Ошибка при обучении модели "a mismatch between the current graph and the graph"

Добрый день! Пытаюсь обучить модель ner_rus_bert. Скрипт обучения :

from deeppavlov import configs, train_model
from deeppavlov.core.commands.utils import parse_config
ner_model = train_model(configs.ner.ner_rus_bert, download=False)

Возникает ошибка : InvalidArgumentError: Restoring from checkpoint failed. This is most likely due to a mismatch between the current graph and the graph from the checkpoint. Please ensure that you have not altered the graph expected based on the checkpoint.

Стек :

    2020-03-23 09:50:45.511 INFO in 'deeppavlov.core.trainers.fit_trainer'['fit_trainer'] at line 68: NNTrainer got additional init parameters ['pytest_max_batches', 'pytest_batch_size'] that will be ignored:
    2020-03-23 09:50:46.20 INFO in 'deeppavlov.core.data.simple_vocab'['simple_vocab'] at line 115: [loading vocabulary from C:\Users\JDrey\.deeppavlov\models\ner_rus_bert\tag.dict]
    2020-03-23 09:50:46.21 INFO in 'deeppavlov.core.data.simple_vocab'['simple_vocab'] at line 101: [saving vocabulary to C:\Users\JDrey\.deeppavlov\models\ner_rus_bert\tag.dict]
    2020-03-23 09:51:12.212 INFO in 'deeppavlov.core.models.tf_model'['tf_model'] at line 51: [loading model from C:\Users\JDrey\.deeppavlov\models\ner_rus_bert\model]
    INFO:tensorflow:Restoring parameters from C:\Users\JDrey\.deeppavlov\models\ner_rus_bert\model
    2020-03-23 09:51:15.552 ERROR in 'deeppavlov.core.common.params'['params'] at line 112: Exception in <class 'deeppavlov.models.bert.bert_sequence_tagger.BertSequenceTagger'>
    Traceback (most recent call last):
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\client\session.py", line 1365, in _do_call
        return fn(*args)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\client\session.py", line 1350, in _run_fn
        target_list, run_metadata)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\client\session.py", line 1443, in _call_tf_sessionrun
        run_metadata)
    tensorflow.python.framework.errors_impl.InvalidArgumentError: Assign requires shapes of both tensors to match. lhs shape= [3] rhs shape= [7]
             [[{{node save/Assign_280}}]]

    During handling of the above exception, another exception occurred:

    Traceback (most recent call last):
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 1290, in restore
        {self.saver_def.filename_tensor_name: save_path})
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\client\session.py", line 956, in run
        run_metadata_ptr)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\client\session.py", line 1180, in _run
        feed_dict_tensor, options, run_metadata)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\client\session.py", line 1359, in _do_run
        run_metadata)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\client\session.py", line 1384, in _do_call
        raise type(e)(node_def, op, message)
    tensorflow.python.framework.errors_impl.InvalidArgumentError: Assign requires shapes of both tensors to match. lhs shape= [3] rhs shape= [7]
             [[node save/Assign_280 (defined at d:\anaconda\lib\site-packages\tensorflow_core\python\framework\ops.py:1748) ]]

    Original stack trace for 'save/Assign_280':
      File "d:\anaconda\lib\runpy.py", line 193, in _run_module_as_main
        "__main__", mod_spec)
      File "d:\anaconda\lib\runpy.py", line 85, in _run_code
        exec(code, run_globals)
      File "d:\anaconda\lib\site-packages\spyder_kernels\console\__main__.py", line 11, in <module>
        start.main()
      File "d:\anaconda\lib\site-packages\spyder_kernels\console\start.py", line 318, in main
        kernel.start()
      File "d:\anaconda\lib\site-packages\ipykernel\kernelapp.py", line 563, in start
        self.io_loop.start()
      File "d:\anaconda\lib\site-packages\tornado\platform\asyncio.py", line 148, in start
        self.asyncio_loop.run_forever()
      File "d:\anaconda\lib\asyncio\base_events.py", line 534, in run_forever
        self._run_once()
      File "d:\anaconda\lib\asyncio\base_events.py", line 1771, in _run_once
        handle._run()
      File "d:\anaconda\lib\asyncio\events.py", line 88, in _run
        self._context.run(self._callback, *self._args)
      File "d:\anaconda\lib\site-packages\tornado\ioloop.py", line 690, in <lambda>
        lambda f: self._run_callback(functools.partial(callback, future))
      File "d:\anaconda\lib\site-packages\tornado\ioloop.py", line 743, in _run_callback
        ret = callback()
      File "d:\anaconda\lib\site-packages\tornado\gen.py", line 787, in inner
        self.run()
      File "d:\anaconda\lib\site-packages\tornado\gen.py", line 748, in run
        yielded = self.gen.send(value)
      File "d:\anaconda\lib\site-packages\ipykernel\kernelbase.py", line 365, in process_one
        yield gen.maybe_future(dispatch(*args))
      File "d:\anaconda\lib\site-packages\tornado\gen.py", line 209, in wrapper
        yielded = next(result)
      File "d:\anaconda\lib\site-packages\ipykernel\kernelbase.py", line 272, in dispatch_shell
        yield gen.maybe_future(handler(stream, idents, msg))
      File "d:\anaconda\lib\site-packages\tornado\gen.py", line 209, in wrapper
        yielded = next(result)
      File "d:\anaconda\lib\site-packages\ipykernel\kernelbase.py", line 542, in execute_request
        user_expressions, allow_stdin,
      File "d:\anaconda\lib\site-packages\tornado\gen.py", line 209, in wrapper
        yielded = next(result)
      File "d:\anaconda\lib\site-packages\ipykernel\ipkernel.py", line 294, in do_execute
        res = shell.run_cell(code, store_history=store_history, silent=silent)
      File "d:\anaconda\lib\site-packages\ipykernel\zmqshell.py", line 536, in run_cell
        return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
      File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 2855, in run_cell
        raw_cell, store_history, silent, shell_futures)
      File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 2881, in _run_cell
        return runner(coro)
      File "d:\anaconda\lib\site-packages\IPython\core\async_helpers.py", line 68, in _pseudo_sync_runner
        coro.send(None)
      File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 3058, in run_cell_async
        interactivity=interactivity, compiler=compiler, result=result)
      File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 3249, in run_ast_nodes
        if (await self.run_code(code, result,  async_=asy)):
      File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 3326, in run_code
        exec(code_obj, self.user_global_ns, self.user_ns)
      File "<ipython-input-6-62567f577e80>", line 1, in <module>
        runfile('D:/Jdrey/PyNet/testLoad/train_pavlov.py', wdir='D:/Jdrey/PyNet/testLoad')
      File "d:\anaconda\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 827, in runfile
        execfile(filename, namespace)
      File "d:\anaconda\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 110, in execfile
        exec(compile(f.read(), filename, 'exec'), namespace)
      File "D:/Jdrey/PyNet/testLoad/train_pavlov.py", line 19, in <module>
        ner_model = train_model(configs.ner.ner_rus_bert, download=False)
      File "d:\anaconda\lib\site-packages\deeppavlov\__init__.py", line 32, in train_model
        train_evaluate_model_from_config(config, download=download, recursive=recursive)
      File "d:\anaconda\lib\site-packages\deeppavlov\core\commands\train.py", line 121, in train_evaluate_model_from_config
        trainer.train(iterator)
      File "d:\anaconda\lib\site-packages\deeppavlov\core\trainers\nn_trainer.py", line 333, in train
        self.fit_chainer(iterator)
      File "d:\anaconda\lib\site-packages\deeppavlov\core\trainers\fit_trainer.py", line 104, in fit_chainer
        component = from_params(component_config, mode='train')
      File "d:\anaconda\lib\site-packages\deeppavlov\core\common\params.py", line 106, in from_params
        component = obj(**dict(config_params, **kwargs))
      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 76, in __call__
        obj.__init__(*args, **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 28, in _wrapped
        return func(*args, **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 529, in __init__
        **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 259, in __init__
        self.load()
      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 28, in _wrapped
        return func(*args, **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 457, in load
        return super().load(exclude_scopes=exclude_scopes, **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py", line 251, in load
        return super().load(exclude_scopes=exclude_scopes, **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py", line 54, in load
        saver = tf.train.Saver(var_list)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 828, in __init__
        self.build()
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 840, in build
        self._build(self._filename, build_save=True, build_restore=True)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 878, in _build
        build_restore=build_restore)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 508, in _build_internal
        restore_sequentially, reshape)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 350, in _AddRestoreOps
        assign_ops.append(saveable.restore(saveable_tensors, shapes))
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saving\saveable_object_util.py", line 73, in restore
        self.op.get_shape().is_fully_defined())
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\ops\state_ops.py", line 227, in assign
        validate_shape=validate_shape)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\ops\gen_state_ops.py", line 65, in assign
        use_locking=use_locking, name=name)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\framework\op_def_library.py", line 794, in _apply_op_helper
        op_def=op_def)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\util\deprecation.py", line 507, in new_func
        return func(*args, **kwargs)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\framework\ops.py", line 3357, in create_op
        attrs, op_def, compute_device)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\framework\ops.py", line 3426, in _create_op_internal
        op_def=op_def)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\framework\ops.py", line 1748, in __init__
        self._traceback = tf_stack.extract_stack()

