Finetuning in webUI broken

New thread as its a different issue this time.
So I load the webui,
Click on train
In finetune model name I write commentator
I drop my audio sample ont the audio input section and wait for it to upload.
I click train.
I get this error:
Traceback (most recent call last):
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\queueing.py", line 489, in call_prediction
    output = await route_utils.call_process_api(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\route_utils.py", line 232, in call_process_api
    output = await app.get_blocks().process_api(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\blocks.py", line 1561, in process_api
    result = await self.call_function(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\blocks.py", line 1179, in call_function
    prediction = await anyio.to_thread.run_sync(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\anyio\to_thread.py", line 56, in run_sync
    return await get_async_backend().run_sync_in_worker_thread(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 2134, in run_sync_in_worker_thread
    return await future
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 851, in run
    result = context.run(func, *args)
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\utils.py", line 678, in wrapper
    response = f(*args, **kwargs)
  File "H:\XTTS\xtts-webui\modules\train.py", line 239, in train_xtts_model
    shutil.copytree(str(ready_folder), str(
  File "C:\Program Files\Python310\lib\shutil.py", line 556, in copytree
    with os.scandir(src) as itr:
FileNotFoundError: [WinError 3] The system cannot find the path specified: 'finetuned_models\\commentator\\ready'

The folder does not exist.
If I click train again it creates the folder and proceeds and I get this error:
finetuned_models\commentator
>> DVAE weights restored from: H:\XTTS\xtts-webui\models\v2.0.2\dvae.pth
Traceback (most recent call last):
  File "H:\XTTS\xtts-webui\modules\train.py", line 87, in train_model
    speaker_xtts_path, config_path, original_xtts_checkpoint, vocab_file, exp_path, speaker_wav = train_gpt(
  File "H:\XTTS\xtts-webui\scripts\utils\gpt_train.py", line 175, in train_gpt
    train_samples, eval_samples = load_tts_samples(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\TTS\tts\datasets\__init__.py", line 121, in load_tts_samples
    assert len(meta_data_train) > 0, f" [!] No training samples found in {root_path}/{meta_file_train}"
AssertionError:  [!] No training samples found in finetuned_models\commentator\dataset/metadata_train.csv
Traceback (most recent call last):
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\queueing.py", line 489, in call_prediction
    output = await route_utils.call_process_api(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\route_utils.py", line 232, in call_process_api
    output = await app.get_blocks().process_api(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\blocks.py", line 1561, in process_api
    result = await self.call_function(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\blocks.py", line 1179, in call_function
    prediction = await anyio.to_thread.run_sync(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\anyio\to_thread.py", line 56, in run_sync
    return await get_async_backend().run_sync_in_worker_thread(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 2134, in run_sync_in_worker_thread
    return await future
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 851, in run
    result = context.run(func, *args)
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\utils.py", line 678, in wrapper
    response = f(*args, **kwargs)
  File "H:\XTTS\xtts-webui\modules\train.py", line 245, in train_xtts_model
    shutil.copy(speaker_reference_path, reference_destination)
  File "C:\Program Files\Python310\lib\shutil.py", line 417, in copy
    copyfile(src, dst, follow_symlinks=follow_symlinks)
  File "C:\Program Files\Python310\lib\shutil.py", line 254, in copyfile
    with open(src, 'rb') as fsrc:
FileNotFoundError: [Errno 2] No such file or directory: 'finetuned_models\\commentator\\ready\\reference.wav'

If i place a wav file called reference.wav in the folder I can proceed to the next error.
Existing language matches target language
Loading Whisper Model!
Existing training metadata found and loaded.
Existing evaluation metadata found and loaded.
Dataset Processed!
finetuned_models\commentator
>> DVAE weights restored from: H:\XTTS\xtts-webui\models\v2.0.2\dvae.pth
Traceback (most recent call last):
  File "H:\XTTS\xtts-webui\modules\train.py", line 87, in train_model
    speaker_xtts_path, config_path, original_xtts_checkpoint, vocab_file, exp_path, speaker_wav = train_gpt(
  File "H:\XTTS\xtts-webui\scripts\utils\gpt_train.py", line 175, in train_gpt
    train_samples, eval_samples = load_tts_samples(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\TTS\tts\datasets\__init__.py", line 121, in load_tts_samples
    assert len(meta_data_train) > 0, f" [!] No training samples found in {root_path}/{meta_file_train}"
AssertionError:  [!] No training samples found in finetuned_models\commentator\dataset/metadata_train.csv

No idea past this point.
Metadata_train.csv just includes "audio_file|text|speaker_name"
Full log including the Git pull, installer run (to make sure requirements are installed) and all the errors:
Microsoft Windows [Version 10.0.22621.3007]
(c) Microsoft Corporation. All rights reserved.

H:\XTTS\xtts-webui>git pull
Already up to date.

H:\XTTS\xtts-webui>install.bat
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Requirement already satisfied: torch==2.1.1 in h:\xtts\xtts-webui\venv\lib\site-packages (from -r .\requirements.txt (line 2)) (2.1.1+cu118)
Requirement already satisfied: torchaudio==2.1.1 in h:\xtts\xtts-webui\venv\lib\site-packages (from -r .\requirements.txt (line 3)) (2.1.1+cu118)
Requirement already satisfied: faster_whisper==0.10.0 in h:\xtts\xtts-webui\venv\lib\site-packages (from -r .\requirements.txt (line 4)) (0.10.0)
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Requirement already satisfied: tzdata in h:\xtts\xtts-webui\venv\lib\site-packages (from tzlocal->dateparser~=1.1.0->gruut[de,es,fr]==2.2.3->tts>=0.22.0->-r .\requirements.txt (line 5)) (2023.4)
Requirement already satisfied: pyasn1<0.6.0,>=0.4.6 in h:\xtts\xtts-webui\venv\lib\site-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard->trainer>=0.0.32->tts>=0.22.0->-r .\requirements.txt (line 5)) (0.5.1)
Requirement already satisfied: oauthlib>=3.0.0 in h:\xtts\xtts-webui\venv\lib\site-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<2,>=0.5->tensorboard->trainer>=0.0.32->tts>=0.22.0->-r .\requirements.txt (line 5)) (3.2.2)

