// Copyright 2020 Google LLC // // This source code is licensed under the BSD-style license found in the // LICENSE file in the root directory of this source tree. #include #include #include #include #include #include #include #include #include #include #include namespace models { ExecutionPlan FP16MobileNetV3Large(bool use_jit, pthreadpool_t threadpool) { alignas(16) static std::array v0; alignas(16) static std::array v1; alignas(16) static std::array v2; alignas(16) static std::array v3; alignas(16) static std::array v4; alignas(16) static std::array v5; alignas(16) static std::array v6; alignas(16) static std::array v7; alignas(16) static std::array v8; alignas(16) static std::array v9; alignas(16) static std::array v10; alignas(16) static std::array v11; alignas(16) static std::array v12; alignas(16) static std::array v13; alignas(16) static std::array v14; alignas(16) static std::array v15; alignas(16) static std::array v16; alignas(16) static std::array v17; alignas(16) static std::array v18; alignas(16) static std::array v19; alignas(16) static std::array v20; alignas(16) static std::array v21; alignas(16) static std::array v22; alignas(16) static std::array v23; alignas(16) static std::array v24; alignas(16) static std::array v25; alignas(16) static std::array v26; alignas(16) static std::array v27; alignas(16) static std::array v28; alignas(16) static std::array v29; alignas(16) static std::array v30; alignas(16) static std::array v31; alignas(16) static std::array v32; alignas(16) static std::array v33; alignas(16) static std::array v34; alignas(16) static std::array v35; alignas(16) static std::array v36; alignas(16) static std::array v37; alignas(16) static std::array v38; alignas(16) static std::array v39; alignas(16) static std::array v40; alignas(16) static std::array v41; alignas(16) static std::array v42; alignas(16) static std::array v43; alignas(16) static std::array v44; alignas(16) static std::array v45; alignas(16) static std::array v46; alignas(16) static std::array v47; alignas(16) static std::array v48; alignas(16) static std::array v49; alignas(16) static std::array v50; alignas(16) static std::array v51; alignas(16) static std::array v52; alignas(16) static std::array v53; alignas(16) static std::array v54; alignas(16) static std::array v55; alignas(16) static std::array v56; alignas(16) static std::array v57; alignas(16) static std::array v58; alignas(16) static std::array v59; alignas(16) static std::array v60; alignas(16) static std::array v61; alignas(16) static std::array v62; alignas(16) static std::array v63; alignas(16) static std::array v64; alignas(16) static std::array v65; alignas(16) static std::array v66; alignas(16) static std::array v67; alignas(16) static std::array v68; alignas(16) static std::array v69; alignas(16) static std::array v70; alignas(16) static std::array v71; alignas(16) static std::array v72; alignas(16) static std::array v73; alignas(16) static std::array v74; alignas(16) static std::array v75; alignas(16) static std::array v76; alignas(16) static std::array v77; alignas(16) static std::array v78; alignas(16) static std::array v79; alignas(16) static std::array v80; alignas(16) static std::array v81; alignas(16) static std::array v82; alignas(16) static std::array v83; alignas(16) static std::array v84; alignas(16) static std::array v85; alignas(16) static std::array v86; alignas(16) static std::array v87; alignas(16) static std::array v88; alignas(16) static std::array v89; alignas(16) static std::array v90; alignas(16) static std::array v91; alignas(16) static std::array v92; alignas(16) static std::array v93; alignas(16) static std::array v94; alignas(16) static std::array v95; alignas(16) static std::array v96; alignas(16) static std::array v97; alignas(16) static std::array v98; alignas(16) static std::array v99; alignas(16) static std::array v100; alignas(16) static std::array v101; alignas(16) static std::array v102; alignas(16) static std::array v103; alignas(16) static std::array v104; alignas(16) static std::array v105; alignas(16) static std::array v106; alignas(16) static std::array v107; alignas(16) static std::array v108; alignas(16) static std::array v109; alignas(16) static std::array v110; alignas(16) static std::array v111; alignas(16) static std::array v112; alignas(16) static std::array v113; alignas(16) static std::array w114; alignas(16) static std::array w115; alignas(16) static std::array w116; alignas(16) static std::array w117; alignas(16) static std::array w118; alignas(16) static std::array w119; alignas(16) static std::array w120; alignas(16) static std::array w121; alignas(16) static std::array w122; alignas(16) static std::array w123; alignas(16) static std::array w124; alignas(16) static std::array w125; alignas(16) static std::array w126; alignas(16) static std::array w127; alignas(16) static std::array w128; alignas(16) static std::array w129; alignas(16) static std::array w130; alignas(16) static std::array w131; alignas(16) static std::array w132; alignas(16) static std::array w133; alignas(16) static std::array w134; alignas(16) static std::array w135; alignas(16) static std::array w136; alignas(16) static std::array w137; alignas(16) static std::array w138; alignas(16) static std::array w139; alignas(16) static std::array w140; alignas(16) static std::array w141; alignas(16) static std::array w142; alignas(16) static std::array w143; alignas(16) static std::array w144; alignas(16) static std::array w145; alignas(16) static std::array w146; alignas(16) static std::array w147; alignas(16) static std::array w148; alignas(16) static std::array w149; alignas(16) static std::array w150; alignas(16) static std::array w151; alignas(16) static std::array w152; alignas(16) static std::array w153; alignas(16) static std::array w154; alignas(16) static std::array w155; alignas(16) static std::array w156; alignas(16) static std::array w157; alignas(16) static std::array w158; alignas(16) static std::array w159; alignas(16) static std::array w160; alignas(16) static std::array w161; alignas(16) static std::array w162; alignas(16) static std::array w163; alignas(16) static std::array w164; alignas(16) static std::array w165; alignas(16) static std::array w166; alignas(16) static std::array w167; alignas(16) static std::array w168; alignas(16) static std::array w169; alignas(16) static std::array w170; alignas(16) static std::array w171; alignas(16) static std::array w172; alignas(16) static std::array w173; alignas(16) static std::array w174; alignas(16) static std::array w175; alignas(16) static std::array w176; alignas(16) static std::array w177; alignas(16) static std::array w178; alignas(16) static std::array w179; alignas(16) static std::array w180; alignas(16) static std::array w181; alignas(16) static std::array w182; alignas(16) static std::array w183; alignas(16) static std::array w184; alignas(16) static std::array w185; alignas(16) static std::array w186; alignas(16) static std::array w187; alignas(16) static std::array w188; alignas(16) static std::array w189; alignas(16) static std::array w190; alignas(16) static std::array w191; alignas(16) static std::array w192; alignas(16) static std::array w193; alignas(16) static std::array w194; alignas(16) static std::array w195; alignas(16) static std::array w196; alignas(16) static std::array w197; alignas(16) static std::array w198; alignas(16) static std::array w199; alignas(16) static std::array w200; alignas(16) static std::array w201; alignas(16) static std::array w202; alignas(16) static std::array w203; alignas(16) static std::array w204; alignas(16) static std::array w205; alignas(16) static std::array w206; alignas(16) static std::array w207; alignas(16) static std::array w208; alignas(16) static std::array w209; alignas(16) static std::array w210; alignas(16) static std::array w211; alignas(16) static std::array w212; alignas(16) static std::array w213; alignas(16) static std::array w214; alignas(16) static std::array w215; alignas(16) static std::array w216; alignas(16) static std::array w217; alignas(16) static std::array w218; alignas(16) static std::array w219; alignas(16) static std::array w220; alignas(16) static std::array w221; alignas(16) static std::array w222; alignas(16) static std::array w223; alignas(16) static std::array w224; alignas(16) static std::array w225; alignas(16) static std::array w226; alignas(16) static std::array w227; alignas(16) static std::array w228; alignas(16) static std::array w229; alignas(16) static std::array w230; alignas(16) static std::array w231; alignas(16) static std::array w232; alignas(16) static std::array w233; alignas(16) static std::array w234; alignas(16) static std::array w235; alignas(16) static std::array w236; alignas(16) static std::array w237; alignas(16) static std::array w238; alignas(16) static std::array w239; alignas(16) static std::array w240; alignas(16) static std::array w241; std::random_device random_device; auto rng = std::mt19937(random_device()); auto f32rng = std::bind(std::uniform_real_distribution(-1.0f, +1.0f), std::ref(rng)); auto