Весь стек не помещается, добавлю конец в комментарии.

Нашла вот такой совет “The model was laded from the old path. the BERT model in the config has load_path and save_path . The old model has different number of tags in the top layer. You should remove the old model from the load_path .” (https://github.com/deepmipt/DeepPavlov/issues/839), но в config пути load_path и save_path одинаковые, соответственно, модель одна и та же.

Остаток стека :

 During handling of the above exception, another exception occurred:

    Traceback (most recent call last):
      File "d:\anaconda\lib\site-packages\deeppavlov\core\common\params.py", line 106, in from_params
        component = obj(**dict(config_params, **kwargs))
      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 76, in __call__
        obj.__init__(*args, **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 28, in _wrapped
        return func(*args, **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 529, in __init__
        **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 259, in __init__
        self.load()
      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 28, in _wrapped
        return func(*args, **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 457, in load
        return super().load(exclude_scopes=exclude_scopes, **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py", line 251, in load
        return super().load(exclude_scopes=exclude_scopes, **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py", line 55, in load
        saver.restore(self.sess, path)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 1326, in restore
        err, "a mismatch between the current graph and the graph")
    tensorflow.python.framework.errors_impl.InvalidArgumentError: Restoring from checkpoint failed. This is most likely due to a mismatch between the current graph and the graph from the checkpoint. Please ensure that you have not altered the graph expected based on the checkpoint. Original error:

    Assign requires shapes of both tensors to match. lhs shape= [3] rhs shape= [7]
             [[node save/Assign_280 (defined at d:\anaconda\lib\site-packages\tensorflow_core\python\framework\ops.py:1748) ]]

    Original stack trace for 'save/Assign_280':
      File "d:\anaconda\lib\runpy.py", line 193, in _run_module_as_main
        "__main__", mod_spec)
      File "d:\anaconda\lib\runpy.py", line 85, in _run_code
        exec(code, run_globals)
      File "d:\anaconda\lib\site-packages\spyder_kernels\console\__main__.py", line 11, in <module>
        start.main()
      File "d:\anaconda\lib\site-packages\spyder_kernels\console\start.py", line 318, in main
        kernel.start()
      File "d:\anaconda\lib\site-packages\ipykernel\kernelapp.py", line 563, in start
        self.io_loop.start()
      File "d:\anaconda\lib\site-packages\tornado\platform\asyncio.py", line 148, in start
        self.asyncio_loop.run_forever()
      File "d:\anaconda\lib\asyncio\base_events.py", line 534, in run_forever
        self._run_once()
      File "d:\anaconda\lib\asyncio\base_events.py", line 1771, in _run_once
        handle._run()
      File "d:\anaconda\lib\asyncio\events.py", line 88, in _run
        self._context.run(self._callback, *self._args)
      File "d:\anaconda\lib\site-packages\tornado\ioloop.py", line 690, in <lambda>
        lambda f: self._run_callback(functools.partial(callback, future))
      File "d:\anaconda\lib\site-packages\tornado\ioloop.py", line 743, in _run_callback
        ret = callback()
      File "d:\anaconda\lib\site-packages\tornado\gen.py", line 787, in inner
        self.run()
      File "d:\anaconda\lib\site-packages\tornado\gen.py", line 748, in run
        yielded = self.gen.send(value)
      File "d:\anaconda\lib\site-packages\ipykernel\kernelbase.py", line 365, in process_one
        yield gen.maybe_future(dispatch(*args))
      File "d:\anaconda\lib\site-packages\tornado\gen.py", line 209, in wrapper
        yielded = next(result)
      File "d:\anaconda\lib\site-packages\ipykernel\kernelbase.py", line 272, in dispatch_shell
        yield gen.maybe_future(handler(stream, idents, msg))
      File "d:\anaconda\lib\site-packages\tornado\gen.py", line 209, in wrapper
        yielded = next(result)
      File "d:\anaconda\lib\site-packages\ipykernel\kernelbase.py", line 542, in execute_request
        user_expressions, allow_stdin,
      File "d:\anaconda\lib\site-packages\tornado\gen.py", line 209, in wrapper
        yielded = next(result)
      File "d:\anaconda\lib\site-packages\ipykernel\ipkernel.py", line 294, in do_execute
        res = shell.run_cell(code, store_history=store_history, silent=silent)
      File "d:\anaconda\lib\site-packages\ipykernel\zmqshell.py", line 536, in run_cell
        return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
      File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 2855, in run_cell
        raw_cell, store_history, silent, shell_futures)
      File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 2881, in _run_cell
        return runner(coro)
      File "d:\anaconda\lib\site-packages\IPython\core\async_helpers.py", line 68, in _pseudo_sync_runner
        coro.send(None)
      File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 3058, in run_cell_async
        interactivity=interactivity, compiler=compiler, result=result)
      File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 3249, in run_ast_nodes
        if (await self.run_code(code, result,  async_=asy)):
      File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 3326, in run_code
        exec(code_obj, self.user_global_ns, self.user_ns)
      File "<ipython-input-6-62567f577e80>", line 1, in <module>
        runfile('D:/Jdrey/PyNet/testLoad/train_pavlov.py', wdir='D:/Jdrey/PyNet/testLoad')
      File "d:\anaconda\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 827, in runfile
        execfile(filename, namespace)
      File "d:\anaconda\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 110, in execfile
        exec(compile(f.read(), filename, 'exec'), namespace)
      File "D:/Jdrey/PyNet/testLoad/train_pavlov.py", line 19, in <module>
        ner_model = train_model(configs.ner.ner_rus_bert, download=False)
      File "d:\anaconda\lib\site-packages\deeppavlov\__init__.py", line 32, in train_model
        train_evaluate_model_from_config(config, download=download, recursive=recursive)
      File "d:\anaconda\lib\site-packages\deeppavlov\core\commands\train.py", line 121, in train_evaluate_model_from_config
        trainer.train(iterator)
      File "d:\anaconda\lib\site-packages\deeppavlov\core\trainers\nn_trainer.py", line 333, in train
        self.fit_chainer(iterator)
      File "d:\anaconda\lib\site-packages\deeppavlov\core\trainers\fit_trainer.py", line 104, in fit_chainer
        component = from_params(component_config, mode='train')
      File "d:\anaconda\lib\site-packages\deeppavlov\core\common\params.py", line 106, in from_params
        component = obj(**dict(config_params, **kwargs))
      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 76, in __call__
        obj.__init__(*args, **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 28, in _wrapped
        return func(*args, **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 529, in __init__
        **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 259, in __init__
        self.load()
      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 28, in _wrapped
        return func(*args, **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 457, in load
        return super().load(exclude_scopes=exclude_scopes, **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py", line 251, in load
        return super().load(exclude_scopes=exclude_scopes, **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py", line 54, in load
        saver = tf.train.Saver(var_list)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 828, in __init__
        self.build()
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 840, in build
        self._build(self._filename, build_save=True, build_restore=True)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 878, in _build
        build_restore=build_restore)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 508, in _build_internal
        restore_sequentially, reshape)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 350, in _AddRestoreOps
        assign_ops.append(saveable.restore(saveable_tensors, shapes))
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saving\saveable_object_util.py", line 73, in restore
        self.op.get_shape().is_fully_defined())
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\ops\state_ops.py", line 227, in assign
        validate_shape=validate_shape)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\ops\gen_state_ops.py", line 65, in assign
        use_locking=use_locking, name=name)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\framework\op_def_library.py", line 794, in _apply_op_helper
        op_def=op_def)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\util\deprecation.py", line 507, in new_func
        return func(*args, **kwargs)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\framework\ops.py", line 3357, in create_op
        attrs, op_def, compute_device)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\framework\ops.py", line 3426, in _create_op_internal
        op_def=op_def)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\framework\ops.py", line 1748, in __init__
        self._traceback = tf_stack.extract_stack()

