I am getting difficultly in implementing sanic worker concept for rasa server as well as action server. Actually for ‘rasa run’ command to run rasa server does not have config to increase the sanic workers within the commands, so I tried directly changing in rasa base code i.e for rasa server I changed in rasa/constant.py file and for action server I changed in rasa_sdk/constant.py file and then tried to run rasa server. Here is the error that I got
/usr/lib/python3.10/random.py:370: DeprecationWarning: non-integer
arguments to randrange() have been deprecated since Python 3.10 and will
be removed in a subsequent version
return self.randrange(a, b+1)
/usr/lib/python3.10/random.py:370: DeprecationWarning: non-integer
arguments to randrange() have been deprecated since Python 3.10 and will
be removed in a subsequent version
return self.randrange(a, b+1)
2023-11-09 07:08:33.790088: E
tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:219] failed to
create cublas handle: the library was not initialized
2023-11-09 07:08:33.790138: E
tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:222] Failure
to initialize cublas may be due to OOM (cublas needs some free memory
when you initialize it, and your deep-learning framework may have
preallocated more than its fair share), or may be because this binary
was not built with support for the GPU in your machine.
2023-11-09 07:08:33.797893: E
tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:219] failed to
create cublas handle: the library was not initialized
2023-11-09 07:08:33.797924: E
tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:222] Failure
to initialize cublas may be due to OOM (cublas needs some free memory
when you initialize it, and your deep-learning framework may have
preallocated more than its fair share), or may be because this binary
was not built with support for the GPU in your machine.
2023-11-09 07:08:33.809678: E
tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:219] failed to
create cublas handle: the library was not initialized
2023-11-09 07:08:33.809714: E
tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:222] Failure
to initialize cublas may be due to OOM (cublas needs some free memory
when you initialize it, and your deep-learning framework may have
preallocated more than its fair share), or may be because this binary
was not built with support for the GPU in your machine.
2023-11-09 07:08:33.811228: E
tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:219] failed to
create cublas handle: the library was not initialized
2023-11-09 07:08:33.811262: E
tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:222] Failure
to initialize cublas may be due to OOM (cublas needs some free memory
when you initialize it, and your deep-learning framework may have
preallocated more than its fair share), or may be because this binary
was not built with support for the GPU in your machine.
2023-11-09 07:08:33.819931: E
tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:219] failed to
create cublas handle: the library was not initialized
2023-11-09 07:08:33.819967: E
tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:222] Failure
to initialize cublas may be due to OOM (cublas needs some free memory
when you initialize it, and your deep-learning framework may have
preallocated more than its fair share), or may be because this binary
was not built with support for the GPU in your machine.
2023-11-09 07:08:34 ERROR rasa.core.agent - Could not load model due
to Error initializing graph component for node run_DIETClassifier5..
Traceback (most recent call last):
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/graph.py",
line 403, in _load_component
self._component: GraphComponent = constructor( # type:
ignore[no-redef]
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1120, in load
return cls._load(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1151, in _load
model = cls._load_model(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1244, in _load_model
model = cls._load_model_class(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1275, in _load_model_class
return cls.model_class().load(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/utils/tensorflow/models.py",
line 445, in load
model.fit(data_generator, verbose=False)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 70, in error_handler
raise e.with_traceback(filtered_tb) from None
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/tensorflow/python/eager/execute.py",
line 52, in quick_execute
tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
tensorflow.python.framework.errors_impl.InternalError: Graph execution
error:
Detected at node 'embed_label/embed_layer_label/MatMul' defined at (most
recent call last):
File "/home/intern/chatbot/venv/bin/rasa", line 8, in <module>
sys.exit(main())
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/__main__.py",
line 133, in main
cmdline_arguments.func(cmdline_arguments)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/cli/run.py",
line 93, in run
rasa.run(**vars(args))
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/api.py",
line 56, in run
rasa.core.run.serve_application(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/run.py",
line 231, in serve_application
app.run(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/app.py",
line 1206, in run
serve_multiple(server_settings, workers)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/server/runners.py",
line 264, in serve_multiple
process.start()
File "/usr/lib/python3.10/multiprocessing/process.py", line 121, in
start
self._popen = self._Popen(self)
File "/usr/lib/python3.10/multiprocessing/context.py", line 281, in
_Popen
return Popen(process_obj)
File "/usr/lib/python3.10/multiprocessing/popen_fork.py", line 19,
in __init__
self._launch(process_obj)
