Issue with training SDXL Textual Inversion in multi GPU environment

I've been trying out textual inversion for SDXL and while it seems to run fine in single GPU enviroment, trying to train in dual GPU enviroment throws a AttributeErrorAttributeError: : 'DistributedDataParallel' object has no attribute 'text_model''DistributedDataParallel' object has no attribute 'text_model' error, even with the --ddp_gradient_as_bucket_view and --ddp_bucket_view
Full stack trace as below:
Traceback (most recent call last):
  File "/kaggle/temp/sd-scripts/sdxl_train_textual_inversion.py", line 141, in <module>
  File "/kaggle/temp/sd-scripts/sdxl_train_textual_inversion.py", line 141, in <module>
    trainer.train(args)
  File "/kaggle/temp/sd-scripts/train_textual_inversion.py", line 444, in train
    trainer.train(args)
  File "/kaggle/temp/sd-scripts/train_textual_inversion.py", line 444, in train
    text_encoder.text_model.encoder.requires_grad_(False)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1614, in __getattr__
    text_encoder.text_model.encoder.requires_grad_(False)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1614, in __getattr__
        raise AttributeError("'{}' object has no attribute '{}'".format(raise AttributeError("'{}' object has no attribute '{}'".format(

AttributeErrorAttributeError: : 'DistributedDataParallel' object has no attribute 'text_model''DistributedDataParallel' object has no attribute 'text_model'

WARNING:torch.distributed.elastic.multiprocessing.api:Sending process 749 closing signal SIGTERM
ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 0 (pid: 748) of binary: /kaggle/temp/venv/bin/python
Traceback (most recent call last):
  File "/kaggle/temp/venv/bin/accelerate", line 8, in <module>
    sys.exit(main())
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/accelerate_cli.py", line 47, in main
    args.func(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/launch.py", line 977, in launch_command
    multi_gpu_launcher(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/launch.py", line 646, in multi_gpu_launcher
    distrib_run.run(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/run.py", line 785, in run
    elastic_launch(
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 134, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 250, in launch_agent
    raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
============================================================
sdxl_train_textual_inversion.py FAILED
------------------------------------------------------------
Failures:
  <NO_OTHER_FAILURES>
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2023-12-24_05:40:05
  host      : 10a2396fa887
  rank      : 0 (local_rank: 0)
  exitcode  : 1 (pid: 748)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
============================================================

Hey @kohya-ss,
Tried out the dev branch and it's able to start training, but I ran into a problem while generating sample images. Stragely, it looks like it might be related to this issue with generating samples images while training LoRAs as well.
Traceback (most recent call last):
  File "/kaggle/temp/sd-scripts/sdxl_train_textual_inversion.py", line 141, in <module>
    trainer.train(args)
  File "/kaggle/temp/sd-scripts/train_textual_inversion.py", line 533, in train
    self.sample_images(
  File "/kaggle/temp/sd-scripts/sdxl_train_textual_inversion.py", line 89, in sample_images
    sdxl_train_util.sample_images(
  File "/kaggle/temp/sd-scripts/library/sdxl_train_util.py", line 367, in sample_images
    return train_util.sample_images_common(SdxlStableDiffusionLongPromptWeightingPipeline, *args, **kwargs)
  File "/kaggle/temp/sd-scripts/library/train_util.py", line 4758, in sample_images_common
    image = pipeline.latents_to_image(latents)[0]
  File "/kaggle/temp/sd-scripts/library/sdxl_lpw_stable_diffusion.py", line 1035, in latents_to_image
    image = self.decode_latents(latents.to(self.vae.dtype))
  File "/kaggle/temp/sd-scripts/library/sdxl_lpw_stable_diffusion.py", line 714, in decode_latents
    image = self.vae.decode(latents.to(self.vae.dtype)).sample
  File "/kaggle/temp/venv/lib/python3.10/site-packages/diffusers/utils/accelerate_utils.py", line 46, in wrapper
    return method(self, *args, **kwargs)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/diffusers/models/autoencoder_kl.py", line 286, in decode
    decoded = self._decode(z).sample
  File "/kaggle/temp/venv/lib/python3.10/site-packages/diffusers/models/autoencoder_kl.py", line 273, in _decode
    dec = self.decoder(z)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/diffusers/models/vae.py", line 272, in forward
    sample = up_block(sample, latent_embeds)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/diffusers/models/unet_2d_blocks.py", line 2375, in forward
    hidden_states = upsampler(hidden_states)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/diffusers/models/resnet.py", line 170, in forward
    hidden_states = self.conv(hidden_states, scale)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/diffusers/models/lora.py", line 163, in forward
    return F.conv2d(
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 1024.00 MiB (GPU 0; 14.76 GiB total capacity; 12.29 GiB already allocated; 905.75 MiB free; 12.82 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
steps:   0%|                                            | 0/120 [00:35<?, ?it/s]
WARNING:torch.distributed.elastic.multiprocessing.api:Sending process 748 closing signal SIGTERM
ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 0 (pid: 747) of binary: /kaggle/temp/venv/bin/python
Traceback (most recent call last):
  File "/kaggle/temp/venv/bin/accelerate", line 8, in <module>
    sys.exit(main())
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/accelerate_cli.py", line 47, in main
    args.func(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/launch.py", line 977, in launch_command
    multi_gpu_launcher(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/launch.py", line 646, in multi_gpu_launcher
    distrib_run.run(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/run.py", line 785, in run
    elastic_launch(
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 134, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 250, in launch_agent
    raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
============================================================
sdxl_train_textual_inversion.py FAILED
------------------------------------------------------------
Failures:
  <NO_OTHER_FAILURES>
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2023-12-24_15:09:43
  host      : ba06d8ffffab
  rank      : 0 (local_rank: 0)
  exitcode  : 1 (pid: 747)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
============================================================

Hrm.. Decided to give up on sample image generation during training for now, but have been running into this issue instead at the start of training
steps:   0%|                                           | 0/6840 [00:00<?, ?it/s]
epoch 1/6
Traceback (most recent call last):
  File "/kaggle/temp/sd-scripts/sdxl_train_textual_inversion.py", line 141, in <module>
    trainer.train(args)
  File "/kaggle/temp/sd-scripts/train_textual_inversion.py", line 619, in train
    accelerator.unwrap_model(text_encoder).get_input_embeddings().weight[
RuntimeError: Index put requires the source and destination dtypes match, got Half for the destination and Float for the source.
Traceback (most recent call last):
  File "/kaggle/temp/sd-scripts/sdxl_train_textual_inversion.py", line 141, in <module>
    trainer.train(args)
  File "/kaggle/temp/sd-scripts/train_textual_inversion.py", line 619, in train
    accelerator.unwrap_model(text_encoder).get_input_embeddings().weight[
RuntimeError: Index put requires the source and destination dtypes match, got Half for the destination and Float for the source.
steps:   0%|                                           | 0/6840 [00:13<?, ?it/s]
WARNING:torch.distributed.elastic.multiprocessing.api:Sending process 1544 closing signal SIGTERM
ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 1 (pid: 1545) of binary: /kaggle/temp/venv/bin/python
Traceback (most recent call last):
  File "/kaggle/temp/venv/bin/accelerate", line 8, in <module>
    sys.exit(main())
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/accelerate_cli.py", line 47, in main
    args.func(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/launch.py", line 977, in launch_command
    multi_gpu_launcher(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/launch.py", line 646, in multi_gpu_launcher
    distrib_run.run(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/run.py", line 785, in run
    elastic_launch(
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 134, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 250, in launch_agent
    raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
============================================================
sdxl_train_textual_inversion.py FAILED
------------------------------------------------------------
Failures:
  <NO_OTHER_FAILURES>
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2023-12-30_16:43:49
  host      : 56716c7ca920
  rank      : 1 (local_rank: 1)
  exitcode  : 1 (pid: 1545)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
============================================================

No worries, hope it was because you were enojoying the holidays with friends and families. I'll test it as soon as I can.

Got a new error this time
ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 0 (pid: 735) of binary: /kaggle/temp/venv/bin/python
Traceback (most recent call last):
  File "/kaggle/temp/venv/bin/accelerate", line 8, in <module>
    sys.exit(main())
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/accelerate_cli.py", line 47, in main
    args.func(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/launch.py", line 1008, in launch_command
    multi_gpu_launcher(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/launch.py", line 666, in multi_gpu_launcher
    distrib_run.run(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/run.py", line 785, in run
    elastic_launch(
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 134, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 250, in launch_agent
    raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
============================================================
sdxl_train_textual_inversion.py FAILED
------------------------------------------------------------
Failures:
[1]:
  time      : 2024-01-06_03:29:24
  host      : 3f8eb37d2946
  rank      : 1 (local_rank: 1)
  exitcode  : 1 (pid: 736)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2024-01-06_03:29:24
  host      : 3f8eb37d2946
  rank      : 0 (local_rank: 0)
  exitcode  : 1 (pid: 735)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
============================================================

