp10
    tmp12 = tl.full(tmp11.shape, 0.0, tmp11.dtype)
    tmp13 = tl.where(tmp6, tmp11, tmp12)
    tmp14 = tl.where(tmp4, tmp5, tmp13)
    tl.store(out_ptr0 + x3, tmp14, None)


@triton.jit
def triton_poi_fused__native_batch_norm_legit_relu_threshold_backward_32(
    in_ptr0, in_ptr1, in_ptr2, in_ptr3, in_ptr4, out_ptr0, out_ptr1, xnumel,
    XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = xindex // 1024 % 32
    tmp0 = tl.load(in_ptr0 + x3, None)
    tmp1 = tl.load(in_ptr1 + x1, None, eviction_policy='evict_last')
    tmp3 = tl.load(in_ptr2 + x1, None, eviction_policy='evict_last')
    tmp10 = tl.load(in_ptr3 + x1, None, eviction_policy='evict_last')
    tmp12 = tl.load(in_ptr4 + x1, None, eviction_policy='evict_last')
    tmp2 = tmp0 - tmp1
    tmp4 = 4096.0
    tmp5 = tmp3 / tmp4
    tmp6 = 1e-05
    tmp7 = tmp5 + tmp6
    tmp8 = libdevice.rsqrt(tmp7)
    tmp9 = tmp2 * tmp8
    tmp11 = tmp9 * tmp10
    tmp13 = tmp11 + tmp12
    tmp14 = tl.full([1], 0, tl.int32)
    tmp15 = triton_helpers.maximum(tmp14, tmp13)
    tmp16 = 0.0
    tmp17 = tmp15 <= tmp16
    tl.store(out_ptr0 + x3, tmp15, None)
    tl.store(out_ptr1 + x3, tmp17, None)


@triton.jit
def triton_poi_fused__to_copy_add_arange_mul_33(out_ptr0, xnumel, XBLOCK:
    tl.constexpr):
    xnumel = 64
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x0 = xindex
    tmp0 = x0
    tmp1 = tmp0.to(tl.float32)
    tmp2 = 0.5
    tmp3 = tmp1 * tmp2
    tmp4 = tmp3.to(tl.int32)
    tl.store(out_ptr0 + x0, tmp4, xmask)


@triton.jit
def triton_poi_fused__unsafe_index_constant_pad_nd_34(in_ptr0, in_ptr1,
    out_ptr0, xnumel, XBLOCK: tl.constexpr):
    xnumel = 540800
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x1 = xindex // 65 % 65
    x0 = xindex % 65
    x2 = xindex // 4225
    x4 = xindex
    tmp0 = x1
    tmp1 = tl.full([1], 64, tl.int64)
    tmp2 = tmp0 < tmp1
    tmp3 = x0
    tmp4 = tmp3 < tmp1
    tmp5 = tmp2 & tmp4
    tmp6 = tl.load(in_ptr0 + x1, tmp5 & xmask, eviction_policy='evict_last',
        other=0.0)
    tmp7 = tl.full([XBLOCK], 32, tl.int32)
    tmp8 = tmp6 + tmp7
    tmp9 = tmp6 < 0
    tmp10 = tl.where(tmp9, tmp8, tmp6)
    tmp11 = tl.load(in_ptr0 + x0, tmp5 & xmask, eviction_policy=
        'evict_last', other=0.0)
    tmp12 = tmp11 + tmp7
    tmp13 = tmp11 < 0
    tmp14 = tl.where(tmp13, tmp12, tmp11)
    tmp15 = tl.load(in_ptr1 + (tmp14 + 32 * tmp10 + 1024 * x2), tmp5 &
        xmask, eviction_policy='evict_last', other=0.0)
    tl.store(out_ptr0 + x4, tmp15, xmask)


@triton.jit
def triton_poi_fused_cat_35(in_ptr0, in_ptr1, in_ptr2, out_ptr0, xnumel,
    XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x1 = xindex // 4096 % 32
    x0 = xindex % 4096
    x2 = xindex // 131072
    x3 = xindex
    tmp0 = x1
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 16, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (x0 + 4096 * x1 + 65536 * x2), tmp4, other=0.0)
    tmp6 = tmp0 >= tmp3
    tl.full([1], 32, tl.int64)
    tmp9 = tl.load(in_ptr1 + (x0 + 4096 * (-16 + x1) + 65536 * x2), tmp6,
        other=0.0)
    tmp10 = tl.load(in_ptr2 + (-16 + x1), tmp6, eviction_policy=
        'evict_last', other=0.0)
    tmp11 = tmp9 + tmp10
    tmp12 = tl.full(tmp11.shape, 0.0, tmp11.dtype)
    tmp13 = tl.where(tmp6, tmp11, tmp12)
    tmp14 = tl.where(tmp4, tmp5, tmp13)
    tl.store(out_ptr0 + x3, tmp14, None)


@triton.jit
def triton_poi_fused_convolution_36(in_out_ptr0, in_ptr0, xnumel, XBLOCK:
    tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x0 = xindex
    tmp0 = tl.load(in_out_ptr0 + x0, None)
    tmp1 = tl.load(in_ptr0 + 0)
    tmp2 = tl.broadcast_to(tmp1, [XBLOCK])
    tmp3 = tmp0 + tmp2
    tl.store(in_out_ptr0 + x0, tmp3, None)


def call(args):
    (primals_1, primals_2, primals_3, primals_4, primals_5, primals_6,
        primals_7, primals_8, primals_9, primals_10, primals_11, primals_12,
        primals_13, primals_14, primals_15, primals_16, primals_17,
        primals_18, primals_19, primals_20, primals_21, primals_22,
        primals_23, primals_24, primals_25, primals_26, primals_27,
        primals_28, primals_29, primals_30, primals_31, primals_32,
        primals_33, primals_34, primals_35, primals_36, primals_37,
        primals_38, primals_39, primals_40, primals_41, primals_42,
        primals_43, primals_44, primals_45, primals_46, primals_47,
        primals_48, primals_49, primals_50, primals_51, primals_52,
        primals_53, primals_54, primals_55, primals_56, primals_57,
        primals_58, primals_59, primals_60, primals_61, primals_62,
        primals_63, primals_64, primals_65, primals_66, primals_67,
        primals_68, primals_69, primals_70, primals_71, primals_72,
        primals_73, primals_74, primals_75, primals_76, primals_77,
        primals_78, primals_79, primals_80, primals_81, primals_82, primals_83
        ) = args
    args.clear()
    assert_size_stride(primals_1, (16, 1, 3, 3), (9, 9, 3, 1))
    assert_size_stride(primals_2, (16,), (1,))
    assert_size_stride(primals_3, (4, 1, 64, 64), (4096, 4096, 64, 1))
    assert_size_stride(primals_4, (16,), (1,))
    assert_size_stride(primals_5, (16,), (1,))
    assert_size_stride(primals_6, (16, 16, 3, 3), (144, 9, 3, 1))
    assert_size_stride(primals_7, (16,), (1,))
    assert_size_stride(primals_8, (16, 16, 3, 3), (144, 9, 3, 1))
    assert_size_stride(primals_9, (16,), (1,))
    assert_size_stride(primals_10, (32, 16, 3, 3), (144, 9, 3, 1))
    assert_size_stride(primals_11, (32,), (1,))
    assert_size_stride(primals_12, (32,), (1,))
    assert_size_stride(primals_13, (32,), (1,))
    assert_size_stride(primals_14, (32, 32, 3, 3), (288, 9, 3, 1))
    assert_size_stride(primals_15, (32,), (1,))
    assert_size_stride(primals_16, (32, 32, 3, 3), (288, 9, 3, 1))
    assert_size_stride(primals_17, (32,), (1,))
    assert_size_stride(primals_18, (64, 32, 3, 3), (288, 9, 3, 1))
    assert_size_stride(primals_19, (64,), (1,))
    assert_size_stride(primals_20, (64,), (1,))
    assert_size_stride(primals_21, (64,), (1,))
    assert_size_stride(primals_22, (64, 64, 3, 3), (576, 9, 3, 1))
    assert_size_stride(primals_23, (64,), (1,))
    assert_size_stride(primals_24, (64, 64, 3, 3), (576, 9, 3, 1))
    assert_size_stride(primals_25, (64,), (1,))
    assert_size_stride(primals_26, (128, 64, 3, 3), (576, 9, 3, 1))
    assert_size_stride(primals_27, (128,), (1,))
    assert_size_stride(primals_28, (128,), (1,))
    assert_size_stride(primals_29, (128,), (1,))
    assert_size_stride(primals_30, (128, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_31, (128,), (1,))
    assert_size_stride(primals_32, (128, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_33, (128,), (1,))
    assert_size_stride(primals_34, (256, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_35, (256,), (1,))
    assert_size_stride(primals_36, (256,), (1,))
    assert_size_stride(primals_37, (256,), (1,))
    assert_size_stride(primals_38, (256, 256, 3, 3), (2304, 9, 3, 1))
    assert_size_stride(primals_39, (256,), (1,))
    assert_size_stride(primals_40, (256, 256, 3, 3), (2304, 9, 3, 1))
    assert_size_stride(primals_41, (256,), (1,))
    assert_size_stride(primals_42, (128, 256, 2, 2), (1024, 4, 2, 1))
    assert_size_stride(primals_43, (128,), (1,))
    assert_size_stride(primals_44, (128, 256, 3, 3), (2304, 9, 3, 1))
    assert_size_stride(primals_45, (128,), (1,))
    assert_size_stride(primals_46, (128,), (1,))
    assert_size_stride(primals_47, (128,), (1,))
    assert_size_stride(primals_48, (128, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_49, (128,), (1,))
    assert_size_stride(primals_50, (128, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_51, (128,), (1,))
    assert_size_stride(primals_52, (64, 128, 2, 2), (512, 4, 2, 1))
    assert_size_stride(primals_53, (64,), (1,))
    assert_size_stride(primals_54, (64, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_55, (64,), (1,))
    assert_size_stride(primals_56, (64,), (1,))
    assert_size_stride(primals_57, (64,), (1,))
    assert_size_stride(primals_58, (64, 64, 3, 3), (576, 9, 3, 1))
    assert_size_stride(primals_59, (64,), (1,))
    assert_size_stride(primals_60, (64, 64, 3, 3), (576, 9, 3, 1))
    assert_size_stride(primals_61, (64,), (1,))
    assert_size_stride(primals_62, (32, 64, 2, 2), (256, 4, 2, 1))
    assert_size_stride(primals_63, (32,), (1,))
    assert_size_stride(primals_64, (32, 64, 3, 3), (576, 9, 3, 1))
    assert_size_stride(primals_65, (32,), (1,))
    assert_size_stride(primals_66, (32,), (1,))
    assert_size_stride(primals_67, (32,), (1,))
    assert_size_stride(primals_68, (32, 32, 3, 3), (288, 9, 3, 1))
    assert_size_stride(primals_69, (32,), (1,))
    assert_size_stride(primals_70, (32, 32, 3, 3), (288, 9, 3, 1))
    assert_size_stride(primals_71, (32,), (1,))
    assert_size_stride(primals_72, (16, 32, 2, 2), (128, 4, 2, 1))
    assert_size_stride(primals_73, (16,), (1,))
    assert_size_stride(primals_74, (16, 32, 3, 3), (288, 9, 3, 1))
    assert_size_stride(primals_75, (16,), (1,))
    assert_size_stride(primals_76, (16,), (1,))
    assert_size_stride(primals_77, (16,), (1,))
    assert_size_stride(primals_78, (16, 16, 3, 3), (144, 9, 3, 1))
    assert_size_stride(primals_79, (16,), (1,))
    assert_size_stride(primals_80, (16, 16, 3, 3), (144, 9, 3, 1))
    assert_size_stride(primals_81, (16,), (1,))
    assert_size_stride(primals_82, (1, 16, 3, 3), (144, 9, 3, 1))
    assert_size_stride(primals_83, (1,), (1,))
    with torch.cuda._DeviceGuard(0):
        torch.cuda.set_device(0)
        buf0 = extern_kernels.convolution(primals_3, primals_1, stride=(1, 
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf0, (4, 16, 64, 64), (65536, 4096, 64, 1))
        buf1 = buf0
        del buf0
        get_raw_stream(0)
        triton_poi_fused_convolution_0[grid(262144)](buf1, primals_2, 
            262144, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_2
        buf2 = empty_strided_cuda((1, 16, 1, 1, 2), (32, 1, 32, 32, 16),
            torch.float32)
        buf3 = empty_strided_cuda((1, 16, 1, 1, 2), (32, 1, 32, 32, 16),
            torch.float32)
        buf4 = empty_strided_cuda((1, 16, 1, 1, 2), (32, 1, 32, 32, 16),
            torch.float32)
        triton_red_fused__native_batch_norm_legit_1[grid(32)](buf1, buf2,
            buf3, buf4, 32, 8192, XBLOCK=1, RBLOCK=2048, num_warps=16,
            num_stages=1)
        buf5 = empty_strided_cuda((1, 16, 1, 1), (16, 1, 16, 16), torch.float32
            )
        buf6 = empty_strided_cuda((1, 16, 1, 1), (16, 1, 16, 16), torch.float32
            )
        buf8 = empty_strided_cuda((1, 16, 1, 1), (16, 1, 16, 16), torch.float32
            )
        triton_per_fused__native_batch_norm_legit_2[grid(16)](buf2, buf3,
            buf4, buf5, buf6, buf8, 16, 2, XBLOCK=8, num_warps=2, num_stages=1)
        buf9 = empty_strided_cuda((4, 16, 64, 64), (65536, 4096, 64, 1),
            torch.float32)
        triton_poi_fused__native_batch_norm_legit_relu_3[grid(262144)](buf1,
            buf5, buf6, primals_4, primals_5, buf9, 262144, XBLOCK=512,
            num_warps=8, num_stages=1)
        buf10 = extern_kernels.convolution(buf9, primals_6, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf10, (4, 16, 64, 64), (65536, 4096, 64, 1))
        buf11 = buf10
        del buf10
        triton_poi_fused_convolution_0[grid(262144)](buf11, primals_7, 
            262144, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_7
        buf12 = buf4
        del buf4
        buf13 = buf3
        del buf3
        buf14 = buf2
        del buf2
        triton_red_fused__native_batch_norm_legit_1[grid(32)](buf11, buf12,
            buf13, buf14, 32, 8192, XBLOCK=1, RBLOCK=2048, num_warps=16,
            num_stages=1)
        buf15 = buf6
        del buf6
        buf16 = empty_strided_cuda((1, 16, 1, 1), (16, 1, 16, 16), torch.
            float32)
        buf18 = empty_strided_cuda((1, 16, 1, 1), (16, 1, 16, 16), torch.
            float32)
        triton_per_fused__native_batch_norm_legit_2[grid(16)](buf12, buf13,
            buf14, buf15, buf16, buf18, 16, 2, XBLOCK=8, num_warps=2,
            num_stages=1)
        buf19 = empty_strided_cuda((4, 16, 64, 64), (65536, 4096, 64, 1),
            torch.float32)
        triton_poi_fused__native_batch_norm_legit_relu_3[grid(262144)](buf11,
            buf15, buf16, primals_4, primals_5, buf19, 262144, XBLOCK=512,
            num_warps=8, num_stages=1)
        buf20 = extern_kernels.convolution(buf19, primals_8, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf20, (4, 16, 64, 64), (65536, 4096, 64, 1))
        buf21 = buf20
        del buf20
        triton_poi_fused_convolution_0[grid(262144)](buf21, primals_9, 
            262144, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_9
        buf22 = buf14
        del buf14
        buf23 = buf13
        del buf13
        buf24 = buf12
        del buf12
        triton_red_fused__native_batch_norm_legit_1[grid(32)](buf21, buf22,
            buf23, buf24, 32, 8192, XBLOCK=1, RBLOCK=2048, num_warps=16,
