Windows issue

When I click RunAll under Windows I get
OSError: [WinError 123] The filename, directory name, or volume label syntax is incorrect: 'D:\\Tests\\RAVE/results/12-10-2023/woman_test/C:'
As if it always appends C: to the path for some reason that causes the script to fail.
Full error
Traceback (most recent call last):
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\queueing.py", line 456, in call_prediction
    output = await route_utils.call_process_api(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\route_utils.py", line 232, in call_process_api
    output = await app.get_blocks().process_api(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\blocks.py", line 1522, in process_api
    result = await self.call_function(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\blocks.py", line 1144, in call_function
    prediction = await anyio.to_thread.run_sync(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\anyio\to_thread.py", line 33, in run_sync
    return await get_asynclib().run_sync_in_worker_thread(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\anyio\_backends\_asyncio.py", line 877, in run_sync_in_worker_thread
    return await future
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\anyio\_backends\_asyncio.py", line 807, in run
    result = context.run(func, *args)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\utils.py", line 674, in wrapper
    response = f(*args, **kwargs)
  File "D:\Tests\RAVE\webui.py", line 114, in run
    input_ns = init_paths(input_ns)
  File "D:\Tests\RAVE\webui.py", line 34, in init_paths
    os.makedirs(save_dir, exist_ok=True)
  File "D:\Python\lib\os.py", line 215, in makedirs
    makedirs(head, exist_ok=exist_ok)
  File "D:\Python\lib\os.py", line 215, in makedirs
    makedirs(head, exist_ok=exist_ok)
  File "D:\Python\lib\os.py", line 215, in makedirs
    makedirs(head, exist_ok=exist_ok)
  [Previous line repeated 5 more times]
  File "D:\Python\lib\os.py", line 225, in makedirs
    mkdir(name, mode)
OSError: [WinError 123] The filename, directory name, or volume label syntax is incorrect: 'D:\\Tests\\RAVE/results/12-10-2023/woman_test/C:'
Traceback (most recent call last):
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\queueing.py", line 456, in call_prediction
    output = await route_utils.call_process_api(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\route_utils.py", line 232, in call_process_api
    output = await app.get_blocks().process_api(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\blocks.py", line 1522, in process_api
    result = await self.call_function(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\blocks.py", line 1144, in call_function
    prediction = await anyio.to_thread.run_sync(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\anyio\to_thread.py", line 33, in run_sync
    return await get_asynclib().run_sync_in_worker_thread(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\anyio\_backends\_asyncio.py", line 877, in run_sync_in_worker_thread
    return await future
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\anyio\_backends\_asyncio.py", line 807, in run
    result = context.run(func, *args)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\utils.py", line 674, in wrapper
    response = f(*args, **kwargs)
  File "D:\Tests\RAVE\webui.py", line 114, in run
    input_ns = init_paths(input_ns)
  File "D:\Tests\RAVE\webui.py", line 34, in init_paths
    os.makedirs(save_dir, exist_ok=True)
  File "D:\Python\lib\os.py", line 215, in makedirs
    makedirs(head, exist_ok=exist_ok)
  File "D:\Python\lib\os.py", line 215, in makedirs
    makedirs(head, exist_ok=exist_ok)
  File "D:\Python\lib\os.py", line 215, in makedirs
    makedirs(head, exist_ok=exist_ok)
  [Previous line repeated 5 more times]
  File "D:\Python\lib\os.py", line 225, in makedirs
    mkdir(name, mode)
OSError: [WinError 123] The filename, directory name, or volume label syntax is incorrect: 'D:\\Tests\\RAVE/results/12-10-2023/woman_test/C:'

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\queueing.py", line 501, in process_events
    response = await self.call_prediction(awake_events, batch)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\queueing.py", line 465, in call_prediction
    raise Exception(str(error) if show_error else None) from error
Exception: None

bump - same

Thank you for your interest and opening issue, we are working on the demo to be able to run in Windows, and the instructions for Windows will be available soon. We would suggest you to use Linux OS.

New error now.  When I click Run All I get these errors.
Do I need to manually download some models?
C:\Users\Jason\AppData\Local\Temp\gradio\8aad7b5c09060a0858874df8fd3cce2a390d68b2\wolf.mp4
Frame count: 4
vae\diffusion_pytorch_model.safetensors not found
Traceback (most recent call last):
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\queueing.py", line 456, in call_prediction
    output = await route_utils.call_process_api(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\route_utils.py", line 232, in call_process_api
    output = await app.get_blocks().process_api(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\blocks.py", line 1522, in process_api
    result = await self.call_function(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\blocks.py", line 1144, in call_function
    prediction = await anyio.to_thread.run_sync(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\anyio\to_thread.py", line 33, in run_sync
    return await get_asynclib().run_sync_in_worker_thread(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\anyio\_backends\_asyncio.py", line 877, in run_sync_in_worker_thread
    return await future
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\anyio\_backends\_asyncio.py", line 807, in run
    result = context.run(func, *args)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\utils.py", line 674, in wrapper
    response = f(*args, **kwargs)
  File "D:\Tests\RAVE\webui.py", line 132, in run
    CN.init_models(input_ns.hf_cn_path, input_ns.hf_path, input_ns.preprocess_name, input_ns.model_id)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "D:\Tests\RAVE\pipelines\sd_controlnet_rave.py", line 49, in init_models
    pipe = self.__init_pipe(hf_cn_path, hf_path)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "D:\Tests\RAVE\pipelines\sd_controlnet_rave.py", line 43, in __init_pipe
    pipe.enable_xformers_memory_efficient_attention()
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\pipelines\pipeline_utils.py", line 1442, in enable_xformers_memory_efficient_attention
    self.set_use_memory_efficient_attention_xformers(True, attention_op)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\pipelines\pipeline_utils.py", line 1468, in set_use_memory_efficient_attention_xformers
    fn_recursive_set_mem_eff(module)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\pipelines\pipeline_utils.py", line 1458, in fn_recursive_set_mem_eff
    module.set_use_memory_efficient_attention_xformers(valid, attention_op)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\models\modeling_utils.py", line 227, in set_use_memory_efficient_attention_xformers
    fn_recursive_set_mem_eff(module)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\models\modeling_utils.py", line 223, in fn_recursive_set_mem_eff
    fn_recursive_set_mem_eff(child)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\models\modeling_utils.py", line 223, in fn_recursive_set_mem_eff
    fn_recursive_set_mem_eff(child)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\models\modeling_utils.py", line 223, in fn_recursive_set_mem_eff
    fn_recursive_set_mem_eff(child)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\models\modeling_utils.py", line 220, in fn_recursive_set_mem_eff
    module.set_use_memory_efficient_attention_xformers(valid, attention_op)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\models\modeling_utils.py", line 227, in set_use_memory_efficient_attention_xformers
    fn_recursive_set_mem_eff(module)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\models\modeling_utils.py", line 223, in fn_recursive_set_mem_eff
    fn_recursive_set_mem_eff(child)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\models\modeling_utils.py", line 223, in fn_recursive_set_mem_eff
    fn_recursive_set_mem_eff(child)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\models\modeling_utils.py", line 220, in fn_recursive_set_mem_eff
    module.set_use_memory_efficient_attention_xformers(valid, attention_op)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\models\attention_processor.py", line 192, in set_use_memory_efficient_attention_xformers
    raise ModuleNotFoundError(
ModuleNotFoundError: Refer to https://github.com/facebookresearch/xformers for more information on how to install xformers
Traceback (most recent call last):
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\queueing.py", line 456, in call_prediction
    output = await route_utils.call_process_api(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\route_utils.py", line 232, in call_process_api
    output = await app.get_blocks().process_api(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\blocks.py", line 1522, in process_api
    result = await self.call_function(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\blocks.py", line 1144, in call_function
    prediction = await anyio.to_thread.run_sync(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\anyio\to_thread.py", line 33, in run_sync
    return await get_asynclib().run_sync_in_worker_thread(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\anyio\_backends\_asyncio.py", line 877, in run_sync_in_worker_thread
    return await future
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\anyio\_backends\_asyncio.py", line 807, in run
    result = context.run(func, *args)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\utils.py", line 674, in wrapper
    response = f(*args, **kwargs)
  File "D:\Tests\RAVE\webui.py", line 132, in run
    CN.init_models(input_ns.hf_cn_path, input_ns.hf_path, input_ns.preprocess_name, input_ns.model_id)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "D:\Tests\RAVE\pipelines\sd_controlnet_rave.py", line 49, in init_models
    pipe = self.__init_pipe(hf_cn_path, hf_path)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "D:\Tests\RAVE\pipelines\sd_controlnet_rave.py", line 43, in __init_pipe
    pipe.enable_xformers_memory_efficient_attention()
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\pipelines\pipeline_utils.py", line 1442, in enable_xformers_memory_efficient_attention
    self.set_use_memory_efficient_attention_xformers(True, attention_op)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\pipelines\pipeline_utils.py", line 1468, in set_use_memory_efficient_attention_xformers
    fn_recursive_set_mem_eff(module)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\pipelines\pipeline_utils.py", line 1458, in fn_recursive_set_mem_eff
    module.set_use_memory_efficient_attention_xformers(valid, attention_op)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\models\modeling_utils.py", line 227, in set_use_memory_efficient_attention_xformers
    fn_recursive_set_mem_eff(module)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\models\modeling_utils.py", line 223, in fn_recursive_set_mem_eff
    fn_recursive_set_mem_eff(child)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\models\modeling_utils.py", line 223, in fn_recursive_set_mem_eff
    fn_recursive_set_mem_eff(child)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\models\modeling_utils.py", line 223, in fn_recursive_set_mem_eff
    fn_recursive_set_mem_eff(child)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\models\modeling_utils.py", line 220, in fn_recursive_set_mem_eff
    module.set_use_memory_efficient_attention_xformers(valid, attention_op)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\models\modeling_utils.py", line 227, in set_use_memory_efficient_attention_xformers
    fn_recursive_set_mem_eff(module)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\models\modeling_utils.py", line 223, in fn_recursive_set_mem_eff
    fn_recursive_set_mem_eff(child)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\models\modeling_utils.py", line 223, in fn_recursive_set_mem_eff
    fn_recursive_set_mem_eff(child)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\models\modeling_utils.py", line 220, in fn_recursive_set_mem_eff
    module.set_use_memory_efficient_attention_xformers(valid, attention_op)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\diffusers\models\attention_processor.py", line 192, in set_use_memory_efficient_attention_xformers
    raise ModuleNotFoundError(
ModuleNotFoundError: Refer to https://github.com/facebookresearch/xformers for more information on how to install xformers

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\queueing.py", line 501, in process_events
    response = await self.call_prediction(awake_events, batch)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\queueing.py", line 465, in call_prediction
    raise Exception(str(error) if show_error else None) from error
Exception: None

it seems that you have not properly installed 'xformers' library to your environment. Please run
pip install xformers==0.0.20
to install it.