    Traceback (most recent call last):

      File "<ipython-input-6-62567f577e80>", line 1, in <module>
        runfile('D:/Jdrey/PyNet/testLoad/train_pavlov.py', wdir='D:/Jdrey/PyNet/testLoad')

      File "d:\anaconda\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 827, in runfile
        execfile(filename, namespace)

      File "d:\anaconda\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 110, in execfile
        exec(compile(f.read(), filename, 'exec'), namespace)

      File "D:/Jdrey/PyNet/testLoad/train_pavlov.py", line 19, in <module>
        ner_model = train_model(configs.ner.ner_rus_bert, download=False)

      File "d:\anaconda\lib\site-packages\deeppavlov\__init__.py", line 32, in train_model
        train_evaluate_model_from_config(config, download=download, recursive=recursive)

      File "d:\anaconda\lib\site-packages\deeppavlov\core\commands\train.py", line 121, in train_evaluate_model_from_config
        trainer.train(iterator)

      File "d:\anaconda\lib\site-packages\deeppavlov\core\trainers\nn_trainer.py", line 333, in train
        self.fit_chainer(iterator)

      File "d:\anaconda\lib\site-packages\deeppavlov\core\trainers\fit_trainer.py", line 104, in fit_chainer
        component = from_params(component_config, mode='train')

      File "d:\anaconda\lib\site-packages\deeppavlov\core\common\params.py", line 106, in from_params
        component = obj(**dict(config_params, **kwargs))

      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 76, in __call__
        obj.__init__(*args, **kwargs)

      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 28, in _wrapped
        return func(*args, **kwargs)

      File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 529, in __init__
        **kwargs)

      File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 259, in __init__
        self.load()

      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 28, in _wrapped
        return func(*args, **kwargs)

      File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 457, in load
        return super().load(exclude_scopes=exclude_scopes, **kwargs)

      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py", line 251, in load
        return super().load(exclude_scopes=exclude_scopes, **kwargs)

      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py", line 55, in load
        saver.restore(self.sess, path)

      File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 1326, in restore
        err, "a mismatch between the current graph and the graph")

    InvalidArgumentError: Restoring from checkpoint failed. This is most likely due to a mismatch between the current graph and the graph from the checkpoint. Please ensure that you have not altered the graph expected based on the checkpoint. Original error:

    Assign requires shapes of both tensors to match. lhs shape= [3] rhs shape= [7]
    	 [[node save/Assign_280 (defined at d:\anaconda\lib\site-packages\tensorflow_core\python\framework\ops.py:1748) ]]

    Original stack trace for 'save/Assign_280':
      File "d:\anaconda\lib\runpy.py", line 193, in _run_module_as_main
        "__main__", mod_spec)
      File "d:\anaconda\lib\runpy.py", line 85, in _run_code
        exec(code, run_globals)
      File "d:\anaconda\lib\site-packages\spyder_kernels\console\__main__.py", line 11, in <module>
        start.main()
      File "d:\anaconda\lib\site-packages\spyder_kernels\console\start.py", line 318, in main
        kernel.start()
      File "d:\anaconda\lib\site-packages\ipykernel\kernelapp.py", line 563, in start
        self.io_loop.start()
      File "d:\anaconda\lib\site-packages\tornado\platform\asyncio.py", line 148, in start
        self.asyncio_loop.run_forever()
      File "d:\anaconda\lib\asyncio\base_events.py", line 534, in run_forever
        self._run_once()
      File "d:\anaconda\lib\asyncio\base_events.py", line 1771, in _run_once
        handle._run()
      File "d:\anaconda\lib\asyncio\events.py", line 88, in _run
        self._context.run(self._callback, *self._args)
      File "d:\anaconda\lib\site-packages\tornado\ioloop.py", line 690, in <lambda>
        lambda f: self._run_callback(functools.partial(callback, future))
      File "d:\anaconda\lib\site-packages\tornado\ioloop.py", line 743, in _run_callback
        ret = callback()
      File "d:\anaconda\lib\site-packages\tornado\gen.py", line 787, in inner
        self.run()
      File "d:\anaconda\lib\site-packages\tornado\gen.py", line 748, in run
        yielded = self.gen.send(value)
      File "d:\anaconda\lib\site-packages\ipykernel\kernelbase.py", line 365, in process_one
        yield gen.maybe_future(dispatch(*args))
      File "d:\anaconda\lib\site-packages\tornado\gen.py", line 209, in wrapper
        yielded = next(result)
      File "d:\anaconda\lib\site-packages\ipykernel\kernelbase.py", line 272, in dispatch_shell
        yield gen.maybe_future(handler(stream, idents, msg))
      File "d:\anaconda\lib\site-packages\tornado\gen.py", line 209, in wrapper
        yielded = next(result)
      File "d:\anaconda\lib\site-packages\ipykernel\kernelbase.py", line 542, in execute_request
        user_expressions, allow_stdin,
      File "d:\anaconda\lib\site-packages\tornado\gen.py", line 209, in wrapper
        yielded = next(result)
      File "d:\anaconda\lib\site-packages\ipykernel\ipkernel.py", line 294, in do_execute
        res = shell.run_cell(code, store_history=store_history, silent=silent)
      File "d:\anaconda\lib\site-packages\ipykernel\zmqshell.py", line 536, in run_cell
        return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
      File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 2855, in run_cell
        raw_cell, store_history, silent, shell_futures)
      File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 2881, in _run_cell
        return runner(coro)
      File "d:\anaconda\lib\site-packages\IPython\core\async_helpers.py", line 68, in _pseudo_sync_runner
        coro.send(None)
      File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 3058, in run_cell_async
        interactivity=interactivity, compiler=compiler, result=result)
      File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 3249, in run_ast_nodes
        if (await self.run_code(code, result,  async_=asy)):
      File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 3326, in run_code
        exec(code_obj, self.user_global_ns, self.user_ns)
      File "<ipython-input-6-62567f577e80>", line 1, in <module>
        runfile('D:/Jdrey/PyNet/testLoad/train_pavlov.py', wdir='D:/Jdrey/PyNet/testLoad')
      File "d:\anaconda\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 827, in runfile
        execfile(filename, namespace)
      File "d:\anaconda\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 110, in execfile
        exec(compile(f.read(), filename, 'exec'), namespace)
      File "D:/Jdrey/PyNet/testLoad/train_pavlov.py", line 19, in <module>
        ner_model = train_model(configs.ner.ner_rus_bert, download=False)
      File "d:\anaconda\lib\site-packages\deeppavlov\__init__.py", line 32, in train_model
        train_evaluate_model_from_config(config, download=download, recursive=recursive)
      File "d:\anaconda\lib\site-packages\deeppavlov\core\commands\train.py", line 121, in train_evaluate_model_from_config
        trainer.train(iterator)
      File "d:\anaconda\lib\site-packages\deeppavlov\core\trainers\nn_trainer.py", line 333, in train
        self.fit_chainer(iterator)
      File "d:\anaconda\lib\site-packages\deeppavlov\core\trainers\fit_trainer.py", line 104, in fit_chainer
        component = from_params(component_config, mode='train')
      File "d:\anaconda\lib\site-packages\deeppavlov\core\common\params.py", line 106, in from_params
        component = obj(**dict(config_params, **kwargs))
      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 76, in __call__
        obj.__init__(*args, **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 28, in _wrapped
        return func(*args, **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 529, in __init__
        **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 259, in __init__
        self.load()
      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 28, in _wrapped
        return func(*args, **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 457, in load
        return super().load(exclude_scopes=exclude_scopes, **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py", line 251, in load
        return super().load(exclude_scopes=exclude_scopes, **kwargs)
      File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py", line 54, in load
        saver = tf.train.Saver(var_list)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 828, in __init__
        self.build()
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 840, in build
        self._build(self._filename, build_save=True, build_restore=True)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 878, in _build
        build_restore=build_restore)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 508, in _build_internal
        restore_sequentially, reshape)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 350, in _AddRestoreOps
        assign_ops.append(saveable.restore(saveable_tensors, shapes))
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saving\saveable_object_util.py", line 73, in restore
        self.op.get_shape().is_fully_defined())
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\ops\state_ops.py", line 227, in assign
        validate_shape=validate_shape)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\ops\gen_state_ops.py", line 65, in assign
        use_locking=use_locking, name=name)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\framework\op_def_library.py", line 794, in _apply_op_helper
        op_def=op_def)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\util\deprecation.py", line 507, in new_func
        return func(*args, **kwargs)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\framework\ops.py", line 3357, in create_op
        attrs, op_def, compute_device)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\framework\ops.py", line 3426, in _create_op_internal
        op_def=op_def)
      File "d:\anaconda\lib\site-packages\tensorflow_core\python\framework\ops.py", line 1748, in __init__
        self._traceback = tf_stack.extract_stack()