[notice] A new release of pip available: 22.2.1 -> 23.3.2
[notice] To update, run: python.exe -m pip install --upgrade pip
Looking in indexes: https://download.pytorch.org/whl/cu118
Requirement already satisfied: torch==2.1.1+cu118 in h:\xtts\xtts-webui\venv\lib\site-packages (2.1.1+cu118)
Requirement already satisfied: torchaudio==2.1.1+cu118 in h:\xtts\xtts-webui\venv\lib\site-packages (2.1.1+cu118)
Requirement already satisfied: networkx in h:\xtts\xtts-webui\venv\lib\site-packages (from torch==2.1.1+cu118) (2.8.8)
Requirement already satisfied: jinja2 in h:\xtts\xtts-webui\venv\lib\site-packages (from torch==2.1.1+cu118) (3.1.2)
Requirement already satisfied: fsspec in h:\xtts\xtts-webui\venv\lib\site-packages (from torch==2.1.1+cu118) (2023.12.2)Requirement already satisfied: sympy in h:\xtts\xtts-webui\venv\lib\site-packages (from torch==2.1.1+cu118) (1.12)
Requirement already satisfied: typing-extensions in h:\xtts\xtts-webui\venv\lib\site-packages (from torch==2.1.1+cu118) (4.9.0)
Requirement already satisfied: filelock in h:\xtts\xtts-webui\venv\lib\site-packages (from torch==2.1.1+cu118) (3.13.1)
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[notice] A new release of pip available: 22.2.1 -> 23.3.2
[notice] To update, run: python.exe -m pip install --upgrade pip
Install deepspeed for windows for python 3.10.x and CUDA 11.8
Install complete.
Press any key to continue . . .

(venv) H:\XTTS\xtts-webui>start_xtts_webui.bat
2024-01-14 21:14:53.628 | INFO     | xtts_webui:<module>:57 - Start loading model v2.0.2
2024-01-14 21:14:53.628 | INFO     | xtts_webui:<module>:60 - this dir: H:\XTTS\xtts-webui
[2024-01-14 21:15:04,963] [INFO] [real_accelerator.py:158:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2024-01-14 21:15:05,143] torch.distributed.elastic.multiprocessing.redirects: [WARNING] NOTE: Redirects are currently not supported in Windows or MacOs.
[2024-01-14 21:15:05,325] [INFO] [logging.py:96:log_dist] [Rank -1] DeepSpeed info: version=0.11.2+unknown, git-hash=unknown, git-branch=unknown
[2024-01-14 21:15:05,326] [WARNING] [config_utils.py:69:_process_deprecated_field] Config parameter replace_method is deprecated. This parameter is no longer needed, please remove from your call to DeepSpeed-inference
[2024-01-14 21:15:05,326] [WARNING] [config_utils.py:69:_process_deprecated_field] Config parameter mp_size is deprecated use tensor_parallel.tp_size instead
[2024-01-14 21:15:05,327] [INFO] [logging.py:96:log_dist] [Rank -1] quantize_bits = 8 mlp_extra_grouping = False, quantize_groups = 1
[2024-01-14 21:15:05,520] [INFO] [logging.py:96:log_dist] [Rank -1] DeepSpeed-Inference config: {'layer_id': 0, 'hidden_size': 1024, 'intermediate_size': 4096, 'heads': 16, 'num_hidden_layers': -1, 'dtype': torch.float32, 'pre_layer_norm': True, 'norm_type': <NormType.LayerNorm: 1>, 'local_rank': -1, 'stochastic_mode': False, 'epsilon': 1e-05, 'mp_size': 1, 'scale_attention': True, 'triangular_masking': True, 'local_attention': False, 'window_size': 1, 'rotary_dim': -1, 'rotate_half': False, 'rotate_every_two': True, 'return_tuple': True, 'mlp_after_attn': True, 'mlp_act_func_type': <ActivationFuncType.GELU: 1>, 'specialized_mode': False, 'training_mp_size': 1, 'bigscience_bloom': False, 'max_out_tokens': 1024, 'min_out_tokens': 1, 'scale_attn_by_inverse_layer_idx': False, 'enable_qkv_quantization': False, 'use_mup': False, 'return_single_tuple': False, 'set_empty_params': False, 'transposed_mode': False, 'use_triton': False, 'triton_autotune': False, 'num_kv': -1, 'rope_theta': 10000}
2024-01-14 21:15:05.974 | INFO     | scripts.tts_funcs:load_model:99 - Pre-create latents for all current speakers
2024-01-14 21:15:05.975 | INFO     | scripts.tts_funcs:get_or_create_latents:173 - creating latents for calm_female: speakers/calm_female.wav
H:\XTTS\xtts-webui\venv\lib\site-packages\torchaudio\functional\functional.py:147: UserWarning: Specified kernel cache directory could not be created! This disables kernel caching. Specified directory is temp/torch/kernels. This warning will appear only once per process. (Triggered internally at ..\aten\src\ATen\native\cuda\jit_utils.cpp:1444.)
  return spec_f.abs().pow(power)
2024-01-14 21:15:07.326 | INFO     | scripts.tts_funcs:get_or_create_latents:173 - creating latents for davidatt: speakers/davidatt.wav
2024-01-14 21:15:07.456 | INFO     | scripts.tts_funcs:get_or_create_latents:173 - creating latents for female: speakers/female.wav
2024-01-14 21:15:07.544 | INFO     | scripts.tts_funcs:get_or_create_latents:173 - creating latents for male: speakers/male.wav
2024-01-14 21:15:07.623 | INFO     | scripts.tts_funcs:get_or_create_latents:173 - creating latents for MorganFreeman: speakers/MorganFreeman.wav
2024-01-14 21:15:07.721 | INFO     | scripts.tts_funcs:get_or_create_latents:173 - creating latents for NarratorNew: ['speakers/NarratorNew\\reference.wav']
2024-01-14 21:15:07.790 | INFO     | scripts.tts_funcs:create_latents_for_all:187 - Latents created for all 6 speakers.
2024-01-14 21:15:07.790 | INFO     | scripts.tts_funcs:load_model:103 - Model successfully loaded
Running on local URL:  http://<IP_ADDRESS>:8010