f16rng = std::bind(fp16_ieee_from_fp32_value, f32rng); std::generate(v0.begin(), v0.end(), std::ref(f16rng)); std::generate(v1.begin(), v1.end(), std::ref(f16rng)); std::generate(v2.begin(), v2.end(), std::ref(f16rng)); std::generate(v3.begin(), v3.end(), std::ref(f16rng)); std::generate(v4.begin(), v4.end(), std::ref(f16rng)); std::generate(v5.begin(), v5.end(), std::ref(f16rng)); std::generate(v6.begin(), v6.end(), std::ref(f16rng)); std::generate(v7.begin(), v7.end(), std::ref(f16rng)); std::generate(v8.begin(), v8.end(), std::ref(f16rng)); std::generate(v9.begin(), v9.end(), std::ref(f16rng)); std::generate(v10.begin(), v10.end(), std::ref(f16rng)); std::generate(v11.begin(), v11.end(), std::ref(f16rng)); std::generate(v12.begin(), v12.end(), std::ref(f16rng)); std::generate(v13.begin(), v13.end(), std::ref(f16rng)); std::generate(v14.begin(), v14.end(), std::ref(f16rng)); std::generate(v15.begin(), v15.end(), std::ref(f16rng)); std::generate(v16.begin(), v16.end(), std::ref(f16rng)); std::generate(v17.begin(), v17.end(), std::ref(f16rng)); std::generate(v18.begin(), v18.end(), std::ref(f16rng)); std::generate(v19.begin(), v19.end(), std::ref(f16rng)); std::generate(v20.begin(), v20.end(), std::ref(f16rng)); std::generate(v21.begin(), v21.end(), std::ref(f16rng)); std::generate(v22.begin(), v22.end(), std::ref(f16rng)); std::generate(v23.begin(), v23.end(), std::ref(f16rng)); std::generate(v24.begin(), v24.end(), std::ref(f16rng)); std::generate(v25.begin(), v25.end(), std::ref(f16rng)); std::generate(v26.begin(), v26.end(), std::ref(f16rng)); std::generate(v27.begin(), v27.end(), std::ref(f16rng)); std::generate(v28.begin(), v28.end(), std::ref(f16rng)); std::generate(v29.begin(), v29.end(), std::ref(f16rng)); std::generate(v30.begin(), v30.end(), std::ref(f16rng)); std::generate(v31.begin(), v31.end(), std::ref(f16rng)); std::generate(v32.begin(), v32.end(), std::ref(f16rng)); std::generate(v33.begin(), v33.end(), std::ref(f16rng)); std::generate(v34.begin(), v34.end(), std::ref(f16rng)); std::generate(v35.begin(), v35.end(), std::ref(f16rng)); std::generate(v36.begin(), v36.end(), std::ref(f16rng)); std::generate(v37.begin(), v37.end(), std::ref(f16rng)); std::generate(v38.begin(), v38.end(), std::ref(f16rng)); std::generate(v39.begin(), v39.end(), std::ref(f16rng)); std::generate(v40.begin(), v40.end(), std::ref(f16rng)); std::generate(v41.begin(), v41.end(), std::ref(f16rng)); std::generate(v42.begin(), v42.end(), std::ref(f16rng)); std::generate(v43.begin(), v43.end(), std::ref(f16rng)); std::generate(v44.begin(), v44.end(), std::ref(f16rng)); std::generate(v45.begin(), v45.end(), std::ref(f16rng)); std::generate(v46.begin(), v46.end(), std::ref(f16rng)); std::generate(v47.begin(), v47.end(), std::ref(f16rng)); std::generate(v48.begin(), v48.end(), std::ref(f16rng)); std::generate(v49.begin(), v49.end(), std::ref(f16rng)); std::generate(v50.begin(), v50.end(), std::ref(f16rng)); std::generate(v51.begin(), v51.end(), std::ref(f16rng)); std::generate(v52.begin(), v52.end(), std::ref(f16rng)); std::generate(v53.begin(), v53.end(), std::ref(f16rng)); std::generate(v54.begin(), v54.end(), std::ref(f16rng)); std::generate(v55.begin(), v55.end(), std::ref(f16rng)); std::generate(v56.begin(), v56.end(), std::ref(f16rng)); std::generate(v57.begin(), v57.end(), std::ref(f16rng)); std::generate(v58.begin(), v58.end(), std::ref(f16rng)); std::generate(v59.begin(), v59.end(), std::ref(f16rng)); std::generate(v60.begin(), v60.end(), std::ref(f16rng)); std::generate(v61.begin(), v61.end(), std::ref(f16rng)); std::generate(v62.begin(), v62.end(), std::ref(f16rng)); std::generate(v63.begin(), v63.end(), std::ref(f16rng)); std::generate(v64.begin(), v64.end(), std::ref(f16rng)); std::generate(v65.begin(), v65.end(), std::ref(f16rng)); std::generate(v66.begin(), v66.end(), std::ref(f16rng)); std::generate(v67.begin(), v67.end(), std::ref(f16rng)); std::generate(v68.begin(), v68.end(), std::ref(f16rng)); std::generate(v69.begin(), v69.end(), std::ref(f16rng)); std::generate(v70.begin(), v70.end(), std::ref(f16rng)); std::generate(v71.begin(), v71.end(), std::ref(f16rng)); std::generate(v72.begin(), v72.end(), std::ref(f16rng)); std::generate(v73.begin(), v73.end(), std::ref(f16rng)); std::generate(v74.begin(), v74.end(), std::ref(f16rng)); std::generate(v75.begin(), v75.end(), std::ref(f16rng)); std::generate(v76.begin(), v76.end(), std::ref(f16rng)); std::generate(v77.begin(), v77.end(), std::ref(f16rng)); std::generate(v78.begin(), v78.end(), std::ref(f16rng)); std::generate(v79.begin(), v79.end(), std::ref(f16rng)); std::generate(v80.begin(), v80.end(), std::ref(f16rng)); std::generate(v81.begin(), v81.end(), std::ref(f16rng)); std::generate(v82.begin(), v82.end(), std::ref(f16rng)); std::generate(v83.begin(), v83.end(), std::ref(f16rng)); std::generate(v84.begin(), v84.end(), std::ref(f16rng)); std::generate(v85.begin(), v85.end(), std::ref(f16rng)); std::generate(v86.begin(), v86.end(), std::ref(f16rng)); std::generate(v87.begin(), v87.end(), std::ref(f16rng)); std::generate(v88.begin(), v88.end(), std::ref(f16rng)); std::generate(v89.begin(), v89.end(), std::ref(f16rng)); std::generate(v90.begin(), v90.end(), std::ref(f16rng)); std::generate(v91.begin(), v91.end(), std::ref(f16rng)); std::generate(v92.begin(), v92.end(), std::ref(f16rng)); std::generate(v93.begin(), v93.end(), std::ref(f16rng)); std::generate(v94.begin(), v94.end(), std::ref(f16rng)); std::generate(v95.begin(), v95.end(), std::ref(f16rng)); std::generate(v96.begin(), v96.end(), std::ref(f16rng)); std::generate(v97.begin(), v97.end(), std::ref(f16rng)); std::generate(v98.begin(), v98.end(), std::ref(f16rng)); std::generate(v99.begin(), v99.end(), std::ref(f16rng)); std::generate(v100.begin(), v100.end(), std::ref(f16rng)); std::generate(v101.begin(), v101.end(), std::ref(f16rng)); std::generate(v102.begin(), v102.end(), std::ref(f16rng)); std::generate(v103.begin(), v103.end(), std::ref(f16rng)); std::generate(v104.begin(), v104.end(), std::ref(f16rng)); std::generate(v105.begin(), v105.end(), std::ref(f16rng)); std::generate(v106.begin(), v106.end(), std::ref(f16rng)); std::generate(v107.begin(), v107.end(), std::ref(f16rng)); std::generate(v108.begin(), v108.end(), std::ref(f16rng)); std::generate(v109.begin(), v109.end(), std::ref(f16rng)); std::generate(v110.begin(), v110.end(), std::ref(f16rng)); std::generate(v111.begin(), v111.end(), std::ref(f16rng)); std::generate(v112.begin(), v112.end(), std::ref(f16rng)); std::generate(v113.begin(), v113.end(), std::ref(f16rng)); std::generate(w114.begin(), w114.end(), std::ref(f16rng)); std::generate(w115.begin(), w115.end(), std::ref(f16rng)); std::generate(w116.begin(), w116.end(), std::ref(f16rng)); std::generate(w117.begin(), w117.end(), std::ref(f16rng)); std::generate(w118.begin(), w118.end(), std::ref(f16rng)); std::generate(w119.begin(), w119.end(), std::ref(f16rng)); std::generate(w120.begin(), w120.end(), std::ref(f16rng)); std::generate(w121.begin(), w121.end(), std::ref(f16rng)); std::generate(w122.begin(), w122.end(), std::ref(f16rng)); std::generate(w123.begin(), w123.end(), std::ref(f16rng)); std::generate(w124.begin(), w124.end(), std::ref(f16rng)); std::generate(w125.begin(), w125.end(), std::ref(f16rng)); std::generate(w126.begin(), w126.end(), std::ref(f16rng)); std::generate(w127.begin(), w127.end(), std::ref(f16rng)); std::generate(w128.begin(), w128.end(), std::ref(f16rng)); std::generate(w129.begin(), w129.end(), std::ref(f16rng)); std::generate(w130.begin(), w130.end(), std::ref(f16rng)); std::generate(w131.begin(), w131.end(), std::ref(f16rng)); std::generate(w132.begin(), w132.end(), std::ref(f16rng)); std::generate(w133.begin(), w133.end(), std::ref(f16rng)); std::generate(w134.begin(), w134.end(), std::ref(f16rng)); std::generate(w135.begin(), w135.end(), std::ref(f16rng)); std::generate(w136.begin(), w136.end(), std::ref(f16rng)); std::generate(w137.begin(), w137.end(), std::ref(f16rng)); std::generate(w138.begin(), w138.end(), std::ref(f16rng)); std::generate(w139.begin(), w139.end(), std::ref(f16rng)); std::generate(w140.begin(), w140.end(), std::ref(f16rng)); std::generate(w141.begin(), w141.end(), std::ref(f16rng)); std::generate(w142.begin(), w142.end(), std::ref(f16rng)); std::generate(w143.begin(), w143.end(), std::ref(f16rng)); std::generate(w144.begin(), w144.end(), std::ref(f16rng)); std::generate(w145.begin(), w145.end(), std::ref(f16rng)); std::generate(w146.begin(), w146.end(), std::ref(f16rng)); std::generate(w147.begin(), w147.end(), std::ref(f16rng)); std::generate(w148.begin(), w148.end(), std::ref(f16rng)); std::generate(w149.begin(), w149.end(), std::ref(f16rng)); std::generate(w150.begin(), w150.end(), std::ref(f16rng)); std::generate(w151.begin(), w151.end(), std::ref(f16rng)); std::generate(w152.begin(), w152.end(), std::ref(f16rng)); std::generate(w153.begin(), w153.end(), std::ref(f16rng)); std::generate(w154.begin(), w154.end(), std::ref(f16rng)); std::generate(w155.begin(), w155.end(), std::ref(f16rng)); std::generate(w156.begin(), w156.end(), std::ref(f16rng)); std::generate(w157.begin(), w157.end(), std::ref(f16rng)); std::generate(w158.begin(), w158.end(), std::ref(f16rng)); std::generate(w159.begin(), w159.end(), std::ref(f16rng)); std::generate(w160.begin(), w160.end(), std::ref(f16rng)); std::generate(w161.begin(), w161.end(), std::ref(f16rng)); std::generate(w162.begin(), w162.end(), std::ref(f16rng)); std::generate(w163.begin(), w163.end(), std::ref(f16rng)); std::generate(w164.begin(), w164.end(), std::ref(f16rng)); std::generate(w165.begin(), w165.end(), std::ref(f16rng)); std::generate(w166.begin(), w166.end(), std::ref(f16rng)); std::generate(w167.begin(), w167.end(), std::ref(f16rng)); std::generate(w168.begin(), w168.end(), std::ref(f16rng)); std::generate(w169.begin(), w169.end(), std::ref(f16rng)); std::generate(w170.begin(), w170.end(), std::ref(f16rng)); std::generate(w171.begin(), w171.end(), std::ref(f16rng)); std::generate(w172.begin(), w172.end(), std::ref(f16rng)); std::generate(w173.begin(), w173.end(), std::ref(f16rng)); std::generate(w174.begin(), w174.end(), std::ref(f16rng)); std::generate(w175.begin(), w175.end(), std::ref(f16rng)); std::generate(w176.begin(), w176.end(), std::ref(f16rng)); std::generate(w177.begin(), w177.end(), std::ref(f16rng)); std::generate(w178.begin(), w178.end(), std::ref(f16rng)); std::generate(w179.begin(), w179.end(), std::ref(f16rng)); std::generate(w180.begin(), w180.end(), std::ref(f16rng)); std::generate(w181.begin(), w181.end(), std::ref(f16rng)); std::generate(w182.begin(), w182.end(), std::ref(f16rng)); std::generate(w183.begin(), w183.end(), std::ref(f16rng)); std::generate(w184.begin(), w184.end(), std::ref(f16rng)); std::generate(w185.begin(), w185.end(), std::ref(f16rng)); std::generate(w186.begin(), w186.end(), std::ref(f16rng)); std::generate(w187.begin(), w187.end(), std::ref(f16rng)); std::generate(w188.begin(), w188.end(), std::ref(f16rng)); std::generate(w189.begin(), w189.end(), std::ref(f16rng)); std::generate(w190.begin(), w190.end(), std::ref(f16rng)); std::generate(w191.begin(), w191.end(), std::ref(f16rng)); std::generate(w192.begin(), w192.end(), std::ref(f16rng)); std::generate(w193.begin(), w193.end(), std::ref(f16rng)); std::generate(w194.begin(), w194.end(), std::ref(f16rng)); std::generate(w195.begin(), w195.end(), std::ref(f16rng)); std::generate(w196.begin(), w196.end(), std::ref(f16rng)); std::generate(w197.begin(), w197.end(), std::ref(f16rng)); std::generate(w198.begin(), w198.end(), std::ref(f16rng)); std::generate(w199.begin(), w199.end(), std::ref(f16rng)); std::generate(w200.begin(), w200.end(), std::ref(f16rng)); std::generate(w201.begin(), w201.end(), std::ref(f16rng)); std::generate(w202.begin(), w202.end(), std::ref(f16rng)); std::generate(w203.begin(), w203.end(), std::ref(f16rng)); std::generate(w204.begin(), w204.end(), std::ref(f16rng)); std::generate(w205.begin(), w205.end(), std::ref(f16rng)); std::generate(w206.begin(), w206.end(), std::ref(f16rng)); std::generate(w207.begin(), w207.end(), std::ref(f16rng)); std::generate(w208.begin(), w208.end(), std::ref(f16rng)); std::generate(w209.begin(), w209.end(), std::ref(f16rng)); std::generate(w210.begin(), w210.end(), std::ref(f16rng)); std::generate(w211.begin(), w211.end(), std::ref(f16rng)); std::generate(w212.begin(), w212.end(), std::ref(f16rng)); std::generate(w213.begin(), w213.end(), std::ref(f16rng)); std::generate(w214.begin(), w214.end(), std::ref(f16rng)); std::generate(w215.begin(), w215.end(), std::ref(f16rng)); std::generate(w216.begin(), w216.end(), std::ref(f16rng)); std::generate(w217.begin(), w217.end(), std::ref(f16rng)); std::generate(w218.begin(), w218.end(), std::ref(f16rng)); std::generate(w219.begin(), w219.end(), std::ref(f16rng)); std::generate(w220.begin(), w220.end(), std::ref(f16rng)); std::generate(w221.begin(), w221.end(), std::ref(f16rng)); std::generate(w222.begin(), w222.end(), std::ref(f16rng)); std::generate(w223.begin(), w223.end(), std::ref(f16rng)); std::generate(w224.begin(), w224.end(), std::ref(f16rng)); std::generate(w225.begin(), w225.end(), std::ref(f16rng)); std::generate(w226.begin(), w226.end(), std::ref(f16rng)); std::generate(w227.begin(), w227.end(), std::ref(f16rng)); std::generate(w228.begin(), w228.end(), std::ref(f16rng)); std::generate(w229.begin(), w229.end(), std::ref(f16rng)); std::generate(w230.begin(), w230.end(), std::ref(f16rng)); std::generate(w231.begin(), w231.end(), std::ref(f16rng)); std::generate(w232.begin(), w232.end(), std::ref(f16rng)); std::generate(w233.begin(), w233.end(), std::ref(f16rng)); std::generate(w234.begin(), w234.end(), std::ref(f16rng)); std::generate(w235.begin(), w235.end(), std::ref(f16rng)); std::generate(w236.begin(), w236.end(), std::ref(f16rng)); std::generate(w237.begin(), w237.end(), std::ref(f16rng)); std::generate(w238.begin(), w238.end(), std::ref(f16rng)); std::generate(w239.begin(), w239.end(), std::ref(f16rng)); std::generate(w240.begin(), w240.end(), std::ref(f16rng)); std::generate(w241.begin(), w241.end(), std::ref(f16rng)); ExecutionPlan operators; xnn_status status; xnn_code_cache* code_cache_ptr = nullptr; #if XNN_PLATFORM_JIT xnn_code_cache code_cache; if (use_jit) { status = xnn_init_code_cache(&code_cache); if (status != xnn_status_success) { std::cerr << "failed to initailize code cache" << std::endl; return ExecutionPlan(); } code_cache_ptr = &code_cache; } #endif // XNN_PLATFORM_JIT xnn_operator_t op0 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 1 /* right padding */, 1 /* bottom padding */, 0 /* left padding */, 3 /* kernel height */, 3 /* kernel width */, 2 /* subsampling height */, 2 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 3 /* input channels per group */, 16 /* output_channels_per_group */, 3 /* input pixel stride */, 16 /* output pixel stride */, w114.data(), w115.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op0); if (status != xnn_status_success) { std::cerr << "failed to create operation #0" << std::endl; return ExecutionPlan(); } operators.emplace_back(op0, xnn_delete_operator); xnn_operator_t op1 = nullptr; status = xnn_create_hardswish_nc_f16( 16 /* channels */, 16 /* input stride */, 16 /* output stride */, 0 /* flags */, &op1); if (status != xnn_status_success) { std::cerr << "failed to create operation #1" << std::endl; return ExecutionPlan(); } operators.emplace_back(op1, xnn_delete_operator); xnn_operator_t op2 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 1 /* top padding */, 1 /* right padding */, 1 /* bottom padding */, 1 /* left padding */, 3 /* kernel height */, 3 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 16 /* groups */, 1 /* input channels per group */, 1 /* output_channels_per_group */, 16 /* input pixel stride */, 16 /* output pixel stride */, w116.data(), w117.data(), 0.0f /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op2); if (status != xnn_status_success) { std::cerr << "failed to create operation #2" << std::endl; return ExecutionPlan(); } operators.emplace_back(op2, xnn_delete_operator); xnn_operator_t op3 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 16 /* input channels per group */, 16 /* output_channels_per_group */, 16 /* input pixel stride */, 16 /* output pixel stride */, w118.data(), w119.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op3); if (status != xnn_status_success) { std::cerr << "failed to create operation #3" << std::endl; return ExecutionPlan(); } operators.emplace_back(op3, xnn_delete_operator); xnn_operator_t op4 = nullptr; status = xnn_create_add_nd_f16( -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, &op4); if (status != xnn_status_success) { std::cerr << "failed to create operation #4" << std::endl; return ExecutionPlan(); } operators.emplace_back(op4, xnn_delete_operator); xnn_operator_t op5 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 16 /* input channels per group */, 64 /* output_channels_per_group */, 16 /* input pixel stride */, 64 /* output pixel stride */, w120.data(), w121.data(), 0.0f /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op5); if (status != xnn_status_success) { std::cerr << "failed to create operation #5" << std::endl; return ExecutionPlan(); } operators.emplace_back(op5, xnn_delete_operator); xnn_operator_t op6 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 1 /* right padding */, 1 /* bottom padding */, 0 /* left padding */, 3 /* kernel height */, 3 /* kernel width */, 2 /* subsampling height */, 2 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 64 /* groups */, 1 /* input channels per group */, 1 /* output_channels_per_group */, 64 /* input pixel stride */, 64 /* output pixel stride */, w122.data(), w123.data(), 0.0f /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op6); if (status != xnn_status_success) { std::cerr << "failed to create operation #6" << std::endl; return ExecutionPlan(); } operators.emplace_back(op6, xnn_delete_operator); xnn_operator_t op7 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 64 /* input channels per group */, 24 /* output_channels_per_group */, 64 /* input pixel stride */, 24 /* output pixel stride */, w124.data(), w125.