// ResNet50 model with placeholder weights, for testing.
// Generated by resnet.ipynb with some manual and automated cleanup for testing.

// RUN: iree-run-mlir --Xcompiler,iree-input-type=stablehlo --Xcompiler,iree-hal-target-backends=llvm-cpu %s --input=1x224x224x3xf32 | FileCheck %s
// RUN: [[ $IREE_VULKAN_DISABLE == 1 ]] || (iree-run-mlir --Xcompiler,iree-input-type=stablehlo --Xcompiler,iree-hal-target-backends=vulkan-spirv %s --input=1x224x224x3xf32 | FileCheck %s)

module {
  util.global private @"__iree_flow___sm_node188__m.layer-2.kernel" {noinline} = dense<1.000000e+00> : tensor<7x7x3x64xf32>
  util.global private @"__iree_flow___sm_node189__m.layer-2.bias" {noinline} = dense<5.000000e-01> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node195__m.layer-3.gamma" {noinline} = dense<0.333333343> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node196__m.layer-3.beta" {noinline} = dense<2.500000e-01> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node197__m.layer-3.moving_mean" {noinline} = dense<2.000000e-01> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node198__m.layer-3.moving_variance" {noinline} = dense<0.166666672> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node215__m.layer-7.kernel" {noinline} = dense<0.142857149> : tensor<1x1x64x64xf32>
  util.global private @"__iree_flow___sm_node216__m.layer-7.bias" {noinline} = dense<1.250000e-01> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node222__m.layer-8.gamma" {noinline} = dense<0.111111112> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node223__m.layer-8.beta" {noinline} = dense<1.000000e-01> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node224__m.layer-8.moving_mean" {noinline} = dense<0.0909090936> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node225__m.layer-8.moving_variance" {noinline} = dense<0.0833333358> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node234__m.layer-10.kernel" {noinline} = dense<0.0769230798> : tensor<3x3x64x64xf32>
  util.global private @"__iree_flow___sm_node235__m.layer-10.bias" {noinline} = dense<0.0714285746> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node241__m.layer-11.gamma" {noinline} = dense<0.0666666701> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node242__m.layer-11.beta" {noinline} = dense<6.250000e-02> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node243__m.layer-11.moving_mean" {noinline} = dense<0.0588235296> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node244__m.layer-11.moving_variance" {noinline} = dense<0.055555556> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node253__m.layer-13.kernel" {noinline} = dense<0.0526315793> : tensor<1x1x64x256xf32>
  util.global private @"__iree_flow___sm_node254__m.layer-13.bias" {noinline} = dense<5.000000e-02> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node259__m.layer-14.kernel" {noinline} = dense<0.0476190485> : tensor<1x1x64x256xf32>
  util.global private @"__iree_flow___sm_node260__m.layer-14.bias" {noinline} = dense<0.0454545468> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node266__m.layer-15.gamma" {noinline} = dense<0.0434782617> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node267__m.layer-15.beta" {noinline} = dense<0.0416666679> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node268__m.layer-15.moving_mean" {noinline} = dense<4.000000e-02> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node269__m.layer-15.moving_variance" {noinline} = dense<0.0384615399> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node275__m.layer-16.gamma" {noinline} = dense<0.0370370373> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node276__m.layer-16.beta" {noinline} = dense<0.0357142873> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node277__m.layer-16.moving_mean" {noinline} = dense<0.0344827585> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node278__m.layer-16.moving_variance" {noinline} = dense<0.0333333351> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node291__m.layer-19.kernel" {noinline} = dense<0.0322580636> : tensor<1x1x256x64xf32>
  util.global private @"__iree_flow___sm_node292__m.layer-19.bias" {noinline} = dense<3.125000e-02> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node298__m.layer-20.gamma" {noinline} = dense<0.0303030312> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node299__m.layer-20.beta" {noinline} = dense<0.0294117648> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node300__m.layer-20.moving_mean" {noinline} = dense<0.0285714287> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node301__m.layer-20.moving_variance" {noinline} = dense<0.027777778> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node310__m.layer-22.kernel" {noinline} = dense<0.0270270277> : tensor<3x3x64x64xf32>
  util.global private @"__iree_flow___sm_node311__m.layer-22.bias" {noinline} = dense<0.0263157897> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node317__m.layer-23.gamma" {noinline} = dense<0.025641026> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node318__m.layer-23.beta" {noinline} = dense<2.500000e-02> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node319__m.layer-23.moving_mean" {noinline} = dense<0.024390243> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node320__m.layer-23.moving_variance" {noinline} = dense<0.0238095243> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node329__m.layer-25.kernel" {noinline} = dense<0.0232558139> : tensor<1x1x64x256xf32>
  util.global private @"__iree_flow___sm_node330__m.layer-25.bias" {noinline} = dense<0.0227272734> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node336__m.layer-26.gamma" {noinline} = dense<0.0222222228> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node337__m.layer-26.beta" {noinline} = dense<0.0217391308> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node338__m.layer-26.moving_mean" {noinline} = dense<0.0212765951> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node339__m.layer-26.moving_variance" {noinline} = dense<0.020833334> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node352__m.layer-29.kernel" {noinline} = dense<0.0204081628> : tensor<1x1x256x64xf32>
  util.global private @"__iree_flow___sm_node353__m.layer-29.bias" {noinline} = dense<2.000000e-02> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node359__m.layer-30.gamma" {noinline} = dense<0.0196078438> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node360__m.layer-30.beta" {noinline} = dense<0.0192307699> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node361__m.layer-30.moving_mean" {noinline} = dense<0.0188679248> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node362__m.layer-30.moving_variance" {noinline} = dense<0.0185185187> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node371__m.layer-32.kernel" {noinline} = dense<0.0181818176> : tensor<3x3x64x64xf32>
  util.global private @"__iree_flow___sm_node372__m.layer-32.bias" {noinline} = dense<0.0178571437> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node378__m.layer-33.gamma" {noinline} = dense<0.0175438598> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node379__m.layer-33.beta" {noinline} = dense<0.0172413792> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node380__m.layer-33.moving_mean" {noinline} = dense<0.0169491526> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node381__m.layer-33.moving_variance" {noinline} = dense<0.0166666675> : tensor<64xf32>
  util.global private @"__iree_flow___sm_node390__m.layer-35.kernel" {noinline} = dense<0.0163934417> : tensor<1x1x64x256xf32>
  util.global private @"__iree_flow___sm_node391__m.layer-35.bias" {noinline} = dense<0.0161290318> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node397__m.layer-36.gamma" {noinline} = dense<0.0158730168> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node398__m.layer-36.beta" {noinline} = dense<1.562500e-02> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node399__m.layer-36.moving_mean" {noinline} = dense<0.0153846154> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node400__m.layer-36.moving_variance" {noinline} = dense<0.0151515156> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node413__m.layer-39.kernel" {noinline} = dense<0.0149253728> : tensor<1x1x256x128xf32>
  util.global private @"__iree_flow___sm_node414__m.layer-39.bias" {noinline} = dense<0.0147058824> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node420__m.layer-40.gamma" {noinline} = dense<0.0144927539> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node421__m.layer-40.beta" {noinline} = dense<0.0142857144> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node422__m.layer-40.moving_mean" {noinline} = dense<0.0140845068> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node423__m.layer-40.moving_variance" {noinline} = dense<0.013888889> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node432__m.layer-42.kernel" {noinline} = dense<0.01369863> : tensor<3x3x128x128xf32>
  util.global private @"__iree_flow___sm_node433__m.layer-42.bias" {noinline} = dense<0.0135135138> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node439__m.layer-43.gamma" {noinline} = dense<0.0133333337> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node440__m.layer-43.beta" {noinline} = dense<0.0131578948> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node441__m.layer-43.moving_mean" {noinline} = dense<0.012987013> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node442__m.layer-43.moving_variance" {noinline} = dense<0.012820513> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node451__m.layer-45.kernel" {noinline} = dense<0.0126582282> : tensor<1x1x256x512xf32>
  util.global private @"__iree_flow___sm_node452__m.layer-45.bias" {noinline} = dense<1.250000e-02> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node457__m.layer-46.kernel" {noinline} = dense<0.0123456791> : tensor<1x1x128x512xf32>
  util.global private @"__iree_flow___sm_node458__m.layer-46.bias" {noinline} = dense<0.0121951215> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node464__m.layer-47.gamma" {noinline} = dense<0.0120481923> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node465__m.layer-47.beta" {noinline} = dense<0.0119047621> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node466__m.layer-47.moving_mean" {noinline} = dense<0.0117647061> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node467__m.layer-47.moving_variance" {noinline} = dense<0.0116279069> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node473__m.layer-48.gamma" {noinline} = dense<0.0114942528> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node474__m.layer-48.beta" {noinline} = dense<0.0113636367> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node475__m.layer-48.moving_mean" {noinline} = dense<0.0112359552> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node476__m.layer-48.moving_variance" {noinline} = dense<0.0111111114> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node489__m.layer-51.kernel" {noinline} = dense<0.0109890113> : tensor<1x1x512x128xf32>
  util.global private @"__iree_flow___sm_node490__m.layer-51.bias" {noinline} = dense<0.0108695654> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node496__m.layer-52.gamma" {noinline} = dense<0.0107526882> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node497__m.layer-52.beta" {noinline} = dense<0.0106382975> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node498__m.layer-52.moving_mean" {noinline} = dense<0.0105263162> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node499__m.layer-52.moving_variance" {noinline} = dense<0.010416667> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node508__m.layer-54.kernel" {noinline} = dense<0.010309278> : tensor<3x3x128x128xf32>
  util.global private @"__iree_flow___sm_node509__m.layer-54.bias" {noinline} = dense<0.0102040814> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node515__m.layer-55.gamma" {noinline} = dense<0.0101010101> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node516__m.layer-55.beta" {noinline} = dense<0.00999999977> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node517__m.layer-55.moving_mean" {noinline} = dense<9.900990e-03> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node518__m.layer-55.moving_variance" {noinline} = dense<0.00980392192> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node527__m.layer-57.kernel" {noinline} = dense<0.00970873795> : tensor<1x1x128x512xf32>
  util.global private @"__iree_flow___sm_node528__m.layer-57.bias" {noinline} = dense<0.00961538497> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node534__m.layer-58.gamma" {noinline} = dense<9.523810e-03> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node535__m.layer-58.beta" {noinline} = dense<0.0094339624> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node536__m.layer-58.moving_mean" {noinline} = dense<0.00934579409> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node537__m.layer-58.moving_variance" {noinline} = dense<0.00925925932> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node550__m.layer-61.kernel" {noinline} = dense<0.00917431153> : tensor<1x1x512x128xf32>
  util.global private @"__iree_flow___sm_node551__m.layer-61.bias" {noinline} = dense<0.0090909088> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node557__m.layer-62.gamma" {noinline} = dense<0.00900900922> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node558__m.layer-62.beta" {noinline} = dense<0.00892857183> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node559__m.layer-62.moving_mean" {noinline} = dense<0.00884955748> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node560__m.layer-62.moving_variance" {noinline} = dense<0.00877192988> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node569__m.layer-64.kernel" {noinline} = dense<0.00869565178> : tensor<3x3x128x128xf32>
  util.global private @"__iree_flow___sm_node570__m.layer-64.bias" {noinline} = dense<8.620690e-03> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node576__m.layer-65.gamma" {noinline} = dense<0.00854700897> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node577__m.layer-65.beta" {noinline} = dense<0.00847457629> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node578__m.layer-65.moving_mean" {noinline} = dense<0.00840336177> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node579__m.layer-65.moving_variance" {noinline} = dense<0.00833333377> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node588__m.layer-67.kernel" {noinline} = dense<0.00826446246> : tensor<1x1x128x512xf32>
  util.global private @"__iree_flow___sm_node589__m.layer-67.bias" {noinline} = dense<0.00819672085> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node595__m.layer-68.gamma" {noinline} = dense<0.008130081> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node596__m.layer-68.beta" {noinline} = dense<0.00806451589> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node597__m.layer-68.moving_mean" {noinline} = dense<8.000000e-03> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node598__m.layer-68.moving_variance" {noinline} = dense<0.00793650839> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node611__m.layer-71.kernel" {noinline} = dense<0.00787401571> : tensor<1x1x512x128xf32>
  util.global private @"__iree_flow___sm_node612__m.layer-71.bias" {noinline} = dense<7.812500e-03> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node618__m.layer-72.gamma" {noinline} = dense<0.00775193795> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node619__m.layer-72.beta" {noinline} = dense<0.0076923077> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node620__m.layer-72.moving_mean" {noinline} = dense<0.00763358781> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node621__m.layer-72.moving_variance" {noinline} = dense<0.0075757578> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node630__m.layer-74.kernel" {noinline} = dense<0.00751879718> : tensor<3x3x128x128xf32>
  util.global private @"__iree_flow___sm_node631__m.layer-74.bias" {noinline} = dense<0.00746268639> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node637__m.layer-75.gamma" {noinline} = dense<0.00740740728> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node638__m.layer-75.beta" {noinline} = dense<0.0073529412> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node639__m.layer-75.moving_mean" {noinline} = dense<7.299270e-03> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node640__m.layer-75.moving_variance" {noinline} = dense<0.00724637694> : tensor<128xf32>
  util.global private @"__iree_flow___sm_node649__m.layer-77.kernel" {noinline} = dense<0.00719424477> : tensor<1x1x128x512xf32>
  util.global private @"__iree_flow___sm_node650__m.layer-77.bias" {noinline} = dense<0.00714285718> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node656__m.layer-78.gamma" {noinline} = dense<0.00709219835> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node657__m.layer-78.beta" {noinline} = dense<0.00704225338> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node658__m.layer-78.moving_mean" {noinline} = dense<0.00699300691> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node659__m.layer-78.moving_variance" {noinline} = dense<0.0069444445> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node672__m.layer-81.kernel" {noinline} = dense<0.0068965517> : tensor<1x1x512x256xf32>
  util.global private @"__iree_flow___sm_node673__m.layer-81.bias" {noinline} = dense<0.00684931502> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node679__m.layer-82.gamma" {noinline} = dense<0.00680272094> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node680__m.layer-82.beta" {noinline} = dense<0.00675675692> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node681__m.layer-82.moving_mean" {noinline} = dense<0.00671140943> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node682__m.layer-82.moving_variance" {noinline} = dense<0.00666666683> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node691__m.layer-84.kernel" {noinline} = dense<0.00662251655> : tensor<3x3x256x256xf32>
  util.global private @"__iree_flow___sm_node692__m.layer-84.bias" {noinline} = dense<0.00657894742> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node698__m.layer-85.gamma" {noinline} = dense<0.00653594779> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node699__m.layer-85.beta" {noinline} = dense<0.00649350649> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node700__m.layer-85.moving_mean" {noinline} = dense<0.0064516128> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node701__m.layer-85.moving_variance" {noinline} = dense<0.00641025649> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node710__m.layer-87.kernel" {noinline} = dense<0.00636942684> : tensor<1x1x512x1024xf32>
  util.global private @"__iree_flow___sm_node711__m.layer-87.bias" {noinline} = dense<0.00632911408> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node716__m.layer-88.kernel" {noinline} = dense<0.00628930796> : tensor<1x1x256x1024xf32>
  util.global private @"__iree_flow___sm_node717__m.layer-88.bias" {noinline} = dense<6.250000e-03> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node723__m.layer-89.gamma" {noinline} = dense<0.00621118024> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node724__m.layer-89.beta" {noinline} = dense<0.00617283955> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node725__m.layer-89.moving_mean" {noinline} = dense<0.00613496918> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node726__m.layer-89.moving_variance" {noinline} = dense<0.00609756075> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node732__m.layer-90.gamma" {noinline} = dense<0.00606060587> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node733__m.layer-90.beta" {noinline} = dense<0.00602409616> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node734__m.layer-90.moving_mean" {noinline} = dense<0.00598802418> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node735__m.layer-90.moving_variance" {noinline} = dense<0.00595238106> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node748__m.layer-93.kernel" {noinline} = dense<5.917160e-03> : tensor<1x1x1024x256xf32>
  util.global private @"__iree_flow___sm_node749__m.layer-93.bias" {noinline} = dense<0.00588235306> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node755__m.layer-94.gamma" {noinline} = dense<0.00584795326> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node756__m.layer-94.beta" {noinline} = dense<0.00581395347> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node757__m.layer-94.moving_mean" {noinline} = dense<0.00578034669> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node758__m.layer-94.moving_variance" {noinline} = dense<0.00574712642> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node767__m.layer-96.kernel" {noinline} = dense<0.00571428565> : tensor<3x3x256x256xf32>