File "/usr/lib/python3.10/multiprocessing/popen_fork.py", line 71,
in _launch
code = process_obj._bootstrap(parent_sentinel=child_r)
File "/usr/lib/python3.10/multiprocessing/process.py", line 314, in
_bootstrap
self.run()
File "/usr/lib/python3.10/multiprocessing/process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/server/runners.py",
line 130, in serve
loop.run_until_complete(app._server_event("init", "before"))
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/app.py",
line 2000, in _server_event
await self.dispatch(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/signals.py",
line 191, in dispatch
return await dispatch
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/signals.py",
line 161, in _dispatch
retval = await maybe_coroutine
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/app.py",
line 1524, in _listener
await maybe_coro
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/run.py",
line 253, in load_agent_on_start
app.ctx.agent = await agent.load_agent(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/agent.py",
line 254, in load_agent
agent.load_model(model_path)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/agent.py",
line 352, in load_model
self.processor = MessageProcessor(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/processor.py",
line 101, in __init__
self.model_filename, self.model_metadata, self.graph_runner =
self._load_model(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/processor.py",
line 138, in _load_model
metadata, runner = loader.load_predict_graph_runner(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/loader.py",
line 29, in load_predict_graph_runner
runner = graph_runner_class.create(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 51, in create
return cls(graph_schema, model_storage, execution_context, hooks)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 37, in __init__
self._instantiated_nodes: Dict[Text, GraphNode] =
self._instantiate_nodes(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 60, in _instantiate_nodes
return {
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 61, in <dictcomp>
node_name: GraphNode.from_schema_node(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/graph.py",
line 566, in from_schema_node
return cls(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/graph.py",
line 392, in __init__
self._load_component()
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/graph.py",
line 403, in _load_component
self._component: GraphComponent = constructor( # type:
ignore[no-redef]
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1120, in load
return cls._load(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1151, in _load
model = cls._load_model(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1244, in _load_model
model = cls._load_model_class(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1275, in _load_model_class
return cls.model_class().load(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/utils/tensorflow/models.py",
line 445, in load
model.fit(data_generator, verbose=False)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 65, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/training.py",
line 1685, in fit
tmp_logs = self.train_function(iterator)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/training.py",
line 1284, in train_function
return step_function(self, iterator)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/training.py",
line 1268, in step_function
outputs = model.distribute_strategy.run(run_step, args=(data,))
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/training.py",
line 1249, in run_step
outputs = model.train_step(data)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/utils/tensorflow/models.py",
line 161, in train_step
prediction_loss = self.batch_loss(batch_in)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1644, in batch_loss
loss = self._batch_loss_intent(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1683, in _batch_loss_intent
loss, acc = self._calculate_label_loss(sentence_vector, label,
label_ids)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1581, in _calculate_label_loss
all_label_ids, all_labels_embed = self._create_all_labels()
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1532, in _create_all_labels
all_labels_embed = self._tf_layers[f"embed.{LABEL}"](x)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 65, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/base_layer.py",
line 1145, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 96, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/utils/tensorflow/layers.py",
line 463, in call
x = self._dense(x)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 65, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/base_layer.py",
line 1145, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 96, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/layers/core/dense.py",
line 241, in call
outputs = tf.matmul(a=inputs, b=self.kernel)
Node: 'embed_label/embed_layer_label/MatMul'
Detected at node 'embed_label/embed_layer_label/MatMul' defined at (most
recent call last):
File "/home/intern/chatbot/venv/bin/rasa", line 8, in <module>
sys.exit(main())
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/__main__.py",
line 133, in main
cmdline_arguments.func(cmdline_arguments)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/cli/run.py",
line 93, in run
rasa.run(**vars(args))
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/api.py",
line 56, in run
rasa.core.run.serve_application(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/run.py",
line 231, in serve_application
app.run(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/app.py",
line 1206, in run
serve_multiple(server_settings, workers)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/server/runners.py",