OK, thanks, that worked.  Got a bit further.  The model downloaded OK, then this error
zoedepth key error?
Traceback (most recent call last):
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\queueing.py", line 456, in call_prediction
    output = await route_utils.call_process_api(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\route_utils.py", line 232, in call_process_api
    output = await app.get_blocks().process_api(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\blocks.py", line 1522, in process_api
    result = await self.call_function(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\blocks.py", line 1144, in call_function
    prediction = await anyio.to_thread.run_sync(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\anyio\to_thread.py", line 33, in run_sync
    return await get_asynclib().run_sync_in_worker_thread(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\anyio\_backends\_asyncio.py", line 877, in run_sync_in_worker_thread
    return await future
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\anyio\_backends\_asyncio.py", line 807, in run
    result = context.run(func, *args)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\utils.py", line 674, in wrapper
    response = f(*args, **kwargs)
  File "D:\Tests\RAVE\webui.py", line 143, in run
    res_vid, control_vid = CN(input_dict)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "D:\Tests\RAVE\pipelines\sd_controlnet_rave.py", line 399, in __call__
    img_batch, control_batch = self.process_image_batch(input_dict['image_pil_list'])
  File "D:\Tests\RAVE\pipelines\sd_controlnet_rave.py", line 311, in process_image_batch
    control_pil = self.preprocess_control_grid(image_pil)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "D:\Tests\RAVE\pipelines\sd_controlnet_rave.py", line 140, in preprocess_control_grid
    list_of_pils = [pu.pixel_perfect_process(np.array(frame_pil, dtype='uint8'), self.preprocess_name) for frame_pil in list_of_image_pils]
  File "D:\Tests\RAVE\pipelines\sd_controlnet_rave.py", line 140, in <listcomp>
    list_of_pils = [pu.pixel_perfect_process(np.array(frame_pil, dtype='uint8'), self.preprocess_name) for frame_pil in list_of_image_pils]
  File "D:\Tests\RAVE\utils\preprocesser_utils.py", line 211, in pixel_perfect_process
    detected_map, _ = preprocessors_dict[p_name](input_image, res=preprocessor_resolution)
  File "D:\Tests\RAVE\utils\preprocesser_utils.py", line 187, in zoe_depth
    result = model_zoe_depth(img)
  File "D:\Tests\RAVE\annotator\zoe\__init__.py", line 38, in __call__
    self.load_model()
  File "D:\Tests\RAVE\annotator\zoe\__init__.py", line 26, in load_model
    conf = get_config("zoedepth", "infer")
  File "D:\Tests\RAVE\annotator\zoe\zoedepth\utils\config.py", line 384, in get_config
    version_name = overwrite_kwargs.get("version_name", config["version_name"])
KeyError: 'version_name'
Traceback (most recent call last):
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\queueing.py", line 456, in call_prediction
    output = await route_utils.call_process_api(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\route_utils.py", line 232, in call_process_api
    output = await app.get_blocks().process_api(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\blocks.py", line 1522, in process_api
    result = await self.call_function(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\blocks.py", line 1144, in call_function
    prediction = await anyio.to_thread.run_sync(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\anyio\to_thread.py", line 33, in run_sync
    return await get_asynclib().run_sync_in_worker_thread(
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\anyio\_backends\_asyncio.py", line 877, in run_sync_in_worker_thread
    return await future
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\anyio\_backends\_asyncio.py", line 807, in run
    result = context.run(func, *args)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\utils.py", line 674, in wrapper
    response = f(*args, **kwargs)
  File "D:\Tests\RAVE\webui.py", line 143, in run
    res_vid, control_vid = CN(input_dict)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "D:\Tests\RAVE\pipelines\sd_controlnet_rave.py", line 399, in __call__
    img_batch, control_batch = self.process_image_batch(input_dict['image_pil_list'])
  File "D:\Tests\RAVE\pipelines\sd_controlnet_rave.py", line 311, in process_image_batch
    control_pil = self.preprocess_control_grid(image_pil)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "D:\Tests\RAVE\pipelines\sd_controlnet_rave.py", line 140, in preprocess_control_grid
    list_of_pils = [pu.pixel_perfect_process(np.array(frame_pil, dtype='uint8'), self.preprocess_name) for frame_pil in list_of_image_pils]
  File "D:\Tests\RAVE\pipelines\sd_controlnet_rave.py", line 140, in <listcomp>
    list_of_pils = [pu.pixel_perfect_process(np.array(frame_pil, dtype='uint8'), self.preprocess_name) for frame_pil in list_of_image_pils]
  File "D:\Tests\RAVE\utils\preprocesser_utils.py", line 211, in pixel_perfect_process
    detected_map, _ = preprocessors_dict[p_name](input_image, res=preprocessor_resolution)
  File "D:\Tests\RAVE\utils\preprocesser_utils.py", line 187, in zoe_depth
    result = model_zoe_depth(img)
  File "D:\Tests\RAVE\annotator\zoe\__init__.py", line 38, in __call__
    self.load_model()
  File "D:\Tests\RAVE\annotator\zoe\__init__.py", line 26, in load_model
    conf = get_config("zoedepth", "infer")
  File "D:\Tests\RAVE\annotator\zoe\zoedepth\utils\config.py", line 384, in get_config
    version_name = overwrite_kwargs.get("version_name", config["version_name"])
KeyError: 'version_name'

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\queueing.py", line 501, in process_events
    response = await self.call_prediction(awake_events, batch)
  File "D:\Tests\RAVE\voc_rave\lib\site-packages\gradio\queueing.py", line 465, in call_prediction
    raise Exception(str(error) if show_error else None) from error
Exception: None

@SoftologyPro Hey, could you please pull and try? I realized that I missed the json files required for depthzoe, now it should work. Thanks

OK, getting further now.  It would be good to have an x/y steps for these stats.
img_size [384, 512]
img_size [384, 512]
img_size [384, 512]
img_size [384, 512]
img_size [384, 512]
img_size [384, 512]
img_size [384, 512]
img_size [384, 512]
img_size [384, 512]
img_size [384, 512]
img_size [384, 512]
img_size [384, 512]

It is now at a stage that has an estimated 1 hour to go?  Is this normal?  I will let it run and see if it completes.
  5%|███████████▌           | 1/20 [03:21<1:03:41, 201.13s/it]

hey @SoftologyPro it is not normal, it is taking around 1-2s/it at most for the wolf video (512x512 sized video). I think you might be using CPU instead of GPU/CUDA.

I thought so too at first, but CPU is 2% and GPU is pegged at 100%.
Still going here
| 12/20 [42:04<28:09, 211.16s/it]
I've got xformers, accelerate and GPU torch.

what gpu are you using?

4090 24 GB

Wait, I just rebooted and restarted the wolf.  Now only 7 minutes estimated.  17.22s/it

hey, here I am also using 4090 with 24 gbs, here it's around 3s/it. Maybe could you try increasing the batch size?

hey, here I am also using 4090 with 24 gbs, here it's around 3s/it. Maybe could you try increasing the batch size?

  That is the default.

Raising batch size to 10 does not seem to help the speed.
Anyway, it works now.  I will do some tetsts on other PCs.

Feel free to do tests, I am closing the issue.


Added ValidateAspNetCoreUrls

This pull request introduces a validation check for the ASPNETCORE_URLS environment variable to ensure it is in the correct format before starting the engine in the Program class. This change helps in preventing runtime errors due to misconfigured URLs.
Key changes:

Added a new method ValidateAspNetCoreUrls to check the format of the ASPNETCORE_URLS environment variable. This method splits the environment variable by commas or semicolons and ensures each part is a valid absolute URI.
Integrated the ValidateAspNetCoreUrls method into the Main method to validate the URLs before proceeding with the engine start. If the validation fails, an error message is printed, and the application exits with an error code.

Why make this change?
The primary motivation is to return a more clear error message to the user.
Closes #2465
What is this change?
Startup validation.
How was this tested?