  util.global private @"__iree_flow___sm_node768__m.layer-96.bias" {noinline} = dense<0.00568181835> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node774__m.layer-97.gamma" {noinline} = dense<0.00564971752> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node775__m.layer-97.beta" {noinline} = dense<0.00561797759> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node776__m.layer-97.moving_mean" {noinline} = dense<0.00558659201> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node777__m.layer-97.moving_variance" {noinline} = dense<0.00555555569> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node786__m.layer-99.kernel" {noinline} = dense<0.00552486209> : tensor<1x1x256x1024xf32>
  util.global private @"__iree_flow___sm_node787__m.layer-99.bias" {noinline} = dense<0.00549450563> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node793__m.layer-100.gamma" {noinline} = dense<0.00546448072> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node794__m.layer-100.beta" {noinline} = dense<0.00543478271> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node795__m.layer-100.moving_mean" {noinline} = dense<0.00540540554> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node796__m.layer-100.moving_variance" {noinline} = dense<0.00537634408> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node809__m.layer-103.kernel" {noinline} = dense<0.00534759369> : tensor<1x1x1024x256xf32>
  util.global private @"__iree_flow___sm_node810__m.layer-103.bias" {noinline} = dense<0.00531914877> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node816__m.layer-104.gamma" {noinline} = dense<0.00529100513> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node817__m.layer-104.beta" {noinline} = dense<0.00526315812> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node818__m.layer-104.moving_mean" {noinline} = dense<0.00523560215> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node819__m.layer-104.moving_variance" {noinline} = dense<0.00520833349> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node828__m.layer-106.kernel" {noinline} = dense<0.00518134702> : tensor<3x3x256x256xf32>
  util.global private @"__iree_flow___sm_node829__m.layer-106.bias" {noinline} = dense<0.00515463902> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node835__m.layer-107.gamma" {noinline} = dense<0.00512820529> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node836__m.layer-107.beta" {noinline} = dense<0.00510204071> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node837__m.layer-107.moving_mean" {noinline} = dense<0.00507614203> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node838__m.layer-107.moving_variance" {noinline} = dense<0.00505050505> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node847__m.layer-109.kernel" {noinline} = dense<0.00502512557> : tensor<1x1x256x1024xf32>
  util.global private @"__iree_flow___sm_node848__m.layer-109.bias" {noinline} = dense<5.000000e-03> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node854__m.layer-110.gamma" {noinline} = dense<0.00497512426> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node855__m.layer-110.beta" {noinline} = dense<0.00495049497> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node856__m.layer-110.moving_mean" {noinline} = dense<0.00492610829> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node857__m.layer-110.moving_variance" {noinline} = dense<0.00490196096> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node870__m.layer-113.kernel" {noinline} = dense<0.00487804879> : tensor<1x1x1024x256xf32>
  util.global private @"__iree_flow___sm_node871__m.layer-113.bias" {noinline} = dense<0.00485436898> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node877__m.layer-114.gamma" {noinline} = dense<0.00483091781> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node878__m.layer-114.beta" {noinline} = dense<0.00480769249> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node879__m.layer-114.moving_mean" {noinline} = dense<0.00478468882> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node880__m.layer-114.moving_variance" {noinline} = dense<0.00476190494> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node889__m.layer-116.kernel" {noinline} = dense<0.00473933667> : tensor<3x3x256x256xf32>
  util.global private @"__iree_flow___sm_node890__m.layer-116.bias" {noinline} = dense<0.0047169812> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node896__m.layer-117.gamma" {noinline} = dense<0.00469483575> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node897__m.layer-117.beta" {noinline} = dense<0.00467289705> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node898__m.layer-117.moving_mean" {noinline} = dense<0.00465116277> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node899__m.layer-117.moving_variance" {noinline} = dense<0.00462962966> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node908__m.layer-119.kernel" {noinline} = dense<0.00460829493> : tensor<1x1x256x1024xf32>
  util.global private @"__iree_flow___sm_node909__m.layer-119.bias" {noinline} = dense<0.00458715577> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node915__m.layer-120.gamma" {noinline} = dense<4.566210e-03> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node916__m.layer-120.beta" {noinline} = dense<0.0045454544> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node917__m.layer-120.moving_mean" {noinline} = dense<0.00452488707> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node918__m.layer-120.moving_variance" {noinline} = dense<0.00450450461> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node931__m.layer-123.kernel" {noinline} = dense<0.00448430516> : tensor<1x1x1024x256xf32>
  util.global private @"__iree_flow___sm_node932__m.layer-123.bias" {noinline} = dense<0.00446428591> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node938__m.layer-124.gamma" {noinline} = dense<0.00444444455> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node939__m.layer-124.beta" {noinline} = dense<0.00442477874> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node940__m.layer-124.moving_mean" {noinline} = dense<0.00440528616> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node941__m.layer-124.moving_variance" {noinline} = dense<0.00438596494> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node950__m.layer-126.kernel" {noinline} = dense<0.0043668123> : tensor<3x3x256x256xf32>
  util.global private @"__iree_flow___sm_node951__m.layer-126.bias" {noinline} = dense<0.00434782589> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node957__m.layer-127.gamma" {noinline} = dense<0.00432900432> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node958__m.layer-127.beta" {noinline} = dense<0.00431034481> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node959__m.layer-127.moving_mean" {noinline} = dense<0.00429184549> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node960__m.layer-127.moving_variance" {noinline} = dense<0.00427350448> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node969__m.layer-129.kernel" {noinline} = dense<0.00425531901> : tensor<1x1x256x1024xf32>
  util.global private @"__iree_flow___sm_node970__m.layer-129.bias" {noinline} = dense<0.00423728814> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node976__m.layer-130.gamma" {noinline} = dense<0.00421940908> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node977__m.layer-130.beta" {noinline} = dense<0.00420168089> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node978__m.layer-130.moving_mean" {noinline} = dense<0.00418410031> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node979__m.layer-130.moving_variance" {noinline} = dense<0.00416666688> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node992__m.layer-133.kernel" {noinline} = dense<0.00414937781> : tensor<1x1x1024x256xf32>
  util.global private @"__iree_flow___sm_node993__m.layer-133.bias" {noinline} = dense<0.00413223123> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node999__m.layer-134.gamma" {noinline} = dense<0.00411522621> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node1000__m.layer-134.beta" {noinline} = dense<0.00409836043> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node1001__m.layer-134.moving_mean" {noinline} = dense<0.00408163248> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node1002__m.layer-134.moving_variance" {noinline} = dense<0.0040650405> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node1011__m.layer-136.kernel" {noinline} = dense<0.0040485831> : tensor<3x3x256x256xf32>
  util.global private @"__iree_flow___sm_node1012__m.layer-136.bias" {noinline} = dense<0.00403225794> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node1018__m.layer-137.gamma" {noinline} = dense<0.00401606411> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node1019__m.layer-137.beta" {noinline} = dense<4.000000e-03> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node1020__m.layer-137.moving_mean" {noinline} = dense<0.00398406386> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node1021__m.layer-137.moving_variance" {noinline} = dense<0.0039682542> : tensor<256xf32>
  util.global private @"__iree_flow___sm_node1030__m.layer-139.kernel" {noinline} = dense<0.00395256933> : tensor<1x1x256x1024xf32>
  util.global private @"__iree_flow___sm_node1031__m.layer-139.bias" {noinline} = dense<0.00393700786> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node1037__m.layer-140.gamma" {noinline} = dense<0.00392156886> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node1038__m.layer-140.beta" {noinline} = dense<3.906250e-03> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node1039__m.layer-140.moving_mean" {noinline} = dense<0.00389105058> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node1040__m.layer-140.moving_variance" {noinline} = dense<0.00387596898> : tensor<1024xf32>
  util.global private @"__iree_flow___sm_node1053__m.layer-143.kernel" {noinline} = dense<0.00386100379> : tensor<1x1x1024x512xf32>
  util.global private @"__iree_flow___sm_node1054__m.layer-143.bias" {noinline} = dense<0.00384615385> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1060__m.layer-144.gamma" {noinline} = dense<0.00383141753> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1061__m.layer-144.beta" {noinline} = dense<0.00381679391> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1062__m.layer-144.moving_mean" {noinline} = dense<0.00380228134> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1063__m.layer-144.moving_variance" {noinline} = dense<0.0037878789> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1072__m.layer-146.kernel" {noinline} = dense<0.00377358496> : tensor<3x3x512x512xf32>
  util.global private @"__iree_flow___sm_node1073__m.layer-146.bias" {noinline} = dense<0.00375939859> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1079__m.layer-147.gamma" {noinline} = dense<0.00374531839> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1080__m.layer-147.beta" {noinline} = dense<0.0037313432> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1081__m.layer-147.moving_mean" {noinline} = dense<0.00371747208> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1082__m.layer-147.moving_variance" {noinline} = dense<0.00370370364> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1091__m.layer-149.kernel" {noinline} = dense<0.00369003695> : tensor<1x1x1024x2048xf32>
  util.global private @"__iree_flow___sm_node1092__m.layer-149.bias" {noinline} = dense<0.0036764706> : tensor<2048xf32>
  util.global private @"__iree_flow___sm_node1097__m.layer-150.kernel" {noinline} = dense<0.00366300368> : tensor<1x1x512x2048xf32>
  util.global private @"__iree_flow___sm_node1098__m.layer-150.bias" {noinline} = dense<0.00364963501> : tensor<2048xf32>
  util.global private @"__iree_flow___sm_node1104__m.layer-151.gamma" {noinline} = dense<0.00363636366> : tensor<2048xf32>
  util.global private @"__iree_flow___sm_node1105__m.layer-151.beta" {noinline} = dense<0.00362318847> : tensor<2048xf32>
  util.global private @"__iree_flow___sm_node1106__m.layer-151.moving_mean" {noinline} = dense<0.00361010828> : tensor<2048xf32>
  util.global private @"__iree_flow___sm_node1107__m.layer-151.moving_variance" {noinline} = dense<0.00359712238> : tensor<2048xf32>
  util.global private @"__iree_flow___sm_node1113__m.layer-152.gamma" {noinline} = dense<0.00358422939> : tensor<2048xf32>
  util.global private @"__iree_flow___sm_node1114__m.layer-152.beta" {noinline} = dense<0.00357142859> : tensor<2048xf32>
  util.global private @"__iree_flow___sm_node1115__m.layer-152.moving_mean" {noinline} = dense<0.00355871883> : tensor<2048xf32>
  util.global private @"__iree_flow___sm_node1116__m.layer-152.moving_variance" {noinline} = dense<0.00354609918> : tensor<2048xf32>
  util.global private @"__iree_flow___sm_node1129__m.layer-155.kernel" {noinline} = dense<0.00353356893> : tensor<1x1x2048x512xf32>
  util.global private @"__iree_flow___sm_node1130__m.layer-155.bias" {noinline} = dense<0.00352112669> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1136__m.layer-156.gamma" {noinline} = dense<0.003508772> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1137__m.layer-156.beta" {noinline} = dense<0.00349650346> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1138__m.layer-156.moving_mean" {noinline} = dense<0.00348432059> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1139__m.layer-156.moving_variance" {noinline} = dense<0.00347222225> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1148__m.layer-158.kernel" {noinline} = dense<0.00346020772> : tensor<3x3x512x512xf32>
  util.global private @"__iree_flow___sm_node1149__m.layer-158.bias" {noinline} = dense<0.00344827585> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1155__m.layer-159.gamma" {noinline} = dense<0.00343642617> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1156__m.layer-159.beta" {noinline} = dense<0.00342465751> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1157__m.layer-159.moving_mean" {noinline} = dense<0.00341296918> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1158__m.layer-159.moving_variance" {noinline} = dense<0.00340136047> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1167__m.layer-161.kernel" {noinline} = dense<0.00338983047> : tensor<1x1x512x2048xf32>
  util.global private @"__iree_flow___sm_node1168__m.layer-161.bias" {noinline} = dense<0.00337837846> : tensor<2048xf32>
  util.global private @"__iree_flow___sm_node1174__m.layer-162.gamma" {noinline} = dense<0.00336700329> : tensor<2048xf32>
  util.global private @"__iree_flow___sm_node1175__m.layer-162.beta" {noinline} = dense<0.00335570471> : tensor<2048xf32>
  util.global private @"__iree_flow___sm_node1176__m.layer-162.moving_mean" {noinline} = dense<0.00334448158> : tensor<2048xf32>
  util.global private @"__iree_flow___sm_node1177__m.layer-162.moving_variance" {noinline} = dense<0.00333333341> : tensor<2048xf32>
  util.global private @"__iree_flow___sm_node1190__m.layer-165.kernel" {noinline} = dense<0.00332225906> : tensor<1x1x2048x512xf32>
  util.global private @"__iree_flow___sm_node1191__m.layer-165.bias" {noinline} = dense<0.00331125828> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1197__m.layer-166.gamma" {noinline} = dense<0.00330033014> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1198__m.layer-166.beta" {noinline} = dense<0.00328947371> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1199__m.layer-166.moving_mean" {noinline} = dense<0.00327868853> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1200__m.layer-166.moving_variance" {noinline} = dense<0.00326797389> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1209__m.layer-168.kernel" {noinline} = dense<0.00325732888> : tensor<3x3x512x512xf32>
  util.global private @"__iree_flow___sm_node1210__m.layer-168.bias" {noinline} = dense<0.00324675324> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1216__m.layer-169.gamma" {noinline} = dense<0.00323624606> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1217__m.layer-169.beta" {noinline} = dense<0.0032258064> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1218__m.layer-169.moving_mean" {noinline} = dense<0.00321543403> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1219__m.layer-169.moving_variance" {noinline} = dense<0.00320512825> : tensor<512xf32>
  util.global private @"__iree_flow___sm_node1228__m.layer-171.kernel" {noinline} = dense<0.00319488812> : tensor<1x1x512x2048xf32>
  util.global private @"__iree_flow___sm_node1229__m.layer-171.bias" {noinline} = dense<0.00318471342> : tensor<2048xf32>
  util.global private @"__iree_flow___sm_node1235__m.layer-172.gamma" {noinline} = dense<0.00317460322> : tensor<2048xf32>
  util.global private @"__iree_flow___sm_node1236__m.layer-172.beta" {noinline} = dense<0.00316455704> : tensor<2048xf32>
  util.global private @"__iree_flow___sm_node1237__m.layer-172.moving_mean" {noinline} = dense<0.00315457419> : tensor<2048xf32>
  util.global private @"__iree_flow___sm_node1238__m.layer-172.moving_variance" {noinline} = dense<0.00314465398> : tensor<2048xf32>
  util.global private @"__iree_flow___sm_node1255__m.layer-176.kernel" {noinline} = dense<0.00313479616> : tensor<2048x1000xf32>
  util.global private @"__iree_flow___sm_node1256__m.layer-176.bias" {noinline} = dense<3.125000e-03> : tensor<1000xf32>
  func.func @predict(%arg0: tensor<1x224x224x3xf32>) -> tensor<1x1000xf32> attributes {iree.module.export, iree.reflection = {abi = "sip", abiv = 1 : i32, sip = "I8!S5!k0_0R3!_0"}} {
    %ptr___iree_flow___sm_node188__m.layer-2.kernel = util.global.address @"__iree_flow___sm_node188__m.layer-2.kernel" : !util.ptr<tensor<7x7x3x64xf32>>
    %ptr___iree_flow___sm_node189__m.layer-2.bias = util.global.address @"__iree_flow___sm_node189__m.layer-2.bias" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node195__m.layer-3.gamma = util.global.address @"__iree_flow___sm_node195__m.layer-3.gamma" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node196__m.layer-3.beta = util.global.address @"__iree_flow___sm_node196__m.layer-3.beta" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node197__m.layer-3.moving_mean = util.global.address @"__iree_flow___sm_node197__m.layer-3.moving_mean" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node198__m.layer-3.moving_variance = util.global.address @"__iree_flow___sm_node198__m.layer-3.moving_variance" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node215__m.layer-7.kernel = util.global.address @"__iree_flow___sm_node215__m.layer-7.kernel" : !util.ptr<tensor<1x1x64x64xf32>>
    %ptr___iree_flow___sm_node216__m.layer-7.bias = util.global.address @"__iree_flow___sm_node216__m.layer-7.bias" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node222__m.layer-8.gamma = util.global.address @"__iree_flow___sm_node222__m.layer-8.gamma" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node223__m.layer-8.beta = util.global.address @"__iree_flow___sm_node223__m.layer-8.beta" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node224__m.layer-8.moving_mean = util.global.address @"__iree_flow___sm_node224__m.layer-8.moving_mean" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node225__m.layer-8.moving_variance = util.global.address @"__iree_flow___sm_node225__m.layer-8.moving_variance" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node234__m.layer-10.kernel = util.global.address @"__iree_flow___sm_node234__m.layer-10.kernel" : !util.ptr<tensor<3x3x64x64xf32>>
    %ptr___iree_flow___sm_node235__m.layer-10.bias = util.global.address @"__iree_flow___sm_node235__m.layer-10.bias" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node241__m.layer-11.gamma = util.global.address @"__iree_flow___sm_node241__m.layer-11.gamma" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node242__m.layer-11.beta = util.global.address @"__iree_flow___sm_node242__m.layer-11.beta" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node243__m.layer-11.moving_mean = util.global.address @"__iree_flow___sm_node243__m.layer-11.moving_mean" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node244__m.layer-11.moving_variance = util.global.address @"__iree_flow___sm_node244__m.layer-11.moving_variance" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node259__m.layer-14.kernel = util.global.address @"__iree_flow___sm_node259__m.layer-14.kernel" : !util.ptr<tensor<1x1x64x256xf32>>
    %ptr___iree_flow___sm_node260__m.layer-14.bias = util.global.address @"__iree_flow___sm_node260__m.layer-14.bias" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node253__m.layer-13.kernel = util.global.address @"__iree_flow___sm_node253__m.layer-13.kernel" : !util.ptr<tensor<1x1x64x256xf32>>
    %ptr___iree_flow___sm_node254__m.layer-13.bias = util.global.address @"__iree_flow___sm_node254__m.layer-13.bias" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node266__m.layer-15.gamma = util.global.address @"__iree_flow___sm_node266__m.layer-15.gamma" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node267__m.layer-15.beta = util.global.address @"__iree_flow___sm_node267__m.layer-15.beta" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node268__m.layer-15.moving_mean = util.global.address @"__iree_flow___sm_node268__m.layer-15.moving_mean" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node269__m.layer-15.moving_variance = util.global.address @"__iree_flow___sm_node269__m.layer-15.moving_variance" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node275__m.layer-16.gamma = util.global.address @"__iree_flow___sm_node275__m.layer-16.gamma" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node276__m.layer-16.beta = util.global.address @"__iree_flow___sm_node276__m.layer-16.beta" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node277__m.layer-16.moving_mean = util.global.address @"__iree_flow___sm_node277__m.layer-16.moving_mean" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node278__m.layer-16.moving_variance = util.global.address @"__iree_flow___sm_node278__m.layer-16.moving_variance" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node291__m.layer-19.kernel = util.global.address @"__iree_flow___sm_node291__m.layer-19.kernel" : !util.ptr<tensor<1x1x256x64xf32>>
