PHI-2 runs out of memory on RTX 3070 Ti with 8Gb memory when running finetuning step

TLDR;
PHI-2 will runs out of memory on an 8Gb Nvidia 3070 card on fine tuning step from Readme.
NOTE: Please advise if there are any ways to reduce batch size or ways to minimize memory footprint on the GPU.
ENVIRONMENT:
Windows
OS Name:                   Microsoft Windows 11 Home
OS Version:                10.0.22631 N/A Build 22631
OS Manufacturer:           Microsoft Corporation
OS Configuration:          Standalone Workstation
OS Build Type:             Multiprocessor Free
System Manufacturer:       Acer
System Model:              Nitro AN515-46
System Type:               x64-based PC
Processor(s):              1 Processor(s) Installed.
[01]: AMD64 Family 25 Model 68 Stepping 1 AuthenticAMD ~3201 Mhz
Total Physical Memory:     15,557 MB
Available Physical Memory: 8,252 MB
Virtual Memory: Max Size:  30,249 MB
Virtual Memory: Available: 10,821 MB
Virtual Memory: In Use:    19,428 MB
Page File Location(s):     C:\pagefile.sys
nvidia-smi
Sun Dec 24 23:11:50 2023
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 545.92                 Driver Version: 545.92       CUDA Version: 12.3     |
|-----------------------------------------+----------------------+----------------------+
| GPU  Name                     TCC/WDDM  | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |
|                                         |                      |               MIG M. |
|=========================================+======================+======================|
|   0  NVIDIA GeForce RTX 3070 ...  WDDM  | 00000000:01:00.0  On |                  N/A |
| N/A   43C    P8              15W / 140W |    706MiB /  8192MiB |      7%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+
SETUP:
Follow #28 for setup I followed...
Ran first_time_setup.sh - which creates the phi-2-env
STEPS:

start Terminal at root of project
conda deactivate
conda activate phi-2-env
python finetuning/invoke_olive.py

EXPECTED: Since PHI-2 model safetensor files total seems to be around 5G, would have expected we could have done a finetune with 8G.
ACTUAL:  Fine tuning model runs out of memory.
(base) ericv@NITRO:/mnt/c/mnt/c/Users/ericv/source/repos/AI/SamplePHI2$ conda deactivate
ericv@NITRO:/mnt/c/mnt/c/Users/ericv/source/repos/AI/SamplePHI2$ conda activate phi-2-env
(phi-2-env) ericv@NITRO:/mnt/c/mnt/c/Users/ericv/source/repos/AI/SamplePHI2$ python finetuning/invoke_olive.py
[2023-12-24 23:02:47,450] [DEBUG] [engine.py:125:setup_accelerators] Initial execution providers: ['CPUExecutionProvider']
[2023-12-24 23:02:47,450] [DEBUG] [engine.py:143:setup_accelerators] Initial accelerators: ['gpu']
[2023-12-24 23:02:47,450] [DEBUG] [engine.py:164:setup_accelerators] Supported execution providers for device gpu: ['CUDAExecutionProvider', 'TensorrtExecutionProvider', 'CPUExecutionProvider']
[2023-12-24 23:02:47,450] [INFO] [engine.py:181:setup_accelerators] Running workflow on accelerator specs: gpu-cpu
[2023-12-24 23:02:47,470] [DEBUG] [engine.py:482:run_no_search] Running ['qlora'] with no search ...
[2023-12-24 23:02:47,470] [INFO] [engine.py:924:_run_pass] Running pass qlora:QLoRA
[2023-12-24 23:02:48,925] [INFO] [hf_utils.py:218:load_model] Loading Huggingface model from model-cache/microsoft/phi-2
Loading checkpoint shards: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:45<00:00, 22.93s/it]
[2023-12-24 23:03:35,592] [DEBUG] [hf_utils.py:254:load_huggingface_model_from_task] Loaded model <class 'transformers.models.auto.modeling_auto.AutoModelForCausalLM'> with name_or_path model-cache/microsoft/phi-2
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
[2023-12-24 23:03:35,804] [INFO] [qlora.py:420:smart_tokenizer_and_embedding_resize] Added 1 new tokens to tokenizer and resized model embedding layer.
[2023-12-24 23:03:35,950] [DEBUG] [qlora.py:388:get_model_tokenizer] Adding LoRA modules
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
[2023-12-24 23:03:47,926] [INFO] [qlora.py:258:_run_for_config] Running QLoRA fine-tuning
0%|                                                                                | 0/1200 [00:00<?, ?it/s][2023-12-24 23:04:05,309] [ERROR] [engine.py:997:_run_pass] Pass run failed.
Traceback (most recent call last):
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/olive/engine/engine.py", line 985, in _run_pass
output_model_config = host.run_pass(p, input_model_config, data_root, output_model_path, pass_search_point)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/olive/systems/local.py", line 32, in run_pass
output_model = the_pass.run(model, data_root, output_model_path, point)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/olive/passes/olive_pass.py", line 367, in run
output_model = self._run_for_config(model, data_root, config, output_model_path)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/olive/passes/pytorch/qlora.py", line 259, in _run_for_config
train_result = trainer.train()
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/transformers/trainer.py", line 1591, in train
return inner_training_loop(
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/transformers/trainer.py", line 1892, in _inner_training_loop
tr_loss_step = self.training_step(model, inputs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/transformers/trainer.py", line 2776, in training_step
loss = self.compute_loss(model, inputs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/transformers/trainer.py", line 2801, in compute_loss
outputs = model(**inputs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/peft/peft_model.py", line 918, in forward
return self.base_model(
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/peft/tuners/tuners_utils.py", line 94, in forward
return self.model.forward(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/accelerate/hooks.py", line 165, in new_forward
output = old_forward(*args, **kwargs)
File "/home/ericv/.cache/huggingface/modules/transformers_modules/phi-2/modeling_phi.py", line 953, in forward
hidden_states = self.transformer(input_ids, past_key_values=past_key_values, attention_mask=attention_mask)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/accelerate/hooks.py", line 165, in new_forward
output = old_forward(*args, **kwargs)
File "/home/ericv/.cache/huggingface/modules/transformers_modules/phi-2/modeling_phi.py", line 915, in forward
hidden_states = layer(
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/accelerate/hooks.py", line 165, in new_forward
output = old_forward(*args, **kwargs)
File "/home/ericv/.cache/huggingface/modules/transformers_modules/phi-2/modeling_phi.py", line 770, in forward
attn_outputs = self.mixer(
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/accelerate/hooks.py", line 165, in new_forward
output = old_forward(*args, **kwargs)
File "/home/ericv/.cache/huggingface/modules/transformers_modules/phi-2/modeling_phi.py", line 722, in forward
attn_output = self._forward_self_attn(x, attention_mask)
File "/home/ericv/.cache/huggingface/modules/transformers_modules/phi-2/modeling_phi.py", line 621, in _forward_self_attn
return self.inner_attn(qkv, key_padding_mask=key_padding_mask)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/amp/autocast_mode.py", line 16, in decorate_autocast
return func(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/amp/autocast_mode.py", line 16, in decorate_autocast
return func(*args, **kwargs)
File "/home/ericv/.cache/huggingface/modules/transformers_modules/phi-2/modeling_phi.py", line 377, in forward
scores = scores + causal_mask.to(dtype=scores.dtype)
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 128.00 MiB. GPU 0 has a total capacty of 8.00 GiB of which 0 bytes is free. Including non-PyTorch memory, this process has<PHONE_NUMBER>4.00 GiB memory in use. Of the allocated memory 14.17 GiB is allocated by PyTorch, and 98.70 MiB 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
[2023-12-24 23:04:05,444] [WARNING] [engine.py:432:run_accelerator] Failed to run Olive on gpu-cpu: CUDA out of memory. Tried to allocate 128.00 MiB. GPU 0 has a total capacty of 8.00 GiB of which 0 bytes is free. Including non-PyTorch memory, this process has<PHONE_NUMBER>4.00 GiB memory in use. Of the allocated memory 14.17 GiB is allocated by PyTorch, and 98.70 MiB 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
Traceback (most recent call last):
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/olive/engine/engine.py", line 412, in run_accelerator
return self.run_no_search(
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/olive/engine/engine.py", line 483, in run_no_search
should_prune, signal, model_ids = self._run_passes(
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/olive/engine/engine.py", line 887, in _run_passes
model_config, model_id = self._run_pass(
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/olive/engine/engine.py", line 985, in _run_pass
output_model_config = host.run_pass(p, input_model_config, data_root, output_model_path, pass_search_point)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/olive/systems/local.py", line 32, in run_pass
output_model = the_pass.run(model, data_root, output_model_path, point)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/olive/passes/olive_pass.py", line 367, in run
output_model = self._run_for_config(model, data_root, config, output_model_path)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/olive/passes/pytorch/qlora.py", line 259, in _run_for_config
train_result = trainer.train()
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/transformers/trainer.py", line 1591, in train
return inner_training_loop(
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/transformers/trainer.py", line 1892, in _inner_training_loop
tr_loss_step = self.training_step(model, inputs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/transformers/trainer.py", line 2776, in training_step
loss = self.compute_loss(model, inputs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/transformers/trainer.py", line 2801, in compute_loss
outputs = model(**inputs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/peft/peft_model.py", line 918, in forward
return self.base_model(
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/peft/tuners/tuners_utils.py", line 94, in forward
return self.model.forward(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/accelerate/hooks.py", line 165, in new_forward
output = old_forward(*args, **kwargs)
File "/home/ericv/.cache/huggingface/modules/transformers_modules/phi-2/modeling_phi.py", line 953, in forward
hidden_states = self.transformer(input_ids, past_key_values=past_key_values, attention_mask=attention_mask)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/accelerate/hooks.py", line 165, in new_forward
output = old_forward(*args, **kwargs)
File "/home/ericv/.cache/huggingface/modules/transformers_modules/phi-2/modeling_phi.py", line 915, in forward
hidden_states = layer(
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/accelerate/hooks.py", line 165, in new_forward
output = old_forward(*args, **kwargs)
File "/home/ericv/.cache/huggingface/modules/transformers_modules/phi-2/modeling_phi.py", line 770, in forward
attn_outputs = self.mixer(
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/accelerate/hooks.py", line 165, in new_forward
output = old_forward(*args, **kwargs)
File "/home/ericv/.cache/huggingface/modules/transformers_modules/phi-2/modeling_phi.py", line 722, in forward
attn_output = self._forward_self_attn(x, attention_mask)
File "/home/ericv/.cache/huggingface/modules/transformers_modules/phi-2/modeling_phi.py", line 621, in _forward_self_attn
return self.inner_attn(qkv, key_padding_mask=key_padding_mask)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/amp/autocast_mode.py", line 16, in decorate_autocast
return func(*args, **kwargs)
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/torch/amp/autocast_mode.py", line 16, in decorate_autocast
return func(*args, **kwargs)
File "/home/ericv/.cache/huggingface/modules/transformers_modules/phi-2/modeling_phi.py", line 377, in forward
scores = scores + causal_mask.to(dtype=scores.dtype)
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 128.00 MiB. GPU 0 has a total capacty of 8.00 GiB of which 0 bytes is free. Including non-PyTorch memory, this process has<PHONE_NUMBER>4.00 GiB memory in use. Of the allocated memory 14.17 GiB is allocated by PyTorch, and 98.70 MiB 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
0%|                                                                                | 0/1200 [00:17<?, ?it/s]
[2023-12-24 23:04:05,707] [INFO] [engine.py:357:run] Run history for gpu-cpu:
[2023-12-24 23:04:06,050] [INFO] [engine.py:630:dump_run_history] run history:
+----------------------------------+-------------------+-------------+----------------+-----------+
| model_id                         | parent_model_id   | from_pass   | duration_sec   | metrics   |
+==================================+===================+=============+================+===========+
| c2ac57d9dcdd152c5f5dbe6b31fb29ca |                   |             |                |           |
+----------------------------------+-------------------+-------------+----------------+-----------+
[2023-12-24 23:04:06,071] [INFO] [engine.py:372:run] No packaging config provided, skip packaging artifacts

