RuntimeError: cuda runtime error (710) : device-side assert triggered at /pytorch/aten/src/THC/THCReduceAll.cuh:327

from simpletransformers.classification import ClassificationModel model = ClassificationModel(‘xlnet’,‘./xlnetpytorch’,num_labels=536, args={“output_dir”: “/content/drive/My Drive/xlnet”,“save_steps”: 0,‘reprocess_input_data’: True}) model.train_model(train)

Error:- /usr/local/lib/python3.6/dist-packages/transformers/modeling_xlnet.py in forward(self, input_ids, attention_mask, mems, perm_mask, target_mapping, token_type_ids, input_mask, head_mask, inputs_embeds, use_cache, output_attentions, output_hidden_states) 892 # 1 indicates not in the same segment [qlen x klen x bsz] 893 seg_mat = (token_type_ids[:, None] != cat_ids[None, :]).long() –> 894 seg_mat = F.one_hot(seg_mat, num_classes=2).to(dtype_float) 895 else: 896 seg_mat = None

RuntimeError: cuda runtime error (710) : device-side assert triggered at /pytorch/aten/src/THC/THCReduceAll.cuh:327

Also the number of classes in the model is also 536. Here is the config file for the model :- { “attn_type”: “bi”, “bi_data”: false, “bos_token_id”: 1, “clamp_len”: -1, “d_head”: 32, “d_inner”: 1024, “d_model”: 256, “dropout”: 0.1, “end_n_top”: 5, “eos_token_id”: 2, “ff_activation”: “relu”, “id2label”: { “0”: “LABEL_0”, “1”: “LABEL_1”, “2”: “LABEL_2”, “3”: “LABEL_3”, “4”: “LABEL_4”, “5”: “LABEL_5”, “6”: “LABEL_6”, “7”: “LABEL_7”, “8”: “LABEL_8”, “9”: “LABEL_9”, “10”: “LABEL_10”, “11”: “LABEL_11”, “12”: “LABEL_12”, “13”: “LABEL_13”, “14”: “LABEL_14”, “15”: “LABEL_15”, “16”: “LABEL_16”, “17”: “LABEL_17”, “18”: “LABEL_18”, “19”: “LABEL_19”, “20”: “LABEL_20”, “21”: “LABEL_21”, “22”: “LABEL_22”, “23”: “LABEL_23”, “24”: “LABEL_24”, “25”: “LABEL_25”, “26”: “LABEL_26”, “27”: “LABEL_27”, “28”: “LABEL_28”, “29”: “LABEL_29”, “30”: “LABEL_30”, “31”: “LABEL_31”, “32”: “LABEL_32”, “33”: “LABEL_33”, “34”: “LABEL_34”, “35”: “LABEL_35”, “36”: “LABEL_36”, “37”: “LABEL_37”, “38”: “LABEL_38”, “39”: “LABEL_39”, “40”: “LABEL_40”, “41”: “LABEL_41”, “42”: “LABEL_42”, “43”: “LABEL_43”, “44”: “LABEL_44”, “45”: “LABEL_45”, “46”: “LABEL_46”, “47”: “LABEL_47”, “48”: “LABEL_48”, “49”: “LABEL_49”, “50”: “LABEL_50”, “51”: “LABEL_51”, “52”: “LABEL_52”, “53”: “LABEL_53”, “54”: “LABEL_54”, “55”: “LABEL_55”, “56”: “LABEL_56”, “57”: “LABEL_57”, “58”: “LABEL_58”, “59”: “LABEL_59”, “60”: “LABEL_60”, “61”: “LABEL_61”, “62”: “LABEL_62”, “63”: “LABEL_63”, “64”: “LABEL_64”, “65”: “LABEL_65”, “66”: “LABEL_66”, “67”: “LABEL_67”, “68”: “LABEL_68”, “69”: “LABEL_69”, “70”: “LABEL_70”, “71”: “LABEL_71”, “72”: “LABEL_72”, “73”: “LABEL_73”, “74”: “LABEL_74”, “75”: “LABEL_75”, “76”: “LABEL_76”, “77”: “LABEL_77”, “78”: “LABEL_78”, “79”: “LABEL_79”, “80”: “LABEL_80”, “81”: “LABEL_81”, “82”: “LABEL_82”, “83”: “LABEL_83”, “84”: “LABEL_84”, “85”: “LABEL_85”, “86”: “LABEL_86”, “87”: “LABEL_87”, “88”: “LABEL_88”, “89”: “LABEL_89”, “90”: “LABEL_90”, “91”: “LABEL_91”, “92”: “LABEL_92”, “93”: “LABEL_93”, “94”: “LABEL_94”, “95”: “LABEL_95”, “96”: “LABEL_96”, “97”: “LABEL_97”, “98”: “LABEL_98”, “99”: “LABEL_99”, “100”: “LABEL_100”, “101”: “LABEL_101”, “102”: “LABEL_102”, “103”: “LABEL_103”, “104”: “LABEL_104”, “105”: “LABEL_105”, “106”: “LABEL_106”, “107”: “LABEL_107”, “108”: “LABEL_108”, “109”: “LABEL_109”, “110”: “LABEL_110”, “111”: “LABEL_111”, “112”: “LABEL_112”, “113”: “LABEL_113”, “114”: “LABEL_114”, “115”: “LABEL_115”, “116”: “LABEL_116”, “117”: “LABEL_117”, “118”: “LABEL_118”, “119”: “LABEL_119”, “120”: “LABEL_120”, “121”: “LABEL_121”, “122”: “LABEL_122”, “123”: “LABEL_123”, “124”: “LABEL_124”, “125”: “LABEL_125”, “126”: “LABEL_126”, “127”: “LABEL_127”, “128”: “LABEL_128”, “129”: “LABEL_129”, “130”: “LABEL_130”, “131”: “LABEL_131”, “132”: “LABEL_132”, “133”: “LABEL_133”, “134”: “LABEL_134”, “135”: “LABEL_135”, “136”: “LABEL_136”, “137”: “LABEL_137”, “138”: “LABEL_138”, “139”: “LABEL_139”, “140”: “LABEL_140”, “141”: “LABEL_141”, “142”: “LABEL_142”, “143”: “LABEL_143”, “144”: “LABEL_144”, “145”: “LABEL_145”, “146”: “LABEL_146”, “147”: 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Please help. 😃

[Sagar1094]

The spiece.model file was at fault, corrected it and everything ran fine. No issues with this amazing library.

[Sagar1094]

The error with use_cuda=False is :-

The error comes with custom trained xlnet only have tried with pre trained xlnet-large-cased working fine.

100% 243852/243852 [10:52<00:00, 373.61it/s]

Epoch 1 of 1: 0% 0/1 [00:00<?, ?it/s] Running Epoch 0 of 1: 0% 0/30482 [00:00<?, ?it/s]

---

IndexError Traceback (most recent call last) <ipython-input-12-714ec37ce099> in <module>() ----> 1 model.train_model(train)

8 frames /usr/local/lib/python3.6/dist-packages/torch/nn/functional.py in embedding(input, weight, padding_idx, max_norm, norm_type, scale_grad_by_freq, sparse) 1722 # remove once script supports set_grad_enabled 1723 no_grad_embedding_renorm(weight, input, max_norm, norm_type) -> 1724 return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse) 1725 1726

IndexError: index out of range in self