[ ] Integration Tests
[ ] Unit Tests

Sample Request(s)
Valid value in END file: ASPNETCORE_URLS="http://localhost:5000;https://localhost:5001"
Invalid value in END file: ASPNETCORE_URLS=http://localhost:5000;https://localhost:5001

@JerryNixon , you can run dotnet format command to fix formatting issues

/azp run

The failing unit test appears to be caused by stale environment variables from one test causing another to fail due to the new validation, when that test expects the program main function to work.
I was able to get the pipeline to pass on another branch (https://github.com/Azure/data-api-builder/tree/dev/aaronburtle/ASP_URL_DEBUGG) by adding in the Environment variable that you are validating to the Environment variable clearing helper function in testhelper.
https://dev.azure.com/sqldab/Data API builder Dependency Packages/_build/results?buildId=7640&view=results
This is the change the seemed to fix it, which also requires that the environment variable constant be moved to the class as a public field so we can borrow its use for testhelper.

/azp run

/azp run


Use PHPStan 2.0

👉🏻 3.x

Oh wow, this is dependency hell 😢 Can we workaround somehow? 🤔

This may be enough: https://github.com/rectorphp/rector/issues/8815

This may be enough: rectorphp/rector#8815

I don't think they will do it soon. It's a huge change. Also they'll need to release Rector 2.0, then spatie/laravel-ray needs to update their code and then workbench needs to update their code.. So we need another solution for now. I'll think about it.

We can add
"replace": {
  "rector/rector": "*"
},

just before installing the dependencies 🤷🏽 Very ugly hack

Fixed in the branch.


robustify handling of NAs in truncation calculate()

an NA in the range or the value of the random variable will trigger an error in R calculate and a -Inf in C calculate when using T(). This really only affects the model checking stage if a data or initial value involved in the range or the value of the random variable is NA.
Perry's suggestion: Another idea is we could make a function like “nimRangeCheck” and replace if(1 <= model$x & model$x <= 2) with nimRangeCheck(model$x, 1, 2), and have that return FALSE if model$x is NA.

Haven't yet addressed this. Moving to nimbleCoreTeam.


Prohibit Generative AI from learning on Terms of Service,

This is not bug but urgent agenda so I created this issue as 'bug'.
Twitter/X is in talks with Midjourney for a potential partnership. No arts on Twitter/X will be protected.
https://twitter.com/cb_doge/status/1759798475959771493
At least, it is desirable to protect arts on Bluesky by Terms of Service.
https://bsky.social/about/support/tos

What does "art" mean? Does it mean only pictures?
If Generative AI is broadly banned, for example, bots or feeds that learn texts posted on Bluesky could also be banned.
Even if it were to be prohibited, the scope should be more restricted.

Isn't this already protected by 2(c) and 2(d)?
Bluesky doesn't have the license to provide material to third parties for the purposes of anything except "(a) providing Bluesky Social and Content, including by sharing User Content throughout Bluesky Social and the AT Protocol as well as developing and improving our current and future offerings; and (b) promoting and marketing Bluesky and Bluesky Social."

The terms of service defines an agreement between you and and Bluesky. As far as Bluesky is concerned, the things listed above is the only thing they've been granted with as per terms.
The art remains yours.

https://github.com/bluesky-social/atproto/discussions/2536#discussioncomment-11392423
Can we do a ToS revision to prohibit AI scraping?

If any ToS revision is made it would have to be very carefully worded. I would not want to see any ToS revision prohibit the use of tools such as @aendra-rininsland's excellent XBlock, for example, which uses machine learning to categorise screenshots.

I think prohibiting only "publishing" data (for example, on Hugging Face) is sufficiently effective. Although this may be already prohibited.


Web sockets not working

I had install the aria2 and enter the web https://ziahamza.github.io/webui-aria2/
it shows me this, help me out pls!!
Web sockets not working due to Failed to construct 'WebSocket': An insecure WebSocket connection may not be initiated from a page loaded over HTTPS.

有一个想法，在github和stackoverflow开个中文板块出来。

Basically 3 ways:

Use http://ziahamza.github.io/webui-aria2/ (HTTP instead of HTTPS)

If you use HTTPS Everywhere, you can disable it for github.io.

your own server

Nginx
Apache
Fork this project and create CNAME-d GitHub pages. Using CNAME since you are not using HTTP on github.io.
e.t.c.

Configure your aria2 to be compatible with WebSocket with Security.

Need a domain and an SSL certificate

Reason described:
It's because it is considered unsafe and information leaking to use WebSocket on HTTPS pages. (Considered by those who created HTTPS)


[SPARK-38725][SQL][TESTS] Test the error class: DUPLICATE_KEY

What changes were proposed in this pull request?
This pr aims to Add one test for the error class DUPLICATE_KEY to QueryParsingErrorsSuite, it's a followup of SPARK-37935.
Why are the changes needed?
Add one test for the error class DUPLICATE_KEY to QueryParsingErrorsSuite
Does this PR introduce any user-facing change?
No
How was this patch tested?

Manual test：

./build/sbt "sql/testOnly *QueryParsingErrorsSuite*"

All tests passed.

Can one of the admins verify this patch?

@panbingkun BTW, it is better to follow the guide: https://spark.apache.org/contributing.html and create a separate branch for the PR, see:
Below steps will take your through the process.
3. Clone your fork and create a new branch
8. Open a pull request against the master branch of apache/spark

new pr: https://github.com/apache/spark/pull/36188, please review, Thanks


UAF avoidance in init_thread_deregister()

I discovered the potential for use-after-free on glob_tevent_reg & its members in this function as a consequence of some static (de-)initialization fiasco in C++ client code.
Long story short, an EVP_PKEY_free() was happening after OPENSSL_cleanup(). Aside from being freed the EVP_PKEY object wasn't actually being used after cleanup, it was basically just an ordering issue.
Obviously the application behavior here is somewhat suspect, but IMO is basically benign. Crashing (most typical outcome of a UAF) doesn't seem the optimal response.
At any rate, the issue can be avoided (at least with regard to this function) by simply updating the pointer to NULL rather than leaving it pointing to the freed memory, as is the typical practice.

AppVeyor failure is unrelated.

24 hours has passed since 'approval: done' was set, but this PR has failing CI tests.  Once the tests pass it will get moved to 'approval: ready to merge' automatically, alternatively please review and set the label manually.

This pull request is ready to merge

Merged, thank you for the PR.


GUI Test

OpenBMC GUI Automation associated with https://github.com/openbmc/openbmc/issues/266

Basic GUI done and we will open individual GUI issues / enhancement.


Scrolling to bottom of Interactive Window with lots of unrendered cells is buggy.

Related to https://github.com/microsoft/vscode/issues/131732, though it's possible to cause this issue on demand by manipulating where the interactive window is scrolled to as execution happens.

Setup for bug https://github.com/microsoft/vscode/issues/131732.
Let it execute all the way through. At this point I assume that you will not be scrolled to the bottom of the IW due to the bug in 131732.

Manually scroll the window via the scrollbar thumb to the last executed cell of the IW.
If I'm seeing it right (as it flashes a bunch) you will get to the end of the executions, but then you'll be repositioned much higher after a fraction of a second. My guess is that VS Code is optimizing to not render plots if they haven't yet been scrolled to. As these plots are pulled into view, is mucks with the known length of the total output and screws up the intention of the scroll.
While this isn't a killer issue, it is rather annoying. I find myself having to scroll to the bottom multiple times to actually get to the bottom. That being said, if 131732 is fixed, then it probably would have less chance to happen as much.

Thanks for creating this issue! We figured it's covering the same as another one we already have. Thus, we closed this one as a duplicate. You can search for similar existing issues. See also our issue reporting guidelines.
Happy Coding!


Update README.md

I believe those two pieces of code should be swapped. Otherwise, it will not compile.

 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.


Add reason weight to Posts API

@angussidney suggested to add the reason weight to the Autoflagging Information script. I'd love to do that, but it needs to be exposed in the API. It could be that the field score is the one I need, but currently it always returns null.

score is not the field you are looking for.

I'm curious to what it is then. That also makes this a feature-request.

Originally intends to store the post score, but we don't use it.


mixin: Fix latency alerts

This PR changes tail latecy alert behaviour to alert on the rate of change rather than absolute value.

[ ] I added CHANGELOG entry for this change.
[ ] Change is not relevant to the end user.

cc @brancz @metalmatze
Changes

Fix latency alerts.

Verification

make examples
make example-rules-lint

This PR doesn't touch anything that e2e tests test. It' ok to move on.

