[Inductor] nanogpt_generate failed due to RuntimeError: probability tensor contains either `inf`, `nan` or element < 0
Labels: high priority, triaged, module: NaNs and Infs, oncall: pt2, module: inductor

### 🐛 Describe the bug
Torchbench model **nanogpt_generate** failure tracked in https://github.com/pytorch/pytorch/issues/93531#issuecomment-1558372237

```bash

cpu  eval  nanogpt_generate                    
[2023-05-22 04:45:49,942] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_383
[2023-05-22 04:45:49,942] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_382
[2023-05-22 04:45:49,942] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_381
[2023-05-22 04:45:49,942] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_380
[2023-05-22 04:45:49,942] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_379
[2023-05-22 04:45:49,942] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_378
[2023-05-22 04:45:49,943] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_377
[2023-05-22 04:45:49,943] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_376
[2023-05-22 04:45:49,943] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_375
[2023-05-22 04:45:49,943] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_374
[2023-05-22 04:45:49,943] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_373
[2023-05-22 04:45:49,943] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_372
[2023-05-22 04:45:49,943] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_371
[2023-05-22 04:45:49,943] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_370
[2023-05-22 04:45:49,943] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_369
[2023-05-22 04:45:49,943] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_368
[2023-05-22 04:45:49,943] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_367
[2023-05-22 04:45:49,943] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_366
[2023-05-22 04:45:49,943] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_365
[2023-05-22 04:45:49,943] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_364
[2023-05-22 04:45:49,944] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_363
[2023-05-22 04:45:49,944] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_362
[2023-05-22 04:45:49,944] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_361
[2023-05-22 04:45:49,944] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_360
[2023-05-22 04:45:49,944] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_359
[2023-05-22 04:45:49,944] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_358
[2023-05-22 04:45:49,944] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_357
[2023-05-22 04:45:49,944] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_356
[2023-05-22 04:45:49,944] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_355
[2023-05-22 04:45:49,944] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_354
[2023-05-22 04:45:49,944] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_353
[2023-05-22 04:45:49,944] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_352
[2023-05-22 04:45:49,944] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_351
[2023-05-22 04:45:49,944] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_350
[2023-05-22 04:45:49,945] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_349
[2023-05-22 04:45:49,945] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_348
[2023-05-22 04:45:49,945] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_347
[2023-05-22 04:45:49,945] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_346
[2023-05-22 04:45:49,945] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_345
[2023-05-22 04:45:49,945] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_344
[2023-05-22 04:45:49,945] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_343
[2023-05-22 04:45:49,945] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_342
[2023-05-22 04:45:49,945] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_341
[2023-05-22 04:45:49,945] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_340
[2023-05-22 04:45:49,945] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_339
[2023-05-22 04:45:49,945] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_338
[2023-05-22 04:45:49,945] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_337
[2023-05-22 04:45:49,945] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_336
[2023-05-22 04:45:49,945] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_335
[2023-05-22 04:45:49,946] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_334
[2023-05-22 04:45:49,946] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_333
[2023-05-22 04:45:49,946] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_332
[2023-05-22 04:45:49,946] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_331
[2023-05-22 04:45:49,946] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_330
[2023-05-22 04:45:49,946] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_329
[2023-05-22 04:45:49,946] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_328
[2023-05-22 04:45:49,946] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_327
[2023-05-22 04:45:49,946] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_326
[2023-05-22 04:45:49,946] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_325
[2023-05-22 04:45:49,946] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_324
[2023-05-22 04:45:49,946] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_323
[2023-05-22 04:45:49,946] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_322
[2023-05-22 04:45:49,946] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_321
[2023-05-22 04:45:49,947] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_320
[2023-05-22 04:45:49,947] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_319
[2023-05-22 04:45:49,947] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_318
[2023-05-22 04:45:49,947] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_317
[2023-05-22 04:45:49,947] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_316
[2023-05-22 04:45:49,947] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_315
[2023-05-22 04:45:49,947] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_314
[2023-05-22 04:45:49,947] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_313
[2023-05-22 04:45:49,947] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_312
[2023-05-22 04:45:49,947] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_311
[2023-05-22 04:45:49,947] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_310
[2023-05-22 04:45:49,947] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_309
[2023-05-22 04:45:49,947] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_308