To create a public link, set `share=True` in `launch()`.
2024-01-14 21:17:32.187 | INFO     | scripts.tts_funcs:unload_model:79 - Model unloaded
Warning, existing language does not match target language. Updated lang.txt with target language.
Loading Whisper Model!
The sum of the duration of the audios that you provided should be at least 2 minutes!
finetuned_models\commentator
Traceback (most recent call last):
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\queueing.py", line 489, in call_prediction
    output = await route_utils.call_process_api(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\route_utils.py", line 232, in call_process_api
    output = await app.get_blocks().process_api(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\blocks.py", line 1561, in process_api
    result = await self.call_function(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\blocks.py", line 1179, in call_function
    prediction = await anyio.to_thread.run_sync(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\anyio\to_thread.py", line 56, in run_sync
    return await get_async_backend().run_sync_in_worker_thread(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 2134, in run_sync_in_worker_thread
    return await future
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 851, in run
    result = context.run(func, *args)
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\utils.py", line 678, in wrapper
    response = f(*args, **kwargs)
  File "H:\XTTS\xtts-webui\modules\train.py", line 239, in train_xtts_model
    shutil.copytree(str(ready_folder), str(
  File "C:\Program Files\Python310\lib\shutil.py", line 556, in copytree
    with os.scandir(src) as itr:
FileNotFoundError: [WinError 3] The system cannot find the path specified: 'finetuned_models\\commentator\\ready'
2024-01-14 21:23:12.341 | INFO     | scripts.tts_funcs:unload_model:79 - Model unloaded
Existing language matches target language
Loading Whisper Model!
Existing training metadata found and loaded.
Existing evaluation metadata found and loaded.
Dataset Processed!
finetuned_models\commentator
>> DVAE weights restored from: H:\XTTS\xtts-webui\models\v2.0.2\dvae.pth
Traceback (most recent call last):
  File "H:\XTTS\xtts-webui\modules\train.py", line 87, in train_model
    speaker_xtts_path, config_path, original_xtts_checkpoint, vocab_file, exp_path, speaker_wav = train_gpt(
  File "H:\XTTS\xtts-webui\scripts\utils\gpt_train.py", line 175, in train_gpt
    train_samples, eval_samples = load_tts_samples(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\TTS\tts\datasets\__init__.py", line 121, in load_tts_samples
    assert len(meta_data_train) > 0, f" [!] No training samples found in {root_path}/{meta_file_train}"
AssertionError:  [!] No training samples found in finetuned_models\commentator\dataset/metadata_train.csv
Traceback (most recent call last):
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\queueing.py", line 489, in call_prediction
    output = await route_utils.call_process_api(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\route_utils.py", line 232, in call_process_api
    output = await app.get_blocks().process_api(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\blocks.py", line 1561, in process_api
    result = await self.call_function(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\blocks.py", line 1179, in call_function
    prediction = await anyio.to_thread.run_sync(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\anyio\to_thread.py", line 56, in run_sync
    return await get_async_backend().run_sync_in_worker_thread(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 2134, in run_sync_in_worker_thread
    return await future
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 851, in run
    result = context.run(func, *args)
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\utils.py", line 678, in wrapper
    response = f(*args, **kwargs)
  File "H:\XTTS\xtts-webui\modules\train.py", line 245, in train_xtts_model
    shutil.copy(speaker_reference_path, reference_destination)
  File "C:\Program Files\Python310\lib\shutil.py", line 417, in copy
    copyfile(src, dst, follow_symlinks=follow_symlinks)
  File "C:\Program Files\Python310\lib\shutil.py", line 254, in copyfile
    with open(src, 'rb') as fsrc:
FileNotFoundError: [Errno 2] No such file or directory: 'finetuned_models\\commentator\\ready\\reference.wav'
2024-01-14 21:24:54.746 | INFO     | scripts.tts_funcs:unload_model:79 - Model unloaded
Existing language matches target language
Loading Whisper Model!
Existing training metadata found and loaded.
Existing evaluation metadata found and loaded.
Dataset Processed!
finetuned_models\commentator
>> DVAE weights restored from: H:\XTTS\xtts-webui\models\v2.0.2\dvae.pth
Traceback (most recent call last):
  File "H:\XTTS\xtts-webui\modules\train.py", line 87, in train_model
    speaker_xtts_path, config_path, original_xtts_checkpoint, vocab_file, exp_path, speaker_wav = train_gpt(
  File "H:\XTTS\xtts-webui\scripts\utils\gpt_train.py", line 175, in train_gpt
    train_samples, eval_samples = load_tts_samples(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\TTS\tts\datasets\__init__.py", line 121, in load_tts_samples
    assert len(meta_data_train) > 0, f" [!] No training samples found in {root_path}/{meta_file_train}"
AssertionError:  [!] No training samples found in finetuned_models\commentator\dataset/metadata_train.csv
Traceback (most recent call last):
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\queueing.py", line 489, in call_prediction
    output = await route_utils.call_process_api(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\route_utils.py", line 232, in call_process_api
    output = await app.get_blocks().process_api(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\blocks.py", line 1561, in process_api
    result = await self.call_function(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\blocks.py", line 1179, in call_function
    prediction = await anyio.to_thread.run_sync(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\anyio\to_thread.py", line 56, in run_sync
    return await get_async_backend().run_sync_in_worker_thread(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 2134, in run_sync_in_worker_thread
    return await future
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 851, in run
    result = context.run(func, *args)
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\gradio\utils.py", line 678, in wrapper
    response = f(*args, **kwargs)
  File "H:\XTTS\xtts-webui\modules\train.py", line 245, in train_xtts_model
    shutil.copy(speaker_reference_path, reference_destination)
  File "C:\Program Files\Python310\lib\shutil.py", line 417, in copy
    copyfile(src, dst, follow_symlinks=follow_symlinks)
  File "C:\Program Files\Python310\lib\shutil.py", line 254, in copyfile
    with open(src, 'rb') as fsrc:
FileNotFoundError: [Errno 2] No such file or directory: 'finetuned_models\\commentator\\ready\\reference.wav'
2024-01-14 21:28:26.131 | INFO     | scripts.tts_funcs:unload_model:79 - Model unloaded
Existing language matches target language
Loading Whisper Model!
Existing training metadata found and loaded.
Existing evaluation metadata found and loaded.
Dataset Processed!
finetuned_models\commentator
>> DVAE weights restored from: H:\XTTS\xtts-webui\models\v2.0.2\dvae.pth
Traceback (most recent call last):
  File "H:\XTTS\xtts-webui\modules\train.py", line 87, in train_model
    speaker_xtts_path, config_path, original_xtts_checkpoint, vocab_file, exp_path, speaker_wav = train_gpt(
  File "H:\XTTS\xtts-webui\scripts\utils\gpt_train.py", line 175, in train_gpt
    train_samples, eval_samples = load_tts_samples(
  File "H:\XTTS\xtts-webui\venv\lib\site-packages\TTS\tts\datasets\__init__.py", line 121, in load_tts_samples
    assert len(meta_data_train) > 0, f" [!] No training samples found in {root_path}/{meta_file_train}"
AssertionError:  [!] No training samples found in finetuned_models\commentator\dataset/metadata_train.csv

Hi, sorry for not replying earlier, lots of work going on right now.
Try deleting the model in the finetune_models folder , and try again

Hi, sorry for not replying earlier, lots of work going on right now.
Try deleting the model in the finetune_models folder , and try again

NP You have a life chap, no one expects immediate replies :)
I do have bad news though.
I created a new folder and started afresh. Same issues popped up.

Hi, sorry for not replying earlier, lots of work going on right now.
Try deleting the model in the finetune_models folder , and try again

Just tried again with another fresh install as i see there was a commit 6 hours ago, but the same issues remain. Can I ask have you tried to recreate the steps I am doing on a fresh install your end?
So I load the webui,
Click on train
In finetune model name I write commentator
I drop my audio sample ont the audio input section and wait for it to upload.
I click train.
I cant see why it wouldnt work on my system if its working on yours but i have even tried installing it on a different hard drive and getting the exact same error sequence.

Hi, sorry for not replying earlier, lots of work going on right now.
Try deleting the model in the finetune_models folder , and try again

While I stand by what i said about not needing instant replies, the issue is still ongoing for 4 days now, is there a fix in the works?

Ok
The issue (as explained to me on discord by MattiaHeron ) is that the samples i am using are not getting detected and processed by whisper (despite the fact the same samples were before a few updates) and so there are no samples going into the dataset and the app gives the error.
Since I am using one large sample it means if it fails thats it, no training dataset.
The chap sent me some test samples where he split them up manually into tracks and that worked (since if one fails there is still tons).
I am going to leave this as a bug though since files that used to work now dont. but atleast now we know why its erroring and hopefully a more verbose error message could be added "No samples processed please upload better quality samples" or some such.
Huge thankyou to MattiaHeron who helped problem solve the issue when I was looking for an alternative to the WebUI.

Same issue.
`Existing language matches target language
Loading Whisper Model!
Existing training metadata found and loaded.
Existing evaluation metadata found and loaded.
Segments from Voice123 - Jose Araujo Cardiff Castle audio tour - Jose Araujo have been previously processed; skipping...
Dataset Processed!
finetuned_models/jose_pteu_base_model

DVAE weights restored from: /content/xtts-webui/models/v2.0.2/dvae.pth
| > Found 29 files in /content/xtts-webui/finetuned_models/jose_pteu_base_model/dataset
usage: app.py [-h] [--continue_path CONTINUE_PATH] [--restore_path RESTORE_PATH]
[--best_path BEST_PATH] [--use_ddp true/false] [--use_accelerate true/false]
[--grad_accum_steps GRAD_ACCUM_STEPS] [--overfit_batch true/false]
[--skip_train_epoch true/false] [--start_with_eval true/false]
[--small_run SMALL_RUN] [--gpu GPU] [--rank RANK] [--group_id GROUP_ID]
app.py: error: argument -h/--help: ignored explicit argument 's'
Traceback (most recent call last):
File "/usr/lib/python3.10/argparse.py", line 1878, in parse_known_args
namespace, args = self._parse_known_args(args, namespace)
File "/usr/lib/python3.10/argparse.py", line 2091, in _parse_known_args
start_index = consume_optional(start_index)
File "/usr/lib/python3.10/argparse.py", line 1999, in consume_optional
raise ArgumentError(action, msg % explicit_arg)
argparse.ArgumentError: argument -h/--help: ignored explicit argument 's'

During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/content/xtts-webui/modules/train.py", line 87, in train_model
speaker_xtts_path, config_path, original_xtts_checkpoint, vocab_file, exp_path, speaker_wav = train_gpt(
File "/content/xtts-webui/scripts/utils/gpt_train.py", line 183, in train_gpt
trainer = Trainer(
File "/usr/local/lib/python3.10/dist-packages/trainer/trainer.py", line 397, in init
args, coqpit_overrides = self.parse_argv(args)
File "/usr/local/lib/python3.10/dist-packages/trainer/trainer.py", line 680, in parse_argv
training_args, coqpit_overrides = parser.parse_known_args()
File "/usr/lib/python3.10/argparse.py", line 1881, in parse_known_args
self.error(str(err))
File "/usr/lib/python3.10/argparse.py", line 2606, in error
self.exit(2, _('%(prog)s: error: %(message)s\n') % args)
File "/usr/lib/python3.10/argparse.py", line 2593, in exit
_sys.exit(status)
SystemExit: 2
Traceback (most recent call last):
File "/usr/local/lib/python3.10/dist-packages/gradio/queueing.py", line 489, in call_prediction
output = await route_utils.call_process_api(
File "/usr/local/lib/python3.10/dist-packages/gradio/route_utils.py", line 232, in call_process_api
output = await app.get_blocks().process_api(
File "/usr/local/lib/python3.10/dist-packages/gradio/blocks.py", line 1561, in process_api
result = await self.call_function(
File "/usr/local/lib/python3.10/dist-packages/gradio/blocks.py", line 1179, in call_function
prediction = await anyio.to_thread.run_sync(
File "/usr/local/lib/python3.10/dist-packages/anyio/to_thread.py", line 33, in run_sync
return await get_asynclib().run_sync_in_worker_thread(
File "/usr/local/lib/python3.10/dist-packages/anyio/_backends/_asyncio.py", line 877, in run_sync_in_worker_thread
return await future
File "/usr/local/lib/python3.10/dist-packages/anyio/_backends/_asyncio.py", line 807, in run
result = context.run(func, *args)
File "/usr/local/lib/python3.10/dist-packages/gradio/utils.py", line 678, in wrapper
response = f(*args, **kwargs)
File "/content/xtts-webui/modules/train.py", line 245, in train_xtts_model
shutil.copy(speaker_reference_path, reference_destination)
File "/usr/lib/python3.10/shutil.py", line 417, in copy
copyfile(src, dst, follow_symlinks=follow_symlinks)
File "/usr/lib/python3.10/shutil.py", line 254, in copyfile
with open(src, 'rb') as fsrc:
FileNotFoundError: [Errno 2] No such file or directory: 'finetuned_models/jose_pteu_base_model/ready/reference.wav'`

Ok The issue (as explained to me on discord by MattiaHeron ) is that the samples i am using are not getting detected and processed by whisper (despite the fact the same samples were before a few updates) and so there are no samples going into the dataset and the app gives the error. Since I am using one large sample it means if it fails thats it, no training dataset. The chap sent me some test samples where he split them up manually into tracks and that worked (since if one fails there is still tons). I am going to leave this as a bug though since files that used to work now dont. but atleast now we know why its erroring and hopefully a more verbose error message could be added "No samples processed please upload better quality samples" or some such. Huge thankyou to MattiaHeron who helped problem solve the issue when I was looking for an alternative to the WebUI.

Thanks mate. You saved me from even more troubleshooting. Been trying to get this to work all day. Will make it a habit to split audio files into many smaller files. Something is probably still not right since GPU usage is never above 20% during training, but that will be explored another day.

Adding on to this, I loaded 4909 small files and the same issue occurred. Now, this is a fresh install on a different drive because I didn't want my SSD to be thrashed. I pre-split them with a StyleTTS2 tool as it happened to match all the boxes that XTTS needs in audio. Sadly, it did not workout and does not explain anything other than the above issues. I would hope to have seen a "no audio files" or "failed to create dataset" sort of error.


add unmarshel func for RoutingTables.Routes

* [x]  Figure out how the unmarshal works for the `Instance` with `NetworkInterfaces` without a wrapper type and dedicated `UnmarshalJSON` function.