:+1: IMO this PR had enough :eyes:  so merging


Heroku "Can't find model 'en'"

Hi Gunther, while my chatbot is working great on my local computer, I'm having trouble deploying it to heroku. Here are the relevant package version:
chatterbot==1.0.8
chatterbot-corpus==1.2.0
python==3.6
spacy==2.3.2
I've tried putting this in my Procfile:
python -m spacy link en_core_web_md en
I've tried forking Chatterbot and changing this line:
self.nlp = spacy.load(self.language.ISO_639_1.lower())
to:
self.nlp = spacy.load('en_core_web_sm')
I always get this error (seen in Heroku log):
2020-10-05T22:47:26.185483+00:00 app[web.1]:   File "/app/rc/chat/bot.py", line 22, in <module>
2020-10-05T22:47:26.185484+00:00 app[web.1]:     'chatterbot.logic.TimeLogicAdapter',
2020-10-05T22:47:26.185484+00:00 app[web.1]:   File "/app/.heroku/python/lib/python3.6/site-packages/chatterbot/chatterbot.py", line 28, in __init__
2020-10-05T22:47:26.185484+00:00 app[web.1]:     self.storage = utils.initialize_class(storage_adapter, **kwargs)
2020-10-05T22:47:26.185485+00:00 app[web.1]:   File "/app/.heroku/python/lib/python3.6/site-packages/chatterbot/utils.py", line 33, in initialize_class
2020-10-05T22:47:26.185485+00:00 app[web.1]:     return Class(*args, **kwargs)
2020-10-05T22:47:26.185485+00:00 app[web.1]:   File "/app/.heroku/python/lib/python3.6/site-packages/chatterbot/storage/sql_storage.py", line 20, in __init__
2020-10-05T22:47:26.185486+00:00 app[web.1]:     super().__init__(**kwargs)
2020-10-05T22:47:26.185486+00:00 app[web.1]:   File "/app/.heroku/python/lib/python3.6/site-packages/chatterbot/storage/storage_adapter.py", line 21, in __init__
2020-10-05T22:47:26.185487+00:00 app[web.1]:     'tagger_language', languages.ENG
2020-10-05T22:47:26.185487+00:00 app[web.1]:   File "/app/.heroku/python/lib/python3.6/site-packages/chatterbot/tagging.py", line 13, in __init__
2020-10-05T22:47:26.185487+00:00 app[web.1]:     self.nlp = spacy.load(self.language.ISO_639_1.lower())
2020-10-05T22:47:26.185488+00:00 app[web.1]:   File "/app/.heroku/python/lib/python3.6/site-packages/spacy/__init__.py", line 30, in load
2020-10-05T22:47:26.185488+00:00 app[web.1]:     return util.load_model(name, **overrides)
2020-10-05T22:47:26.185488+00:00 app[web.1]:   File "/app/.heroku/python/lib/python3.6/site-packages/spacy/util.py", line 175, in load_model
2020-10-05T22:47:26.185489+00:00 app[web.1]:     raise IOError(Errors.E050.format(name=name))
2020-10-05T22:47:26.185490+00:00 app[web.1]: OSError: [E050] Can't find model 'en'. It doesn't seem to be a shortcut link, a Python package or a valid path to a data directory.

Any help would be much appreciated.

I think it's working.
My requirements.txt has this instead of chatterbot:
git+git://github.com/riverscuomo/ChatterBot.git#egg=ChatterBot
This fork has this line:
self.nlp = spacy.load(self.language.ISO_639_1.lower())
to:
self.nlp = spacy.load('en_core_web_sm')
Also in requirements I put:
spacy>=2.1,<2.2
https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-2.1.0/en_core_web_sm-2.1.0.tar.gz#egg=en_core_web_sm
nltk==3.5

if i use pip installed chatterbot, does this mean I need change to use source code?

@OhnkytaBlabdey Yes. I forked the source code and changed line 26 in the tagging.py file. Here's the file:
https://github.com/riverscuomo/ChatterBot/blob/master/chatterbot/tagging.py
You can add a similar line for any language you want. For example, Chinese would be:
self.nlp = spacy.load('zh_core_web_sm')
You can find the names for different language models here:
https://spacy.io/usage


Hi, how can I move more than one face of a 3D object with a single instruction, already knowing which face IDs I want to move?

Hi @enrique-rc ,
You have 2 options right now.

 In a loop you will move all the faces you needed.

For now it is not implemented MoveFaces as it is in the API, where you could add a list with ID Faces. But you could use the AEDT API command directly:
oEditor = aedtapp.modeler.oeditor
#AEDT API Command
oEditor.MoveFaces(
[
"NAME:Selections",
"Selections:="		, "Cylinder8",
"NewPartsModelFlag:="	, "Model"
],
[
"NAME:Parameters",
[
"NAME:MoveFacesParameters",
"MoveAlongNormalFlag:="	, True,
"OffsetDistance:="	, "1mm",
"MoveVectorX:="		, "0mm",
"MoveVectorY:="		, "0mm",
"MoveVectorZ:="		, "0mm",
"FacesToMove:="		, [421,423]
]
])

We will think about including it in the future.
Let me know if it works for your case.

hi @Samuelopez-ansys ,
In my case, moving faces one by one with method 1 deforms the object in such way that it causes the modeler to fail. I will stick with method 2 then.
Thank you for you support.

Hi @enrique-rc ,
I have added a new method, it is in the last main version:
aedtapp.modeler.move_face(face_list, offset)
face_list could be a list or not of Faces ID  or also the type pyaedt.modeler.Object3d.FacePrimitive. Both will work.
I will close the issue. Thanks


🐛 Bug Report: The issue of AWS Code Commit integration

📜 Description
First of all, thank you so much for creating the AWS Codecommit Integration feature.
I tried this feature as soon as it was released and I found one problem.
In the link below, config.host is forced to console.aws.amazon.com, so, If I set repoContentsUrl to {region}.console.aws.amazon.com in the catalog:register action, No Integration error occurs.
https://github.com/stijnbrouwers/backstage/blob/master/packages/integration/src/awsCodeCommit/config.ts#L67
Instead, if I remove the region from the url, an error occurs due to the link below.
https://github.com/stijnbrouwers/backstage/blob/master/packages/backend-common/src/reading/AwsCodeCommitUrlReader.ts#L70
I think it should be changed to load the host from config instead of forcefully assigning it in the first link.
👍 Expected behavior
I think the steps below should succeed.
  input:
    catalogInfoPath: .backstage/catalog-info.yaml
    repoContentsUrl: https://ap-northeast-2.console.aws.amazon.com/codesuite/codecommit/repositories/test-repo/browse/--/

👎 Actual Behavior with Screenshots
InputError: No integration found for host https://ap-northeast-2.console.aws.amazon.com/codesuite/codecommit/repositories/test-repo/browse/refs/heads/main/--/catalog-info.yaml
👟 Reproduction steps

make simple template
add Register step like below

id: register
name: Register2
action: catalog:register
input:
catalogInfoPath: .backstage/catalog-info.yaml
repoContentsUrl: https://ap-northeast-2.console.aws.amazon.com/codesuite/codecommit/repositories/test-repo/browse/--/

📃 Provide the context for the Bug.
No response
🖥 Your Environment
backstage : v1.26.5
@backstage/backend-common: 0.21.6
@backstage/integration: 1.10.0
👀 Have you spent some time to check if this bug has been raised before?

[X] I checked and didn't find similar issue

🏢 Have you read the Code of Conduct?

[X] I have read the Code of Conduct

Are you willing to submit PR?
None

I created a PR that can be modified. (https://github.com/backstage/backstage/pull/24771)

I think this issue can be closed due to #24843 ...


[Enhancement] Use a template extension instead of the actual filetype

Writing a template with invalid syntax causes the file to have show up with diagnostic errors and syntax highlighting errors etc. Would you consider using something like main.go.template so that the file type isn't triggered as go and that LSPs and syntax highlighting don't explode.
Alternatively, this plugin could automatically register an autocommand on BufRead of the template dir files and use vim.diagnostic.disable but this won't disable weird syntax highlighting.

good question. I had think about use a new extension to avoid the diagnostic and i found i just edit template once or twice. so I think i can ignore diagnostic . there has two ways

use tmpl or tpl extension
like you said. use autocmd filetype check file path string if match template dir then disable diagnostic. I think this way you can do it on your config

@glepnir so I added the second way in my config but tbh I still have a bunch of treesitter syntax errors and disabling via vim.diagnostic does not turn off everything. Also I just think fundamentally the file isn't a valid x filetype so should not behave as a filetype. I think looking at a file in my templates' directory in my config in nvim should show up without the same highlighting. Would be nice if there was template highlighting but tbh this is completely out of scope

looks like works fine with me .  currently I work on lspsaga outline (80%) when I finished I will recheck it .

@glepnir I guess you disable TSError highlight, but I don't so that still shows up, also in your screenshot you will notice that even after you disable your statusline still shows the error count for the buffer.

I guess I can ignore the TSError highlight and maybe the vim.diagnostic behaviour is an upstream bug. Seems like having to work around all this stuff though 🤔

I think I found a way to do it .

@akinsho  how do you config temp dir use os.getenv('home') or ~

Something like vim.fn.expand('~/.dotfiles')..rest_of_the_path

Please test .should be works fine

oh use vim.diagnostic.disable will be better

it works. but statusline still show diagnostic info . maybe can ignore ?

@glepnir it's really not a big deal, just a minor annoyance. I guess I don't spend much time in that file, it's just that all diagnostics are always present so now in my config looking at diagnostics in qf always shows errors. I'll see if there's a better way to ignore them

use a new extension it will solve all problem but need add highlight for all filetype

Yeah, I imagine that will be a fair bit of work maybe 🤔 maybe it can be done without syntax highlighting for the underlying filetype just using :syntax and highlighting only the template variables/syntax, or maybe it can inherit vim's :syntax for the filetype and just add extensions for the template syntax
e.g.
" syntax/template
exe 'runtime! syntax/'.ft.'.vim'
syntax match " blah blah I'm not a syntax expert 😅

Well, you would need to be able to inject ft somehow


Lemon Leak tutorial - not able to close Hint window

On the 2nd step of the Lemon Leak tutorial, I can't close the Hint window, even when clicking on Workspace or Hint icon

This is on Edge

Also, sometimes in that 2nd step in other Tutorials, when I click on the Hint icon, the Hint window does not open.


chore(master): release 0.23.0

:robot: I have created a release beep boop
0.23.0 (2023-05-03)
Features

upgrade bee to v1.15.0 (#341) (004b075)

This PR was generated with Release Please. See documentation.