line 264, in serve_multiple
process.start()
File "/usr/lib/python3.10/multiprocessing/process.py", line 121, in
start
self._popen = self._Popen(self)
File "/usr/lib/python3.10/multiprocessing/context.py", line 281, in
_Popen
return Popen(process_obj)
File "/usr/lib/python3.10/multiprocessing/popen_fork.py", line 19,
in __init__
self._launch(process_obj)
File "/usr/lib/python3.10/multiprocessing/popen_fork.py", line 71,
in _launch
code = process_obj._bootstrap(parent_sentinel=child_r)
File "/usr/lib/python3.10/multiprocessing/process.py", line 314, in
_bootstrap
self.run()
File "/usr/lib/python3.10/multiprocessing/process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/server/runners.py",
line 130, in serve
loop.run_until_complete(app._server_event("init", "before"))
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/app.py",
line 2000, in _server_event
await self.dispatch(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/signals.py",
line 191, in dispatch
return await dispatch
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/signals.py",
line 161, in _dispatch
retval = await maybe_coroutine
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/app.py",
line 1524, in _listener
await maybe_coro
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/run.py",
line 253, in load_agent_on_start
app.ctx.agent = await agent.load_agent(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/agent.py",
line 254, in load_agent
agent.load_model(model_path)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/agent.py",
line 352, in load_model
self.processor = MessageProcessor(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/processor.py",
line 101, in __init__
self.model_filename, self.model_metadata, self.graph_runner =
self._load_model(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/processor.py",
line 138, in _load_model
metadata, runner = loader.load_predict_graph_runner(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/loader.py",
line 29, in load_predict_graph_runner
runner = graph_runner_class.create(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 51, in create
return cls(graph_schema, model_storage, execution_context, hooks)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 37, in __init__
self._instantiated_nodes: Dict[Text, GraphNode] =
self._instantiate_nodes(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 60, in _instantiate_nodes
return {
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 61, in <dictcomp>
node_name: GraphNode.from_schema_node(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/graph.py",
line 566, in from_schema_node
return cls(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/graph.py",
line 392, in __init__
self._load_component()
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/graph.py",
line 403, in _load_component
self._component: GraphComponent = constructor( # type:
ignore[no-redef]
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1120, in load
return cls._load(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1151, in _load
model = cls._load_model(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1244, in _load_model
model = cls._load_model_class(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1275, in _load_model_class
return cls.model_class().load(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/utils/tensorflow/models.py",
line 445, in load
model.fit(data_generator, verbose=False)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 65, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/training.py",
line 1685, in fit
tmp_logs = self.train_function(iterator)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/training.py",
line 1284, in train_function
return step_function(self, iterator)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/training.py",
line 1268, in step_function
outputs = model.distribute_strategy.run(run_step, args=(data,))
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/training.py",
line 1249, in run_step
outputs = model.train_step(data)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/utils/tensorflow/models.py",
line 161, in train_step
prediction_loss = self.batch_loss(batch_in)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1644, in batch_loss
loss = self._batch_loss_intent(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1683, in _batch_loss_intent
loss, acc = self._calculate_label_loss(sentence_vector, label,
label_ids)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1581, in _calculate_label_loss
all_label_ids, all_labels_embed = self._create_all_labels()
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1532, in _create_all_labels
all_labels_embed = self._tf_layers[f"embed.{LABEL}"](x)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 65, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/base_layer.py",
line 1145, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 96, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/utils/tensorflow/layers.py",
line 463, in call
x = self._dense(x)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 65, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/base_layer.py",
line 1145, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 96, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/layers/core/dense.py",
line 241, in call
outputs = tf.matmul(a=inputs, b=self.kernel)
Node: 'embed_label/embed_layer_label/MatMul'
2 root error(s) found.
(0) INTERNAL: Attempting to perform BLAS operation using
StreamExecutor without BLAS support
[[{{node embed_label/embed_layer_label/MatMul}}]]
[[crf/cond/StatefulPartitionedCall/crf/cond/else/_236/crf/cond/Maximum/_312]]
(1) INTERNAL: Attempting to perform BLAS operation using
StreamExecutor without BLAS support
[[{{node embed_label/embed_layer_label/MatMul}}]]
0 successful operations.
0 derived errors ignored. [Op:__inference_train_function_50041]
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/agent.py",
line 254, in load_agent
agent.load_model(model_path)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/agent.py",
line 352, in load_model
self.processor = MessageProcessor(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/processor.py",
line 101, in __init__
self.model_filename, self.model_metadata, self.graph_runner =
self._load_model(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/processor.py",
line 138, in _load_model
metadata, runner = loader.load_predict_graph_runner(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/loader.py",
line 29, in load_predict_graph_runner
runner = graph_runner_class.create(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 51, in create
return cls(graph_schema, model_storage, execution_context, hooks)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 37, in __init__
self._instantiated_nodes: Dict[Text, GraphNode] =
self._instantiate_nodes(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 60, in _instantiate_nodes
return {
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 61, in <dictcomp>
node_name: GraphNode.from_schema_node(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/graph.py",
line 566, in from_schema_node
return cls(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/graph.py",
line 392, in __init__
self._load_component()
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/graph.py",
line 416, in _load_component
raise GraphComponentException(
rasa.engine.exceptions.GraphComponentException: Error initializing graph
component for node run_DIETClassifier5.
2023-11-09 07:08:34 ERROR rasa.core.agent - Could not load model due
to Error initializing graph component for node run_DIETClassifier5..
Traceback (most recent call last):
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/graph.py",
line 403, in _load_component
self._component: GraphComponent = constructor( # type:
ignore[no-redef]
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1120, in load
return cls._load(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1151, in _load
model = cls._load_model(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1244, in _load_model
model = cls._load_model_class(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1275, in _load_model_class
return cls.model_class().load(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/utils/tensorflow/models.py",
line 445, in load
model.fit(data_generator, verbose=False)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 70, in error_handler
raise e.with_traceback(filtered_tb) from None
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/tensorflow/python/eager/execute.py",
line 52, in quick_execute
tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
tensorflow.python.framework.errors_impl.InternalError: Graph execution
error:
Detected at node
'rasa_sequence_layer_text/text_encoder/randomly_connected_dense/Tensordot/MatMul'
defined at (most recent call last):
File "/home/intern/chatbot/venv/bin/rasa", line 8, in <module>
sys.exit(main())
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/__main__.py",
line 133, in main
cmdline_arguments.func(cmdline_arguments)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/cli/run.py",
line 93, in run
rasa.run(**vars(args))
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/api.py",
line 56, in run
rasa.core.run.serve_application(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/run.py",
line 231, in serve_application
app.run(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/app.py",
line 1206, in run
serve_multiple(server_settings, workers)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/server/runners.py",
line 264, in serve_multiple
process.start()
File "/usr/lib/python3.10/multiprocessing/process.py", line 121, in
start
self._popen = self._Popen(self)
File "/usr/lib/python3.10/multiprocessing/context.py", line 281, in
_Popen
return Popen(process_obj)
File "/usr/lib/python3.10/multiprocessing/popen_fork.py", line 19,
in __init__
self._launch(process_obj)
File "/usr/lib/python3.10/multiprocessing/popen_fork.py", line 71,
in _launch
code = process_obj._bootstrap(parent_sentinel=child_r)
File "/usr/lib/python3.10/multiprocessing/process.py", line 314, in
_bootstrap
self.run()
File "/usr/lib/python3.10/multiprocessing/process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/server/runners.py",
line 130, in serve
loop.run_until_complete(app._server_event("init", "before"))
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/app.py",
line 2000, in _server_event
await self.dispatch(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/signals.py",
line 191, in dispatch
return await dispatch
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/signals.py",
line 161, in _dispatch
retval = await maybe_coroutine
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/app.py",
line 1524, in _listener
await maybe_coro
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/run.py",
line 253, in load_agent_on_start
app.ctx.agent = await agent.load_agent(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/agent.py",
line 254, in load_agent
agent.load_model(model_path)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/agent.py",
line 352, in load_model
self.processor = MessageProcessor(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/processor.py",
line 101, in __init__
self.model_filename, self.model_metadata, self.graph_runner =
self._load_model(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/processor.py",
line 138, in _load_model
metadata, runner = loader.load_predict_graph_runner(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/loader.py",
line 29, in load_predict_graph_runner
runner = graph_runner_class.create(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 51, in create
return cls(graph_schema, model_storage, execution_context, hooks)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 37, in __init__
self._instantiated_nodes: Dict[Text, GraphNode] =
self._instantiate_nodes(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 60, in _instantiate_nodes
