Error on train using DIET classifier autograph

[LoveMeWithoutAll]

Rasa version:
2.2.9

Python version: 3.8

Tensorflow version: 2.3.1

Operating system (windows, osx, ...): MacOS

Issue: error on train

    NotImplementedError: Cannot convert a symbolic Tensor (strided_slice_6:0) to a numpy array. This error may indicate that you're trying to pass a Tensor to a NumPy call, which is not supported

Error (including full traceback):

Traceback (most recent call last):
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/rasa/__main__.py", line 116, in main
    cmdline_arguments.func(cmdline_arguments)
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/rasa/cli/train.py", line 58, in <lambda>
    train_parser.set_defaults(func=lambda args: train(args, can_exit=True))
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/rasa/cli/train.py", line 90, in train
    training_result = rasa.train(
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/rasa/train.py", line 94, in train
    return rasa.utils.common.run_in_loop(
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/rasa/utils/common.py", line 308, in run_in_loop
    result = loop.run_until_complete(f)
  File "uvloop/loop.pyx", line 1456, in uvloop.loop.Loop.run_until_complete
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/rasa/train.py", line 163, in train_async
    return await _train_async_internal(
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/rasa/train.py", line 342, in _train_async_internal
    await _do_training(
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/rasa/train.py", line 388, in _do_training
    model_path = await _train_nlu_with_validated_data(
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/rasa/train.py", line 811, in _train_nlu_with_validated_data
    await rasa.nlu.train(
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/rasa/nlu/train.py", line 116, in train
    interpreter = trainer.train(training_data, **kwargs)
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/rasa/nlu/model.py", line 209, in train
    updates = component.train(working_data, self.config, **context)
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/rasa/nlu/classifiers/diet_classifier.py", line 816, in train
    self.model.fit(
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/rasa/utils/tensorflow/models.py", line 220, in fit
    ) = self._get_tf_train_functions(eager, model_data, batch_strategy)
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/rasa/utils/tensorflow/models.py", line 481, in _get_tf_train_functions
    self._get_tf_call_model_function(
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/rasa/utils/tensorflow/models.py", line 464, in _get_tf_call_model_function
    tf_call_model_function(next(iter(init_dataset)))
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 780, in __call__
    result = self._call(*args, **kwds)
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 823, in _call
    self._initialize(args, kwds, add_initializers_to=initializers)
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 696, in _initialize
    self._stateful_fn._get_concrete_function_internal_garbage_collected(  # pylint: disable=protected-access
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 2855, in _get_concrete_function_internal_garbage_collected
    graph_function, _, _ = self._maybe_define_function(args, kwargs)
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 3213, in _maybe_define_function
    graph_function = self._create_graph_function(args, kwargs)
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 3065, in _create_graph_function
    func_graph_module.func_graph_from_py_func(
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py", line 986, in func_graph_from_py_func
    func_outputs = python_func(*func_args, **func_kwargs)
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 600, in wrapped_fn
    return weak_wrapped_fn().__wrapped__(*args, **kwds)
  File "/Users/ys/dev/rasa/venv/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py", line 973, in wrapper
    raise e.ag_error_metadata.to_exception(e)
NotImplementedError: in user code:
    /Users/ys/dev/rasa/venv/lib/python3.8/site-packages/rasa/utils/tensorflow/models.py:293 train_on_batch  *
        prediction_loss = self.batch_loss(batch_in)
    /Users/ys/dev/rasa/venv/lib/python3.8/site-packages/rasa/nlu/classifiers/diet_classifier.py:1417 batch_loss  *
        sequence_lengths = self._get_sequence_lengths(
    /Users/ys/dev/rasa/venv/lib/python3.8/site-packages/rasa/utils/tensorflow/models.py:1112 _get_sequence_lengths  *
        sequence_lengths = tf.ones([batch_dim], dtype=tf.int32)
    /Users/ys/dev/rasa/venv/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:201 wrapper  **
        return target(*args, **kwargs)
    /Users/ys/dev/rasa/venv/lib/python3.8/site-packages/tensorflow/python/ops/array_ops.py:3041 ones
        output = _constant_if_small(one, shape, dtype, name)
    /Users/ys/dev/rasa/venv/lib/python3.8/site-packages/tensorflow/python/ops/array_ops.py:2732 _constant_if_small
        if np.prod(shape) < 1000:
    <__array_function__ internals>:5 prod
        
    /Users/ys/dev/rasa/venv/lib/python3.8/site-packages/numpy/core/fromnumeric.py:3030 prod
        return _wrapreduction(a, np.multiply, 'prod', axis, dtype, out,
    /Users/ys/dev/rasa/venv/lib/python3.8/site-packages/numpy/core/fromnumeric.py:87 _wrapreduction
        return ufunc.reduce(obj, axis, dtype, out, **passkwargs)
    /Users/ys/dev/rasa/venv/lib/python3.8/site-packages/tensorflow/python/framework/ops.py:845 __array__
        raise NotImplementedError(
    NotImplementedError: Cannot convert a symbolic Tensor (strided_slice_6:0) to a numpy array. This error may indicate that you're trying to pass a Tensor to a NumPy call, which is not supported

Command or request that led to error:

rasa train

Content of configuration file (config.yml) (if relevant):

language: ko
pipeline:
- name: WhitespaceTokenizer
- name: RegexFeaturizer
- name: LexicalSyntacticFeaturizer
- name: CountVectorsFeaturizer
- name: CountVectorsFeaturizer
  analyzer: char_wb
  min_ngram: 1
  max_ngram: 4
- name: DIETClassifier
  epochs: 100
- name: EntitySynonymMapper
- name: ResponseSelector
  epochs: 100
policies:
- name: MemoizationPolicy
- name: TEDPolicy
  max_history: 5
  epochs: 100
- name: RulePolicy

[sara-tagger]

Thanks for raising this issue, @wochinge will get back to you about it soon✨

Please also check out the docs and the forum in case your issue was raised there too 🤗

[nsorros]

I ran into the same problem just now and it was resolved by uninstalling numpy 1.20.0 and installing numpy 1.18.0

[wochinge]

duplicate of #7885

This is an error with older pip versions which isn't able to resolve dependencies properly.