I’m on Ubuntu18.04, PyTorch 1.5.0.dev20200208, torchvision 0.6.0a0+e2573a7 and Python 3.6.
I’m not too familiar with the CPU path, but I assume some acceleration might be used, e.g. Intel MKL-DNN.
These are the results for Intel(R) Xeon(R) CPU E5-2698 v4 @ 2.20GHz:
{'eager_mode': [0.41640684998128563,
                0.7120672950986773,
                1.2824941909639165,
                1.3912344899727032,
                0.40768929792102426,
                0.4139971520053223,
                0.38925268698949367,
                0.402484250953421,
                0.3884121150476858,
                0.4785128979710862,
                0.4067832449218258,
                0.545752897975035,
                0.5732599410694093,
                0.4258149970555678,
                0.3968868920346722,
                0.48566950601525605,
                0.43550701497588307,
                0.4440762479789555,
                0.7503554919967428,
                0.38166197296231985,
                0.3821106309769675,
                0.44661023293156177,
                0.38337251101620495,
                0.3819082749541849,
                0.37819257692899555,
                1.1893695519538596,
                1.5388466010335833,
                1.525529143982567,
                0.48465632600709796,
                0.45776070607826114],
'script_mode': [0.4976730769267306,
                 0.43659254198428243,
                 0.773980311001651,
                 0.478324937983416,
                 0.4924765909090638,
                 0.5786028039874509,
                 0.4377919939579442,
                 0.4363677880028263,
                 0.5326749039813876,
                 0.4483696899842471,
                 0.4391987449489534,
                 0.5024611499393359,
                 1.5762734409654513,
                 1.595031026052311,
                 0.8721332249697298,
                 0.450302682002075,
                 0.4429084720322862,
                 0.44220093509647995,
                 0.4409501899499446,
                 0.44036652601789683,
                 0.441320842015557,
                 0.48320439900271595,
                 0.4452905689831823,
                 0.44349693809635937,
                 0.4408123919274658,
                 0.4539205359760672,
                 0.4490093319909647,
                 0.44213455193676054,
                 0.44304988998919725,
                 0.75286894896999],
 'trace_mode': [0.3898515000473708,                                                                                                                                                                 [0/1929]
                0.3109738149214536,
                0.40837487496901304,
                0.3113917140290141,
                0.30807038000784814,
                0.30801420705392957,
                0.39118307502940297,
                0.3760412859264761,
                0.3090534210205078,
                0.3969404149102047,
                0.30979375808965415,
                0.31236658501438797,
                0.31614084099419415,
                0.3127995830727741,
                0.31163546594325453,
                0.34516514698043466,
                0.31197512603830546,
                0.3150515320012346,
                0.31840068206656724,
                0.324663263047114,
                0.31104419799521565,
                0.35024457494728267,
                0.31061191798653454,
                0.311683111009188,
                0.31441817595623434,
                0.31754313490819186,
                0.3199888019589707,
                0.3113331060158089,
                0.3175580579554662,
                0.449888464063406]}

Could you check out the latest nightly binaries, as (if I’m not mistaken) MKL-DNN was recently activated for Windows.