Summary of the discussion with @olasaadi99 : For the RoutingTable type there was a need to add a wrapper type to Route, since the standard unmarshal failed to unmarshal Route object, because it contained an interface type field for next_hop.
The custom unmarshal UnmarshalJSON  added to the wrapper type - called vpcv1.UnmarshalRoute, which could handle the unmarshaling of Route objects including this next_hop field..
(In the case of NetworkInterfaces for Instance the standard unmarshal worked, because this struct did not contain fields of type interface).
@kyorav @zivnevo  I think we might want to change the unmarshaling of the collector to always call the dedicated Unmarshal functions of the vpcv1 pkg , so that we are not susceptible to fields of interface types that fail the standard unmarshal function. I think this would be more robust and would eliminate the "wrapper types" work-around used currently. Let me know what you think.

I am not sure how this would work. Our model is different from the vpc1, so we still need to write our own un-marsheling function in certain places. If I remember correctly, as soon as you call the vpc1 function you cannot interrupt it with your own code (without modifying the vpc1 module). Can you sketch what you mean by "always call the dedicated Unmarshal functions of the vpcv1 pkg"?

I am not sure how this would work. Our model is different from the vpc1, so we still need to write our own un-marsheling function in certain places. If I remember correctly, as soon as you call the vpc1 function you cannot interrupt it with your own code (without modifying the vpc1 module). Can you sketch what you mean by "always call the dedicated Unmarshal functions of the vpcv1 pkg"?

I think we can implement UnmarshalJSON for every type of our data_model, for example it was already implemented for EndpointGateway, where it calls vpcv1.UnmarshalEndpointGateway on the field that is imported from vpc1.
Similarly, for our model's RoutingTable , we can have UnmarshalJSON  that calls both UnmarshalRoutingTable and UnmarshalRoute for the list of routes, and assigns the unmarshaled objects in their fields of the RoutingTable  object.
The goal is that we don't use the standard unmarshal function for vpc1 fields in our model.

Approving this PR, will continue the discussion offline, and open a separate issue if we decide to change the unmarshal implementation.


sort imports with isort rules by ruff linter

sort imports by applying isort rules with ruff linter

Disclaimer: This review was made by a crew of AI Agents.
Code Review Comment for PR #1730 - crewAI Repository
Overview
This pull request introduces several significant enhancements focused on code organization, import statements, and linting configurations. These changes promote improved maintainability and readability within the codebase.
1. Linting Configuration Updates
The PR adds a dedicated .ruff.toml configuration file and updates pre-commit hooks.
Issues Found:

While the Ruff configuration is a great addition, it may benefit from broader linting checks to catch potential issues early.

Suggestions:
Consider expanding the configuration to include additional checks:
[lint]
select = [
    "I",    # isort
    "E",    # pycodestyle errors
    "F",    # pyflakes
    "B",    # flake8-bugbear
    "UP"    # pyupgrade
]
line-length = 88  # Match black's default

2. Import Statement Organization
Various files were improved in terms of import organization with consistent grouping.
Recommendations:
Although many imports are organized well, some files could further refine their structure. For instance, in src/crewai/cli/authentication/main.py, the import organization could benefit from clearer delineation:
Current:
import requests
from rich.console import Console
from crewai.cli.tools.main import ToolCommand

Recommended:
# Standard library imports
from typing import Dict, Any

# Third-party imports
import requests
from rich.console import Console

# Local imports
from crewai.cli.tools.main import ToolCommand

3. Type Hints and Documentation
The introduction of comprehensive type hints and docstrings is essential for maintainability.
Suggestions:
For the Settings class in src/crewai/cli/config.py, consider adding detailed docstrings:
class Settings(BaseModel):
    """
    Configuration settings for CrewAI CLI.

    Attributes:
        tool_repository_username (Optional[str]): Username for tool repository access.
        tool_repository_password (Optional[str]): Password for tool repository access.
        config_path (Path): Path to configuration file.
    """

4. Error Handling
Enhancing error handling is paramount to ensure robustness.
Recommendations:
For proper error signaling in src/crewai/cli/authentication/token.py, implement custom exceptions:
class AuthenticationError(Exception):
    """Raised when authentication fails."""
    pass

def get_auth_token() -> str:
    """
    Get the authentication token.

    Raises:
        AuthenticationError: If no valid token is available.
    """

5. Code Structure
Usage of abstract base classes should be done effectively to define clear interfaces.
Recommendations:
For memory-related classes, you may leverage abstract base classes, making the implementation structure clearer:
class BaseMemory(ABC):
    """Abstract base class for all memory implementations."""

6. Testing Improvements
The test files are well-covered but can be made more robust.
Suggestions:
Ensure that test cases in tests/cli/config_test.py thoroughly validate the functionality, including edge cases.
Historical Context and Related Pull Requests
While I couldn't fetch detailed historical context or related pull requests, it is important to keep in mind the active discussions around standardizing linting configurations and improving error handling practices that have surfaced in previous PRs. Aligning with these insights through this PR can foster consistency in the codebase and improve overall quality.
Summary
The changes proposed in PR #1730 significantly enhance the CrewAI codebase in terms of organization and best practices. Here are the key takeaways:

Improved linting configurations and import organization.
Encouraged comprehensive type hints and documentation.
Enhanced error management and structural clarity.

As a reminder, the proposed changes appear safe to merge once the aforementioned recommendations are implemented. Engaging with these improvements will lead to a cleaner, more maintainable codebase moving forward.

Hey @bowenliang123 thanks for the PR.
The lint portion didn't pass, can you check it so we can review it?

Hi @pythonbyte , all the linter violations have been fixed. Please have a review.

Great work @bowenliang123! This is much needed!!

Cheers, and thanks for reviewing and merging. 🍻


chore: bdd-spring-1575574665 to 0.0.1

chore: Promote bdd-spring-1575574665 to version 0.0.1

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Issues with generation

This issue was originally created by @micimize here, before being automatically moved:
https://github.com/angel-dart-archive/graphql/issues/24

generating types in a single file models.dart still results in the following issues:

recursive types are generated in a way that static resolution fails
nested references to other serializables don't work

My temporary workaround for 1 was to terminate a recursive reference 1 level deep, then remove the generated code:
GraphQLObjectType _characterType(GraphQLType self) => objectType(
      'Character',
      isInterface: true,
      interfaces: [],
      fields: [
        field('id', graphQLString, description: 'The ID of the character'),
        field('name', graphQLString, description: 'The name of the character'),
        field('friends', listOf(self),
            description:
                'The friends of the character, or an empty list if they have none'),
        field(
          'appearsIn',
          listOf(episodeGraphQLType),
          description: 'The movies this character appears in',
        ),
        field('graphql', graphQLString)
      ],
    );

GraphQLObjectType _characterLeafGraphQLType = _characterType(graphQLString);
GraphQLObjectType characterGraphQLType =
    _characterType(_characterLeafGraphQLType);

For 2 I generated the code for List<Starship> with List<Character>, then edited it. I then moved all generated code to models_g.dart

@thosakwe commented:
Seeking a bit more info, so I can finally resolve this:

recursive types are generated in a way that static resolution fails

What specifically do you mean by this? By "recursive type," do you mean a type that references itself? Or one that references a parent type? Or something else? Secondly, what specifically does "static resolution" mean in this case? Trying to understand it better.

nested references to other serializables don't work

Could you potentially show me your models.dart? Actually, show me the ideal version of models.dart that you'd like to have, and why it isn't currently possible, and I can correct that. Thanks.

@micimize commented:

By "recursive type," do you mean a type that references itself?

Yes, though a parent type would likely also cause the problem

what specifically does "static resolution" mean in this case?

That dart will fail to compile the file because  a "Compile-time constant expression depends on itself.", i.e. the generated statement is
GraphQLObjectType characterGraphQLType = objectType(
      'Character',
      isInterface: true,
      interfaces: [],
      fields: [
        field('id', graphQLString, description: 'The ID of the character'),
        field('name', graphQLString, description: 'The name of the character'),|
        // !!!! self reference that throws the compilation error:
        field('friends', listOf(characterGraphQLType),
            description:
                'The friends of the character, or an empty list if they have none'),
        field(
          'appearsIn',
          listOf(episodeGraphQLType),
          description: 'The movies this character appears in',
        ),
        field('graphql', graphQLString)
      ],
    );

The "workaround" models.dart from my angel_starwars_test_server.
To get a good testing scenario, you could add friends to your starwars example model:
@graphQLClass
abstract class Character {
  @GraphQLDocumentation(description: "The ID of the character")
  String get id;

  @GraphQLDocumentation(description: "The name of the character")
  String get name;

  @GraphQLDocumentation(
      description:
          "The friends of the character, or an empty list if they have none")
  List<Character> get friends;
}

@thosakwe commented:
Thanks for the info. I'm working on a 1.2.0 release of graphql_parser, among other things. So I'll be sure to get this done ASAP. Also coming is parsing of GraphQL's type IDL (this was omitted before because the parser was aimed only at servers, but I can see now how useful it can be. Plus, well-written parsers are straightforward to test.)

@thosakwe commented:
Take a look at graphql_server/introspection.dart, where top-level "fields" are actually getters for private fields that may or may not be null.
One possible solution is to support passing fields as a Iterable<GraphQLObjectField> Function() (or maybe as a different member, named computeFields()). In fact, this is probably the solution I'll end up adopting.

@micimize commented:
@deep-gaurav you can disable introspection, though naturally this not ideal:
  var graphQL = GraphQL(
    schema,
    introspect: false,
    customTypes: [
      episodeGraphQLType,
      starshipGraphQLType,
      droidGraphQLType,
      humanGraphQLType,
      reviewGraphQLType,
    ],
  );

@deep-gaurav commented:
I would like to add that trying to add object in field later results in Stack Overflow error during introspection
For Eg
  var A = objectType(
    'A',
    fields: [],
  );
  A.fields.add(field('A',A,resolve:(_,__)=>A));

Results in
[WARNING] angel_graphql: No `reflector` was passed to the Angel constructor, so reflection will not be available.
Features like controllers, constructor dependency injection, and `ioc` require reflection, and will not work without it.

For more, see the documentation:
https://docs.angel-dart.dev/guides/dependency-injection#enabling-dart-mirrors-or-other-reflection

Unhandled exception:
Stack Overflow
#0      List.addAll  (dart:core-patch/growable_array.dart:166:3)
#1      _fetchAllTypesFromObject
#2      _fetchAllTypesFromObject
#3      _fetchAllTypesFromObject
#4      _fetchAllTypesFromObject
#5      _fetchAllTypesFromObject
#6      _fetchAllTypesFromObject
#7      _fetchAllTypesFromObject
#8      _fetchAllTypesFromObject
#9      _fetchAllTypesFromObject
#10     _fetchAllTypesFromObject
#11     _fetchAllTypesFromObject
#12     _fetchAllTypesFromObject
#13     _fetchAllTypesFromObject
#14     _fetchAllTypesFromObject
#15     _fetchAllTypesFromObject
#16     _fetchAllTypesFromObject
#17     _fetchAllTypesFromObject
#18     _fetchAllTypesFromObject
#19     _fetchAllTypesFromObject
#20     _fetchAllTypesFromObject
#21     _fetchAllTypesFromObject
#22     _fetchAllTypesFromObject
#23     _fetchAllTypesFromObject
#24     _fetchAllTypesFromObject
#25     _fetchAllTypesFromObject
#26     _fetchAllTypesFromObject
#27     _fetchAllTypesFromObject
#28     _fetchAllTypesFromObject
#29     _fetchAllTypesFromObject
#30     _fetchAllTypesFromObject
#31     _fetchAllTypesFromObject
#32     _fetchAllTypesFromObject
#33     _fetchAllTypesFromObject
#34     _fetchAllTypesFromObject
#35     _fetchAllTypesFromObject
#36     _fetchAllTypesFromObject
#37     _fetchAllTypesFromObject
#38     _fetchAllTypesFromObject
#39     _fetchAllTypesFromObject
#40     _fetchAllTypesFromObject
#41     _fetchAllTypesFromObject
#42     _fetchAllTypesFromObject
#43     _fetchAllTypesFromObject
...
...
#8724   _fetchAllTypesFromObject
#8725   _fetchAllTypesFromObject
#8726   _fetchAllTypesFromObject
#8727   _fetchAllTypesFromObject
#8728   _fetchAllTypesFromObject
#8729   _fetchAllTypesFromObject
#8730   _fetchAllTypesFromObject
#8731   _fetchAllTypesFromObject
#8732   _fetchAllTypesFromObject
#8733   _fetchAllTypesFromObject
#8734   _fetchAllTypesFromObject
#8735   _fetchAllTypesFromObject
#8736   _fetchAllTypesFromObject
#8737   _fetchAllTypesFromObject
#8738   _fetchAllTypesFromObject
#8739   _fetchAllTypesFromObject
#8740   _fetchAllTypesFromObject
#8741   _fetchAllTypesFromObject
#8742   _fetchAllTypesFromObject
#8743   _fetchAllTypesFromObject
#8744   _fetchAllTypesFromObject
#8745   _fetchAllTypesFromObject
#8746   _fetchAllTypesFromObject
#8747   _fetchAllTypesFromObject
#8748   _fetchAllTypesFromObject
#8749   _fetchAllTypesFromObject
#8750   _fetchAllTypesFromObject
#8751   _fetchAllTypesFromObject
#8752   _fetchAllTypesFromObject
#8753   _fetchAllTypesFromObject
#8754   _fetchAllTypesFromObject
#8755   _fetchAllTypesFromObject
#8756   _fetchAllTypesFromObject
#8757   fetchAllTypes
#8758   reflectSchema
#8759   new GraphQL
#8760   main
#8761   _AsyncAwaitCompleter.start  (dart:async-patch/async_patch.dart:43:6)
#8762   main
#8763   _startIsolate.<anonymous closure>  (dart:isolate-patch/isolate_patch.dart:305:19)
#8764   _RawReceivePortImpl._handleMessage  (dart:isolate-patch/isolate_patch.dart:172:12)