            num_stages=1)
        buf25 = buf16
        del buf16
        buf26 = empty_strided_cuda((1, 16, 1, 1), (16, 1, 16, 16), torch.
            float32)
        buf28 = empty_strided_cuda((1, 16, 1, 1), (16, 1, 16, 16), torch.
            float32)
        triton_per_fused__native_batch_norm_legit_2[grid(16)](buf22, buf23,
            buf24, buf25, buf26, buf28, 16, 2, XBLOCK=8, num_warps=2,
            num_stages=1)
        buf29 = empty_strided_cuda((4, 16, 64, 64), (65536, 4096, 64, 1),
            torch.float32)
        triton_poi_fused__native_batch_norm_legit_relu_3[grid(262144)](buf21,
            buf25, buf26, primals_4, primals_5, buf29, 262144, XBLOCK=512,
            num_warps=8, num_stages=1)
        del primals_5
        buf30 = empty_strided_cuda((4, 16, 32, 32), (16384, 1024, 32, 1),
            torch.float32)
        buf31 = empty_strided_cuda((4, 16, 32, 32), (16384, 1024, 32, 1),
            torch.int8)
        triton_poi_fused_max_pool2d_with_indices_4[grid(65536)](buf29,
            buf30, buf31, 65536, XBLOCK=512, num_warps=4, num_stages=1)
        buf32 = extern_kernels.convolution(buf30, primals_10, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf32, (4, 32, 32, 32), (32768, 1024, 32, 1))
        buf33 = buf32
        del buf32
        triton_poi_fused_convolution_5[grid(131072)](buf33, primals_11, 
            131072, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_11
        buf34 = reinterpret_tensor(buf24, (1, 32, 1, 1), (32, 1, 32, 32), 0)
        del buf24
        buf35 = reinterpret_tensor(buf23, (1, 32, 1, 1), (32, 1, 32, 32), 0)
        del buf23
        buf37 = reinterpret_tensor(buf22, (1, 32, 1, 1), (32, 1, 32, 32), 0)
        del buf22
        triton_red_fused__native_batch_norm_legit_6[grid(32)](buf33, buf34,
            buf35, buf37, 32, 4096, XBLOCK=1, RBLOCK=2048, num_warps=16,
            num_stages=1)
        buf38 = empty_strided_cuda((4, 32, 32, 32), (32768, 1024, 32, 1),
            torch.float32)
        triton_poi_fused__native_batch_norm_legit_relu_7[grid(131072)](buf33,
            buf34, buf35, primals_12, primals_13, buf38, 131072, XBLOCK=512,
            num_warps=8, num_stages=1)
        buf39 = extern_kernels.convolution(buf38, primals_14, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf39, (4, 32, 32, 32), (32768, 1024, 32, 1))
        buf40 = buf39
        del buf39
        triton_poi_fused_convolution_5[grid(131072)](buf40, primals_15, 
            131072, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_15
        buf41 = buf35
        del buf35
        buf42 = empty_strided_cuda((1, 32, 1, 1), (32, 1, 32, 32), torch.
            float32)
        buf44 = empty_strided_cuda((1, 32, 1, 1), (32, 1, 32, 32), torch.
            float32)
        triton_red_fused__native_batch_norm_legit_6[grid(32)](buf40, buf41,
            buf42, buf44, 32, 4096, XBLOCK=1, RBLOCK=2048, num_warps=16,
            num_stages=1)
        buf45 = empty_strided_cuda((4, 32, 32, 32), (32768, 1024, 32, 1),
            torch.float32)
        triton_poi_fused__native_batch_norm_legit_relu_7[grid(131072)](buf40,
            buf41, buf42, primals_12, primals_13, buf45, 131072, XBLOCK=512,
            num_warps=8, num_stages=1)
        buf46 = extern_kernels.convolution(buf45, primals_16, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf46, (4, 32, 32, 32), (32768, 1024, 32, 1))
        buf47 = buf46
        del buf46
        triton_poi_fused_convolution_5[grid(131072)](buf47, primals_17, 
            131072, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_17
        buf48 = buf42
        del buf42
        buf49 = empty_strided_cuda((1, 32, 1, 1), (32, 1, 32, 32), torch.
            float32)
        buf51 = empty_strided_cuda((1, 32, 1, 1), (32, 1, 32, 32), torch.
            float32)
        triton_red_fused__native_batch_norm_legit_6[grid(32)](buf47, buf48,
            buf49, buf51, 32, 4096, XBLOCK=1, RBLOCK=2048, num_warps=16,
            num_stages=1)
        buf52 = empty_strided_cuda((4, 32, 32, 32), (32768, 1024, 32, 1),
            torch.float32)
        triton_poi_fused__native_batch_norm_legit_relu_7[grid(131072)](buf47,
            buf48, buf49, primals_12, primals_13, buf52, 131072, XBLOCK=512,
            num_warps=8, num_stages=1)
        del primals_13
        buf53 = empty_strided_cuda((4, 32, 16, 16), (8192, 256, 16, 1),
            torch.float32)
        buf54 = empty_strided_cuda((4, 32, 16, 16), (8192, 256, 16, 1),
            torch.int8)
        triton_poi_fused_max_pool2d_with_indices_8[grid(32768)](buf52,
            buf53, buf54, 32768, XBLOCK=128, num_warps=4, num_stages=1)
        buf55 = extern_kernels.convolution(buf53, primals_18, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf55, (4, 64, 16, 16), (16384, 256, 16, 1))
        buf56 = buf55
        del buf55
        triton_poi_fused_convolution_9[grid(65536)](buf56, primals_19, 
            65536, XBLOCK=512, num_warps=4, num_stages=1)
        del primals_19
        buf57 = empty_strided_cuda((1, 64, 1, 1), (64, 1, 64, 64), torch.
            float32)
        buf58 = empty_strided_cuda((1, 64, 1, 1), (64, 1, 64, 64), torch.
            float32)
        buf60 = empty_strided_cuda((1, 64, 1, 1), (64, 1, 64, 64), torch.
            float32)
        triton_per_fused__native_batch_norm_legit_10[grid(64)](buf56, buf57,
            buf58, buf60, 64, 1024, num_warps=8, num_stages=1)
        buf61 = empty_strided_cuda((4, 64, 16, 16), (16384, 256, 16, 1),
            torch.float32)
        triton_poi_fused__native_batch_norm_legit_relu_11[grid(65536)](buf56,
            buf57, buf58, primals_20, primals_21, buf61, 65536, XBLOCK=512,
            num_warps=4, num_stages=1)
        buf62 = extern_kernels.convolution(buf61, primals_22, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf62, (4, 64, 16, 16), (16384, 256, 16, 1))
        buf63 = buf62
        del buf62
        triton_poi_fused_convolution_9[grid(65536)](buf63, primals_23, 
            65536, XBLOCK=512, num_warps=4, num_stages=1)
        del primals_23
        buf64 = buf58
        del buf58
        buf65 = empty_strided_cuda((1, 64, 1, 1), (64, 1, 64, 64), torch.
            float32)
        buf67 = empty_strided_cuda((1, 64, 1, 1), (64, 1, 64, 64), torch.
            float32)
        triton_per_fused__native_batch_norm_legit_10[grid(64)](buf63, buf64,
            buf65, buf67, 64, 1024, num_warps=8, num_stages=1)
        buf68 = empty_strided_cuda((4, 64, 16, 16), (16384, 256, 16, 1),
            torch.float32)
        triton_poi_fused__native_batch_norm_legit_relu_11[grid(65536)](buf63,
            buf64, buf65, primals_20, primals_21, buf68, 65536, XBLOCK=512,
            num_warps=4, num_stages=1)
        buf69 = extern_kernels.convolution(buf68, primals_24, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf69, (4, 64, 16, 16), (16384, 256, 16, 1))
        buf70 = buf69
        del buf69
        triton_poi_fused_convolution_9[grid(65536)](buf70, primals_25, 
            65536, XBLOCK=512, num_warps=4, num_stages=1)
        del primals_25
        buf71 = buf65
        del buf65
        buf72 = empty_strided_cuda((1, 64, 1, 1), (64, 1, 64, 64), torch.
            float32)
        buf74 = empty_strided_cuda((1, 64, 1, 1), (64, 1, 64, 64), torch.
            float32)
        triton_per_fused__native_batch_norm_legit_10[grid(64)](buf70, buf71,
            buf72, buf74, 64, 1024, num_warps=8, num_stages=1)
        buf75 = empty_strided_cuda((4, 64, 16, 16), (16384, 256, 16, 1),
            torch.float32)
        triton_poi_fused__native_batch_norm_legit_relu_11[grid(65536)](buf70,
            buf71, buf72, primals_20, primals_21, buf75, 65536, XBLOCK=512,
            num_warps=4, num_stages=1)
        del primals_21
        buf76 = empty_strided_cuda((4, 64, 8, 8), (4096, 64, 8, 1), torch.
            float32)
        buf77 = empty_strided_cuda((4, 64, 8, 8), (4096, 64, 8, 1), torch.int8)
        triton_poi_fused_max_pool2d_with_indices_12[grid(16384)](buf75,
            buf76, buf77, 16384, XBLOCK=256, num_warps=4, num_stages=1)
        buf78 = extern_kernels.convolution(buf76, primals_26, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf78, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf79 = buf78
        del buf78
        triton_poi_fused_convolution_13[grid(32768)](buf79, primals_27, 
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_27
        buf80 = empty_strided_cuda((1, 128, 1, 1), (128, 1, 128, 128),
            torch.float32)
        buf81 = empty_strided_cuda((1, 128, 1, 1), (128, 1, 128, 128),
            torch.float32)
        buf83 = empty_strided_cuda((1, 128, 1, 1), (128, 1, 128, 128),
            torch.float32)
        triton_per_fused__native_batch_norm_legit_14[grid(128)](buf79,
            buf80, buf81, buf83, 128, 256, num_warps=2, num_stages=1)
        buf84 = empty_strided_cuda((4, 128, 8, 8), (8192, 64, 8, 1), torch.
            float32)
        triton_poi_fused__native_batch_norm_legit_relu_15[grid(32768)](buf79,
            buf80, buf81, primals_28, primals_29, buf84, 32768, XBLOCK=256,
            num_warps=4, num_stages=1)
        buf85 = extern_kernels.convolution(buf84, primals_30, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf85, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf86 = buf85
        del buf85