I'm running phi-2 finetuning on a lesser GPU (RTX 3060Ti 8GB) and works. It just takes a long time to finish:
(phi-2-env) zcobol@TEXAS:/mnt/c/ai/phi-2$ python finetuning/invoke_olive.py
[2023-12-25 08:59:57,186] [DEBUG] [engine.py:125:setup_accelerators] Initial execution providers: ['CPUExecutionProvider']
[2023-12-25 08:59:57,186] [DEBUG] [engine.py:143:setup_accelerators] Initial accelerators: ['gpu']
[2023-12-25 08:59:57,187] [DEBUG] [engine.py:164:setup_accelerators] Supported execution providers for device gpu: ['CUDAExecutionProvider', 'TensorrtExecutionProvider', 'CPUExecutionProvider']
[2023-12-25 08:59:57,187] [INFO] [engine.py:181:setup_accelerators] Running workflow on accelerator specs: gpu-cpu
[2023-12-25 08:59:57,213] [DEBUG] [engine.py:482:run_no_search] Running ['qlora'] with no search ...
[2023-12-25 08:59:57,213] [INFO] [engine.py:924:_run_pass] Running pass qlora:QLoRA
[2023-12-25 08:59:58,537] [INFO] [hf_utils.py:218:load_model] Loading Huggingface model from model-cache/microsoft/phi-2
Loading checkpoint shards: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:47<00:00, 23.74s/it]
[2023-12-25 09:00:48,867] [DEBUG] [hf_utils.py:254:load_huggingface_model_from_task] Loaded model <class 'transformers.models.auto.modeling_auto.AutoModelForCausalLM'> with name_or_path model-cache/microsoft/phi-2
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
[2023-12-25 09:00:48,971] [INFO] [qlora.py:420:smart_tokenizer_and_embedding_resize] Added 1 new tokens to tokenizer and resized model embedding layer.
[2023-12-25 09:00:48,986] [DEBUG] [qlora.py:388:get_model_tokenizer] Adding LoRA modules
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
[2023-12-25 09:00:59,652] [INFO] [qlora.py:258:_run_for_config] Running QLoRA fine-tuning
{'loss': 1.7088, 'learning_rate': 0.0001, 'epoch': 1.21}
{'loss': 0.9402, 'learning_rate': 0.0001, 'epoch': 2.42}
  2%|█████▎                                                                                | 29/1200 [55:06<37:05:12, 114.02s/it]{'loss': 0.781, 'learning_rate': 0.0001, 'epoch': 3.64}
{'loss': 0.6497, 'learning_rate': 0.0001, 'epoch': 4.85}
{'loss': 0.5381, 'learning_rate': 0.0001, 'epoch': 6.06}
{'loss': 0.4499, 'learning_rate': 0.0001, 'epoch': 7.27}
{'loss': 0.3674, 'learning_rate': 0.0001, 'epoch': 8.48}
{'loss': 0.3085, 'learning_rate': 0.0001, 'epoch': 9.7}
{'loss': 0.2549, 'learning_rate': 0.0001, 'epoch': 10.91}
  8%|█████████████████▏                                                                                | 95/1200 [3:00:31<35:00:44, 114.07s/it

nvidia-smi output inside WSL instance:
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 535.54.02              Driver Version: 536.19       CUDA Version: 12.2     |
|-----------------------------------------+----------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |
|                                         |                      |               MIG M. |
|=========================================+======================+======================|
|   0  NVIDIA GeForce RTX 3060 Ti     On  | 00000000:02:00.0  On |                  N/A |
| 30%   58C    P2              71W / 200W |   7875MiB /  8192MiB |    100%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+

+---------------------------------------------------------------------------------------+
| Processes:                                                                            |
|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |
|        ID   ID                                                             Usage      |
|=======================================================================================|
|  No running processes found                                                           |
+---------------------------------------------------------------------------------------+

The host system has 32GB of RAM and about 5GB is used by WSL. How much RAM has your host , and how much is reserved for WSL?

@zcobol
Host system:
Windows 11 Home...
16G DDR5 RAM...
RTX 3070 TI 8GB
WSL environment: (default of the previous error)
(phi-2-env) ericv@NITRO:/mnt/c/mnt/c/Users/ericv/source/repos/AI/SamplePHI2$ free -h --giga
total        used        free      shared  buff/cache   available
Mem:            7.5G        1.0G        6.0G        3.0M        503M        6.3G
Swap:           2.0G          0B        2.0G
There was no .wslconfig file at the default %USER_PROFILE% location...
So I created one tried multiple configs of upping memory limit... (restarted the WSLService service to get the configuration)
Settings apply across all Linux distros running on WSL 2
[wsl2]
Limits VM memory  to use no more than 4 GB, this can be set as whole numbers using GB or MB
memory=12GB
Sets the VM to use two virtual processors
processors=4
...
free -h --giga
total        used        free      shared  buff/cache   available
Mem:             11G        447M         11G        3.0M        395M         11G
Swap:           3.1G          0B        3.1G
...
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 128.00 MiB. GPU 0 has a total capacty of 8.00 GiB of which 0 bytes is free. Including non-PyTorch memory, this process has<PHONE_NUMBER>4.00 GiB memory in use. Of the allocated memory 14.17 GiB is allocated by PyTorch, and 98.70 MiB 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
0%|                                                                                | 0/1200 [00:12<?, ?it/s]
[2023-12-25 21:52:15,399] [INFO] [engine.py:357:run] Run history for gpu-cpu:
[2023-12-25 21:52:15,448] [INFO] [engine.py:630:dump_run_history] run history:
+----------------------------------+-------------------+-------------+----------------+-----------+
| model_id                         | parent_model_id   | from_pass   | duration_sec   | metrics   |
+==================================+===================+=============+================+===========+
| c2ac57d9dcdd152c5f5dbe6b31fb29ca |                   |             |                |           |
+----------------------------------+-------------------+-------------+----------------+-----------+
[2023-12-25 21:52:15,465] [INFO] [engine.py:372:run] No packaging config provided, skip packaging artifacts
Not sure why it works on your system and not mine, or whether I need to upgrade the system memory...

OK - Happy New Years first of all to each of you.
I got back to this (learning a bit more about what QLoRA is about over the holidays) and finally got it to work by changing a setting in the olive config file
./finetuning/olive-config.json
changed:
"source_max_len": 1024,
to:
"source_max_len": 512,
Note: I found this suggestion out by using copilot.microsoft.com...
Although, it also suggested that "gradient_checkpointing": true, ... however, this results in another error that check pointing is not support further down the stack. So I reverted that...
File "/opt/miniconda/envs/phi-2-env/lib/python3.9/site-packages/transformers/modeling_utils.py", line 1827, in gradient_checkpointing_enable
raise ValueError(f"{self.class.name} does not support gradient checkpointing.")
ValueError: PhiForCausalLM does not support gradient checkpointing.
So with the tweaked source_max_len being smaller - it works. (my guess for Olive, this setting is synonymous with batch_size)
Final Output:
(phi-2-env) ericv@NITRO:~/AI/SamplePHI2$ python finetuning/invoke_olive.py
[2024-01-01 12:11:25,770] [DEBUG] [engine.py:125:setup_accelerators] Initial execution providers: ['CPUExecutionProvider']
[2024-01-01 12:11:25,770] [DEBUG] [engine.py:143:setup_accelerators] Initial accelerators: ['gpu']
[2024-01-01 12:11:25,770] [DEBUG] [engine.py:164:setup_accelerators] Supported execution providers for device gpu: ['CUDAExecutionProvider', 'TensorrtExecutionProvider', 'CPUExecutionProvider']
[2024-01-01 12:11:25,770] [INFO] [engine.py:181:setup_accelerators] Running workflow on accelerator specs: gpu-cpu
[2024-01-01 12:11:25,791] [DEBUG] [engine.py:482:run_no_search] Running ['qlora'] with no search ...
[2024-01-01 12:11:25,792] [INFO] [engine.py:924:_run_pass] Running pass qlora:QLoRA
[2024-01-01 12:11:27,149] [INFO] [hf_utils.py:218:load_model] Loading Huggingface model from model-cache/microsoft/phi-2
Loading checkpoint shards: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [01:53<00:00, 56.94s/it]
[2024-01-01 12:13:21,643] [DEBUG] [hf_utils.py:254:load_huggingface_model_from_task] Loaded model <class 'transformers.models.auto.modeling_auto.AutoModelForCausalLM'> with name_or_path model-cache/microsoft/phi-2
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
[2024-01-01 12:13:21,981] [INFO] [qlora.py:420:smart_tokenizer_and_embedding_resize] Added 1 new tokens to tokenizer and resized model embedding layer.
[2024-01-01 12:13:22,017] [DEBUG] [qlora.py:388:get_model_tokenizer] Adding LoRA modules
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
[2024-01-01 12:13:33,618] [INFO] [qlora.py:258:_run_for_config] Running QLoRA fine-tuning
{'loss': 1.9, 'learning_rate': 0.0001, 'epoch': 0.6}
{'loss': 1.0769, 'learning_rate': 0.0001, 'epoch': 1.19}
{'loss': 0.8712, 'learning_rate': 0.0001, 'epoch': 1.79}
...
{'loss': 0.0062, 'learning_rate': 0.0001, 'epoch': 71.04}
{'loss': 0.0061, 'learning_rate': 0.0001, 'epoch': 71.64}
{'train_runtime': 4195.7947, 'train_samples_per_second': 1.144, 'train_steps_per_second': 0.286, 'train_loss': 0.10114002790302039, 'epoch': 71.64}
100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1200/1200 [1:09:55<00:00,  3.50s/it]
[2024-01-01 13:23:29,587] [DEBUG] [qlora.py:260:_run_for_config] train_result: TrainOutput(global_step=1200, training_loss=0.10114002790302039, metrics={'train_runtime': 4195.7947, 'train_samples_per_second': 1.144, 'train_steps_per_second': 0.286, 'train_loss': 0.10114002790302039, 'epoch': 71.64})
[2024-01-01 13:23:29,921] [DEBUG] [resource_path.py:157:create_resource_path] Resource path cache/models/11_QLoRA-c2ac57d9dcdd152c5f5dbe6b31fb29ca-ebf2cb49fc53f7d5dc8c54563ff5bd31/output_model/adapter is inferred to be of type folder.
[2024-01-01 13:23:29,990] [DEBUG] [engine.py:904:_run_passes] Signal: None
[2024-01-01 13:23:30,006] [DEBUG] [resource_path.py:157:create_resource_path] Resource path /mnt/c/mnt/c/Users/ericv/source/repos/AI/SamplePHI2/cache/models/11_QLoRA-c2ac57d9dcdd152c5f5dbe6b31fb29ca-ebf2cb49fc53f7d5dc8c54563ff5bd31/output_model/adapter is inferred to be of type folder.
[2024-01-01 13:23:32,912] [INFO] [engine.py:357:run] Run history for gpu-cpu:
[2024-01-01 13:23:32,928] [INFO] [engine.py:630:dump_run_history] run history:
+----------------------------------------------------------------------------+----------------------------------+-------------+----------------+-----------+
| model_id                                                                   | parent_model_id                  | from_pass   |   duration_sec | metrics   |
+============================================================================+==================================+=============+================+===========+
| c2ac57d9dcdd152c5f5dbe6b31fb29ca                                           |                                  |             |                |           |
+----------------------------------------------------------------------------+----------------------------------+-------------+----------------+-----------+
| 11_QLoRA-c2ac57d9dcdd152c5f5dbe6b31fb29ca-ebf2cb49fc53f7d5dc8c54563ff5bd31 | c2ac57d9dcdd152c5f5dbe6b31fb29ca | QLoRA       |        4324.18 |           |
+----------------------------------------------------------------------------+----------------------------------+-------------+----------------+-----------+
[2024-01-01 13:23:32,932] [INFO] [engine.py:372:run] No packaging config provided, skip packaging artifacts


Improve config file formatting with indented binding redirects

unitil now paket puts all binding redirects in one line which is very annoying when some binding is changing. With this pr we should improve the formatting in the config file and make it easier for the users to see what changes when they commit the changed config files.

Cool.
There was already an issue for this somewhere. @dnauck

what about already existig xml. do we reformat that?

Yes, but only the part in the runtime/configuration/assemblyBinding. Any problem with that?
The root cause of the problem is, that we load the existing config with PreserveWhitespaces which prevents reformatting on adding new XElements.

Ok if we only reformat assembly bindings then it should be fine.
@agross @dnauck?
On Apr 12, 2015 10:26 AM, "Christian"<EMAIL_ADDRESS>wrote:

Yes, but only the part in the runtime/configuration/assemblyBinding. Any
problem with that?
The root cause of the problem is, that we load the existing config with
PreserveWhitespaces which prevents reformatting on adding new XElements.
—
Reply to this email directly or view it on GitHub
https://github.com/fsprojects/Paket/pull/769#issuecomment-92008924.

:+1:

Lovely

line commits with +10k are a little bit strange when unexperienced devs see that. hope it helps also others.

@forki this was issue #597
I'll test this new stuff today.