Oops, sorry, Thought I had already included the full traceback
The params:
accelerate launch --config_file="/kaggle/temp/sd-scripts/accelerate_config/config.yaml" --num_cpu_threads_per_process=1  sdxl_train_textual_inversion.py --sample_prompts="/kaggle/temp/LoRA/train_data/json/sample_prompt_ti.toml" --no_half_vae --shuffle_caption --ddp_gradient_as_bucket_view --ddp_static_graph --pretrained_model_name_or_path="/kaggle/input/stable-diffusion-xl/pytorch/base-1-0/1" --vae="/kaggle/temp/vae/sdxl_vae.safetensors" --output_dir="/kaggle/temp/output/TCL_Waifu_TI" --output_name="TCL_Waifu_TI" --token_string="TCL_Waifu" --init_word="woman" --num_vectors_per_token=10 --save_precision="fp16" --save_every_n_epochs=1 --train_batch_size=4 --max_token_length=225 --mem_eff_attn --sdpa --max_train_epochs=6 --gradient_checkpointing --gradient_accumulation_steps=1 --mixed_precision="fp16" --cache_latents_to_disk --prior_loss_weight=1.0 --full_fp16 --sample_every_n_epochs=1 --sample_sampler="k_euler_a" --save_model_as="safetensors" --huggingface_token="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" --optimizer_type="AdaFactor" --learning_rate=1e-06 --max_grad_norm=0 --lr_scheduler="constant" --lr_warmup_steps=0 --dataset_config="/kaggle/temp/LoRA/train_data/json/dataset_config_TI.toml"
The traceback
Traceback (most recent call last):
  File "/kaggle/temp/sd-scripts/sdxl_train_textual_inversion.py", line 141, in <module>
    trainer.train(args)
  File "/kaggle/temp/sd-scripts/train_textual_inversion.py", line 605, in train
    accelerator.backward(loss)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/accelerator.py", line 1903, in backward
    self.scaler.scale(loss).backward(**kwargs)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/_tensor.py", line 487, in backward
    torch.autograd.backward(
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/autograd/__init__.py", line 200, in backward
    Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
SystemError: <built-in method run_backward of torch._C._EngineBase object at 0x7a102a23f410> returned NULL without setting an exception
Traceback (most recent call last):
  File "/kaggle/temp/sd-scripts/sdxl_train_textual_inversion.py", line 141, in <module>
    trainer.train(args)
  File "/kaggle/temp/sd-scripts/train_textual_inversion.py", line 605, in train
    accelerator.backward(loss)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/accelerator.py", line 1903, in backward
    self.scaler.scale(loss).backward(**kwargs)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/_tensor.py", line 487, in backward
    torch.autograd.backward(
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/autograd/__init__.py", line 200, in backward
    Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
SystemError: <built-in method run_backward of torch._C._EngineBase object at 0x79c4683c3410> returned NULL without setting an exception
steps:   0%|                                           | 0/1728 [00:16<?, ?it/s]
ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 0 (pid: 735) of binary: /kaggle/temp/venv/bin/python
Traceback (most recent call last):
  File "/kaggle/temp/venv/bin/accelerate", line 8, in <module>
    sys.exit(main())
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/accelerate_cli.py", line 47, in main
    args.func(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/launch.py", line 1008, in launch_command
    multi_gpu_launcher(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/launch.py", line 666, in multi_gpu_launcher
    distrib_run.run(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/run.py", line 785, in run
    elastic_launch(
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 134, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 250, in launch_agent
    raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
============================================================
sdxl_train_textual_inversion.py FAILED
------------------------------------------------------------
Failures:
[1]:
  time      : 2024-01-06_03:29:24
  host      : 3f8eb37d2946
  rank      : 1 (local_rank: 1)
  exitcode  : 1 (pid: 736)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2024-01-06_03:29:24
  host      : 3f8eb37d2946
  rank      : 0 (local_rank: 0)
  exitcode  : 1 (pid: 735)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
============================================================

Interesting. Even running the current Torch 2.1.2 gives the identical error.
One... interesting clue is running with only the --ddp_gradient_as_bucket_view flag seems to allow it to complete one step before failing. Running without both needs further testing at this point, as was able to complete training once, but might be throwing errors currently
With --ddp_gradient_as_bucket_view and --ddp_static_graph
Traceback (most recent call last):
  File "/kaggle/temp/sd-scripts/sdxl_train_textual_inversion.py", line 141, in <module>
    trainer.train(args)
  File "/kaggle/temp/sd-scripts/train_textual_inversion.py", line 607, in train
    accelerator.backward(loss)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/accelerator.py", line 1903, in backward
    self.scaler.scale(loss).backward(**kwargs)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/_tensor.py", line 492, in backward
    torch.autograd.backward(
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/autograd/__init__.py", line 251, in backward
    Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
SystemError: <built-in method run_backward of torch._C._EngineBase object at 0x7cbc30f73850> returned NULL without setting an exception
steps:   0%|                                            | 0/462 [00:16<?, ?it/s]
Traceback (most recent call last):
  File "/kaggle/temp/sd-scripts/sdxl_train_textual_inversion.py", line 141, in <module>
    trainer.train(args)
  File "/kaggle/temp/sd-scripts/train_textual_inversion.py", line 607, in train
    accelerator.backward(loss)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/accelerator.py", line 1903, in backward
    self.scaler.scale(loss).backward(**kwargs)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/_tensor.py", line 492, in backward
    torch.autograd.backward(
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/autograd/__init__.py", line 251, in backward
    Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
SystemError: <built-in method run_backward of torch._C._EngineBase object at 0x7bf81259b850> returned NULL without setting an exception
[2024-01-14 13:56:22,964] torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: 1) local_rank: 0 (pid: 839) of binary: /kaggle/temp/venv/bin/python
Traceback (most recent call last):
  File "/kaggle/temp/venv/bin/accelerate", line 8, in <module>
    sys.exit(main())
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/accelerate_cli.py", line 47, in main
    args.func(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/launch.py", line 1008, in launch_command
    multi_gpu_launcher(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/launch.py", line 666, in multi_gpu_launcher
    distrib_run.run(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/run.py", line 797, in run
    elastic_launch(
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 134, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 264, in launch_agent
    raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
============================================================
sdxl_train_textual_inversion.py FAILED
------------------------------------------------------------
Failures:
[1]:
  time      : 2024-01-14_13:56:22
  host      : e9d4d6462f9d
  rank      : 1 (local_rank: 1)
  exitcode  : 1 (pid: 840)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2024-01-14_13:56:22
  host      : e9d4d6462f9d
  rank      : 0 (local_rank: 0)
  exitcode  : 1 (pid: 839)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
============================================================
ERROR: ld.so: object '/kaggle/temp/libtcmalloc_minimal.so.4' from LD_PRELOAD cannot be preloaded (file too short): ignored.
ERROR: ld.so: object '/kaggle/temp/libtcmalloc_minimal.so.4' from LD_PRELOAD cannot be preloaded (file too short): ignored.
ERROR: ld.so: object '/kaggle/temp/libtcmalloc_minimal.so.4' from LD_PRELOAD cannot be preloaded (file too short): ignored.
Name: torch
Version: 2.1.2
Summary: Tensors and Dynamic neural networks in Python with strong GPU acceleration
Home-page: https://pytorch.org/
Author: PyTorch Team
Author-email<EMAIL_ADDRESS>License: BSD-3
Location: /kaggle/temp/venv/lib/python3.10/site-packages
Requires: filelock, fsspec, jinja2, networkx, nvidia-cublas-cu12, nvidia-cuda-cupti-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-runtime-cu12, nvidia-cudnn-cu12, nvidia-cufft-cu12, nvidia-curand-cu12, nvidia-cusolver-cu12, nvidia-cusparse-cu12, nvidia-nccl-cu12, nvidia-nvtx-cu12, sympy, triton, typing-extensions
Required-by: accelerate, open-clip-torch, pytorch-lightning, timm, torchmetrics, torchvision

With --ddp_static_graph only
Traceback (most recent call last):
  File "/kaggle/temp/sd-scripts/sdxl_train_textual_inversion.py", line 141, in <module>
    trainer.train(args)
  File "/kaggle/temp/sd-scripts/train_textual_inversion.py", line 607, in train
    accelerator.backward(loss)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/accelerator.py", line 1903, in backward
    self.scaler.scale(loss).backward(**kwargs)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/_tensor.py", line 492, in backward
    torch.autograd.backward(
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/autograd/__init__.py", line 251, in backward
    Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
SystemError: <built-in method run_backward of torch._C._EngineBase object at 0x7aff5729f850> returned NULL without setting an exception
Traceback (most recent call last):
  File "/kaggle/temp/sd-scripts/sdxl_train_textual_inversion.py", line 141, in <module>
    trainer.train(args)
  File "/kaggle/temp/sd-scripts/train_textual_inversion.py", line 607, in train
    accelerator.backward(loss)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/accelerator.py", line 1903, in backward
    self.scaler.scale(loss).backward(**kwargs)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/_tensor.py", line 492, in backward
    torch.autograd.backward(
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/autograd/__init__.py", line 251, in backward
    Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
SystemError: <built-in method run_backward of torch._C._EngineBase object at 0x7964d78ff850> returned NULL without setting an exception
steps:   0%|                                            | 0/462 [00:17<?, ?it/s]
[2024-01-14 14:14:03,240] torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: 1) local_rank: 0 (pid: 1126) of binary: /kaggle/temp/venv/bin/python
Traceback (most recent call last):
  File "/kaggle/temp/venv/bin/accelerate", line 8, in <module>
    sys.exit(main())
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/accelerate_cli.py", line 47, in main
    args.func(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/launch.py", line 1008, in launch_command
    multi_gpu_launcher(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/launch.py", line 666, in multi_gpu_launcher
    distrib_run.run(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/run.py", line 797, in run
    elastic_launch(
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 134, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 264, in launch_agent
    raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
============================================================
sdxl_train_textual_inversion.py FAILED
------------------------------------------------------------
Failures:
[1]:
  time      : 2024-01-14_14:14:03
  host      : e9d4d6462f9d
  rank      : 1 (local_rank: 1)
  exitcode  : 1 (pid: 1127)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2024-01-14_14:14:03
  host      : e9d4d6462f9d
  rank      : 0 (local_rank: 0)
  exitcode  : 1 (pid: 1126)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
============================================================
ERROR: ld.so: object '/kaggle/temp/libtcmalloc_minimal.so.4' from LD_PRELOAD cannot be preloaded (file too short): ignored.
ERROR: ld.so: object '/kaggle/temp/libtcmalloc_minimal.so.4' from LD_PRELOAD cannot be preloaded (file too short): ignored.
ERROR: ld.so: object '/kaggle/temp/libtcmalloc_minimal.so.4' from LD_PRELOAD cannot be preloaded (file too short): ignored.
Name: torch
Version: 2.1.2
Summary: Tensors and Dynamic neural networks in Python with strong GPU acceleration
Home-page: https://pytorch.org/
Author: PyTorch Team
Author-email<EMAIL_ADDRESS>License: BSD-3
Location: /kaggle/temp/venv/lib/python3.10/site-packages
Requires: filelock, fsspec, jinja2, networkx, nvidia-cublas-cu12, nvidia-cuda-cupti-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-runtime-cu12, nvidia-cudnn-cu12, nvidia-cufft-cu12, nvidia-curand-cu12, nvidia-cusolver-cu12, nvidia-cusparse-cu12, nvidia-nccl-cu12, nvidia-nvtx-cu12, sympy, triton, typing-extensions
Required-by: accelerate, open-clip-torch, pytorch-lightning, timm, torchmetrics, torchvision