        triton_poi_fused_convolution_13[grid(32768)](buf86, primals_31, 
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_31
        buf87 = buf81
        del buf81
        buf88 = empty_strided_cuda((1, 128, 1, 1), (128, 1, 128, 128),
            torch.float32)
        buf90 = empty_strided_cuda((1, 128, 1, 1), (128, 1, 128, 128),
            torch.float32)
        triton_per_fused__native_batch_norm_legit_14[grid(128)](buf86,
            buf87, buf88, buf90, 128, 256, num_warps=2, num_stages=1)
        buf91 = empty_strided_cuda((4, 128, 8, 8), (8192, 64, 8, 1), torch.
            float32)
        triton_poi_fused__native_batch_norm_legit_relu_15[grid(32768)](buf86,
            buf87, buf88, primals_28, primals_29, buf91, 32768, XBLOCK=256,
            num_warps=4, num_stages=1)
        buf92 = extern_kernels.convolution(buf91, primals_32, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf92, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf93 = buf92
        del buf92
        triton_poi_fused_convolution_13[grid(32768)](buf93, primals_33, 
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_33
        buf94 = buf88
        del buf88
        buf95 = empty_strided_cuda((1, 128, 1, 1), (128, 1, 128, 128),
            torch.float32)
        buf97 = empty_strided_cuda((1, 128, 1, 1), (128, 1, 128, 128),
            torch.float32)
        triton_per_fused__native_batch_norm_legit_14[grid(128)](buf93,
            buf94, buf95, buf97, 128, 256, num_warps=2, num_stages=1)
        buf98 = empty_strided_cuda((4, 128, 8, 8), (8192, 64, 8, 1), torch.
            float32)
        triton_poi_fused__native_batch_norm_legit_relu_15[grid(32768)](buf93,
            buf94, buf95, primals_28, primals_29, buf98, 32768, XBLOCK=256,
            num_warps=4, num_stages=1)
        del primals_29
        buf99 = empty_strided_cuda((4, 128, 4, 4), (2048, 16, 4, 1), torch.
            float32)
        buf100 = empty_strided_cuda((4, 128, 4, 4), (2048, 16, 4, 1), torch
            .int8)
        triton_poi_fused_max_pool2d_with_indices_16[grid(8192)](buf98,
            buf99, buf100, 8192, XBLOCK=128, num_warps=4, num_stages=1)
        buf101 = extern_kernels.convolution(buf99, primals_34, stride=(1, 1
            ), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf101, (4, 256, 4, 4), (4096, 16, 4, 1))
        buf102 = buf101
        del buf101
        triton_poi_fused_convolution_17[grid(16384)](buf102, primals_35, 
            16384, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_35
        buf103 = empty_strided_cuda((1, 256, 1, 1), (256, 1, 256, 256),
            torch.float32)
        buf104 = empty_strided_cuda((1, 256, 1, 1), (256, 1, 256, 256),
            torch.float32)
        buf106 = empty_strided_cuda((1, 256, 1, 1), (256, 1, 256, 256),
            torch.float32)
        triton_per_fused__native_batch_norm_legit_18[grid(256)](buf102,
            buf103, buf104, buf106, 256, 64, XBLOCK=8, num_warps=4,
            num_stages=1)
        buf107 = empty_strided_cuda((4, 256, 4, 4), (4096, 16, 4, 1), torch
            .float32)
        triton_poi_fused__native_batch_norm_legit_relu_19[grid(16384)](buf102,
            buf103, buf104, primals_36, primals_37, buf107, 16384, XBLOCK=
            128, num_warps=4, num_stages=1)
        buf108 = extern_kernels.convolution(buf107, primals_38, stride=(1, 
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf108, (4, 256, 4, 4), (4096, 16, 4, 1))
        buf109 = buf108
        del buf108
        triton_poi_fused_convolution_17[grid(16384)](buf109, primals_39, 
            16384, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_39
        buf110 = buf104
        del buf104
        buf111 = empty_strided_cuda((1, 256, 1, 1), (256, 1, 256, 256),
            torch.float32)
        buf113 = empty_strided_cuda((1, 256, 1, 1), (256, 1, 256, 256),
            torch.float32)
        triton_per_fused__native_batch_norm_legit_18[grid(256)](buf109,
            buf110, buf111, buf113, 256, 64, XBLOCK=8, num_warps=4,
            num_stages=1)
        buf114 = empty_strided_cuda((4, 256, 4, 4), (4096, 16, 4, 1), torch
            .float32)
        triton_poi_fused__native_batch_norm_legit_relu_19[grid(16384)](buf109,
            buf110, buf111, primals_36, primals_37, buf114, 16384, XBLOCK=
            128, num_warps=4, num_stages=1)
        buf115 = extern_kernels.convolution(buf114, primals_40, stride=(1, 
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf115, (4, 256, 4, 4), (4096, 16, 4, 1))
        buf116 = buf115
        del buf115
        triton_poi_fused_convolution_17[grid(16384)](buf116, primals_41, 
            16384, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_41
        buf117 = buf111
        del buf111
        buf118 = empty_strided_cuda((1, 256, 1, 1), (256, 1, 256, 256),
            torch.float32)
        buf120 = empty_strided_cuda((1, 256, 1, 1), (256, 1, 256, 256),
            torch.float32)
        triton_per_fused__native_batch_norm_legit_18[grid(256)](buf116,
            buf117, buf118, buf120, 256, 64, XBLOCK=8, num_warps=4,
            num_stages=1)
        buf121 = empty_strided_cuda((4, 256, 4, 4), (4096, 16, 4, 1), torch
            .float32)
        buf236 = empty_strided_cuda((4, 256, 4, 4), (4096, 16, 4, 1), torch
            .bool)
        triton_poi_fused__native_batch_norm_legit_relu_threshold_backward_20[
            grid(16384)](buf116, buf117, buf118, primals_36, primals_37,
            buf121, buf236, 16384, XBLOCK=256, num_warps=4, num_stages=1)
        del buf118
        del primals_37
        buf122 = empty_strided_cuda((8,), (1,), torch.int64)
        triton_poi_fused__to_copy_add_arange_mul_21[grid(8)](buf122, 8,
            XBLOCK=8, num_warps=1, num_stages=1)
        buf123 = empty_strided_cuda((4, 256, 9, 9), (20736, 81, 9, 1),
            torch.float32)
        triton_poi_fused__unsafe_index_constant_pad_nd_22[grid(82944)](buf122,
            buf121, buf123, 82944, XBLOCK=512, num_warps=8, num_stages=1)
        del buf121
        buf124 = extern_kernels.convolution(buf123, primals_42, stride=(1, 
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf124, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf125 = empty_strided_cuda((4, 256, 8, 8), (16384, 64, 8, 1),
            torch.float32)
        triton_poi_fused_cat_23[grid(65536)](buf98, buf124, primals_43,
            buf125, 65536, XBLOCK=512, num_warps=4, num_stages=1)
        del primals_43
        buf126 = extern_kernels.convolution(buf125, primals_44, stride=(1, 
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf126, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf127 = buf126
        del buf126
        triton_poi_fused_convolution_13[grid(32768)](buf127, primals_45, 
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_45
        buf128 = buf95
        del buf95
        buf129 = empty_strided_cuda((1, 128, 1, 1), (128, 1, 128, 128),
            torch.float32)
        buf131 = empty_strided_cuda((1, 128, 1, 1), (128, 1, 128, 128),
            torch.float32)
        triton_per_fused__native_batch_norm_legit_14[grid(128)](buf127,
            buf128, buf129, buf131, 128, 256, num_warps=2, num_stages=1)
        buf132 = buf124
        del buf124
        triton_poi_fused__native_batch_norm_legit_relu_15[grid(32768)](buf127,
            buf128, buf129, primals_46, primals_47, buf132, 32768, XBLOCK=
            256, num_warps=4, num_stages=1)
        buf133 = extern_kernels.convolution(buf132, primals_48, stride=(1, 
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf133, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf134 = buf133
        del buf133
        triton_poi_fused_convolution_13[grid(32768)](buf134, primals_49, 
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_49
        buf135 = buf129
        del buf129
        buf136 = empty_strided_cuda((1, 128, 1, 1), (128, 1, 128, 128),
            torch.float32)
        buf138 = empty_strided_cuda((1, 128, 1, 1), (128, 1, 128, 128),
            torch.float32)
        triton_per_fused__native_batch_norm_legit_14[grid(128)](buf134,
            buf135, buf136, buf138, 128, 256, num_warps=2, num_stages=1)
        buf139 = empty_strided_cuda((4, 128, 8, 8), (8192, 64, 8, 1), torch
            .float32)
        triton_poi_fused__native_batch_norm_legit_relu_15[grid(32768)](buf134,
            buf135, buf136, primals_46, primals_47, buf139, 32768, XBLOCK=
            256, num_warps=4, num_stages=1)
        buf140 = extern_kernels.convolution(buf139, primals_50, stride=(1, 
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf140, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf141 = buf140
        del buf140
        triton_poi_fused_convolution_13[grid(32768)](buf141, primals_51, 
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_51
        buf142 = buf136
        del buf136
        buf143 = empty_strided_cuda((1, 128, 1, 1), (128, 1, 128, 128),
            torch.float32)
        buf145 = empty_strided_cuda((1, 128, 1, 1), (128, 1, 128, 128),
            torch.float32)
        triton_per_fused__native_batch_norm_legit_14[grid(128)](buf141,
            buf142, buf143, buf145, 128, 256, num_warps=2, num_stages=1)
        buf146 = empty_strided_cuda((4, 128, 8, 8), (8192, 64, 8, 1), torch
            .float32)
        buf235 = empty_strided_cuda((4, 128, 8, 8), (8192, 64, 8, 1), torch
            .bool)
        triton_poi_fused__native_batch_norm_legit_relu_threshold_backward_24[
            grid(32768)](buf141, buf142, buf143, primals_46, primals_47,
            buf146, buf235, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del buf143
        del primals_47
        buf147 = empty_strided_cuda((16,), (1,), torch.int64)
        triton_poi_fused__to_copy_add_arange_mul_25[grid(16)](buf147, 16,
            XBLOCK=16, num_warps=1, num_stages=1)
        buf148 = empty_strided_cuda((4, 128, 17, 17), (36992, 289, 17, 1),
            torch.float32)
        triton_poi_fused__unsafe_index_constant_pad_nd_26[grid(147968)](buf147,
            buf146, buf148, 147968, XBLOCK=512, num_warps=8, num_stages=1)
        del buf146
        buf149 = extern_kernels.convolution(buf148, primals_52, stride=(1, 
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf149, (4, 64, 16, 16), (16384, 256, 16, 1))
        buf150 = empty_strided_cuda((4, 128, 16, 16), (32768, 256, 16, 1),
            torch.float32)
        triton_poi_fused_cat_27[grid(131072)](buf75, buf149, primals_53,
            buf150, 131072, XBLOCK=512, num_warps=8, num_stages=1)
        del primals_53
        buf151 = extern_kernels.convolution(buf150, primals_54, stride=(1, 
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf151, (4, 64, 16, 16), (16384, 256, 16, 1))
        buf152 = buf151
        del buf151
        triton_poi_fused_convolution_9[grid(65536)](buf152, primals_55, 
            65536, XBLOCK=512, num_warps=4, num_stages=1)
        del primals_55
        buf153 = buf72
        del buf72
        buf154 = empty_strided_cuda((1, 64, 1, 1), (64, 1, 64, 64), torch.
            float32)
        buf156 = empty_strided_cuda((1, 64, 1, 1), (64, 1, 64, 64), torch.
            float32)
        triton_per_fused__native_batch_norm_legit_10[grid(64)](buf152,
            buf153, buf154, buf156, 64, 1024, num_warps=8, num_stages=1)
        buf157 = buf149
        del buf149
        triton_poi_fused__native_batch_norm_legit_relu_11[grid(65536)](buf152,
            buf153, buf154, primals_56, primals_57, buf157, 65536, XBLOCK=
            512, num_warps=4, num_stages=1)
        buf158 = extern_kernels.convolution(buf157, primals_58, stride=(1, 
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf158, (4, 64, 16, 16), (16384, 256, 16, 1))
        buf159 = buf158
        del buf158
        triton_poi_fused_convolution_9[grid(65536)](buf159, primals_59, 
            65536, XBLOCK=512, num_warps=4, num_stages=1)
        del primals_59
        buf160 = buf154
        del buf154
        buf161 = empty_strided_cuda((1, 64, 1, 1), (64, 1, 64, 64), torch.
            float32)
        buf163 = empty_strided_cuda((1, 64, 1, 1), (64, 1, 64, 64), torch.
            float32)
        triton_per_fused__native_batch_norm_legit_10[grid(64)](buf159,
            buf160, buf161, buf163, 64, 1024, num_warps=8, num_stages=1)
        buf164 = empty_strided_cuda((4, 64, 16, 16), (16384, 256, 16, 1),
            torch.float32)
        triton_poi_fused__native_batch_norm_legit_relu_11[grid(65536)](buf159,
            buf160, buf161, primals_56, primals_57, buf164, 65536, XBLOCK=
            512, num_warps=4, num_stages=1)
        buf165 = extern_kernels.convolution(buf164, primals_60, stride=(1, 
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf165, (4, 64, 16, 16), (16384, 256, 16, 1))
        buf166 = buf165
        del buf165
        triton_poi_fused_convolution_9[grid(65536)](buf166, primals_61, 
            65536, XBLOCK=512, num_warps=4, num_stages=1)
        del primals_61
        buf167 = buf161
        del buf161
        buf168 = empty_strided_cuda((1, 64, 1, 1), (64, 1, 64, 64), torch.
            float32)
        buf170 = empty_strided_cuda((1, 64, 1, 1), (64, 1, 64, 64), torch.
            float32)
        triton_per_fused__native_batch_norm_legit_10[grid(64)](buf166,
            buf167, buf168, buf170, 64, 1024, num_warps=8, num_stages=1)
        buf171 = empty_strided_cuda((4, 64, 16, 16), (16384, 256, 16, 1),
            torch.float32)
        buf234 = empty_strided_cuda((4, 64, 16, 16), (16384, 256, 16, 1),
            torch.bool)
        triton_poi_fused__native_batch_norm_legit_relu_threshold_backward_28[
            grid(65536)](buf166, buf167, buf168, primals_56, primals_57,
            buf171, buf234, 65536, XBLOCK=512, num_warps=4, num_stages=1)
        del buf168
        del primals_57
        buf172 = empty_strided_cuda((32,), (1,), torch.int64)
        triton_poi_fused__to_copy_add_arange_mul_29[grid(32)](buf172, 32,
            XBLOCK=32, num_warps=1, num_stages=1)
        buf173 = empty_strided_cuda((4, 64, 33, 33), (69696, 1089, 33, 1),
            torch.float32)
        triton_poi_fused__unsafe_index_constant_pad_nd_30[grid(278784)](buf172,
            buf171, buf173, 278784, XBLOCK=512, num_warps=8, num_stages=1)
        del buf171
        buf174 = extern_kernels.convolution(buf173, primals_62, stride=(1, 
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf174, (4, 32, 32, 32), (32768, 1024, 32, 1))
        buf175 = empty_strided_cuda((4, 64, 32, 32), (65536, 1024, 32, 1),
            torch.float32)
        triton_poi_fused_cat_31[grid(262144)](buf52, buf174, primals_63,
            buf175, 262144, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_63
        buf176 = extern_kernels.convolution(buf175, primals_64, stride=(1, 
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf176, (4, 32, 32, 32), (32768, 1024, 32, 1))
        buf177 = buf176
        del buf176
        triton_poi_fused_convolution_5[grid(131072)](buf177, primals_65, 
            131072, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_65
        buf178 = buf49
        del buf49
        buf179 = empty_strided_cuda((1, 32, 1, 1), (32, 1, 32, 32), torch.
            float32)
        buf181 = empty_strided_cuda((1, 32, 1, 1), (32, 1, 32, 32), torch.
            float32)
        triton_red_fused__native_batch_norm_legit_6[grid(32)](buf177,
            buf178, buf179, buf181, 32, 4096, XBLOCK=1, RBLOCK=2048,
            num_warps=16, num_stages=1)
        buf182 = buf174
        del buf174
        triton_poi_fused__native_batch_norm_legit_relu_7[grid(131072)](buf177,
            buf178, buf179, primals_66, primals_67, buf182, 131072, XBLOCK=
            512, num_warps=8, num_stages=1)
        buf183 = extern_kernels.convolution(buf182, primals_68, stride=(1, 
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf183, (4, 32, 32, 32), (32768, 1024, 32, 1))
        buf184 = buf183
        del buf183
        triton_poi_fused_convolution_5[grid(131072)](buf184, primals_69, 
            131072, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_69
        buf185 = buf179
        del buf179
        buf186 = empty_strided_cuda((1, 32, 1, 1), (32, 1, 32, 32), torch.
            float32)
        buf188 = empty_strided_cuda((1, 32, 1, 1), (32, 1, 32, 32), torch.
            float32)
        triton_red_fused__native_batch_norm_legit_6[grid(32)](buf184,
            buf185, buf186, buf188, 32, 4096, XBLOCK=1, RBLOCK=2048,
            num_warps=16, num_stages=1)
        buf189 = empty_strided_cuda((4, 32, 32, 32), (32768, 1024, 32, 1),
            torch.float32)
        triton_poi_fused__native_batch_norm_legit_relu_7[grid(131072)](buf184,
            buf185, buf186, primals_66, primals_67, buf189, 131072, XBLOCK=
            512, num_warps=8, num_stages=1)
        buf190 = extern_kernels.convolution(buf189, primals_70, stride=(1, 
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf190, (4, 32, 32, 32), (32768, 1024, 32, 1))
        buf191 = buf190
        del buf190
        triton_poi_fused_convolution_5[grid(131072)](buf191, primals_71, 
            131072, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_71
        buf192 = buf186
        del buf186
        buf193 = empty_strided_cuda((1, 32, 1, 1), (32, 1, 32, 32), torch.
            float32)
        buf195 = empty_strided_cuda((1, 32, 1, 1), (32, 1, 32, 32), torch.
            float32)
        triton_red_fused__native_batch_norm_legit_6[grid(32)](buf191,
            buf192, buf193, buf195, 32, 4096, XBLOCK=1, RBLOCK=2048,
            num_warps=16, num_stages=1)
        buf196 = empty_strided_cuda((4, 32, 32, 32), (32768, 1024, 32, 1),
            torch.float32)
        buf233 = empty_strided_cuda((4, 32, 32, 32), (32768, 1024, 32, 1),
            torch.bool)
        triton_poi_fused__native_batch_norm_legit_relu_threshold_backward_32[
            grid(131072)](buf191, buf192, buf193, primals_66, primals_67,
            buf196, buf233, 131072, XBLOCK=512, num_warps=8, num_stages=1)
        del primals_67
        buf197 = empty_strided_cuda((64,), (1,), torch.int64)
        triton_poi_fused__to_copy_add_arange_mul_33[grid(64)](buf197, 64,
            XBLOCK=64, num_warps=1, num_stages=1)
        buf198 = empty_strided_cuda((4, 32, 65, 65), (135200, 4225, 65, 1),
            torch.float32)
        triton_poi_fused__unsafe_index_constant_pad_nd_34[grid(540800)](buf197,
            buf196, buf198, 540800, XBLOCK=512, num_warps=8, num_stages=1)
        del buf196
        buf199 = extern_kernels.convolution(buf198, primals_72, stride=(1, 
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf199, (4, 16, 64, 64), (65536, 4096, 64, 1))
        buf200 = empty_strided_cuda((4, 32, 64, 64), (131072, 4096, 64, 1),