Write more docs!

I am willing to take this on, but if anyone wants to lend a hand, please do!
I've peppered the entire Rust codebase with comments and descriptions of what everything is doing, and very soon I'm going to create a video explaining exactly how the macros work and where to find the key ingredients.
Regardless, as we get closer to beta release, we're gonna need some docs!
Feel free to join me in grabbing anything worth covering in detail from the codebase and documenting it in the markdown files on the doc site: docs/md

Hi, I can take this on with you! Would be my first time writing documentation for a project such as this so might need a bit of help at the start.

go for it, mate! The code blocks on the docs site look pretty shaky right now, as mentioned in #52 but don't let that stop you

Alright :), will start going through the code and see where I can contribute. If I have any questions is this a good medium to ask them or is there any other specific channel where I could post them?


File cannot be read after restarting meteor

Hi,
I tried to upload image using UploadFS.Uploader. It was successful and image can be accessed with the url 'http://localhost:3000/ufs/photos/uZthJNGD8twqvMJAB/iphone7plus-portrait.jpg'
After restarting meteor that url can no longer be accessed and in terminal it shows:
W20161119-12:58:43.354(7)? (STDERR) Cannot read iphone7plus-portrait.jpg
Photo item data:
{
  "_id": "uZthJNGD8twqvMJAB",
  "name": "iphone7plus-portrait.jpg",
  "size": 155971,
  "type": "image/jpeg",
  "store": "photos",
  "complete": true,
  "uploading": false,
  "extension": "jpg",
  "progress": 1,
  "userId": "bii8RJhmPfm3FCbaJ",
  "path": "ufs/photos/uZthJNGD8twqvMJAB/iphone7plus-portrait.jpg",
  "token": "2BebEb6af9",
  "uploadedAt": "2016-11-19T05:56:00.890Z",
  "url": "http://localhost:3000/ufs/photos/uZthJNGD8twqvMJAB/iphone7plus-portrait.jpg"
}

Do you have any idea how to fix this? Thanks heaps!

I've just found the answer here https://github.com/VeliovGroup/Meteor-Files/issues/46


Merge: Transition Integration Tests

Description
Transition at TTD to the merge consensus mechanism is a critical point and is likely to be encounter edge and adversarial cases.  Besu needs comprehensive coverage of the transition and reorg cases as it relates to TTD.
For more detail see:
https://eips.ethereum.org/EIPS/eip-3675#terminal-total-difficulty-vs-block-number
Acceptance Criteria
minimally, integration test cases for

nominal transition at TTD
reorg post-TTD but pre-first finalized block / call to engine_forkChoiceUpdated
attempted post-TTD reorg, post first finalized block

we could/should leverage kurtosis, but will need to add besu as a supported execution client:
https://github.com/kurtosis-tech/eth2-merge-kurtosis-module

https://github.com/parithosh/nightly-kurtosis-test/blob/main/.github/workflows/kurtosis.yml

Close in favor of hive


List index out of range  error

If I run cartpole.py I am getting list index out of range error

The issue was due to csv.reader reading a blank line. Adding a simple check resolved the issue.
add the below if statement on line 63 of score_logger.py in scores directory.
if data[i]:


Workarounds for team id inconsistency

Hello!
PROBLEM:

grafana-backup-tool can't create team with same id as in backup (api limitations)
grafana uses only team id to add team member and folder permissions
That's means impossibility to use api export + import without workarounds

WORKAROUND:
Find the real team id by name before adding a user
Thanks for your improvements to grafana-backup-tool!

BTW, let's add some file inside backup archive with version of grafana-backup-tool for clarity?


Fixed #29917 — Adjusted MRO collection of ModelAdmin.actions.

BC alternative for #10603.
Adds test case for failure from https://code.djangoproject.com/ticket/29917 plus prior/existing behaviour.
This behaviour has been untouched since https://github.com/django/django/commit/bb15cee58a43eeb0d060f8a31f9078b3406f195a, which was some time ago.

From #10603:

It seems to me that one problem with the current implementation is that there's no way to remove an action that's defined in a superclass.

The standard way is to implement get_actions() as described in Conditionally enabling or disabling actions docs.
(But implementing the kind of hierarchies needed to hit this issue, and then wanting to disable an action, might seem like a sign to do otherwise...)

This would work too of course. That being said, I have the impression that Django is a framework which eschews magic, but keeping the collecting behavior doesn't look like that to me.
There is a symmetry e.g. between list_display and get_list_display and other ModelAdmin attributes and the corresponding get_* methods, but actions and get_actions is different. I'm repeating myself, but I don't see good reasons for keeping the untested, undocumented and surprisingly different behavior around, and fixing the misbehaving code by adding even more code.
Django has historically broken backwards compatibility in ways that were much more impactful to library authors (the get_query_set -> get_queryset rename comes to mind -- but that was far from the only one). I really don't see the problem with removing a magic feature here, especially since the old behavior can be easily implemented by people really wanting it on their own by writing a short get_actions method.

Hi @matthiask. Yes, either approach would work to fix the bug you reported. For me, the one changes an API that's been stable for ≈10 years. The other leaves it as is.
I suspect that we introduce a breaking change here and then have to handle a steady stream of "Hey this used to work!" I'm not seeing the benefit of the change to justify that. (The bug has been there the whole ten years and only just reported...)
However, we could go either way.

Yes, I definitely understand that you want to avoid those reports. That was the reason for implementing the system check in the first place.
But yeah, whatever works. Your call.

Sure, thanks.
And one thing I want to look at tomorrow here is Why it was implemented this way originally. We tend to work on the assumption that previous decisions were correct (because in general they are) and so if I can dig up the history a bit, we might find a reason. (If there isn't one then the Normal Python argument gains favour.)

I followed up on the ticket.
https://code.djangoproject.com/ticket/29917#comment:12

Planning to go with https://github.com/django/django/pull/10603 unless some objections are raised within a week.

Yep. Good.


Fix link

Since this is a community submitted pull request, a Jenkins build has not been kicked off automatically. Can an Elastic organization member please verify the contents of this patch and then kick off a build manually?

When you get a chance can you take a look at the CLA. Merging is disabled unless the CLA status check is passing.

I'm closing this PR as CLA wasn't signed and URL fix was included in https://github.com/elastic/helm-charts/pull/95.


[fastlane_core] move keychain_path to core 1/3

This series of PR tries to solve following issue:

https://github.com/fastlane/fastlane/pull/7048

This is PR 1/3
as described the path is to move keychain_path to fastlane_core:

PR 1/3 -> move keychain_path to fastlane_core #7075
PR 2/3 -> refactor match to use fastlane_core keychain_path #7076
PR 3/3 -> refactor unlock_keychain to use fastlane_core keychain_path #7077

needs to be merged in the right order

Linking back here to the original issue: #7046


Rewrite Cond

Is there a way that I can add RewriteCond or I can only add rewrite rules?
Thanks

I would like to know the answer to this as well.


Question: Drivers to Connect to GS400/DB2 iSeries and create ERD

Hello,
I would like to use DBeaver to create the entity relationship diagram of a DB2 iSeries database.
I have read that in order to connect DBeaver to DB2, drivers are needed. Can you provide a list of the drivers? Does the application on top on DB2 plays any role?
Thank you in advance.

DBeaver already has DB2 drivers. Select which one you need in New database connection.
If you want to add some specific driver, this article should help you.

DBeaver already has DB2 drivers. Select which one you need in New database connection.
If you want to add some specific driver, this article should help you.

Thank you Kseniuia! Much appreciated!
On Thu, Jan 28, 2021 at 6:33 AM Kseniia<EMAIL_ADDRESS>wrote:

DBeaver already has DB2 drivers. Select which one you need in New
database connection
https://github.com/dbeaver/dbeaver/wiki/Create-Connection.
If you want to add some specific driver, this article
https://github.com/dbeaver/dbeaver/wiki/Database-drivers should help
you.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/dbeaver/dbeaver/issues/11042#issuecomment-768792756,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AKLM4CNRPXZHUN56SQUEYALS4DSJ5ANCNFSM4WIM3FGQ
.