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op7); if (status != xnn_status_success) { std::cerr << "failed to create operation #7" << std::endl; return ExecutionPlan(); } operators.emplace_back(op7, xnn_delete_operator); xnn_operator_t op8 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 24 /* input channels per group */, 72 /* output_channels_per_group */, 24 /* input pixel stride */, 72 /* output pixel stride */, w126.data(), w127.data(), 0.0f /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op8); if (status != xnn_status_success) { std::cerr << "failed to create operation #8" << std::endl; return ExecutionPlan(); } operators.emplace_back(op8, xnn_delete_operator); xnn_operator_t op9 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 1 /* top padding */, 1 /* right padding */, 1 /* bottom padding */, 1 /* left padding */, 3 /* kernel height */, 3 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 72 /* groups */, 1 /* input channels per group */, 1 /* output_channels_per_group */, 72 /* input pixel stride */, 72 /* output pixel stride */, w128.data(), w129.data(), 0.0f /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op9); if (status != xnn_status_success) { std::cerr << "failed to create operation #9" << std::endl; return ExecutionPlan(); } operators.emplace_back(op9, xnn_delete_operator); xnn_operator_t op10 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 72 /* input channels per group */, 24 /* output_channels_per_group */, 72 /* input pixel stride */, 24 /* output pixel stride */, w130.data(), w131.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op10); if (status != xnn_status_success) { std::cerr << "failed to create operation #10" << std::endl; return ExecutionPlan(); } operators.emplace_back(op10, xnn_delete_operator); xnn_operator_t op11 = nullptr; status = xnn_create_add_nd_f16( -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, &op11); if (status != xnn_status_success) { std::cerr << "failed to create operation #11" << std::endl; return ExecutionPlan(); } operators.emplace_back(op11, xnn_delete_operator); xnn_operator_t op12 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 24 /* input channels per group */, 72 /* output_channels_per_group */, 24 /* input pixel stride */, 72 /* output pixel stride */, w132.data(), w133.data(), 0.0f /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op12); if (status != xnn_status_success) { std::cerr << "failed to create operation #12" << std::endl; return ExecutionPlan(); } operators.emplace_back(op12, xnn_delete_operator); xnn_operator_t op13 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 1 /* top padding */, 2 /* right padding */, 2 /* bottom padding */, 1 /* left padding */, 5 /* kernel height */, 5 /* kernel width */, 2 /* subsampling height */, 2 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 72 /* groups */, 1 /* input channels per group */, 1 /* output_channels_per_group */, 72 /* input pixel stride */, 72 /* output pixel stride */, w134.data(), w135.data(), 0.0f /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op13); if (status != xnn_status_success) { std::cerr << "failed to create operation #13" << std::endl; return ExecutionPlan(); } operators.emplace_back(op13, xnn_delete_operator); xnn_operator_t op14 = nullptr; status = xnn_create_global_average_pooling_nwc_f16( 72 /* channels */, 72 /* input stride */, 72 /* output stride */, -std::numeric_limits::infinity(), std::numeric_limits::infinity(), 0 /* flags */, &op14); if (status != xnn_status_success) { std::cerr << "failed to create operation #14" << std::endl; return ExecutionPlan(); } operators.emplace_back(op14, xnn_delete_operator); xnn_operator_t op15 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 72 /* input channels per group */, 24 /* output_channels_per_group */, 72 /* input pixel stride */, 24 /* output pixel stride */, w136.data(), w137.data(), 0.0f /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op15); if (status != xnn_status_success) { std::cerr << "failed to create operation #15" << std::endl; return ExecutionPlan(); } operators.emplace_back(op15, xnn_delete_operator); xnn_operator_t op16 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 24 /* input channels per group */, 72 /* output_channels_per_group */, 24 /* input pixel stride */, 72 /* output pixel stride */, w138.data(), w139.data(), 0.0f /* output min */, +0x1.00014Fp+0 /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op16); if (status != xnn_status_success) { std::cerr << "failed to create operation #16" << std::endl; return ExecutionPlan(); } operators.emplace_back(op16, xnn_delete_operator); xnn_operator_t op17 = nullptr; status = xnn_create_multiply_nd_f16( -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, &op17); if (status != xnn_status_success) { std::cerr << "failed to create operation #17" << std::endl; return ExecutionPlan(); } operators.emplace_back(op17, xnn_delete_operator); xnn_operator_t op18 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 72 /* input channels per group */, 40 /* output_channels_per_group */, 72 /* input pixel stride */, 40 /* output pixel stride */, w140.data(), w141.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op18); if (status != xnn_status_success) { std::cerr << "failed to create operation #18" << std::endl; return ExecutionPlan(); } operators.emplace_back(op18, xnn_delete_operator); xnn_operator_t op19 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 40 /* input channels per group */, 120 /* output_channels_per_group */, 40 /* input pixel stride */, 120 /* output pixel stride */, w142.data(), w143.data(), 0.0f /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op19); if (status != xnn_status_success) { std::cerr << "failed to create operation #19" << std::endl; return ExecutionPlan(); } operators.emplace_back(op19, xnn_delete_operator); xnn_operator_t op20 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 2 /* top padding */, 2 /* right padding */, 2 /* bottom padding */, 2 /* left padding */, 5 /* kernel height */, 5 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 120 /* groups */, 1 /* input channels per group */, 1 /* output_channels_per_group */, 120 /* input pixel stride */, 120 /* output pixel stride */, w144.data(), w145.data(), 0.0f /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op20); if (status != xnn_status_success) { std::cerr << "failed to create operation #20" << std::endl; return ExecutionPlan(); } operators.emplace_back(op20, xnn_delete_operator); xnn_operator_t op21 = nullptr; status = xnn_create_global_average_pooling_nwc_f16( 120 /* channels */, 120 /* input stride */, 120 /* output stride */, -std::numeric_limits::infinity(), std::numeric_limits::infinity(), 0 /* flags */, &op21); if (status != xnn_status_success) { std::cerr << "failed to create operation #21" << std::endl; return ExecutionPlan(); } operators.emplace_back(op21, xnn_delete_operator); xnn_operator_t op22 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 120 /* input channels per group */, 32 /* output_channels_per_group */, 120 /* input pixel stride */, 32 /* output pixel stride */, w146.data(), w147.data(), 0.0f /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op22); if (status != xnn_status_success) { std::cerr << "failed to create operation #22" << std::endl; return ExecutionPlan(); } operators.emplace_back(op22, xnn_delete_operator); xnn_operator_t op23 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 32 /* input channels per group */, 120 /* output_channels_per_group */, 32 /* input pixel stride */, 120 /* output pixel stride */, w148.data(), w149.data(), 0.0f /* output min */, +0x1.00014Fp+0 /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op23); if (status != xnn_status_success) { std::cerr << "failed to create operation #23" << std::endl; return ExecutionPlan(); } operators.emplace_back(op23, xnn_delete_operator); xnn_operator_t op24 = nullptr; status = xnn_create_multiply_nd_f16( -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, &op24); if (status != xnn_status_success) { std::cerr << "failed to create operation #24" << std::endl; return ExecutionPlan(); } operators.emplace_back(op24, xnn_delete_operator); xnn_operator_t op25 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 120 /* input channels per group */, 40 /* output_channels_per_group */, 120 /* input pixel stride */, 40 /* output pixel stride */, w150.data(), w151.