Remember the self. function here it is using might be based on metadata files, so check while recalling the sanitization function you are following the same code implementation as the course provided.
you can check this with requirements.txt file provided in file==>Open section which might provide you the module version as module version discrepancies cam also cause such error
Greetings Deepti, thanks for the quick response. Would you please direct me to this āfile=>Openā section.
The Jupyter notebook has a File menu with an Openā¦ choice. However I donāt see anything called requirements in any of the folders shown there. Also checked the .cache directory locally, not there.
Many thanks.
Also, complete error below:
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.13/lib/python3.13/site-packages/gradio/queueing.py", line 626, in process_events
response = await route_utils.call_process_api(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
...<5 lines>...
)
^
File "/Library/Frameworks/Python.framework/Versions/3.13/lib/python3.13/site-packages/gradio/route_utils.py", line 322, in call_process_api
output = await app.get_blocks().process_api(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
...<11 lines>...
)
^
File "/Library/Frameworks/Python.framework/Versions/3.13/lib/python3.13/site-packages/gradio/blocks.py", line 2229, in process_api
result = await self.call_function(
^^^^^^^^^^^^^^^^^^^^^^^^^
...<8 lines>...
)
^
File "/Library/Frameworks/Python.framework/Versions/3.13/lib/python3.13/site-packages/gradio/blocks.py", line 1740, in call_function
prediction = await anyio.to_thread.run_sync( # type: ignore
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
fn, *processed_input, limiter=self.limiter
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/Library/Frameworks/Python.framework/Versions/3.13/lib/python3.13/site-packages/anyio/to_thread.py", line 56, in run_sync
return await get_async_backend().run_sync_in_worker_thread(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
func, args, abandon_on_cancel=abandon_on_cancel, limiter=limiter
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/Library/Frameworks/Python.framework/Versions/3.13/lib/python3.13/site-packages/anyio/_backends/_asyncio.py", line 2470, in run_sync_in_worker_thread
return await future
^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.13/lib/python3.13/site-packages/anyio/_backends/_asyncio.py", line 967, in run
result = context.run(func, *args)
File "/Library/Frameworks/Python.framework/Versions/3.13/lib/python3.13/site-packages/gradio/utils.py", line 940, in wrapper
response = f(*args, **kwargs)
File "/Users/pspry/Documents/AI/lesson6.py", line 28, in transcribe_long_form
output = asr(
filepath,
...<2 lines>...
batch_size=8,
)
File "/Library/Frameworks/Python.framework/Versions/3.13/lib/python3.13/site-packages/transformers/pipelines/automatic_speech_recognition.py", line 271, in __call__
return super().__call__(inputs, **kwargs)
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.13/lib/python3.13/site-packages/transformers/pipelines/base.py", line 1417, in __call__
preprocess_params, forward_params, postprocess_params = self._sanitize_parameters(**kwargs)
~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^
TypeError: AutomaticSpeechRecognitionPipeline._sanitize_parameters() got an unexpected keyword argument 'max_new_tokens'
Hi Deepti, the lesson is: https://s172-29-106-101p8888.lab-aws-production.deeplearning.ai/notebooks/L07/L7_Text_to_Speech.ipynb
If I download the Jupyter notebook and run it in a local install of Jupyter I do not get this error. However, running the code as a python script (included below) I continue to get the āmax_new_tokenā error. I have double checked and confirmed that I have satisfied all the library requirements listed in the lab.
Running on MacBook Pro 2024, Sequoia 15.2 in Python 3.13
#!/usr/bin/env python
# coding: utf-8
# # Lesson 6: Automatic Speech Recognition
# - In the classroom, the libraries are already installed for you.
# - If you would like to run this code on your own machine, you can install the following:
# ```
# !pip install transformers
# !pip install -U datasets
# !pip install soundfile
# !pip install librosa
# !pip install gradio
# ```
#
# The `librosa` library may need to have [ffmpeg](https://www.ffmpeg.org/download.html) installed.
# - This page on [librosa](https://pypi.org/project/librosa/) provides installation instructions for ffmpeg.
# - Here is some code that suppresses warning messages.
from transformers.utils import logging
logging.set_verbosity_error()
# Build the pipeline
from transformers import pipeline
# Build pipeline
asr = pipeline(task="automatic-speech-recognition",
model="distil-whisper/distil-small.en")
# Info about [distil-whisper/distil-small.en](https://huggingface.co/distil-whisper)
# ### Build a shareable app with Gradio
#
# ### Troubleshooting Tip
# - Note, in the classroom, you may see the code for creating the Gradio app run indefinitely.
# - This is specific to this classroom environment when it's serving many learners at once, and you won't wouldn't experience this issue if you run this code on your own machine.
# - To fix this, please restart the kernel (Menu Kernel->Restart Kernel) and re-run the code in the lab from the beginning of the lesson.
import os
import gradio as gr
demo = gr.Blocks()
def transcribe_long_form(filepath):
if filepath is None:
gr.Warning("No audio found, please retry.")
return ""
output = asr(
filepath,
max_new_tokens=256,
chunk_length_s=30,
batch_size=8,
)
return output["text"]
mic_transcribe = gr.Interface(
fn=transcribe_long_form,
inputs=gr.Audio(sources="microphone",
type="filepath"),
outputs=gr.Textbox(label="Transcription",
lines=3),
allow_flagging="never")
file_transcribe = gr.Interface(
fn=transcribe_long_form,
inputs=gr.Audio(sources="upload",
type="filepath"),
outputs=gr.Textbox(label="Transcription",
lines=3),
allow_flagging="never",
)
with demo:
gr.TabbedInterface(
[mic_transcribe,
file_transcribe],
["Transcribe Microphone",
"Transcribe Audio File"],
)
demo.launch(share=False,
server_port=8000) #int(os.environ['PORT1']))
# demo.close()
# ## Note: Please stop the demo before continuing with the rest of the lab.
# - The app will continue running unless you run
# ```Python
# demo.close()
# ```
# - If you run another gradio app (later in this lesson) without first closing this appp, you'll see an error message:
# ```Python
# OSError: Cannot find empty port in range
# ```
understood your issue, finding solution please wait.
until then please check the modules you installed in system matches with the course provided version ESPECIALLY transformer because your pipeline is invoking this error.
Also confirm if made sure the utils.py file and/or metadata changes were considered while writing this python script as this could have also caused issue because in course provided they must have defined a function to include the max token to the pipeline.
Hi Deepti, no change after adding the additional import. I.E. same error appears.
Checking dependencies in local python vs the Jupyter notebook I see find:
Local Python: transformers 4.53.1
Lesson notebook: transformers 4.37.2
And the file in site-packages/transformers/generation/utils.py uses the term max_new_tokens 20 times. Unfortunately, downgrading transformers to 4.37.1 generates a host of incompatibility dependency conflicts.
Iām not sure where I can check for metadata changes you mention.
utils.py file and other files (model) is called metadata.
I was looking at the lab codes, can I ask you, did you download the distill whisper small.en also? locally.
max new token being 20 is a default max value, here is a git hub link explaining the same
you could download the required transformer version with pip install statement in the notebook you are working upon, here is a link explaining the same Link
Try this and let me know if this helps.
I also got to know you need to download distill whisper small en checkpoint locally in your system for the speech recognition model to work. so make sure you do that too.
If you notice in the lab you shared, in the file==>Open section, there is a folder model (so they have downloaded all the required models to run the code successfully) and probably that is what is missing in your local system.
Hi Deepti, I downgraded transformers to 4.37.2 and still had the max_new_tokens error. I finally removed that parameter from call and it is working fine.