Exited (255)

@deep-gaurav commented:
@micimize  as you said that isn't ideal and not solves problem in my case anyway, or atleast creates many if it solves one.
I encountered it while making a GraphQL library similar to type-graphql for Dart,
It's currently available on my repo dart_graphql and uses reflectors for annotations,
Having set introspection disabled in library is certainly not good :sweat_smile:

@micimize commented:
@deep-gaurav decided to tackle recursive type introspection in #40:
dependency_overrides:
  graphql_server:
    git:
      url: git://github.com/micimize/graphql.git
      ref: introspective-cycles
      path: graphql_server

It won't fix the code generation issuue though

@thosakwe commented:
Thanks for the great PR, going to work on getting that rolled out today.
On Sun, Jan 19, 2020 at 11:11 AM Michael Joseph Rosenthal <
<EMAIL_ADDRESS>wrote:

@deep-gaurav https://github.com/deep-gaurav decided to tackle recursive
type introspection in #40 https://github.com/angel-dart/graphql/pull/40:
dependency_overrides:
graphql_server:
git:
url: git://github.com/micimize/graphql.git
ref: introspective-cycles
path: graphql_server
It won't fix the code generation issuue though
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@ralcon commented:
Got the same problem while implementing the following example structure:
User
- blogPosts: [BlogPost]
     |
     ------------   BlogPost
                     - user: User
                     - comments: [Comment]
                           |
                           ----------- Comment
                                        - blogPost: BlogPost

Any progress?

@thosakwe commented:
I've merged the PR related to resolving cycles in introspection, as well as making field resolution asynchronous. Going to still keep this open, as cycle support is important.


Overrides wait for ssh delay time

This patch overrides the wait for ssh delay time. This will give
containers longer to start before failing on ssh.
This is to reduce gate failures on "wait for container ssh" which occour
when ansible fails to connect to a container after creation or restart.
Connects rcbops/u-suk-dev#279
(cherry picked from commit d4ae2b1ee2169a86b5e009e212d1ee39384c3eb3)
Conflicts:
rpcd/etc/openstack_deploy/user_osa_variables_defaults.yml

Looks good to me! :+1:

Nice and simple. 👍


E2EE with access token

++ This pull request is not merge ready ++
What the PR solves
This PR solves the following problem for me:

Create an account and obtain an access token for a bot via the admin API e.g.

$ curl -XPOST -d '{
    "identifier": { "type": "m.id.user", "user": "test-registration-bot" },
    "password": "mypassword",
    "type": "m.login.password",
    "device_id": "bot_testinstance"
}' 'https://synapse.example.com/_matrix/client/r0/login'

Activate E2EE for the bot

smbl_config = botlib.Config()
smbl_config.emoji_verify = True
smbl_config.ignore_unverified_devices = True

Try to run the bot fails. The problem is, that the smbl can not load the device_id from the store (as this does not yet exist) but also never updates it by asking the server (like in https://github.com/i10b/simplematrixbotlib/blob/master/simplematrixbotlib/api.py#L106). Therefore the device ID is not set and this happens.

Traceback (most recent call last):
  File "/home/moanos/software/matrix-registration-bot/matrix_registration_bot/bot.py", line 208, in <module>
    run_bot()
  File "/home/moanos/software/matrix-registration-bot/matrix_registration_bot/bot.py", line 200, in run_bot
    bot.run()
  File "/home/moanos/software/matrix-registration-bot/venv/lib/python3.10/site-packages/simplematrixbotlib/bot.py", line 88, in run
    asyncio.run(self.main())
  File "/usr/lib/python3.10/asyncio/runners.py", line 44, in run
    return loop.run_until_complete(main)
  File "/usr/lib/python3.10/asyncio/base_events.py", line 646, in run_until_complete
    return future.result()
  File "/home/moanos/software/matrix-registration-bot/venv/lib/python3.10/site-packages/simplematrixbotlib/bot.py", line 50, in main
    await self.api.login()
  File "/home/moanos/software/matrix-registration-bot/venv/lib/python3.10/site-packages/simplematrixbotlib/api.py", line 145, in login
    self.async_client.load_store()
  File "/home/moanos/software/matrix-registration-bot/venv/lib/python3.10/site-packages/nio/client/base_client.py", line 359, in load_store
    raise LocalProtocolError("Device id is not set")
nio.exceptions.LocalProtocolError: Device id is not set

Why is this not merge ready?
I think there still is an issue with device verification that is not solved by this PR. So this can also be treated as an issue :)

smbl is moving to codeberg. could you move this PR to https://codeberg.org/imbev/simplematrixbotlib/pulls ?


Fix crash on GUI entity removal with levels

Signed-off-by: Ashton Larkin<EMAIL_ADDRESS>🦟 Bug fix
Fixes https://github.com/ignitionrobotics/ign-gazebo/pull/856#pullrequestreview-686953945
Summary
After debugging the segfault pointed out in the link above, it seems like the levels system still tries to add components to entities even after they're removed (I'm not 100% certain if levels is to blame for this, but when I removed an entity in the shapes.sdf world, I did not see this behavior). This caused a segfault in #856 because components are not created if an entity doesn't exist, but the non existing entity (and component) were still marked as modified. This "mismatch" in data is problematic when EntityComponentManagerPrivate::CalculateStateThreadLoad is called in EntityComponentmanager::State, so, this PR adds a check when calling EntityComponentManager::CreateComponentImplementation to make sure that the entity exists.
While the bug fix here ended up being a simple one, I found something interesting when comparing #856 to the main branch. In the main branch, components are always created, regardless of whether an entity exists or not (I was also able to confirm this by testing the levels world that caused a segfault in #856 - as you can see, there's no checking for if the entity exists): https://github.com/ignitionrobotics/ign-gazebo/blob/c07b49c51caae6da1566c383d2b6ff91f4cb8097/src/EntityComponentManager.cc#L530-L566
So, on the main branch, we don't see this segfault since both 1) the component is created, and 2) the (non existent) entity and the component are marked as modified. This actually seems like incorrect behavior to me, and I believe that we should fix main (and other released versions as well) to prevent creating components for entities that do not exist. @iche033, what do you think?
Checklist

[x] Signed all commits for DCO
[x] Added tests
[x] Updated documentation (as needed)
[ ] Updated migration guide (as needed)
[ ] codecheck passed (See contributing)
[ ] All tests passed (See test coverage)
[ ] While waiting for a review on your PR, please help review another open pull request to support the maintainers

Note to maintainers: Remember to use Squash-Merge

I think the diff_drive plugin is creating various vel cmd components on every PreUpdate for entities that no longer exist hence causing the crash. We should probably fix the diff drive plugin too.
Maybe print an error in CreateComponentImplementation if users are trying to create components for entities that do not exist?

