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[ROCm] Add more timm models, forward fix #165381 (#165569)

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PR #165381 added timm models to cuda and cpu expected accuracy files. ROCm expected accuracy files were not updated.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/165569
Approved by: https://github.com/jeffdaily

Co-authored-by: Jeff Daily <jeff.daily@amd.com>
This commit is contained in:
Jeff Daily
2025-10-15 18:11:21 +00:00
committed by PyTorch MergeBot
parent 84d141e910
commit 7a97832585
11 changed files with 176 additions and 0 deletions
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16
benchmarks/dynamo/ci_expected_accuracy/rocm/aot_eager_timm_inference.csv
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@ -10,10 +10,18 @@ beit_base_patch16_224,pass,0
convnextv2_nano.fcmae_ft_in22k_in1k,pass,0
deit_base_distilled_patch16_224,pass,0
deit_tiny_patch16_224.fb_in1k,pass,0
dm_nfnet_f0,pass,0
@ -55,3 +63,11 @@ tf_efficientnet_b0,pass,0
visformer_small,pass,0
vit_base_patch14_dinov2.lvd142m,pass,0
vit_base_patch16_siglip_256,pass,0

1 name accuracy graph_breaks
10 mobilevit_s mobilenetv2_100 pass 0
11 nfnet_l0 mobilenetv3_large_100 pass 0
12 repvgg_a2 mobilevit_s pass 0
13 nfnet_l0 pass 0
14 repvgg_a2 pass 0
15 swin_base_patch4_window7_224 pass 0
16 tf_efficientnet_b0 pass 0
17 swin_base_patch4_window7_224 visformer_small pass 0
18 tf_efficientnet_b0 vit_base_patch14_dinov2.lvd142m pass 0
19 visformer_small vit_base_patch16_siglip_256 pass 0
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benchmarks/dynamo/ci_expected_accuracy/rocm/aot_eager_timm_training.csv
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@ -10,10 +10,18 @@ beit_base_patch16_224,pass,7
convnextv2_nano.fcmae_ft_in22k_in1k,pass,7
deit_base_distilled_patch16_224,pass,7
deit_tiny_patch16_224.fb_in1k,pass,7
dm_nfnet_f0,pass,6
@ -55,3 +63,11 @@ tf_efficientnet_b0,pass,6
visformer_small,pass,7
vit_base_patch14_dinov2.lvd142m,pass,7
vit_base_patch16_siglip_256,pass,7

1 name accuracy graph_breaks
10 mobilevit_s mobilenetv2_100 pass 6 7
11 nfnet_l0 mobilenetv3_large_100 pass 7
12 repvgg_a2 mobilevit_s pass 7 6
13 nfnet_l0 pass 7
14 repvgg_a2 pass 7
15 swin_base_patch4_window7_224 pass 7
16 tf_efficientnet_b0 pass 6
17 swin_base_patch4_window7_224 visformer_small pass 7
18 tf_efficientnet_b0 vit_base_patch14_dinov2.lvd142m pass 6 7
19 visformer_small vit_base_patch16_siglip_256 pass 7
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benchmarks/dynamo/ci_expected_accuracy/rocm/aot_inductor_timm_inference.csv
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@ -10,10 +10,18 @@ beit_base_patch16_224,pass,0
convnextv2_nano.fcmae_ft_in22k_in1k,pass,0
deit_base_distilled_patch16_224,pass,0
deit_tiny_patch16_224.fb_in1k,pass,0
dm_nfnet_f0,pass,0
@ -55,3 +63,11 @@ tf_efficientnet_b0,pass,0
visformer_small,pass,0
vit_base_patch14_dinov2.lvd142m,pass,0
vit_base_patch16_siglip_256,pass,0

1 name accuracy graph_breaks
10 mobilevit_s mobilenetv2_100 pass 0
11 nfnet_l0 mobilenetv3_large_100 pass 0
12 repvgg_a2 mobilevit_s pass 0
13 nfnet_l0 pass 0
14 repvgg_a2 pass 0
15 swin_base_patch4_window7_224 pass 0
16 tf_efficientnet_b0 pass 0
17 swin_base_patch4_window7_224 visformer_small pass 0
18 tf_efficientnet_b0 vit_base_patch14_dinov2.lvd142m pass 0
19 visformer_small vit_base_patch16_siglip_256 pass 0
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benchmarks/dynamo/ci_expected_accuracy/rocm/dynamic_aot_eager_timm_inference.csv
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@ -10,10 +10,18 @@ beit_base_patch16_224,pass,0
convnextv2_nano.fcmae_ft_in22k_in1k,pass,0
deit_base_distilled_patch16_224,pass,0
deit_tiny_patch16_224.fb_in1k,pass,0
dm_nfnet_f0,pass,0
@ -55,3 +63,11 @@ tf_efficientnet_b0,pass,0
visformer_small,pass,0
vit_base_patch14_dinov2.lvd142m,pass,0
vit_base_patch16_siglip_256,pass,0