    %ptr___iree_flow___sm_node292__m.layer-19.bias = util.global.address @"__iree_flow___sm_node292__m.layer-19.bias" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node298__m.layer-20.gamma = util.global.address @"__iree_flow___sm_node298__m.layer-20.gamma" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node299__m.layer-20.beta = util.global.address @"__iree_flow___sm_node299__m.layer-20.beta" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node300__m.layer-20.moving_mean = util.global.address @"__iree_flow___sm_node300__m.layer-20.moving_mean" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node301__m.layer-20.moving_variance = util.global.address @"__iree_flow___sm_node301__m.layer-20.moving_variance" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node310__m.layer-22.kernel = util.global.address @"__iree_flow___sm_node310__m.layer-22.kernel" : !util.ptr<tensor<3x3x64x64xf32>>
    %ptr___iree_flow___sm_node311__m.layer-22.bias = util.global.address @"__iree_flow___sm_node311__m.layer-22.bias" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node317__m.layer-23.gamma = util.global.address @"__iree_flow___sm_node317__m.layer-23.gamma" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node318__m.layer-23.beta = util.global.address @"__iree_flow___sm_node318__m.layer-23.beta" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node319__m.layer-23.moving_mean = util.global.address @"__iree_flow___sm_node319__m.layer-23.moving_mean" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node320__m.layer-23.moving_variance = util.global.address @"__iree_flow___sm_node320__m.layer-23.moving_variance" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node329__m.layer-25.kernel = util.global.address @"__iree_flow___sm_node329__m.layer-25.kernel" : !util.ptr<tensor<1x1x64x256xf32>>
    %ptr___iree_flow___sm_node330__m.layer-25.bias = util.global.address @"__iree_flow___sm_node330__m.layer-25.bias" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node336__m.layer-26.gamma = util.global.address @"__iree_flow___sm_node336__m.layer-26.gamma" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node337__m.layer-26.beta = util.global.address @"__iree_flow___sm_node337__m.layer-26.beta" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node338__m.layer-26.moving_mean = util.global.address @"__iree_flow___sm_node338__m.layer-26.moving_mean" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node339__m.layer-26.moving_variance = util.global.address @"__iree_flow___sm_node339__m.layer-26.moving_variance" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node352__m.layer-29.kernel = util.global.address @"__iree_flow___sm_node352__m.layer-29.kernel" : !util.ptr<tensor<1x1x256x64xf32>>
    %ptr___iree_flow___sm_node353__m.layer-29.bias = util.global.address @"__iree_flow___sm_node353__m.layer-29.bias" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node359__m.layer-30.gamma = util.global.address @"__iree_flow___sm_node359__m.layer-30.gamma" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node360__m.layer-30.beta = util.global.address @"__iree_flow___sm_node360__m.layer-30.beta" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node361__m.layer-30.moving_mean = util.global.address @"__iree_flow___sm_node361__m.layer-30.moving_mean" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node362__m.layer-30.moving_variance = util.global.address @"__iree_flow___sm_node362__m.layer-30.moving_variance" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node371__m.layer-32.kernel = util.global.address @"__iree_flow___sm_node371__m.layer-32.kernel" : !util.ptr<tensor<3x3x64x64xf32>>
    %ptr___iree_flow___sm_node372__m.layer-32.bias = util.global.address @"__iree_flow___sm_node372__m.layer-32.bias" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node378__m.layer-33.gamma = util.global.address @"__iree_flow___sm_node378__m.layer-33.gamma" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node379__m.layer-33.beta = util.global.address @"__iree_flow___sm_node379__m.layer-33.beta" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node380__m.layer-33.moving_mean = util.global.address @"__iree_flow___sm_node380__m.layer-33.moving_mean" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node381__m.layer-33.moving_variance = util.global.address @"__iree_flow___sm_node381__m.layer-33.moving_variance" : !util.ptr<tensor<64xf32>>
    %ptr___iree_flow___sm_node390__m.layer-35.kernel = util.global.address @"__iree_flow___sm_node390__m.layer-35.kernel" : !util.ptr<tensor<1x1x64x256xf32>>
    %ptr___iree_flow___sm_node391__m.layer-35.bias = util.global.address @"__iree_flow___sm_node391__m.layer-35.bias" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node397__m.layer-36.gamma = util.global.address @"__iree_flow___sm_node397__m.layer-36.gamma" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node398__m.layer-36.beta = util.global.address @"__iree_flow___sm_node398__m.layer-36.beta" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node399__m.layer-36.moving_mean = util.global.address @"__iree_flow___sm_node399__m.layer-36.moving_mean" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node400__m.layer-36.moving_variance = util.global.address @"__iree_flow___sm_node400__m.layer-36.moving_variance" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node413__m.layer-39.kernel = util.global.address @"__iree_flow___sm_node413__m.layer-39.kernel" : !util.ptr<tensor<1x1x256x128xf32>>
    %ptr___iree_flow___sm_node414__m.layer-39.bias = util.global.address @"__iree_flow___sm_node414__m.layer-39.bias" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node420__m.layer-40.gamma = util.global.address @"__iree_flow___sm_node420__m.layer-40.gamma" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node421__m.layer-40.beta = util.global.address @"__iree_flow___sm_node421__m.layer-40.beta" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node422__m.layer-40.moving_mean = util.global.address @"__iree_flow___sm_node422__m.layer-40.moving_mean" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node423__m.layer-40.moving_variance = util.global.address @"__iree_flow___sm_node423__m.layer-40.moving_variance" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node432__m.layer-42.kernel = util.global.address @"__iree_flow___sm_node432__m.layer-42.kernel" : !util.ptr<tensor<3x3x128x128xf32>>
    %ptr___iree_flow___sm_node433__m.layer-42.bias = util.global.address @"__iree_flow___sm_node433__m.layer-42.bias" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node439__m.layer-43.gamma = util.global.address @"__iree_flow___sm_node439__m.layer-43.gamma" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node440__m.layer-43.beta = util.global.address @"__iree_flow___sm_node440__m.layer-43.beta" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node441__m.layer-43.moving_mean = util.global.address @"__iree_flow___sm_node441__m.layer-43.moving_mean" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node442__m.layer-43.moving_variance = util.global.address @"__iree_flow___sm_node442__m.layer-43.moving_variance" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node457__m.layer-46.kernel = util.global.address @"__iree_flow___sm_node457__m.layer-46.kernel" : !util.ptr<tensor<1x1x128x512xf32>>
    %ptr___iree_flow___sm_node458__m.layer-46.bias = util.global.address @"__iree_flow___sm_node458__m.layer-46.bias" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node451__m.layer-45.kernel = util.global.address @"__iree_flow___sm_node451__m.layer-45.kernel" : !util.ptr<tensor<1x1x256x512xf32>>
    %ptr___iree_flow___sm_node452__m.layer-45.bias = util.global.address @"__iree_flow___sm_node452__m.layer-45.bias" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node464__m.layer-47.gamma = util.global.address @"__iree_flow___sm_node464__m.layer-47.gamma" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node465__m.layer-47.beta = util.global.address @"__iree_flow___sm_node465__m.layer-47.beta" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node466__m.layer-47.moving_mean = util.global.address @"__iree_flow___sm_node466__m.layer-47.moving_mean" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node467__m.layer-47.moving_variance = util.global.address @"__iree_flow___sm_node467__m.layer-47.moving_variance" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node473__m.layer-48.gamma = util.global.address @"__iree_flow___sm_node473__m.layer-48.gamma" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node474__m.layer-48.beta = util.global.address @"__iree_flow___sm_node474__m.layer-48.beta" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node475__m.layer-48.moving_mean = util.global.address @"__iree_flow___sm_node475__m.layer-48.moving_mean" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node476__m.layer-48.moving_variance = util.global.address @"__iree_flow___sm_node476__m.layer-48.moving_variance" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node489__m.layer-51.kernel = util.global.address @"__iree_flow___sm_node489__m.layer-51.kernel" : !util.ptr<tensor<1x1x512x128xf32>>
    %ptr___iree_flow___sm_node490__m.layer-51.bias = util.global.address @"__iree_flow___sm_node490__m.layer-51.bias" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node496__m.layer-52.gamma = util.global.address @"__iree_flow___sm_node496__m.layer-52.gamma" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node497__m.layer-52.beta = util.global.address @"__iree_flow___sm_node497__m.layer-52.beta" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node498__m.layer-52.moving_mean = util.global.address @"__iree_flow___sm_node498__m.layer-52.moving_mean" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node499__m.layer-52.moving_variance = util.global.address @"__iree_flow___sm_node499__m.layer-52.moving_variance" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node508__m.layer-54.kernel = util.global.address @"__iree_flow___sm_node508__m.layer-54.kernel" : !util.ptr<tensor<3x3x128x128xf32>>
    %ptr___iree_flow___sm_node509__m.layer-54.bias = util.global.address @"__iree_flow___sm_node509__m.layer-54.bias" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node515__m.layer-55.gamma = util.global.address @"__iree_flow___sm_node515__m.layer-55.gamma" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node516__m.layer-55.beta = util.global.address @"__iree_flow___sm_node516__m.layer-55.beta" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node517__m.layer-55.moving_mean = util.global.address @"__iree_flow___sm_node517__m.layer-55.moving_mean" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node518__m.layer-55.moving_variance = util.global.address @"__iree_flow___sm_node518__m.layer-55.moving_variance" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node527__m.layer-57.kernel = util.global.address @"__iree_flow___sm_node527__m.layer-57.kernel" : !util.ptr<tensor<1x1x128x512xf32>>
    %ptr___iree_flow___sm_node528__m.layer-57.bias = util.global.address @"__iree_flow___sm_node528__m.layer-57.bias" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node534__m.layer-58.gamma = util.global.address @"__iree_flow___sm_node534__m.layer-58.gamma" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node535__m.layer-58.beta = util.global.address @"__iree_flow___sm_node535__m.layer-58.beta" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node536__m.layer-58.moving_mean = util.global.address @"__iree_flow___sm_node536__m.layer-58.moving_mean" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node537__m.layer-58.moving_variance = util.global.address @"__iree_flow___sm_node537__m.layer-58.moving_variance" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node550__m.layer-61.kernel = util.global.address @"__iree_flow___sm_node550__m.layer-61.kernel" : !util.ptr<tensor<1x1x512x128xf32>>
    %ptr___iree_flow___sm_node551__m.layer-61.bias = util.global.address @"__iree_flow___sm_node551__m.layer-61.bias" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node557__m.layer-62.gamma = util.global.address @"__iree_flow___sm_node557__m.layer-62.gamma" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node558__m.layer-62.beta = util.global.address @"__iree_flow___sm_node558__m.layer-62.beta" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node559__m.layer-62.moving_mean = util.global.address @"__iree_flow___sm_node559__m.layer-62.moving_mean" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node560__m.layer-62.moving_variance = util.global.address @"__iree_flow___sm_node560__m.layer-62.moving_variance" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node569__m.layer-64.kernel = util.global.address @"__iree_flow___sm_node569__m.layer-64.kernel" : !util.ptr<tensor<3x3x128x128xf32>>
    %ptr___iree_flow___sm_node570__m.layer-64.bias = util.global.address @"__iree_flow___sm_node570__m.layer-64.bias" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node576__m.layer-65.gamma = util.global.address @"__iree_flow___sm_node576__m.layer-65.gamma" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node577__m.layer-65.beta = util.global.address @"__iree_flow___sm_node577__m.layer-65.beta" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node578__m.layer-65.moving_mean = util.global.address @"__iree_flow___sm_node578__m.layer-65.moving_mean" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node579__m.layer-65.moving_variance = util.global.address @"__iree_flow___sm_node579__m.layer-65.moving_variance" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node588__m.layer-67.kernel = util.global.address @"__iree_flow___sm_node588__m.layer-67.kernel" : !util.ptr<tensor<1x1x128x512xf32>>
    %ptr___iree_flow___sm_node589__m.layer-67.bias = util.global.address @"__iree_flow___sm_node589__m.layer-67.bias" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node595__m.layer-68.gamma = util.global.address @"__iree_flow___sm_node595__m.layer-68.gamma" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node596__m.layer-68.beta = util.global.address @"__iree_flow___sm_node596__m.layer-68.beta" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node597__m.layer-68.moving_mean = util.global.address @"__iree_flow___sm_node597__m.layer-68.moving_mean" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node598__m.layer-68.moving_variance = util.global.address @"__iree_flow___sm_node598__m.layer-68.moving_variance" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node611__m.layer-71.kernel = util.global.address @"__iree_flow___sm_node611__m.layer-71.kernel" : !util.ptr<tensor<1x1x512x128xf32>>
    %ptr___iree_flow___sm_node612__m.layer-71.bias = util.global.address @"__iree_flow___sm_node612__m.layer-71.bias" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node618__m.layer-72.gamma = util.global.address @"__iree_flow___sm_node618__m.layer-72.gamma" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node619__m.layer-72.beta = util.global.address @"__iree_flow___sm_node619__m.layer-72.beta" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node620__m.layer-72.moving_mean = util.global.address @"__iree_flow___sm_node620__m.layer-72.moving_mean" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node621__m.layer-72.moving_variance = util.global.address @"__iree_flow___sm_node621__m.layer-72.moving_variance" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node630__m.layer-74.kernel = util.global.address @"__iree_flow___sm_node630__m.layer-74.kernel" : !util.ptr<tensor<3x3x128x128xf32>>
    %ptr___iree_flow___sm_node631__m.layer-74.bias = util.global.address @"__iree_flow___sm_node631__m.layer-74.bias" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node637__m.layer-75.gamma = util.global.address @"__iree_flow___sm_node637__m.layer-75.gamma" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node638__m.layer-75.beta = util.global.address @"__iree_flow___sm_node638__m.layer-75.beta" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node639__m.layer-75.moving_mean = util.global.address @"__iree_flow___sm_node639__m.layer-75.moving_mean" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node640__m.layer-75.moving_variance = util.global.address @"__iree_flow___sm_node640__m.layer-75.moving_variance" : !util.ptr<tensor<128xf32>>
    %ptr___iree_flow___sm_node649__m.layer-77.kernel = util.global.address @"__iree_flow___sm_node649__m.layer-77.kernel" : !util.ptr<tensor<1x1x128x512xf32>>
    %ptr___iree_flow___sm_node650__m.layer-77.bias = util.global.address @"__iree_flow___sm_node650__m.layer-77.bias" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node656__m.layer-78.gamma = util.global.address @"__iree_flow___sm_node656__m.layer-78.gamma" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node657__m.layer-78.beta = util.global.address @"__iree_flow___sm_node657__m.layer-78.beta" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node658__m.layer-78.moving_mean = util.global.address @"__iree_flow___sm_node658__m.layer-78.moving_mean" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node659__m.layer-78.moving_variance = util.global.address @"__iree_flow___sm_node659__m.layer-78.moving_variance" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node672__m.layer-81.kernel = util.global.address @"__iree_flow___sm_node672__m.layer-81.kernel" : !util.ptr<tensor<1x1x512x256xf32>>
    %ptr___iree_flow___sm_node673__m.layer-81.bias = util.global.address @"__iree_flow___sm_node673__m.layer-81.bias" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node679__m.layer-82.gamma = util.global.address @"__iree_flow___sm_node679__m.layer-82.gamma" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node680__m.layer-82.beta = util.global.address @"__iree_flow___sm_node680__m.layer-82.beta" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node681__m.layer-82.moving_mean = util.global.address @"__iree_flow___sm_node681__m.layer-82.moving_mean" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node682__m.layer-82.moving_variance = util.global.address @"__iree_flow___sm_node682__m.layer-82.moving_variance" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node691__m.layer-84.kernel = util.global.address @"__iree_flow___sm_node691__m.layer-84.kernel" : !util.ptr<tensor<3x3x256x256xf32>>
    %ptr___iree_flow___sm_node692__m.layer-84.bias = util.global.address @"__iree_flow___sm_node692__m.layer-84.bias" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node698__m.layer-85.gamma = util.global.address @"__iree_flow___sm_node698__m.layer-85.gamma" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node699__m.layer-85.beta = util.global.address @"__iree_flow___sm_node699__m.layer-85.beta" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node700__m.layer-85.moving_mean = util.global.address @"__iree_flow___sm_node700__m.layer-85.moving_mean" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node701__m.layer-85.moving_variance = util.global.address @"__iree_flow___sm_node701__m.layer-85.moving_variance" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node716__m.layer-88.kernel = util.global.address @"__iree_flow___sm_node716__m.layer-88.kernel" : !util.ptr<tensor<1x1x256x1024xf32>>
    %ptr___iree_flow___sm_node717__m.layer-88.bias = util.global.address @"__iree_flow___sm_node717__m.layer-88.bias" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node710__m.layer-87.kernel = util.global.address @"__iree_flow___sm_node710__m.layer-87.kernel" : !util.ptr<tensor<1x1x512x1024xf32>>
    %ptr___iree_flow___sm_node711__m.layer-87.bias = util.global.address @"__iree_flow___sm_node711__m.layer-87.bias" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node723__m.layer-89.gamma = util.global.address @"__iree_flow___sm_node723__m.layer-89.gamma" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node724__m.layer-89.beta = util.global.address @"__iree_flow___sm_node724__m.layer-89.beta" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node725__m.layer-89.moving_mean = util.global.address @"__iree_flow___sm_node725__m.layer-89.moving_mean" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node726__m.layer-89.moving_variance = util.global.address @"__iree_flow___sm_node726__m.layer-89.moving_variance" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node732__m.layer-90.gamma = util.global.address @"__iree_flow___sm_node732__m.layer-90.gamma" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node733__m.layer-90.beta = util.global.address @"__iree_flow___sm_node733__m.layer-90.beta" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node734__m.layer-90.moving_mean = util.global.address @"__iree_flow___sm_node734__m.layer-90.moving_mean" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node735__m.layer-90.moving_variance = util.global.address @"__iree_flow___sm_node735__m.layer-90.moving_variance" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node748__m.layer-93.kernel = util.global.address @"__iree_flow___sm_node748__m.layer-93.kernel" : !util.ptr<tensor<1x1x1024x256xf32>>
