benchmark_results.md

performance tested on Ascend 910(8p) with graph mode

model	top-1 (%)	top-5 (%)	params(M)	batch size	cards	ms/step	jit_level	recipe	download
bit_resnet50	76.81	93.17	25.55	32	8	74.52	O2	yaml	weights
cmt_small	83.24	96.41	26.09	128	8	500.64	O2	yaml	weights
coat_tiny	79.67	94.88	5.50	32	8	207.74	O2	yaml	weights
convit_tiny	73.66	91.72	5.71	256	8	231.62	O2	yaml	weights
convnext_tiny	81.91	95.79	28.59	16	8	66.79	O2	yaml	weights
convnextv2_tiny	82.43	95.98	28.64	128	8	400.20	O2	yaml	weights
crossvit_9	73.56	91.79	8.55	256	8	550.79	O2	yaml	weights
densenet121	75.64	92.84	8.06	32	8	43.28	O2	yaml	weights
dpn92	79.46	94.49	37.79	32	8	78.22	O2	yaml	weights
edgenext_xx_small	71.02	89.99	1.33	256	8	191.24	O2	yaml	weights
efficientnet_b0	76.89	93.16	5.33	128	8	172.78	O2	yaml	weights
ghostnet_050	66.03	86.64	2.60	128	8	211.13	O2	yaml	weights
googlenet	72.68	90.89	6.99	32	8	21.40	O2	yaml	weights
halonet_50t	79.53	94.79	22.79	64	8	421.66	O2	yaml	weights
hrnet_w32	80.64	95.44	41.30	128	8	279.10	O2	yaml	weights
inception_v3	79.11	94.40	27.20	32	8	76.42	O2	yaml	weights
inception_v4	80.88	95.34	42.74	32	8	76.19	O2	yaml	weights
mixnet_s	75.52	92.52	4.17	128	8	252.49	O2	yaml	weights
mnasnet_075	71.81	90.53	3.20	256	8	165.43	O2	yaml	weights
mobilenet_v1_025	53.87	77.66	0.47	64	8	42.43	O2	yaml	weights
mobilenet_v2_075	69.98	89.32	2.66	256	8	155.94	O2	yaml	weights
mobilenet_v3_small_100	68.10	87.86	2.55	75	8	48.14	O2	yaml	weights
mobilenet_v3_large_100	75.23	92.31	5.51	75	8	47.49	O2	yaml	weights
mobilevit_xx_small	68.91	88.91	1.27	64	8	53.52	O2	yaml	weights
nasnet_a_4x1056	73.65	91.25	5.33	256	8	330.89	O2	yaml	weights
pit_ti	72.96	91.33	4.85	128	8	271.50	O2	yaml	weights
poolformer_s12	77.33	93.34	11.92	128	8	220.13	O2	yaml	weights
pvt_tiny	74.81	92.18	13.23	128	8	229.63	O2	yaml	weights
pvt_v2_b0	71.50	90.60	3.67	128	8	269.38	O2	yaml	weights
regnet_x_800mf	76.04	92.97	7.26	64	8	42.49	O2	yaml	weights
repmlp_t224	76.71	93.30	38.30	128	8	578.23	O2	yaml	weights
repvgg_a0	72.19	90.75	9.13	32	8	20.58	O2	yaml	weights
repvgg_a1	74.19	91.89	14.12	32	8	20.70	O2	yaml	weights
res2net50	79.35	94.64	25.76	32	8	39.68	O2	yaml	weights
resnest50	80.81	95.16	27.55	128	8	244.92	O2	yaml	weights
resnet50	76.69	93.50	25.61	32	8	31.41	O2	yaml	weights
resnetv2_50	76.90	93.37	25.60	32	8	32.66	O2	yaml	weights
resnext50_32x4d	78.53	94.10	25.10	32	8	37.22	O2	yaml	weights
rexnet_09	77.06	93.41	4.13	64	8	130.10	O2	yaml	weights
seresnet18	71.81	90.49	11.80	64	8	44.40	O2	yaml	weights
shufflenet_v1_g3_05	57.05	79.73	0.73	64	8	40.62	O2	yaml	weights
shufflenet_v2_x0_5	60.53	82.11	1.37	64	8	41.87	O2	yaml	weights
skresnet18	73.09	91.20	11.97	64	8	45.84	O2	yaml	weights
squeezenet1_0	59.01	81.01	1.25	32	8	22.36	O2	yaml	weights
swin_tiny	80.82	94.80	33.38	256	8	454.49	O2	yaml	weights
swinv2_tiny_window8	81.42	95.43	28.78	128	8	317.19	O2	yaml	weights
vgg13	72.87	91.02	133.04	32	8	55.20	O2	yaml	weights
vgg19	75.21	92.56	143.66	32	8	67.42	O2	yaml	weights
visformer_tiny	78.28	94.15	10.33	128	8	217.92	O2	yaml	weights
vit_b_32_224	75.86	92.08	87.46	512	8	454.57	O2	yaml	weights
volo_d1	82.59	95.99	27	128	8	270.79	O2	yaml	weights
xception	79.01	94.25	22.91	32	8	92.78	O2	yaml	weights
xcit_tiny_12_p16_224	77.67	93.79	7.00	128	8	252.98	O2	yaml	weights