With --ddp_gradient_as_bucket_view only
steps:   0%|                     | 1/462 [00:18<2:19:27, 18.15s/it, loss=0.0952]Traceback (most recent call last):
  File "/kaggle/temp/sd-scripts/sdxl_train_textual_inversion.py", line 141, in <module>
    trainer.train(args)
  File "/kaggle/temp/sd-scripts/train_textual_inversion.py", line 607, in train
    accelerator.backward(loss)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/accelerator.py", line 1903, in backward
    self.scaler.scale(loss).backward(**kwargs)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/_tensor.py", line 492, in backward
    torch.autograd.backward(
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/autograd/__init__.py", line 251, in backward
    Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/autograd/function.py", line 288, in apply
    return user_fn(self, *args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/utils/checkpoint.py", line 288, in backward
    torch.autograd.backward(outputs_with_grad, args_with_grad)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/autograd/__init__.py", line 251, in backward
    Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 300.00 MiB. GPU 1 has a total capacty of 14.75 GiB of which 173.06 MiB is free. Process 15213 has 14.58 GiB memory in use. Of the allocated memory 13.18 GiB is allocated by PyTorch, and 1.15 GiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
[2024-01-14 14:07:50,667] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1048 closing signal SIGTERM
[2024-01-14 14:07:50,831] torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: 1) local_rank: 1 (pid: 1049) of binary: /kaggle/temp/venv/bin/python
Traceback (most recent call last):
  File "/kaggle/temp/venv/bin/accelerate", line 8, in <module>
    sys.exit(main())
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/accelerate_cli.py", line 47, in main
    args.func(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/launch.py", line 1008, in launch_command
    multi_gpu_launcher(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/launch.py", line 666, in multi_gpu_launcher
    distrib_run.run(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/run.py", line 797, in run
    elastic_launch(
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 134, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 264, in launch_agent
    raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
============================================================
sdxl_train_textual_inversion.py FAILED
------------------------------------------------------------
Failures:
  <NO_OTHER_FAILURES>
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2024-01-14_14:07:50
  host      : e9d4d6462f9d
  rank      : 1 (local_rank: 1)
  exitcode  : 1 (pid: 1049)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
============================================================
ERROR: ld.so: object '/kaggle/temp/libtcmalloc_minimal.so.4' from LD_PRELOAD cannot be preloaded (file too short): ignored.
ERROR: ld.so: object '/kaggle/temp/libtcmalloc_minimal.so.4' from LD_PRELOAD cannot be preloaded (file too short): ignored.
ERROR: ld.so: object '/kaggle/temp/libtcmalloc_minimal.so.4' from LD_PRELOAD cannot be preloaded (file too short): ignored.
Name: torch
Version: 2.1.2
Summary: Tensors and Dynamic neural networks in Python with strong GPU acceleration
Home-page: https://pytorch.org/
Author: PyTorch Team
Author-email<EMAIL_ADDRESS>License: BSD-3
Location: /kaggle/temp/venv/lib/python3.10/site-packages
Requires: filelock, fsspec, jinja2, networkx, nvidia-cublas-cu12, nvidia-cuda-cupti-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-runtime-cu12, nvidia-cudnn-cu12, nvidia-cufft-cu12, nvidia-curand-cu12, nvidia-cusolver-cu12, nvidia-cusparse-cu12, nvidia-nccl-cu12, nvidia-nvtx-cu12, sympy, triton, typing-extensions
Required-by: accelerate, open-clip-torch, pytorch-lightning, timm, torchmetrics, torchvision

With --ddp_gradient_as_bucket_view only, the error seems to be caused by OOM.

torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 300.00 MiB. GPU 1 has a total capacty of 14.75 GiB of which 173.06 MiB is free. Process 15213 has 14.58 GiB memory in use. Of the allocated memory 13.18 GiB is allocated by PyTorch, and 1.15 GiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF

Could you please decrease the batch size?

When trying this, training seems to mostly be successful, however, at the end, when saving state, it seems to throw another error.
epoch 3/3
steps: 100%|██████████████████████| 165/165 [47:47<00:00, 17.38s/it, loss=0.126]
saving last state.
Traceback (most recent call last):
  File "/kaggle/temp/sd-scripts/sdxl_train_textual_inversion.py", line 141, in <module>
    trainer.train(args)
  File "/kaggle/temp/sd-scripts/train_textual_inversion.py", line 739, in train
    updated_embs = text_encoder.get_input_embeddings().weight[token_ids].data.detach().clone()
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1695, in __getattr__
    raise AttributeError(f"'{type(self).__name__}' object has no attribute '{name}'")
AttributeError: 'DistributedDataParallel' object has no attribute 'get_input_embeddings'

saving checkpoint: /kaggle/temp/output/TCLohwx_TI/TCLohwx_TI.safetensors
model saved.
steps: 100%|██████████████████████| 165/165 [48:35<00:00, 17.67s/it, loss=0.126]
[2024-01-20 13:26:15,105] torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: 1) local_rank: 1 (pid: 806) of binary: /kaggle/temp/venv/bin/python
Traceback (most recent call last):
  File "/kaggle/temp/venv/bin/accelerate", line 8, in <module>
    sys.exit(main())
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/accelerate_cli.py", line 47, in main
    args.func(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/launch.py", line 1008, in launch_command
    multi_gpu_launcher(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/accelerate/commands/launch.py", line 666, in multi_gpu_launcher
    distrib_run.run(args)
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/run.py", line 797, in run
    elastic_launch(
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 134, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/kaggle/temp/venv/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 264, in launch_agent
    raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
============================================================
sdxl_train_textual_inversion.py FAILED
------------------------------------------------------------
Failures:
  <NO_OTHER_FAILURES>
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2024-01-20_13:26:15
  host      : 73fc472f4265
  rank      : 1 (local_rank: 1)
  exitcode  : 1 (pid: 806)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
============================================================
Name: torch
Version: 2.1.2
Summary: Tensors and Dynamic neural networks in Python with strong GPU acceleration
Home-page: https://pytorch.org/
Author: PyTorch Team
Author-email<EMAIL_ADDRESS>License: BSD-3
Location: /kaggle/temp/venv/lib/python3.10/site-packages
Requires: filelock, fsspec, jinja2, networkx, nvidia-cublas-cu12, nvidia-cuda-cupti-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-runtime-cu12, nvidia-cudnn-cu12, nvidia-cufft-cu12, nvidia-curand-cu12, nvidia-cusolver-cu12, nvidia-cusparse-cu12, nvidia-nccl-cu12, nvidia-nvtx-cu12, sympy, triton, typing-extensions
Required-by: accelerate, open-clip-torch, pytorch-lightning, timm, torchmetrics, torchvision

The saving issue has been fixed and able to save now, although I... am puzzled with the training results I'm getting. Doing more experiments to test with and without --ddp_gradient_as_bucket_view to see how it's affecting the training results.
Also, while I do not understand the behaivour, the issue I've had with random VRAM OOMs I've been experiencing during image sampling on multiple GPU enviroments is because there's spike in VRAM usage when the latents are being converted into images in the sample image generation using the VAE. I'm not quite sure as what the root cause is as it seems to be somewhere in the Torch libraries, but basically, it seems that the VRAM is reserved, although in theory is available, causing it to OOM.
I've been able to workaround this issue by inserting a call to torch.cuda.empty_cache() after the latents have been generated, and before the latents are converted into images.


Fix: Update equation that gov / anc ust lp provide / ust balance

Codecov Report

Merging #88 (ec1d146) into master (2270309) will not change coverage.
The diff coverage is n/a.

@@          Coverage Diff           @@
##           master     #88   +/-   ##
======================================
  Coverage    5.93%   5.93%
======================================
  Files         437     437
  Lines        8673    8673
  Branches     2319    2319
======================================
  Hits          515     515
  Misses       8158    8158

Impacted Files
Coverage Δ

app/src/pages/gov/components/AncUstLpProvide.tsx
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add Llama 3.2 support

### Tasks
- [ ] https://github.com/pytorch/torchtitan/pull/589
- [ ] https://github.com/pytorch/torchtitan/pull/626
- [ ] Numerically stable validation for ViT
- [ ] Numerically stable validation for decoder
- [ ] Enable dataloading for dataset OBELICS and update the tokenizer
- [ ] enabling loading the pretrained checkpoints for ViT and non-crossed layer in decoder
- [ ] Training receipe for MM model
- [ ] Perf and numerically stability for 1D (FSDP) for MM model

Hi @tianyu-l, is anyone working on the Enable dataloading for dataset OBELICS and update the tokenizer task? Let me know if I could contribute to this task!

Hi @TJ-Solergibert, it'd be great if you can help on that. I can help discuss and review the code / design / etc. You may create a separate issue (and add the link above) to track progress if needed.

@TJ-Solergibert you can add me as the code reviewer as well.


Fix webhooks overview overflow bug

Linear: https://linear.app/buildkite/issue/ONB-16/
Docs Webhooks Overview page content overflows to the right. This introduces a horizontal scrollbar where one is not expected or desired. Not identified on any other pages.
Impacting all viewport widths. Present with and without new nav banner.

Tracked root cause to the second HTTP headers table which has a long string of example text in it: timestamp=1619071700,signature=30222eb518dc3fb61ec9e64dd78d163f62cb134a6ldb768f1d40e0edbn6e43f0 This doesn't have any whitespace in it and therefore isn't wrapping nicely
Tried a few options to fix, including adding spaces to the string (fixed the issue but traded off accuracy of the documentation) and trying unsuccessfully to get the text to wrap through various means. Landed on adding the option to make a table "fixed width". This forces the text to wrap.
This won't fix overflow in the future but gives us a tool to use when we encounter it without changing overall table design across docs, clipping content or reducing accuracy of documentation.
Fixed version:

Also in this PR:

Minor refactor to group media queries for Docs__article together.
Removed redundant CSS in @media (min-width: $screen-lg)
Added Webhooks to API section of homepage
Added fixed-width to styleguide

Thanks all. Updated @plaindocs with both of your suggestions 👍 re-requested review


chore: upgrade dependencies

The current dependencies are behind a few major versions, so I've bumped them to the most recent versions available (as of today). In addition, electron doesn't support apple silicon until version 11, so that was one of the main motivations for upgrading.

I appreciate the pull request, but for security reasons, we don't accept dependency updates from non-members of the Electron org or Dependabot.

@malept Understandable, would it make sense to open up a new issue requesting a dependency bump for electron to support apple silicon projects? The current version (9.4.0) is 3 major versions behind and apple silicon support wasn't added until >=11. Appreciate the response!

This should do it: https://github.com/electron/electron-quick-start-typescript/pull/55

@malept thank you for your time!


[Question] Supported React Native Versions

This library seems really great!
Up to which version of React Native is it supported? Does it work with versions 0.68 or 0.71 as well?

Thanks!
Nitro requires react-native 0.75 or newer. See Minimum Requirements


Bugfix/all variables injected when function has no variables

Fix bug where function decorated as task receives all variables that are available to the task causing an unexpected keyword argument error. Referenced in #337.
The bug originates from the zeebe grpc API for ActivateJobs. If no variables are passed to fetchVariable , it fetches all available variables.
Changes

Add a include_variables flag to private function _create_job_from_raw_job. If flag is set to False, retrieved variables will be ignored.
The function is called in one place, which now calls it with bool(variables_to_fetch) as the flag's value. None or an empty list will cause no variables to be injected to the Job object, so they will never end up getting passed to the function.

API Updates
New Features (required)

Support for functions with no arguments as task functions

Checklist

[ ] Unit tests
[ ] Documentation

References
ActivateJobs API
Fixes #337

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.

