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使用自己的训练数据集进行模型训练,在bert_ner_api.py的main函数中选择use_train = False进行预测时,报错: tensorflow.python.framework.errors_impl.InvalidArgumentError: Assign requires shapes of both tensors to match. lhs shape= [10] rhs shape= [11] 但我并无修改代码中任何位置
The text was updated successfully, but these errors were encountered:
这个错误表明在恢复检查点时,TensorFlow 发现当前模型的张量形状与检查点中的张量形状不匹配。具体来说,左侧张量的形状是 [10],而右侧张量的形状是 [11]。这通常是由于模型定义与保存的检查点不匹配导致的。
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使用自己的训练数据集进行模型训练,在bert_ner_api.py的main函数中选择use_train = False进行预测时,报错:
tensorflow.python.framework.errors_impl.InvalidArgumentError: Assign requires shapes of both tensors to match. lhs shape= [10] rhs shape= [11]
但我并无修改代码中任何位置
The text was updated successfully, but these errors were encountered: