Properly parenthesize dynamo_dynamic_indices test (#99823)

I've got the E2E test case which triggered this in https://github.com/pytorch/pytorch/pull/99809

Signed-off-by: Edward Z. Yang <ezyang@meta.com>

Pull Request resolved: https://github.com/pytorch/pytorch/pull/99823
Approved by: https://github.com/voznesenskym

benchmarks/dynamo/ci_expected_accuracy/inductor_huggingface_dynamic_training.csv

@@ -1,7 +1,7 @@
 name,accuracy,graph_breaks
 AlbertForMaskedLM,fail_to_run,4
 AlbertForQuestionAnswering,fail_to_run,4
-AllenaiLongformerBase,pass,159
+AllenaiLongformerBase,pass,160
 BartForCausalLM,fail_to_run,4
 BertForMaskedLM,fail_to_run,4
 BertForQuestionAnswering,fail_to_run,4
@@ -12,7 +12,7 @@ DebertaForMaskedLM,fail_to_run,4
 DebertaForQuestionAnswering,fail_to_run,4
 DebertaV2ForMaskedLM,pass_due_to_skip,0
 DistilBertForMaskedLM,fail_to_run,4
-DistilBertForQuestionAnswering,pass,6
+DistilBertForQuestionAnswering,pass,7
 DistillGPT2,fail_to_run,4
 ElectraForCausalLM,fail_to_run,4
 ElectraForQuestionAnswering,fail_to_run,4
@@ -21,7 +21,7 @@ LayoutLMForMaskedLM,fail_to_run,4
 LayoutLMForSequenceClassification,fail_to_run,4
 M2M100ForConditionalGeneration,fail_to_run,4
 MBartForCausalLM,fail_to_run,4
-MBartForConditionalGeneration,pass,6
+MBartForConditionalGeneration,pass,7
 MT5ForConditionalGeneration,fail_to_run,4
 MegatronBertForCausalLM,fail_to_run,4
 MegatronBertForQuestionAnswering,fail_to_run,4
@@ -29,7 +29,7 @@ MobileBertForMaskedLM,fail_to_run,4
 MobileBertForQuestionAnswering,pass,4
 OPTForCausalLM,fail_to_run,4
 PLBartForCausalLM,fail_to_run,4
-PLBartForConditionalGeneration,pass,6
+PLBartForConditionalGeneration,pass,7
 PegasusForCausalLM,fail_to_run,4
 PegasusForConditionalGeneration,fail_to_run,4
 RobertaForCausalLM,fail_to_run,4

benchmarks/dynamo/ci_expected_accuracy/inductor_timm_dynamic_training.csv

@@ -1,60 +1,60 @@
 name,accuracy,graph_breaks
-adv_inception_v3,pass,8
-beit_base_patch16_224,pass,8
-botnet26t_256,pass,8
-coat_lite_mini,pass,8
+adv_inception_v3,pass,9
+beit_base_patch16_224,pass,9
+botnet26t_256,pass,11
+coat_lite_mini,pass,9
 convit_base,fail_to_run,8
 convmixer_768_32,pass,6
-convnext_base,pass,8
-crossvit_9_240,pass,8
-cspdarknet53,pass,8
-deit_base_distilled_patch16_224,pass,8
-dla102,pass,8
-dm_nfnet_f0,pass,8
-dpn107,pass,8
-eca_botnext26ts_256,pass,8
-eca_halonext26ts,pass,8
-ese_vovnet19b_dw,pass,8
-fbnetc_100,pass,8
-fbnetv3_b,pass,8
-gernet_l,pass,8
-ghostnet_100,pass,8
-gluon_inception_v3,pass,8
-gluon_xception65,pass,8
-gmixer_24_224,pass,8
-gmlp_s16_224,pass,8
+convnext_base,pass,9
+crossvit_9_240,pass,9
+cspdarknet53,pass,11
+deit_base_distilled_patch16_224,pass,9
+dla102,pass,9
+dm_nfnet_f0,pass,9
+dpn107,pass,11
+eca_botnext26ts_256,pass,11
+eca_halonext26ts,pass,11
+ese_vovnet19b_dw,pass,11
+fbnetc_100,pass,11
+fbnetv3_b,pass,11
+gernet_l,pass,11
+ghostnet_100,pass,11
+gluon_inception_v3,pass,9
+gluon_xception65,pass,9
+gmixer_24_224,pass,9
+gmlp_s16_224,pass,9
 hrnet_w18,pass,6
-inception_v3,pass,8
-jx_nest_base,pass,8
-lcnet_050,pass,8
-mixer_b16_224,pass,8
-mixnet_l,pass,8
-mnasnet_100,pass,8
-mobilenetv2_100,pass,8
-mobilenetv3_large_100,pass,8
-mobilevit_s,pass,8
-nfnet_l0,pass,8
-pit_b_224,pass,8
-pnasnet5large,pass,6
-poolformer_m36,pass,8
-regnety_002,pass,8
-repvgg_a2,pass,8
-res2net101_26w_4s,pass,8
-res2net50_14w_8s,pass,8
-res2next50,pass,8
-resmlp_12_224,pass,8
-resnest101e,pass,8
-rexnet_100,pass,8
-selecsls42b,pass,8
-spnasnet_100,pass,8
-swin_base_patch4_window7_224,pass,8
-swsl_resnext101_32x16d,pass,8
-tf_efficientnet_b0,pass,8
-tf_mixnet_l,pass,8
-tinynet_a,pass,8
-tnt_s_patch16_224,pass,8
-twins_pcpvt_base,pass,8
-visformer_small,pass,8
-vit_base_patch16_224,pass,8
-volo_d1_224,pass,8
-xcit_large_24_p8_224,pass,8
+inception_v3,pass,9
+jx_nest_base,pass,9
+lcnet_050,pass,11
+mixer_b16_224,pass,9
+mixnet_l,pass,11
+mnasnet_100,pass,11
+mobilenetv2_100,pass,11
+mobilenetv3_large_100,pass,11
+mobilevit_s,pass,11
+nfnet_l0,pass,9
+pit_b_224,pass,9
+pnasnet5large,pass,8
+poolformer_m36,pass,9
+regnety_002,pass,11
+repvgg_a2,pass,11
+res2net101_26w_4s,pass,9
+res2net50_14w_8s,pass,9
+res2next50,pass,9
+resmlp_12_224,pass,9
+resnest101e,pass,9
+rexnet_100,pass,11
+selecsls42b,pass,9
+spnasnet_100,pass,11
+swin_base_patch4_window7_224,pass,9
+swsl_resnext101_32x16d,pass,9
+tf_efficientnet_b0,pass,11
+tf_mixnet_l,pass,11
+tinynet_a,pass,11
+tnt_s_patch16_224,pass,9
+twins_pcpvt_base,pass,9
+visformer_small,pass,9
+vit_base_patch16_224,pass,9
+volo_d1_224,pass,9
+xcit_large_24_p8_224,pass,9