В итоге просто удалила модель из {NER} и обучение запустилось.

Привет, @IDrei!

Если вы учите модель на своих данных, то итоговые размерности вашей получившейся модели и модели, предобученной на других данных, могут не совпадать из-за разного количества видов сущностей, например.
Поэтому я бы вам советовал скопировать конфигурацию ner_rus_bert в удобное для вас место, убрать из загрузок архив с моделью и поменять data_path в датасет ридере и переменную NER_PATH, чтобы избежать коллизий.

Спасибо за ответ!
Уточняющий вопрос :
после манипуляций из вашего комментария я работаю со скопированной моделью ? (которая “скопировать конфигурацию ner_rus_bert в удобное для вас место” ) ? каким образом тогда мне указать именно эту модель при запуске обучения? Команда

ner_model = train_model(configs.ner.ner_rus_bert)

смотрит только в “своё” обычное место. Я могу одновременно иметь два варианта модели в разных местах, переключаясь с помощью конфига? то есть я представляю это наподобие:

my_ner_model = train_model(configs.ner.my.ner_rus_bert) - здесь используется отредактированный ner_rus_bert.json . но так не работает )))

build_model() и train_model() первым аргументом принимают путь к файлу конфигурации, поэтому можно просто запустить train_model('./my_ner.json'), чтобы запустить тренировку по конфигу my_ner.json, находящемуся в текущей папке.
Структура configs в своих листьях тоже содержит пути.

Во время обучения модели возникает сообщение “Ядро остановилось, перезапуск” и , соответственно, процесс прекращается. С чем это может быть связано?

2020-03-26 15:59:55.875 WARNING in 'deeppavlov.dataset_readers.conll2003_reader'['conll2003_reader'] at line 96: Skip '\xa0\tI-ORG\n', splitted as ['I-ORG']
2020-03-26 15:59:55.896 WARNING in 'deeppavlov.dataset_readers.conll2003_reader'['conll2003_reader'] at line 96: Skip '\xa0\tI-ORG\n', splitted as ['I-ORG']
2020-03-26 15:59:55.915 WARNING in 'deeppavlov.dataset_readers.conll2003_reader'['conll2003_reader'] at line 96: Skip '\xa0\tI-ORG\n', splitted as ['I-ORG']
2020-03-26 15:59:55.919 INFO in 'deeppavlov.core.trainers.fit_trainer'['fit_trainer'] at line 68: NNTrainer got additional init parameters ['pytest_max_batches', 'pytest_batch_size'] that will be ignored:
2020-03-26 15:59:56.446 INFO in 'deeppavlov.core.data.simple_vocab'['simple_vocab'] at line 101: [saving vocabulary to C:\Users\JDrey\.deeppavlov\models\my\ner_rus_bert\tag.dict]
2020-03-26 16:00:23.554 INFO in 'deeppavlov.models.bert.bert_sequence_tagger'['bert_sequence_tagger'] at line 251: [initializing model with Bert from C:\Users\JDrey\.deeppavlov\downloads\bert_models\rubert_cased_L-12_H-768_A-12_v1\bert_model.ckpt]
2020-03-26 16:01:49.891 DEBUG in 'deeppavlov.metrics.fmeasure'['fmeasure'] at line 394: processed 8243 tokens with 1487 phrases; found: 1755 phrases; correct: 0.

precision:  4.50%; recall:  5.31%; FB1:  4.87

        GPE: precision:  6.00%; recall:  13.14%; F1:  8.24 683

        ORG: precision:  3.54%; recall:  3.23%; F1:  3.38 1072


2020-03-26 16:01:49.903 INFO in 'deeppavlov.core.trainers.nn_trainer'['nn_trainer'] at line 198: Initial best ner_f1 of 4.8735
{"valid": {"eval_examples_count": 2261, "metrics": {"ner_f1": 4.8735, "ner_token_f1": 37.0945}, "time_spent": "0:01:24", "epochs_done": 0, "batches_seen": 0, "train_examples_seen": 0, "impatience": 0, "patience_limit": 100}}
2020-03-26 16:03:13.988 DEBUG in 'deeppavlov.metrics.fmeasure'['fmeasure'] at line 394: processed 49 tokens with 11 phrases; found: 0 phrases; correct: 0.

precision:  0.00%; recall:  0.00%; FB1:  0.00

        GPE: precision:  0.00%; recall:  0.00%; F1:  0.00 0

        ORG: precision:  0.00%; recall:  0.00%; F1:  0.00 0


{"train": {"eval_examples_count": 16, "metrics": {"ner_f1": 0, "ner_token_f1": 0}, "time_spent": "0:02:48", "epochs_done": 0, "batches_seen": 20, "train_examples_seen": 320, "head_learning_rate": 0.0010000000474974513, "bert_learning_rate": 2.0000000949949027e-05, "loss": 6.537015223503113}}
2020-03-26 16:04:42.624 DEBUG in 'deeppavlov.metrics.fmeasure'['fmeasure'] at line 394: processed 8243 tokens with 1487 phrases; found: 3 phrases; correct: 0.