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op25); if (status != xnn_status_success) { std::cerr << "failed to create operation #25" << std::endl; return ExecutionPlan(); } operators.emplace_back(op25, xnn_delete_operator); xnn_operator_t op26 = nullptr; status = xnn_create_add_nd_f16( -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, &op26); if (status != xnn_status_success) { std::cerr << "failed to create operation #26" << std::endl; return ExecutionPlan(); } operators.emplace_back(op26, xnn_delete_operator); xnn_operator_t op27 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 40 /* input channels per group */, 120 /* output_channels_per_group */, 40 /* input pixel stride */, 120 /* output pixel stride */, w152.data(), w153.data(), 0.0f /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op27); if (status != xnn_status_success) { std::cerr << "failed to create operation #27" << std::endl; return ExecutionPlan(); } operators.emplace_back(op27, xnn_delete_operator); xnn_operator_t op28 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 2 /* top padding */, 2 /* right padding */, 2 /* bottom padding */, 2 /* left padding */, 5 /* kernel height */, 5 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 120 /* groups */, 1 /* input channels per group */, 1 /* output_channels_per_group */, 120 /* input pixel stride */, 120 /* output pixel stride */, w154.data(), w155.data(), 0.0f /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op28); if (status != xnn_status_success) { std::cerr << "failed to create operation #28" << std::endl; return ExecutionPlan(); } operators.emplace_back(op28, xnn_delete_operator); xnn_operator_t op29 = nullptr; status = xnn_create_global_average_pooling_nwc_f16( 120 /* channels */, 120 /* input stride */, 120 /* output stride */, -std::numeric_limits::infinity(), std::numeric_limits::infinity(), 0 /* flags */, &op29); if (status != xnn_status_success) { std::cerr << "failed to create operation #29" << std::endl; return ExecutionPlan(); } operators.emplace_back(op29, xnn_delete_operator); xnn_operator_t op30 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 120 /* input channels per group */, 32 /* output_channels_per_group */, 120 /* input pixel stride */, 32 /* output pixel stride */, w156.data(), w157.data(), 0.0f /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op30); if (status != xnn_status_success) { std::cerr << "failed to create operation #30" << std::endl; return ExecutionPlan(); } operators.emplace_back(op30, xnn_delete_operator); xnn_operator_t op31 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 32 /* input channels per group */, 120 /* output_channels_per_group */, 32 /* input pixel stride */, 120 /* output pixel stride */, w158.data(), w159.data(), 0.0f /* output min */, +0x1.00014Fp+0 /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op31); if (status != xnn_status_success) { std::cerr << "failed to create operation #31" << std::endl; return ExecutionPlan(); } operators.emplace_back(op31, xnn_delete_operator); xnn_operator_t op32 = nullptr; status = xnn_create_multiply_nd_f16( -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, &op32); if (status != xnn_status_success) { std::cerr << "failed to create operation #32" << std::endl; return ExecutionPlan(); } operators.emplace_back(op32, xnn_delete_operator); xnn_operator_t op33 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 120 /* input channels per group */, 40 /* output_channels_per_group */, 120 /* input pixel stride */, 40 /* output pixel stride */, w160.data(), w161.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op33); if (status != xnn_status_success) { std::cerr << "failed to create operation #33" << std::endl; return ExecutionPlan(); } operators.emplace_back(op33, xnn_delete_operator); xnn_operator_t op34 = nullptr; status = xnn_create_add_nd_f16( -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, &op34); if (status != xnn_status_success) { std::cerr << "failed to create operation #34" << std::endl; return ExecutionPlan(); } operators.emplace_back(op34, xnn_delete_operator); xnn_operator_t op35 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 40 /* input channels per group */, 240 /* output_channels_per_group */, 40 /* input pixel stride */, 240 /* output pixel stride */, w162.data(), w163.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op35); if (status != xnn_status_success) { std::cerr << "failed to create operation #35" << std::endl; return ExecutionPlan(); } operators.emplace_back(op35, xnn_delete_operator); xnn_operator_t op36 = nullptr; status = xnn_create_hardswish_nc_f16( 240 /* channels */, 240 /* input stride */, 240 /* output stride */, 0 /* flags */, &op36); if (status != xnn_status_success) { std::cerr << "failed to create operation #36" << std::endl; return ExecutionPlan(); } operators.emplace_back(op36, xnn_delete_operator); xnn_operator_t op37 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 1 /* right padding */, 1 /* bottom padding */, 0 /* left padding */, 3 /* kernel height */, 3 /* kernel width */, 2 /* subsampling height */, 2 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 240 /* groups */, 1 /* input channels per group */, 1 /* output_channels_per_group */, 240 /* input pixel stride */, 240 /* output pixel stride */, w164.data(), w165.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op37); if (status != xnn_status_success) { std::cerr << "failed to create operation #37" << std::endl; return ExecutionPlan(); } operators.emplace_back(op37, xnn_delete_operator); xnn_operator_t op38 = nullptr; status = xnn_create_hardswish_nc_f16( 240 /* channels */, 240 /* input stride */, 240 /* output stride */, 0 /* flags */, &op38); if (status != xnn_status_success) { std::cerr << "failed to create operation #38" << std::endl; return ExecutionPlan(); } operators.emplace_back(op38, xnn_delete_operator); xnn_operator_t op39 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 240 /* input channels per group */, 80 /* output_channels_per_group */, 240 /* input pixel stride */, 80 /* output pixel stride */, w166.data(), w167.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op39); if (status != xnn_status_success) { std::cerr << "failed to create operation #39" << std::endl; return ExecutionPlan(); } operators.emplace_back(op39, xnn_delete_operator); xnn_operator_t op40 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 80 /* input channels per group */, 200 /* output_channels_per_group */, 80 /* input pixel stride */, 200 /* output pixel stride */, w168.data(), w169.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op40); if (status != xnn_status_success) { std::cerr << "failed to create operation #40" << std::endl; return ExecutionPlan(); } operators.emplace_back(op40, xnn_delete_operator); xnn_operator_t op41 = nullptr; status = xnn_create_hardswish_nc_f16( 200 /* channels */, 200 /* input stride */, 200 /* output stride */, 0 /* flags */, &op41); if (status != xnn_status_success) { std::cerr << "failed to create operation #41" << std::endl; return ExecutionPlan(); } operators.emplace_back(op41, xnn_delete_operator); xnn_operator_t op42 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 1 /* top padding */, 1 /* right padding */, 1 /* bottom padding */, 1 /* left padding */, 3 /* kernel height */, 3 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 200 /* groups */, 1 /* input channels per group */, 1 /* output_channels_per_group */, 200 /* input pixel stride */, 200 /* output pixel stride */, w170.data(), w171.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op42); if (status != xnn_status_success) { std::cerr << "failed to create operation #42" << std::endl; return ExecutionPlan(); } operators.emplace_back(op42, xnn_delete_operator); xnn_operator_t op43 = nullptr; status = xnn_create_hardswish_nc_f16( 200 /* channels */, 200 /* input stride */, 200 /* output stride */, 0 /* flags */, &op43); if (status != xnn_status_success) { std::cerr << "failed to create operation #43" << std::endl; return ExecutionPlan(); } operators.emplace_back(op43, xnn_delete_operator); xnn_operator_t op44 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 200 /* input channels per group */, 80 /* output_channels_per_group */, 200 /* input pixel stride */, 80 /* output pixel stride */, w172.data(), w173.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op44); if (status != xnn_status_success) { std::cerr << "failed to create operation #44" << std::endl; return ExecutionPlan(); } operators.emplace_back(op44, xnn_delete_operator); xnn_operator_t op45 = nullptr; status = xnn_create_add_nd_f16( -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, &op45); if (status != xnn_status_success) { std::cerr << "failed to create operation #45" << std::endl; return ExecutionPlan(); } operators.emplace_back(op45, xnn_delete_operator); xnn_operator_t op46 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 80 /* input channels per group */, 184 /* output_channels_per_group */, 80 /* input pixel stride */, 184 /* output pixel stride */, w174.data(), w175.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op46); if (status != xnn_status_success) { std::cerr << "failed to create operation #46" << std::endl; return ExecutionPlan(); } operators.emplace_back(op46, xnn_delete_operator); xnn_operator_t op47 = nullptr; status = xnn_create_hardswish_nc_f16( 184 /* channels */, 184 /* input stride */, 184 /* output stride */, 0 /* flags */, &op47); if (status != xnn_status_success) { std::cerr << "failed to create operation #47" << std::endl; return ExecutionPlan(); } operators.emplace_back(op47, xnn_delete_operator); xnn_operator_t op48 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 1 /* top padding */, 1 /* right padding */, 1 /* bottom padding */, 1 /* left padding */, 3 /* kernel height */, 3 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 184 /* groups */, 1 /* input channels per group */, 1 /* output_channels_per_group */, 184 /* input pixel stride */, 184 /* output pixel stride */, w176.data(), w177.