return {
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 61, in <dictcomp>
node_name: GraphNode.from_schema_node(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/graph.py",
line 566, in from_schema_node
return cls(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/graph.py",
line 392, in __init__
self._load_component()
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/graph.py",
line 403, in _load_component
self._component: GraphComponent = constructor( # type:
ignore[no-redef]
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1120, in load
return cls._load(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1151, in _load
model = cls._load_model(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1244, in _load_model
model = cls._load_model_class(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1275, in _load_model_class
return cls.model_class().load(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/utils/tensorflow/models.py",
line 445, in load
model.fit(data_generator, verbose=False)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 65, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/training.py",
line 1685, in fit
tmp_logs = self.train_function(iterator)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/training.py",
line 1284, in train_function
return step_function(self, iterator)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/training.py",
line 1268, in step_function
outputs = model.distribute_strategy.run(run_step, args=(data,))
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/training.py",
line 1249, in run_step
outputs = model.train_step(data)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/utils/tensorflow/models.py",
line 161, in train_step
prediction_loss = self.batch_loss(batch_in)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1614, in batch_loss
) = self._tf_layers[f"sequence_layer.{self.text_name}"](
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 65, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/base_layer.py",
line 1145, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 96, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/utils/tensorflow/rasa_layers.py",
line 1030, in call
if self._has_transformer:
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/utils/tensorflow/rasa_layers.py",
line 1032, in call
outputs, attention_weights = self._tf_layers[self.TRANSFORMER](
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 65, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/base_layer.py",
line 1145, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 96, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/utils/tensorflow/transformer.py",
line 611, in call
x = self._embedding(x) # (batch_size, length, units)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 65, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/base_layer.py",
line 1145, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 96, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/utils/tensorflow/layers.py",
line 368, in call
return super().call(inputs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/layers/core/dense.py",
line 244, in call
outputs = tf.tensordot(inputs, self.kernel, [[rank - 1], [0]])
Node:
'rasa_sequence_layer_text/text_encoder/randomly_connected_dense/Tensordot/MatMul'
Detected at node
'rasa_sequence_layer_text/text_encoder/randomly_connected_dense/Tensordot/MatMul'
defined at (most recent call last):
File "/home/intern/chatbot/venv/bin/rasa", line 8, in <module>
sys.exit(main())
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/__main__.py",
line 133, in main
cmdline_arguments.func(cmdline_arguments)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/cli/run.py",
line 93, in run
rasa.run(**vars(args))
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/api.py",
line 56, in run
rasa.core.run.serve_application(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/run.py",
line 231, in serve_application
app.run(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/app.py",
line 1206, in run
serve_multiple(server_settings, workers)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/server/runners.py",
line 264, in serve_multiple
process.start()
File "/usr/lib/python3.10/multiprocessing/process.py", line 121, in
start
self._popen = self._Popen(self)
File "/usr/lib/python3.10/multiprocessing/context.py", line 281, in
_Popen
return Popen(process_obj)
File "/usr/lib/python3.10/multiprocessing/popen_fork.py", line 19,
in __init__
self._launch(process_obj)
File "/usr/lib/python3.10/multiprocessing/popen_fork.py", line 71,
in _launch
code = process_obj._bootstrap(parent_sentinel=child_r)
File "/usr/lib/python3.10/multiprocessing/process.py", line 314, in
_bootstrap
self.run()
File "/usr/lib/python3.10/multiprocessing/process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/server/runners.py",
line 130, in serve
loop.run_until_complete(app._server_event("init", "before"))
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/app.py",
line 2000, in _server_event
await self.dispatch(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/signals.py",
line 191, in dispatch
return await dispatch
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/signals.py",
line 161, in _dispatch
retval = await maybe_coroutine
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/sanic/app.py",
line 1524, in _listener
await maybe_coro
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/run.py",
line 253, in load_agent_on_start
app.ctx.agent = await agent.load_agent(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/agent.py",
line 254, in load_agent
agent.load_model(model_path)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/agent.py",
line 352, in load_model
self.processor = MessageProcessor(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/processor.py",
line 101, in __init__
self.model_filename, self.model_metadata, self.graph_runner =
self._load_model(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/processor.py",
line 138, in _load_model
metadata, runner = loader.load_predict_graph_runner(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/loader.py",
line 29, in load_predict_graph_runner