            torch.float32)
        triton_poi_fused_cat_35[grid(524288)](buf29, buf199, primals_73,
            buf200, 524288, XBLOCK=512, num_warps=8, num_stages=1)
        del primals_73
        buf201 = extern_kernels.convolution(buf200, primals_74, stride=(1, 
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf201, (4, 16, 64, 64), (65536, 4096, 64, 1))
        buf202 = buf201
        del buf201
        triton_poi_fused_convolution_0[grid(262144)](buf202, primals_75, 
            262144, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_75
        buf203 = reinterpret_tensor(buf193, (1, 16, 1, 1, 2), (32, 1, 32, 
            32, 16), 0)
        del buf193
        buf204 = empty_strided_cuda((1, 16, 1, 1, 2), (32, 1, 32, 32, 16),
            torch.float32)
        buf205 = empty_strided_cuda((1, 16, 1, 1, 2), (32, 1, 32, 32, 16),
            torch.float32)
        triton_red_fused__native_batch_norm_legit_1[grid(32)](buf202,
            buf203, buf204, buf205, 32, 8192, XBLOCK=1, RBLOCK=2048,
            num_warps=16, num_stages=1)
        buf206 = buf26
        del buf26
        buf207 = empty_strided_cuda((1, 16, 1, 1), (16, 1, 16, 16), torch.
            float32)
        buf209 = empty_strided_cuda((1, 16, 1, 1), (16, 1, 16, 16), torch.
            float32)
        triton_per_fused__native_batch_norm_legit_2[grid(16)](buf203,
            buf204, buf205, buf206, buf207, buf209, 16, 2, XBLOCK=8,
            num_warps=2, num_stages=1)
        buf210 = buf199
        del buf199
        triton_poi_fused__native_batch_norm_legit_relu_3[grid(262144)](buf202,
            buf206, buf207, primals_76, primals_77, buf210, 262144, XBLOCK=
            512, num_warps=8, num_stages=1)
        buf211 = extern_kernels.convolution(buf210, primals_78, stride=(1, 
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf211, (4, 16, 64, 64), (65536, 4096, 64, 1))
        buf212 = buf211
        del buf211
        triton_poi_fused_convolution_0[grid(262144)](buf212, primals_79, 
            262144, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_79
        buf213 = buf205
        del buf205
        buf214 = buf204
        del buf204
        buf215 = buf203
        del buf203
        triton_red_fused__native_batch_norm_legit_1[grid(32)](buf212,
            buf213, buf214, buf215, 32, 8192, XBLOCK=1, RBLOCK=2048,
            num_warps=16, num_stages=1)
        buf216 = buf207
        del buf207
        buf217 = empty_strided_cuda((1, 16, 1, 1), (16, 1, 16, 16), torch.
            float32)
        buf219 = empty_strided_cuda((1, 16, 1, 1), (16, 1, 16, 16), torch.
            float32)
        triton_per_fused__native_batch_norm_legit_2[grid(16)](buf213,
            buf214, buf215, buf216, buf217, buf219, 16, 2, XBLOCK=8,
            num_warps=2, num_stages=1)
        buf220 = empty_strided_cuda((4, 16, 64, 64), (65536, 4096, 64, 1),
            torch.float32)
        triton_poi_fused__native_batch_norm_legit_relu_3[grid(262144)](buf212,
            buf216, buf217, primals_76, primals_77, buf220, 262144, XBLOCK=
            512, num_warps=8, num_stages=1)
        buf221 = extern_kernels.convolution(buf220, primals_80, stride=(1, 
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf221, (4, 16, 64, 64), (65536, 4096, 64, 1))
        buf222 = buf221
        del buf221
        triton_poi_fused_convolution_0[grid(262144)](buf222, primals_81, 
            262144, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_81
        buf223 = buf215
        del buf215
        buf224 = buf214
        del buf214
        buf225 = buf213
        del buf213
        triton_red_fused__native_batch_norm_legit_1[grid(32)](buf222,
            buf223, buf224, buf225, 32, 8192, XBLOCK=1, RBLOCK=2048,
            num_warps=16, num_stages=1)
        buf226 = buf217
        del buf217
        buf227 = empty_strided_cuda((1, 16, 1, 1), (16, 1, 16, 16), torch.
            float32)
        buf229 = empty_strided_cuda((1, 16, 1, 1), (16, 1, 16, 16), torch.
            float32)
        triton_per_fused__native_batch_norm_legit_2[grid(16)](buf223,
            buf224, buf225, buf226, buf227, buf229, 16, 2, XBLOCK=8,
            num_warps=2, num_stages=1)
        del buf223
        del buf224
        del buf225
        buf230 = empty_strided_cuda((4, 16, 64, 64), (65536, 4096, 64, 1),
            torch.float32)
        triton_poi_fused__native_batch_norm_legit_relu_3[grid(262144)](buf222,
            buf226, buf227, primals_76, primals_77, buf230, 262144, XBLOCK=
            512, num_warps=8, num_stages=1)
        del buf227
        del primals_77
        buf231 = extern_kernels.convolution(buf230, primals_82, stride=(1, 
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf231, (4, 1, 64, 64), (4096, 4096, 64, 1))
        buf232 = buf231
        del buf231
        triton_poi_fused_convolution_36[grid(16384)](buf232, primals_83, 
            16384, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_83
    return (buf232, primals_1, primals_3, primals_4, primals_6, primals_8,
        primals_10, primals_12, primals_14, primals_16, primals_18,
        primals_20, primals_22, primals_24, primals_26, primals_28,
        primals_30, primals_32, primals_34, primals_36, primals_38,
        primals_40, primals_42, primals_44, primals_46, primals_48,
        primals_50, primals_52, primals_54, primals_56, primals_58,
        primals_60, primals_62, primals_64, primals_66, primals_68,
        primals_70, primals_72, primals_74, primals_76, primals_78,
        primals_80, primals_82, buf1, reinterpret_tensor(buf8, (16,), (1,),
        0), buf9, buf11, reinterpret_tensor(buf18, (16,), (1,), 0), buf19,
        buf21, reinterpret_tensor(buf28, (16,), (1,), 0), buf29, buf30,
        buf31, buf33, reinterpret_tensor(buf37, (32,), (1,), 0), buf38,
        buf40, reinterpret_tensor(buf44, (32,), (1,), 0), buf45, buf47,
        reinterpret_tensor(buf51, (32,), (1,), 0), buf52, buf53, buf54,
        buf56, reinterpret_tensor(buf60, (64,), (1,), 0), buf61, buf63,
        reinterpret_tensor(buf67, (64,), (1,), 0), buf68, buf70,
        reinterpret_tensor(buf74, (64,), (1,), 0), buf75, buf76, buf77,
        buf79, reinterpret_tensor(buf83, (128,), (1,), 0), buf84, buf86,
        reinterpret_tensor(buf90, (128,), (1,), 0), buf91, buf93,
        reinterpret_tensor(buf97, (128,), (1,), 0), buf98, buf99, buf100,
        buf102, reinterpret_tensor(buf106, (256,), (1,), 0), buf107, buf109,
        reinterpret_tensor(buf113, (256,), (1,), 0), buf114, buf116,
        reinterpret_tensor(buf120, (256,), (1,), 0), buf122, buf123, buf125,
        buf127, reinterpret_tensor(buf131, (128,), (1,), 0), buf132, buf134,
        reinterpret_tensor(buf138, (128,), (1,), 0), buf139, buf141,
        reinterpret_tensor(buf145, (128,), (1,), 0), buf147, buf148, buf150,
        buf152, reinterpret_tensor(buf156, (64,), (1,), 0), buf157, buf159,
        reinterpret_tensor(buf163, (64,), (1,), 0), buf164, buf166,
        reinterpret_tensor(buf170, (64,), (1,), 0), buf172, buf173, buf175,
        buf177, reinterpret_tensor(buf181, (32,), (1,), 0), buf182, buf184,
        reinterpret_tensor(buf188, (32,), (1,), 0), buf189, buf191,
        reinterpret_tensor(buf195, (32,), (1,), 0), buf197, buf198, buf200,
        buf202, reinterpret_tensor(buf209, (16,), (1,), 0), buf210, buf212,
        reinterpret_tensor(buf219, (16,), (1,), 0), buf220, buf222,
        reinterpret_tensor(buf229, (16,), (1,), 0), buf230,
        reinterpret_tensor(buf226, (1, 16, 1, 1), (16, 1, 1, 1), 0),
        reinterpret_tensor(buf216, (1, 16, 1, 1), (16, 1, 1, 1), 0),
        reinterpret_tensor(buf206, (1, 16, 1, 1), (16, 1, 1, 1), 0), buf233,
        reinterpret_tensor(buf192, (1, 32, 1, 1), (32, 1, 1, 1), 0),
        reinterpret_tensor(buf185, (1, 32, 1, 1), (32, 1, 1, 1), 0),
        reinterpret_tensor(buf178, (1, 32, 1, 1), (32, 1, 1, 1), 0), buf234,
        reinterpret_tensor(buf167, (1, 64, 1, 1), (64, 1, 1, 1), 0),
        reinterpret_tensor(buf160, (1, 64, 1, 1), (64, 1, 1, 1), 0),
        reinterpret_tensor(buf153, (1, 64, 1, 1), (64, 1, 1, 1), 0), buf235,
        reinterpret_tensor(buf142, (1, 128, 1, 1), (128, 1, 1, 1), 0),
        reinterpret_tensor(buf135, (1, 128, 1, 1), (128, 1, 1, 1), 0),
        reinterpret_tensor(buf128, (1, 128, 1, 1), (128, 1, 1, 1), 0),
        buf236, reinterpret_tensor(buf117, (1, 256, 1, 1), (256, 1, 1, 1), 
        0), reinterpret_tensor(buf110, (1, 256, 1, 1), (256, 1, 1, 1), 0),
        reinterpret_tensor(buf103, (1, 256, 1, 1), (256, 1, 1, 1), 0),
        reinterpret_tensor(buf94, (1, 128, 1, 1), (128, 1, 1, 1), 0),
        reinterpret_tensor(buf87, (1, 128, 1, 1), (128, 1, 1, 1), 0),
        reinterpret_tensor(buf80, (1, 128, 1, 1), (128, 1, 1, 1), 0),
        reinterpret_tensor(buf71, (1, 64, 1, 1), (64, 1, 1, 1), 0),
        reinterpret_tensor(buf64, (1, 64, 1, 1), (64, 1, 1, 1), 0),
        reinterpret_tensor(buf57, (1, 64, 1, 1), (64, 1, 1, 1), 0),
        reinterpret_tensor(buf48, (1, 32, 1, 1), (32, 1, 1, 1), 0),
        reinterpret_tensor(buf41, (1, 32, 1, 1), (32, 1, 1, 1), 0),
        reinterpret_tensor(buf34, (1, 32, 1, 1), (32, 1, 1, 1), 0),
        reinterpret_tensor(buf25, (1, 16, 1, 1), (16, 1, 1, 1), 0),
        reinterpret_tensor(buf15, (1, 16, 1, 1), (16, 1, 1, 1), 0),
        reinterpret_tensor(buf5, (1, 16, 1, 1), (16, 1, 1, 1), 0))


