Seeking help: TypeError: DacModel.decode() missing 1 required positional argument: 'quantized_representation'
Could anyone please help to resolve the error below, (let me know which dac package worked for compilation of this code)?
In my case, Following compilation/interpreting error occured when I tried to use this model:
generation = model.generate(input_ids=input_ids, prompt_input_ids=prompt_input_ids, attention_mask=attention_mask,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:_Develop_dev\px3.pixi\envs\default\Lib\site-packages\torch\utils_contextlib.py", line 116, in decorate_context
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "D:_Develop_dev\px3.pixi\envs\default\Lib\site-packages\parler_tts\modeling_parler_tts.py", line 3637, in generate
sample = self.audio_encoder.decode(audio_codes=sample[None, ...], **single_audio_decode_kwargs).audio_values
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: DacModel.decode() missing 1 required positional argument: 'quantized_representation'
(I added attentionmask for description, prompt due to errors still this DAC error is seen),
Is there any specific transformers version that worked for you?
Thanks in advance
In the same windows setup the base indic-parler-tts compiled (but was slow for our usage)
I guess it should work in transformers==4.46.0.dev0.
1st call to generate() doesnot give error but
2nd call to generate() gives error : "AttributeError: 'StaticCache' object has no attribute 'max_batch_size'. Did you mean: 'batch_size'?"
generation = model.generate(input_ids=input_ids, prompt_input_ids=prompt_input_ids, attention_mask=attention_mask, prompt_attention_mask=prompt_attention_mask,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:_Develop_dev\px3.pixi\envs\default\Lib\site-packages\torch\utils_contextlib.py", line 116, in decorate_context
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "D:_Develop_dev\px3.pixi\envs\default\Lib\site-packages\parler_tts\modeling_parler_tts.py", line 3491, in generate
model_kwargs["past_key_values"] = self._get_cache(
^^^^^^^^^^^^^^^^
File "D:_Develop_dev\px3.pixi\envs\default\Lib\site-packages\parler_tts\modeling_parler_tts.py", line 3275, in _get_cache
or cache_to_check.max_batch_size != max_batch_size
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:_Develop_dev\px3.pixi\envs\default\Lib\site-packages\torch\nn\modules\module.py", line 1928, in getattr
raise AttributeError(
AttributeError: 'StaticCache' object has no attribute 'max_batch_size'. Did you mean: 'batch_size'?
Could you let me know a specific fix if can be done locally?
- Even with same Description string, in a single batch also the voice is different!
Is there any setting to only follow 1 single voice as long as the description string is identical?
It looks like the issue is related to the StaticCache object not having the max_batch_size attribute. This might be due to a change in the library where max_batch_size has been deprecated or replaced with batch_size.
Here are a few things you can try to fix this locally:
- Check the library version: If you're using an older version of
transformers, upgrading to the latest version might resolve the issue. Try running:pip install --upgrade transformers - Modify the code: If
max_batch_sizehas been replaced withbatch_size, you can try changing occurrences ofmax_batch_sizetobatch_sizein your code, particularly in_get_cache()function. - Check GitHub issues: There are discussions on GitHub where similar issues have been reported. You might find a fix or workaround there.
- Verify StaticCache implementation: If you're manually using
StaticCache, ensure that it supportsmax_batch_size. If not, you may need to initialize it differently.
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