1 name accuracy graph_breaks
10 mobilevit_s mobilenetv2_100 pass 0
11 nfnet_l0 mobilenetv3_large_100 pass 0
12 repvgg_a2 mobilevit_s pass 0
13 nfnet_l0 pass 0
14 repvgg_a2 pass 0
15 swin_base_patch4_window7_224 pass 0
16 tf_efficientnet_b0 pass 0
17 swin_base_patch4_window7_224 visformer_small pass 0
18 tf_efficientnet_b0 vit_base_patch14_dinov2.lvd142m pass 0
19 visformer_small vit_base_patch16_siglip_256 pass 0
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benchmarks/dynamo/ci_expected_accuracy/rocm/dynamic_aot_eager_timm_training.csv
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@ -10,10 +10,18 @@ beit_base_patch16_224,pass,7
convnextv2_nano.fcmae_ft_in22k_in1k,pass,7
deit_base_distilled_patch16_224,pass,7
deit_tiny_patch16_224.fb_in1k,pass,7
dm_nfnet_f0,pass,6
@ -55,3 +63,11 @@ tf_efficientnet_b0,pass,6
visformer_small,pass,7
vit_base_patch14_dinov2.lvd142m,pass,7
vit_base_patch16_siglip_256,pass,7

1 name accuracy graph_breaks
10 mobilevit_s mobilenetv2_100 pass 6 7
11 nfnet_l0 mobilenetv3_large_100 pass 7
12 repvgg_a2 mobilevit_s pass 7 6
13 nfnet_l0 pass 7
14 repvgg_a2 pass 7
15 swin_base_patch4_window7_224 pass 7
16 tf_efficientnet_b0 pass 6
17 swin_base_patch4_window7_224 visformer_small pass 7
18 tf_efficientnet_b0 vit_base_patch14_dinov2.lvd142m pass 6 7
19 visformer_small vit_base_patch16_siglip_256 pass 7
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benchmarks/dynamo/ci_expected_accuracy/rocm/dynamic_inductor_timm_inference.csv
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@ -10,10 +10,18 @@ beit_base_patch16_224,pass,0
convnextv2_nano.fcmae_ft_in22k_in1k,pass,0
deit_base_distilled_patch16_224,pass,0
deit_tiny_patch16_224.fb_in1k,pass,0
dm_nfnet_f0,pass,0
@ -55,3 +63,11 @@ tf_efficientnet_b0,pass,0
visformer_small,pass,0
vit_base_patch14_dinov2.lvd142m,pass,0
vit_base_patch16_siglip_256,pass,0

1 name accuracy graph_breaks
10 mobilevit_s mobilenetv2_100 pass 0
11 nfnet_l0 mobilenetv3_large_100 pass 0
12 repvgg_a2 mobilevit_s fail_accuracy pass 0
13 nfnet_l0 pass 0
14 repvgg_a2 fail_accuracy 0
15 swin_base_patch4_window7_224 pass 0
16 tf_efficientnet_b0 pass 0
17 swin_base_patch4_window7_224 visformer_small pass 0
18 tf_efficientnet_b0 vit_base_patch14_dinov2.lvd142m pass 0
19 visformer_small vit_base_patch16_siglip_256 pass 0
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benchmarks/dynamo/ci_expected_accuracy/rocm/dynamic_inductor_timm_training.csv
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@ -10,10 +10,18 @@ beit_base_patch16_224,pass,7
convnextv2_nano.fcmae_ft_in22k_in1k,pass,7
deit_base_distilled_patch16_224,pass,7
deit_tiny_patch16_224.fb_in1k,pass,7
dm_nfnet_f0,pass,6
@ -55,3 +63,11 @@ tf_efficientnet_b0,pass,6
visformer_small,fail_accuracy,7
vit_base_patch14_dinov2.lvd142m,pass,7
vit_base_patch16_siglip_256,pass,7

1 name accuracy graph_breaks
10 mobilevit_s mobilenetv2_100 pass fail_accuracy 6 7
11 nfnet_l0 mobilenetv3_large_100 pass 7
12 repvgg_a2 mobilevit_s fail_accuracy pass 7 6
13 nfnet_l0 pass 7
14 repvgg_a2 fail_accuracy 7
15 swin_base_patch4_window7_224 pass 7
16 tf_efficientnet_b0 pass 6
17 swin_base_patch4_window7_224 visformer_small pass fail_accuracy 7
18 tf_efficientnet_b0 vit_base_patch14_dinov2.lvd142m pass 6 7
19 visformer_small vit_base_patch16_siglip_256 fail_accuracy pass 7
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benchmarks/dynamo/ci_expected_accuracy/rocm/dynamo_eager_timm_inference.csv
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@ -10,10 +10,18 @@ beit_base_patch16_224,pass,0
convnextv2_nano.fcmae_ft_in22k_in1k,pass,0
deit_base_distilled_patch16_224,pass,0
deit_tiny_patch16_224.fb_in1k,pass,0
dm_nfnet_f0,pass,0
@ -55,3 +63,11 @@ tf_efficientnet_b0,pass,0
visformer_small,pass,0
vit_base_patch14_dinov2.lvd142m,pass,0
vit_base_patch16_siglip_256,pass,0