[2023-05-22 04:45:49,947] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_307
[2023-05-22 04:45:49,947] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_306
[2023-05-22 04:45:49,948] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_305
[2023-05-22 04:45:49,948] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_304
[2023-05-22 04:45:49,948] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_303
[2023-05-22 04:45:49,948] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_302
[2023-05-22 04:45:49,948] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_301
[2023-05-22 04:45:49,948] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_300
[2023-05-22 04:45:49,948] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_299
[2023-05-22 04:45:49,948] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_298
[2023-05-22 04:45:49,948] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_297
[2023-05-22 04:45:49,948] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_296
[2023-05-22 04:45:49,948] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_295
[2023-05-22 04:45:49,948] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_294
[2023-05-22 04:45:49,948] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_293
[2023-05-22 04:45:49,948] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_292
[2023-05-22 04:45:49,949] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_291
[2023-05-22 04:45:49,949] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_290
[2023-05-22 04:45:49,949] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_289
[2023-05-22 04:45:49,949] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_288
[2023-05-22 04:45:49,949] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_287
[2023-05-22 04:45:49,949] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_286
[2023-05-22 04:45:49,949] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_285
[2023-05-22 04:45:49,949] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_284
[2023-05-22 04:45:49,949] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_283
[2023-05-22 04:45:49,949] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_282
[2023-05-22 04:45:49,949] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_281
[2023-05-22 04:45:49,949] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_280
[2023-05-22 04:45:49,949] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_279
[2023-05-22 04:45:49,949] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_278
[2023-05-22 04:45:49,950] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_277
[2023-05-22 04:45:49,950] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_276
[2023-05-22 04:45:49,950] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_275
[2023-05-22 04:45:49,950] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_274
[2023-05-22 04:45:49,950] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_273
[2023-05-22 04:45:49,950] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_272
[2023-05-22 04:45:49,950] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_271
[2023-05-22 04:45:49,950] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_270
[2023-05-22 04:45:49,950] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_269
[2023-05-22 04:45:49,950] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_268
[2023-05-22 04:45:49,950] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_267
[2023-05-22 04:45:49,950] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_266
[2023-05-22 04:45:49,950] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_265
[2023-05-22 04:45:49,950] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_264
[2023-05-22 04:45:49,950] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_263
[2023-05-22 04:45:49,951] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_262
[2023-05-22 04:45:49,951] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_261
[2023-05-22 04:45:49,951] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_260
[2023-05-22 04:45:49,951] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_259
[2023-05-22 04:45:49,951] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_258
[2023-05-22 04:45:49,951] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_257
[2023-05-22 04:45:49,951] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_256
[2023-05-22 04:45:49,951] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_255
[2023-05-22 04:45:49,951] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_254
[2023-05-22 04:45:49,951] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_253
[2023-05-22 04:45:49,951] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_252
[2023-05-22 04:45:49,951] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_251
[2023-05-22 04:45:49,951] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_250
[2023-05-22 04:45:49,951] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_249
[2023-05-22 04:45:49,952] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_248
[2023-05-22 04:45:49,952] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_247
[2023-05-22 04:45:49,952] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_246
[2023-05-22 04:45:49,952] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_245
[2023-05-22 04:45:49,952] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_244
[2023-05-22 04:45:49,952] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_243
[2023-05-22 04:45:49,952] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_242
[2023-05-22 04:45:49,952] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_241
[2023-05-22 04:45:49,952] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_240
[2023-05-22 04:45:49,952] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_239
[2023-05-22 04:45:49,952] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_238
[2023-05-22 04:45:49,952] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_237
[2023-05-22 04:45:49,952] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_236
[2023-05-22 04:45:49,952] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_235
[2023-05-22 04:45:49,953] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_234
[2023-05-22 04:45:49,953] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_233
[2023-05-22 04:45:49,953] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_232
[2023-05-22 04:45:49,953] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_231
[2023-05-22 04:45:49,953] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_230
[2023-05-22 04:45:49,953] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_229
[2023-05-22 04:45:49,953] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_228
[2023-05-22 04:45:49,953] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_227
[2023-05-22 04:45:49,953] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_226