def conv3x3(in_channels, out_channels):
    return nn.Conv2d(in_channels, out_channels, kernel_size=3, stride=1,
        padding=1, bias=True)


def maxpool2x2():
    return nn.MaxPool2d(kernel_size=2, stride=2, padding=0)


def concat(xh, xv):
    return torch.cat([xh, xv], dim=1)


class UpConv2x2(nn.Module):

    def __init__(self, channels):
        super(UpConv2x2, self).__init__()
        self.conv = nn.Conv2d(channels, channels // 2, kernel_size=2,
            stride=1, padding=0, bias=True)

    def forward(self, x):
        x = F.interpolate(x, scale_factor=2, mode='nearest')
        x = F.pad(x, (0, 1, 0, 1))
        x = self.conv(x)
        return x


class ConvBlock(nn.Module):

    def __init__(self, in_channels, out_channels):
        """
        Args:
            in_channels: number of channels in input (1st) feature map
            out_channels: number of channels in output feature maps
        """
        super(ConvBlock, self).__init__()
        self.conv1 = conv3x3(in_channels, out_channels)
        self.conv2 = conv3x3(out_channels, out_channels)
        self.conv3 = conv3x3(out_channels, out_channels)
        self.norm = nn.BatchNorm2d(out_channels, track_running_stats=False)

    def forward(self, x):
        x = F.relu(self.norm(self.conv1(x)))
        x = F.relu(self.norm(self.conv2(x)))
        x = F.relu(self.norm(self.conv3(x)))
        return x


class DownConvBlock(nn.Module):

