Datasets:
GPUMODE
/
backendbench_tests

Dataset card Data Studio Files
xet
 Community
6
operator name
stringclasses
180 values
used in model
stringclasses
155 values
args
stringlengths
19
5.24k
aten.cat.default
TIMM/mixnet_l
(([T([64, 792, 7, 7], f16), T([64, 792, 7, 7], f16)], 1), {})
aten.cat.default
TIMM/tf_mixnet_l
(([T([64, 792, 7, 7], f16), T([64, 792, 7, 7], f16)], 1), {})
aten.cat.default
TIMM/mixnet_l
(([T([64, 80, 14, 14], f16), T([64, 80, 14, 14], f16)], 1), {})
aten.cat.default
TIMM/tf_mixnet_l
(([T([64, 80, 14, 14], f16), T([64, 80, 14, 14], f16)], 1), {})
aten.cat.default
TIMM/mixnet_l
(([T([64, 96, 112, 112], f16), T([64, 96, 112, 112], f16)], 1), {})
aten.cat.default
TIMM/tf_mixnet_l
(([T([64, 96, 112, 112], f16), T([64, 96, 112, 112], f16)], 1), {})
aten.cat.default
TIMM/mobilevit_s
(([T([64, 96, 32, 32], f16), T([64, 96, 32, 32], f16)], 1), {})
aten.cat.default
TIMM/mixnet_l
(([T([64, 96, 56, 56], f16), T([64, 96, 56, 56], f16)], 1), {})
aten.cat.default
TIMM/tf_mixnet_l
(([T([64, 96, 56, 56], f16), T([64, 96, 56, 56], f16)], 1), {})
aten.cat.default
TIMM/beit_base_patch16_224
(([T([768], f16), T([768], f16), T([768], f16)],), {})
aten.cat.default
TorchBench/timm_vision_transformer
(([T([8, 1, 384], f16, stride=(0, 384, 1)), T([8, 196, 384], f16, stride=(75264, 1, 196))], 1), {})
aten.cat.default
HuggingFace/MegatronBertForQuestionAnswering
(([T([8, 128, 1], f16), T([8, 128, 1], f16)], 2), {})
aten.cat.default
TorchBench/yolov3
(([T([8, 128, 48, 64], f16), T([8, 256, 48, 64], f16)], 1), {})
aten.cat.default
TorchBench/yolov3
(([T([8, 256, 24, 32], f16), T([8, 512, 24, 32], f16)], 1), {})
aten.cat.default
TorchBench/yolov3
(([T([8, 512, 12, 16], f16), T([8, 512, 12, 16], f16), T([8, 512, 12, 16], f16), T([8, 512, 12, 16], f16)], 1), {})
aten.cat.default
TorchBench/yolov3
(([T([8, 576, 85], f16), T([8, 2304, 85], f16), T([8, 9216, 85], f16)], 1), {})
aten.cat.default
TorchBench/speech_transformer
(([T([9], i64), T([1], i64)],), {})
aten.clamp.default
TorchBench/vision_maskrcnn
((T([0, 182], f16), 0, 1115), {})
aten.clamp.default
TorchBench/vision_maskrcnn
((T([0, 182], f16), 0, 1155), {})
aten.clamp.default
TorchBench/vision_maskrcnn
((T([0, 182], f16), 0, 1199), {})
aten.clamp.default
TorchBench/vision_maskrcnn
((T([0, 182], f16), 0, 799), {})
aten.clamp.default
TorchBench/vision_maskrcnn
((T([0, 182], f16), 0, 800), {})
aten.clamp.default
TorchBench/vision_maskrcnn
((T([0, 91], f16), None, 4.135166556742356), {})
aten.clamp.default
TorchBench/vision_maskrcnn
((T([0], f32), 2, 5), {})
aten.clamp.default
TorchBench/vision_maskrcnn
((T([1438452, 1], f16), None, 4.135166556742356), {})
aten.clamp.default
HuggingFace/DebertaV2ForQuestionAnswering
((T([1], i64), 0, 512), {})
aten.clamp.default
HuggingFace/AlbertForQuestionAnswering
((T([2], i64), 0, 512), {})
aten.clamp.default
HuggingFace/DistilBertForQuestionAnswering
((T([32], i64), 0, 128), {})
aten.clamp.default
HuggingFace/MobileBertForQuestionAnswering
((T([32], i64), 0, 128), {})
aten.clamp.default
HuggingFace/DebertaForQuestionAnswering
((T([4], i64), 0, 512), {})
aten.clamp.default
TorchBench/vision_maskrcnn
((T([5000, 2], f16, stride=(4, 2)), 0, 1115), {})
aten.clamp.default
TorchBench/vision_maskrcnn
((T([5000, 2], f16, stride=(4, 2)), 0, 1155), {})
aten.clamp.default
TorchBench/vision_maskrcnn
((T([5000, 2], f16, stride=(4, 2)), 0, 1199), {})
aten.clamp.default
TorchBench/vision_maskrcnn
((T([5000, 2], f16, stride=(4, 2)), 0, 799), {})
aten.clamp.default
TorchBench/vision_maskrcnn
((T([5000, 2], f16, stride=(4, 2)), 0, 800), {})
aten.clamp.default
TorchBench/timm_efficientdet
((T([5000, 4], f32), 0), {})
aten.clamp.default
HuggingFace/BertForQuestionAnswering
((T([64], i64), 0, 128), {})
aten.clamp.default
HuggingFace/RobertaForQuestionAnswering
((T([64], i64), 0, 128), {})
aten.clamp.default
HuggingFace/ElectraForQuestionAnswering
((T([64], i64), 0, 512), {})
aten.clamp.default
HuggingFace/MegatronBertForQuestionAnswering
((T([8], i64), 0, 128), {})
aten.clamp_min.default
TorchBench/tts_angular
((T([64, 1], f16), 1e-12), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 10, 1, 1], f16),), {})
aten.clone.default
