Hi, I’m using Conda virtual environment and have installed Rasa v2.8.14 and Python 3.8.0.
Encountered the following errors when initiating a new project:
(venv) PS C:\Users\DerickTeo\development> rasa init
Welcome to Rasa! 
To get started quickly, an initial project will be created.
If you need some help, check out the documentation at Introduction to Rasa Open Source.
Now let’s start! 
? Please enter a path where the project will be created [default: current directory]
? Directory ‘C:\Users\DerickTeo\development’ is not empty. Continue? Yes
Created project directory at ‘C:\Users\DerickTeo\development’.
Finished creating project structure.
? Do you want to train an initial model? 
Yes
Training an initial model…
The configuration for policies and pipeline was chosen automatically. It was written into the config file at ‘.\config.yml’.
Training NLU model…
2021-11-19 22:53:08 INFO rasa.shared.nlu.training_data.training_data - Training data stats:
2021-11-19 22:53:08 INFO rasa.shared.nlu.training_data.training_data - Number of intent examples: 69 (7 distinct intents)
2021-11-19 22:53:08 INFO rasa.shared.nlu.training_data.training_data - Found intents: ‘affirm’, ‘bot_challenge’, ‘mood_great’, ‘greet’, ‘deny’, ‘goodbye’, ‘mood_unhappy’ 2021-11-19 22:53:08 INFO rasa.shared.nlu.training_data.training_data - Number of response examples: 0 (0 distinct responses) 2021-11-19 22:53:08 INFO rasa.shared.nlu.training_data.training_data - Number of entity examples: 0 (0 distinct entities) 2021-11-19 22:53:08 INFO rasa.nlu.model - Starting to train component WhitespaceTokenizer 2021-11-19 22:53:08 INFO rasa.nlu.model - Finished training component. 2021-11-19 22:53:08 INFO rasa.nlu.model - Starting to train component RegexFeaturizer 2021-11-19 22:53:08 INFO rasa.nlu.model - Finished training component. 2021-11-19 22:53:08 INFO rasa.nlu.model - Starting to train component LexicalSyntacticFeaturizer 2021-11-19 22:53:08 INFO rasa.nlu.model - Finished training component. 2021-11-19 22:53:08 INFO rasa.nlu.model - Starting to train component CountVectorsFeaturizer 2021-11-19 22:53:08 INFO rasa.nlu.featurizers.sparse_featurizer.count_vectors_featurizer - 80 vocabulary items were created for text attribute. 2021-11-19 22:53:08 INFO rasa.nlu.model - Finished training component. 2021-11-19 22:53:08 INFO rasa.nlu.model - Starting to train component CountVectorsFeaturizer 2021-11-19 22:53:08 INFO rasa.nlu.featurizers.sparse_featurizer.count_vectors_featurizer - 697 vocabulary items were created for text attribute. 2021-11-19 22:53:08 INFO rasa.nlu.model - Finished training component. 2021-11-19 22:53:08 INFO rasa.nlu.model - Starting to train component DIETClassifier C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\rasa\utils\tensorflow\model_data.py:750: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify ‘dtype=object’ when creating the ndarray np.concatenate(np.array(f)), Epochs: 100%|██████████████████████████████████████████████| 100/100 [00:29<00:00, 3.38it/s, t_loss=1.21, i_acc=0.986] 2021-11-19 22:53:38 INFO rasa.nlu.model - Finished training component. 2021-11-19 22:53:38 INFO rasa.nlu.model - Starting to train component EntitySynonymMapper 2021-11-19 22:53:38 INFO rasa.nlu.model - Finished training component. 2021-11-19 22:53:38 INFO rasa.nlu.model - Starting to train component ResponseSelector 2021-11-19 22:53:38 INFO rasa.nlu.selectors.response_selector - Retrieval intent parameter was left to its default value. This response selector will be trained on training examples combining all retrieval intents. 2021-11-19 22:53:38 INFO rasa.nlu.model - Finished training component. 