precision:  0.00%; recall:  0.00%; FB1:  0.00

        GPE: precision:  0.00%; recall:  0.00%; F1:  0.00 0

        ORG: precision:  0.00%; recall:  0.00%; F1:  0.00 3


2020-03-26 16:04:42.698 INFO in 'deeppavlov.core.trainers.nn_trainer'['nn_trainer'] at line 211: Did not improve on the ner_f1 of 4.8735
{"valid": {"eval_examples_count": 2261, "metrics": {"ner_f1": 0, "ner_token_f1": 0.1461}, "time_spent": "0:04:17", "epochs_done": 0, "batches_seen": 20, "train_examples_seen": 320, "impatience": 1, "patience_limit": 100}}
2020-03-26 16:06:18.35 DEBUG in 'deeppavlov.metrics.fmeasure'['fmeasure'] at line 394: processed 49 tokens with 10 phrases; found: 4 phrases; correct: 0.

precision:  50.00%; recall:  20.00%; FB1:  28.57

        GPE: precision:  0.00%; recall:  0.00%; F1:  0.00 0

        ORG: precision:  50.00%; recall:  28.57%; F1:  36.36 4


{"train": {"eval_examples_count": 16, "metrics": {"ner_f1": 28.5714, "ner_token_f1": 57.1429}, "time_spent": "0:05:52", "epochs_done": 0, "batches_seen": 40, "train_examples_seen": 640, "head_learning_rate": 0.0010000000474974513, "bert_learning_rate": 2.0000000949949027e-05, "loss": 4.112382471561432}}
2020-03-26 16:07:55.785 DEBUG in 'deeppavlov.metrics.fmeasure'['fmeasure'] at line 394: processed 8243 tokens with 1487 phrases; found: 689 phrases; correct: 0.

precision:  77.21%; recall:  35.78%; FB1:  48.90

        GPE: precision:  0.00%; recall:  0.00%; F1:  0.00 0

        ORG: precision:  77.21%; recall:  45.28%; F1:  57.08 689


2020-03-26 16:07:55.830 INFO in 'deeppavlov.core.trainers.nn_trainer'['nn_trainer'] at line 206: Improved best ner_f1 of 48.8971
2020-03-26 16:07:55.831 INFO in 'deeppavlov.core.trainers.nn_trainer'['nn_trainer'] at line 208: Saving model
2020-03-26 16:07:55.982 INFO in 'deeppavlov.core.models.tf_model'['tf_model'] at line 75: [saving model to C:\Users\JDrey\.deeppavlov\models\my\ner_rus_bert\model]
{"valid": {"eval_examples_count": 2261, "metrics": {"ner_f1": 48.8971, "ner_token_f1": 56.6008}, "time_spent": "0:07:30", "epochs_done": 0, "batches_seen": 40, "train_examples_seen": 640, "impatience": 0, "patience_limit": 100}}
2020-03-26 16:09:38.576 DEBUG in 'deeppavlov.metrics.fmeasure'['fmeasure'] at line 394: processed 67 tokens with 11 phrases; found: 4 phrases; correct: 0.

precision:  100.00%; recall:  36.36%; FB1:  53.33

        GPE: precision:  0.00%; recall:  0.00%; F1:  0.00 0

        ORG: precision:  100.00%; recall:  66.67%; F1:  80.00 4


{"train": {"eval_examples_count": 16, "metrics": {"ner_f1": 53.3333, "ner_token_f1": 46.1538}, "time_spent": "0:09:13", "epochs_done": 0, "batches_seen": 60, "train_examples_seen": 960, "head_learning_rate": 0.0010000000474974513, "bert_learning_rate": 2.0000000949949027e-05, "loss": 2.9206926882267}}
2020-03-26 16:11:03.146 DEBUG in 'deeppavlov.metrics.fmeasure'['fmeasure'] at line 394: processed 8243 tokens with 1487 phrases; found: 1267 phrases; correct: 0.

precision:  64.72%; recall:  55.14%; FB1:  59.55

        GPE: precision:  50.00%; recall:  1.28%; F1:  2.50 8

        ORG: precision:  64.81%; recall:  69.45%; F1:  67.05 1259


2020-03-26 16:11:03.204 INFO in 'deeppavlov.core.trainers.nn_trainer'['nn_trainer'] at line 206: Improved best ner_f1 of 59.5497
2020-03-26 16:11:03.205 INFO in 'deeppavlov.core.trainers.nn_trainer'['nn_trainer'] at line 208: Saving model
2020-03-26 16:11:03.354 INFO in 'deeppavlov.core.models.tf_model'['tf_model'] at line 75: [saving model to C:\Users\JDrey\.deeppavlov\models\my\ner_rus_bert\model]
{"valid": {"eval_examples_count": 2261, "metrics": {"ner_f1": 59.5497, "ner_token_f1": 74.7158}, "time_spent": "0:10:37", "epochs_done": 0, "batches_seen": 60, "train_examples_seen": 960, "impatience": 0, "patience_limit": 100}}
2020-03-26 16:12:34.381 DEBUG in 'deeppavlov.metrics.fmeasure'['fmeasure'] at line 394: processed 57 tokens with 12 phrases; found: 10 phrases; correct: 0.

precision:  70.00%; recall:  58.33%; FB1:  63.64

        GPE: precision:  0.00%; recall:  0.00%; F1:  0.00 0

        ORG: precision:  70.00%; recall:  77.78%; F1:  73.68 10


{"train": {"eval_examples_count": 16, "metrics": {"ner_f1": 63.6364, "ner_token_f1": 71.4286}, "time_spent": "0:12:08", "epochs_done": 0, "batches_seen": 80, "train_examples_seen": 1280, "head_learning_rate": 0.0010000000474974513, "bert_learning_rate": 2.0000000949949027e-05, "loss": 2.402541899681091}}
2020-03-26 16:14:02.331 DEBUG in 'deeppavlov.metrics.fmeasure'['fmeasure'] at line 394: processed 8243 tokens with 1487 phrases; found: 1491 phrases; correct: 0.

precision:  58.89%; recall:  59.05%; FB1:  58.97

        GPE: precision:  70.37%; recall:  6.09%; F1:  11.21 27

        ORG: precision:  58.67%; recall:  73.11%; F1:  65.10 1464


2020-03-26 16:14:02.404 INFO in 'deeppavlov.core.trainers.nn_trainer'['nn_trainer'] at line 211: Did not improve on the ner_f1 of 59.5497
{"valid": {"eval_examples_count": 2261, "metrics": {"ner_f1": 58.9657, "ner_token_f1": 79.6518}, "time_spent": "0:13:36", "epochs_done": 0, "batches_seen": 80, "train_examples_seen": 1280, "impatience": 1, "patience_limit": 100}}
2020-03-26 16:15:18.277 DEBUG in 'deeppavlov.metrics.fmeasure'['fmeasure'] at line 394: processed 56 tokens with 10 phrases; found: 11 phrases; correct: 0.

precision:  81.82%; recall:  90.00%; FB1:  85.71

        GPE: precision:  100.00%; recall:  100.00%; F1:  100.00 2

        ORG: precision:  77.78%; recall:  87.50%; F1:  82.35 9


{"train": {"eval_examples_count": 16, "metrics": {"ner_f1": 85.7143, "ner_token_f1": 100.0}, "time_spent": "0:14:52", "epochs_done": 0, "batches_seen": 100, "train_examples_seen": 1600, "head_learning_rate": 0.0010000000474974513, "bert_learning_rate": 2.0000000949949027e-05, "loss": 1.5030339866876603}}
2020-03-26 16:16:45.653 DEBUG in 'deeppavlov.metrics.fmeasure'['fmeasure'] at line 394: processed 8243 tokens with 1487 phrases; found: 1630 phrases; correct: 0.