[2023-05-22 04:45:49,953] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_225
[2023-05-22 04:45:49,953] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_224
[2023-05-22 04:45:49,953] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_223
[2023-05-22 04:45:49,953] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_222
[2023-05-22 04:45:49,953] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_221
[2023-05-22 04:45:49,953] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_220
[2023-05-22 04:45:49,954] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_219
[2023-05-22 04:45:49,954] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_218
[2023-05-22 04:45:49,954] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_217
[2023-05-22 04:45:49,954] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_216
[2023-05-22 04:45:49,954] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_215
[2023-05-22 04:45:49,954] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_214
[2023-05-22 04:45:49,954] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_213
[2023-05-22 04:45:49,954] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_212
[2023-05-22 04:45:49,954] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_211
[2023-05-22 04:45:49,954] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_210
[2023-05-22 04:45:49,954] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_209
[2023-05-22 04:45:49,954] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_208
[2023-05-22 04:45:49,954] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_207
[2023-05-22 04:45:49,954] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_206
[2023-05-22 04:45:49,955] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_205
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[2023-05-22 04:45:49,968] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_23
[2023-05-22 04:45:49,968] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_22
[2023-05-22 04:45:49,968] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_21
[2023-05-22 04:45:49,968] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_20
[2023-05-22 04:45:49,968] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_19
[2023-05-22 04:45:49,968] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_18
[2023-05-22 04:45:49,969] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_17
[2023-05-22 04:45:49,969] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_16
[2023-05-22 04:45:49,969] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_15
[2023-05-22 04:45:49,969] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_14
[2023-05-22 04:45:49,969] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_13
[2023-05-22 04:45:49,969] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_12
[2023-05-22 04:45:49,969] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_11
[2023-05-22 04:45:49,969] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_10
[2023-05-22 04:45:49,969] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_9
[2023-05-22 04:45:49,969] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_8
[2023-05-22 04:45:49,969] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_7
[2023-05-22 04:45:49,969] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_6
[2023-05-22 04:45:49,969] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_5
[2023-05-22 04:45:49,969] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_4
[2023-05-22 04:45:49,970] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_3
[2023-05-22 04:45:49,970] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_2
[2023-05-22 04:45:49,970] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split_1
[2023-05-22 04:45:49,970] torch._inductor.fx_passes.split_cat: [WARNING] example value absent for node: split
ERROR:common:Backend dynamo failed in warmup()
Traceback (most recent call last):
  File "/workspace/pytorch/benchmarks/dynamo/common.py", line 1551, in warmup
    fn(model, example_inputs)
  File "/workspace/pytorch/torch/_dynamo/eval_frame.py", line 287, in _fn
    return fn(*args, **kwargs)
  File "benchmarks/dynamo/torchbench.py", line 406, in forward_pass
    def forward_pass(self, mod, inputs, collect_outputs=True):
  File "/workspace/pytorch/torch/_dynamo/eval_frame.py", line 287, in _fn
    return fn(*args, **kwargs)
  File "/workspace/pytorch/torch/_dynamo/external_utils.py", line 17, in inner
    return fn(*args, **kwargs)
  File "/workspace/pytorch/torch/_functorch/aot_autograd.py", line 3714, in forward
    return compiled_fn(full_args)
  File "/workspace/pytorch/torch/_functorch/aot_autograd.py", line 1438, in g
    return f(*args)
  File "/workspace/pytorch/torch/_functorch/aot_autograd.py", line 2411, in runtime_wrapper
    all_outs = call_func_with_args(
  File "/workspace/pytorch/torch/_functorch/aot_autograd.py", line 1463, in call_func_with_args
    out = normalize_as_list(f(args))
  File "/workspace/pytorch/torch/_functorch/aot_autograd.py", line 1556, in rng_functionalization_wrapper
    return compiled_fw(args)
  File "/tmp/tmp02tc9psn/uy/cuyyj5fpynwpu76mfolhwnrzqrl5i3ns7yn77huwb4o675qu6vkb.py", line 185819, in call
    buf302 = torch.ops.aten.multinomial.default(buf301, 1)
  File "/workspace/pytorch/torch/_ops.py", line 398, in __call__
    return self._op(*args, **kwargs or {})
RuntimeError: probability tensor contains either `inf`, `nan` or element < 0
ERROR


```
SW information:
SW	| Nightly commit	| Main commit
-- | -- | --
Pytorch|[1c93857](https://github.com/pytorch/pytorch/commit/1c93857)|[9e8da7f](https://github.com/pytorch/pytorch/commit/9e8da7f)
Torchbench|/|[987bbec3](https://github.com/pytorch/benchmark/commit/987bbec3)
torchaudio|[894388d](https://github.com/pytorch/audio/commit/894388d)|[72d3fe0](https://github.com/pytorch/audio/commit/72d3fe0)
torchtext|[3cf1db6](https://github.com/pytorch/text/commit/3cf1db6)| [0dc07eb](https://github.com/pytorch/text/commit/0dc07eb)
torchvision|[50fb988](https://github.com/pytorch/vision/commit/50fb988)|[abc40ef](https://github.com/pytorch/vision/commit/abc40ef)
torchdata|[a754743](https://github.com/pytorch/data/commit/a754743)|[ba31745](https://github.com/pytorch/data/commit/ba31745)
dynamo_benchmarks|[174d01b](https://github.com/pytorch/pytorch/commit/174d01b)|/


### Versions


```bash
python -m torch.backends.xeon.run_cpu --node_id 0 benchmarks/dynamo/torchbench.py --performance --inference --float32 -dcpu -n50 --inductor  --no-skip --dashboard --only nanogpt_generate  --cold_start_latency
```

cc @ezyang @gchanan @zou3519 @msaroufim @wconstab @bdhirsh @anijain2305 @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @Xia-Weiwen @wenzhe-nrv @jiayisunx @peterbell10 @ipiszy @ngimel @yf225 @chenyang78 @kadeng @muchulee8 @aakhundov