@nik202 I also have this error. It appears that it happens where use_masked_language_model=True. I get the error at the first evaluation before anything is written to tensorboard. If I remove the masked_language_model then itworks.
Rasa Version : 2.8.11
Minimum Compatible Version: 2.8.9
Rasa SDK Version : 2.8.3
Rasa X Version : 0.42.5
Python Version : 3.8.8
Operating System : Linux-5.10.60.1-microsoft-standard-WSL2-x86_64-with-glibc2.10
Python Path : /home/simon/anaconda3/bin/python
language: en
pipeline:
- name: enzopreprocessor.EnzoPreprocessor
# language model
- name: WhitespaceTokenizer
- name: LanguageModelFeaturizer
model_weights: distilbert-base-uncased
model_name: distilbert
# Regex for phone numbers
- name: RegexFeaturizer
# dual intentity and entity
- name: DIETClassifier
random_seed: 42
batch_size: 16
intent_classification: True
entity_recognition: True
use_masked_language_model: True
constrain_similarities: True
epochs: 200
evaluate_on_number_of_examples: 200
evaluate_every_number_of_epochs: 1
tensorboard_log_directory: "./tbdiet"
tensorboard_log_level: "batch"
############ ERROR MESSAGE
Traceback (most recent call last):
File “/home/simon/anaconda3/bin/rasa”, line 8, in
sys.exit(main())
File “/home/simon/anaconda3/lib/python3.8/site-packages/rasa/main.py”, line 118, in main
cmdline_arguments.func(cmdline_arguments)
File “/home/simon/anaconda3/lib/python3.8/site-packages/rasa/cli/train.py”, line 59, in
train_parser.set_defaults(func=lambda args: run_training(args, can_exit=True))
File “/home/simon/anaconda3/lib/python3.8/site-packages/rasa/cli/train.py”, line 91, in run_training
training_result = train_all(
File “/home/simon/anaconda3/lib/python3.8/site-packages/rasa/api.py”, line 109, in train
return rasa.utils.common.run_in_loop(
File “/home/simon/anaconda3/lib/python3.8/site-packages/rasa/utils/common.py”, line 296, in run_in_loop
result = loop.run_until_complete(f)
File “uvloop/loop.pyx”, line 1456, in uvloop.loop.Loop.run_until_complete
File “/home/simon/anaconda3/lib/python3.8/site-packages/rasa/model_training.py”, line 108, in train_async
return await _train_async_internal(
File “/home/simon/anaconda3/lib/python3.8/site-packages/rasa/model_training.py”, line 288, in _train_async_internal
await _do_training(
File “/home/simon/anaconda3/lib/python3.8/site-packages/rasa/model_training.py”, line 334, in _do_training
model_path = await _train_nlu_with_validated_data(
File “/home/simon/anaconda3/lib/python3.8/site-packages/rasa/model_training.py”, line 758, in _train_nlu_with_validated_data
await rasa.nlu.train.train(
File “/home/simon/anaconda3/lib/python3.8/site-packages/rasa/nlu/train.py”, line 111, in train
interpreter = trainer.train(training_data, **kwargs)
File “/home/simon/anaconda3/lib/python3.8/site-packages/rasa/nlu/model.py”, line 221, in train
component.train(working_data, self.config, **context)
File “/home/simon/anaconda3/lib/python3.8/site-packages/rasa/nlu/classifiers/diet_classifier.py”, line 880, in train
self.model.fit(
File “/home/simon/anaconda3/lib/python3.8/site-packages/rasa/utils/tensorflow/temp_keras_modules.py”, line 217, in fit
val_logs = self.evaluate(
File “/home/simon/.local/lib/python3.8/site-packages/keras/engine/training.py”, line 1501, in evaluate
tmp_logs = self.test_function(iterator)
File “/home/simon/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py”, line 885, in call
result = self._call(*args, **kwds)
File “/home/simon/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py”, line 933, in _call
self._initialize(args, kwds, add_initializers_to=initializers)
File “/home/simon/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py”, line 759, in _initialize
self._stateful_fn._get_concrete_function_internal_garbage_collected( # pylint: disable=protected-access
File “/home/simon/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/function.py”, line 3066, in _get_concrete_function_internal_garbage_collected
graph_function, _ = self._maybe_define_function(args, kwargs)
File “/home/simon/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/function.py”, line 3463, in _maybe_define_function
graph_function = self._create_graph_function(args, kwargs)
File “/home/simon/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/function.py”, line 3298, in _create_graph_function
func_graph_module.func_graph_from_py_func(
File “/home/simon/anaconda3/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py”, line 1007, in func_graph_from_py_func
func_outputs = python_func(*func_args, **func_kwargs)
File “/home/simon/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py”, line 668, in wrapped_fn
out = weak_wrapped_fn().wrapped(*args, **kwds)
File “/home/simon/anaconda3/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py”, line 994, in wrapper
raise e.ag_error_metadata.to_exception(e)
TypeError: in user code:
/home/simon/.local/lib/python3.8/site-packages/keras/engine/training.py:1330 test_function *
return step_function(self, iterator)
/home/simon/.local/lib/python3.8/site-packages/keras/engine/training.py:1320 step_function **
outputs = model.distribute_strategy.run(run_step, args=(data,))
/home/simon/anaconda3/lib/python3.8/site-packages/tensorflow/python/distribute/distribute_lib.py:1286 run
return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
/home/simon/anaconda3/lib/python3.8/site-packages/tensorflow/python/distribute/distribute_lib.py:2849 call_for_each_replica
return self._call_for_each_replica(fn, args, kwargs)
/home/simon/anaconda3/lib/python3.8/site-packages/tensorflow/python/distribute/distribute_lib.py:3632 _call_for_each_replica
return fn(*args, **kwargs)
/home/simon/.local/lib/python3.8/site-packages/keras/engine/training.py:1313 run_step **
outputs = model.test_step(data)
/home/simon/anaconda3/lib/python3.8/site-packages/rasa/utils/tensorflow/models.py:200 test_step prediction_loss = self.batch_loss(batch_in)
/home/simon/anaconda3/lib/python3.8/site-packages/rasa/nlu/classifiers/diet_classifier.py:1567 batch_loss
loss, acc = self._mask_loss(
/home/simon/anaconda3/lib/python3.8/site-packages/rasa/nlu/classifiers/diet_classifier.py:1477 _mask_loss
tf.reduce_any(mlm_mask_boolean),
/home/simon/anaconda3/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:206 wrapper
return target(*args, **kwargs)
/home/simon/anaconda3/lib/python3.8/site-packages/tensorflow/python/ops/math_ops.py:3267 reduce_any
gen_math_ops._any(
/home/simon/anaconda3/lib/python3.8/site-packages/tensorflow/python/ops/gen_math_ops.py:685 _any
_, _, _op, _outputs = _op_def_library._apply_op_helper(
/home/simon/anaconda3/lib/python3.8/site-packages/tensorflow/python/framework/op_def_library.py:544 _apply_op_helper
raise TypeError("%s expected type of %s." %
TypeError: Input 'input' of 'Any' Op has type float32 that does not match expected type of bool.
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