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op48); if (status != xnn_status_success) { std::cerr << "failed to create operation #48" << std::endl; return ExecutionPlan(); } operators.emplace_back(op48, xnn_delete_operator); xnn_operator_t op49 = nullptr; status = xnn_create_hardswish_nc_f16( 184 /* channels */, 184 /* input stride */, 184 /* output stride */, 0 /* flags */, &op49); if (status != xnn_status_success) { std::cerr << "failed to create operation #49" << std::endl; return ExecutionPlan(); } operators.emplace_back(op49, xnn_delete_operator); xnn_operator_t op50 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 184 /* input channels per group */, 80 /* output_channels_per_group */, 184 /* input pixel stride */, 80 /* output pixel stride */, w178.data(), w179.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op50); if (status != xnn_status_success) { std::cerr << "failed to create operation #50" << std::endl; return ExecutionPlan(); } operators.emplace_back(op50, xnn_delete_operator); xnn_operator_t op51 = nullptr; status = xnn_create_add_nd_f16( -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, &op51); if (status != xnn_status_success) { std::cerr << "failed to create operation #51" << std::endl; return ExecutionPlan(); } operators.emplace_back(op51, xnn_delete_operator); xnn_operator_t op52 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 80 /* input channels per group */, 184 /* output_channels_per_group */, 80 /* input pixel stride */, 184 /* output pixel stride */, w180.data(), w181.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op52); if (status != xnn_status_success) { std::cerr << "failed to create operation #52" << std::endl; return ExecutionPlan(); } operators.emplace_back(op52, xnn_delete_operator); xnn_operator_t op53 = nullptr; status = xnn_create_hardswish_nc_f16( 184 /* channels */, 184 /* input stride */, 184 /* output stride */, 0 /* flags */, &op53); if (status != xnn_status_success) { std::cerr << "failed to create operation #53" << std::endl; return ExecutionPlan(); } operators.emplace_back(op53, xnn_delete_operator); xnn_operator_t op54 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 1 /* top padding */, 1 /* right padding */, 1 /* bottom padding */, 1 /* left padding */, 3 /* kernel height */, 3 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 184 /* groups */, 1 /* input channels per group */, 1 /* output_channels_per_group */, 184 /* input pixel stride */, 184 /* output pixel stride */, w182.data(), w183.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op54); if (status != xnn_status_success) { std::cerr << "failed to create operation #54" << std::endl; return ExecutionPlan(); } operators.emplace_back(op54, xnn_delete_operator); xnn_operator_t op55 = nullptr; status = xnn_create_hardswish_nc_f16( 184 /* channels */, 184 /* input stride */, 184 /* output stride */, 0 /* flags */, &op55); if (status != xnn_status_success) { std::cerr << "failed to create operation #55" << std::endl; return ExecutionPlan(); } operators.emplace_back(op55, xnn_delete_operator); xnn_operator_t op56 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 184 /* input channels per group */, 80 /* output_channels_per_group */, 184 /* input pixel stride */, 80 /* output pixel stride */, w184.data(), w185.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op56); if (status != xnn_status_success) { std::cerr << "failed to create operation #56" << std::endl; return ExecutionPlan(); } operators.emplace_back(op56, xnn_delete_operator); xnn_operator_t op57 = nullptr; status = xnn_create_add_nd_f16( -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, &op57); if (status != xnn_status_success) { std::cerr << "failed to create operation #57" << std::endl; return ExecutionPlan(); } operators.emplace_back(op57, xnn_delete_operator); xnn_operator_t op58 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 80 /* input channels per group */, 480 /* output_channels_per_group */, 80 /* input pixel stride */, 480 /* output pixel stride */, w186.data(), w187.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op58); if (status != xnn_status_success) { std::cerr << "failed to create operation #58" << std::endl; return ExecutionPlan(); } operators.emplace_back(op58, xnn_delete_operator); xnn_operator_t op59 = nullptr; status = xnn_create_hardswish_nc_f16( 480 /* channels */, 480 /* input stride */, 480 /* output stride */, 0 /* flags */, &op59); if (status != xnn_status_success) { std::cerr << "failed to create operation #59" << std::endl; return ExecutionPlan(); } operators.emplace_back(op59, xnn_delete_operator); xnn_operator_t op60 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 1 /* top padding */, 1 /* right padding */, 1 /* bottom padding */, 1 /* left padding */, 3 /* kernel height */, 3 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 480 /* groups */, 1 /* input channels per group */, 1 /* output_channels_per_group */, 480 /* input pixel stride */, 480 /* output pixel stride */, w188.data(), w189.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op60); if (status != xnn_status_success) { std::cerr << "failed to create operation #60" << std::endl; return ExecutionPlan(); } operators.emplace_back(op60, xnn_delete_operator); xnn_operator_t op61 = nullptr; status = xnn_create_hardswish_nc_f16( 480 /* channels */, 480 /* input stride */, 480 /* output stride */, 0 /* flags */, &op61); if (status != xnn_status_success) { std::cerr << "failed to create operation #61" << std::endl; return ExecutionPlan(); } operators.emplace_back(op61, xnn_delete_operator); xnn_operator_t op62 = nullptr; status = xnn_create_global_average_pooling_nwc_f16( 480 /* channels */, 480 /* input stride */, 480 /* output stride */, -std::numeric_limits::infinity(), std::numeric_limits::infinity(), 0 /* flags */, &op62); if (status != xnn_status_success) { std::cerr << "failed to create operation #62" << std::endl; return ExecutionPlan(); } operators.emplace_back(op62, xnn_delete_operator); xnn_operator_t op63 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 480 /* input channels per group */, 120 /* output_channels_per_group */, 480 /* input pixel stride */, 120 /* output pixel stride */, w190.data(), w191.data(), 0.0f /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op63); if (status != xnn_status_success) { std::cerr << "failed to create operation #63" << std::endl; return ExecutionPlan(); } operators.emplace_back(op63, xnn_delete_operator); xnn_operator_t op64 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 120 /* input channels per group */, 480 /* output_channels_per_group */, 120 /* input pixel stride */, 480 /* output pixel stride */, w192.data(), w193.data(), 0.0f /* output min */, +0x1.00014Fp+0 /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op64); if (status != xnn_status_success) { std::cerr << "failed to create operation #64" << std::endl; return ExecutionPlan(); } operators.emplace_back(op64, xnn_delete_operator); xnn_operator_t op65 = nullptr; status = xnn_create_multiply_nd_f16( -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, &op65); if (status != xnn_status_success) { std::cerr << "failed to create operation #65" << std::endl; return ExecutionPlan(); } operators.emplace_back(op65, xnn_delete_operator); xnn_operator_t op66 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 480 /* input channels per group */, 112 /* output_channels_per_group */, 480 /* input pixel stride */, 112 /* output pixel stride */, w194.data(), w195.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op66); if (status != xnn_status_success) { std::cerr << "failed to create operation #66" << std::endl; return ExecutionPlan(); } operators.emplace_back(op66, xnn_delete_operator); xnn_operator_t op67 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 112 /* input channels per group */, 672 /* output_channels_per_group */, 112 /* input pixel stride */, 672 /* output pixel stride */, w196.data(), w197.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op67); if (status != xnn_status_success) { std::cerr << "failed to create operation #67" << std::endl; return ExecutionPlan(); } operators.emplace_back(op67, xnn_delete_operator); xnn_operator_t op68 = nullptr; status = xnn_create_hardswish_nc_f16( 672 /* channels */, 672 /* input stride */, 672 /* output stride */, 0 /* flags */, &op68); if (status != xnn_status_success) { std::cerr << "failed to create operation #68" << std::endl; return ExecutionPlan(); } operators.emplace_back(op68, xnn_delete_operator); xnn_operator_t op69 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 1 /* top padding */, 1 /* right padding */, 1 /* bottom padding */, 1 /* left padding */, 3 /* kernel height */, 3 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 672 /* groups */, 1 /* input channels per group */, 1 /* output_channels_per_group */, 672 /* input pixel stride */, 672 /* output pixel stride */, w198.data(), w199.