I believe that we should fix main (and other released versions as well) to prevent creating components for entities that do not exist. @iche033, what do you think?

yeah that sounds good to me.

Maybe print an error in CreateComponentImplementation if users are trying to create components for entities that do not exist?

Done in https://github.com/ignitionrobotics/ign-gazebo/pull/913/commits/fd46a05363eec3fd4e9290279628e11583fda43f

I have also updated the diff_drive plugin to skip removed entities in https://github.com/ignitionrobotics/ign-gazebo/pull/927. Once that change gets forward-ported to main, we should be able to merge this PR (I have started the forward-port process in https://github.com/ignitionrobotics/ign-gazebo/pull/933).

We should probably fix the diff drive plugin too.

@iche033, the diff drive plugin should now be fixed in all released versions (#927 has been forward-ported from Citadel to Fortress). Would you mind testing the bug you found in https://github.com/ignitionrobotics/ign-gazebo/pull/856#pullrequestreview-686953945 one last time before I merge it?

CI caught a compilation error and I can reproduce it locally

Oops, it looks like that came from https://github.com/ignitionrobotics/ign-gazebo/pull/913/commits/158a1af2efcf6be5b466e1b1f0acd74cfd2aac79 :sweat_smile: it should be fixed in https://github.com/ignitionrobotics/ign-gazebo/pull/913/commits/713c848b53818bed1de5bd5ccf3305a47d0776ad. I just tested the levels world, and removing entities seemed to work fine for me. Just as a note, I typically just build gazebo from source and then use the binary dependencies for PR testing, but I found that I also had to build ign-launch from source as well. I believe it's because of the changes that were made in include/ignition/gazebo/components/Factory.hh in #856.


Outdated dependencies.

In the composer.json file, Laravel version is 5.3, the latest version is 5.4.
AUTH-3374

We upgraded it to 5.5


MOTR-84 MOTR-62 MOTR-68 Frontend UI Enhancements

Key Changes:

Created<EMAIL_ADDRESS>email address and updated Contact page with placeholder content.
Added config to remove eslint warnings on global browser variables (e.g. window, document).
Added Co-Investigators to the Team page and updated its UI styling.
Updated Dashboard page UI layout and its test assertions due to the UI changes.
Refactored Landing page to improve its responsiveness in various viewport sizes.
Updated External Links page UI and styling.
Minor UI and styling updates throughout other pages as well as navbar/sidebar for visual consistency.
Updated respective unit tests and Storybook stories due to various UI changes.

Merged MOTR-84 MOTR-62 MOTR-68


Cannot auto-install Flex SDK with version 1.3.0

For some reason I'm getting "The Flex/AIR home location isn't specified" on one computer. I get it even on sample auto-install project after changing gradlefx version to 1.3.0 (btw 1.2.0 works right fine). The strange thing it works on different mac.

This is probably related to https://github.com/GradleFx/GradleFx/commit/9974143c3cc0486df8b73769c85c5ac5c4b1d71c
I'll see if I can get a fix in tonight

Looking forward, thanks!

fixed with https://github.com/GradleFx/GradleFx/commit/8d2be63d5bdc79871f90fbfc6649ff6ccf5558c1
available now on our snapshot repo as version 1.3.1-SNAPSHOT.
I'll be making this a release asap given the criticality of this bug.

Best support ever! I will check it first thing tomorrow

How did it go?

works great, thanks


Fix glibc specific conditional for Mac OS/X

MacOS seems to define GLIBC but not __GLIBC_PREREQ.
The issue was reported against this commit.  It follows on from the changes in #5231

An alternative solution would be to conditionally define __GLIBC_PREREQ:
#ifndef __GLIBC_PREREQ
#define __GLIBC_PREREQ(a, b) (0)
#endif

somewhere.

@lodenos this might help.

Thanks @richsalz
Merged

BTW, referred comment asks "work?", this conversation says "might help". You know what? It doesn't work. In fact it doesn't work on any system [that attempts to compile this] but Linux.

Which systems doesn't this work for?
Our CI builds for Windows & Solaris built okay.  AIXand HP/UX didn't for a different reason.
That conditional is getting complex.  Grouping the _POSIX_C_SOURCE checks makes sense and was missed on the previous commit.  Would the alternative of defining __GLIBC_PREREQ if it isn't already defined help?  I could also add a comment about what it is trying to achieve.

Which systems doesn't this work for?

Once again, any that tries to compile it and is not Linux, such as MacOS X, *BSD, OSF, IRIX... VMS ought to fail too...

In what way isn't this conditional working?  I'm confused.

Just remove __sun condition and see for yourself on Solaris.

Thanks, got it now.  PR coming.

Which systems doesn't this work for?

it does not work for MacOS El Capitan, Sierra, and High Sierra. See #5290.


Progressbar type property updates conflicts with ngAnimate causing no animation

When ngAnimate is imported updating a progress bar value and type at the same time results in the progress bar not animating.  Here is an example
http://plnkr.co/edit/uZr9XqsUgyT4sjDTKhLS?p=preview
It seems the best way to fix this is by this by removing ngCass from the bar templates and just update the bar element class directly in the directive.  I will create the pull request if this seems like a reasonable approach.

@chrisirhc what do I need to do to get this out of purgatory?  :smiley:   This is still an issue with 0.12.0

It looks like this was a bug in AngularJS 1.2 . This is now fixed if you upgrade to AngularJS 1.3 . Since our next release (0.13) moves support to AngularJS 1.3 and above, this issue won't be valid once the 0.13 is released.
Reference Plunker with AngularJS 1.3: http://plnkr.co/edit/VNXiMsLlmqAhOwgy7Agt?p=preview
For AngularJS 1.2 users, an alternative fix is to insert the following style in your stylesheet:
.progress-bar.ng-animate {
  -webkit-transition: 0;
  transition: 0;
}

Reference Plunker with CSS fix: http://plnkr.co/edit/SAb7P6jcDtcvALL9Ll00?p=preview

This issue seems to be back with the newer Angular versions ( tried 1.4.3 & 1.4.8)
See Plunker


Write supervisord log to /var/log

Currently it's written to /tmp which gets wiped on reboot

This issue should go into senic-os

https://github.com/getsenic/senic-os/issues/34