    %ptr___iree_flow___sm_node749__m.layer-93.bias = util.global.address @"__iree_flow___sm_node749__m.layer-93.bias" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node755__m.layer-94.gamma = util.global.address @"__iree_flow___sm_node755__m.layer-94.gamma" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node756__m.layer-94.beta = util.global.address @"__iree_flow___sm_node756__m.layer-94.beta" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node757__m.layer-94.moving_mean = util.global.address @"__iree_flow___sm_node757__m.layer-94.moving_mean" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node758__m.layer-94.moving_variance = util.global.address @"__iree_flow___sm_node758__m.layer-94.moving_variance" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node767__m.layer-96.kernel = util.global.address @"__iree_flow___sm_node767__m.layer-96.kernel" : !util.ptr<tensor<3x3x256x256xf32>>
    %ptr___iree_flow___sm_node768__m.layer-96.bias = util.global.address @"__iree_flow___sm_node768__m.layer-96.bias" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node774__m.layer-97.gamma = util.global.address @"__iree_flow___sm_node774__m.layer-97.gamma" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node775__m.layer-97.beta = util.global.address @"__iree_flow___sm_node775__m.layer-97.beta" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node776__m.layer-97.moving_mean = util.global.address @"__iree_flow___sm_node776__m.layer-97.moving_mean" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node777__m.layer-97.moving_variance = util.global.address @"__iree_flow___sm_node777__m.layer-97.moving_variance" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node786__m.layer-99.kernel = util.global.address @"__iree_flow___sm_node786__m.layer-99.kernel" : !util.ptr<tensor<1x1x256x1024xf32>>
    %ptr___iree_flow___sm_node787__m.layer-99.bias = util.global.address @"__iree_flow___sm_node787__m.layer-99.bias" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node793__m.layer-100.gamma = util.global.address @"__iree_flow___sm_node793__m.layer-100.gamma" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node794__m.layer-100.beta = util.global.address @"__iree_flow___sm_node794__m.layer-100.beta" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node795__m.layer-100.moving_mean = util.global.address @"__iree_flow___sm_node795__m.layer-100.moving_mean" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node796__m.layer-100.moving_variance = util.global.address @"__iree_flow___sm_node796__m.layer-100.moving_variance" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node809__m.layer-103.kernel = util.global.address @"__iree_flow___sm_node809__m.layer-103.kernel" : !util.ptr<tensor<1x1x1024x256xf32>>
    %ptr___iree_flow___sm_node810__m.layer-103.bias = util.global.address @"__iree_flow___sm_node810__m.layer-103.bias" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node816__m.layer-104.gamma = util.global.address @"__iree_flow___sm_node816__m.layer-104.gamma" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node817__m.layer-104.beta = util.global.address @"__iree_flow___sm_node817__m.layer-104.beta" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node818__m.layer-104.moving_mean = util.global.address @"__iree_flow___sm_node818__m.layer-104.moving_mean" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node819__m.layer-104.moving_variance = util.global.address @"__iree_flow___sm_node819__m.layer-104.moving_variance" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node828__m.layer-106.kernel = util.global.address @"__iree_flow___sm_node828__m.layer-106.kernel" : !util.ptr<tensor<3x3x256x256xf32>>
    %ptr___iree_flow___sm_node829__m.layer-106.bias = util.global.address @"__iree_flow___sm_node829__m.layer-106.bias" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node835__m.layer-107.gamma = util.global.address @"__iree_flow___sm_node835__m.layer-107.gamma" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node836__m.layer-107.beta = util.global.address @"__iree_flow___sm_node836__m.layer-107.beta" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node837__m.layer-107.moving_mean = util.global.address @"__iree_flow___sm_node837__m.layer-107.moving_mean" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node838__m.layer-107.moving_variance = util.global.address @"__iree_flow___sm_node838__m.layer-107.moving_variance" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node847__m.layer-109.kernel = util.global.address @"__iree_flow___sm_node847__m.layer-109.kernel" : !util.ptr<tensor<1x1x256x1024xf32>>
    %ptr___iree_flow___sm_node848__m.layer-109.bias = util.global.address @"__iree_flow___sm_node848__m.layer-109.bias" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node854__m.layer-110.gamma = util.global.address @"__iree_flow___sm_node854__m.layer-110.gamma" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node855__m.layer-110.beta = util.global.address @"__iree_flow___sm_node855__m.layer-110.beta" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node856__m.layer-110.moving_mean = util.global.address @"__iree_flow___sm_node856__m.layer-110.moving_mean" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node857__m.layer-110.moving_variance = util.global.address @"__iree_flow___sm_node857__m.layer-110.moving_variance" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node870__m.layer-113.kernel = util.global.address @"__iree_flow___sm_node870__m.layer-113.kernel" : !util.ptr<tensor<1x1x1024x256xf32>>
    %ptr___iree_flow___sm_node871__m.layer-113.bias = util.global.address @"__iree_flow___sm_node871__m.layer-113.bias" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node877__m.layer-114.gamma = util.global.address @"__iree_flow___sm_node877__m.layer-114.gamma" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node878__m.layer-114.beta = util.global.address @"__iree_flow___sm_node878__m.layer-114.beta" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node879__m.layer-114.moving_mean = util.global.address @"__iree_flow___sm_node879__m.layer-114.moving_mean" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node880__m.layer-114.moving_variance = util.global.address @"__iree_flow___sm_node880__m.layer-114.moving_variance" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node889__m.layer-116.kernel = util.global.address @"__iree_flow___sm_node889__m.layer-116.kernel" : !util.ptr<tensor<3x3x256x256xf32>>
    %ptr___iree_flow___sm_node890__m.layer-116.bias = util.global.address @"__iree_flow___sm_node890__m.layer-116.bias" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node896__m.layer-117.gamma = util.global.address @"__iree_flow___sm_node896__m.layer-117.gamma" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node897__m.layer-117.beta = util.global.address @"__iree_flow___sm_node897__m.layer-117.beta" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node898__m.layer-117.moving_mean = util.global.address @"__iree_flow___sm_node898__m.layer-117.moving_mean" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node899__m.layer-117.moving_variance = util.global.address @"__iree_flow___sm_node899__m.layer-117.moving_variance" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node908__m.layer-119.kernel = util.global.address @"__iree_flow___sm_node908__m.layer-119.kernel" : !util.ptr<tensor<1x1x256x1024xf32>>
    %ptr___iree_flow___sm_node909__m.layer-119.bias = util.global.address @"__iree_flow___sm_node909__m.layer-119.bias" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node915__m.layer-120.gamma = util.global.address @"__iree_flow___sm_node915__m.layer-120.gamma" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node916__m.layer-120.beta = util.global.address @"__iree_flow___sm_node916__m.layer-120.beta" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node917__m.layer-120.moving_mean = util.global.address @"__iree_flow___sm_node917__m.layer-120.moving_mean" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node918__m.layer-120.moving_variance = util.global.address @"__iree_flow___sm_node918__m.layer-120.moving_variance" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node931__m.layer-123.kernel = util.global.address @"__iree_flow___sm_node931__m.layer-123.kernel" : !util.ptr<tensor<1x1x1024x256xf32>>
    %ptr___iree_flow___sm_node932__m.layer-123.bias = util.global.address @"__iree_flow___sm_node932__m.layer-123.bias" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node938__m.layer-124.gamma = util.global.address @"__iree_flow___sm_node938__m.layer-124.gamma" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node939__m.layer-124.beta = util.global.address @"__iree_flow___sm_node939__m.layer-124.beta" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node940__m.layer-124.moving_mean = util.global.address @"__iree_flow___sm_node940__m.layer-124.moving_mean" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node941__m.layer-124.moving_variance = util.global.address @"__iree_flow___sm_node941__m.layer-124.moving_variance" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node950__m.layer-126.kernel = util.global.address @"__iree_flow___sm_node950__m.layer-126.kernel" : !util.ptr<tensor<3x3x256x256xf32>>
    %ptr___iree_flow___sm_node951__m.layer-126.bias = util.global.address @"__iree_flow___sm_node951__m.layer-126.bias" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node957__m.layer-127.gamma = util.global.address @"__iree_flow___sm_node957__m.layer-127.gamma" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node958__m.layer-127.beta = util.global.address @"__iree_flow___sm_node958__m.layer-127.beta" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node959__m.layer-127.moving_mean = util.global.address @"__iree_flow___sm_node959__m.layer-127.moving_mean" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node960__m.layer-127.moving_variance = util.global.address @"__iree_flow___sm_node960__m.layer-127.moving_variance" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node969__m.layer-129.kernel = util.global.address @"__iree_flow___sm_node969__m.layer-129.kernel" : !util.ptr<tensor<1x1x256x1024xf32>>
    %ptr___iree_flow___sm_node970__m.layer-129.bias = util.global.address @"__iree_flow___sm_node970__m.layer-129.bias" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node976__m.layer-130.gamma = util.global.address @"__iree_flow___sm_node976__m.layer-130.gamma" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node977__m.layer-130.beta = util.global.address @"__iree_flow___sm_node977__m.layer-130.beta" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node978__m.layer-130.moving_mean = util.global.address @"__iree_flow___sm_node978__m.layer-130.moving_mean" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node979__m.layer-130.moving_variance = util.global.address @"__iree_flow___sm_node979__m.layer-130.moving_variance" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node992__m.layer-133.kernel = util.global.address @"__iree_flow___sm_node992__m.layer-133.kernel" : !util.ptr<tensor<1x1x1024x256xf32>>
    %ptr___iree_flow___sm_node993__m.layer-133.bias = util.global.address @"__iree_flow___sm_node993__m.layer-133.bias" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node999__m.layer-134.gamma = util.global.address @"__iree_flow___sm_node999__m.layer-134.gamma" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node1000__m.layer-134.beta = util.global.address @"__iree_flow___sm_node1000__m.layer-134.beta" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node1001__m.layer-134.moving_mean = util.global.address @"__iree_flow___sm_node1001__m.layer-134.moving_mean" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node1002__m.layer-134.moving_variance = util.global.address @"__iree_flow___sm_node1002__m.layer-134.moving_variance" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node1011__m.layer-136.kernel = util.global.address @"__iree_flow___sm_node1011__m.layer-136.kernel" : !util.ptr<tensor<3x3x256x256xf32>>
    %ptr___iree_flow___sm_node1012__m.layer-136.bias = util.global.address @"__iree_flow___sm_node1012__m.layer-136.bias" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node1018__m.layer-137.gamma = util.global.address @"__iree_flow___sm_node1018__m.layer-137.gamma" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node1019__m.layer-137.beta = util.global.address @"__iree_flow___sm_node1019__m.layer-137.beta" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node1020__m.layer-137.moving_mean = util.global.address @"__iree_flow___sm_node1020__m.layer-137.moving_mean" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node1021__m.layer-137.moving_variance = util.global.address @"__iree_flow___sm_node1021__m.layer-137.moving_variance" : !util.ptr<tensor<256xf32>>
    %ptr___iree_flow___sm_node1030__m.layer-139.kernel = util.global.address @"__iree_flow___sm_node1030__m.layer-139.kernel" : !util.ptr<tensor<1x1x256x1024xf32>>
    %ptr___iree_flow___sm_node1031__m.layer-139.bias = util.global.address @"__iree_flow___sm_node1031__m.layer-139.bias" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node1037__m.layer-140.gamma = util.global.address @"__iree_flow___sm_node1037__m.layer-140.gamma" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node1038__m.layer-140.beta = util.global.address @"__iree_flow___sm_node1038__m.layer-140.beta" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node1039__m.layer-140.moving_mean = util.global.address @"__iree_flow___sm_node1039__m.layer-140.moving_mean" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node1040__m.layer-140.moving_variance = util.global.address @"__iree_flow___sm_node1040__m.layer-140.moving_variance" : !util.ptr<tensor<1024xf32>>
    %ptr___iree_flow___sm_node1053__m.layer-143.kernel = util.global.address @"__iree_flow___sm_node1053__m.layer-143.kernel" : !util.ptr<tensor<1x1x1024x512xf32>>
    %ptr___iree_flow___sm_node1054__m.layer-143.bias = util.global.address @"__iree_flow___sm_node1054__m.layer-143.bias" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1060__m.layer-144.gamma = util.global.address @"__iree_flow___sm_node1060__m.layer-144.gamma" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1061__m.layer-144.beta = util.global.address @"__iree_flow___sm_node1061__m.layer-144.beta" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1062__m.layer-144.moving_mean = util.global.address @"__iree_flow___sm_node1062__m.layer-144.moving_mean" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1063__m.layer-144.moving_variance = util.global.address @"__iree_flow___sm_node1063__m.layer-144.moving_variance" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1072__m.layer-146.kernel = util.global.address @"__iree_flow___sm_node1072__m.layer-146.kernel" : !util.ptr<tensor<3x3x512x512xf32>>
    %ptr___iree_flow___sm_node1073__m.layer-146.bias = util.global.address @"__iree_flow___sm_node1073__m.layer-146.bias" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1079__m.layer-147.gamma = util.global.address @"__iree_flow___sm_node1079__m.layer-147.gamma" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1080__m.layer-147.beta = util.global.address @"__iree_flow___sm_node1080__m.layer-147.beta" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1081__m.layer-147.moving_mean = util.global.address @"__iree_flow___sm_node1081__m.layer-147.moving_mean" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1082__m.layer-147.moving_variance = util.global.address @"__iree_flow___sm_node1082__m.layer-147.moving_variance" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1097__m.layer-150.kernel = util.global.address @"__iree_flow___sm_node1097__m.layer-150.kernel" : !util.ptr<tensor<1x1x512x2048xf32>>
    %ptr___iree_flow___sm_node1098__m.layer-150.bias = util.global.address @"__iree_flow___sm_node1098__m.layer-150.bias" : !util.ptr<tensor<2048xf32>>
    %ptr___iree_flow___sm_node1091__m.layer-149.kernel = util.global.address @"__iree_flow___sm_node1091__m.layer-149.kernel" : !util.ptr<tensor<1x1x1024x2048xf32>>
    %ptr___iree_flow___sm_node1092__m.layer-149.bias = util.global.address @"__iree_flow___sm_node1092__m.layer-149.bias" : !util.ptr<tensor<2048xf32>>
    %ptr___iree_flow___sm_node1104__m.layer-151.gamma = util.global.address @"__iree_flow___sm_node1104__m.layer-151.gamma" : !util.ptr<tensor<2048xf32>>
    %ptr___iree_flow___sm_node1105__m.layer-151.beta = util.global.address @"__iree_flow___sm_node1105__m.layer-151.beta" : !util.ptr<tensor<2048xf32>>
    %ptr___iree_flow___sm_node1106__m.layer-151.moving_mean = util.global.address @"__iree_flow___sm_node1106__m.layer-151.moving_mean" : !util.ptr<tensor<2048xf32>>
    %ptr___iree_flow___sm_node1107__m.layer-151.moving_variance = util.global.address @"__iree_flow___sm_node1107__m.layer-151.moving_variance" : !util.ptr<tensor<2048xf32>>
    %ptr___iree_flow___sm_node1113__m.layer-152.gamma = util.global.address @"__iree_flow___sm_node1113__m.layer-152.gamma" : !util.ptr<tensor<2048xf32>>
    %ptr___iree_flow___sm_node1114__m.layer-152.beta = util.global.address @"__iree_flow___sm_node1114__m.layer-152.beta" : !util.ptr<tensor<2048xf32>>
    %ptr___iree_flow___sm_node1115__m.layer-152.moving_mean = util.global.address @"__iree_flow___sm_node1115__m.layer-152.moving_mean" : !util.ptr<tensor<2048xf32>>
    %ptr___iree_flow___sm_node1116__m.layer-152.moving_variance = util.global.address @"__iree_flow___sm_node1116__m.layer-152.moving_variance" : !util.ptr<tensor<2048xf32>>
    %ptr___iree_flow___sm_node1129__m.layer-155.kernel = util.global.address @"__iree_flow___sm_node1129__m.layer-155.kernel" : !util.ptr<tensor<1x1x2048x512xf32>>
    %ptr___iree_flow___sm_node1130__m.layer-155.bias = util.global.address @"__iree_flow___sm_node1130__m.layer-155.bias" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1136__m.layer-156.gamma = util.global.address @"__iree_flow___sm_node1136__m.layer-156.gamma" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1137__m.layer-156.beta = util.global.address @"__iree_flow___sm_node1137__m.layer-156.beta" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1138__m.layer-156.moving_mean = util.global.address @"__iree_flow___sm_node1138__m.layer-156.moving_mean" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1139__m.layer-156.moving_variance = util.global.address @"__iree_flow___sm_node1139__m.layer-156.moving_variance" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1148__m.layer-158.kernel = util.global.address @"__iree_flow___sm_node1148__m.layer-158.kernel" : !util.ptr<tensor<3x3x512x512xf32>>
    %ptr___iree_flow___sm_node1149__m.layer-158.bias = util.global.address @"__iree_flow___sm_node1149__m.layer-158.bias" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1155__m.layer-159.gamma = util.global.address @"__iree_flow___sm_node1155__m.layer-159.gamma" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1156__m.layer-159.beta = util.global.address @"__iree_flow___sm_node1156__m.layer-159.beta" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1157__m.layer-159.moving_mean = util.global.address @"__iree_flow___sm_node1157__m.layer-159.moving_mean" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1158__m.layer-159.moving_variance = util.global.address @"__iree_flow___sm_node1158__m.layer-159.moving_variance" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1167__m.layer-161.kernel = util.global.address @"__iree_flow___sm_node1167__m.layer-161.kernel" : !util.ptr<tensor<1x1x512x2048xf32>>
    %ptr___iree_flow___sm_node1168__m.layer-161.bias = util.global.address @"__iree_flow___sm_node1168__m.layer-161.bias" : !util.ptr<tensor<2048xf32>>
    %ptr___iree_flow___sm_node1174__m.layer-162.gamma = util.global.address @"__iree_flow___sm_node1174__m.layer-162.gamma" : !util.ptr<tensor<2048xf32>>
    %ptr___iree_flow___sm_node1175__m.layer-162.beta = util.global.address @"__iree_flow___sm_node1175__m.layer-162.beta" : !util.ptr<tensor<2048xf32>>
    %ptr___iree_flow___sm_node1176__m.layer-162.moving_mean = util.global.address @"__iree_flow___sm_node1176__m.layer-162.moving_mean" : !util.ptr<tensor<2048xf32>>
    %ptr___iree_flow___sm_node1177__m.layer-162.moving_variance = util.global.address @"__iree_flow___sm_node1177__m.layer-162.moving_variance" : !util.ptr<tensor<2048xf32>>
    %ptr___iree_flow___sm_node1190__m.layer-165.kernel = util.global.address @"__iree_flow___sm_node1190__m.layer-165.kernel" : !util.ptr<tensor<1x1x2048x512xf32>>