:robot: Release is at https://github.com/ethersphere/swarm-desktop/releases/tag/untagged-ed6aef5e7919f9ea430c :sunflower:


feat: Update algolia cli to use env vars

https://asaphub.atlassian.net/jira/software/c/projects/CRN/boards/6

@peterstarling Please add the Jira task ID

turns out its not possible


Add device as constructor arg to QuantumCircuit

Let's just manually take care of the the devices of input tensors/models like its usually done in pytorch or use torch.set_default_device


Build a separate Article migration path

A separate tool was built: https://support.desk.com/customer/portal/articles/2927086-desk-to-salesforce-knowledge-article-migration-tool---implementation-guide?b_id=16915


link to UB definition

@bors r+

:pushpin: Commit e843077d1d673019518055c47dc39c7098993b0c has been approved by RalfJung

:hourglass: Testing commit e843077d1d673019518055c47dc39c7098993b0c with merge e59f9cb2598d9bd090e6eb28628685aa91de8ddd...

:sunny: Test successful - checks-travis, status-appveyor
Approved by: RalfJung
Pushing e59f9cb2598d9bd090e6eb28628685aa91de8ddd to master...


[Enhancement] add timeout for clear expire state in primary key

If so many expired entries in dynamic cache, and we want to clear them at once, which will hold _lock in dynamic cache for a long time. We use  dynamic cache to store primary index, so if clear expire index cost too much time, it will make data loading hang, and waiting for _lock in dynamic cache.
So I add config clear_expire_primary_key_state_timeout_millis here to control the timeout of clear expire entries in dynamic cache, no timeout by default.
What type of PR is this:

[ ] BugFix
[ ] Feature
[x] Enhancement
[ ] Refactor
[ ] UT
[ ] Doc
[ ] Tool

Does this PR entail a change in behavior?

[x] Yes, this PR will result in a change in behavior.
[ ] No, this PR will not result in a change in behavior.

If yes, please specify the type of change:

[ ] Interface/UI changes: syntax, type conversion, expression evaluation, display information
[x] Parameter changes: default values, similar parameters but with different default values
[ ] Policy changes: use new policy to replace old one, functionality automatically enabled
[ ] Feature removed
[ ] Miscellaneous: upgrade & downgrade compatibility, etc.

Checklist:

[x] I have added test cases for my bug fix or my new feature
[ ] This pr needs user documentation (for new or modified features or behaviors)

[ ] I have added documentation for my new feature or new function

Bugfix cherry-pick branch check:

[x] I have checked the version labels which the pr will be auto-backported to the target branch

[x] 3.2
[x] 3.1
[x] 3.0
[x] 2.5

@Mergifyio backport branch-3.2

@Mergifyio backport branch-3.1

@Mergifyio backport branch-3.0

@Mergifyio backport branch-2.5

[FE Incremental Coverage Report]
:heart_eyes: pass : 0 / 0 (0%)

[BE Incremental Coverage Report]
:heart_eyes: pass : 21 / 24 (87.50%)
file detail

path
covered_line
new_line
coverage
not_covered_line_detail

:large_blue_circle:
src/util/dynamic_cache.h
18
21
85.71%
[239, 336, 343]

:large_blue_circle:
src/storage/update_manager.cpp
3
3
100.00%
[]


Add Mstdn.science verification to homepage

We should aim to veriy that<EMAIL_ADDRESS>indeed is our page:
Can we have a link to the mstdn.science account somewhere on the webpage?
Mastodon

Can it be anywhere on the site? eg. a new section on https://nf-co.re/join ?
Or does it have to be on every page?

Nevermind, can add the icon to the footer, we already have them there..


Token implementation /3

Next turn after error fixing _onData as _onDataToken etc.

Whew! This took me a while.
Sorry to always closing PRs and opening another - this was the only way I found to correct previous PRs.
As soon as this PR and the following regarding the RawRequests will be merged, things get easier for me, as I then will be able to directly test with my device.


jira collector java.net.SocketTimeoutException

Jira version: 7.2.0
I'm getting the followin exception after running the collector on Jira:
2016-09-23 13:56:00,001 INFO  c.c.d.collector.CollectorTask - Running Collector: Jira
2016-09-23 13:56:00,011 INFO  c.c.d.collector.CollectorTask - -----------------------------------
2016-09-23 13:56:00,011 INFO  c.c.d.collector.CollectorTask - http://<IP_ADDRESS>:8080
2016-09-23 13:56:00,011 INFO  c.c.d.collector.CollectorTask - -----------------------------------
2016-09-23 13:56:20,265 ERROR c.c.d.collector.FeatureCollectorTask - Failed to collect jira information
java.lang.RuntimeException: java.net.SocketTimeoutException
at com.google.common.base.Throwables.propagate(Throwables.java:160) ~[guava-14.0.jar!/:na]
at com.atlassian.httpclient.apache.httpcomponents.DefaultHttpClient$3.apply(DefaultHttpClient.java:256) ~[atlassian-httpclient-apache-httpcomponents-0.13.2.jar!/:na]
at com.atlassian.httpclient.apache.httpcomponents.DefaultHttpClient$3.apply(DefaultHttpClient.java:249) ~[atlassian-httpclient-apache-httpcomponents-0.13.2.jar!/:na]
at com.atlassian.util.concurrent.Promises$Of$2.apply(Promises.java:276) ~[atlassian-util-concurrent-2.4.0-M9.jar!/:na]
at com.atlassian.util.concurrent.Promises$Of$2.apply(Promises.java:272) ~[atlassian-util-concurrent-2.4.0-M9.jar!/:na]
at com.atlassian.util.concurrent.Promises$2.onFailure(Promises.java:167) ~[atlassian-util-concurrent-2.4.0-M9.jar!/:na]
at com.google.common.util.concurrent.Futures$4.run(Futures.java:1145) ~[guava-14.0.jar!/:na]
at com.google.common.util.concurrent.MoreExecutors$SameThreadExecutorService.execute(MoreExecutors.java:293) ~[guava-14.0.jar!/:na]
Can anybody tell me what may be the issue here? The communication with Mongo is working fine and I believe I configured correctly the properties file. Will appreciate any help.
Thanks,
Leo

The collector is having issues communicating with jira. The connection is timing out. Try hitting the rest api manually to see if issues come back in a timely manner. You can also try decreasing the page size.

Alredy tried what you are suggesting. Tried with curl from same place where I'm running the collector and its working file, I'm getting the response. Also tried decreasing the page size. Don't know what else to try.

Turn up debugging by putting these in your properties file:
logging.level.com.atlassian.jira=INFO
logging.level.com.capitalone.dashboard=DEBUG
logging.level.com.capitalone.dashboard.collector=DEBUG

those options are not available through docker-compose so you have to modify the command that is run and point it to a mounted properties file.
Is there more to the stack trace? What line is failing on in the hygieia code?