precision:  61.72%; recall:  67.65%; FB1:  64.55

        GPE: precision:  72.59%; recall:  31.41%; F1:  43.85 135

        ORG: precision:  60.74%; recall:  77.28%; F1:  68.01 1495


2020-03-26 16:16:45.701 INFO in 'deeppavlov.core.trainers.nn_trainer'['nn_trainer'] at line 206: Improved best ner_f1 of 64.5492
2020-03-26 16:16:45.702 INFO in 'deeppavlov.core.trainers.nn_trainer'['nn_trainer'] at line 208: Saving model
2020-03-26 16:16:45.855 INFO in 'deeppavlov.core.models.tf_model'['tf_model'] at line 75: [saving model to C:\Users\JDrey\.deeppavlov\models\my\ner_rus_bert\model]
{"valid": {"eval_examples_count": 2261, "metrics": {"ner_f1": 64.5492, "ner_token_f1": 85.2427}, "time_spent": "0:16:20", "epochs_done": 0, "batches_seen": 100, "train_examples_seen": 1600, "impatience": 0, "patience_limit": 100}}
2020-03-26 16:18:25.196 DEBUG in 'deeppavlov.metrics.fmeasure'['fmeasure'] at line 394: processed 60 tokens with 11 phrases; found: 11 phrases; correct: 0.

precision:  81.82%; recall:  81.82%; FB1:  81.82

        GPE: precision:  100.00%; recall:  100.00%; F1:  100.00 2

        ORG: precision:  77.78%; recall:  77.78%; F1:  77.78 9


{"train": {"eval_examples_count": 16, "metrics": {"ner_f1": 81.8182, "ner_token_f1": 95.4545}, "time_spent": "0:17:59", "epochs_done": 0, "batches_seen": 120, "train_examples_seen": 1920, "head_learning_rate": 0.0010000000474974513, "bert_learning_rate": 2.0000000949949027e-05, "loss": 1.169089126586914}}
2020-03-26 16:19:51.38 DEBUG in 'deeppavlov.metrics.fmeasure'['fmeasure'] at line 394: processed 8243 tokens with 1487 phrases; found: 1593 phrases; correct: 0.

precision:  78.59%; recall:  84.20%; FB1:  81.30

        GPE: precision:  74.23%; recall:  69.23%; F1:  71.64 291

        ORG: precision:  79.57%; recall:  88.17%; F1:  83.65 1302


2020-03-26 16:19:51.69 INFO in 'deeppavlov.core.trainers.nn_trainer'['nn_trainer'] at line 206: Improved best ner_f1 of 81.2987
2020-03-26 16:19:51.70 INFO in 'deeppavlov.core.trainers.nn_trainer'['nn_trainer'] at line 208: Saving model
2020-03-26 16:19:51.217 INFO in 'deeppavlov.core.models.tf_model'['tf_model'] at line 75: [saving model to C:\Users\JDrey\.deeppavlov\models\my\ner_rus_bert\model]

Ядро остановилось, перезапуск

Причём модель, сохранённая перед возникновением ошибки, находится в некорректном состоянии, её невозможно “достать” с помощью build_model (хотя,возможно, это и неправильно делать):

from deeppavlov import configs, build_model
ner_model_my = build_model('d:/anaconda/Lib/site-packages/deeppavlov/configs/ner/my/ner_rus_bert.json', download=False)
[nltk_data] Downloading package punkt to
[nltk_data]     C:\Users\JDrey\AppData\Roaming\nltk_data...
[nltk_data]   Package punkt is already up-to-date!
[nltk_data] Downloading package stopwords to
[nltk_data]     C:\Users\JDrey\AppData\Roaming\nltk_data...
[nltk_data]   Package stopwords is already up-to-date!
[nltk_data] Downloading package perluniprops to
[nltk_data]     C:\Users\JDrey\AppData\Roaming\nltk_data...
[nltk_data]   Package perluniprops is already up-to-date!
[nltk_data] Downloading package nonbreaking_prefixes to
[nltk_data]     C:\Users\JDrey\AppData\Roaming\nltk_data...
[nltk_data]   Package nonbreaking_prefixes is already up-to-date!
WARNING:tensorflow:From d:\anaconda\lib\site-packages\bert_dp\tokenization.py:125: The name tf.gfile.GFile is deprecated. Please use tf.io.gfile.GFile instead.

2020-03-26 16:26:41.589 INFO in 'deeppavlov.core.data.simple_vocab'['simple_vocab'] at line 115: [loading vocabulary from C:\Users\JDrey\.deeppavlov\models\my\ner_rus_bert\tag.dict]
WARNING:tensorflow:From d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py:37: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.

WARNING:tensorflow:From d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py:222: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.

WARNING:tensorflow:From d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py:222: The name tf.train.Optimizer is deprecated. Please use tf.compat.v1.train.Optimizer instead.

WARNING:tensorflow:From d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py:193: The name tf.train.AdamOptimizer is deprecated. Please use tf.compat.v1.train.AdamOptimizer instead.

WARNING:tensorflow:From d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py:236: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead.

WARNING:tensorflow:From d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py:314: The name tf.placeholder_with_default is deprecated. Please use tf.compat.v1.placeholder_with_default instead.

WARNING:tensorflow:From d:\anaconda\lib\site-packages\bert_dp\modeling.py:178: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.

WARNING:tensorflow:From d:\anaconda\lib\site-packages\bert_dp\modeling.py:418: The name tf.get_variable is deprecated. Please use tf.compat.v1.get_variable instead.

WARNING:tensorflow:From d:\anaconda\lib\site-packages\bert_dp\modeling.py:499: The name tf.assert_less_equal is deprecated. Please use tf.compat.v1.assert_less_equal instead.

WARNING:tensorflow:
The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:
  * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
  * https://github.com/tensorflow/addons
  * https://github.com/tensorflow/io (for I/O related ops)
If you depend on functionality not listed there, please file an issue.

WARNING:tensorflow:From d:\anaconda\lib\site-packages\bert_dp\modeling.py:366: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version.
Instructions for updating:
Please use `rate` instead of `keep_prob`. Rate should be set to `rate = 1 - keep_prob`.
WARNING:tensorflow:From d:\anaconda\lib\site-packages\bert_dp\modeling.py:680: dense (from tensorflow.python.layers.core) is deprecated and will be removed in a future version.
Instructions for updating:
Use keras.layers.Dense instead.
WARNING:tensorflow:From d:\anaconda\lib\site-packages\tensorflow_core\python\layers\core.py:187: Layer.apply (from tensorflow.python.keras.engine.base_layer) is deprecated and will be removed in a future version.
Instructions for updating:
Please use `layer.__call__` method instead.
WARNING:tensorflow:From d:\anaconda\lib\site-packages\bert_dp\modeling.py:283: The name tf.erf is deprecated. Please use tf.math.erf instead.

WARNING:tensorflow:Variable *= will be deprecated. Use `var.assign(var * other)` if you want assignment to the variable value or `x = x * y` if you want a new python Tensor object.
WARNING:tensorflow:From d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py:75: where (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.where in 2.0, which has the same broadcast rule as np.where
WARNING:tensorflow:From d:\anaconda\lib\site-packages\tensorflow_core\contrib\crf\python\ops\crf.py:213: dynamic_rnn (from tensorflow.python.ops.rnn) is deprecated and will be removed in a future version.
Instructions for updating:
Please use `keras.layers.RNN(cell)`, which is equivalent to this API
WARNING:tensorflow:From d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py:131: The name tf.get_collection is deprecated. Please use tf.compat.v1.get_collection instead.

WARNING:tensorflow:From d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py:131: The name tf.GraphKeys is deprecated. Please use tf.compat.v1.GraphKeys instead.

WARNING:tensorflow:From d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py:94: The name tf.global_variables is deprecated. Please use tf.compat.v1.global_variables instead.

WARNING:tensorflow:From d:\anaconda\lib\site-packages\tensorflow_core\python\training\moving_averages.py:433: Variable.initialized_value (from tensorflow.python.ops.variables) is deprecated and will be removed in a future version.
Instructions for updating:
Use Variable.read_value. Variables in 2.X are initialized automatically both in eager and graph (inside tf.defun) contexts.
WARNING:tensorflow:From d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py:671: The name tf.assign is deprecated. Please use tf.compat.v1.assign instead.