2021-11-19 22:53:38 INFO rasa.nlu.model - Starting to train component FallbackClassifier 2021-11-19 22:53:38 INFO rasa.nlu.model - Finished training component. Traceback (most recent call last): File “C:\Users\DerickTeo.conda\envs\venv\lib\runpy.py”, line 194, in _run_module_as_main return run_code(code, main_globals, None, File “C:\Users\DerickTeo.conda\envs\venv\lib\runpy.py”, line 87, in run_code exec(code, run_globals) File "C:\Users\DerickTeo.conda\envs\venv\Scripts\rasa.exe_main.py", line 7, in File "C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\rasa_main.py", line 118, in main cmdline_arguments.func(cmdline_arguments) File “C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\rasa\cli\scaffold.py”, line 235, in run init_project(args, path) File “C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\rasa\cli\scaffold.py”, line 130, in init_project print_train_or_instructions(args, path) File “C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\rasa\cli\scaffold.py”, line 69, in print_train_or_instructions training_result = rasa.train(domain, config, training_files, output) File “C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\rasa\api.py”, line 109, in train return rasa.utils.common.run_in_loop( File “C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\rasa\utils\common.py”, line 296, in run_in_loop result = loop.run_until_complete(f) File “C:\Users\DerickTeo.conda\envs\venv\lib\asyncio\base_events.py”, line 616, in run_until_complete return future.result() File “C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\rasa\model_training.py”, line 108, in train_async return await _train_async_internal( File “C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\rasa\model_training.py”, line 288, in _train_async_internal await _do_training( File “C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\rasa\model_training.py”, line 334, in _do_training model_path = await _train_nlu_with_validated_data( File “C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\rasa\model_training.py”, line 758, in _train_nlu_with_validated_data await rasa.nlu.train.train( File “C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\rasa\nlu\train.py”, line 114, in train persisted_path = trainer.persist( File “C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\rasa\nlu\model.py”, line 259, in persist update = component.persist(file_name, dir_name) File “C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\rasa\nlu\classifiers\diet_classifier.py”, line 1021, in persist self.model.save(str(tf_model_file)) File “C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\rasa\utils\tensorflow\models.py”, line 392, in save self.save_weights(model_file_name, overwrite=overwrite, save_format=“tf”) File “C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\keras\engine\training.py”, line 2258, in save_weights self._trackable_saver.save(filepath, session=session, options=options) File “C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\tensorflow\python\training\tracking\util.py”, line 1262, in save save_path, new_feed_additions = self._save_cached_when_graph_building( File “C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\tensorflow\python\training\tracking\util.py”, line 1208, in _save_cached_when_graph_building save_op = saver.save(file_prefix, options=options) File “C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\tensorflow\python\training\saving\functional_saver.py”, line 300, in save return save_fn() File “C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\tensorflow\python\training\saving\functional_saver.py”, line 274, in save_fn sharded_saves.append(saver.save(shard_prefix, options)) File “C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\tensorflow\python\training\saving\functional_saver.py”, line 83, in save return io_ops.save_v2(file_prefix, tensor_names, tensor_slices, tensors) File “C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\tensorflow\python\ops\gen_io_ops.py”, line 1695, in save_v2 return save_v2_eager_fallback( File “C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\tensorflow\python\ops\gen_io_ops.py”, line 1716, in save_v2_eager_fallback _result = _execute.execute(b"SaveV2", 0, inputs=_inputs_flat, attrs=_attrs, File “C:\Users\DerickTeo.conda\envs\venv\lib\site-packages\tensorflow\python\eager\execute.py”, line 59, in quick_execute tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name, tensorflow.python.framework.errors_impl.ResourceExhaustedError: Failed to rename: C:\Users\DERICK~1\AppData\Local\Temp\tmp1o2wd7ci\nlu\component_5_DIETClassifier.tf_model_temp/part-00000-of-00001.data-00000-of-00001.tempstate11337403341004488306 to: C:\Users\DERICK~1\AppData\Local\Temp\tmp1o2wd7ci\nlu\component_5_DIETClassifier.tf_model_temp/part-00000-of-00001.data-00000-of-00001 : A device attached to the system is not functioning. ; Too many links [Op:SaveV2]