Thank you Kseniuia! Much appreciated!
On Thu, Jan 28, 2021 at 6:33 AM Kseniia<EMAIL_ADDRESS>wrote:

DBeaver already has DB2 drivers. Select which one you need in New
database connection
https://github.com/dbeaver/dbeaver/wiki/Create-Connection.
If you want to add some specific driver, this article
https://github.com/dbeaver/dbeaver/wiki/Database-drivers should help
you.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
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.

you are welcome)

you are welcome)


rmf_task: 2.3.0-1 in 'rolling/distribution.yaml' [bloom]

Increasing version of package(s) in repository rmf_task to 2.3.0-1:

upstream repository: https://github.com/open-rmf/rmf_task.git
release repository: https://github.com/ros2-gbp/rmf_task-release.git
distro file: rolling/distribution.yaml
bloom version: 0.11.2
previous version for package: 2.1.3-1

rmf_task

No changes

rmf_task_sequence

No changes

Updated doc and source versions as per https://github.com/ros2-gbp/rmf_task-release/pull/1


Set executable bit on runit run scripts.

Just ran into an issue in production. The 'run' scripts exported for runit actually need to be executable, else it won't work.
Not really happy with the test though. The problem is that FakeFS lacks support for FileUtils.chmod and Stat#mode, so this is a quick stub. It doesn't verify any expectation.

Why 0744 instead of 0755?

No particular reason. All that was required to get the service working was a chmod +x run. The runit script is actually started as root, so I guess that is why 0744 is enough.
I always try to be as restrictive as possible when it comes to file permissions, but 0755 would be fine too.


upgrade to nginx 1.21.1

Codecov Report

Merging #5152 (64203a5) into master (3e6138d) will increase coverage by 22.80%.
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feat: set List.toArray equal to Array.mk

List.toArray l is a natural simp normal form for arrays since it unfolds during compilation so that Array literals (which are defined as List.toArray [...] of an list literal) can unfold.  The current recursive List.toArray function makes reasoning about array literals more difficult than necessary however since it is a recursive function distinct from the constructor (though the recursive definition is used by interpreter and compiler).
This makes the two logically the same, but uses csimp lemma show equivalence so that compilation behavior is preserved.
As part of this, I removed a lemma that is equivalent to Array.mk.injEq and added a test case to check compiler output.

!bench

Here is a tangentially related zulip thread about Array.data vs. Array.toList. Maybe they can be similarly made “the same” to avoid that confusion:
https://leanprover.zulipchat.com/#narrow/stream/270676-lean4/topic/Understanding.20the.20docstring.20for.20docs.23Array.2Edata/near/398705430
On the weekend I was playing around with verifying some code that uses ByteArray and Array, which are isomorphic to Lists, and it wasn’t smooth sailing yet. Pondering this issue a bit more, I think there is a design decision that std4 has to take (if it hasn't sailed yet), between:

Each of these types has a full-fledged API, with it’s own simp-canonical form, suitable extensionality lemma and all the simp lemmas you expect (often one per combination of operations).

Only one of these types is meant to be used for verification (likely List). Operations on Array and ByteArray are each specified in terms of the List one and the suitable conversion ((Array.filter xs p).toList = List.filter xs.toList p).

Currently, I think we are mostly doing 1, but there are operations (like Array.findIdx?) that don’t have the set of lemmas you’d expect. I found I sometimes had to convert from Arrays to Lists and back to get to apply the lemmas that I care about.
I have a gut feeling that 2 will scale better and lead to better, more consistent proofs, but probably only if applied consistently, i.e. there should then be no proofs about operations on Arrays besides the lemma that transports to arrays.
But it’s not what we have right now, and be too disruptive. We we’d have to do 1, but then an entitled user like me would probably expect to consistently find that every operation has the same set of lemmas on all three isomorphic data types, plus all the transport lemmas. Quite some explosion.
You probably thought about this too already; just jotting down some late evening thoughts here.

I think we can do both, to some extent. In particular, following (2) is not incompatible with having other theorems anyway, as long as all the transfer theorems are there. My inclination is to start with lemmas facilitating (2) and add API lemmas for (1) on an as-needed basis.

That’s true. I’m wondering if there is merit (hypothetically) in an an exclusive (2) approach. With a mixed approach, you start proving things at the abstraction level of ByteStrings, and half-way through you find that some lemmas you need are only there for Lists. Now you maybe start to convert back and forth in an unprincipled way, and things get hairy.
But Joe mentioned plans to have some code in place to check for API completeness. Presumably it can help to achieve (1) completely, and warn if a lemma about ByteStrings is missing based on the existence of a lemma about List.

That’s true. I’m wondering if there is merit (hypothetically) in an an exclusive (2) approach. With a mixed approach, you start proving things at the abstraction level of ByteStrings, and half-way through you find that some lemmas you need are only there for Lists. Now you maybe start to convert back and forth in an unprincipled way, and things get hairy.

All of the (1) lemmas would have very easy proofs as long as a robust (2) bridge exists, and if a (1) lemma is missing you can prove it on the spot by transporting across the bridge (and there is no "and back", it's just lifting everything to List and proving things there). And if you needed to do that, maybe PR the lemma once you're done. It should not get hairy; if it does then there are missing lemmas.

I've made some experiments with the compiler and this code, and it affects the generated code.
I'm going to see if this change in particular is easy to fix, but more changes may need to wait until there is time for the new compiler.

!bench

I've manually inspected compilation results on a small example program as well as the results of update-stage0.  This change appears to consistently preserve compiler behavior.

I think I have resolved the issue.  The csimp application seems to stop working with some changes to Init.Core, my testing would show that even an empty List namespace would cause tests to fail:
e.g., I get different behavior if I add this to Init.Core:
namespace List
end List

Moving the Append String instance from Init.Data.List.Basic to Init.Core also changed behavior.  The tests are passing now after being very careful to only move essential definitions.

What tests failed, and how? Adding a namespace List can indeed change things since it will implicitly declare the namespace if it hasn't already been declared, which in turn affects the behavior of the open command, but I don't see any particular reason this should cause issues if code was already importing Init which of course defines the List namespace.

What tests failed, and how?

Hi @digama0, It turns out I need to prioritize other issues and so I've closed this for now.
However, if you create a lean namespace in Init.Core like below, then I would see test cases that compiled to appendTR calls instead compile to append calls.  It's pretty strange.
namespace Lean
end Lean

With regards to the broader issue of Array and List compatibility, I think for some operations close equivalence is good, but others there may be efficient and elegant definitions for arrays since you have fast indexing and a Decidable instance for Fin and quantifiers (will be separate PR).
Here are a couple definitions I created before switching gears:
namespace Array

-- | This is equivalent to Array.allDiff
def allDiffIdx [BEq α] (as : Array α) : Bool :=
  ∀(i : Fin as.size) (j : Fin i),
    as[i] != as[j]'(Nat.lt_trans j.isLt i.isLt)

-- | This is equivalent to Array.all
-- It has some definite issues due to current omega limitations, but I
-- think this approach has a lot of potential to replace inductive
-- reasoning.
def allIdx (as : Array α) (p : α → Bool) (start : optParam Nat 0) (stop : optParam Nat as.size) : Bool :=
  let stop : Nat := stop
  let n := min stop as.size
  ∀(i : Fin (n - start)),
    let ⟨i, lt⟩ := i
    have _ : n ≤ as.size :=  Nat.min_le_right stop as.size
    p (as[start + i]'(by omega))

end Array


df.attrs contains only data_path

This code
gen_object = GenLauncher(mzprime=1.25, m4=0.140, neval=1000, noHF=True, HNLtype="dirac", loglevel="INFO")
df_1 = gen_object.run()

creates the dataframe df_1.
If I inspect df_1.attrs, it contains only:
{'data_path': PosixPath('data/miniboone_fhc/3plus1/m4_0.14_mzprime_1.25_dirac')}

Fixed -- not sure what the problem was, in my version it always contained both detector and model classes inside attrs?
Can you confirm this is a problem on your end? I'll put a test entry for that.

The standard behavior for older versions of pandas was to drop df.attrs when concatenating two pandas dataframes. Now we check if this happens, and if it does, we add it back in manually.


  Speed optimizations, API optimizations and refactors, some bugfixes, more thorough testing of API features.

Replaced by #88


Merging latest dev changes into global 10.27

@angaither I did a merge instead of a rebase of dev into global, and here's the result. I confirmed with @sergii-tkachenko that the latest dev changes were the correct changes for /bin/ds-global which had most of the conflicts.

:+1:


added google tag manager

Merging this... Should we need to add gtag on every Query Change?

Merging this... Should we need to add gtag on every Query Change?

Let's not do this for now. We can implement this later.