Looks good, but please add a simple unit test so that this bug doesn't reproduce.

Looks good, but please add a simple unit test so that this bug doesn't reproduce.

Done.
Something to have in mind that someone mentioned to me - this pr will remove the ability to intentionally get all parameters by setting the variables_to_fetch to [] or None.
I don;t think that's a problem or intended functionality, but just making sure

Waiting for re-review :)

fixed in #404


chef-server 12 on RHEL7: chef-server-ctl reconfigure hangs when configuring embedded rabbitmq

Version
chef-server-core-12.0.1-1.x86_64.rpm
Downloaded from https://web-dl.packagecloud.io/chef/stable/packages/el/6/chef-server-core-12.0.1-1.x86_64.rpm
Environment
RHEL 7.0 x86_64
Summary
When I tried to install and configure a chef-server 12 on RHEL7, I got stuck when executing chef-server-ctl. I know current chef-server 12 does not officially support RHEL7. But since it is opensource, maybe we can find a workaround way here.
Recreate Procedure
# chef-server-ctl reconfigure

Log and symptom
# chef-server-ctl reconfigure
the ffi-yajl and yajl-ruby gems have incompatible C libyajl libs and should not be loaded in the same Ruby VM
falling back to ffi which might work (or might not, no promises)
ffi-yajl/json_gem is deprecated, these monkeypatches will be dropped shortly
the ffi-yajl and yajl-ruby gems have incompatible C libyajl libs and should not be loaded in the same Ruby VM
falling back to ffi which might work (or might not, no promises)
ffi-yajl/json_gem is deprecated, these monkeypatches will be dropped shortly
Starting Chef Client, version 11.12.2
Compiling Cookbooks...
Recipe: private-chef::default
  * directory[/etc/opscode] action create (up to date)
  * directory[/etc/opscode/logrotate.d] action create
    - create new directory /etc/opscode/logrotate.d
    - change mode from '' to '0755'
    - change owner from '' to 'root'
    - change group from '' to 'root'
    - restore selinux security context

[2014-12-04T03:34:39-05:00] WARN: Cloning resource attributes for template[/opt/opscode/embedded/service/chef-server-bootstrap/bootstrapper-config/pivotal.yml] from prior resource (CHEF-3694)
[2014-12-04T03:34:39-05:00] WARN: Previous template[/opt/opscode/embedded/service/chef-server-bootstrap/bootstrapper-config/pivotal.yml]: /opt/opscode/embedded/cookbooks/private-chef/recipes/bootstrap.rb:32:in `from_file'
[2014-12-04T03:34:39-05:00] WARN: Current  template[/opt/opscode/embedded/service/chef-server-bootstrap/bootstrapper-config/pivotal.yml]: /opt/opscode/embedded/cookbooks/private-chef/recipes/bootstrap.rb:62:in `from_file'
[2014-12-04T03:34:39-05:00] WARN: Cloning resource attributes for runit_service[redis_lb] from prior resource (CHEF-3694)
[2014-12-04T03:34:39-05:00] WARN: Previous runit_service[redis_lb]: /opt/opscode/embedded/cookbooks/enterprise/definitions/component_runit_service.rb:36:in `block in from_file'
[2014-12-04T03:34:39-05:00] WARN: Current  runit_service[redis_lb]: /opt/opscode/embedded/cookbooks/private-chef/recipes/redis_lb.rb:83:in `from_file'
[2014-12-04T03:34:39-05:00] WARN: Cloning resource attributes for directory[/var/opt/opscode/nginx/etc/addon.d] from prior resource (CHEF-3694)
[2014-12-04T03:34:39-05:00] WARN: Previous directory[/var/opt/opscode/nginx/etc/addon.d]: /opt/opscode/embedded/cookbooks/private-chef/recipes/oc_id.rb:151:in `from_file'
[2014-12-04T03:34:39-05:00] WARN: Current  directory[/var/opt/opscode/nginx/etc/addon.d]: /opt/opscode/embedded/cookbooks/private-chef/recipes/nginx.rb:33:in `block in from_file'
Generating RSA private key, 2048 bit long modulus
.......................................................+++
............+++
e is 65537 (0x10001)
Converging 279 resources
  * link[/usr/bin/private-chef-ctl] action create (up to date)
  * link[/usr/bin/chef-server-ctl] action create (up to date)
  * directory[/etc/opscode] action nothing (skipped due to action :nothing)
  * directory[/etc/opscode/logrotate.d] action nothing (skipped due to action :nothing)
  * log[opscode_webui deprecation notice] action write (skipped due to only_if)
Recipe: private-chef::users
  * user[opscode] action create
    - create user user[opscode]

  * group[opscode] action create
    - alter group group[opscode]
    - replace group members with new list of members

Recipe: private-chef::default
  * file[/etc/opscode/dark_launch_features.json] action create
    - create new file /etc/opscode/dark_launch_features.json
    - update content in file /etc/opscode/dark_launch_features.json from none to 05b75f
        --- /etc/opscode/dark_launch_features.json      2014-12-04 03:34:39.961877633 -0500
        +++ /tmp/.dark_launch_features.json20141204-10966-noalb2        2014-12-04 03:34:39.961877633 -0500
        @@ -1 +1,17 @@
        +{
        +  "quick_start": false,
        +  "new_theme": true,
        +  "private-chef": true,
        +  "sql_users": true,
        +  "add_type_and_bag_to_items": true,
        +  "reporting": true,
        +  "actions": true,
        +  "503_mode": false,
        +  "couchdb_containers": false,
        +  "couchdb_groups": false,
        +  "couchdb_acls": false,
        +  "couchdb_association_requests": false,
        +  "couchdb_organizations": false,
        +  "couchdb_associations": false
        +}
    - change mode from '' to '0644'
    - change owner from '' to 'opscode'
    - change group from '' to 'root'
    - restore selinux security context

  * file[/etc/opscode/webui_pub.pem] action create
    - create new file /etc/opscode/webui_pub.pem
    - update content in file /etc/opscode/webui_pub.pem from none to 191680
        --- /etc/opscode/webui_pub.pem  2014-12-04 03:34:39.988877631 -0500
        +++ /tmp/.webui_pub.pem20141204-10966-1hrnhd6   2014-12-04 03:34:39.989877631 -0500
        @@ -1 +1,10 @@
        +-----BEGIN PUBLIC KEY-----
        +<key content>
        +-----END PUBLIC KEY-----
    - change mode from '' to '0644'
    - change owner from '' to 'root'
    - change group from '' to 'root'
    - restore selinux security context

  * file[/etc/opscode/webui_priv.pem] action create
    - create new file /etc/opscode/webui_priv.pem
    - update content in file /etc/opscode/webui_priv.pem from none to 5c3b78
        --- /etc/opscode/webui_priv.pem 2014-12-04 03:34:40.015877629 -0500
        +++ /tmp/.webui_priv.pem20141204-10966-vh4br9   2014-12-04 03:34:40.015877629 -0500
        @@ -1 +1,28 @@
        +-----BEGIN RSA PRIVATE KEY-----
        +<key content>
        +-----END RSA PRIVATE KEY-----
    - change mode from '' to '0600'
    - change owner from '' to 'opscode'
    - change group from '' to 'root'
    - restore selinux security context

  * file[/etc/opscode/worker-public.pem] action create
    - create new file /etc/opscode/worker-public.pem
    - update content in file /etc/opscode/worker-public.pem from none to c904c5
        --- /etc/opscode/worker-public.pem      2014-12-04 03:34:40.041877627 -0500
        +++ /tmp/.worker-public.pem20141204-10966-1opa5g8       2014-12-04 03:34:40.042877627 -0500
        @@ -1 +1,10 @@
        +-----BEGIN PUBLIC KEY-----
        +<key content>
        +-----END PUBLIC KEY-----
    - change mode from '' to '0644'
    - change owner from '' to 'root'
    - change group from '' to 'root'
    - restore selinux security context

  * file[/etc/opscode/worker-private.pem] action create
    - create new file /etc/opscode/worker-private.pem
    - update content in file /etc/opscode/worker-private.pem from none to faae02
        --- /etc/opscode/worker-private.pem     2014-12-04 03:34:40.057877626 -0500
        +++ /tmp/.worker-private.pem20141204-10966-5gy5ye       2014-12-04 03:34:40.058877626 -0500
        @@ -1 +1,28 @@
        +-----BEGIN RSA PRIVATE KEY-----
        +<key content>
        +-----END RSA PRIVATE KEY-----
    - change mode from '' to '0600'
    - change owner from '' to 'opscode'
    - change group from '' to 'root'
    - restore selinux security context

  * file[/etc/opscode/pivotal.cert] action create
    - create new file /etc/opscode/pivotal.cert
    - update content in file /etc/opscode/pivotal.cert from none to 8e1b81
        --- /etc/opscode/pivotal.cert   2014-12-04 03:34:40.084877624 -0500
        +++ /tmp/.pivotal.cert20141204-10966-1wol606    2014-12-04 03:34:40.084877624 -0500
        @@ -1 +1,22 @@
        +-----BEGIN CERTIFICATE-----
        +<cert content>
        +-----END CERTIFICATE-----
    - change mode from '' to '0644'
    - change owner from '' to 'root'
    - change group from '' to 'root'
    - restore selinux security context

  * file[/etc/opscode/pivotal.pem] action create
    - create new file /etc/opscode/pivotal.pem
    - update content in file /etc/opscode/pivotal.pem from none to a98e47
        --- /etc/opscode/pivotal.pem    2014-12-04 03:34:40.110877622 -0500
        +++ /tmp/.pivotal.pem20141204-10966-dtx8oj      2014-12-04 03:34:40.111877622 -0500
        @@ -1 +1,28 @@
        +-----BEGIN RSA PRIVATE KEY-----
        +<key-content>
        +-----END RSA PRIVATE KEY-----
    - change mode from '' to '0600'
    - change owner from '' to 'opscode'
    - change group from '' to 'root'
    - restore selinux security context

  * directory[/etc/chef] action create
    - create new directory /etc/chef
    - change mode from '' to '0775'
    - change owner from '' to 'root'
    - change group from '' to 'opscode'
    - restore selinux security context

  * directory[/var/opt/opscode] action create (up to date)
  * directory[/var/log/opscode] action create
    - create new directory /var/log/opscode
    - change mode from '' to '0755'
    - change owner from '' to 'opscode'
    - change group from '' to 'opscode'
    - restore selinux security context

  * private-chef_keepalived_safemode[warmfuzzy] action create (skipped due to only_if)
Recipe: enterprise::runit_sysvinit
  * execute[echo 'SV:123456:respawn:/opt/opscode/embedded/bin/runsvdir-start' >> /etc/inittab] action run
    - execute echo 'SV:123456:respawn:/opt/opscode/embedded/bin/runsvdir-start' >> /etc/inittab