    %ptr___iree_flow___sm_node1191__m.layer-165.bias = util.global.address @"__iree_flow___sm_node1191__m.layer-165.bias" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1197__m.layer-166.gamma = util.global.address @"__iree_flow___sm_node1197__m.layer-166.gamma" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1198__m.layer-166.beta = util.global.address @"__iree_flow___sm_node1198__m.layer-166.beta" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1199__m.layer-166.moving_mean = util.global.address @"__iree_flow___sm_node1199__m.layer-166.moving_mean" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1200__m.layer-166.moving_variance = util.global.address @"__iree_flow___sm_node1200__m.layer-166.moving_variance" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1209__m.layer-168.kernel = util.global.address @"__iree_flow___sm_node1209__m.layer-168.kernel" : !util.ptr<tensor<3x3x512x512xf32>>
    %ptr___iree_flow___sm_node1210__m.layer-168.bias = util.global.address @"__iree_flow___sm_node1210__m.layer-168.bias" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1216__m.layer-169.gamma = util.global.address @"__iree_flow___sm_node1216__m.layer-169.gamma" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1217__m.layer-169.beta = util.global.address @"__iree_flow___sm_node1217__m.layer-169.beta" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1218__m.layer-169.moving_mean = util.global.address @"__iree_flow___sm_node1218__m.layer-169.moving_mean" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1219__m.layer-169.moving_variance = util.global.address @"__iree_flow___sm_node1219__m.layer-169.moving_variance" : !util.ptr<tensor<512xf32>>
    %ptr___iree_flow___sm_node1228__m.layer-171.kernel = util.global.address @"__iree_flow___sm_node1228__m.layer-171.kernel" : !util.ptr<tensor<1x1x512x2048xf32>>
    %ptr___iree_flow___sm_node1229__m.layer-171.bias = util.global.address @"__iree_flow___sm_node1229__m.layer-171.bias" : !util.ptr<tensor<2048xf32>>
    %ptr___iree_flow___sm_node1235__m.layer-172.gamma = util.global.address @"__iree_flow___sm_node1235__m.layer-172.gamma" : !util.ptr<tensor<2048xf32>>
    %ptr___iree_flow___sm_node1236__m.layer-172.beta = util.global.address @"__iree_flow___sm_node1236__m.layer-172.beta" : !util.ptr<tensor<2048xf32>>
    %ptr___iree_flow___sm_node1237__m.layer-172.moving_mean = util.global.address @"__iree_flow___sm_node1237__m.layer-172.moving_mean" : !util.ptr<tensor<2048xf32>>
    %ptr___iree_flow___sm_node1238__m.layer-172.moving_variance = util.global.address @"__iree_flow___sm_node1238__m.layer-172.moving_variance" : !util.ptr<tensor<2048xf32>>
    %ptr___iree_flow___sm_node1255__m.layer-176.kernel = util.global.address @"__iree_flow___sm_node1255__m.layer-176.kernel" : !util.ptr<tensor<2048x1000xf32>>
    %ptr___iree_flow___sm_node1256__m.layer-176.bias = util.global.address @"__iree_flow___sm_node1256__m.layer-176.bias" : !util.ptr<tensor<1000xf32>>
    %0 = stablehlo.constant dense<0.000000e+00> : tensor<1x112x112x64xf32>
    %1 = stablehlo.constant dense<0.000000e+00> : tensor<1x56x56x64xf32>
    %2 = stablehlo.constant dense<0.000000e+00> : tensor<1x56x56x256xf32>
    %3 = stablehlo.constant dense<0.000000e+00> : tensor<1x28x28x128xf32>
    %4 = stablehlo.constant dense<0.000000e+00> : tensor<1x28x28x512xf32>
    %5 = stablehlo.constant dense<0.000000e+00> : tensor<1x14x14x256xf32>
    %6 = stablehlo.constant dense<0.000000e+00> : tensor<1x14x14x1024xf32>
    %7 = stablehlo.constant dense<0.000000e+00> : tensor<1x7x7x512xf32>
    %8 = stablehlo.constant dense<0.000000e+00> : tensor<1x7x7x2048xf32>
    %9 = stablehlo.constant dense<4.900000e+01> : tensor<1x2048xf32>
    %10 = stablehlo.constant dense<0xFF800000> : tensor<f32>
    %11 = stablehlo.constant dense<0.000000e+00> : tensor<f32>
    %12 = util.global.load.indirect %ptr___iree_flow___sm_node198__m.layer-3.moving_variance : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %13 = util.global.load.indirect %ptr___iree_flow___sm_node197__m.layer-3.moving_mean : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %14 = util.global.load.indirect %ptr___iree_flow___sm_node196__m.layer-3.beta : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %15 = util.global.load.indirect %ptr___iree_flow___sm_node195__m.layer-3.gamma : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %16 = util.global.load.indirect %ptr___iree_flow___sm_node189__m.layer-2.bias : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %17 = util.global.load.indirect %ptr___iree_flow___sm_node188__m.layer-2.kernel : !util.ptr<tensor<7x7x3x64xf32>> -> tensor<7x7x3x64xf32>
    %18 = util.global.load.indirect %ptr___iree_flow___sm_node269__m.layer-15.moving_variance : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %19 = util.global.load.indirect %ptr___iree_flow___sm_node268__m.layer-15.moving_mean : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %20 = util.global.load.indirect %ptr___iree_flow___sm_node267__m.layer-15.beta : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %21 = util.global.load.indirect %ptr___iree_flow___sm_node266__m.layer-15.gamma : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %22 = util.global.load.indirect %ptr___iree_flow___sm_node254__m.layer-13.bias : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %23 = util.global.load.indirect %ptr___iree_flow___sm_node253__m.layer-13.kernel : !util.ptr<tensor<1x1x64x256xf32>> -> tensor<1x1x64x256xf32>
    %24 = util.global.load.indirect %ptr___iree_flow___sm_node225__m.layer-8.moving_variance : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %25 = util.global.load.indirect %ptr___iree_flow___sm_node224__m.layer-8.moving_mean : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %26 = util.global.load.indirect %ptr___iree_flow___sm_node223__m.layer-8.beta : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %27 = util.global.load.indirect %ptr___iree_flow___sm_node222__m.layer-8.gamma : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %28 = util.global.load.indirect %ptr___iree_flow___sm_node216__m.layer-7.bias : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %29 = util.global.load.indirect %ptr___iree_flow___sm_node215__m.layer-7.kernel : !util.ptr<tensor<1x1x64x64xf32>> -> tensor<1x1x64x64xf32>
    %30 = util.global.load.indirect %ptr___iree_flow___sm_node244__m.layer-11.moving_variance : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %31 = util.global.load.indirect %ptr___iree_flow___sm_node243__m.layer-11.moving_mean : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %32 = util.global.load.indirect %ptr___iree_flow___sm_node242__m.layer-11.beta : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %33 = util.global.load.indirect %ptr___iree_flow___sm_node241__m.layer-11.gamma : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %34 = util.global.load.indirect %ptr___iree_flow___sm_node235__m.layer-10.bias : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %35 = util.global.load.indirect %ptr___iree_flow___sm_node234__m.layer-10.kernel : !util.ptr<tensor<3x3x64x64xf32>> -> tensor<3x3x64x64xf32>
    %36 = util.global.load.indirect %ptr___iree_flow___sm_node278__m.layer-16.moving_variance : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %37 = util.global.load.indirect %ptr___iree_flow___sm_node277__m.layer-16.moving_mean : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %38 = util.global.load.indirect %ptr___iree_flow___sm_node276__m.layer-16.beta : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %39 = util.global.load.indirect %ptr___iree_flow___sm_node275__m.layer-16.gamma : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %40 = util.global.load.indirect %ptr___iree_flow___sm_node260__m.layer-14.bias : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %41 = util.global.load.indirect %ptr___iree_flow___sm_node259__m.layer-14.kernel : !util.ptr<tensor<1x1x64x256xf32>> -> tensor<1x1x64x256xf32>
    %42 = util.global.load.indirect %ptr___iree_flow___sm_node301__m.layer-20.moving_variance : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %43 = util.global.load.indirect %ptr___iree_flow___sm_node300__m.layer-20.moving_mean : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %44 = util.global.load.indirect %ptr___iree_flow___sm_node299__m.layer-20.beta : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %45 = util.global.load.indirect %ptr___iree_flow___sm_node298__m.layer-20.gamma : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %46 = util.global.load.indirect %ptr___iree_flow___sm_node292__m.layer-19.bias : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %47 = util.global.load.indirect %ptr___iree_flow___sm_node291__m.layer-19.kernel : !util.ptr<tensor<1x1x256x64xf32>> -> tensor<1x1x256x64xf32>
    %48 = util.global.load.indirect %ptr___iree_flow___sm_node320__m.layer-23.moving_variance : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %49 = util.global.load.indirect %ptr___iree_flow___sm_node319__m.layer-23.moving_mean : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %50 = util.global.load.indirect %ptr___iree_flow___sm_node318__m.layer-23.beta : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %51 = util.global.load.indirect %ptr___iree_flow___sm_node317__m.layer-23.gamma : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %52 = util.global.load.indirect %ptr___iree_flow___sm_node311__m.layer-22.bias : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %53 = util.global.load.indirect %ptr___iree_flow___sm_node310__m.layer-22.kernel : !util.ptr<tensor<3x3x64x64xf32>> -> tensor<3x3x64x64xf32>
    %54 = util.global.load.indirect %ptr___iree_flow___sm_node339__m.layer-26.moving_variance : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %55 = util.global.load.indirect %ptr___iree_flow___sm_node338__m.layer-26.moving_mean : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %56 = util.global.load.indirect %ptr___iree_flow___sm_node337__m.layer-26.beta : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %57 = util.global.load.indirect %ptr___iree_flow___sm_node336__m.layer-26.gamma : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %58 = util.global.load.indirect %ptr___iree_flow___sm_node330__m.layer-25.bias : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %59 = util.global.load.indirect %ptr___iree_flow___sm_node329__m.layer-25.kernel : !util.ptr<tensor<1x1x64x256xf32>> -> tensor<1x1x64x256xf32>
    %60 = util.global.load.indirect %ptr___iree_flow___sm_node362__m.layer-30.moving_variance : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %61 = util.global.load.indirect %ptr___iree_flow___sm_node361__m.layer-30.moving_mean : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %62 = util.global.load.indirect %ptr___iree_flow___sm_node360__m.layer-30.beta : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %63 = util.global.load.indirect %ptr___iree_flow___sm_node359__m.layer-30.gamma : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %64 = util.global.load.indirect %ptr___iree_flow___sm_node353__m.layer-29.bias : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %65 = util.global.load.indirect %ptr___iree_flow___sm_node352__m.layer-29.kernel : !util.ptr<tensor<1x1x256x64xf32>> -> tensor<1x1x256x64xf32>
    %66 = util.global.load.indirect %ptr___iree_flow___sm_node381__m.layer-33.moving_variance : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %67 = util.global.load.indirect %ptr___iree_flow___sm_node380__m.layer-33.moving_mean : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %68 = util.global.load.indirect %ptr___iree_flow___sm_node379__m.layer-33.beta : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %69 = util.global.load.indirect %ptr___iree_flow___sm_node378__m.layer-33.gamma : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %70 = util.global.load.indirect %ptr___iree_flow___sm_node372__m.layer-32.bias : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
    %71 = util.global.load.indirect %ptr___iree_flow___sm_node371__m.layer-32.kernel : !util.ptr<tensor<3x3x64x64xf32>> -> tensor<3x3x64x64xf32>
    %72 = util.global.load.indirect %ptr___iree_flow___sm_node400__m.layer-36.moving_variance : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %73 = util.global.load.indirect %ptr___iree_flow___sm_node399__m.layer-36.moving_mean : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %74 = util.global.load.indirect %ptr___iree_flow___sm_node398__m.layer-36.beta : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %75 = util.global.load.indirect %ptr___iree_flow___sm_node397__m.layer-36.gamma : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %76 = util.global.load.indirect %ptr___iree_flow___sm_node391__m.layer-35.bias : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %77 = util.global.load.indirect %ptr___iree_flow___sm_node390__m.layer-35.kernel : !util.ptr<tensor<1x1x64x256xf32>> -> tensor<1x1x64x256xf32>
    %78 = util.global.load.indirect %ptr___iree_flow___sm_node467__m.layer-47.moving_variance : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %79 = util.global.load.indirect %ptr___iree_flow___sm_node466__m.layer-47.moving_mean : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %80 = util.global.load.indirect %ptr___iree_flow___sm_node465__m.layer-47.beta : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %81 = util.global.load.indirect %ptr___iree_flow___sm_node464__m.layer-47.gamma : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %82 = util.global.load.indirect %ptr___iree_flow___sm_node452__m.layer-45.bias : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %83 = util.global.load.indirect %ptr___iree_flow___sm_node451__m.layer-45.kernel : !util.ptr<tensor<1x1x256x512xf32>> -> tensor<1x1x256x512xf32>
    %84 = util.global.load.indirect %ptr___iree_flow___sm_node423__m.layer-40.moving_variance : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %85 = util.global.load.indirect %ptr___iree_flow___sm_node422__m.layer-40.moving_mean : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %86 = util.global.load.indirect %ptr___iree_flow___sm_node421__m.layer-40.beta : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %87 = util.global.load.indirect %ptr___iree_flow___sm_node420__m.layer-40.gamma : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %88 = util.global.load.indirect %ptr___iree_flow___sm_node414__m.layer-39.bias : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %89 = util.global.load.indirect %ptr___iree_flow___sm_node413__m.layer-39.kernel : !util.ptr<tensor<1x1x256x128xf32>> -> tensor<1x1x256x128xf32>
    %90 = util.global.load.indirect %ptr___iree_flow___sm_node442__m.layer-43.moving_variance : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %91 = util.global.load.indirect %ptr___iree_flow___sm_node441__m.layer-43.moving_mean : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %92 = util.global.load.indirect %ptr___iree_flow___sm_node440__m.layer-43.beta : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %93 = util.global.load.indirect %ptr___iree_flow___sm_node439__m.layer-43.gamma : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %94 = util.global.load.indirect %ptr___iree_flow___sm_node433__m.layer-42.bias : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %95 = util.global.load.indirect %ptr___iree_flow___sm_node432__m.layer-42.kernel : !util.ptr<tensor<3x3x128x128xf32>> -> tensor<3x3x128x128xf32>
    %96 = util.global.load.indirect %ptr___iree_flow___sm_node476__m.layer-48.moving_variance : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %97 = util.global.load.indirect %ptr___iree_flow___sm_node475__m.layer-48.moving_mean : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %98 = util.global.load.indirect %ptr___iree_flow___sm_node474__m.layer-48.beta : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %99 = util.global.load.indirect %ptr___iree_flow___sm_node473__m.layer-48.gamma : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %100 = util.global.load.indirect %ptr___iree_flow___sm_node458__m.layer-46.bias : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %101 = util.global.load.indirect %ptr___iree_flow___sm_node457__m.layer-46.kernel : !util.ptr<tensor<1x1x128x512xf32>> -> tensor<1x1x128x512xf32>
    %102 = util.global.load.indirect %ptr___iree_flow___sm_node499__m.layer-52.moving_variance : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %103 = util.global.load.indirect %ptr___iree_flow___sm_node498__m.layer-52.moving_mean : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %104 = util.global.load.indirect %ptr___iree_flow___sm_node497__m.layer-52.beta : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %105 = util.global.load.indirect %ptr___iree_flow___sm_node496__m.layer-52.gamma : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %106 = util.global.load.indirect %ptr___iree_flow___sm_node490__m.layer-51.bias : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %107 = util.global.load.indirect %ptr___iree_flow___sm_node489__m.layer-51.kernel : !util.ptr<tensor<1x1x512x128xf32>> -> tensor<1x1x512x128xf32>
    %108 = util.global.load.indirect %ptr___iree_flow___sm_node518__m.layer-55.moving_variance : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %109 = util.global.load.indirect %ptr___iree_flow___sm_node517__m.layer-55.moving_mean : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %110 = util.global.load.indirect %ptr___iree_flow___sm_node516__m.layer-55.beta : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %111 = util.global.load.indirect %ptr___iree_flow___sm_node515__m.layer-55.gamma : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %112 = util.global.load.indirect %ptr___iree_flow___sm_node509__m.layer-54.bias : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %113 = util.global.load.indirect %ptr___iree_flow___sm_node508__m.layer-54.kernel : !util.ptr<tensor<3x3x128x128xf32>> -> tensor<3x3x128x128xf32>
    %114 = util.global.load.indirect %ptr___iree_flow___sm_node537__m.layer-58.moving_variance : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %115 = util.global.load.indirect %ptr___iree_flow___sm_node536__m.layer-58.moving_mean : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %116 = util.global.load.indirect %ptr___iree_flow___sm_node535__m.layer-58.beta : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %117 = util.global.load.indirect %ptr___iree_flow___sm_node534__m.layer-58.gamma : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %118 = util.global.load.indirect %ptr___iree_flow___sm_node528__m.layer-57.bias : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %119 = util.global.load.indirect %ptr___iree_flow___sm_node527__m.layer-57.kernel : !util.ptr<tensor<1x1x128x512xf32>> -> tensor<1x1x128x512xf32>
    %120 = util.global.load.indirect %ptr___iree_flow___sm_node560__m.layer-62.moving_variance : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %121 = util.global.load.indirect %ptr___iree_flow___sm_node559__m.layer-62.moving_mean : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %122 = util.global.load.indirect %ptr___iree_flow___sm_node558__m.layer-62.beta : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %123 = util.global.load.indirect %ptr___iree_flow___sm_node557__m.layer-62.gamma : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %124 = util.global.load.indirect %ptr___iree_flow___sm_node551__m.layer-61.bias : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %125 = util.global.load.indirect %ptr___iree_flow___sm_node550__m.layer-61.kernel : !util.ptr<tensor<1x1x512x128xf32>> -> tensor<1x1x512x128xf32>
    %126 = util.global.load.indirect %ptr___iree_flow___sm_node579__m.layer-65.moving_variance : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %127 = util.global.load.indirect %ptr___iree_flow___sm_node578__m.layer-65.moving_mean : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %128 = util.global.load.indirect %ptr___iree_flow___sm_node577__m.layer-65.beta : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %129 = util.global.load.indirect %ptr___iree_flow___sm_node576__m.layer-65.gamma : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %130 = util.global.load.indirect %ptr___iree_flow___sm_node570__m.layer-64.bias : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %131 = util.global.load.indirect %ptr___iree_flow___sm_node569__m.layer-64.kernel : !util.ptr<tensor<3x3x128x128xf32>> -> tensor<3x3x128x128xf32>
    %132 = util.global.load.indirect %ptr___iree_flow___sm_node598__m.layer-68.moving_variance : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %133 = util.global.load.indirect %ptr___iree_flow___sm_node597__m.layer-68.moving_mean : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %134 = util.global.load.indirect %ptr___iree_flow___sm_node596__m.layer-68.beta : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %135 = util.global.load.indirect %ptr___iree_flow___sm_node595__m.layer-68.gamma : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %136 = util.global.load.indirect %ptr___iree_flow___sm_node589__m.layer-67.bias : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %137 = util.global.load.indirect %ptr___iree_flow___sm_node588__m.layer-67.kernel : !util.ptr<tensor<1x1x128x512xf32>> -> tensor<1x1x128x512xf32>
    %138 = util.global.load.indirect %ptr___iree_flow___sm_node621__m.layer-72.moving_variance : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %139 = util.global.load.indirect %ptr___iree_flow___sm_node620__m.layer-72.moving_mean : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %140 = util.global.load.indirect %ptr___iree_flow___sm_node619__m.layer-72.beta : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %141 = util.global.load.indirect %ptr___iree_flow___sm_node618__m.layer-72.gamma : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %142 = util.global.load.indirect %ptr___iree_flow___sm_node612__m.layer-71.bias : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %143 = util.global.load.indirect %ptr___iree_flow___sm_node611__m.layer-71.kernel : !util.ptr<tensor<1x1x512x128xf32>> -> tensor<1x1x512x128xf32>