benchmarks/dynamo/ci_expected_accuracy/inductor_torchbench_dynamic_training.csv

@@ -1,46 +1,46 @@
 name,accuracy,graph_breaks
-BERT_pytorch,pass,8
-LearningToPaint,pass,8
-Super_SloMo,pass,8
-alexnet,pass,8
-attention_is_all_you_need_pytorch,pass,8
-dcgan,pass,8
-densenet121,pass,8
+BERT_pytorch,pass,11
+LearningToPaint,pass,9
+Super_SloMo,pass,9
+alexnet,pass,9
+attention_is_all_you_need_pytorch,pass,9
+dcgan,pass,9
+densenet121,pass,9
 drq,pass,8
-fastNLP_Bert,pass,13
-functorch_dp_cifar10,pass,8
+fastNLP_Bert,pass,14
+functorch_dp_cifar10,pass,9
 functorch_maml_omniglot,pass,9
-hf_Albert,pass,7
-hf_Bart,pass,7
-hf_Bert,pass,7
-hf_Bert_large,pass,7
-hf_DistilBert,pass,7
-hf_GPT2,pass,7
-hf_Reformer,pass,44
+hf_Albert,pass,8
+hf_Bart,pass,8
+hf_Bert,pass,8
+hf_Bert_large,pass,8
+hf_DistilBert,pass,8
+hf_GPT2,pass,8
+hf_Reformer,pass,45
 hf_T5_large,pass_due_to_skip,0
-lennard_jones,pass,8
-maml_omniglot,pass,8
-mnasnet1_0,pass,8
-mobilenet_v2,pass,8
-nvidia_deeprecommender,pass,8
-phlippe_densenet,pass,8
-phlippe_resnet,pass,8
+lennard_jones,pass,9
+maml_omniglot,pass,9
+mnasnet1_0,pass,9
+mobilenet_v2,pass,9
+nvidia_deeprecommender,pass,9
+phlippe_densenet,pass,9
+phlippe_resnet,pass,9
 pytorch_CycleGAN_and_pix2pix,pass,9
-pytorch_stargan,pass,8
-pytorch_unet,pass,8
-resnet152,pass,8
-resnet18,pass,8
-resnet50,pass,8
-resnext50_32x4d,pass,8
-shufflenet_v2_x1_0,pass,8
-soft_actor_critic,pass,7
+pytorch_stargan,pass,9
+pytorch_unet,pass,9
+resnet152,pass,9
+resnet18,pass,9
+resnet50,pass,9
+resnext50_32x4d,pass,9
+shufflenet_v2_x1_0,pass,9
+soft_actor_critic,pass,8
 speech_transformer,fail_to_run,4
-squeezenet1_1,pass,8
-timm_efficientnet,pass,8
-timm_regnet,pass,8
-timm_resnest,pass,8
-timm_vision_transformer,pass,8
+squeezenet1_1,pass,9
+timm_efficientnet,pass,9
+timm_regnet,pass,9
+timm_resnest,pass,9
+timm_vision_transformer,pass,9
 timm_vision_transformer_large,pass_due_to_skip,0
-timm_vovnet,pass,8
-tts_angular,pass,10
-vgg16,pass,8
+timm_vovnet,pass,9
+tts_angular,pass,11
+vgg16,pass,9

torch/_dynamo/guards.py

@@ -568,7 +568,7 @@ class GuardBuilder(GuardBuilderBase):
             if not static:
                 if hasattr(value, "_dynamo_dynamic_indices"):
                     code.append(
-                        f"({tensor_name}._dynamo_dynamic_indices.issubset({value._dynamo_dynamic_indices})) if hasattr({tensor_name}, '_dynamo_dynamic_indices') else True"  # noqa: B950
+                        f"(({tensor_name}._dynamo_dynamic_indices.issubset({value._dynamo_dynamic_indices})) if hasattr({tensor_name}, '_dynamo_dynamic_indices') else True)"  # noqa: B950
                     )
                 # In the case of us not having any dynamic dimension indices, we compiled the frame with no chance of
                 # raising for this specific tensor - and any inputs with more dynamic user directives specified must be recompiled.