  * execute[init q] action run
    - execute init q

  * execute[init q] action nothing (skipped due to action :nothing)
Recipe: private-chef::sysctl-updates
  * execute[sysctl-reload] action nothing (skipped due to action :nothing)
  * bash[dual ip4/ip6 portbind] action run (skipped due to only_if)
Recipe: private-chef::plugins
  * chef_run[recipe[chef-ha-drbd::disable]] action runCompiling Cookbooks...
Converging 0 resources

    - Running chef-run with run list recipe[chef-ha-drbd::disable]

Recipe: private-chef::rabbitmq
  * directory[/var/opt/opscode/rabbitmq] action create
    - create new directory /var/opt/opscode/rabbitmq
    - change mode from '' to '0750'
    - change owner from '' to 'opscode'
    - change group from '' to 'opscode'
    - restore selinux security context

  * directory[/var/opt/opscode/rabbitmq/etc] action create
    - create new directory /var/opt/opscode/rabbitmq/etc
    - change mode from '' to '0750'
    - change owner from '' to 'opscode'
    - change group from '' to 'opscode'
    - restore selinux security context

  * directory[/var/opt/opscode/rabbitmq/db] action create
    - create new directory /var/opt/opscode/rabbitmq/db
    - change mode from '' to '0750'
    - change owner from '' to 'opscode'
    - change group from '' to 'opscode'
    - restore selinux security context

  * directory[/var/log/opscode/rabbitmq] action create
    - create new directory /var/log/opscode/rabbitmq
    - change mode from '' to '0750'
    - change owner from '' to 'opscode'
    - change group from '' to 'opscode'
    - restore selinux security context

  * link[/var/opt/opscode/rabbitmq/db] action create (skipped due to not_if)
  * link[/opt/opscode/embedded/bin/rabbitmqctl] action create (up to date)
  * link[/opt/opscode/embedded/bin/rabbitmq-defaults] action create
    - create symlink at /opt/opscode/embedded/bin/rabbitmq-defaults to /opt/opscode/embedded/service/rabbitmq/sbin/rabbitmq-defaults

  * link[/opt/opscode/embedded/bin/rabbitmq-env] action create (up to date)
  * link[/opt/opscode/embedded/bin/rabbitmq-plugins] action create
    - create symlink at /opt/opscode/embedded/bin/rabbitmq-plugins to /opt/opscode/embedded/service/rabbitmq/sbin/rabbitmq-plugins

  * link[/opt/opscode/embedded/bin/rabbitmq-server] action create (up to date)
  * template[/opt/opscode/embedded/service/rabbitmq/sbin/rabbitmq-defaults] action create
    - update content in file /opt/opscode/embedded/service/rabbitmq/sbin/rabbitmq-defaults from 4bcf8e to 2463be
        --- /opt/opscode/embedded/service/rabbitmq/sbin/rabbitmq-defaults       2014-12-17 14:40:02.000000000 -0500
        +++ /tmp/chef-rendered-template20141204-10966-14wuk75   2014-12-04 03:34:40.525877593 -0500
        @@ -16,7 +16,7 @@
         ##

         ### next line potentially updated in package install steps
        -SYS_PREFIX=${RABBITMQ_HOME}
        +SYS_PREFIX=/var/opt/opscode/rabbitmq

         ### next line will be updated when generating a standalone release
         ERL_DIR=
        @@ -26,12 +26,12 @@

         ## Set default values

        -CONFIG_FILE=${SYS_PREFIX}/etc/rabbitmq/rabbitmq
        -LOG_BASE=${SYS_PREFIX}/var/log/rabbitmq
        -MNESIA_BASE=${SYS_PREFIX}/var/lib/rabbitmq/mnesia
        -ENABLED_PLUGINS_FILE=${SYS_PREFIX}/etc/rabbitmq/enabled_plugins
        +CONFIG_FILE=${SYS_PREFIX}/etc/rabbitmq
        +LOG_BASE=${SYS_PREFIX}/log
        +MNESIA_BASE=${SYS_PREFIX}/db
        +ENABLED_PLUGINS_FILE=${SYS_PREFIX}/etc/enabled_plugins

         PLUGINS_DIR="${RABBITMQ_HOME}/plugins"

        -CONF_ENV_FILE=${SYS_PREFIX}/etc/rabbitmq/rabbitmq-env.conf
        +CONF_ENV_FILE=/var/opt/opscode/rabbitmq/etc/rabbitmq.conf
    - restore selinux security context

  * template[/var/opt/opscode/rabbitmq/etc/rabbitmq.conf] action create
    - create new file /var/opt/opscode/rabbitmq/etc/rabbitmq.conf
    - update content in file /var/opt/opscode/rabbitmq/etc/rabbitmq.conf from none to 40477a
        --- /var/opt/opscode/rabbitmq/etc/rabbitmq.conf 2014-12-04 03:34:40.552877591 -0500
        +++ /tmp/chef-rendered-template20141204-10966-1b46tr8   2014-12-04 03:34:40.553877591 -0500
        @@ -1 +1,7 @@
        +HOME="/var/opt/opscode/rabbitmq"
        +RABBITMQ_MNESIA_BASE="/var/opt/opscode/rabbitmq/db"
        +RABBITMQ_LOG_BASE="/var/opt/opscode/rabbitmq/log"
        +RABBITMQ_NODE_IP_ADDRESS="<IP_ADDRESS>"
        +RABBITMQ_NODE_PORT="5672"
        +NODENAME="rabbit@localhost"
    - change mode from '' to '0644'
    - change owner from '' to 'root'
    - change group from '' to 'root'
    - restore selinux security context

  * execute[restart_rabbitmq_log_service] action nothing (skipped due to action :nothing)
  * template[/var/log/opscode/rabbitmq/config] action create
    - create new file /var/log/opscode/rabbitmq/config
    - update content in file /var/log/opscode/rabbitmq/config from none to c52569
        --- /var/log/opscode/rabbitmq/config    2014-12-04 03:34:40.604877587 -0500
        +++ /tmp/chef-rendered-template20141204-10966-56xbvm    2014-12-04 03:34:40.607877587 -0500
        @@ -1 +1,4 @@
        +# svlogd configuration
        +S104857600
        +n10
    - change mode from '' to '0644'
    - change owner from '' to 'root'
    - change group from '' to 'root'
    - restore selinux security context

Recipe: <Dynamically Defined Resource>
  * service[rabbitmq] action nothing (skipped due to action :nothing)
Recipe: private-chef::rabbitmq
  * runit_service[rabbitmq] action enableRecipe: <Dynamically Defined Resource>
  * directory[/opt/opscode/sv/rabbitmq] action create
    - create new directory /opt/opscode/sv/rabbitmq
    - change mode from '' to '0755'
    - restore selinux security context

  * template[/opt/opscode/sv/rabbitmq/run] action create
    - create new file /opt/opscode/sv/rabbitmq/run
    - update content in file /opt/opscode/sv/rabbitmq/run from none to c7603d
        --- /opt/opscode/sv/rabbitmq/run        2014-12-04 03:34:40.662877583 -0500
        +++ /tmp/chef-rendered-template20141204-10966-15axhlb   2014-12-04 03:34:40.663877583 -0500
        @@ -1 +1,5 @@
        +#!/bin/sh
        +exec 2>&1
        +exec chpst -P -u opscode -U opscode /usr/bin/env HOME=/var/opt/opscode/rabbitmq /opt/opscode/embedded/bin/rabbitmq-server
        +
    - change mode from '' to '0755'
    - restore selinux security context

  * directory[/opt/opscode/sv/rabbitmq/log] action create
    - create new directory /opt/opscode/sv/rabbitmq/log
    - change mode from '' to '0755'
    - restore selinux security context

  * directory[/opt/opscode/sv/rabbitmq/log/main] action create
    - create new directory /opt/opscode/sv/rabbitmq/log/main
    - change mode from '' to '0755'
    - restore selinux security context

  * template[/opt/opscode/sv/rabbitmq/log/run] action create
    - create new file /opt/opscode/sv/rabbitmq/log/run
    - update content in file /opt/opscode/sv/rabbitmq/log/run from none to 0e09b8
        --- /opt/opscode/sv/rabbitmq/log/run    2014-12-04 03:34:40.735877578 -0500
        +++ /tmp/chef-rendered-template20141204-10966-1ogqpsu   2014-12-04 03:34:40.736877578 -0500
        @@ -1 +1,4 @@
        +#!/bin/sh
        +exec chpst -U opscode -u opscode \
        +  svlogd -tt /var/log/opscode/rabbitmq
    - change mode from '' to '0755'
    - restore selinux security context

  * template[/opt/opscode/sv/rabbitmq/log/config] action create
    - create new file /opt/opscode/sv/rabbitmq/log/config
    - update content in file /opt/opscode/sv/rabbitmq/log/config from none to e3b0c4
        (no diff)
    - change mode from '' to '0644'
    - restore selinux security context

  * link[/opt/opscode/init/rabbitmq] action create
    - create symlink at /opt/opscode/init/rabbitmq to /opt/opscode/embedded/bin/sv

    - configure service runit_service[rabbitmq]  * link[/opt/opscode/service/rabbitmq] action create
    - create symlink at /opt/opscode/service/rabbitmq to /opt/opscode/sv/rabbitmq

The process stuck at above forever. I tried to wait for hours, but not progress. I need to interrupt it by CTRL+C. And it reports as:
^C[2015-01-15T21:19:16-05:00] FATAL: SIGINT received, stopping
  * directory[/opt/opscode/sv/rabbitmq] action create (up to date)
  * template[/opt/opscode/sv/rabbitmq/run] action create (up to date)
  * directory[/opt/opscode/sv/rabbitmq/log] action create (up to date)
  * directory[/opt/opscode/sv/rabbitmq/log/main] action create (up to date)
  * template[/opt/opscode/sv/rabbitmq/log/run] action create (up to date)
  * template[/opt/opscode/sv/rabbitmq/log/config] action create (up to date)
  * link[/opt/opscode/init/rabbitmq] action create (up to date)

    - configure service runit_service[rabbitmq]

Recipe: private-chef::rabbitmq
  * execute[/opt/opscode/bin/private-chef-ctl start rabbitmq] action run
================================================================================
Error executing action `run` on resource 'execute[restart_rabbitmq_log_service]'
================================================================================

Mixlib::ShellOut::ShellCommandFailed
------------------------------------
Expected process to exit with [0], but received '1'
---- Begin output of /opt/opscode/embedded/bin/sv restart /opt/opscode/sv/rabbitmq/log ----
STDOUT: warning: /opt/opscode/sv/rabbitmq/log: unable to open supervise/ok: file does not exist
STDERR:
---- End output of /opt/opscode/embedded/bin/sv restart /opt/opscode/sv/rabbitmq/log ----
Ran /opt/opscode/embedded/bin/sv restart /opt/opscode/sv/rabbitmq/log returned 1