    %144 = util.global.load.indirect %ptr___iree_flow___sm_node640__m.layer-75.moving_variance : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %145 = util.global.load.indirect %ptr___iree_flow___sm_node639__m.layer-75.moving_mean : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %146 = util.global.load.indirect %ptr___iree_flow___sm_node638__m.layer-75.beta : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %147 = util.global.load.indirect %ptr___iree_flow___sm_node637__m.layer-75.gamma : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %148 = util.global.load.indirect %ptr___iree_flow___sm_node631__m.layer-74.bias : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
    %149 = util.global.load.indirect %ptr___iree_flow___sm_node630__m.layer-74.kernel : !util.ptr<tensor<3x3x128x128xf32>> -> tensor<3x3x128x128xf32>
    %150 = util.global.load.indirect %ptr___iree_flow___sm_node659__m.layer-78.moving_variance : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %151 = util.global.load.indirect %ptr___iree_flow___sm_node658__m.layer-78.moving_mean : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %152 = util.global.load.indirect %ptr___iree_flow___sm_node657__m.layer-78.beta : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %153 = util.global.load.indirect %ptr___iree_flow___sm_node656__m.layer-78.gamma : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %154 = util.global.load.indirect %ptr___iree_flow___sm_node650__m.layer-77.bias : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %155 = util.global.load.indirect %ptr___iree_flow___sm_node649__m.layer-77.kernel : !util.ptr<tensor<1x1x128x512xf32>> -> tensor<1x1x128x512xf32>
    %156 = util.global.load.indirect %ptr___iree_flow___sm_node726__m.layer-89.moving_variance : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %157 = util.global.load.indirect %ptr___iree_flow___sm_node725__m.layer-89.moving_mean : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %158 = util.global.load.indirect %ptr___iree_flow___sm_node724__m.layer-89.beta : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %159 = util.global.load.indirect %ptr___iree_flow___sm_node723__m.layer-89.gamma : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %160 = util.global.load.indirect %ptr___iree_flow___sm_node711__m.layer-87.bias : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %161 = util.global.load.indirect %ptr___iree_flow___sm_node710__m.layer-87.kernel : !util.ptr<tensor<1x1x512x1024xf32>> -> tensor<1x1x512x1024xf32>
    %162 = util.global.load.indirect %ptr___iree_flow___sm_node682__m.layer-82.moving_variance : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %163 = util.global.load.indirect %ptr___iree_flow___sm_node681__m.layer-82.moving_mean : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %164 = util.global.load.indirect %ptr___iree_flow___sm_node680__m.layer-82.beta : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %165 = util.global.load.indirect %ptr___iree_flow___sm_node679__m.layer-82.gamma : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %166 = util.global.load.indirect %ptr___iree_flow___sm_node673__m.layer-81.bias : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %167 = util.global.load.indirect %ptr___iree_flow___sm_node672__m.layer-81.kernel : !util.ptr<tensor<1x1x512x256xf32>> -> tensor<1x1x512x256xf32>
    %168 = util.global.load.indirect %ptr___iree_flow___sm_node701__m.layer-85.moving_variance : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %169 = util.global.load.indirect %ptr___iree_flow___sm_node700__m.layer-85.moving_mean : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %170 = util.global.load.indirect %ptr___iree_flow___sm_node699__m.layer-85.beta : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %171 = util.global.load.indirect %ptr___iree_flow___sm_node698__m.layer-85.gamma : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %172 = util.global.load.indirect %ptr___iree_flow___sm_node692__m.layer-84.bias : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %173 = util.global.load.indirect %ptr___iree_flow___sm_node691__m.layer-84.kernel : !util.ptr<tensor<3x3x256x256xf32>> -> tensor<3x3x256x256xf32>
    %174 = util.global.load.indirect %ptr___iree_flow___sm_node735__m.layer-90.moving_variance : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %175 = util.global.load.indirect %ptr___iree_flow___sm_node734__m.layer-90.moving_mean : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %176 = util.global.load.indirect %ptr___iree_flow___sm_node733__m.layer-90.beta : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %177 = util.global.load.indirect %ptr___iree_flow___sm_node732__m.layer-90.gamma : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %178 = util.global.load.indirect %ptr___iree_flow___sm_node717__m.layer-88.bias : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %179 = util.global.load.indirect %ptr___iree_flow___sm_node716__m.layer-88.kernel : !util.ptr<tensor<1x1x256x1024xf32>> -> tensor<1x1x256x1024xf32>
    %180 = util.global.load.indirect %ptr___iree_flow___sm_node758__m.layer-94.moving_variance : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %181 = util.global.load.indirect %ptr___iree_flow___sm_node757__m.layer-94.moving_mean : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %182 = util.global.load.indirect %ptr___iree_flow___sm_node756__m.layer-94.beta : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %183 = util.global.load.indirect %ptr___iree_flow___sm_node755__m.layer-94.gamma : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %184 = util.global.load.indirect %ptr___iree_flow___sm_node749__m.layer-93.bias : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %185 = util.global.load.indirect %ptr___iree_flow___sm_node748__m.layer-93.kernel : !util.ptr<tensor<1x1x1024x256xf32>> -> tensor<1x1x1024x256xf32>
    %186 = util.global.load.indirect %ptr___iree_flow___sm_node777__m.layer-97.moving_variance : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %187 = util.global.load.indirect %ptr___iree_flow___sm_node776__m.layer-97.moving_mean : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %188 = util.global.load.indirect %ptr___iree_flow___sm_node775__m.layer-97.beta : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %189 = util.global.load.indirect %ptr___iree_flow___sm_node774__m.layer-97.gamma : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %190 = util.global.load.indirect %ptr___iree_flow___sm_node768__m.layer-96.bias : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %191 = util.global.load.indirect %ptr___iree_flow___sm_node767__m.layer-96.kernel : !util.ptr<tensor<3x3x256x256xf32>> -> tensor<3x3x256x256xf32>
    %192 = util.global.load.indirect %ptr___iree_flow___sm_node796__m.layer-100.moving_variance : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %193 = util.global.load.indirect %ptr___iree_flow___sm_node795__m.layer-100.moving_mean : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %194 = util.global.load.indirect %ptr___iree_flow___sm_node794__m.layer-100.beta : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %195 = util.global.load.indirect %ptr___iree_flow___sm_node793__m.layer-100.gamma : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %196 = util.global.load.indirect %ptr___iree_flow___sm_node787__m.layer-99.bias : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %197 = util.global.load.indirect %ptr___iree_flow___sm_node786__m.layer-99.kernel : !util.ptr<tensor<1x1x256x1024xf32>> -> tensor<1x1x256x1024xf32>
    %198 = util.global.load.indirect %ptr___iree_flow___sm_node819__m.layer-104.moving_variance : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %199 = util.global.load.indirect %ptr___iree_flow___sm_node818__m.layer-104.moving_mean : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %200 = util.global.load.indirect %ptr___iree_flow___sm_node817__m.layer-104.beta : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %201 = util.global.load.indirect %ptr___iree_flow___sm_node816__m.layer-104.gamma : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %202 = util.global.load.indirect %ptr___iree_flow___sm_node810__m.layer-103.bias : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %203 = util.global.load.indirect %ptr___iree_flow___sm_node809__m.layer-103.kernel : !util.ptr<tensor<1x1x1024x256xf32>> -> tensor<1x1x1024x256xf32>
    %204 = util.global.load.indirect %ptr___iree_flow___sm_node838__m.layer-107.moving_variance : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %205 = util.global.load.indirect %ptr___iree_flow___sm_node837__m.layer-107.moving_mean : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %206 = util.global.load.indirect %ptr___iree_flow___sm_node836__m.layer-107.beta : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %207 = util.global.load.indirect %ptr___iree_flow___sm_node835__m.layer-107.gamma : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %208 = util.global.load.indirect %ptr___iree_flow___sm_node829__m.layer-106.bias : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %209 = util.global.load.indirect %ptr___iree_flow___sm_node828__m.layer-106.kernel : !util.ptr<tensor<3x3x256x256xf32>> -> tensor<3x3x256x256xf32>
    %210 = util.global.load.indirect %ptr___iree_flow___sm_node857__m.layer-110.moving_variance : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %211 = util.global.load.indirect %ptr___iree_flow___sm_node856__m.layer-110.moving_mean : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %212 = util.global.load.indirect %ptr___iree_flow___sm_node855__m.layer-110.beta : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %213 = util.global.load.indirect %ptr___iree_flow___sm_node854__m.layer-110.gamma : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %214 = util.global.load.indirect %ptr___iree_flow___sm_node848__m.layer-109.bias : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %215 = util.global.load.indirect %ptr___iree_flow___sm_node847__m.layer-109.kernel : !util.ptr<tensor<1x1x256x1024xf32>> -> tensor<1x1x256x1024xf32>
    %216 = util.global.load.indirect %ptr___iree_flow___sm_node880__m.layer-114.moving_variance : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %217 = util.global.load.indirect %ptr___iree_flow___sm_node879__m.layer-114.moving_mean : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %218 = util.global.load.indirect %ptr___iree_flow___sm_node878__m.layer-114.beta : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %219 = util.global.load.indirect %ptr___iree_flow___sm_node877__m.layer-114.gamma : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %220 = util.global.load.indirect %ptr___iree_flow___sm_node871__m.layer-113.bias : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %221 = util.global.load.indirect %ptr___iree_flow___sm_node870__m.layer-113.kernel : !util.ptr<tensor<1x1x1024x256xf32>> -> tensor<1x1x1024x256xf32>
    %222 = util.global.load.indirect %ptr___iree_flow___sm_node899__m.layer-117.moving_variance : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %223 = util.global.load.indirect %ptr___iree_flow___sm_node898__m.layer-117.moving_mean : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %224 = util.global.load.indirect %ptr___iree_flow___sm_node897__m.layer-117.beta : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %225 = util.global.load.indirect %ptr___iree_flow___sm_node896__m.layer-117.gamma : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %226 = util.global.load.indirect %ptr___iree_flow___sm_node890__m.layer-116.bias : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %227 = util.global.load.indirect %ptr___iree_flow___sm_node889__m.layer-116.kernel : !util.ptr<tensor<3x3x256x256xf32>> -> tensor<3x3x256x256xf32>
    %228 = util.global.load.indirect %ptr___iree_flow___sm_node918__m.layer-120.moving_variance : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %229 = util.global.load.indirect %ptr___iree_flow___sm_node917__m.layer-120.moving_mean : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %230 = util.global.load.indirect %ptr___iree_flow___sm_node916__m.layer-120.beta : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %231 = util.global.load.indirect %ptr___iree_flow___sm_node915__m.layer-120.gamma : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %232 = util.global.load.indirect %ptr___iree_flow___sm_node909__m.layer-119.bias : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %233 = util.global.load.indirect %ptr___iree_flow___sm_node908__m.layer-119.kernel : !util.ptr<tensor<1x1x256x1024xf32>> -> tensor<1x1x256x1024xf32>
    %234 = util.global.load.indirect %ptr___iree_flow___sm_node941__m.layer-124.moving_variance : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %235 = util.global.load.indirect %ptr___iree_flow___sm_node940__m.layer-124.moving_mean : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %236 = util.global.load.indirect %ptr___iree_flow___sm_node939__m.layer-124.beta : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %237 = util.global.load.indirect %ptr___iree_flow___sm_node938__m.layer-124.gamma : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %238 = util.global.load.indirect %ptr___iree_flow___sm_node932__m.layer-123.bias : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %239 = util.global.load.indirect %ptr___iree_flow___sm_node931__m.layer-123.kernel : !util.ptr<tensor<1x1x1024x256xf32>> -> tensor<1x1x1024x256xf32>
    %240 = util.global.load.indirect %ptr___iree_flow___sm_node960__m.layer-127.moving_variance : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %241 = util.global.load.indirect %ptr___iree_flow___sm_node959__m.layer-127.moving_mean : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %242 = util.global.load.indirect %ptr___iree_flow___sm_node958__m.layer-127.beta : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %243 = util.global.load.indirect %ptr___iree_flow___sm_node957__m.layer-127.gamma : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %244 = util.global.load.indirect %ptr___iree_flow___sm_node951__m.layer-126.bias : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %245 = util.global.load.indirect %ptr___iree_flow___sm_node950__m.layer-126.kernel : !util.ptr<tensor<3x3x256x256xf32>> -> tensor<3x3x256x256xf32>
    %246 = util.global.load.indirect %ptr___iree_flow___sm_node979__m.layer-130.moving_variance : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %247 = util.global.load.indirect %ptr___iree_flow___sm_node978__m.layer-130.moving_mean : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %248 = util.global.load.indirect %ptr___iree_flow___sm_node977__m.layer-130.beta : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %249 = util.global.load.indirect %ptr___iree_flow___sm_node976__m.layer-130.gamma : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %250 = util.global.load.indirect %ptr___iree_flow___sm_node970__m.layer-129.bias : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %251 = util.global.load.indirect %ptr___iree_flow___sm_node969__m.layer-129.kernel : !util.ptr<tensor<1x1x256x1024xf32>> -> tensor<1x1x256x1024xf32>
    %252 = util.global.load.indirect %ptr___iree_flow___sm_node1002__m.layer-134.moving_variance : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %253 = util.global.load.indirect %ptr___iree_flow___sm_node1001__m.layer-134.moving_mean : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %254 = util.global.load.indirect %ptr___iree_flow___sm_node1000__m.layer-134.beta : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %255 = util.global.load.indirect %ptr___iree_flow___sm_node999__m.layer-134.gamma : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %256 = util.global.load.indirect %ptr___iree_flow___sm_node993__m.layer-133.bias : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %257 = util.global.load.indirect %ptr___iree_flow___sm_node992__m.layer-133.kernel : !util.ptr<tensor<1x1x1024x256xf32>> -> tensor<1x1x1024x256xf32>
    %258 = util.global.load.indirect %ptr___iree_flow___sm_node1021__m.layer-137.moving_variance : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %259 = util.global.load.indirect %ptr___iree_flow___sm_node1020__m.layer-137.moving_mean : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %260 = util.global.load.indirect %ptr___iree_flow___sm_node1019__m.layer-137.beta : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %261 = util.global.load.indirect %ptr___iree_flow___sm_node1018__m.layer-137.gamma : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %262 = util.global.load.indirect %ptr___iree_flow___sm_node1012__m.layer-136.bias : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
    %263 = util.global.load.indirect %ptr___iree_flow___sm_node1011__m.layer-136.kernel : !util.ptr<tensor<3x3x256x256xf32>> -> tensor<3x3x256x256xf32>
    %264 = util.global.load.indirect %ptr___iree_flow___sm_node1040__m.layer-140.moving_variance : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %265 = util.global.load.indirect %ptr___iree_flow___sm_node1039__m.layer-140.moving_mean : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %266 = util.global.load.indirect %ptr___iree_flow___sm_node1038__m.layer-140.beta : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %267 = util.global.load.indirect %ptr___iree_flow___sm_node1037__m.layer-140.gamma : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %268 = util.global.load.indirect %ptr___iree_flow___sm_node1031__m.layer-139.bias : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
    %269 = util.global.load.indirect %ptr___iree_flow___sm_node1030__m.layer-139.kernel : !util.ptr<tensor<1x1x256x1024xf32>> -> tensor<1x1x256x1024xf32>
    %270 = util.global.load.indirect %ptr___iree_flow___sm_node1107__m.layer-151.moving_variance : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
    %271 = util.global.load.indirect %ptr___iree_flow___sm_node1106__m.layer-151.moving_mean : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
    %272 = util.global.load.indirect %ptr___iree_flow___sm_node1105__m.layer-151.beta : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
    %273 = util.global.load.indirect %ptr___iree_flow___sm_node1104__m.layer-151.gamma : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
    %274 = util.global.load.indirect %ptr___iree_flow___sm_node1092__m.layer-149.bias : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
    %275 = util.global.load.indirect %ptr___iree_flow___sm_node1091__m.layer-149.kernel : !util.ptr<tensor<1x1x1024x2048xf32>> -> tensor<1x1x1024x2048xf32>
    %276 = util.global.load.indirect %ptr___iree_flow___sm_node1063__m.layer-144.moving_variance : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %277 = util.global.load.indirect %ptr___iree_flow___sm_node1062__m.layer-144.moving_mean : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %278 = util.global.load.indirect %ptr___iree_flow___sm_node1061__m.layer-144.beta : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %279 = util.global.load.indirect %ptr___iree_flow___sm_node1060__m.layer-144.gamma : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %280 = util.global.load.indirect %ptr___iree_flow___sm_node1054__m.layer-143.bias : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %281 = util.global.load.indirect %ptr___iree_flow___sm_node1053__m.layer-143.kernel : !util.ptr<tensor<1x1x1024x512xf32>> -> tensor<1x1x1024x512xf32>
    %282 = util.global.load.indirect %ptr___iree_flow___sm_node1082__m.layer-147.moving_variance : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %283 = util.global.load.indirect %ptr___iree_flow___sm_node1081__m.layer-147.moving_mean : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %284 = util.global.load.indirect %ptr___iree_flow___sm_node1080__m.layer-147.beta : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %285 = util.global.load.indirect %ptr___iree_flow___sm_node1079__m.layer-147.gamma : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %286 = util.global.load.indirect %ptr___iree_flow___sm_node1073__m.layer-146.bias : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %287 = util.global.load.indirect %ptr___iree_flow___sm_node1072__m.layer-146.kernel : !util.ptr<tensor<3x3x512x512xf32>> -> tensor<3x3x512x512xf32>
    %288 = util.global.load.indirect %ptr___iree_flow___sm_node1116__m.layer-152.moving_variance : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
    %289 = util.global.load.indirect %ptr___iree_flow___sm_node1115__m.layer-152.moving_mean : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
    %290 = util.global.load.indirect %ptr___iree_flow___sm_node1114__m.layer-152.beta : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
    %291 = util.global.load.indirect %ptr___iree_flow___sm_node1113__m.layer-152.gamma : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