PHP notice Undefined offset: 0 Error when creating a feed

Hi,
I'm getting the following error when I try and create a new XML or JSON feed.
PHP notice
Undefined offset: 0

I'm really not sure my feeds are in a proper format. Is it possible to see an example XML or JSON feed that works with the plugin please?
Thanks

Hi there - this is likely due to not specifying the Primary Element field correctly. For reference, it should be the repeating node containing your information.
For instance, you might have:
<videos>
    <video>
        <title>My Title</title>
    </video>
    <video>
        <title>Another Title</title>
    </video>
</videos>

In which case, the primary element would be video.
Having said that, the latest master should fix all that!

Thanks for the reply, and you were indeed correct. It was my data that was causing the issue.

No worries - its a little confusing at the moment. Will be putting together full examples with walkthrough soon for XML and JSON!


Need help with certificates and connecting to ACI

This issue is for a: (mark with an x)
- [ ] bug report -> please search issues before submitting
- [ ] feature request
- [x] documentation issue or request
- [ ] regression (a behavior that used to work and stopped in a new release)

Minimal steps to reproduce

Click the "Deploy to Azure" button from the readme.

Any log messages given by the failure

On the OPC Client software
Error establishing a connection: BadNotConnected
I'm getting lots of traffic on the OPC server, potentially bots, but when connected to the logs from the azure portal here are some related messages from the OPC Server

[17:59:51 ERR] OPC: TCPSERVERCHANNEL ForceChannelFault Socket=027CB571, ChannelId=0, TokenId=0, Reason=BadConnectionClosed 'Remote side closed connection'
[17:59:51 ERR] OPC: 06/16/2022 17:59:51.575 TCPSERVERCHANNEL ForceChannelFault Socket=027CB571, ChannelId=0, TokenId=0, Reason=BadConnectionClosed 'Remote side closed connection'
[17:59:51 ERR] OPC: TCPSERVERCHANNEL ForceChannelFault Socket=03FE6417, ChannelId=0, TokenId=0, Reason=BadConnectionClosed 'Remote side closed connection'
[17:59:51 ERR] OPC: 06/16/2022 17:59:51.780 TCPSERVERCHANNEL ForceChannelFault Socket=03FE6417, ChannelId=0, TokenId=0, Reason=BadConnectionClosed 'Remote side closed connection'

Expected/desired behavior

That I can connect to the OPC Server

OS and Version?

Running cat /etc/issue on the connect of the aci returns
Debian GNU/Linux 11 \n \l
The OPC UA Client is running on my windows 10 machine.

Versions

The aci Logs show: OpcPlc V2.3.0 starting up ...

Mention any other details that might be useful
I tried my best to find documentation on the readme about how to run this docker image as an aci and manage the certificates but was not able to find any. I apologize if it's in an obvious place, but I could not find any.
As per the directions on the readme, after you run the Deploy to Azure you should be able to connect using
opc.tcp://<NAME>.<REGION>.azurecontainer.io:50000
Looking at the container logs I tried this as well as since it said it was Starting server on endpoint <endpoint-below> ...
opc.tcp://aci-<NAME>-<RNG>-plc1.<REGION>.azurecontainer.io:50000
both didn't work.
I believe the issues is that I need the certificate (der file) from the aci / opc ua server on my client machine so I can connect but I do not know how to get it. Here is some of the log at the end when the certificates are created:
[17:54:05 INF] Application store contains 1 certs
[17:54:05 INF] 01: Subject 'CN=OpcPlc' (thumbprint: xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx)
[17:54:05 INF] Trusted issuer store contains 0 certs
[17:54:05 INF] Trusted issuer store has 0 CRLs.
[17:54:05 INF] Trusted peer store contains 0 certs
[17:54:05 INF] Trusted peer store has 0 CRLs.

Looking at the logs I see there are several entries where it's creating the certificates on the container instance but that doesn't seem to be a good idea. Also, do I need to copy my OPC UA Client certificates to the server as well? I haven't gotten to that phase yet but that might be something that is needed?
I figure I can't connect because I don't have certificates on my OPC UA Client machine and perhaps I need to get certificates to the OPC UA server eventually, but none of that is clear on how to do with aci.
Can I configure the aci with where to get the certificates? is there other ways?

What client are you using to connect to the opcplc? (pls try UaExpert, for example)
You don't need to get the server certificate or upload the one from the client. The client usually shows a warning and you can accept the risk of connecting to a self-signed certificate and connect to it.
You can get the URI to your server from the Azure Portal, this is where you need to connect to:

I was using a custom client, but I downloaded UaExpert and tried and I still get an error and can't connect.
I get the option to

Please try another configuration or press 'Ignore' to force trying to connect.

Ideally I would like to have a better solution where I can actually use security and connect to an OPC UA server, hosted in a container in more realistic production scenario. Event I can get around these various prompts of getting it to work, I suspect that if I restart the container, then all the connections would fail, because a new Container would start up and a brand new set of certificates would be created and I'd have to go through this headache again.
Is there not a way to run this project, as an ACI, with some level of certificate security?
If so, can I have some help on how to do that?

In the readme we mention the following, have you tried it like this?
Note: Make sure that your OPC UA client uses security policy Basic256Sha256 and message security mode Sign & Encrypt to connect.

Restarting the container will indeed reset the certificates. You will have to mount a share to be able to persist the certificates. You will then need to modify the deployment template to pass the options related to the certificate storage, just search for "appcert" and "trustedstore" in the readme file.

Hello @ondrelogin Just checking back, could you please let us know if you need further help in this matter. Please refer  to the above response and do let us know.

Closing due to no response. Feel free to reopen if we can help.


🚀 📝 Add TFLite-convertible TFFastSpeech

This commit adds TFLite-convertible logics inside LengthRegulator.
This is tested with tf-nightly. 20200630 version. The quantized FastSpeech TFLite file can work with varied-length input & output.
Also,  we fixed the batch_size = 1 during inference.
In addition, the real problem was the input tensor_spec mismatch inside of tf.while_loop().
the 4th and 5th input tensors are growing (outputs, encoder_masks). this kind of dynamic size (not dynamic shape, please be careful of words. they are different) is not well recommended in TFLite converter. In this assumption, we removed the tf.while_loop() during inference as well.

@jaeyoo could not be more appreciated :D. Really nice trick, sice we tflite support batch-size 1 so we can simply remove tf.while_loop :)). Can you make the PR for notebook examples convert to tflite tacotron2 and fastspeech ?, i can do it if you don't have a time to do :D. BTW, What brings you here :)))

@dathudeptrai I've already created colab notebooks for both models with google internal environment. So I suggest you not to do duplicated work. Let me open the PRs for notebooks next week after cleaning up the codes. Thanks!

@dathudeptrai I've already created colab notebooks for both models with google internal environment. So I suggest you not to do duplicated work. Let me open the PRs for notebooks next week after cleaning up the codes. Thanks!

I meant, will open the new PRs for notebooks after merging my two PRs. and FYI, this PR, fastspeech, doesn't depend on dynamic_decode(), so it can be merged now. Thanks.

@jaeyoo we can copy dynamic_decode to util folder and modify it so we don't really need wait for tf_addons updated it :)) it will take much time, i think =)). When tf_addons update, i can simply remove dynamic_decode from util folder and re-install newest tf_addons :)).

@jaeyoo even if input signature is [1, None] why second dim is [1,1] ? , is this a bug ? , should i report in tflite ?
{'name': 'input_ids', 'index': 0, 'shape': array([1, 1], dtype=int32), 'shape_signature': array([ 1, -1], dtype=int32), 'dtype': <class 'numpy.int32'>, 'quantization': (0.0, 0), 'quantization_parameters': {'scales': array([], dtype=float32), 'zero_points': array([], dtype=int32), 'quantized_dimension': 0}, 'sparsity_parameters': {}}, {'name': 'attention_mask', 'index': 1, 'shape': array([1, 1], dtype=int32), 'shape_signature': array([ 1, -1], dtype=int32), 'dtype': <class 'numpy.bool_'>, 'quantization': (0.0, 0), 'quantization_parameters': {'scales': array([], dtype=float32), 'zero_points': array([], dtype=int32), 'quantized_dimension': 0}, 'sparsity_parameters': {}}, {'name': 'speaker_ids', 'index': 2, 'shape': array([1], dtype=int32), 'shape_signature': array([1], dtype=int32), 'dtype': <class 'numpy.int32'>, 'quantization': (0.0, 0), 'quantization_parameters': {'scales': array([], dtype=float32), 'zero_points': array([], dtype=int32), 'quantized_dimension': 0}, 'sparsity_parameters': {}}, {'name': 'speed_ratios', 'index': 3, 'shape': array([1], dtype=int32), 'shape_signature': array([1], dtype=int32), 'dtype': <class 'numpy.float32'>, 'quantization': (0.0, 0), 'quantization_parameters': {'scales': array([], dtype=float32), 'zero_points': array([], dtype=int32), 'quantized_dimension': 0}, 'sparsity_parameters': {}}

@manmay-nakhashi that ok :))). Don't care the shape infomation. Pls look
 'shape_signature': array([ 1, -1], dtype=int32)

-1 here is None :)) and dynamic.