1 name accuracy graph_breaks
10 mobilevit_s mobilenetv2_100 pass 0
11 nfnet_l0 mobilenetv3_large_100 pass 0
12 repvgg_a2 mobilevit_s pass 0
13 nfnet_l0 pass 0
14 repvgg_a2 pass 0
15 swin_base_patch4_window7_224 pass 0
16 tf_efficientnet_b0 pass 0
17 swin_base_patch4_window7_224 visformer_small pass 0
18 tf_efficientnet_b0 vit_base_patch14_dinov2.lvd142m pass 0
19 visformer_small vit_base_patch16_siglip_256 pass 0
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benchmarks/dynamo/ci_expected_accuracy/rocm/dynamo_eager_timm_training.csv
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@ -10,10 +10,18 @@ beit_base_patch16_224,pass,7
convnextv2_nano.fcmae_ft_in22k_in1k,pass,7
deit_base_distilled_patch16_224,pass,7
deit_tiny_patch16_224.fb_in1k,pass,7
dm_nfnet_f0,pass,6
@ -55,3 +63,11 @@ tf_efficientnet_b0,pass,6
visformer_small,pass,7
vit_base_patch14_dinov2.lvd142m,pass,7
vit_base_patch16_siglip_256,pass,7

1 name accuracy graph_breaks
10 mobilevit_s mobilenetv2_100 pass 6 7
11 nfnet_l0 mobilenetv3_large_100 pass 7
12 repvgg_a2 mobilevit_s pass 7 6
13 nfnet_l0 pass 7
14 repvgg_a2 pass 7
15 swin_base_patch4_window7_224 pass 7
16 tf_efficientnet_b0 pass 6
17 swin_base_patch4_window7_224 visformer_small pass 7
18 tf_efficientnet_b0 vit_base_patch14_dinov2.lvd142m pass 6 7
19 visformer_small vit_base_patch16_siglip_256 pass 7
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benchmarks/dynamo/ci_expected_accuracy/rocm/inductor_timm_inference.csv
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@ -10,10 +10,18 @@ beit_base_patch16_224,pass,0
convnextv2_nano.fcmae_ft_in22k_in1k,pass,0
deit_base_distilled_patch16_224,pass,0
deit_tiny_patch16_224.fb_in1k,pass,0
dm_nfnet_f0,pass,0
@ -55,3 +63,11 @@ tf_efficientnet_b0,pass,0
visformer_small,pass,0
vit_base_patch14_dinov2.lvd142m,pass,0
vit_base_patch16_siglip_256,pass,0

1 name accuracy graph_breaks
10 mobilevit_s mobilenetv2_100 pass 0
11 nfnet_l0 mobilenetv3_large_100 pass 0
12 repvgg_a2 mobilevit_s pass 0
13 nfnet_l0 pass 0
14 repvgg_a2 pass 0
15 swin_base_patch4_window7_224 pass 0
16 tf_efficientnet_b0 pass 0
17 swin_base_patch4_window7_224 visformer_small pass 0
18 tf_efficientnet_b0 vit_base_patch14_dinov2.lvd142m pass 0
19 visformer_small vit_base_patch16_siglip_256 pass 0
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benchmarks/dynamo/ci_expected_accuracy/rocm/inductor_timm_training.csv
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@ -10,10 +10,18 @@ beit_base_patch16_224,pass,7
convnextv2_nano.fcmae_ft_in22k_in1k,fail_accuracy,7
deit_base_distilled_patch16_224,pass,7
deit_tiny_patch16_224.fb_in1k,pass,7
dm_nfnet_f0,pass,6
@ -55,3 +63,11 @@ tf_efficientnet_b0,pass,6
visformer_small,pass,7
vit_base_patch14_dinov2.lvd142m,fail_accuracy,7
vit_base_patch16_siglip_256,pass,7

1 name accuracy graph_breaks
10 mobilevit_s mobilenetv2_100 pass 6 7
11 nfnet_l0 mobilenetv3_large_100 pass 7
12 repvgg_a2 mobilevit_s pass 7 6
13 nfnet_l0 pass 7
14 repvgg_a2 pass 7
15 swin_base_patch4_window7_224 pass 7
16 tf_efficientnet_b0 pass 6
17 swin_base_patch4_window7_224 visformer_small pass 7
18 tf_efficientnet_b0 vit_base_patch14_dinov2.lvd142m pass fail_accuracy 6 7
19 visformer_small vit_base_patch16_siglip_256 pass 7
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