Models not supported by white box XAI methods
goodsong81 opened this issue · 1 comments
goodsong81 commented
Following models are not yet supported in addition to NOT_SUPPORTED_BY_BB_MODELS mentioned in #29 due to various reasons.
SUPPORTED_BUT_FAILED_BY_WB_MODELS = {
# "convformer": "Cannot find output backbone_node in auto mode, please provide target_layer.",
"swin": "Only two outputs of the between block Add node supported, but got 1. Try to use black-box.",
"vit_base_patch16_rpn_224": "Number of normalization outputs > 1",
"vit_relpos_medium_patch16_rpn_224": "ValueError in openvino_xai/methods/white_box/recipro_cam.py:215",
}
NOT_SUPPORTED_BY_WB_MODELS = {
**NOT_SUPPORTED_BY_BB_MODELS,
# Killed on WB
"beit_large_patch16_512": "Failed to allocate 94652825600 bytes of memory",
"convmixer_1536_20": "OOM Killed",
"eva_large_patch14_336": "OOM Killed",
"eva02_base_patch14_448": "OOM Killed",
"eva02_large_patch14_448": "OOM Killed",
"mobilevit_": "Segmentation fault",
"mobilevit_xxs": "Segmentation fault",
"mvitv2_base.fb_in1k": "Segmentation fault",
"mvitv2_large": "OOM Killed",
"mvitv2_small": "Segmentation fault",
"mvitv2_tiny": "Segmentation fault",
"pit_": "Segmentation fault",
"pvt_": "Segmentation fault",
"tf_efficientnet_l2.ns_jft_in1k": "OOM Killed",
"xcit_large": "Failed to allocate 81581875200 bytes of memory",
"xcit_medium_24_p8_384": "OOM Killed",
"xcit_small_12_p8_384": "OOM Killed",
"xcit_small_24_p8_384": "OOM Killed",
# Not expected to work for now
# "botnet26t_256": "Only two outputs of the between block Add node supported, but got 1",
# "caformer": "One (and only one) of the nodes has to be Add type. But got MVN and Multiply.",
"cait_": "Cannot create an empty Constant. Please provide valid data.",
"coat_": "Only two outputs of the between block Add node supported, but got 1.",
# "coatn": "Cannot find output backbone_node in auto mode, please provide target_layer.",
"convmixer": "Cannot find output backbone_node in auto mode, please provide target_layer.",
"crossvit": "One (and only one) of the nodes has to be Add type. But got StridedSlice and StridedSlice.",
# "davit": "Only two outputs of the between block Add node supported, but got 1.",
# "edgenext": "Only two outputs of the between block Add node supported, but got 1",
# "efficientformer": "Cannot find output backbone_node in auto mode.",
# "focalnet": "Cannot find output backbone_node in auto mode, please provide target_layer.",
# "gcvit": "Cannot find output backbone_node in auto mode, please provide target_layer.",
"levit_": "Cannot find output backbone_node in auto mode, please provide target_layer.",
# "maxvit": "Cannot find output backbone_node in auto mode, please provide target_layer.",
# "maxxvit": "Cannot find output backbone_node in auto mode, please provide target_layer.",
# "mobilevitv2": "Cannot find output backbone_node in auto mode, please provide target_layer.",
# "nest_": "Cannot find output backbone_node in auto mode, please provide target_layer.",
# "poolformer": "Cannot find output backbone_node in auto mode, please provide target_layer.",
# "sebotnet": "Only two outputs of the between block Add node supported, but got 1.",
"sequencer2d": "Cannot find output backbone_node in auto mode, please provide target_layer.",
"tnt_s_patch16_224": "Only two outputs of the between block Add node supported, but got 1.",
# "tresnet": "Batch shape of the output should be dynamic, but it is static.",
"twins": "One (and only one) of the nodes has to be Add type. But got ShapeOf and Transpose.",
# "visformer": "Cannot find output backbone_node in auto mode, please provide target_layer",
}goodsong81 commented