@dathudeptrai but when i am running inference it's saying it can't take multiple second dim ?
ValueError: Cannot set tensor: Dimension mismatch. Got 2 but expected 1 for input 2.

@manmay-nakhashi can you use tflite-nightly ? . Dynamic shape have just supported recently. Or maybe this is an missmatch between mobile API and python API. It should run fine when deploy on real mobile :))).

@dathudeptrai i an using tflite-nightly suggested version , i think it's mobile vs python API mismatch , i'll try it on mobile :+1:

@jaeyoo even if input signature is [1, None] why dim is [1,1] ? , is this a bug ? , should i report in tflite ?
{'name': 'input_ids', 'index': 0, 'shape': array([1, 1], dtype=int32), 'shape_signature': array([ 1, -1], dtype=int32), 'dtype': <class 'numpy.int32'>, 'quantization': (0.0, 0), 'quantization_parameters': {'scales': array([], dtype=float32), 'zero_points': array([], dtype=int32), 'quantized_dimension': 0}, 'sparsity_parameters': {}}, {'name': 'attention_mask', 'index': 1, 'shape': array([1, 1], dtype=int32), 'shape_signature': array([ 1, -1], dtype=int32), 'dtype': <class 'numpy.bool_'>, 'quantization': (0.0, 0), 'quantization_parameters': {'scales': array([], dtype=float32), 'zero_points': array([], dtype=int32), 'quantized_dimension': 0}, 'sparsity_parameters': {}}, {'name': 'speaker_ids', 'index': 2, 'shape': array([1], dtype=int32), 'shape_signature': array([1], dtype=int32), 'dtype': <class 'numpy.int32'>, 'quantization': (0.0, 0), 'quantization_parameters': {'scales': array([], dtype=float32), 'zero_points': array([], dtype=int32), 'quantized_dimension': 0}, 'sparsity_parameters': {}}, {'name': 'speed_ratios', 'index': 3, 'shape': array([1], dtype=int32), 'shape_signature': array([1], dtype=int32), 'dtype': <class 'numpy.float32'>, 'quantization': (0.0, 0), 'quantization_parameters': {'scales': array([], dtype=float32), 'zero_points': array([], dtype=int32), 'quantized_dimension': 0}, 'sparsity_parameters': {}}

No, it is intended. please give me some time to open a new PR including notebook file for inference with TFLite file. For short, we need to user interpreter.resize_tensor_input() for the input_idx tensor and then run interpreter.allocate_tensors()

@jaeyoo ok


Jobs not working

I installed this plugin through Spigot and /jobs is not working. Jobs are enabled on the configs page, it is set to true. Is there anything I can do to try to fix this?

Hi @ughary, /job is the right command and it looks like it's working (as in it doesn't error out when running it), though it's not displaying anything. Is that correct? Are you running the command through chat as a player or are you using some other plugin to execute the command? Looks like you're using a non-standard way of executing those commands.

It is not displaying anything. I am new to plugins so I am not sure if I needed to do anything after getting it in my server. I am able to use balance and pay other players, but the /job command isn't working. I am running the command through chat as a player and not some other plugin. How do I use a standard way of executing those commands?

The chatbox looks different then I'm use to, though doesn't seem like that matters since the other commands are working; which is a good sign. A few other questions just to make sure we have a full picture:

Any console errors?
Which version of Total Economy? The latest (0.12.1)?
Which version of Spigot?
What does your config.yml look like under plugins/TotalEconomy/config.yml? VERY IMPORTANT: REMOVE DATABASE INFORMATION BEFORE SENDING

From what I can tell from testing on my end, when the job feature is disabled you'll end up seeing what's in your picture (the command displays in the chat but it doesn't actually execute anything). Might simply be something misconfigured in your config.yml file.

No console errors, when I type job in console it shows up as:
23.06 06:30:51 [Server] Server thread/INFO /job
23.06 06:30:51 [Multicraft] ughAry ran command: job
Yes, 0.12.1 (April 26th)
Spigot 1.21 (latest)
Under database, it says Features and then jobs: true. True is in purple. That's all.

I'll try testing it with the above versions you provided tomorrow.
In the meantime, is it "Features" or "features" that you have? Make sure it looks something like this:
database:
    url: jdbc:mysql://localhost:3306/totaleconomy
    user: root
    password: password
features:
    jobs: true

user: root
password: password

features:
jobs: true
Yes it's exactly the same

I have essentialsX plugin and vault

No console errors, when I type job in console it shows up as:
23.06 06:30:51 [Server] Server thread/INFO /job
23.06 06:30:51 [Multicraft] ughAry ran command: job
Yes, 0.12.1 (April 26th)
Spigot 1.21 (latest)
Under database, it says Features and then jobs: true. True is in purple. That's all.

Haven't had the chance to test this with the above versions on my end yet, though another thing to note is that 0.12.1 is not tested on versions after 1.20.4..

Hey @ughary, was able to test some stuff on my end. First of all, Total Economy 0.12.1 does not support Bukkit/Spigot/Paper 1.21; 1.20.4 is the highest version supported currently. Attempting to launch Total Economy 0.12.1 against 1.21 led to some issues, which is expected.
I think the reasons the balance and pay commands work is because those are also EssentialsX commands as they provide an economy implementation of their own. If you downgrade to 1.20.4 and remove EssentialsX (or disable the economy portion of EssentialsX), you shouldn't encounter any issues. I realize Essentials also provides tons of other useful commands, though I have no experience with that plugin so I'd recommend reaching out to them and asking how to handle compatibility between their plugin and other economy plugins like Total Economy; they probably have something on their wiki. I assume they have a configuration option to allow compatibility with other economy plugins.
Let me know if the downgrading to 1.20.4 and disabling the conflicting EssentialsX functionality works. Thanks.

I changed the version, but I can't disable economy in EssentialsX. I can't remove EssentialsX because of their other features so I reached out to them and see if I could use another plugin's (TotalEconomy) economy instead. Thank you for your help!

Going to close for now. Please feel free to reopen if necessary. Thanks.


how to use it in a component library?

is it suitable for a component library?

Hi @lili21, thanks for your interest. CSS Hooks works great for component libraries! In fact, the only setup required for someone using your component library is to add your hooks style sheet somewhere in their app as described in Step 3 of the Getting started guide. It's up to you how you'd like to document this for your users; or, if you wanted to hide CSS Hooks completely as a "private implementation detail", you could even create a simplified component wrapper around the <style> element, along the lines of this example (although you might want to consider a more generic name in this case, e.g. ComponentLibraryStyleSheet).
Please let me know if you have any specific questions/concerns, and I'd be happy to discuss! Otherwise, I'll leave the issue open for a few days in case anyone else wants to chime in.


Octokit::ServerError in Communication::Website::IndirectObject::SyncWithGitJob@elephant

Error in Osuny
Octokit::ServerError in Communication::Website::IndirectObject::SyncWithGitJob@elephant
POST https://api.github.com/repos/osunyorg/sufficiencylab-site/git/commits: 504 -

Unicorn! · GitHub

An error linked to this issue has been marked as fixed in Bugsnag
Octokit::ServerError in Communication::Website::IndirectObject::SyncWithGitJob@elephant

An error linked to this issue has been reopened in Bugsnag
Octokit::ServerError in Communication::Website::CleanAndRebuildJob@whale


Problem with Huawei phone encripted backup

Hello people, I need help considering this topic, I have Huawei backup done directly from the phone Mate 10 Pro under Android 10, it was done from recovery mode with the Emergency Backup peocedure. BUT, backup didn't finished completely and correctly, some folders like pictures are completely copied, but I am missing some informational file called info.xml (and maybe also some others), and restore procedure from phone, or this Python script and procedure is not working because it can't locate this file and backup is not recognized, restore is not starting. My files that are successfully copied are normal size and with normal extensions, but they are crypted with password that I had to use, the password is not the problem, I know it, but I don't know how to decrypt now my files without complete informational files that are missing from backup structure. Any help, ideas, please?

