operator name
stringclasses
180 values
used in model
stringclasses
155 values
args
stringlengths
19
5.24k
aten.mean.dim
TIMM/legacy_senet154
((T([32, 2048, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/resnest101e
((T([32, 2048, 8, 8], f16), [-1, -2], True), {})
aten.mean.dim
TorchBench/timm_regnet
((T([32, 224, 56, 56], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_regnet
((T([32, 2240, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TorchBench/timm_regnet
((T([32, 2240, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_efficientnet
((T([32, 240, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_efficientnet
((T([32, 240, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TIMM/resnest101e
((T([32, 256, 16, 16], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_resnest
((T([32, 256, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TIMM/convnext_base
((T([32, 256, 28, 28], f16, stride=(200704, 1, 7168, 256)), [1], True), {})
aten.mean.dim
TIMM/resnest101e
((T([32, 256, 32, 32], f16), [2, 3], True), {})
aten.mean.dim
TIMM/gluon_senet154
((T([32, 256, 56, 56], f16), [2, 3], True), {})
aten.mean.dim
TIMM/legacy_senet154
((T([32, 256, 56, 56], f16), [2, 3], True), {})
aten.mean.dim
TIMM/dpn107
((T([32, 2688, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TorchBench/timm_efficientnet
((T([32, 32, 112, 112], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_regnet
((T([32, 448, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/mobilenet_v3_large
((T([32, 480, 14, 14], f16), [-1, -2], True), {})
aten.mean.dim
TorchBench/timm_efficientnet
((T([32, 480, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/twins_pcpvt_base
((T([32, 49, 512], f16), [1]), {})
aten.mean.dim
TorchBench/timm_resnest
((T([32, 512, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/convnext_base
((T([32, 512, 14, 14], f16, stride=(100352, 1, 7168, 512)), [1], True), {})
aten.mean.dim
TIMM/resnest101e
((T([32, 512, 16, 16], f16), [2, 3], True), {})
aten.mean.dim
TIMM/gluon_senet154
((T([32, 512, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TIMM/legacy_senet154
((T([32, 512, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TIMM/resnest101e
((T([32, 512, 8, 8], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_resnest
((T([32, 64, 56, 56], f16), [2, 3], True), {})
aten.mean.dim
TIMM/resnest101e
((T([32, 64, 64, 64], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/mobilenet_v3_large
((T([32, 672, 14, 14], f16), [-1, -2], True), {})
aten.mean.dim
TorchBench/timm_efficientnet
((T([32, 672, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/mobilenet_v3_large
((T([32, 672, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TorchBench/timm_efficientnet
((T([32, 672, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/mobilenet_v3_large
((T([32, 72, 28, 28], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/convmixer_768_32
((T([32, 768, 32, 32], f16), [-1, -2], True), {})
aten.mean.dim
TorchBench/timm_regnet
((T([32, 896, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/timm_efficientnet
((T([32, 96, 56, 56], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/mobilenet_v3_large
((T([32, 960, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TorchBench/densenet121
((T([4, 1024, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
HuggingFace/DebertaForMaskedLM
((T([4, 512, 768], f32), [-1], True), {})
aten.mean.dim
HuggingFace/DebertaForQuestionAnswering
((T([4, 512, 768], f32), [-1], True), {})
aten.mean.dim
TIMM/ecaresnet101d
((T([64, 1024, 14, 14], f16), [2, 3]), {})
aten.mean.dim
TIMM/densenet121
((T([64, 1024, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/dla102
((T([64, 1024, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/cspdarknet53
((T([64, 1024, 8, 8], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/sebotnet33ts_256
((T([64, 128, 32, 32], f16), [2, 3], True), {})
aten.mean.dim
TIMM/sebotnet33ts_256
((T([64, 1280, 8, 8], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/mixnet_l
((T([64, 1536, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/tf_mixnet_l
((T([64, 1536, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/mixnet_l
((T([64, 1584, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tf_mixnet_l
((T([64, 1584, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/gmlp_s16_224
((T([64, 196, 256], f16), [1]), {})