Still not running anything with docker.  I have Mongo Up, the API layer UP and connected to the DB, the UI is also showing me that is connected to the API successfully. Only the collector seems to be giving me problems, it is reaching the DB, cause i see it on the log file but for some reason is not getting anything from Jira and I'm getting that Timeout that I showed you.
I added the lines you gave me and here is the complete stack trace:
2016-09-23 16:40:00,003 INFO  c.c.d.collector.CollectorTask - Running Collector: Jira
2016-09-23 16:40:00,015 INFO  c.c.d.collector.CollectorTask - -----------------------------------
2016-09-23 16:40:00,015 INFO  c.c.d.collector.CollectorTask - http://<IP_ADDRESS>:8080/
2016-09-23 16:40:00,015 INFO  c.c.d.collector.CollectorTask - -----------------------------------
2016-09-23 16:40:00,015 DEBUG c.c.d.client.team.TeamDataClientImpl - Constructing data collection for the feature widget, team-level data...
2016-09-23 16:40:20,036 ERROR c.c.d.collector.FeatureCollectorTask - Failed to collect jira information
java.lang.RuntimeException: java.net.SocketTimeoutException
at com.google.common.base.Throwables.propagate(Throwables.java:160) ~[guava-14.0.jar!/:na]
at com.atlassian.httpclient.apache.httpcomponents.DefaultHttpClient$3.apply(DefaultHttpClient.java:256) ~[atlassian-httpclient-apache-httpcomponents-0.13.2.jar!/:na]
at com.atlassian.httpclient.apache.httpcomponents.DefaultHttpClient$3.apply(DefaultHttpClient.java:249) ~[atlassian-httpclient-apache-httpcomponents-0.13.2.jar!/:na]
at com.atlassian.util.concurrent.Promises$Of$2.apply(Promises.java:276) ~[atlassian-util-concurrent-2.4.0-M9.jar!/:na]
at com.atlassian.util.concurrent.Promises$Of$2.apply(Promises.java:272) ~[atlassian-util-concurrent-2.4.0-M9.jar!/:na]
at com.atlassian.util.concurrent.Promises$2.onFailure(Promises.java:167) ~[atlassian-util-concurrent-2.4.0-M9.jar!/:na]
at com.google.common.util.concurrent.Futures$4.run(Futures.java:1145) ~[guava-14.0.jar!/:na]
at com.google.common.util.concurrent.MoreExecutors$SameThreadExecutorService.execute(MoreExecutors.java:293) ~[guava-14.0.jar!/:na]
at com.google.common.util.concurrent.ExecutionList$RunnableExecutorPair.execute(ExecutionList.java:150) ~[guava-14.0.jar!/:na]
at com.google.common.util.concurrent.ExecutionList.execute(ExecutionList.java:135) ~[guava-14.0.jar!/:na]
at com.google.common.util.concurrent.AbstractFuture.setException(AbstractFuture.java:203) ~[guava-14.0.jar!/:na]
at com.google.common.util.concurrent.SettableFuture.setException(SettableFuture.java:68) ~[guava-14.0.jar!/:na]
at com.atlassian.httpclient.apache.httpcomponents.SettableFuturePromiseHttpPromiseAsyncClient$1$2.run(SettableFuturePromiseHttpPromiseAsyncClient.java:59) ~[atlassian-httpclient-apache-httpcomponents-0.13.2.jar!/:na]
at com.atlassian.httpclient.apache.httpcomponents.SettableFuturePromiseHttpPromiseAsyncClient$ThreadLocalDelegateRunnable$1.run(SettableFuturePromiseHttpPromiseAsyncClient.java:197) ~[atlassian-httpclient-apache-httpcomponents-0.13.2.jar!/:na]
at com.atlassian.httpclient.apache.httpcomponents.SettableFuturePromiseHttpPromiseAsyncClient.runInContext(SettableFuturePromiseHttpPromiseAsyncClient.java:90) ~[atlassian-httpclient-apache-httpcomponents-0.13.2.jar!/:na]
at com.atlassian.httpclient.apache.httpcomponents.SettableFuturePromiseHttpPromiseAsyncClient$ThreadLocalDelegateRunnable.run(SettableFuturePromiseHttpPromiseAsyncClient.java:192) ~[atlassian-httpclient-apache-httpcomponents-0.13.2.jar!/:na]
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) [na:1.8.0_101]
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) [na:1.8.0_101]
at java.lang.Thread.run(Thread.java:745) [na:1.8.0_101]
Caused by: java.net.SocketTimeoutException: null
at org.apache.http.nio.protocol.HttpAsyncRequestExecutor.timeout(HttpAsyncRequestExecutor.java:279) ~[httpcore-nio-4.2.2.jar!/:4.2.2]
at org.apache.http.impl.nio.client.LoggingAsyncRequestExecutor.timeout(LoggingAsyncRequestExecutor.java:128) ~[httpasyncclient-4.0-beta3-atlassian-1.jar!/:4.0-beta3-atlassian-1]
at org.apache.http.impl.nio.DefaultHttpClientIODispatch.onTimeout(DefaultHttpClientIODispatch.java:136) ~[httpcore-nio-4.2.2.jar!/:4.2.2]
at org.apache.http.impl.nio.DefaultHttpClientIODispatch.onTimeout(DefaultHttpClientIODispatch.java:50) ~[httpcore-nio-4.2.2.jar!/:4.2.2]
at org.apache.http.impl.nio.reactor.AbstractIODispatch.timeout(AbstractIODispatch.java:169) ~[httpcore-nio-4.2.2.jar!/:4.2.2]
at org.apache.http.impl.nio.reactor.BaseIOReactor.sessionTimedOut(BaseIOReactor.java:257) ~[httpcore-nio-4.2.2.jar!/:4.2.2]
at org.apache.http.impl.nio.reactor.AbstractIOReactor.timeoutCheck(AbstractIOReactor.java:494) ~[httpcore-nio-4.2.2.jar!/:4.2.2]
at org.apache.http.impl.nio.reactor.BaseIOReactor.validate(BaseIOReactor.java:207) ~[httpcore-nio-4.2.2.jar!/:4.2.2]
at org.apache.http.impl.nio.reactor.AbstractIOReactor.execute(AbstractIOReactor.java:284) ~[httpcore-nio-4.2.2.jar!/:4.2.2]
at org.apache.http.impl.nio.reactor.BaseIOReactor.execute(BaseIOReactor.java:106) ~[httpcore-nio-4.2.2.jar!/:4.2.2]
at org.apache.http.impl.nio.reactor.AbstractMultiworkerIOReactor$Worker.run(AbstractMultiworkerIOReactor.java:604) ~[httpcore-nio-4.2.2.jar!/:4.2.2]
... 1 common frames omitted

Does curl work from within the running docker container? You can attach a bash shell to the container and run curl.
Is your user account locked that it is trying to use? Is jira behind a proxy?
The code is failing to get all of the projects on the jira server.

I have the same issue.

@oshingc jira version? I have had problems with 7.1.9. In the past it could pull 200 issues in ~1 second. Now it takes 30 seconds. I had to decrease the page size to 25 to get it to work without timing out.

The version I use is Jira v6.4.13

Did you resolve it?

I solved this following some instructions, see more here #901


Investigate the unicode situation

Check that unicode strings work throughout the entire program.

Closing for now as unicode support is irrelevant to the use case for the program.


Allow Symfony 5 for config component

Allow Symfony 5 for the symfony/config dependency

Close in favorite of https://github.com/Behat/MinkExtension/pull/360


Key not found: Steam

╰─❱ protonutils list
Key not found: Steam

╰─❱ protonutils config
user: ""

I just installed protonutils and it can't list games nor config. I don't know how can I make it work. I have Steam installed and a couple of games as well, one of them require Proton (I have proton-ge-custom installed), which is used for that game (which is Poppy Playtime). I also have a non-Steam game added to my library and a couple of native games.

Thanks for trying protonutils and for reporting this issue!
protonutils config should actually show an empty config unless any values are set explicitly by the user.
All the features should work without explicitly specifying the Steam user in the config.
However, protonutils list should work right away just as you tried and yield no such error!
Please answer some questions to pinpoint this issue:

Did you enable Steam Play for all titles?
Did you override the default Proton version for "Poppy Playtime"?
Which version of protonutils are you using?

It looks like the "CompatToolMapping" configuration is looking different than on my machines (or is empty).
Would you send me your ~/.steam/root/config/config.vdf via mail, please?

I did not, but I just tried enabling Proton-GE globally and I still got the same error.
Yes, with proton-ge-custom
1.3.1-1

I'll send you an email with the requested file right away.

Thanks for sending the file! In your config, the "CompatToolMapping" is saved under a lower case "steam" key, whereas in my config (and seemingly also for the majority of other users), the mapping is saved under a capitalized "Steam" key.
I changed the code to try both, now.
Please retest with and report back:
https://github.com/nning/protonutils/suites/4648747079/artifacts/126140837

That works 👍🏻

Great, thanks for your help!


Running new model based on BiseNetV2

Hello!
I am having a problem running your last weights. The original weights run great. The error I have is:
Traceback (most recent call last):   File "tools/test_lanenet.py", line 154, in <module>     test_lanenet(args.image_path, args.weights_path)   File "tools/test_lanenet.py", line 107, in test_lanenet     saver.restore(sess=sess, save_path=weights_path)   File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/saver.py", line 1282, in restore     checkpoint_prefix) ValueError: The passed save_path is not a valid checkpoint: ./model/tusimple_lanenet_vgg/tusimple_lanenet_vgg.ckpt
It seems that the model has not been saved correclty?
Thank you!

@apusky Download the new pretrained model here https://www.dropbox.com/sh/0b6r0ljqi76kyg9/AADedYWO3bnx4PhK1BmbJkJKa?dl=0

@MaybeShewill-CV it's the same link as your post update. I tried again and it doesn't work. Should I change something in the code to make it work? I also tried the full PATH and it doesn't work. Thank you for your quick response

@apusky The new model was named tusimple_lanenet.ckpt instead of tusimple_lanenet_vgg.ckpt. Please make sure you have used the right model weights file path by yourself:)

@MaybeShewill-CV Sorry for that silly mistake. I got it replaced and it seems that it is loading now.
When it is running I got the following error:
During handling of the above exception, another exception occurred:
Traceback (most recent call last):   File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/saver.py", line 1300, in restore     names_to_keys = object_graph_key_mapping(save_path)   File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/saver.py", line 1618, in object_graph_key_mapping     object_graph_string = reader.get_tensor(trackable.OBJECT_GRAPH_PROTO_KEY)   File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/pywrap_tensorflow_internal.py", line 915, in get_tensor     return CheckpointReader_GetTensor(self, compat.as_bytes(tensor_str)) tensorflow.python.framework.errors_impl.NotFoundError: Key _CHECKPOINTABLE_OBJECT_GRAPH not found in checkpoint
During handling of the above exception, another exception occurred:
Traceback (most recent call last):   File "tools/test_lanenet.py", line 154, in <module>     test_lanenet(args.image_path, args.weights_path)   File "tools/test_lanenet.py", line 107, in test_lanenet     saver.restore(sess=sess, save_path=weights_path)   File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/saver.py", line 1306, in restore     err, "a Variable name or other graph key that is missing") tensorflow.python.framework.errors_impl.NotFoundError: Restoring from checkpoint failed. This is most likely due to a Variable name or other graph key that is missing from the checkpoint. Please ensure that you have not altered the graph expected based on the checkpoint. Original error:
2 root error(s) found.   (0) Not found: Key lanenet_model/vgg_backend/instance_seg/pix_bn/beta not found in checkpoint 	 [[node save/RestoreV2 (defined at /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py:1748) ]]   (1) Not found: Key lanenet_model/vgg_backend/instance_seg/pix_bn/beta not found in checkpoint 	 [[node save/RestoreV2 (defined at /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py:1748) ]] 	 [[save/RestoreV2/_301]] 0 successful operations. 0 derived errors ignored.

@apusky Paste the full command you used here.  Please use tf.compat.v1.placeholder instead.

W0618 03:22:04.169868 773 module_wrapper.py:139] From /content/drive/My Drive/Colab Notebooks/lanenet-lane-detection/semantic_segmentation_zoo/vgg16_based_fcn.py:355: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.

W0618 03:22:04.170398 773 lazy_loader.py:50]
The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:
  * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
  * https://github.com/tensorflow/addons
  * https://github.com/tensorflow/io (for I/O related ops)
If you depend on functionality not listed there, please file an issue.