Resource Declaration:
---------------------
# In /opt/opscode/embedded/cookbooks/enterprise/definitions/component_runit_service.rb

 18:   execute "restart_#{component}_log_service" do
 19:     command "#{node['runit']['sv_bin']} restart #{node['runit']['sv_dir']}/#{component}/log"
 20:     action :nothing
 21:   end
 22:

Compiled Resource:
------------------
# Declared in /opt/opscode/embedded/cookbooks/enterprise/definitions/component_runit_service.rb:18:in `block in from_file'

execute("restart_rabbitmq_log_service") do
  params {:package=>"private_chef", :log_directory=>nil, :svlogd_size=>nil, :svlogd_num=>nil, :ha=>nil, :control=>nil, :action=>:enable, :name=>"rabbitmq"}
  action [:nothing]
  retries 0
  retry_delay 2
  guard_interpreter :default
  command "/opt/opscode/embedded/bin/sv restart /opt/opscode/sv/rabbitmq/log"
  backup 5
  returns 0
  cookbook_name :"private-chef"
  recipe_name "rabbitmq"
end

Running handlers:
[2015-01-15T21:20:23-05:00] ERROR: Running exception handlers
Running handlers complete

[2015-01-15T21:20:23-05:00] ERROR: Exception handlers complete
[2015-01-15T21:20:23-05:00] FATAL: Stacktrace dumped to /opt/opscode/embedded/cookbooks/cache/chef-stacktrace.out
Chef Client failed. 33 resources updated in 3692746.209538932 seconds
[2015-01-15T21:20:23-05:00] FATAL: Chef::Exceptions::MultipleFailures: Multiple failures occurred:
* Mixlib::ShellOut::ShellCommandFailed occurred in chef run: execute[/opt/opscode/bin/private-chef-ctl start rabbitmq] (private-chef::rabbitmq line 80) had an error: Mixlib::ShellOut::ShellCommandFailed: Expected process to exit with [0], but received '1'
---- Begin output of /opt/opscode/bin/private-chef-ctl start rabbitmq ----
STDOUT: warning: rabbitmq: unable to open supervise/ok: file does not exist
STDERR: the ffi-yajl and yajl-ruby gems have incompatible C libyajl libs and should not be loaded in the same Ruby VM
falling back to ffi which might work (or might not, no promises)
ffi-yajl/json_gem is deprecated, these monkeypatches will be dropped shortly
---- End output of /opt/opscode/bin/private-chef-ctl start rabbitmq ----
Ran /opt/opscode/bin/private-chef-ctl start rabbitmq returned 1
* Mixlib::ShellOut::ShellCommandFailed occurred in delayed notification: execute[restart_rabbitmq_log_service] (private-chef::rabbitmq line 18) had an error: Mixlib::ShellOut::ShellCommandFailed: Expected process to exit with [0], but received '1'
---- Begin output of /opt/opscode/embedded/bin/sv restart /opt/opscode/sv/rabbitmq/log ----
STDOUT: warning: /opt/opscode/sv/rabbitmq/log: unable to open supervise/ok: file does not exist
STDERR:
---- End output of /opt/opscode/embedded/bin/sv restart /opt/opscode/sv/rabbitmq/log ----
Ran /opt/opscode/embedded/bin/sv restart /opt/opscode/sv/rabbitmq/log returned 1

It will wait for a while on execute[/opt/opscode/bin/private-chef-ctl start rabbitmq] action run, and then failed.
Similar Issue

There is a similar issue reported:
https://github.com/hw-cookbooks/runit/issues/74#issuecomment-70075119
However, it is using 11.x chef server
Another issue on CentOS 7:
https://github.com/opscode/chef/issues/1955
It was also using chef server 11.x. And from the output log, it fails to locate /etc/init folder, which does not fit the symptom here.

This issue is caused by enterprise cookbook included in chef-server 12.0.1 (/opt/opscode/embedded/cookbooks/enterprise).
From the log:
Recipe: enterprise::runit_sysvinit
  * execute[echo 'SV:123456:respawn:/opt/opscode/embedded/bin/runsvdir-start' >> /etc/inittab] action run
    - execute echo 'SV:123456:respawn:/opt/opscode/embedded/bin/runsvdir-start' >> /etc/inittab

  * execute[init q] action run
    - execute init q

  * execute[init q] action nothing (skipped due to action :nothing)

Within chef-server-ctl reconfigure came to enterprise cookbook (https://github.com/opscode-cookbooks/enterprise-chef-common/blob/master/recipes/runit.rb#L27), it used runit_sysvinit for RHEL7. However, above command in log did not make the /opt/opscode/embedded/bin/runsvdir-start to work. Therefore, it prevented following embedded services to register to runsv and start. The first one is "rabbitmq". That's why we saw the progress hung on rabbitmq, but that is not the rabbitmq recipe issue.

Opened an issue in enterprise cookbook: https://github.com/opscode-cookbooks/enterprise-chef-common/issues/26
Fix to enterprise cookbook issue will be tracked in that issue.

This should be fixed in 12.0.3.

its not fixed in chef-server-core-12.0.5-1.el6.x86_64.rpm

Just got this same error trying to install inside a docker container:
[2015-08-12T05:54:59+00:00] INFO: Processing execute[init q] action run (enterprise::runit_sysvinit line 18)

================================================================================
Error executing action `run` on resource 'execute[init q]'
================================================================================

Mixlib::ShellOut::ShellCommandFailed
------------------------------------
Expected process to exit with [0], but received '1'
---- Begin output of init q ----
STDOUT:
STDERR: Couldn't find an alternative telinit implementation to spawn.
---- End output of init q ----
Ran init q returned 1

Resource Declaration:
---------------------
# In /opt/opscode/embedded/cookbooks/cache/cookbooks/enterprise/recipes/runit_sysvinit.rb

 18: execute "init q" do
 19:   action :nothing
 20: end

Compiled Resource:
------------------
# Declared in /opt/opscode/embedded/cookbooks/cache/cookbooks/enterprise/recipes/runit_sysvinit.rb:18:in `from_file'

execute("init q") do
  action [:nothing]
  retries 0
  retry_delay 2
  default_guard_interpreter :execute
  command "init q"
  backup 5
  returns 0
  declared_type :execute
  cookbook_name "enterprise"
  recipe_name "runit_sysvinit"
end

[2015-08-12T05:54:59+00:00] INFO: Running queued delayed notifications before re-raising exception
[2015-08-12T05:54:59+00:00] ERROR: Running exception handlers
[2015-08-12T05:54:59+00:00] ERROR: Exception handlers complete
[2015-08-12T05:54:59+00:00] FATAL: Stacktrace dumped to /opt/opscode/embedded/cookbooks/cache/chef-stacktrace.out
[2015-08-12T05:54:59+00:00] FATAL: Mixlib::ShellOut::ShellCommandFailed: execute[init q] (enterprise::runit_sysvinit line 18) had an error: Mixlib::ShellOut::ShellCommandFailed: Expected process to exit with [0], but received '1'
---- Begin output of init q ----
STDOUT:
STDERR: Couldn't find an alternative telinit implementation to spawn.
---- End output of init q ----
Ran init q returned 1

Sorry issue with Centos7, ignore the above comment: https://github.com/docker/docker/issues/13297

Just got the same error on chef-server-core-12.3.0-1.el6.x86_64.rpm

Got this same error with both 12.4.1 and 12.4.0 on Ubuntu 14.04.

Same error for 12.6.0-1 on Ubuntu 16.04

Same error Chef Server 12.5.0-1 on Ubuntu 14.04.

Reopened this as a number of people are seeing the same symptoms still.

If these are occurring in Docker images, this is a known limitation - let's open a new issue for that so that we can track if this issue is occurring on supported configurations, or only under Docker.
That being said, if you are seeing this on Docker, there is a workaround that you can try.
Chef Server users runit - and if we tell it to run as a full init system, it takes care of this issue.
To do this, manually fork the runsv-start that's embedded with chef-server.  This will permit the runit-enabled services to start successfuly. If you're looking to reconfigure and run from a running instance  with a pre-installed (but unconfigured) image:
Dockerfile:
ADD /path/to/chef-server-startup.sh /chef-server-startup.sh
CMD ["bash", "/chef-server-startup.sh"]

chef-server-startup.sh:
#!/bin/bash
export PATH=/opt/opscode/bin:/opt/opscode/bin/embedded:$PATH

# Start this so that chef-server-ctl sv-related commands can
# interact with its services via runsv
/opt/opscode/embedded/bin/runsvdir-start &
chef-server-ctl reconfigure

# Something useful that also keeps the container running...
tail -f /var/log/opscode/nginx/access.log

It's similar if you want to reconfigure in the Docker image  build and start Chef Server in the running container.  In this case, your container build will need to do the same thing:
Dockerfile:
ADD chef-server-setup.sh /chef-server-setup.sh
RUN /bin/bash /chef-server-setup.sh
ADD /path/to/chef-server-startup.sh /chef-server-startup.sh
CMD ["bash", "/chef-server-startup.sh"]

chef-server-setup.sh:

/opt/opscode/embedded/bin/runsvdir-start &
chef-server-ctl reconfigure
chef-server-startup.sh
```bash
#!/bin/bash
export PATH=/opt/opscode/bin:/opt/opscode/bin/embedded:$PATH
/opt/opscode/embedded/bin/runsvdir-start &
chef-server-ctl start
# Output current state of things for sanity's sake
chef-server-ctl status
# Something useful that also keeps the container running...
tail -f /var/log/opscode/nginx/access.log

In any case - can we get clarification from those currently seeing this @ephracis @z-math  @Ufflo  - are you encountering this on a docker or LXC container, or is it on VM/bare metal?

I'm not on Docker. Using Ubuntu14.04 on regular AWS EC2 VM.

I am running it on a VM using Vagrant/VirtualBox.
I believe my case was caused by the VM running low on memory. I bumped it from the default 2 Gb to 4 Gb and it I haven't had any issues since.

Hi Everyone,
Sorry you've had trouble getting chef-server installed.  The originally reported issue is likely fixed (we build and test full installs of chef-server on RHEL 7 with every commit).  I don't doubt, however, that many of you have seen similar looking error messages.  I'm going to close this out, but if you are still seeing something similar, please open a new bug report with:

The operating system you are running on
A bit of information about the environment (docker/no-docker, system memory, cpu, etc), and
The full error output that you are seeing

I believe the issue was solved by increasing the amount of memory to 4 GiB.
On Wed, 2 Nov 2016 at 01:08, Steven Danna<EMAIL_ADDRESS>wrote:

Hi Everyone,
Sorry you've had trouble getting chef-server installed. The originally
reported issue is likely fixed (we build and test full installs of
chef-server on RHEL 7 with every commit). I don't doubt, however, that many
of you have seen similar looking error messages. I'm going to close this
out, but if you are still seeing something similar, please open a new bug
report with:

The operating system you are running on
A bit of information about the environment (docker/no-docker, system
memory, cpu, etc), and
The full error output that you are seeing

—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/chef/chef-server/issues/62#issuecomment-257736360,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AAPHa0IRlFEXjUBLXbJY81usYIqZBgq3ks5q59RxgaJpZM4DTKiB
.

FYI, Got the same ERROR when trying to install chef-server-core-12.13 on EC2 micro instance with RHEL7.3, 1 CPU and 1 GB RAM and later Re-installed on EC2 Medium sized with 2 CPU and 4GB RAM which worked perfectly without any trouble

I have tried this on docker, but still its not working. can some one please help me on this.
export PATH=/opt/opscode/bin:/opt/opscode/bin/embedded:$PATH
Start this so that chef-server-ctl sv-related commands can
interact with its services via runsv
/opt/opscode/embedded/bin/runsvdir-start &
chef-server-ctl reconfigur


Add support for delete

This checklist is used to make sure that common guidelines for a pull request are followed.
General Guidelines

[ ] The PR has modified HISTORY.rst with an appropriate description of the change (see Modifying change log).

Command Guidelines

[ ] Each command and parameter has a meaningful description.
[ ] Each new command has a test.

(see Authoring Command Modules)

Examples
    Delete a repository from the specified container registry.
        az acr repository delete -n MyRegistry --repository MyRepository

    Delete a tag from the given repository in the specified container registry, but keep the
    manifest referenced by the tag.
        az acr repository delete -n MyRegistry --repository MyRepository --tag MyTag

    Delete the manifest referenced by a tag and all tags referencing the manifest from the given
    repository in the specified container registry.
        az acr repository delete -n MyRegistry --repository MyRepository --tag MyTag --manifest

    Delete a manfiest and all tags referencing the manifest from the given repository in the
    specified container registry.
        az acr repository delete -n MyRegistry --repository MyRepository --manifest MyManifest

@SajayAntony @yuwaMSFT2


⚠ Avatar API Endpoint has degraded performance

In 96013c5, Avatar API Endpoint (https://avatar.roblox.com/v1/avatar-rules) experienced degraded performance:

HTTP code: 200
Response time: 4787 ms

Resolved: Avatar API Endpoint performance has improved in 0fe39fb after 3 minutes.


Version bump

Changes since release 1.12.0:

Add :itc_provider option for deliver and pilot
Ads Apple Developer Id to itunes_transporter.rb. Allows deliver to work with multiple iTunes Providers
Revert "Allow deliver to work with multiple iTunes Providers" (#4961)
Enabled fastlane plugins for all the tools (#4941)
Make deliver setup honor the skip_screenshots flag (#4919)

👍


Why Dalston.SR1 version won't execute fallbackFactory method  when the server which is called  return status 500

In service call with feignClient , I use a consume servce named "A" to call a producer service named "B" , if  "B" occur an internal exception and return http status 500 ,  "A" won't trigger fallback.
I used Dalston.SR1 version meanwhile set feign.hystrix.enable: true in my .yml file.
But when I change version to Camden.SR6 , the situation I described  above won't occur and It will  trigger fallback as expected.
I tested , if @FeignClient(value = "service-name", url = "http://<IP_ADDRESS>:2222", fallback = ComputeClientFallback.class, configuration = CustomerFeignConfiguration.class)  use fallback props , both version is ok , only @FeignClient(value = "service-name", url = "http://<IP_ADDRESS>:2222", fallbackFactory = ComputeClientFallbackFactory.class, configuration = CustomerFeignConfiguration.class)  use fallbackFactory pros and version Dalston.SR1 will be bad.
I fell puzzled , thanks for feedback in advance.

I'm afraid you'll need to be more detailed explaination, I'm having a hard time following. Maybe a full sample would be nice.

It's my bad.  feign.hystrix.enabled: true is right. I write the wrong properties name. sorry. orz


Encoding issues

Hey Folks,
you have some Encoding problems.
Found in (JSON files):
every node with text attribute have these problem
If you want to know how to fix you can use my fork. I commited the solution a few minutes ago.
5b3b30d69b1b21563cef9daff1f5f0b7f57d9040
Cheers,
Flipso

For example
    "edge_media_to_caption": {
        "edges": [
            {
                "node": {
                    "text": "miss \u2018em already"
                }
            }
        ]
    }

and comments:
{
"id":<PHONE_NUMBER>1126918,
"created_at":<PHONE_NUMBER>,
"text": "Aww love you skippy \u2764\ufe0f\ud83d\ude14",
}

The encoding is fine.

How can this be understood? As shown in the example, emoticons are currently not supported by you. Should this be a feature?


Strict concurrency is ready

Although the CI is failing, I will first merge it since it is a part of another feature branch [strict-concurrency](https://github.com/onevcat/Kingfisher/tree/fix/strict-concurrency).
And the failing CI will be solved there.


What is the license of this project?

Hi!
There is no LICENSE file in the root of the project, nor any README explaining the usage terms of the projects. Without this I cannot use the project, as I'm not granted any rights to do so.
Please provide a LICENSE to I can evaluate and maybe use the library in my project.
Github provides detailed description on setting the license in a way it can parse it: https://help.github.com/articles/licensing-a-repository/
Thanks!

Hi,
the project is licensed under Apache License 2.0. Please refer to the Codeplex page until the documentation is completely migrated to Github:
License: http://imapx.codeplex.com/license
Documentation: http://imapx.codeplex.com/documentation

Thanks!

Thats due the finalized shutdown of codeplex. As long as the docs aren't migrated to Github you can hit the "Download Archive"-button on codeplex. You'll get the whole archive including the wiki which lives in a bunch of html files which are not linked among each other which makes it quite annoying to handle but it works.

@Jasonthurston , yes, that's the only way currently. I am working on a new version (first results are in the next branch), however, due to a tight schedule on other projects, I do not see a release coming before April. The docs will be updated along with the rollout of the new version.

@azanov I parsed the codeplex doc (only plain text/html) and fixed the inline references. It's pretty handable as a offline documentation. Please let me now if it's ok to upload and post it here.

@emuuu That's great. If you don't mind, I can also upload it in a subfolder on imapx.org, just send me the zip to<EMAIL_ADDRESS>

I did send it to you and also created  imapxDocumentation

Thanks, the docs are now available at https://imapx.org/docs/


Support for Flash_api

We're using this plugin for our player, and need compatibility with HLS videos on IE 11. Right now, our solution is forcing Flash on this browser. We noticed that videos were not playing, and it was because videojs-ima gave an error that this.contentPlayer was undefined when trying to get hasAttribute('autoplay').
I realized that the plugin was establishing the ID strictly by appending "_html5_api" to the plugin settings ID.
We solved it locally by using the following line:
this.contentPlayer = document.getElementById(this.settings.id).getElementsByClassName('vjs-tech')[0];
Since both object and video have this class when the player is instanced.
Can this be included in the plugin?
Thanks.

We should be able to add this, as long as it doesn't break anything. We also accept pull requests if you're able to sign our SLA and you're feeling ambitious :)

Done deal! Thanks.

Resolved by #442


109_fix_macos_installer

Fixes #109

do not add to system path during installation

Hi @constantinpape,
shall I proceed to add the signing workflow with a "Developer ID Installer certificate" for MacOs?
I created a free developer account but certificates seem to be behind a paywall.
Information about signing and the certificates can be found here and here.

Hi @paulhfu ,
is the signing necessary for the installation to work, or will it only throw a warning if it's not signed?

Ah, I found it:
On macOS, if your app isn’t downloaded from the Mac App Store or signed with a Developer ID certificate, it won’t launch unless the user completely disables [Gatekeeper](https://help.apple.com/xcode/mac/current/#/dev190d53ccb). Users have the option of enabling or disabling identified developers in System Preferences.

Ok, so from what I understand, for signing you need a developer account, which is 100$ a year. So let's not do that.
Either we:

Use the bundled app solution (I will follow up in #109 on that)
Or we don't provide a Mac installer

Yes, this is also how I understood it.

I will go ahead and merge it, but reopen #109 so we can discuss there if there is anything else we can do for mac.


List.reduceWhile

Experimental function for early-stop reduces, helps with simulating processes.
This can be treated as a specialized version of #1196.
TODO:

[x] tests
[x] documentation
[ ] decide if this is solid enough to publish under List and not under Danger

Codecov Report

Merging #2068 (ff82d08) into develop (6426117) will increase coverage by 0.75%.
The diff coverage is n/a.

:exclamation: Current head ff82d08 differs from pull request most recent head 49ed5b1. Consider uploading reports for the commit 49ed5b1 to get more accurate results

:exclamation: Your organization is not using the GitHub App Integration. As a result you may experience degraded service beginning May 15th. Please install the Github App Integration for your organization. Read more.
@@             Coverage Diff             @@
##           develop    #2068      +/-   ##
===========================================
+ Coverage    70.10%   70.86%   +0.75%
===========================================
  Files          101      106       +5
  Lines         5084     5292     +208
  Branches       968     1026      +58
===========================================
+ Hits          3564     3750     +186
- Misses        1476     1505      +29
+ Partials        44       37       -7

see 52 files with indirect coverage changes

Looks like this works very similarly to Rambda's implementation, which seems good.
https://ramdajs.com/docs/#reduceWhile

(@OAGr, you posted this on a wrong PR, I'll respond here)
Ramda's predicate is more powerful: it takes both the accumulator and the current element. My version in this PR takes only acc. I guess we could add curr too, with the same trick as map's index, but we can do that later.


Investigate to Improve Error Reporting Upon Email Sending Failure at SignIn

Currently whenever a user tries to sign-in in to the platform we redirect them to the success page to say that the majic link is on its way.

However there are situations where the user don't actually get this email; for example due to Mailgun adding the email to the suppression list (it has been tried before and failed). However in these cases the user has no clue whether something is wrong. Maybe it would be nice if we could catch these errors from MailGun and show a generic error to the user like "Something went wrong, please contact<EMAIL_ADDRESS>This way the user doesn't have to re-try or wait for sometime before realizing the emails aren't arriving.