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op69); if (status != xnn_status_success) { std::cerr << "failed to create operation #69" << std::endl; return ExecutionPlan(); } operators.emplace_back(op69, xnn_delete_operator); xnn_operator_t op70 = nullptr; status = xnn_create_hardswish_nc_f16( 672 /* channels */, 672 /* input stride */, 672 /* output stride */, 0 /* flags */, &op70); if (status != xnn_status_success) { std::cerr << "failed to create operation #70" << std::endl; return ExecutionPlan(); } operators.emplace_back(op70, xnn_delete_operator); xnn_operator_t op71 = nullptr; status = xnn_create_global_average_pooling_nwc_f16( 672 /* channels */, 672 /* input stride */, 672 /* output stride */, -std::numeric_limits::infinity(), std::numeric_limits::infinity(), 0 /* flags */, &op71); if (status != xnn_status_success) { std::cerr << "failed to create operation #71" << std::endl; return ExecutionPlan(); } operators.emplace_back(op71, xnn_delete_operator); xnn_operator_t op72 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 672 /* input channels per group */, 168 /* output_channels_per_group */, 672 /* input pixel stride */, 168 /* output pixel stride */, w200.data(), w201.data(), 0.0f /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op72); if (status != xnn_status_success) { std::cerr << "failed to create operation #72" << std::endl; return ExecutionPlan(); } operators.emplace_back(op72, xnn_delete_operator); xnn_operator_t op73 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 168 /* input channels per group */, 672 /* output_channels_per_group */, 168 /* input pixel stride */, 672 /* output pixel stride */, w202.data(), w203.data(), 0.0f /* output min */, +0x1.00014Fp+0 /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op73); if (status != xnn_status_success) { std::cerr << "failed to create operation #73" << std::endl; return ExecutionPlan(); } operators.emplace_back(op73, xnn_delete_operator); xnn_operator_t op74 = nullptr; status = xnn_create_multiply_nd_f16( -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, &op74); if (status != xnn_status_success) { std::cerr << "failed to create operation #74" << std::endl; return ExecutionPlan(); } operators.emplace_back(op74, xnn_delete_operator); xnn_operator_t op75 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 672 /* input channels per group */, 112 /* output_channels_per_group */, 672 /* input pixel stride */, 112 /* output pixel stride */, w204.data(), w205.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op75); if (status != xnn_status_success) { std::cerr << "failed to create operation #75" << std::endl; return ExecutionPlan(); } operators.emplace_back(op75, xnn_delete_operator); xnn_operator_t op76 = nullptr; status = xnn_create_add_nd_f16( -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, &op76); if (status != xnn_status_success) { std::cerr << "failed to create operation #76" << std::endl; return ExecutionPlan(); } operators.emplace_back(op76, xnn_delete_operator); xnn_operator_t op77 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 112 /* input channels per group */, 672 /* output_channels_per_group */, 112 /* input pixel stride */, 672 /* output pixel stride */, w206.data(), w207.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op77); if (status != xnn_status_success) { std::cerr << "failed to create operation #77" << std::endl; return ExecutionPlan(); } operators.emplace_back(op77, xnn_delete_operator); xnn_operator_t op78 = nullptr; status = xnn_create_hardswish_nc_f16( 672 /* channels */, 672 /* input stride */, 672 /* output stride */, 0 /* flags */, &op78); if (status != xnn_status_success) { std::cerr << "failed to create operation #78" << std::endl; return ExecutionPlan(); } operators.emplace_back(op78, xnn_delete_operator); xnn_operator_t op79 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 1 /* top padding */, 2 /* right padding */, 2 /* bottom padding */, 1 /* left padding */, 5 /* kernel height */, 5 /* kernel width */, 2 /* subsampling height */, 2 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 672 /* groups */, 1 /* input channels per group */, 1 /* output_channels_per_group */, 672 /* input pixel stride */, 672 /* output pixel stride */, w208.data(), w209.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op79); if (status != xnn_status_success) { std::cerr << "failed to create operation #79" << std::endl; return ExecutionPlan(); } operators.emplace_back(op79, xnn_delete_operator); xnn_operator_t op80 = nullptr; status = xnn_create_hardswish_nc_f16( 672 /* channels */, 672 /* input stride */, 672 /* output stride */, 0 /* flags */, &op80); if (status != xnn_status_success) { std::cerr << "failed to create operation #80" << std::endl; return ExecutionPlan(); } operators.emplace_back(op80, xnn_delete_operator); xnn_operator_t op81 = nullptr; status = xnn_create_global_average_pooling_nwc_f16( 672 /* channels */, 672 /* input stride */, 672 /* output stride */, -std::numeric_limits::infinity(), std::numeric_limits::infinity(), 0 /* flags */, &op81); if (status != xnn_status_success) { std::cerr << "failed to create operation #81" << std::endl; return ExecutionPlan(); } operators.emplace_back(op81, xnn_delete_operator); xnn_operator_t op82 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 672 /* input channels per group */, 168 /* output_channels_per_group */, 672 /* input pixel stride */, 168 /* output pixel stride */, w210.data(), w211.data(), 0.0f /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op82); if (status != xnn_status_success) { std::cerr << "failed to create operation #82" << std::endl; return ExecutionPlan(); } operators.emplace_back(op82, xnn_delete_operator); xnn_operator_t op83 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 168 /* input channels per group */, 672 /* output_channels_per_group */, 168 /* input pixel stride */, 672 /* output pixel stride */, w212.data(), w213.data(), 0.0f /* output min */, +0x1.00014Fp+0 /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op83); if (status != xnn_status_success) { std::cerr << "failed to create operation #83" << std::endl; return ExecutionPlan(); } operators.emplace_back(op83, xnn_delete_operator); xnn_operator_t op84 = nullptr; status = xnn_create_multiply_nd_f16( -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, &op84); if (status != xnn_status_success) { std::cerr << "failed to create operation #84" << std::endl; return ExecutionPlan(); } operators.emplace_back(op84, xnn_delete_operator); xnn_operator_t op85 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 672 /* input channels per group */, 160 /* output_channels_per_group */, 672 /* input pixel stride */, 160 /* output pixel stride */, w214.data(), w215.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op85); if (status != xnn_status_success) { std::cerr << "failed to create operation #85" << std::endl; return ExecutionPlan(); } operators.emplace_back(op85, xnn_delete_operator); xnn_operator_t op86 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 160 /* input channels per group */, 960 /* output_channels_per_group */, 160 /* input pixel stride */, 960 /* output pixel stride */, w216.data(), w217.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op86); if (status != xnn_status_success) { std::cerr << "failed to create operation #86" << std::endl; return ExecutionPlan(); } operators.emplace_back(op86, xnn_delete_operator); xnn_operator_t op87 = nullptr; status = xnn_create_hardswish_nc_f16( 960 /* channels */, 960 /* input stride */, 960 /* output stride */, 0 /* flags */, &op87); if (status != xnn_status_success) { std::cerr << "failed to create operation #87" << std::endl; return ExecutionPlan(); } operators.emplace_back(op87, xnn_delete_operator); xnn_operator_t op88 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 2 /* top padding */, 2 /* right padding */, 2 /* bottom padding */, 2 /* left padding */, 5 /* kernel height */, 5 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 960 /* groups */, 1 /* input channels per group */, 1 /* output_channels_per_group */, 960 /* input pixel stride */, 960 /* output pixel stride */, w218.data(), w219.