WARNING:tensorflow:From d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py:244: The name tf.global_variables_initializer is deprecated. Please use tf.compat.v1.global_variables_initializer instead.

WARNING:tensorflow:From d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py:249: checkpoint_exists (from tensorflow.python.training.checkpoint_management) is deprecated and will be removed in a future version.
Instructions for updating:
Use standard file APIs to check for files with this prefix.
2020-03-26 16:27:13.107 INFO in 'deeppavlov.core.models.tf_model'['tf_model'] at line 51: [loading model from C:\Users\JDrey\.deeppavlov\models\my\ner_rus_bert\model]
WARNING:tensorflow:From d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py:54: The name tf.train.Saver is deprecated. Please use tf.compat.v1.train.Saver instead.

INFO:tensorflow:Restoring parameters from C:\Users\JDrey\.deeppavlov\models\my\ner_rus_bert\model
2020-03-26 16:27:15.484 ERROR in 'deeppavlov.core.common.params'['params'] at line 112: Exception in <class 'deeppavlov.models.bert.bert_sequence_tagger.BertSequenceTagger'>
Traceback (most recent call last):
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\client\session.py", line 1365, in _do_call
    return fn(*args)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\client\session.py", line 1350, in _run_fn
    target_list, run_metadata)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\client\session.py", line 1443, in _call_tf_sessionrun
    run_metadata)
tensorflow.python.framework.errors_impl.DataLossError: Checksum does not match: stored 1484353159 vs. calculated on the restored bytes 3522348434
         [[{{node save/RestoreV2}}]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "d:\anaconda\lib\site-packages\deeppavlov\core\common\params.py", line 106, in from_params
    component = obj(**dict(config_params, **kwargs))
  File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 76, in __call__
    obj.__init__(*args, **kwargs)
  File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 28, in _wrapped
    return func(*args, **kwargs)
  File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 529, in __init__
    **kwargs)
  File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 259, in __init__
    self.load()
  File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 28, in _wrapped
    return func(*args, **kwargs)
  File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 457, in load
    return super().load(exclude_scopes=exclude_scopes, **kwargs)
  File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py", line 251, in load
    return super().load(exclude_scopes=exclude_scopes, **kwargs)
  File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py", line 55, in load
    saver.restore(self.sess, path)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 1290, in restore
    {self.saver_def.filename_tensor_name: save_path})
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\client\session.py", line 956, in run
    run_metadata_ptr)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\client\session.py", line 1180, in _run
    feed_dict_tensor, options, run_metadata)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\client\session.py", line 1359, in _do_run
    run_metadata)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\client\session.py", line 1384, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.DataLossError: Checksum does not match: stored 1484353159 vs. calculated on the restored bytes 3522348434
         [[node save/RestoreV2 (defined at d:\anaconda\lib\site-packages\tensorflow_core\python\framework\ops.py:1748) ]]

Original stack trace for 'save/RestoreV2':
  File "d:\anaconda\lib\runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "d:\anaconda\lib\runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "d:\anaconda\lib\site-packages\spyder_kernels\console\__main__.py", line 11, in <module>
    start.main()
  File "d:\anaconda\lib\site-packages\spyder_kernels\console\start.py", line 318, in main
    kernel.start()
  File "d:\anaconda\lib\site-packages\ipykernel\kernelapp.py", line 563, in start
    self.io_loop.start()
  File "d:\anaconda\lib\site-packages\tornado\platform\asyncio.py", line 148, in start
    self.asyncio_loop.run_forever()
  File "d:\anaconda\lib\asyncio\base_events.py", line 534, in run_forever
    self._run_once()
  File "d:\anaconda\lib\asyncio\base_events.py", line 1771, in _run_once
    handle._run()
  File "d:\anaconda\lib\asyncio\events.py", line 88, in _run
    self._context.run(self._callback, *self._args)
  File "d:\anaconda\lib\site-packages\tornado\ioloop.py", line 690, in <lambda>
    lambda f: self._run_callback(functools.partial(callback, future))
  File "d:\anaconda\lib\site-packages\tornado\ioloop.py", line 743, in _run_callback
    ret = callback()
  File "d:\anaconda\lib\site-packages\tornado\gen.py", line 787, in inner
    self.run()
  File "d:\anaconda\lib\site-packages\tornado\gen.py", line 748, in run
    yielded = self.gen.send(value)
  File "d:\anaconda\lib\site-packages\ipykernel\kernelbase.py", line 365, in process_one
    yield gen.maybe_future(dispatch(*args))
  File "d:\anaconda\lib\site-packages\tornado\gen.py", line 209, in wrapper
    yielded = next(result)
  File "d:\anaconda\lib\site-packages\ipykernel\kernelbase.py", line 272, in dispatch_shell
    yield gen.maybe_future(handler(stream, idents, msg))
  File "d:\anaconda\lib\site-packages\tornado\gen.py", line 209, in wrapper
    yielded = next(result)
  File "d:\anaconda\lib\site-packages\ipykernel\kernelbase.py", line 542, in execute_request
    user_expressions, allow_stdin,
  File "d:\anaconda\lib\site-packages\tornado\gen.py", line 209, in wrapper
    yielded = next(result)
  File "d:\anaconda\lib\site-packages\ipykernel\ipkernel.py", line 294, in do_execute
    res = shell.run_cell(code, store_history=store_history, silent=silent)
  File "d:\anaconda\lib\site-packages\ipykernel\zmqshell.py", line 536, in run_cell
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
  File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 2855, in run_cell
    raw_cell, store_history, silent, shell_futures)
  File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 2881, in _run_cell
    return runner(coro)
  File "d:\anaconda\lib\site-packages\IPython\core\async_helpers.py", line 68, in _pseudo_sync_runner
    coro.send(None)
  File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 3058, in run_cell_async
    interactivity=interactivity, compiler=compiler, result=result)
  File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 3249, in run_ast_nodes
    if (await self.run_code(code, result,  async_=asy)):
  File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 3326, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-2-86acfd68390f>", line 2, in <module>
    ner_model_my = build_model('d:/anaconda/Lib/site-packages/deeppavlov/configs/ner/my/ner_rus_bert.json', download=False)
  File "d:\anaconda\lib\site-packages\deeppavlov\core\commands\infer.py", line 61, in build_model
    component = from_params(component_config, mode=mode, serialized=component_serialized)
  File "d:\anaconda\lib\site-packages\deeppavlov\core\common\params.py", line 106, in from_params
    component = obj(**dict(config_params, **kwargs))
  File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 76, in __call__
    obj.__init__(*args, **kwargs)
  File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 28, in _wrapped
    return func(*args, **kwargs)
  File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 529, in __init__
    **kwargs)
  File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 259, in __init__
    self.load()
  File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 28, in _wrapped
    return func(*args, **kwargs)
  File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 457, in load
    return super().load(exclude_scopes=exclude_scopes, **kwargs)
  File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py", line 251, in load
    return super().load(exclude_scopes=exclude_scopes, **kwargs)
  File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py", line 54, in load
    saver = tf.train.Saver(var_list)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 828, in __init__
    self.build()
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 840, in build
    self._build(self._filename, build_save=True, build_restore=True)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 878, in _build
    build_restore=build_restore)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 508, in _build_internal
    restore_sequentially, reshape)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 328, in _AddRestoreOps
    restore_sequentially)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 575, in bulk_restore
    return io_ops.restore_v2(filename_tensor, names, slices, dtypes)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\ops\gen_io_ops.py", line 1695, in restore_v2
    name=name)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\framework\op_def_library.py", line 794, in _apply_op_helper
    op_def=op_def)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\util\deprecation.py", line 507, in new_func
    return func(*args, **kwargs)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\framework\ops.py", line 3357, in create_op
    attrs, op_def, compute_device)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\framework\ops.py", line 3426, in _create_op_internal
    op_def=op_def)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\framework\ops.py", line 1748, in __init__
    self._traceback = tf_stack.extract_stack()