I0618 03:22:04.409512 773 utils.py:141] NumExpr defaulting to 2 threads.
W0618 03:22:04.814890 773 module_wrapper.py:139] From /content/drive/My Drive/Colab Notebooks/lanenet-lane-detection/semantic_segmentation_zoo/cnn_basenet.py:70: The name tf.get_variable is deprecated. Please use tf.compat.v1.get_variable instead.

W0618 03:22:04.826056 773 deprecation.py:323] From /content/drive/My Drive/Colab Notebooks/lanenet-lane-detection/semantic_segmentation_zoo/cnn_basenet.py:342: batch_normalization (from tensorflow.python.layers.normalization) is deprecated and will be removed in a future version.
Instructions for updating:
Use keras.layers.BatchNormalization instead.  In particular, `tf.control_dependencies(tf.GraphKeys.UPDATE_OPS)` should not be used (consult the `tf.keras.layers.batch_normalization` documentation).
W0618 03:22:04.826737 773 deprecation.py:323] From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/layers/normalization.py:327: Layer.apply (from tensorflow.python.keras.engine.base_layer) is deprecated and will be removed in a future version.
Instructions for updating:
Please use `layer.__call__` method instead.
W0618 03:22:04.875171 773 module_wrapper.py:139] From /content/drive/My Drive/Colab Notebooks/lanenet-lane-detection/semantic_segmentation_zoo/cnn_basenet.py:173: The name tf.nn.max_pool is deprecated. Please use tf.nn.max_pool2d instead.

W0618 03:22:05.269595 773 deprecation.py:323] From /content/drive/My Drive/Colab Notebooks/lanenet-lane-detection/semantic_segmentation_zoo/cnn_basenet.py:425: conv2d_transpose (from tensorflow.python.layers.convolutional) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.keras.layers.Conv2DTranspose` instead.
W0618 03:22:06.162201 773 module_wrapper.py:139] From tools/test_lanenet.py:95: The name tf.train.Saver is deprecated. Please use tf.compat.v1.train.Saver instead.

W0618 03:22:06.441568 773 module_wrapper.py:139] From tools/test_lanenet.py:98: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead.

W0618 03:22:06.441898 773 module_wrapper.py:139] From tools/test_lanenet.py:103: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.

2020-06-18 03:22:06.442176: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2020-06-18 03:22:06.447316: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency:<PHONE_NUMBER> Hz
2020-06-18 03:22:06.447588: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x2555640 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-06-18 03:22:06.447623: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2020-06-18 03:22:06.449913: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2020-06-18 03:22:06.525301: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-06-18 03:22:06.526220: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x2555480 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2020-06-18 03:22:06.526261: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Tesla K80, Compute Capability 3.7
2020-06-18 03:22:06.526487: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-06-18 03:22:06.527187: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1639] Found device 0 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:00:04.0
2020-06-18 03:22:06.527561: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2020-06-18 03:22:06.528878: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0
2020-06-18 03:22:06.530305: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0
2020-06-18 03:22:06.530682: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0
2020-06-18 03:22:06.532345: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0
2020-06-18 03:22:06.533707: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0
2020-06-18 03:22:06.537672: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2020-06-18 03:22:06.537840: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-06-18 03:22:06.538645: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-06-18 03:22:06.539329: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1767] Adding visible gpu devices: 0
2020-06-18 03:22:06.539407: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2020-06-18 03:22:06.541351: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1180] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-06-18 03:22:06.541387: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1186]      0
2020-06-18 03:22:06.541403: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1199] 0:   N
2020-06-18 03:22:06.541584: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-06-18 03:22:06.542385: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-06-18 03:22:06.543092: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1325] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9152 MB memory) -> physical GPU (device: 0, name: Tesla K80, pci bus id: 0000:00:04.0, compute capability: 3.7)
I0618 03:22:06.545681 773 saver.py:1284] Restoring parameters from model/tusimple_lanenet_vgg/tusimple_lanenet.ckpt
2020-06-18 03:22:06.726866: W tensorflow/core/framework/op_kernel.cc:1651] OP_REQUIRES failed at save_restore_v2_ops.cc:184 : Not found: Key lanenet_model/vgg_backend/instance_seg/pix_bn/beta not found in checkpoint
Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1365, in _do_call
    return fn(*args)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1350, in _run_fn
    target_list, run_metadata)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1443, in _call_tf_sessionrun
    run_metadata)
tensorflow.python.framework.errors_impl.NotFoundError: 2 root error(s) found.
  (0) Not found: Key lanenet_model/vgg_backend/instance_seg/pix_bn/beta not found in checkpoint
	 [[{{node save/RestoreV2}}]]
	 [[save/RestoreV2/_301]]
  (1) Not found: Key lanenet_model/vgg_backend/instance_seg/pix_bn/beta not found in checkpoint
	 [[{{node save/RestoreV2}}]]
0 successful operations.
0 derived errors ignored.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/saver.py", line 1290, in restore
    {self.saver_def.filename_tensor_name: save_path})
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 956, in run
    run_metadata_ptr)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1180, in _run
    feed_dict_tensor, options, run_metadata)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1359, in _do_run
    run_metadata)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1384, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.NotFoundError: 2 root error(s) found.
  (0) Not found: Key lanenet_model/vgg_backend/instance_seg/pix_bn/beta not found in checkpoint
	 [[node save/RestoreV2 (defined at /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py:1748) ]]
	 [[save/RestoreV2/_301]]
  (1) Not found: Key lanenet_model/vgg_backend/instance_seg/pix_bn/beta not found in checkpoint
	 [[node save/RestoreV2 (defined at /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py:1748) ]]
0 successful operations.
0 derived errors ignored.

Original stack trace for 'save/RestoreV2':
  File "tools/test_lanenet.py", line 154, in <module>
    test_lanenet(args.image_path, args.weights_path)
  File "tools/test_lanenet.py", line 95, in test_lanenet
    saver = tf.train.Saver()
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/saver.py", line 828, in __init__
    self.build()
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/saver.py", line 840, in build
    self._build(self._filename, build_save=True, build_restore=True)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/saver.py", line 878, in _build
    build_restore=build_restore)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/saver.py", line 508, in _build_internal
    restore_sequentially, reshape)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/saver.py", line 328, in _AddRestoreOps
    restore_sequentially)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/saver.py", line 575, in bulk_restore
    return io_ops.restore_v2(filename_tensor, names, slices, dtypes)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/ops/gen_io_ops.py", line 1696, in restore_v2
    name=name)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/op_def_library.py", line 794, in _apply_op_helper
    op_def=op_def)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/util/deprecation.py", line 507, in new_func
    return func(*args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py", line 3357, in create_op
    attrs, op_def, compute_device)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py", line 3426, in _create_op_internal
    op_def=op_def)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py", line 1748, in __init__
    self._traceback = tf_stack.extract_stack()

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/saver.py", line 1300, in restore
    names_to_keys = object_graph_key_mapping(save_path)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/saver.py", line 1618, in object_graph_key_mapping
    object_graph_string = reader.get_tensor(trackable.OBJECT_GRAPH_PROTO_KEY)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/pywrap_tensorflow_internal.py", line 915, in get_tensor
    return CheckpointReader_GetTensor(self, compat.as_bytes(tensor_str))
tensorflow.python.framework.errors_impl.NotFoundError: Key _CHECKPOINTABLE_OBJECT_GRAPH not found in checkpoint

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "tools/test_lanenet.py", line 154, in <module>
    test_lanenet(args.image_path, args.weights_path)
  File "tools/test_lanenet.py", line 107, in test_lanenet
    saver.restore(sess=sess, save_path=weights_path)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/saver.py", line 1306, in restore
    err, "a Variable name or other graph key that is missing")
tensorflow.python.framework.errors_impl.NotFoundError: Restoring from checkpoint failed. This is most likely due to a Variable name or other graph key that is missing from the checkpoint. Please ensure that you have not altered the graph expected based on the checkpoint. Original error:

2 root error(s) found.
  (0) Not found: Key lanenet_model/vgg_backend/instance_seg/pix_bn/beta not found in checkpoint
	 [[node save/RestoreV2 (defined at /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py:1748) ]]
	 [[save/RestoreV2/_301]]
  (1) Not found: Key lanenet_model/vgg_backend/instance_seg/pix_bn/beta not found in checkpoint
	 [[node save/RestoreV2 (defined at /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py:1748) ]]
0 successful operations.
0 derived errors ignored.

Original stack trace for 'save/RestoreV2':
  File "tools/test_lanenet.py", line 154, in <module>
    test_lanenet(args.image_path, args.weights_path)
  File "tools/test_lanenet.py", line 95, in test_lanenet
    saver = tf.train.Saver()
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/saver.py", line 828, in __init__
    self.build()
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/saver.py", line 840, in build
    self._build(self._filename, build_save=True, build_restore=True)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/saver.py", line 878, in _build
    build_restore=build_restore)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/saver.py", line 508, in _build_internal
    restore_sequentially, reshape)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/saver.py", line 328, in _AddRestoreOps
    restore_sequentially)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/saver.py", line 575, in bulk_restore
    return io_ops.restore_v2(filename_tensor, names, slices, dtypes)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/ops/gen_io_ops.py", line 1696, in restore_v2
    name=name)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/op_def_library.py", line 794, in _apply_op_helper
    op_def=op_def)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/util/deprecation.py", line 507, in new_func
    return func(*args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py", line 3357, in create_op
    attrs, op_def, compute_device)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py", line 3426, in _create_op_internal
    op_def=op_def)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py", line 1748, in __init__
    self._traceback = tf_stack.extract_stack()

@apusky Make sure you have git pull the new code:)

@apusky Make sure you have downloaded the right model weighs here https://www.dropbox.com/sh/0b6r0ljqi76kyg9/AADedYWO3bnx4PhK1BmbJkJKa?dl=0

@MaybeShewill-CV I just pulled the repository and downloaded the weights again. It works now!
I got an inference time of 0.02316s using google colab GPU.
Thank you and have a good one!