    def __init__(self, in_channels, out_channels):
        """
        Args:
            in_channels: number of channels in input (1st) feature map
            out_channels: number of channels in output feature maps
        """
        super(DownConvBlock, self).__init__()
        self.maxpool = maxpool2x2()
        self.conv1 = conv3x3(in_channels, out_channels)
        self.conv2 = conv3x3(out_channels, out_channels)
        self.conv3 = conv3x3(out_channels, out_channels)
        self.norm = nn.BatchNorm2d(out_channels, track_running_stats=False)

    def forward(self, x):
        x = self.maxpool(x)
        x = F.relu(self.norm(self.conv1(x)))
        x = F.relu(self.norm(self.conv2(x)))
        x = F.relu(self.norm(self.conv3(x)))
        return x


class UpConvBlock(nn.Module):

    def __init__(self, in_channels, out_channels):
        """
        Args:
            in_channels: number of channels in input (1st) feature map
            out_channels: number of channels in output feature maps
        """
        super(UpConvBlock, self).__init__()
        self.upconv = UpConv2x2(in_channels)
        self.conv1 = conv3x3(in_channels, out_channels)
        self.conv2 = conv3x3(out_channels, out_channels)
        self.conv3 = conv3x3(out_channels, out_channels)
        self.norm = nn.BatchNorm2d(out_channels, track_running_stats=False)

    def forward(self, xh, xv):
        """
        Args:
            xh: torch Variable, activations from same resolution feature maps (gray arrow in diagram)
            xv: torch Variable, activations from lower resolution feature maps (green arrow in diagram)
        """
        xv = self.upconv(xv)
        x = concat(xh, xv)
        x = F.relu(self.norm(self.conv1(x)))
        x = F.relu(self.norm(self.conv2(x)))
        x = F.relu(self.norm(self.conv3(x)))
        return x


class UNetNew(nn.Module):

    def __init__(self):
        super(UNetNew, self).__init__()
        fs = [16, 32, 64, 128, 256]
        self.conv_in = ConvBlock(1, fs[0])
        self.dconv1 = DownConvBlock(fs[0], fs[1])
        self.dconv2 = DownConvBlock(fs[1], fs[2])
        self.dconv3 = DownConvBlock(fs[2], fs[3])
        self.dconv4 = DownConvBlock(fs[3], fs[4])
        self.uconv1 = UpConvBlock(fs[4], fs[3])
        self.uconv2 = UpConvBlock(fs[3], fs[2])
        self.uconv3 = UpConvBlock(fs[2], fs[1])
        self.uconv4 = UpConvBlock(fs[1], fs[0])
        self.conv_out = conv3x3(fs[0], 1)
        self._initialize_weights()

    def _initialize_weights(self):
        conv_modules = [m for m in self.modules() if isinstance(m, nn.Conv2d)]
        for m in conv_modules:
            n = m.weight.shape[1] * m.weight.shape[2] * m.weight.shape[3]
            m.weight.data.normal_(0, np.sqrt(2.0 / n))
            m.bias.data.zero_()

    def forward(self, input_0):
        primals_1 = self.conv_in.conv1.weight
        primals_2 = self.conv_in.conv1.bias
        primals_6 = self.conv_in.conv2.weight
        primals_4 = self.conv_in.conv2.bias
        primals_8 = self.conv_in.conv3.weight
        primals_5 = self.conv_in.conv3.bias
        primals_7 = self.conv_in.norm.weight
        primals_9 = self.conv_in.norm.bias
        primals_10 = self.dconv1.conv1.weight
        primals_11 = self.dconv1.conv1.bias
        primals_14 = self.dconv1.conv2.weight
        primals_12 = self.dconv1.conv2.bias
        primals_16 = self.dconv1.conv3.weight
        primals_13 = self.dconv1.conv3.bias
        primals_15 = self.dconv1.norm.weight
        primals_17 = self.dconv1.norm.bias
        primals_18 = self.dconv2.conv1.weight
        primals_19 = self.dconv2.conv1.bias
        primals_22 = self.dconv2.conv2.weight
        primals_20 = self.dconv2.conv2.bias
        primals_24 = self.dconv2.conv3.weight
        primals_21 = self.dconv2.conv3.bias
        primals_23 = self.dconv2.norm.weight
        primals_25 = self.dconv2.norm.bias
        primals_26 = self.dconv3.conv1.weight
        primals_27 = self.dconv3.conv1.bias
        primals_30 = self.dconv3.conv2.weight
        primals_28 = self.dconv3.conv2.bias
        primals_32 = self.dconv3.conv3.weight
        primals_29 = self.dconv3.conv3.bias
        primals_31 = self.dconv3.norm.weight
        primals_33 = self.dconv3.norm.bias
        primals_34 = self.dconv4.conv1.weight
        primals_35 = self.dconv4.conv1.bias
        primals_38 = self.dconv4.conv2.weight
        primals_36 = self.dconv4.conv2.bias
        primals_40 = self.dconv4.conv3.weight
        primals_37 = self.dconv4.conv3.bias
        primals_39 = self.dconv4.norm.weight
        primals_41 = self.dconv4.norm.bias
        primals_42 = self.uconv1.upconv.conv.weight
        primals_43 = self.uconv1.upconv.conv.bias
        primals_44 = self.uconv1.conv1.weight
        primals_45 = self.uconv1.conv1.bias
        primals_48 = self.uconv1.conv2.weight
        primals_46 = self.uconv1.conv2.bias
        primals_50 = self.uconv1.conv3.weight
        primals_47 = self.uconv1.conv3.bias
        primals_49 = self.uconv1.norm.weight
        primals_51 = self.uconv1.norm.bias
        primals_52 = self.uconv2.upconv.conv.weight
        primals_53 = self.uconv2.upconv.conv.bias
        primals_54 = self.uconv2.conv1.weight
        primals_55 = self.uconv2.conv1.bias
        primals_58 = self.uconv2.conv2.weight
        primals_56 = self.uconv2.conv2.bias
        primals_60 = self.uconv2.conv3.weight
        primals_57 = self.uconv2.conv3.bias
        primals_59 = self.uconv2.norm.weight
        primals_61 = self.uconv2.norm.bias
        primals_62 = self.uconv3.upconv.conv.weight
        primals_63 = self.uconv3.upconv.conv.bias
        primals_64 = self.uconv3.conv1.weight
        primals_65 = self.uconv3.conv1.bias
        primals_68 = self.uconv3.conv2.weight
        primals_66 = self.uconv3.conv2.bias
        primals_70 = self.uconv3.conv3.weight
        primals_67 = self.uconv3.conv3.bias
        primals_69 = self.uconv3.norm.weight
        primals_71 = self.uconv3.norm.bias
        primals_72 = self.uconv4.upconv.conv.weight
        primals_73 = self.uconv4.upconv.conv.bias
        primals_74 = self.uconv4.conv1.weight
        primals_75 = self.uconv4.conv1.bias
        primals_78 = self.uconv4.conv2.weight
        primals_76 = self.uconv4.conv2.bias
        primals_80 = self.uconv4.conv3.weight
        primals_77 = self.uconv4.conv3.bias
        primals_79 = self.uconv4.norm.weight
        primals_81 = self.uconv4.norm.bias
        primals_82 = self.conv_out.weight
        primals_83 = self.conv_out.bias
        primals_3 = input_0
        output = call([primals_1, primals_2, primals_3, primals_4,
            primals_5, primals_6, primals_7, primals_8, primals_9,
            primals_10, primals_11, primals_12, primals_13, primals_14,
            primals_15, primals_16, primals_17, primals_18, primals_19,
            primals_20, primals_21, primals_22, primals_23, primals_24,
            primals_25, primals_26, primals_27, primals_28, primals_29,
            primals_30, primals_31, primals_32, primals_33, primals_34,
            primals_35, primals_36, primals_37, primals_38, primals_39,
            primals_40, primals_41, primals_42, primals_43, primals_44,
            primals_45, primals_46, primals_47, primals_48, primals_49,
            primals_50, primals_51, primals_52, primals_53, primals_54,
            primals_55, primals_56, primals_57, primals_58, primals_59,
            primals_60, primals_61, primals_62, primals_63, primals_64,
            primals_65, primals_66, primals_67, primals_68, primals_69,
            primals_70, primals_71, primals_72, primals_73, primals_74,
            primals_75, primals_76, primals_77, primals_78, primals_79,
            primals_80, primals_81, primals_82, primals_83])
        return output[0]


Measured latency_ms: 0.033126