HuggingFace/AllenaiLongformerBase
((T([1, 1024], i64),), {})
aten.clone.default
HuggingFace/BigBird
((T([1, 1024], i64),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 1152, 20, 20], f16),), {})
aten.clone.default
HuggingFace/GPTNeoForCausalLM
((T([1, 128], i64),), {})
aten.clone.default
HuggingFace/GPTNeoForSequenceClassification
((T([1, 128], i64),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 144, 160, 160], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 144, 80, 80], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 16, 320, 320], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 1920, 20, 20], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 20, 1, 1], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 240, 40, 40], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 240, 80, 80], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 28, 1, 1], f16),), {})
aten.clone.default
TorchBench/pytorch_CycleGAN_and_pix2pix
((T([1, 3, 256, 256], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 3, 640, 640], f16),), {})
aten.clone.default
TorchBench/pytorch_unet
((T([1, 3, 640, 959], f16),), {})
aten.clone.default
TorchBench/attention_is_all_you_need_pytorch
((T([1, 31, 512], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 32, 320, 320], f16),), {})
aten.clone.default
TorchBench/attention_is_all_you_need_pytorch
((T([1, 33, 512], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 4, 1, 1], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 48, 1, 1], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 480, 40, 40], f16),), {})
aten.clone.default
HuggingFace/CamemBert
((T([1, 512], i64),), {})
aten.clone.default
HuggingFace/DebertaV2ForMaskedLM
((T([1, 512], i64),), {})
aten.clone.default
HuggingFace/DebertaV2ForQuestionAnswering
((T([1, 512], i64),), {})
aten.clone.default
HuggingFace/DistillGPT2
((T([1, 512], i64),), {})
aten.clone.default
HuggingFace/ElectraForCausalLM
((T([1, 512], i64),), {})
aten.clone.default
HuggingFace/GoogleFnet
((T([1, 512], i64),), {})
aten.clone.default
HuggingFace/YituTechConvBert
((T([1, 512], i64),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 6, 1, 1], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 672, 20, 20], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 672, 40, 40], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 8, 1, 1], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 80, 1, 1], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 88, 10, 10], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 88, 20, 20], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 88, 40, 40], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 88, 5, 5], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 88, 80, 80], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 96, 160, 160], f16),), {})
aten.clone.default
TorchBench/timm_efficientdet
((T([1, 96, 320, 320], f16),), {})
aten.clone.default
TorchBench/speech_transformer
((T([10, 204, 320], f16),), {})
aten.clone.default
TorchBench/speech_transformer
((T([10, 21], i64),), {})
aten.clone.default
TorchBench/fambench_dlrm
((T([1024, 2000], f16),), {})
aten.clone.default
TorchBench/speech_transformer
((T([10], i64),), {})
aten.clone.default
TIMM/tf_efficientnet_b0
((T([128, 10, 1, 1], f16),), {})
aten.clone.default
TIMM/tinynet_a
((T([128, 10, 1, 1], f16),), {})
aten.clone.default
TIMM/eca_botnext26ts_256
((T([128, 1024, 16, 16], f16),), {})
aten.clone.default
TIMM/eca_halonext26ts
((T([128, 1024, 16, 16], f16),), {})
aten.clone.default
TIMM/rexnet_100
((T([128, 1044, 7, 7], f16),), {})
aten.clone.default
TIMM/fbnetv3_b
((T([128, 1104, 7, 7], f16),), {})
aten.clone.default
TIMM/tinynet_a
((T([128, 1152, 6, 6], f16),), {})
aten.clone.default
TIMM/hardcorenas_a
((T([128, 1152, 7, 7], f16),), {})
aten.clone.default
TIMM/tf_efficientnet_b0
((T([128, 1152, 7, 7], f16),), {})
aten.clone.default
TIMM/fbnetv3_b
((T([128, 120, 28, 28], f16),), {})
aten.clone.default
TIMM/fbnetv3_b
((T([128, 120, 56, 56], f16),), {})
aten.clone.default
TIMM/lcnet_050
((T([128, 128, 14, 14], f16),), {})
aten.clone.default
TIMM/nfnet_l0
((T([128, 128, 28, 28], f16),), {})