aten.mean.dim
TIMM/gmixer_24_224
((T([64, 196, 384], f16), [1]), {})
aten.mean.dim
TIMM/mixer_b16_224
((T([64, 196, 768], f16), [1]), {})
aten.mean.dim
TIMM/beit_base_patch16_224
((T([64, 196, 768], f16, stride=(151296, 768, 1)), [1]), {})
aten.mean.dim
TIMM/ecaresnet101d
((T([64, 2048, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/res2net101_26w_4s
((T([64, 2048, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/ecaresnet101d
((T([64, 2048, 7, 7], f16), [2, 3]), {})
aten.mean.dim
TIMM/mixnet_l
((T([64, 240, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tf_mixnet_l
((T([64, 240, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TIMM/sebotnet33ts_256
((T([64, 256, 16, 16], f16), [2, 3], True), {})
aten.mean.dim
TIMM/ecaresnet101d
((T([64, 256, 56, 56], f16), [2, 3]), {})
aten.mean.dim
TIMM/mixnet_l
((T([64, 336, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tf_mixnet_l
((T([64, 336, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/mixnet_l
((T([64, 336, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tf_mixnet_l
((T([64, 336, 28, 28], f16), [2, 3], True), {})
aten.mean.dim
TIMM/mixnet_l
((T([64, 480, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tf_mixnet_l
((T([64, 480, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/swin_base_patch4_window7_224
((T([64, 49, 1024], f16), [1]), {})
aten.mean.dim
TIMM/jx_nest_base
((T([64, 512, 14, 14], f16, stride=(100352, 1, 7168, 512)), [-1, -2], True), {})
aten.mean.dim
TIMM/ecaresnet101d
((T([64, 512, 28, 28], f16), [2, 3]), {})
aten.mean.dim
TIMM/mixnet_l
((T([64, 624, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tf_mixnet_l
((T([64, 624, 14, 14], f16), [2, 3], True), {})
aten.mean.dim
TIMM/sebotnet33ts_256
((T([64, 64, 64, 64], f16), [2, 3], True), {})
aten.mean.dim
TIMM/mobilevit_s
((T([64, 640, 8, 8], f16), [-1, -2], True), {})
aten.mean.dim
TIMM/poolformer_m36
((T([64, 768, 7, 7], f16), [-2, -1]), {})
aten.mean.dim
TIMM/mixnet_l
((T([64, 960, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TIMM/tf_mixnet_l
((T([64, 960, 7, 7], f16), [2, 3], True), {})
aten.mean.dim
TorchBench/resnext50_32x4d
((T([8, 2048, 7, 7], f16), [-1, -2], True), {})
aten.mean.dim
TorchBench/mobilenet_v2
((T([96, 1280, 7, 7], f16), [-1, -2], True), {})
aten.min.default
TorchBench/vision_maskrcnn
((T([2], i64),), {})
aten.minimum.default
HuggingFace/BigBird
((T([1, 1, 1, 448], f16), T([1, 12, 64, 448], f32)), {})
aten.minimum.default
TorchBench/hf_BigBird
((T([2, 1, 1, 448], f16), T([2, 12, 64, 448], f32)), {})
aten.minimum.default
TorchBench/timm_efficientdet
((T([5000, 4], f32), T([4], f16)), {})
aten.minimum.default
TorchBench/vision_maskrcnn
((T([], f32), T([], f32)), {})
aten.mm.default
TorchBench/vision_maskrcnn
((T([0, 1024], f16), T([1024, 1024], f16)), {})
aten.mm.default
TorchBench/vision_maskrcnn
((T([0, 1024], f16), T([1024, 12544], f16)), {})
aten.mm.default
TorchBench/vision_maskrcnn
((T([0, 364], f16), T([364, 1024], f16)), {})
aten.mm.default
TorchBench/vision_maskrcnn
((T([0, 91], f16), T([91, 1024], f16)), {})
aten.mm.default
TorchBench/fambench_dlrm
((T([1, 1024], f16), T([1024, 4000], f16)), {})
aten.mm.default
TIMM/volo_d1_224
((T([1000, 12544], f16, stride=(1, 1000)), T([12544, 384], f16)), {})
aten.mm.default
TorchBench/shufflenet_v2_x1_0
((T([1000, 128], f16, stride=(0, 0)), T([128, 1024], f16)), {})
aten.mm.default
TorchBench/timm_nfnet
((T([1000, 128], f16, stride=(0, 0)), T([128, 3072], f16)), {})
aten.mm.default
TorchBench/alexnet
((T([1000, 128], f16, stride=(0, 0)), T([128, 4096], f16)), {})
aten.mm.default
TIMM/ese_vovnet19b_dw
((T([1000, 128], f16, stride=(1, 1000)), T([128, 1024], f16)), {})
aten.mm.default
TIMM/selecsls42b
((T([1000, 128], f16, stride=(1, 1000)), T([128, 1024], f16)), {})
aten.mm.default
TIMM/ghostnet_100
((T([1000, 128], f16, stride=(1, 1000)), T([128, 1280], f16)), {})
aten.mm.default
TIMM/hardcorenas_a
((T([1000, 128], f16, stride=(1, 1000)), T([128, 1280], f16)), {})
aten.mm.default
TIMM/lcnet_050
((T([1000, 128], f16, stride=(1, 1000)), T([128, 1280], f16)), {})
aten.mm.default
TIMM/mnasnet_100
((T([1000, 128], f16, stride=(1, 1000)), T([128, 1280], f16)), {})
aten.mm.default
TIMM/mobilenetv2_100
((T([1000, 128], f16, stride=(1, 1000)), T([128, 1280], f16)), {})
aten.mm.default
TIMM/mobilenetv3_large_100
((T([1000, 128], f16, stride=(1, 1000)), T([128, 1280], f16)), {})