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op88); if (status != xnn_status_success) { std::cerr << "failed to create operation #88" << std::endl; return ExecutionPlan(); } operators.emplace_back(op88, xnn_delete_operator); xnn_operator_t op89 = nullptr; status = xnn_create_hardswish_nc_f16( 960 /* channels */, 960 /* input stride */, 960 /* output stride */, 0 /* flags */, &op89); if (status != xnn_status_success) { std::cerr << "failed to create operation #89" << std::endl; return ExecutionPlan(); } operators.emplace_back(op89, xnn_delete_operator); xnn_operator_t op90 = nullptr; status = xnn_create_global_average_pooling_nwc_f16( 960 /* channels */, 960 /* input stride */, 960 /* output stride */, -std::numeric_limits::infinity(), std::numeric_limits::infinity(), 0 /* flags */, &op90); if (status != xnn_status_success) { std::cerr << "failed to create operation #90" << std::endl; return ExecutionPlan(); } operators.emplace_back(op90, xnn_delete_operator); xnn_operator_t op91 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 960 /* input channels per group */, 240 /* output_channels_per_group */, 960 /* input pixel stride */, 240 /* output pixel stride */, w220.data(), w221.data(), 0.0f /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op91); if (status != xnn_status_success) { std::cerr << "failed to create operation #91" << std::endl; return ExecutionPlan(); } operators.emplace_back(op91, xnn_delete_operator); xnn_operator_t op92 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 240 /* input channels per group */, 960 /* output_channels_per_group */, 240 /* input pixel stride */, 960 /* output pixel stride */, w222.data(), w223.data(), 0.0f /* output min */, +0x1.00014Fp+0 /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op92); if (status != xnn_status_success) { std::cerr << "failed to create operation #92" << std::endl; return ExecutionPlan(); } operators.emplace_back(op92, xnn_delete_operator); xnn_operator_t op93 = nullptr; status = xnn_create_multiply_nd_f16( -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, &op93); if (status != xnn_status_success) { std::cerr << "failed to create operation #93" << std::endl; return ExecutionPlan(); } operators.emplace_back(op93, xnn_delete_operator); xnn_operator_t op94 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 960 /* input channels per group */, 160 /* output_channels_per_group */, 960 /* input pixel stride */, 160 /* output pixel stride */, w224.data(), w225.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op94); if (status != xnn_status_success) { std::cerr << "failed to create operation #94" << std::endl; return ExecutionPlan(); } operators.emplace_back(op94, xnn_delete_operator); xnn_operator_t op95 = nullptr; status = xnn_create_add_nd_f16( -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, &op95); if (status != xnn_status_success) { std::cerr << "failed to create operation #95" << std::endl; return ExecutionPlan(); } operators.emplace_back(op95, xnn_delete_operator); xnn_operator_t op96 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 160 /* input channels per group */, 960 /* output_channels_per_group */, 160 /* input pixel stride */, 960 /* output pixel stride */, w226.data(), w227.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op96); if (status != xnn_status_success) { std::cerr << "failed to create operation #96" << std::endl; return ExecutionPlan(); } operators.emplace_back(op96, xnn_delete_operator); xnn_operator_t op97 = nullptr; status = xnn_create_hardswish_nc_f16( 960 /* channels */, 960 /* input stride */, 960 /* output stride */, 0 /* flags */, &op97); if (status != xnn_status_success) { std::cerr << "failed to create operation #97" << std::endl; return ExecutionPlan(); } operators.emplace_back(op97, xnn_delete_operator); xnn_operator_t op98 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 2 /* top padding */, 2 /* right padding */, 2 /* bottom padding */, 2 /* left padding */, 5 /* kernel height */, 5 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 960 /* groups */, 1 /* input channels per group */, 1 /* output_channels_per_group */, 960 /* input pixel stride */, 960 /* output pixel stride */, w228.data(), w229.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op98); if (status != xnn_status_success) { std::cerr << "failed to create operation #98" << std::endl; return ExecutionPlan(); } operators.emplace_back(op98, xnn_delete_operator); xnn_operator_t op99 = nullptr; status = xnn_create_hardswish_nc_f16( 960 /* channels */, 960 /* input stride */, 960 /* output stride */, 0 /* flags */, &op99); if (status != xnn_status_success) { std::cerr << "failed to create operation #99" << std::endl; return ExecutionPlan(); } operators.emplace_back(op99, xnn_delete_operator); xnn_operator_t op100 = nullptr; status = xnn_create_global_average_pooling_nwc_f16( 960 /* channels */, 960 /* input stride */, 960 /* output stride */, -std::numeric_limits::infinity(), std::numeric_limits::infinity(), 0 /* flags */, &op100); if (status != xnn_status_success) { std::cerr << "failed to create operation #100" << std::endl; return ExecutionPlan(); } operators.emplace_back(op100, xnn_delete_operator); xnn_operator_t op101 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 960 /* input channels per group */, 240 /* output_channels_per_group */, 960 /* input pixel stride */, 240 /* output pixel stride */, w230.data(), w231.data(), 0.0f /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op101); if (status != xnn_status_success) { std::cerr << "failed to create operation #101" << std::endl; return ExecutionPlan(); } operators.emplace_back(op101, xnn_delete_operator); xnn_operator_t op102 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 240 /* input channels per group */, 960 /* output_channels_per_group */, 240 /* input pixel stride */, 960 /* output pixel stride */, w232.data(), w233.data(), 0.0f /* output min */, +0x1.00014Fp+0 /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op102); if (status != xnn_status_success) { std::cerr << "failed to create operation #102" << std::endl; return ExecutionPlan(); } operators.emplace_back(op102, xnn_delete_operator); xnn_operator_t op103 = nullptr; status = xnn_create_multiply_nd_f16( -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, &op103); if (status != xnn_status_success) { std::cerr << "failed to create operation #103" << std::endl; return ExecutionPlan(); } operators.emplace_back(op103, xnn_delete_operator); xnn_operator_t op104 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 960 /* input channels per group */, 160 /* output_channels_per_group */, 960 /* input pixel stride */, 160 /* output pixel stride */, w234.data(), w235.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op104); if (status != xnn_status_success) { std::cerr << "failed to create operation #104" << std::endl; return ExecutionPlan(); } operators.emplace_back(op104, xnn_delete_operator); xnn_operator_t op105 = nullptr; status = xnn_create_add_nd_f16( -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, &op105); if (status != xnn_status_success) { std::cerr << "failed to create operation #105" << std::endl; return ExecutionPlan(); } operators.emplace_back(op105, xnn_delete_operator); xnn_operator_t op106 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 160 /* input channels per group */, 960 /* output_channels_per_group */, 160 /* input pixel stride */, 960 /* output pixel stride */, w236.data(), w237.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op106); if (status != xnn_status_success) { std::cerr << "failed to create operation #106" << std::endl; return ExecutionPlan(); } operators.emplace_back(op106, xnn_delete_operator); xnn_operator_t op107 = nullptr; status = xnn_create_hardswish_nc_f16( 960 /* channels */, 960 /* input stride */, 960 /* output stride */, 0 /* flags */, &op107); if (status != xnn_status_success) { std::cerr << "failed to create operation #107" << std::endl; return ExecutionPlan(); } operators.emplace_back(op107, xnn_delete_operator); xnn_operator_t op108 = nullptr; status = xnn_create_global_average_pooling_nwc_f16( 960 /* channels */, 960 /* input stride */, 960 /* output stride */, -std::numeric_limits::infinity(), std::numeric_limits::infinity(), 0 /* flags */, &op108); if (status != xnn_status_success) { std::cerr << "failed to create operation #108" << std::endl; return ExecutionPlan(); } operators.emplace_back(op108, xnn_delete_operator); xnn_operator_t op109 = nullptr; status = xnn_create_convolution2d_nhwc_f16( 0 /* top padding */, 0 /* right padding */, 0 /* bottom padding */, 0 /* left padding */, 1 /* kernel height */, 1 /* kernel width */, 1 /* subsampling height */, 1 /* subsampling width */, 1 /* dilation_height */, 1 /* dilation_width */, 1 /* groups */, 960 /* input channels per group */, 1280 /* output_channels_per_group */, 960 /* input pixel stride */, 1280 /* output pixel stride */, w238.data(), w239.data(), -std::numeric_limits::infinity() /* output min */, std::numeric_limits::infinity() /* output max */, 0 /* flags */, code_cache_ptr, nullptr, &op109); if (status != xnn_status_success) { std::cerr << "failed to create operation #109" << std::endl; return ExecutionPlan(); } operators.emplace_back(op109, xnn_delete_operator); xnn_operator_t op110 = nullptr; status = xnn_create_hardswish_nc_f16( 1280 /* channels */, 1280 /* input stride */, 1280 /* output stride */, 0 /* flags */, &op110); if (status != xnn_status_success) { std::cerr << "failed to create operation #110" << std::endl; return ExecutionPlan(); } operators.emplace_back(op110, xnn_delete_operator); xnn_operator_t op111 = nullptr; status = xnn_create_global_average_pooling_nwc_f16( 1280 /* channels */, 1280 /* input stride */, 1280 /* output stride */, -std::numeric_limits::infinity(), std::numeric_limits