{'token_ids': [[-1, -1], 'int64'], 'label_ids': [[-1], 'int64']} {'token_ids': [[-1, -1], 'int64']} {'token_ids': [[-1, -1], 'int64'], 'label_ids': [[-1], 'int64'], u'input_mask': [[-1, -1, 1], 'float32'], u'position_ids': [[-1, -1], 'int64'], u'task_ids': [[-1, -1], 'int64'], u'segment_ids': [[-1, -1], 'int64']} {'token_ids': [[-1, -1], 'int64']} preparing data... 0 61 done! name: "tmp_0" type { type: LOD_TENSOR lod_tensor { tensor { data_type: INT64 dims: 1 } lod_level: 0 } } name: "reduce_sum_0.tmp_0" type { type: LOD_TENSOR lod_tensor { tensor { data_type: FP32 dims: 1 } } } persistable: false name: "reduce_sum_1.tmp_0" type { type: LOD_TENSOR lod_tensor { tensor { data_type: FP32 dims: 1 } } } persistable: false random init params... Loading pretraining parameters from pretrain/ernie/params... Warning: cls.cls_out_w not found in pretrain/ernie/params. Warning: cls.cls_out_b not found in pretrain/ernie/params. Warning: senti_cls.cls_out_w not found in pretrain/ernie/params. Warning: senti_cls.cls_out_b not found in pretrain/ernie/params. ok! cls: expected train steps 30. senti_cls: expected train steps 30. ok! Estimated overall train steps 60. {'__task_id': array([0]), u'token_ids': array([[ 101, 2073, 2515, 5843, 4518, 1998, 8460, 2272, 2013, 22254, 12848, 3593, 8787, 6177, 2028, 2012, 1037, 2051, 1012, 100, 26286, 2081, 1996, 1036, 1036, 5843, 1005, 1005, 2029, 2052, 2031, 2042, 1037, 1036, 1036, 2674, 5843, 1005, 1005, 1010, 1036, 1036, 5217, 5843, 1005, 1005, 1010, 1036, 1036, 13493, 5843, 1005, 1005, 4385, 1012, 102, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [ 101, 100, 12904, 2683, 1010, 100, 2001, 10836, 2011, 2029, 2111, 1029, 100, 100, 2000, 5676, 1996, 3408, 1997, 1996, 100, 1997, 100, 2419, 100, 100, 1010, 2004, 100, 1997, 100, 1010, 2000, 3627, 2004, 4621, 11590, 2104, 1996, 2516, 1997, 100, 1997, 100, 1012, 100, 2516, 2001, 4379, 2000, 2010, 3920, 2365, 2021, 2043, 100, 1005, 1055, 8215, 14153, 2351, 1996, 2516, 1997, 100, 1997, 100, 1998, 100, 1997, 100, 2150, 4372, 21077, 1999, 2028, 102, 0, 0, 0, 0, 0, 0], [ 101, 100, 100, 2003, 1996, 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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]), u'cls.label_ids': array([0, 0, 0, 3]), u'segment_ids': array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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