runner = graph_runner_class.create(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 51, in create
return cls(graph_schema, model_storage, execution_context, hooks)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 37, in __init__
self._instantiated_nodes: Dict[Text, GraphNode] =
self._instantiate_nodes(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 60, in _instantiate_nodes
return {
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 61, in <dictcomp>
node_name: GraphNode.from_schema_node(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/graph.py",
line 566, in from_schema_node
return cls(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/graph.py",
line 392, in __init__
self._load_component()
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/graph.py",
line 403, in _load_component
self._component: GraphComponent = constructor( # type:
ignore[no-redef]
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1120, in load
return cls._load(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1151, in _load
model = cls._load_model(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1244, in _load_model
model = cls._load_model_class(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1275, in _load_model_class
return cls.model_class().load(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/utils/tensorflow/models.py",
line 445, in load
model.fit(data_generator, verbose=False)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 65, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/training.py",
line 1685, in fit
tmp_logs = self.train_function(iterator)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/training.py",
line 1284, in train_function
return step_function(self, iterator)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/training.py",
line 1268, in step_function
outputs = model.distribute_strategy.run(run_step, args=(data,))
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/training.py",
line 1249, in run_step
outputs = model.train_step(data)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/utils/tensorflow/models.py",
line 161, in train_step
prediction_loss = self.batch_loss(batch_in)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/nlu/classifiers/diet_classifier.py",
line 1614, in batch_loss
) = self._tf_layers[f"sequence_layer.{self.text_name}"](
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 65, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/base_layer.py",
line 1145, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 96, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/utils/tensorflow/rasa_layers.py",
line 1030, in call
if self._has_transformer:
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/utils/tensorflow/rasa_layers.py",
line 1032, in call
outputs, attention_weights = self._tf_layers[self.TRANSFORMER](
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 65, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/base_layer.py",
line 1145, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 96, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/utils/tensorflow/transformer.py",
line 611, in call
x = self._embedding(x) # (batch_size, length, units)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 65, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/engine/base_layer.py",
line 1145, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/utils/traceback_utils.py",
line 96, in error_handler
return fn(*args, **kwargs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/utils/tensorflow/layers.py",
line 368, in call
return super().call(inputs)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/keras/layers/core/dense.py",
line 244, in call
outputs = tf.tensordot(inputs, self.kernel, [[rank - 1], [0]])
Node:
'rasa_sequence_layer_text/text_encoder/randomly_connected_dense/Tensordot/MatMul'
2 root error(s) found.
(0) INTERNAL: Attempting to perform BLAS operation using
StreamExecutor without BLAS support
[[{{node
rasa_sequence_layer_text/text_encoder/randomly_connected_dense/Tensordot/MatMul}}]]
[[crf/cond/StatefulPartitionedCall/crf/cond/else/_236/crf/cond/Cast/_310]]
(1) INTERNAL: Attempting to perform BLAS operation using
StreamExecutor without BLAS support
[[{{node
rasa_sequence_layer_text/text_encoder/randomly_connected_dense/Tensordot/MatMul}}]]
0 successful operations.
0 derived errors ignored. [Op:__inference_train_function_50041]
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/agent.py",
line 254, in load_agent
agent.load_model(model_path)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/agent.py",
line 352, in load_model
self.processor = MessageProcessor(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/processor.py",
line 101, in __init__
self.model_filename, self.model_metadata, self.graph_runner =
self._load_model(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/core/processor.py",
line 138, in _load_model
metadata, runner = loader.load_predict_graph_runner(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/loader.py",
line 29, in load_predict_graph_runner
runner = graph_runner_class.create(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 51, in create
return cls(graph_schema, model_storage, execution_context, hooks)
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 37, in __init__
self._instantiated_nodes: Dict[Text, GraphNode] =
self._instantiate_nodes(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 60, in _instantiate_nodes
return {
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/runner/dask.py",
line 61, in <dictcomp>
node_name: GraphNode.from_schema_node(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/graph.py",
line 566, in from_schema_node
return cls(
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/graph.py",
line 392, in __init__
self._load_component()
File
"/home/intern/chatbot/venv/lib/python3.10/site-packages/rasa/engine/graph.py",
line 416, in _load_component
raise GraphComponentException(
rasa.engine.exceptions.GraphComponentException: Error initializing graph
component for node run_DIETClassifier5.
can someone help me in resolving this or is there any other way to handle concurrent users in rasa