    %292 = util.global.load.indirect %ptr___iree_flow___sm_node1098__m.layer-150.bias : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
    %293 = util.global.load.indirect %ptr___iree_flow___sm_node1097__m.layer-150.kernel : !util.ptr<tensor<1x1x512x2048xf32>> -> tensor<1x1x512x2048xf32>
    %294 = util.global.load.indirect %ptr___iree_flow___sm_node1139__m.layer-156.moving_variance : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %295 = util.global.load.indirect %ptr___iree_flow___sm_node1138__m.layer-156.moving_mean : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %296 = util.global.load.indirect %ptr___iree_flow___sm_node1137__m.layer-156.beta : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %297 = util.global.load.indirect %ptr___iree_flow___sm_node1136__m.layer-156.gamma : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %298 = util.global.load.indirect %ptr___iree_flow___sm_node1130__m.layer-155.bias : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %299 = util.global.load.indirect %ptr___iree_flow___sm_node1129__m.layer-155.kernel : !util.ptr<tensor<1x1x2048x512xf32>> -> tensor<1x1x2048x512xf32>
    %300 = util.global.load.indirect %ptr___iree_flow___sm_node1158__m.layer-159.moving_variance : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %301 = util.global.load.indirect %ptr___iree_flow___sm_node1157__m.layer-159.moving_mean : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %302 = util.global.load.indirect %ptr___iree_flow___sm_node1156__m.layer-159.beta : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %303 = util.global.load.indirect %ptr___iree_flow___sm_node1155__m.layer-159.gamma : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %304 = util.global.load.indirect %ptr___iree_flow___sm_node1149__m.layer-158.bias : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %305 = util.global.load.indirect %ptr___iree_flow___sm_node1148__m.layer-158.kernel : !util.ptr<tensor<3x3x512x512xf32>> -> tensor<3x3x512x512xf32>
    %306 = util.global.load.indirect %ptr___iree_flow___sm_node1177__m.layer-162.moving_variance : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
    %307 = util.global.load.indirect %ptr___iree_flow___sm_node1176__m.layer-162.moving_mean : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
    %308 = util.global.load.indirect %ptr___iree_flow___sm_node1175__m.layer-162.beta : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
    %309 = util.global.load.indirect %ptr___iree_flow___sm_node1174__m.layer-162.gamma : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
    %310 = util.global.load.indirect %ptr___iree_flow___sm_node1168__m.layer-161.bias : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
    %311 = util.global.load.indirect %ptr___iree_flow___sm_node1167__m.layer-161.kernel : !util.ptr<tensor<1x1x512x2048xf32>> -> tensor<1x1x512x2048xf32>
    %312 = util.global.load.indirect %ptr___iree_flow___sm_node1200__m.layer-166.moving_variance : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %313 = util.global.load.indirect %ptr___iree_flow___sm_node1199__m.layer-166.moving_mean : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %314 = util.global.load.indirect %ptr___iree_flow___sm_node1198__m.layer-166.beta : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %315 = util.global.load.indirect %ptr___iree_flow___sm_node1197__m.layer-166.gamma : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %316 = util.global.load.indirect %ptr___iree_flow___sm_node1191__m.layer-165.bias : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %317 = util.global.load.indirect %ptr___iree_flow___sm_node1190__m.layer-165.kernel : !util.ptr<tensor<1x1x2048x512xf32>> -> tensor<1x1x2048x512xf32>
    %318 = util.global.load.indirect %ptr___iree_flow___sm_node1219__m.layer-169.moving_variance : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %319 = util.global.load.indirect %ptr___iree_flow___sm_node1218__m.layer-169.moving_mean : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %320 = util.global.load.indirect %ptr___iree_flow___sm_node1217__m.layer-169.beta : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %321 = util.global.load.indirect %ptr___iree_flow___sm_node1216__m.layer-169.gamma : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %322 = util.global.load.indirect %ptr___iree_flow___sm_node1210__m.layer-168.bias : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
    %323 = util.global.load.indirect %ptr___iree_flow___sm_node1209__m.layer-168.kernel : !util.ptr<tensor<3x3x512x512xf32>> -> tensor<3x3x512x512xf32>
    %324 = util.global.load.indirect %ptr___iree_flow___sm_node1238__m.layer-172.moving_variance : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
    %325 = util.global.load.indirect %ptr___iree_flow___sm_node1237__m.layer-172.moving_mean : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
    %326 = util.global.load.indirect %ptr___iree_flow___sm_node1236__m.layer-172.beta : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
    %327 = util.global.load.indirect %ptr___iree_flow___sm_node1235__m.layer-172.gamma : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
    %328 = util.global.load.indirect %ptr___iree_flow___sm_node1229__m.layer-171.bias : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
    %329 = util.global.load.indirect %ptr___iree_flow___sm_node1228__m.layer-171.kernel : !util.ptr<tensor<1x1x512x2048xf32>> -> tensor<1x1x512x2048xf32>
    %330 = util.global.load.indirect %ptr___iree_flow___sm_node1256__m.layer-176.bias : !util.ptr<tensor<1000xf32>> -> tensor<1000xf32>
    %331 = util.global.load.indirect %ptr___iree_flow___sm_node1255__m.layer-176.kernel : !util.ptr<tensor<2048x1000xf32>> -> tensor<2048x1000xf32>
    %332 = stablehlo.pad %arg0, %11, low = [0, 3, 3, 0], high = [0, 3, 3, 0], interior = [0, 0, 0, 0] : (tensor<1x224x224x3xf32>, tensor<f32>) -> tensor<1x230x230x3xf32>
    %333 = stablehlo.convolution(%332, %17) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [2, 2], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x230x230x3xf32>, tensor<7x7x3x64xf32>) -> tensor<1x112x112x64xf32>
    %334 = stablehlo.broadcast_in_dim %16, dims = [3] : (tensor<64xf32>) -> tensor<1x112x112x64xf32>
    %335 = stablehlo.add %333, %334 : tensor<1x112x112x64xf32>
    %336 = "stablehlo.batch_norm_inference"(%335, %15, %14, %13, %12) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x112x112x64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>) -> tensor<1x112x112x64xf32>
    %337 = stablehlo.maximum %336, %0 : tensor<1x112x112x64xf32>
    %338 = stablehlo.pad %337, %11, low = [0, 1, 1, 0], high = [0, 1, 1, 0], interior = [0, 0, 0, 0] : (tensor<1x112x112x64xf32>, tensor<f32>) -> tensor<1x114x114x64xf32>
    %339 = "stablehlo.reduce_window"(%338, %10) ({
    ^bb0(%arg1: tensor<f32>, %arg2: tensor<f32>):
      %624 = stablehlo.maximum %arg1, %arg2 : tensor<f32>
      stablehlo.return %624 : tensor<f32>
    }) {window_dimensions = dense<[1, 3, 3, 1]> : tensor<4xi64>, window_strides = dense<[1, 2, 2, 1]> : tensor<4xi64>} : (tensor<1x114x114x64xf32>, tensor<f32>) -> tensor<1x56x56x64xf32>
    %340 = stablehlo.convolution(%339, %23) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x56x56x64xf32>, tensor<1x1x64x256xf32>) -> tensor<1x56x56x256xf32>
    %341 = stablehlo.broadcast_in_dim %22, dims = [3] : (tensor<256xf32>) -> tensor<1x56x56x256xf32>
    %342 = stablehlo.add %340, %341 : tensor<1x56x56x256xf32>
    %343 = "stablehlo.batch_norm_inference"(%342, %21, %20, %19, %18) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x56x56x256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>) -> tensor<1x56x56x256xf32>
    %344 = stablehlo.convolution(%339, %29) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x56x56x64xf32>, tensor<1x1x64x64xf32>) -> tensor<1x56x56x64xf32>
    %345 = stablehlo.broadcast_in_dim %28, dims = [3] : (tensor<64xf32>) -> tensor<1x56x56x64xf32>
    %346 = stablehlo.add %344, %345 : tensor<1x56x56x64xf32>
    %347 = "stablehlo.batch_norm_inference"(%346, %27, %26, %25, %24) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x56x56x64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>) -> tensor<1x56x56x64xf32>
    %348 = stablehlo.maximum %347, %1 : tensor<1x56x56x64xf32>
    %349 = stablehlo.convolution(%348, %35) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[1, 1], [1, 1]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x56x56x64xf32>, tensor<3x3x64x64xf32>) -> tensor<1x56x56x64xf32>
    %350 = stablehlo.broadcast_in_dim %34, dims = [3] : (tensor<64xf32>) -> tensor<1x56x56x64xf32>
    %351 = stablehlo.add %349, %350 : tensor<1x56x56x64xf32>
    %352 = "stablehlo.batch_norm_inference"(%351, %33, %32, %31, %30) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x56x56x64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>) -> tensor<1x56x56x64xf32>
    %353 = stablehlo.maximum %352, %1 : tensor<1x56x56x64xf32>
    %354 = stablehlo.convolution(%353, %41) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x56x56x64xf32>, tensor<1x1x64x256xf32>) -> tensor<1x56x56x256xf32>
    %355 = stablehlo.broadcast_in_dim %40, dims = [3] : (tensor<256xf32>) -> tensor<1x56x56x256xf32>
    %356 = stablehlo.add %354, %355 : tensor<1x56x56x256xf32>
    %357 = "stablehlo.batch_norm_inference"(%356, %39, %38, %37, %36) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x56x56x256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>) -> tensor<1x56x56x256xf32>
    %358 = stablehlo.add %343, %357 : tensor<1x56x56x256xf32>
    %359 = stablehlo.maximum %358, %2 : tensor<1x56x56x256xf32>
    %360 = stablehlo.convolution(%359, %47) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x56x56x256xf32>, tensor<1x1x256x64xf32>) -> tensor<1x56x56x64xf32>
    %361 = stablehlo.broadcast_in_dim %46, dims = [3] : (tensor<64xf32>) -> tensor<1x56x56x64xf32>
    %362 = stablehlo.add %360, %361 : tensor<1x56x56x64xf32>
    %363 = "stablehlo.batch_norm_inference"(%362, %45, %44, %43, %42) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x56x56x64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>) -> tensor<1x56x56x64xf32>
    %364 = stablehlo.maximum %363, %1 : tensor<1x56x56x64xf32>
    %365 = stablehlo.convolution(%364, %53) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[1, 1], [1, 1]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x56x56x64xf32>, tensor<3x3x64x64xf32>) -> tensor<1x56x56x64xf32>
    %366 = stablehlo.broadcast_in_dim %52, dims = [3] : (tensor<64xf32>) -> tensor<1x56x56x64xf32>
    %367 = stablehlo.add %365, %366 : tensor<1x56x56x64xf32>
    %368 = "stablehlo.batch_norm_inference"(%367, %51, %50, %49, %48) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x56x56x64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>) -> tensor<1x56x56x64xf32>
    %369 = stablehlo.maximum %368, %1 : tensor<1x56x56x64xf32>
    %370 = stablehlo.convolution(%369, %59) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x56x56x64xf32>, tensor<1x1x64x256xf32>) -> tensor<1x56x56x256xf32>
    %371 = stablehlo.broadcast_in_dim %58, dims = [3] : (tensor<256xf32>) -> tensor<1x56x56x256xf32>
    %372 = stablehlo.add %370, %371 : tensor<1x56x56x256xf32>
    %373 = "stablehlo.batch_norm_inference"(%372, %57, %56, %55, %54) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x56x56x256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>) -> tensor<1x56x56x256xf32>
    %374 = stablehlo.add %359, %373 : tensor<1x56x56x256xf32>
    %375 = stablehlo.maximum %374, %2 : tensor<1x56x56x256xf32>
    %376 = stablehlo.convolution(%375, %65) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x56x56x256xf32>, tensor<1x1x256x64xf32>) -> tensor<1x56x56x64xf32>
    %377 = stablehlo.broadcast_in_dim %64, dims = [3] : (tensor<64xf32>) -> tensor<1x56x56x64xf32>
    %378 = stablehlo.add %376, %377 : tensor<1x56x56x64xf32>
    %379 = "stablehlo.batch_norm_inference"(%378, %63, %62, %61, %60) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x56x56x64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>) -> tensor<1x56x56x64xf32>
    %380 = stablehlo.maximum %379, %1 : tensor<1x56x56x64xf32>
    %381 = stablehlo.convolution(%380, %71) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[1, 1], [1, 1]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x56x56x64xf32>, tensor<3x3x64x64xf32>) -> tensor<1x56x56x64xf32>
    %382 = stablehlo.broadcast_in_dim %70, dims = [3] : (tensor<64xf32>) -> tensor<1x56x56x64xf32>
    %383 = stablehlo.add %381, %382 : tensor<1x56x56x64xf32>
    %384 = "stablehlo.batch_norm_inference"(%383, %69, %68, %67, %66) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x56x56x64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>) -> tensor<1x56x56x64xf32>
    %385 = stablehlo.maximum %384, %1 : tensor<1x56x56x64xf32>
    %386 = stablehlo.convolution(%385, %77) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x56x56x64xf32>, tensor<1x1x64x256xf32>) -> tensor<1x56x56x256xf32>
    %387 = stablehlo.broadcast_in_dim %76, dims = [3] : (tensor<256xf32>) -> tensor<1x56x56x256xf32>
    %388 = stablehlo.add %386, %387 : tensor<1x56x56x256xf32>
    %389 = "stablehlo.batch_norm_inference"(%388, %75, %74, %73, %72) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x56x56x256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>) -> tensor<1x56x56x256xf32>
    %390 = stablehlo.add %375, %389 : tensor<1x56x56x256xf32>
    %391 = stablehlo.maximum %390, %2 : tensor<1x56x56x256xf32>
    %392 = stablehlo.convolution(%391, %83) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [2, 2], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x56x56x256xf32>, tensor<1x1x256x512xf32>) -> tensor<1x28x28x512xf32>
    %393 = stablehlo.broadcast_in_dim %82, dims = [3] : (tensor<512xf32>) -> tensor<1x28x28x512xf32>
    %394 = stablehlo.add %392, %393 : tensor<1x28x28x512xf32>
    %395 = "stablehlo.batch_norm_inference"(%394, %81, %80, %79, %78) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x28x28x512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>) -> tensor<1x28x28x512xf32>
    %396 = stablehlo.convolution(%391, %89) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [2, 2], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x56x56x256xf32>, tensor<1x1x256x128xf32>) -> tensor<1x28x28x128xf32>
    %397 = stablehlo.broadcast_in_dim %88, dims = [3] : (tensor<128xf32>) -> tensor<1x28x28x128xf32>
    %398 = stablehlo.add %396, %397 : tensor<1x28x28x128xf32>
    %399 = "stablehlo.batch_norm_inference"(%398, %87, %86, %85, %84) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x28x28x128xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>) -> tensor<1x28x28x128xf32>
    %400 = stablehlo.maximum %399, %3 : tensor<1x28x28x128xf32>
    %401 = stablehlo.convolution(%400, %95) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[1, 1], [1, 1]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x28x28x128xf32>, tensor<3x3x128x128xf32>) -> tensor<1x28x28x128xf32>
    %402 = stablehlo.broadcast_in_dim %94, dims = [3] : (tensor<128xf32>) -> tensor<1x28x28x128xf32>
    %403 = stablehlo.add %401, %402 : tensor<1x28x28x128xf32>
    %404 = "stablehlo.batch_norm_inference"(%403, %93, %92, %91, %90) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x28x28x128xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>) -> tensor<1x28x28x128xf32>
    %405 = stablehlo.maximum %404, %3 : tensor<1x28x28x128xf32>
    %406 = stablehlo.convolution(%405, %101) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x28x28x128xf32>, tensor<1x1x128x512xf32>) -> tensor<1x28x28x512xf32>
    %407 = stablehlo.broadcast_in_dim %100, dims = [3] : (tensor<512xf32>) -> tensor<1x28x28x512xf32>
    %408 = stablehlo.add %406, %407 : tensor<1x28x28x512xf32>
    %409 = "stablehlo.batch_norm_inference"(%408, %99, %98, %97, %96) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x28x28x512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>) -> tensor<1x28x28x512xf32>
    %410 = stablehlo.add %395, %409 : tensor<1x28x28x512xf32>
    %411 = stablehlo.maximum %410, %4 : tensor<1x28x28x512xf32>
    %412 = stablehlo.convolution(%411, %107) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x28x28x512xf32>, tensor<1x1x512x128xf32>) -> tensor<1x28x28x128xf32>
    %413 = stablehlo.broadcast_in_dim %106, dims = [3] : (tensor<128xf32>) -> tensor<1x28x28x128xf32>
    %414 = stablehlo.add %412, %413 : tensor<1x28x28x128xf32>
    %415 = "stablehlo.batch_norm_inference"(%414, %105, %104, %103, %102) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x28x28x128xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>) -> tensor<1x28x28x128xf32>
    %416 = stablehlo.maximum %415, %3 : tensor<1x28x28x128xf32>
    %417 = stablehlo.convolution(%416, %113) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[1, 1], [1, 1]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x28x28x128xf32>, tensor<3x3x128x128xf32>) -> tensor<1x28x28x128xf32>
    %418 = stablehlo.broadcast_in_dim %112, dims = [3] : (tensor<128xf32>) -> tensor<1x28x28x128xf32>
    %419 = stablehlo.add %417, %418 : tensor<1x28x28x128xf32>
    %420 = "stablehlo.batch_norm_inference"(%419, %111, %110, %109, %108) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x28x28x128xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>) -> tensor<1x28x28x128xf32>
    %421 = stablehlo.maximum %420, %3 : tensor<1x28x28x128xf32>
    %422 = stablehlo.convolution(%421, %119) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x28x28x128xf32>, tensor<1x1x128x512xf32>) -> tensor<1x28x28x512xf32>
    %423 = stablehlo.broadcast_in_dim %118, dims = [3] : (tensor<512xf32>) -> tensor<1x28x28x512xf32>
    %424 = stablehlo.add %422, %423 : tensor<1x28x28x512xf32>
    %425 = "stablehlo.batch_norm_inference"(%424, %117, %116, %115, %114) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x28x28x512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>) -> tensor<1x28x28x512xf32>
    %426 = stablehlo.add %411, %425 : tensor<1x28x28x512xf32>
    %427 = stablehlo.maximum %426, %4 : tensor<1x28x28x512xf32>
    %428 = stablehlo.convolution(%427, %125) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x28x28x512xf32>, tensor<1x1x512x128xf32>) -> tensor<1x28x28x128xf32>
    %429 = stablehlo.broadcast_in_dim %124, dims = [3] : (tensor<128xf32>) -> tensor<1x28x28x128xf32>
    %430 = stablehlo.add %428, %429 : tensor<1x28x28x128xf32>
    %431 = "stablehlo.batch_norm_inference"(%430, %123, %122, %121, %120) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x28x28x128xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>) -> tensor<1x28x28x128xf32>
    %432 = stablehlo.maximum %431, %3 : tensor<1x28x28x128xf32>
    %433 = stablehlo.convolution(%432, %131) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[1, 1], [1, 1]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x28x28x128xf32>, tensor<3x3x128x128xf32>) -> tensor<1x28x28x128xf32>
    %434 = stablehlo.broadcast_in_dim %130, dims = [3] : (tensor<128xf32>) -> tensor<1x28x28x128xf32>
    %435 = stablehlo.add %433, %434 : tensor<1x28x28x128xf32>
    %436 = "stablehlo.batch_norm_inference"(%435, %129, %128, %127, %126) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x28x28x128xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>) -> tensor<1x28x28x128xf32>
    %437 = stablehlo.maximum %436, %3 : tensor<1x28x28x128xf32>
    %438 = stablehlo.convolution(%437, %137) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x28x28x128xf32>, tensor<1x1x128x512xf32>) -> tensor<1x28x28x512xf32>
    %439 = stablehlo.broadcast_in_dim %136, dims = [3] : (tensor<512xf32>) -> tensor<1x28x28x512xf32>
    %440 = stablehlo.add %438, %439 : tensor<1x28x28x512xf32>
    %441 = "stablehlo.batch_norm_inference"(%440, %135, %134, %133, %132) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x28x28x512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>) -> tensor<1x28x28x512xf32>
    %442 = stablehlo.add %427, %441 : tensor<1x28x28x512xf32>
    %443 = stablehlo.maximum %442, %4 : tensor<1x28x28x512xf32>
    %444 = stablehlo.convolution(%443, %143) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x28x28x512xf32>, tensor<1x1x512x128xf32>) -> tensor<1x28x28x128xf32>
    %445 = stablehlo.broadcast_in_dim %142, dims = [3] : (tensor<128xf32>) -> tensor<1x28x28x128xf32>
    %446 = stablehlo.add %444, %445 : tensor<1x28x28x128xf32>
    %447 = "stablehlo.batch_norm_inference"(%446, %141, %140, %139, %138) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x28x28x128xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>) -> tensor<1x28x28x128xf32>
    %448 = stablehlo.maximum %447, %3 : tensor<1x28x28x128xf32>
    %449 = stablehlo.convolution(%448, %149) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[1, 1], [1, 1]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x28x28x128xf32>, tensor<3x3x128x128xf32>) -> tensor<1x28x28x128xf32>
    %450 = stablehlo.broadcast_in_dim %148, dims = [3] : (tensor<128xf32>) -> tensor<1x28x28x128xf32>
    %451 = stablehlo.add %449, %450 : tensor<1x28x28x128xf32>
    %452 = "stablehlo.batch_norm_inference"(%451, %147, %146, %145, %144) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x28x28x128xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>, tensor<128xf32>) -> tensor<1x28x28x128xf32>
    %453 = stablehlo.maximum %452, %3 : tensor<1x28x28x128xf32>