Traceback (most recent call last):

  File "<ipython-input-2-86acfd68390f>", line 2, in <module>
    ner_model_my = build_model('d:/anaconda/Lib/site-packages/deeppavlov/configs/ner/my/ner_rus_bert.json', download=False)

  File "d:\anaconda\lib\site-packages\deeppavlov\core\commands\infer.py", line 61, in build_model
    component = from_params(component_config, mode=mode, serialized=component_serialized)

  File "d:\anaconda\lib\site-packages\deeppavlov\core\common\params.py", line 106, in from_params
    component = obj(**dict(config_params, **kwargs))

  File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 76, in __call__
    obj.__init__(*args, **kwargs)

  File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 28, in _wrapped
    return func(*args, **kwargs)

  File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 529, in __init__
    **kwargs)

  File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 259, in __init__
    self.load()

  File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 28, in _wrapped
    return func(*args, **kwargs)

  File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 457, in load
    return super().load(exclude_scopes=exclude_scopes, **kwargs)

  File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py", line 251, in load
    return super().load(exclude_scopes=exclude_scopes, **kwargs)

  File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py", line 55, in load
    saver.restore(self.sess, path)

  File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 1290, in restore
    {self.saver_def.filename_tensor_name: save_path})

  File "d:\anaconda\lib\site-packages\tensorflow_core\python\client\session.py", line 956, in run
    run_metadata_ptr)

  File "d:\anaconda\lib\site-packages\tensorflow_core\python\client\session.py", line 1180, in _run
    feed_dict_tensor, options, run_metadata)

  File "d:\anaconda\lib\site-packages\tensorflow_core\python\client\session.py", line 1359, in _do_run
    run_metadata)

  File "d:\anaconda\lib\site-packages\tensorflow_core\python\client\session.py", line 1384, in _do_call
    raise type(e)(node_def, op, message)

DataLossError: Checksum does not match: stored 1484353159 vs. calculated on the restored bytes 3522348434
	 [[node save/RestoreV2 (defined at d:\anaconda\lib\site-packages\tensorflow_core\python\framework\ops.py:1748) ]]

Original stack trace for 'save/RestoreV2':
  File "d:\anaconda\lib\runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "d:\anaconda\lib\runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "d:\anaconda\lib\site-packages\spyder_kernels\console\__main__.py", line 11, in <module>
    start.main()
  File "d:\anaconda\lib\site-packages\spyder_kernels\console\start.py", line 318, in main
    kernel.start()
  File "d:\anaconda\lib\site-packages\ipykernel\kernelapp.py", line 563, in start
    self.io_loop.start()
  File "d:\anaconda\lib\site-packages\tornado\platform\asyncio.py", line 148, in start
    self.asyncio_loop.run_forever()
  File "d:\anaconda\lib\asyncio\base_events.py", line 534, in run_forever
    self._run_once()
  File "d:\anaconda\lib\asyncio\base_events.py", line 1771, in _run_once
    handle._run()
  File "d:\anaconda\lib\asyncio\events.py", line 88, in _run
    self._context.run(self._callback, *self._args)
  File "d:\anaconda\lib\site-packages\tornado\ioloop.py", line 690, in <lambda>
    lambda f: self._run_callback(functools.partial(callback, future))
  File "d:\anaconda\lib\site-packages\tornado\ioloop.py", line 743, in _run_callback
    ret = callback()
  File "d:\anaconda\lib\site-packages\tornado\gen.py", line 787, in inner
    self.run()
  File "d:\anaconda\lib\site-packages\tornado\gen.py", line 748, in run
    yielded = self.gen.send(value)
  File "d:\anaconda\lib\site-packages\ipykernel\kernelbase.py", line 365, in process_one
    yield gen.maybe_future(dispatch(*args))
  File "d:\anaconda\lib\site-packages\tornado\gen.py", line 209, in wrapper
    yielded = next(result)
  File "d:\anaconda\lib\site-packages\ipykernel\kernelbase.py", line 272, in dispatch_shell
    yield gen.maybe_future(handler(stream, idents, msg))
  File "d:\anaconda\lib\site-packages\tornado\gen.py", line 209, in wrapper
    yielded = next(result)
  File "d:\anaconda\lib\site-packages\ipykernel\kernelbase.py", line 542, in execute_request
    user_expressions, allow_stdin,
  File "d:\anaconda\lib\site-packages\tornado\gen.py", line 209, in wrapper
    yielded = next(result)
  File "d:\anaconda\lib\site-packages\ipykernel\ipkernel.py", line 294, in do_execute
    res = shell.run_cell(code, store_history=store_history, silent=silent)
  File "d:\anaconda\lib\site-packages\ipykernel\zmqshell.py", line 536, in run_cell
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
  File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 2855, in run_cell
    raw_cell, store_history, silent, shell_futures)
  File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 2881, in _run_cell
    return runner(coro)
  File "d:\anaconda\lib\site-packages\IPython\core\async_helpers.py", line 68, in _pseudo_sync_runner
    coro.send(None)
  File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 3058, in run_cell_async
    interactivity=interactivity, compiler=compiler, result=result)
  File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 3249, in run_ast_nodes
    if (await self.run_code(code, result,  async_=asy)):
  File "d:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 3326, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-2-86acfd68390f>", line 2, in <module>
    ner_model_my = build_model('d:/anaconda/Lib/site-packages/deeppavlov/configs/ner/my/ner_rus_bert.json', download=False)
  File "d:\anaconda\lib\site-packages\deeppavlov\core\commands\infer.py", line 61, in build_model
    component = from_params(component_config, mode=mode, serialized=component_serialized)
  File "d:\anaconda\lib\site-packages\deeppavlov\core\common\params.py", line 106, in from_params
    component = obj(**dict(config_params, **kwargs))
  File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 76, in __call__
    obj.__init__(*args, **kwargs)
  File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 28, in _wrapped
    return func(*args, **kwargs)
  File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 529, in __init__
    **kwargs)
  File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 259, in __init__
    self.load()
  File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_backend.py", line 28, in _wrapped
    return func(*args, **kwargs)
  File "d:\anaconda\lib\site-packages\deeppavlov\models\bert\bert_sequence_tagger.py", line 457, in load
    return super().load(exclude_scopes=exclude_scopes, **kwargs)
  File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py", line 251, in load
    return super().load(exclude_scopes=exclude_scopes, **kwargs)
  File "d:\anaconda\lib\site-packages\deeppavlov\core\models\tf_model.py", line 54, in load
    saver = tf.train.Saver(var_list)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 828, in __init__
    self.build()
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 840, in build
    self._build(self._filename, build_save=True, build_restore=True)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 878, in _build
    build_restore=build_restore)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 508, in _build_internal
    restore_sequentially, reshape)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 328, in _AddRestoreOps
    restore_sequentially)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\training\saver.py", line 575, in bulk_restore
    return io_ops.restore_v2(filename_tensor, names, slices, dtypes)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\ops\gen_io_ops.py", line 1695, in restore_v2
    name=name)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\framework\op_def_library.py", line 794, in _apply_op_helper
    op_def=op_def)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\util\deprecation.py", line 507, in new_func
    return func(*args, **kwargs)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\framework\ops.py", line 3357, in create_op
    attrs, op_def, compute_device)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\framework\ops.py", line 3426, in _create_op_internal
    op_def=op_def)
  File "d:\anaconda\lib\site-packages\tensorflow_core\python\framework\ops.py", line 1748, in __init__
    self._traceback = tf_stack.extract_stack()