That's an interesting idea. Your proposal to display a generic error is good: we don't want to display errors straight from Mailgun as they could contain private information.
If we have a hook on the API to catch these errors, we may as well improve how we log them to make the investigation easier on the support side. A good first step would be to push them on Sentry, but if we want the rest of the support team to be able to access them we could create a dedicated (private) Slack channel and push the errors there (email/reason).


List of the tags in the documentation is not complete

/area documentation
What would you like to be added:
The documentation states that all tags added by default are in this list. This is not true as there are tags like file and mitre_* in the default rules file. You can update the sentence to say this is a subset of the tags or add all the tags to it.

Issues go stale after 90d of inactivity.
Mark the issue as fresh with /remove-lifecycle stale.
Stale issues rot after an additional 30d of inactivity and eventually close.
If this issue is safe to close now please do so with /close.
Provide feedback via https://github.com/falcosecurity/community.
/lifecycle stale

Stale issues rot after 30d of inactivity.
Mark the issue as fresh with /remove-lifecycle rotten.
Rotten issues close after an additional 30d of inactivity.
If this issue is safe to close now please do so with /close.
Provide feedback via https://github.com/falcosecurity/community.
/lifecycle rotten


All the things

how to even review this

Consider replacing the somewhat obscure .button() calls in RobotContainer with the more friendly .a() or .b() etc. We're using the XBoxController and PS4Controller classes now, so we have those conveniences. Makes the code much more readable too.

Smattering of TODO notes I have. Up to the team on what priority to rank these, they're just things I don't see in here currently.

Intake subsystem needs two additional motors added to it. These are for the star things. The two motors need to run invert of each other. The .follow() function can take an optional 2nd arg that's a boolean for "invert" so that's useful. For now I would say just drive that with midtake, doesn't need separate control

Consider putting up a generic shoot command for testing. In my demo branch I'm just using something like ...

        shoot_med.whileTrue(
            new StartEndCommand(
                () -> m_shooter.SetShooter(0.70),
                () -> m_shooter.SetShooter(0),
                m_shooter)
        );

The "flipIntake" thing is going to change again, most likely. We can chat about this more tomorrow. For now, I would recommend just mapping the manual raise / lower features to driver controller. That way all features can be exercised on one controller.

To lower the stress on the intake arm, they've added a spring
The spring is great, it should help the motor not be so stressed
The downside is that when you've nearly retracted the arm the spring is pulling in the same direction you're going. So your motor goes from fighting a counter force to being pulled along
Probably not a huge deal ? If we want it to move smoothly I'd recommend using the CAN Spark Max's built in PID system with position mode. Yay encoders.

Consider replacing the somewhat obscure .button() calls in RobotContainer with the more friendly .a() or .b() etc. We're using the XBoxController and PS4Controller classes now, so we have those conveniences. Makes the code much more readable too.

I'll do this.


docs: order of "Getting setup" in CONTRIBUTING.md

The yarn install shall precede yarn build, that's all...
Oh, and using ordinals in markdown ordered list is not needed, it just needs to be number, so I changed the ordinals to 1. everywhere, it is easier to maintain -- there is no need to reorder when changed.

Nice catch

Nice catch


📜 Multiple instances of image-builder fail to send logs to cloudwatch

We are seeing this error in OpenShift:
Failed to fire hook: InvalidSequenceTokenException: The given sequenceToken is invalid. The next expected sequenceToken is:<PHONE_NUMBER>9762469195597770664378024234801679062591571890
{
  RespMetadata: {
    StatusCode: 400,
    RequestID: "da491f7a-ae72-4317-b52b-5038030bfd19"
  },
  ExpectedSequenceToken: "49612946959762469195597770664378024234801679062591571890",
  Message_: "The given sequenceToken is invalid. The next expected sequenceToken is:<PHONE_NUMBER>9762469195597770664378024234801679062591571890"
}

The issue seems to be related to one of the pods sending a message and incrementing its log sequence token, but then the other pod sends a log with the old sequence token. More details are in this stack overflow post.

Asking in #sd-app-sre in Slack to find out what a solution should be.

Asking in #sd-app-sre in Slack to find out what a solution should be.

Fixed in #97, using the hostname (on openshift that results in the pod name, so image-builder-qwd9212) as stream. Having separate streams where each has it's own sequencetoken should fix the problem.

Fixed in #97, using the hostname (on openshift that results in the pod name, so image-builder-qwd9212) as stream. Having separate streams where each has it's own sequencetoken should fix the problem.


Couple of patches (Abandoned)

First patch is to adjust ssh command parameters and -f option
Second patch is for skipping cluster_expansion code.
Signed-off-by: gitsridhar<EMAIL_ADDRESS>

abandoned


Transfer this repo to a separate organization for better maintenance?

This is really a question for @tarruda and @faceleg.
What do you think about transferring this repo to my employer's github organization (https://github.com/mojotech)? It would result in more eyes on the development of the project and better maintenance than I can provide alone. I believe @faceleg's concerns of keeping this the canonical zsh autosuggest plugin would be solved by a redirect from this url to mojotech/zsh-autosuggestions.
More info on transferring Github repos: https://help.github.com/articles/transferring-a-repository/

I'm for it, but IMHO it is @tarruda's call

What about transferring instead to https://github.com/zsh-users , which already hosts and gives visibility to a lot of successful plugins?

It makes more sense to transfer this repo to zsh-users(which is a zsh-focused org), as suggested by @ronjouch.

Yeah, you're probably right. Should I reach out to zsh-users, or would you like to handle this @tarruda?

Pinging @nicoulaj. Thinking about bringing this plugin under zsh-users. Thoughts?

Of course this project is welcome in zsh-users.
@tarruda, you can transfer the project, and since you are already an owner of the organization, you just need to edit these two teams:

https://github.com/orgs/zsh-users/teams/zsh-autosuggestions-admins
https://github.com/orgs/zsh-users/teams/zsh-autosuggestions-committers

Pinging @tarruda... I'm happy to be an admin and keep maintaining this project. Will handle the cleanup after the repo's been transferred. I think we can just pull the trigger on this whenever.

Sorry for the delay, I ended up missing @nicoulaj's message. The repository is transfered :)

Nice, teams should be properly setup now.


PoC: implement syncer

What type of PR is this?
/area simulator
/kind feature

What this PR does / why we need it:
Implement syncer which keep copying the resources from the external kube-apiserver to the simulator's one.
It's based on https://github.com/kubernetes-sigs/kube-scheduler-simulator/pull/333 so that it won't be hard to rebase in the future.
Which issue(s) this PR fixes:

Fixes #327
Special notes for your reviewer:
/label tide/merge-method-squash

We are happy to take over this PR, but could you tell me what its status is?

Feel free to just take over by cherry pick or whatever

/close


add createDocumentFragment

We need to add fragment to reduce the overflow of dom.

I have released a new version: https://github.com/Nerzal/tinydom/releases/tag/v0.0.15

Thank you for the contribution! <3
You are the first one beside me! That is really cool!
:)

Good! When I think of other GO WASM client framework, I think Tinydom is a really cool project!


Automatic generation/assistance making release notes

Our current release notes are fairly brief, and focus on the main new features or significant changes in a release.
There is a variety of information that would be useful to include such as

dependency changes (mostly dependabot originated)
Enhancements
list of commits
API changes
type changes

In some cases we may wish to include this, in other cases point to a query
However to generate these automatically (at least as a draft to cut/paste) we need a more rigid process - documentation and enforcement through actions ie to

be able to easily list the PRs merged into a particular release
be able to consistently link back from a PR and/or commits to the relevant issues
more consistent and enforced tagging of issues and PRs (ie bugfix vs security vs enhancement)
Adding ability to pull in a short abstract from a PR/issue relevant to release notes
filtering - tech preview vs release vs development
.....

Opening as a future item to look at ....

needs to be considered as part of our release process -- leaving open for further discussion

needs to be considered as part of our release process -- leaving open for further discussion

still would be useful

I think the first part of this is to define what good release notes should contain, and look at possible GitHub queries to help
answer some of the 'what has changed' questions.
Only then could we look at how to automate some of the capture of that information

See https://github.blog/2021-10-04-beta-github-releases-improving-release-experience/
The release note generation can be tweaked via pull request labels  - for example I could group all the dependabot updates together, we could use an agreed label to eliminate irrelevant PRs, and we might be able to use other categories
As we go through this month I may add some new PR tags and annotate your PRs with such tags to see if this process is going to be useful for the github release notes which could be useful alongside our more manually curated notes


bug: Missing short_term_strategy input parameter in consolidation functions

When using one of the consolidation functions, e.g. get_best_ratings, internally the function get_scores_from_ratings will be called. This function accepts an input parameter called short_term_strategy.
However, get_best_ratings doesn't provide a comparable input parameter. As a result, get_scores_from_ratings will always work with the base strategy.
https://github.com/hsbc/pyratings/blob/717c635d3632edddd246978b1e85a57df674d63f/src/pyratings/consolidate.py#L26-L31
https://github.com/hsbc/pyratings/blob/717c635d3632edddd246978b1e85a57df674d63f/src/pyratings/consolidate.py#L83-L86
https://github.com/hsbc/pyratings/blob/717c635d3632edddd246978b1e85a57df674d63f/src/pyratings/get_scores.py#L152-L157
https://github.com/hsbc/pyratings/blob/717c635d3632edddd246978b1e85a57df674d63f/src/pyratings/get_scores.py#L308-L309

When consolidating short-term ratings, human-readable ratings will be translated into rating scores in order to do a meaningful comparison.
As we don't know anything about the corresponding long-term rating, it seems absolutely reasonable to go with base strategy. As a result, no consolidation function (get_best_ratings, get_second_best_ratings, and get_worst_ratings) needs the short_term_strategy parameter.


min_doc_count isn't respected outside of histogram aggregations

Describe the bug
The min_doc_count field on an aggregation isn't respected outside of histogram aggregations. This results in us getting fields with 0 hits back, despite us explicitly requesting a min_doc_count of 1 in our terms aggregation.
Requirements (place an x in each of the [ ])**

[X] I've read and understood the Contributing guidelines and have done my best effort to follow them.
[X] I've read and agree to the Code of Conduct.
[X] I've searched for any related issues and avoided creating a duplicate issue.

To Reproduce
Steps to reproduce the behavior:
0. Submit a query for a (non histogram) aggregation that returns multiple fields

Set the min_doc_count to be higher than one of the values
Observe the field still being returned in the aggregation

Expected behavior
An field with a value lower than min_doc_count is filtered out of an aggregation.
Screenshots
N/A
Reproducible in:
Astra version: All
JVM version: All
OS version(s): All
Additional context
N/A

@allcontributors please add @kyle-sammons for bug


Update evernote to 6.11_454874

After making all changes to the cask:

[x] brew cask audit --download {{cask_file}} is error-free.
[x] brew cask style --fix {{cask_file}} left no offenses.
[x] The commit message includes the cask’s name and version.

@giannitm can we have update title in the PR, as this is not a PR which is bumping the version up ?

@gobinathm I usually just leave it because this is what the cask-repair script sets the PR title as by default.