    %454 = stablehlo.convolution(%453, %155) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x28x28x128xf32>, tensor<1x1x128x512xf32>) -> tensor<1x28x28x512xf32>
    %455 = stablehlo.broadcast_in_dim %154, dims = [3] : (tensor<512xf32>) -> tensor<1x28x28x512xf32>
    %456 = stablehlo.add %454, %455 : tensor<1x28x28x512xf32>
    %457 = "stablehlo.batch_norm_inference"(%456, %153, %152, %151, %150) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x28x28x512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>) -> tensor<1x28x28x512xf32>
    %458 = stablehlo.add %443, %457 : tensor<1x28x28x512xf32>
    %459 = stablehlo.maximum %458, %4 : tensor<1x28x28x512xf32>
    %460 = stablehlo.convolution(%459, %161) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [2, 2], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x28x28x512xf32>, tensor<1x1x512x1024xf32>) -> tensor<1x14x14x1024xf32>
    %461 = stablehlo.broadcast_in_dim %160, dims = [3] : (tensor<1024xf32>) -> tensor<1x14x14x1024xf32>
    %462 = stablehlo.add %460, %461 : tensor<1x14x14x1024xf32>
    %463 = "stablehlo.batch_norm_inference"(%462, %159, %158, %157, %156) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x14x14x1024xf32>, tensor<1024xf32>, tensor<1024xf32>, tensor<1024xf32>, tensor<1024xf32>) -> tensor<1x14x14x1024xf32>
    %464 = stablehlo.convolution(%459, %167) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [2, 2], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x28x28x512xf32>, tensor<1x1x512x256xf32>) -> tensor<1x14x14x256xf32>
    %465 = stablehlo.broadcast_in_dim %166, dims = [3] : (tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %466 = stablehlo.add %464, %465 : tensor<1x14x14x256xf32>
    %467 = "stablehlo.batch_norm_inference"(%466, %165, %164, %163, %162) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x14x14x256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %468 = stablehlo.maximum %467, %5 : tensor<1x14x14x256xf32>
    %469 = stablehlo.convolution(%468, %173) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[1, 1], [1, 1]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x14x14x256xf32>, tensor<3x3x256x256xf32>) -> tensor<1x14x14x256xf32>
    %470 = stablehlo.broadcast_in_dim %172, dims = [3] : (tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %471 = stablehlo.add %469, %470 : tensor<1x14x14x256xf32>
    %472 = "stablehlo.batch_norm_inference"(%471, %171, %170, %169, %168) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x14x14x256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %473 = stablehlo.maximum %472, %5 : tensor<1x14x14x256xf32>
    %474 = stablehlo.convolution(%473, %179) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x14x14x256xf32>, tensor<1x1x256x1024xf32>) -> tensor<1x14x14x1024xf32>
    %475 = stablehlo.broadcast_in_dim %178, dims = [3] : (tensor<1024xf32>) -> tensor<1x14x14x1024xf32>
    %476 = stablehlo.add %474, %475 : tensor<1x14x14x1024xf32>
    %477 = "stablehlo.batch_norm_inference"(%476, %177, %176, %175, %174) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x14x14x1024xf32>, tensor<1024xf32>, tensor<1024xf32>, tensor<1024xf32>, tensor<1024xf32>) -> tensor<1x14x14x1024xf32>
    %478 = stablehlo.add %463, %477 : tensor<1x14x14x1024xf32>
    %479 = stablehlo.maximum %478, %6 : tensor<1x14x14x1024xf32>
    %480 = stablehlo.convolution(%479, %185) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x14x14x1024xf32>, tensor<1x1x1024x256xf32>) -> tensor<1x14x14x256xf32>
    %481 = stablehlo.broadcast_in_dim %184, dims = [3] : (tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %482 = stablehlo.add %480, %481 : tensor<1x14x14x256xf32>
    %483 = "stablehlo.batch_norm_inference"(%482, %183, %182, %181, %180) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x14x14x256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %484 = stablehlo.maximum %483, %5 : tensor<1x14x14x256xf32>
    %485 = stablehlo.convolution(%484, %191) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[1, 1], [1, 1]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x14x14x256xf32>, tensor<3x3x256x256xf32>) -> tensor<1x14x14x256xf32>
    %486 = stablehlo.broadcast_in_dim %190, dims = [3] : (tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %487 = stablehlo.add %485, %486 : tensor<1x14x14x256xf32>
    %488 = "stablehlo.batch_norm_inference"(%487, %189, %188, %187, %186) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x14x14x256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %489 = stablehlo.maximum %488, %5 : tensor<1x14x14x256xf32>
    %490 = stablehlo.convolution(%489, %197) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x14x14x256xf32>, tensor<1x1x256x1024xf32>) -> tensor<1x14x14x1024xf32>
    %491 = stablehlo.broadcast_in_dim %196, dims = [3] : (tensor<1024xf32>) -> tensor<1x14x14x1024xf32>
    %492 = stablehlo.add %490, %491 : tensor<1x14x14x1024xf32>
    %493 = "stablehlo.batch_norm_inference"(%492, %195, %194, %193, %192) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x14x14x1024xf32>, tensor<1024xf32>, tensor<1024xf32>, tensor<1024xf32>, tensor<1024xf32>) -> tensor<1x14x14x1024xf32>
    %494 = stablehlo.add %479, %493 : tensor<1x14x14x1024xf32>
    %495 = stablehlo.maximum %494, %6 : tensor<1x14x14x1024xf32>
    %496 = stablehlo.convolution(%495, %203) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x14x14x1024xf32>, tensor<1x1x1024x256xf32>) -> tensor<1x14x14x256xf32>
    %497 = stablehlo.broadcast_in_dim %202, dims = [3] : (tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %498 = stablehlo.add %496, %497 : tensor<1x14x14x256xf32>
    %499 = "stablehlo.batch_norm_inference"(%498, %201, %200, %199, %198) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x14x14x256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %500 = stablehlo.maximum %499, %5 : tensor<1x14x14x256xf32>
    %501 = stablehlo.convolution(%500, %209) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[1, 1], [1, 1]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x14x14x256xf32>, tensor<3x3x256x256xf32>) -> tensor<1x14x14x256xf32>
    %502 = stablehlo.broadcast_in_dim %208, dims = [3] : (tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %503 = stablehlo.add %501, %502 : tensor<1x14x14x256xf32>
    %504 = "stablehlo.batch_norm_inference"(%503, %207, %206, %205, %204) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x14x14x256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %505 = stablehlo.maximum %504, %5 : tensor<1x14x14x256xf32>
    %506 = stablehlo.convolution(%505, %215) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x14x14x256xf32>, tensor<1x1x256x1024xf32>) -> tensor<1x14x14x1024xf32>
    %507 = stablehlo.broadcast_in_dim %214, dims = [3] : (tensor<1024xf32>) -> tensor<1x14x14x1024xf32>
    %508 = stablehlo.add %506, %507 : tensor<1x14x14x1024xf32>
    %509 = "stablehlo.batch_norm_inference"(%508, %213, %212, %211, %210) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x14x14x1024xf32>, tensor<1024xf32>, tensor<1024xf32>, tensor<1024xf32>, tensor<1024xf32>) -> tensor<1x14x14x1024xf32>
    %510 = stablehlo.add %495, %509 : tensor<1x14x14x1024xf32>
    %511 = stablehlo.maximum %510, %6 : tensor<1x14x14x1024xf32>
    %512 = stablehlo.convolution(%511, %221) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x14x14x1024xf32>, tensor<1x1x1024x256xf32>) -> tensor<1x14x14x256xf32>
    %513 = stablehlo.broadcast_in_dim %220, dims = [3] : (tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %514 = stablehlo.add %512, %513 : tensor<1x14x14x256xf32>
    %515 = "stablehlo.batch_norm_inference"(%514, %219, %218, %217, %216) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x14x14x256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %516 = stablehlo.maximum %515, %5 : tensor<1x14x14x256xf32>
    %517 = stablehlo.convolution(%516, %227) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[1, 1], [1, 1]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x14x14x256xf32>, tensor<3x3x256x256xf32>) -> tensor<1x14x14x256xf32>
    %518 = stablehlo.broadcast_in_dim %226, dims = [3] : (tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %519 = stablehlo.add %517, %518 : tensor<1x14x14x256xf32>
    %520 = "stablehlo.batch_norm_inference"(%519, %225, %224, %223, %222) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x14x14x256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %521 = stablehlo.maximum %520, %5 : tensor<1x14x14x256xf32>
    %522 = stablehlo.convolution(%521, %233) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x14x14x256xf32>, tensor<1x1x256x1024xf32>) -> tensor<1x14x14x1024xf32>
    %523 = stablehlo.broadcast_in_dim %232, dims = [3] : (tensor<1024xf32>) -> tensor<1x14x14x1024xf32>
    %524 = stablehlo.add %522, %523 : tensor<1x14x14x1024xf32>
    %525 = "stablehlo.batch_norm_inference"(%524, %231, %230, %229, %228) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x14x14x1024xf32>, tensor<1024xf32>, tensor<1024xf32>, tensor<1024xf32>, tensor<1024xf32>) -> tensor<1x14x14x1024xf32>
    %526 = stablehlo.add %511, %525 : tensor<1x14x14x1024xf32>
    %527 = stablehlo.maximum %526, %6 : tensor<1x14x14x1024xf32>
    %528 = stablehlo.convolution(%527, %239) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x14x14x1024xf32>, tensor<1x1x1024x256xf32>) -> tensor<1x14x14x256xf32>
    %529 = stablehlo.broadcast_in_dim %238, dims = [3] : (tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %530 = stablehlo.add %528, %529 : tensor<1x14x14x256xf32>
    %531 = "stablehlo.batch_norm_inference"(%530, %237, %236, %235, %234) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x14x14x256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %532 = stablehlo.maximum %531, %5 : tensor<1x14x14x256xf32>
    %533 = stablehlo.convolution(%532, %245) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[1, 1], [1, 1]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x14x14x256xf32>, tensor<3x3x256x256xf32>) -> tensor<1x14x14x256xf32>
    %534 = stablehlo.broadcast_in_dim %244, dims = [3] : (tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %535 = stablehlo.add %533, %534 : tensor<1x14x14x256xf32>
    %536 = "stablehlo.batch_norm_inference"(%535, %243, %242, %241, %240) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x14x14x256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %537 = stablehlo.maximum %536, %5 : tensor<1x14x14x256xf32>
    %538 = stablehlo.convolution(%537, %251) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x14x14x256xf32>, tensor<1x1x256x1024xf32>) -> tensor<1x14x14x1024xf32>
    %539 = stablehlo.broadcast_in_dim %250, dims = [3] : (tensor<1024xf32>) -> tensor<1x14x14x1024xf32>
    %540 = stablehlo.add %538, %539 : tensor<1x14x14x1024xf32>
    %541 = "stablehlo.batch_norm_inference"(%540, %249, %248, %247, %246) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x14x14x1024xf32>, tensor<1024xf32>, tensor<1024xf32>, tensor<1024xf32>, tensor<1024xf32>) -> tensor<1x14x14x1024xf32>
    %542 = stablehlo.add %527, %541 : tensor<1x14x14x1024xf32>
    %543 = stablehlo.maximum %542, %6 : tensor<1x14x14x1024xf32>
    %544 = stablehlo.convolution(%543, %257) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x14x14x1024xf32>, tensor<1x1x1024x256xf32>) -> tensor<1x14x14x256xf32>
    %545 = stablehlo.broadcast_in_dim %256, dims = [3] : (tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %546 = stablehlo.add %544, %545 : tensor<1x14x14x256xf32>
    %547 = "stablehlo.batch_norm_inference"(%546, %255, %254, %253, %252) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x14x14x256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %548 = stablehlo.maximum %547, %5 : tensor<1x14x14x256xf32>
    %549 = stablehlo.convolution(%548, %263) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[1, 1], [1, 1]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x14x14x256xf32>, tensor<3x3x256x256xf32>) -> tensor<1x14x14x256xf32>
    %550 = stablehlo.broadcast_in_dim %262, dims = [3] : (tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %551 = stablehlo.add %549, %550 : tensor<1x14x14x256xf32>
    %552 = "stablehlo.batch_norm_inference"(%551, %261, %260, %259, %258) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x14x14x256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>, tensor<256xf32>) -> tensor<1x14x14x256xf32>
    %553 = stablehlo.maximum %552, %5 : tensor<1x14x14x256xf32>
    %554 = stablehlo.convolution(%553, %269) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x14x14x256xf32>, tensor<1x1x256x1024xf32>) -> tensor<1x14x14x1024xf32>
    %555 = stablehlo.broadcast_in_dim %268, dims = [3] : (tensor<1024xf32>) -> tensor<1x14x14x1024xf32>
    %556 = stablehlo.add %554, %555 : tensor<1x14x14x1024xf32>
    %557 = "stablehlo.batch_norm_inference"(%556, %267, %266, %265, %264) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x14x14x1024xf32>, tensor<1024xf32>, tensor<1024xf32>, tensor<1024xf32>, tensor<1024xf32>) -> tensor<1x14x14x1024xf32>
    %558 = stablehlo.add %543, %557 : tensor<1x14x14x1024xf32>
    %559 = stablehlo.maximum %558, %6 : tensor<1x14x14x1024xf32>
    %560 = stablehlo.convolution(%559, %275) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [2, 2], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x14x14x1024xf32>, tensor<1x1x1024x2048xf32>) -> tensor<1x7x7x2048xf32>
    %561 = stablehlo.broadcast_in_dim %274, dims = [3] : (tensor<2048xf32>) -> tensor<1x7x7x2048xf32>
    %562 = stablehlo.add %560, %561 : tensor<1x7x7x2048xf32>
    %563 = "stablehlo.batch_norm_inference"(%562, %273, %272, %271, %270) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x7x7x2048xf32>, tensor<2048xf32>, tensor<2048xf32>, tensor<2048xf32>, tensor<2048xf32>) -> tensor<1x7x7x2048xf32>
    %564 = stablehlo.convolution(%559, %281) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [2, 2], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x14x14x1024xf32>, tensor<1x1x1024x512xf32>) -> tensor<1x7x7x512xf32>
    %565 = stablehlo.broadcast_in_dim %280, dims = [3] : (tensor<512xf32>) -> tensor<1x7x7x512xf32>
    %566 = stablehlo.add %564, %565 : tensor<1x7x7x512xf32>
    %567 = "stablehlo.batch_norm_inference"(%566, %279, %278, %277, %276) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x7x7x512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>) -> tensor<1x7x7x512xf32>
    %568 = stablehlo.maximum %567, %7 : tensor<1x7x7x512xf32>
    %569 = stablehlo.convolution(%568, %287) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[1, 1], [1, 1]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x7x7x512xf32>, tensor<3x3x512x512xf32>) -> tensor<1x7x7x512xf32>
    %570 = stablehlo.broadcast_in_dim %286, dims = [3] : (tensor<512xf32>) -> tensor<1x7x7x512xf32>
    %571 = stablehlo.add %569, %570 : tensor<1x7x7x512xf32>
    %572 = "stablehlo.batch_norm_inference"(%571, %285, %284, %283, %282) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x7x7x512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>) -> tensor<1x7x7x512xf32>
    %573 = stablehlo.maximum %572, %7 : tensor<1x7x7x512xf32>
    %574 = stablehlo.convolution(%573, %293) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x7x7x512xf32>, tensor<1x1x512x2048xf32>) -> tensor<1x7x7x2048xf32>
    %575 = stablehlo.broadcast_in_dim %292, dims = [3] : (tensor<2048xf32>) -> tensor<1x7x7x2048xf32>
    %576 = stablehlo.add %574, %575 : tensor<1x7x7x2048xf32>
    %577 = "stablehlo.batch_norm_inference"(%576, %291, %290, %289, %288) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x7x7x2048xf32>, tensor<2048xf32>, tensor<2048xf32>, tensor<2048xf32>, tensor<2048xf32>) -> tensor<1x7x7x2048xf32>
    %578 = stablehlo.add %563, %577 : tensor<1x7x7x2048xf32>
    %579 = stablehlo.maximum %578, %8 : tensor<1x7x7x2048xf32>
    %580 = stablehlo.convolution(%579, %299) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x7x7x2048xf32>, tensor<1x1x2048x512xf32>) -> tensor<1x7x7x512xf32>
    %581 = stablehlo.broadcast_in_dim %298, dims = [3] : (tensor<512xf32>) -> tensor<1x7x7x512xf32>
    %582 = stablehlo.add %580, %581 : tensor<1x7x7x512xf32>
    %583 = "stablehlo.batch_norm_inference"(%582, %297, %296, %295, %294) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x7x7x512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>) -> tensor<1x7x7x512xf32>
    %584 = stablehlo.maximum %583, %7 : tensor<1x7x7x512xf32>
    %585 = stablehlo.convolution(%584, %305) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[1, 1], [1, 1]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x7x7x512xf32>, tensor<3x3x512x512xf32>) -> tensor<1x7x7x512xf32>
    %586 = stablehlo.broadcast_in_dim %304, dims = [3] : (tensor<512xf32>) -> tensor<1x7x7x512xf32>
    %587 = stablehlo.add %585, %586 : tensor<1x7x7x512xf32>
    %588 = "stablehlo.batch_norm_inference"(%587, %303, %302, %301, %300) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x7x7x512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>) -> tensor<1x7x7x512xf32>
    %589 = stablehlo.maximum %588, %7 : tensor<1x7x7x512xf32>
    %590 = stablehlo.convolution(%589, %311) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x7x7x512xf32>, tensor<1x1x512x2048xf32>) -> tensor<1x7x7x2048xf32>
    %591 = stablehlo.broadcast_in_dim %310, dims = [3] : (tensor<2048xf32>) -> tensor<1x7x7x2048xf32>
    %592 = stablehlo.add %590, %591 : tensor<1x7x7x2048xf32>
    %593 = "stablehlo.batch_norm_inference"(%592, %309, %308, %307, %306) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x7x7x2048xf32>, tensor<2048xf32>, tensor<2048xf32>, tensor<2048xf32>, tensor<2048xf32>) -> tensor<1x7x7x2048xf32>
    %594 = stablehlo.add %579, %593 : tensor<1x7x7x2048xf32>
    %595 = stablehlo.maximum %594, %8 : tensor<1x7x7x2048xf32>
    %596 = stablehlo.convolution(%595, %317) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x7x7x2048xf32>, tensor<1x1x2048x512xf32>) -> tensor<1x7x7x512xf32>
    %597 = stablehlo.broadcast_in_dim %316, dims = [3] : (tensor<512xf32>) -> tensor<1x7x7x512xf32>
    %598 = stablehlo.add %596, %597 : tensor<1x7x7x512xf32>
    %599 = "stablehlo.batch_norm_inference"(%598, %315, %314, %313, %312) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x7x7x512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>) -> tensor<1x7x7x512xf32>
    %600 = stablehlo.maximum %599, %7 : tensor<1x7x7x512xf32>
    %601 = stablehlo.convolution(%600, %323) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[1, 1], [1, 1]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x7x7x512xf32>, tensor<3x3x512x512xf32>) -> tensor<1x7x7x512xf32>
    %602 = stablehlo.broadcast_in_dim %322, dims = [3] : (tensor<512xf32>) -> tensor<1x7x7x512xf32>
    %603 = stablehlo.add %601, %602 : tensor<1x7x7x512xf32>
    %604 = "stablehlo.batch_norm_inference"(%603, %321, %320, %319, %318) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x7x7x512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>, tensor<512xf32>) -> tensor<1x7x7x512xf32>
    %605 = stablehlo.maximum %604, %7 : tensor<1x7x7x512xf32>
    %606 = stablehlo.convolution(%605, %329) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = [[0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x7x7x512xf32>, tensor<1x1x512x2048xf32>) -> tensor<1x7x7x2048xf32>
    %607 = stablehlo.broadcast_in_dim %328, dims = [3] : (tensor<2048xf32>) -> tensor<1x7x7x2048xf32>
    %608 = stablehlo.add %606, %607 : tensor<1x7x7x2048xf32>
    %609 = "stablehlo.batch_norm_inference"(%608, %327, %326, %325, %324) {epsilon = 1.001000e-05 : f32, feature_index = 3 : i64} : (tensor<1x7x7x2048xf32>, tensor<2048xf32>, tensor<2048xf32>, tensor<2048xf32>, tensor<2048xf32>) -> tensor<1x7x7x2048xf32>
    %610 = stablehlo.add %595, %609 : tensor<1x7x7x2048xf32>
    %611 = stablehlo.maximum %610, %8 : tensor<1x7x7x2048xf32>
    %612 = stablehlo.reduce(%611 init: %11) across dimensions = [1, 2] : (tensor<1x7x7x2048xf32>, tensor<f32>) -> tensor<1x2048xf32>
     reducer(%arg1: tensor<f32>, %arg2: tensor<f32>)  {
      %624 = stablehlo.add %arg1, %arg2 : tensor<f32>
      stablehlo.return %624 : tensor<f32>
    }
    %613 = stablehlo.divide %612, %9 : tensor<1x2048xf32>
    %614 = stablehlo.dot %613, %331 : (tensor<1x2048xf32>, tensor<2048x1000xf32>) -> tensor<1x1000xf32>
    %615 = stablehlo.broadcast_in_dim %330, dims = [1] : (tensor<1000xf32>) -> tensor<1x1000xf32>
    %616 = stablehlo.add %614, %615 : tensor<1x1000xf32>
    %617 = stablehlo.reduce(%616 init: %10) across dimensions = [1] : (tensor<1x1000xf32>, tensor<f32>) -> tensor<1xf32>
     reducer(%arg1: tensor<f32>, %arg2: tensor<f32>)  {
      %624 = stablehlo.maximum %arg1, %arg2 : tensor<f32>
      stablehlo.return %624 : tensor<f32>
    }
    %618 = stablehlo.broadcast_in_dim %617, dims = [0] : (tensor<1xf32>) -> tensor<1x1000xf32>
    %619 = stablehlo.subtract %616, %618 : tensor<1x1000xf32>
    %620 = stablehlo.exponential %619 : tensor<1x1000xf32>
    %621 = stablehlo.reduce(%620 init: %11) across dimensions = [1] : (tensor<1x1000xf32>, tensor<f32>) -> tensor<1xf32>
     reducer(%arg1: tensor<f32>, %arg2: tensor<f32>)  {
      %624 = stablehlo.add %arg1, %arg2 : tensor<f32>
      stablehlo.return %624 : tensor<f32>
    }
    %622 = stablehlo.broadcast_in_dim %621, dims = [0] : (tensor<1xf32>) -> tensor<1x1000xf32>
    %623 = stablehlo.divide %620, %622 : tensor<1x1000xf32>
    return %623 : tensor<1x1000xf32>
  }
}

// CHECK: 1x1000xf32=[0.001 0.001 0.001 0.001 0.001