performance tested on Ascend 910*(8p) with graph mode

model	top-1 (%)	top-5 (%)	params(M)	batch size	cards	ms/step	jit_level	recipe	download
convit_tiny	73.79	91.70	5.71	256	8	226.51	O2	yaml	weights
convnext_tiny	81.28	95.61	28.59	16	8	48.7	O2	yaml	weights
convnextv2_tiny	82.39	95.95	28.64	128	8	257.2	O2	yaml	weights
crossvit_9	73.38	91.51	8.55	256	8	514.36	O2	yaml	weights
densenet121	75.67	92.77	8.06	32	8	47.34	O2	yaml	weights
edgenext_xx_small	70.64	89.75	1.33	256	8	239.38	O2	yaml	weights
efficientnet_b0	76.88	93.28	5.33	128	8	172.64	O2	yaml	weights
googlenet	72.89	90.89	6.99	32	8	23.5	O2	yaml	weights
hrnet_w32	80.66	95.30	41.30	128	8	238.03	O2	yaml	weights
inception_v3	79.25	94.47	27.20	32	8	70.83	O2	yaml	weights
inception_v4	80.98	95.25	42.74	32	8	80.97	O2	yaml	weights
mixnet_s	75.58	95.54	4.17	128	8	228.03	O2	yaml	weights
mnasnet_075	71.77	90.52	3.20	256	8	175.85	O2	yaml	weights
mobilenet_v1_025	54.05	77.74	0.47	64	8	47.47	O2	yaml	weights
mobilenet_v2_075	69.73	89.35	2.66	256	8	174.65	O2	yaml	weights
mobilenet_v3_small_100	68.07	87.77	2.55	75	8	52.38	O2	yaml	weights
mobilenet_v3_large_100	75.59	92.57	5.51	75	8	55.89	O2	yaml	weights
mobilevit_xx_small	67.11	87.85	1.27	64	8	67.24	O2	yaml	weights
nasnet_a_4x1056	74.12	91.36	5.33	256	8	364.35	O2	yaml	weights
pit_ti	73.26	91.57	4.85	128	8	266.47	O2	yaml	weights
poolformer_s12	77.49	93.55	11.92	128	8	211.81	O2	yaml	weights
pvt_tiny	74.88	92.12	13.23	128	8	237.5	O2	yaml	weights
pvt_v2_b0	71.25	90.50	3.67	128	8	255.76	O2	yaml	weights
regnet_x_800mf	76.11	93.00	7.26	64	8	50.74	O2	yaml	weights
repvgg_a0	72.29	90.78	9.13	32	8	24.12	O2	yaml	weights
repvgg_a1	73.68	91.51	14.12	32	8	28.29	O2	yaml	weights
res2net50	79.33	94.64	25.76	32	8	39.6	O2	yaml	weights
resnet50	76.76	93.31	25.61	32	8	31.9	O2	yaml	weights
resnetv2_50	77.03	93.29	25.60	32	8	32.19	O2	yaml	weights
resnext50_32x4d	78.64	94.18	25.10	32	8	44.61	O2	yaml	weights
rexnet_09	76.14	92.96	4.13	64	8	115.61	O2	yaml	weights
seresnet18	72.05	90.59	11.80	64	8	51.09	O2	yaml	weights
shufflenet_v1_g3_05	57.08	79.89	0.73	64	8	47.77	O2	yaml	weights
shufflenet_v2_x0_5	60.65	82.26	1.37	64	8	47.32	O2	yaml	weights
skresnet18	72.85	90.83	11.97	64	8	49.83	O2	yaml	weights
squeezenet1_0	58.75	80.76	1.25	32	8	23.48	O2	yaml	weights
swin_tiny	80.90	94.90	33.38	256	8	466.6	O2	yaml	weights
swinv2_tiny_window8	81.38	95.46	28.78	128	8	335.18	O2	yaml	weights
vgg13	72.81	91.02	133.04	32	8	30.52	O2	yaml	weights
vgg19	75.24	92.55	143.66	32	8	39.17	O2	yaml	weights
visformer_tiny	78.40	94.30	10.33	128	8	201.14	O2	yaml	weights
xcit_tiny_12_p16_224	77.27	93.56	7.00	128	8	229.25	O2	yaml	weights

Notes

• Top-1 and Top-5: Accuracy reported on the validation set of ImageNet-1K.