@apusky Welcome :)

@apusky  Hello, if it is not too much trouble, could you facilitate your collaboration, to be able to use it from there? :)

Hello, do you still need it? I can't see your reply on GitHub.
Regards,
Apusky
On Fri, Jun 19, 2020, 6:56 PM dpramirez<EMAIL_ADDRESS>wrote:

@apusky https://github.com/apusky Hello, if it is not too much trouble,
could you facilitate your collaboration, to be able to use it from there? :)
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/MaybeShewill-CV/lanenet-lane-detection/issues/404#issuecomment-646901603,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AGJXVXFU2CBR36UEIXJGHULRXP3MTANCNFSM4N74ZZJQ
.


"url" field in Appointment extension should return specified URL, not "#"

url field in extension should be "[base]/extension/vidyo-portal-data" where base is the auth server's domain name, not "#"

Specified URL for Appointment extension
https://github.com/LibreEHR/fhir/pull/43


[SPARK-19601] [SQL] Fix CollapseRepartition rule to preserve shuffle-enabled Repartition

What changes were proposed in this pull request?
Observed by @felixcheung  in https://github.com/apache/spark/pull/16739, when users use the shuffle-enabled repartition API, they expect the partition they got should be the exact number they provided, even if they call shuffle-disabled coalesce later.
Currently, CollapseRepartition rule does not consider whether shuffle is enabled or not. Thus, we got the following unexpected result.
    val df = spark.range(0, 10000, 1, 5)
    val df2 = df.repartition(10)
    assert(df2.coalesce(13).rdd.getNumPartitions == 5)
    assert(df2.coalesce(7).rdd.getNumPartitions == 5)
    assert(df2.coalesce(3).rdd.getNumPartitions == 3)

This PR is to fix the issue. We preserve shuffle-enabled Repartition.
How was this patch tested?
Added a test case

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cc @cloud-fan @hvanhovell

Test build #74045 has started for PR 16933 at commit 5453ad4.

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Test build #74137 has started for PR 16933 at commit 8306c49.

Let me re-write the whole test cases. Thanks!

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LGTM, pending test

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retest this please

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retest this please

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Thanks! Merging to master.

awesome!


BigInt.toInt could be zero-cost

Small thing, if wanting to some compile-time overhead. It also is a good deal faster for me at runtime

https://github.com/rescript-association/rescript-core/blob/main/src/Core__BigInt.res#L16
@scope("BigInt")
external toInt: (@as(32) _, bigint) => int = "asIntN"

Sure would be nice if we could bind a rescript external function to a js expression for the **:
external exp: (t, t) => t = %rawExpression("%{1} ** %{2}")

My mistake, this doesn't actually convert to Number unfortunately.

Shoot! 😄


How to remove placeholders in TextInput and Textarea?

I want to remove placeholders from these widgets, but I think it can't be done unless modifying this app's source code.
Is there another solutions?
Thank you.

Is it possible to do this for a single form? I generally want placeholders to be generated, but in some cases I need them to disappear.

+1 @beruic


Made a change to wiki for dual username/email logins

I am not intimately familiar with Devise internals so can someone please confirm it's a sane change.
https://github.com/plataformatec/devise/wiki/How-To:-Allow-users-to-sign-in-using-their-username-or-email-address/_compare/eac2167e82272e20f18e6015a5c439be4f23d293...286498bb1b2f5a4e6d3a5a2531ef986983c93b05

Yup, looks good. Thanks.


Fixed Width Layout

I am planning to use spectre.css in one of my side project. The problem that currently I am facing is, with fixed-width container. Do we have fixed width container? From the documentation I only seen container with full width.
I found that you are using something called .grid-960 but not sure of it usage.

@chauhankiran Yes, container is full width container. You can use grid-1280(1280px inside), grid-960(960px inside) and grid-480(480px inside) for different fixed width container.

@chauhankiran Latest version 0.2.15 is released. I have updated the responsive container docs here.


refactor the publishing of the runtimes to move the version of the language in the tag

To publish our runtimes into the apache organization we have to stick to a fixed set of runtimes. So we have to move the version of the language fron the name (runtime-python-v311:) to the tag (openserverless-python:3.11-0.1.0.timestamp).
Afther this we have to publish in the apache docker hub and automatically update a runtime.json to be published in the runtime repo.

Looks like we finally got the image so we can now try to publish them on the apache github repo, refactoring the names to use the tags for the language version
https://issues.apache.org/jira/browse/INFRA-25975

We have an initial set of images under the apache repository for the operator, runtime-common, and also go, python, nodes and php.
operator and common images have been pushed from the respective official apache GitHub repos, used the ASF DockerHub enforced secrets.
The remaining images, are using s dedicated docker cloud build which is currently running under another docker hub account. ASF enforced secrets do not have access to the docker cloud builder, so current images have been pushed from a forked repository.


Macro Redefinition and Header Conflicts Causes Issue Installing

I am using vcpkg on windows whenever I try to install glog
vcpkg install glog

I get macro redefinition  errors. The issue is caused by two google projects ctemplate and glog which use same macros for different purposes.  See this line.
https://github.com/OlafvdSpek/ctemplate/blob/master/src/windows/config.h#L19
#define GOOGLE_NAMESPACE  ctemplate

and  on this https://github.com/google/glog/blob/master/src/windows/config.h#L4
#define GOOGLE_NAMESPACE  google

see issue microsoft/vcpkg#1514 and OlafvdSpek/ctemplate#127

Is glog/config.h supposed to be a public header?

@OlafvdSpek I am going to open this for them to answer your question


MWPW-161289 Catalog CTA IMS country used in commerce calls

IMS country should not be used in https://www.adobe.com/web_commerce_artifact calls
When data-ims-country is updated, the /web_commerce_artifact call is triggered again with IMS country in query parameters. By removing that data attribute from observedAttributes I prevented that.
On catalog pages I found one hidden CTA where /web_commerce_artifact is called with IMS country even after this change so I had to add overrides.imsCountry = null to fix that case as well.
Test URL :
https://main--cc--adobecom.hlx.page/products/catalog?milolibs=mwpw161289ctaims--milo--bozojovicic
Resolves: MWPW-161289
Test URLs:

Before: https://main--milo--adobecom.hlx.page/drafts/bozo/price-cta?martech=off
After: https://mwpw161289ctaims--milo--bozojovicic.hlx.page/drafts/bozo/price-cta?martech=off

@yesil @3ch023 @npeltier @bozojovicic
Even though this seems to be fixed for catalog page, for studio I still get placeholder-failed and ims RS. Could you please check? Do we need to separate jiras for catalog and studio in this matter?

@bozojovicic mas.js build is missing in your PR, can you rebuild and commit it please?

@afmicka thanks, @bozojovicic PR was missing mas.js build, asked him to rebuild it.
but on top, we need a small PR to mas to remove ims atribute at the end: https://github.com/adobecom/mas/blob/main/studio/src/aem/render-view.js#L51

@yesil new mas.js build pushed
but who will do this part ?
we need a small PR to mas to remove ims atribute at the end: https://github.com/adobecom/mas/blob/main/studio/src/aem/render-view.js#L51
This is "uncharted territory" for me.

Checked on
https://main--cc--adobecom.hlx.live/products/photoshop?milolibs=mwpw161289ctaims--milo--bozojovicic
looks good with my DE user. WCS request country=US, CTA link country=DE

@bozojovicic @yesil @3ch023
this time, CTA placeholders are resolved in studio but on catalog page if i log in with the user with FR as ims country, the ctas resolve to US (the site locale and not user's ims)
https://main--cc--adobecom.hlx.page/products/catalog?milolibs=mwpw161289ctaims--milo--bozojovicic#miniplans-buy-acrobat

will log a separate jira for the issue mentioned above. Approving this one.


Be more selective grabbing logfiles

If there are more than one ELB worth of log files in the same S3 Prefix, honeyelb should not try upload every log file from every ELB each time that it tries to ingest logs for an ELB.

LGTM

It won't help with the issue where BREAK DOWN by elb wasn't working, though, will it?


Fixes typo in Sigils

In relation to #181

LGTM :+1:
cc / @doomspork Can you let the translators know of this fix?

Ping @milmazz (es), @michalvalasek (sk), @brain-geek (ru), @3100 (jp), @cizixs (cn), @joneslee85 (vi)
As a heads up there's been an important, albeit one word, change to the sigil basics lessons.


end to end method

Add a end to end method, loading data from server at tbFotm

Coverage increased (+0.6%) to 74.859% when pulling 5b5e937ae66f4c8fdeb9d6806ece162eb002f73c on chubbsnes65:master into 8e6c61324a5c28e995d6656fe8f4d1aa3bb6db79 on unosquare:master.


[Docs][TextField] Added inputStyle property in info section

Hope this will save some time for those who trying to override the textField input inline styles (:

Indeed https://github.com/callemall/material-ui/blob/master/src/text-field.jsx#L45

@xmityaz Thanks, could you also squash down to one commit

@xmityaz Thanks


Question: can we adapt department names?

Question / Story
Question: can we adapt department names?
Name in Biblio: Department of Structural engineering
Correct name: Department of Structural Engineering and Building Materials

done