Then do you have cinfoset.dat or backupinfo.ini? cinfoset.dat seems to be having identical content with info.xml so you can copy/rename it i guess. Don't know if backupinfo.ini is useful on its own as well. It also seems that the encryption uses not only user-entered password but also random salt (it's salt, not sh*t), so one or more of the info files are necessary. Not sure. Better wait for the author to reply.

Hi @AcaRadovanovic
Never got an Emergency Backup to with, so I don't know if there is something special (I guess..). Particularly a "broken" one. I would try to act as @oO0oO0oO0o0o00 suggested.


Update recommended npm-scripts to use local webpack version in docs

Hey Jeffrey, had an issue with your recommended npm scripts in the docs:
When not having webpack globally installed, there was an error because the global install was used.
Hope this was not of any purpose and thank you for your work :)

You do not actually need webpack to be globally installed for the current package.json scripts to work.

I think this should be merge

@simonvomeyser npm look for bin files from your project folder first at your_project_folder/node_modules/.bin/ before resorting to globals. You might need to check if the .bin folder exists in your setup.


Name-Registry: Replace str[8] with String

Motivation
As a precursor to #450 we may update to use the hash of the string.

Closed by https://github.com/FuelLabs/sway-applications/pull/761


Add oper-specific help

This still needs work... an app with a single operation should still call the oper's help methods.


Auditing: using OSystem server database

In v2.2 the Auditing has to log into the System Database instead of current database, by using 1 cluster per database with the following name: <db>_auditing

Released in 2.2.1.


About file encoding?

It look like MoonPlus can not handle file encoding utf8 with special characters...
Or may be windows build have that problem:
print "月+ = 🌙"

=>
return print("月+ = ")

Maybe I don't know but what encoding MoonPlus using or anyway to config that?
Can you check that?
Thanks and regards!

Found that used the wrong converter function from STL that can't handle special unicode character. Should be fixed by newest commit now.

Found that used the wrong converter function from STL that can't handle special unicode character. Should be fixed by newest commit now.

confirmed!
Thanks!

confirmed!
Thanks!


Time-off policy for requests under 4 hours

URL of RTD document: https://civicactions-handbook.readthedocs.io/en/iris-i-patch-1/

Rejecting this PR. I will submit a new PR with revised language that communicates the same substantive point.


Investigate timeouts in remote imports

See https://github.com/jakubpawlowicz/clean-css/issues/372#issuecomment-91899163

@MarkHerhold please see cc8a285e2889e3736a8eeef7ab606088970ba1d3 for details - let's see if it helps, but it may also be anything related to network configuration - see https://github.com/jakubpawlowicz/clean-css/issues/372#issuecomment-93849824

@jakubpawlowicz Great, thanks!
I'll give it a shot tonight!

I still get sporadic timeouts when importing google fonts with this fix applied (v3.2.10)
I get it in various network configurations.
It happens around 30% of the times i'd say.
I circumvented it by applying --skip-import so it's not a big deal for me...

@mderazon that's odd indeed - I wonder if it applies to anything else than Google Fonts...


No output for html reports

Hi team, I have tried to run reports functions on jupyter notebook. However, there's no outpute for
qs.reports.html(stock, "SPY"), could any one advise what's missing? Thanks
`

qs.reports.metrics(mode='basic|full", ...) - shows basic/full metrics
qs.reports.plots(mode='basic|full", ...) - shows basic/full plots
qs.reports.basic(...) - shows basic metrics and plots
qs.reports.full(...) - shows full metrics and plots
qs.reports.html(...) - generates a complete report as html`

problem solved

No output is generated for me too, How did you solve this problem? @boyac

@AkiMosi Please try this out qs.reports.html(output="yourfilename.html")

Yaa, got the file. Thank you @boyac

@AkiMosi awesome! 👍


Bug with CSS color squares when moving line up

VSCode Version: Code - Insiders 1.12.0-insider (fc7f97dcafd2d9df7cfd45ac895c376727057491, 2017-04-02T01:13:41.591Z)
OS Version: Linux x64 4.8.0-45-generic
Extensions:

Extension
Author
Version

EditorConfig
EditorConfig
0.6.2

lorem-ipsum
Tyriar
1.0.0

sort-lines
Tyriar
1.2.0

theme-sapphire
Tyriar
0.0.5

vscode-svgviewer
cssho
1.4.0

tslint
eg2
0.11.0

git-project-manager
felipecaputo
1.2.1

md-navigate
jrieken
0.0.1

vscode-scss
mrmlnc
0.6.2

seti-icons
qinjia
0.1.3

IMO it has to do on how decorator positions are adapted on document changes
No plans to fix. I realise it looks funny, but placement recovers.


Some minor documentation fixes

Description in PR https://github.com/maebert/jrnl/pull/425

Merged, thanks!


lms7 - bad freqency reported for TX and RX

as of commit c02f4358 API returns bad values for RX and TX frequency ranges supported by device (and it broke for example sdrangel). please apply following patch to fix this issue:
diff --git a/src/API/lms7_device.cpp b/src/API/lms7_device.cpp
index c957dd7..b576ce1 100644
--- a/src/API/lms7_device.cpp
+++ b/src/API/lms7_device.cpp
@@ -748,7 +748,7 @@ LMS7_Device::Range LMS7_Device::GetTxPathBand(unsigned path, unsigned chan) cons
 {
   switch (path)
   {
-      case LMS_PATH_TX2: return Range(2e6, 3.8e6);
+      case LMS_PATH_TX2: return Range(2e9, 3.8e9);
       case LMS_PATH_TX1: return Range(30e3, 2e9);
       default: return Range();
   }
@@ -1291,7 +1291,7 @@ double LMS7_Device::GetFrequency(bool tx, unsigned chan) const

 LMS7_Device::Range LMS7_Device::GetFrequencyRange(bool tx) const
 {
-  return Range(30e6, 3.8e6);
+  return Range(30e6, 3.8e9);
 }

 int LMS7_Device::Init()

patch applied 67d88c54690eecf6b73f0a06ab5e58429926bc6d

ok, but souldn't it actually be 100e3 - 3.8e9 for limesdr and 10e6 - 3.5e9 for the mini?
I've also noticed that LMS_PATH_TX1 above is off as well - it's 30e3 and not 30e6.

Already fixed in 29f8f4c39b8a0


Credit card checker in c++

I want to add code for credit card checker in c++. Please assign this issue to be under hacktoberfest 2024.

Hey @DHEERAJHARODE , I'm interested in this issue , can you assign this issue to me for the Hacktoberfest 2024.


Migration from netlify-cms

I followed all migration steps from docs but still netlify-cms opening on admin path.

Git Gateway with Netlify backend
removing all netlify-cms imports and components
also did a clean npm
-latest version of static-cms

If you are still getting netlify-cms, that means you must have missed something when replacing it.

Did you remember to uninstall netlify-cms, besides simply installing static-cms?
Is there a script loaded from CDN that you didn't change, perhaps someplace you forgot you had it?

Could you show your admin/index.html?

I uninstalled netlify-cms and netlify-cms-app components and of course gatsby-plugin-netlify-cms, changed import to @staticcms/core
my static/admin/config.yml looks like this:
backend:
  name: git-gateway
  branch: main

locale: 'de'
media_folder: static/img
public_folder: /img

collections:

  - name: "blog"
    label: "News"

and my src/cms/cms.js looks like this:
import CMS, { de } from '@staticcms/core'
CMS.registerLocale('de', de)
CMS.init()

Well, then I don't know. Seems nonsensical that netlify-cms shows up even though it's not even installed, Only thing I can think of is that maybe there is a <script<EMAIL_ADDRESS>lurking somwehere you forgot, don't understand how else netlify-cms could be there.
You're probably gonna have to wait for someone more knowledgeable than me to help out.

Another possibility:
Did you remove netlify-cms from package.json. I'm guessing the build command includes npm install. In that case the build process would just reinstall netlify-cms every time.

Yes, netlify-cms is removed everywhere

Do you have a repository you could link to? So I could take a look at what the issue may be.
Also there is a Gatsby template here you can use as a reference: https://github.com/StaticJsCMS/static-cms-gatsby-netlify-template

Thank you for the Gatsby template, I had a look on this and found that the gatsby-plugin-static-cms was missing. netlify-cms is now cleaned but whitescreen on /admin path to login like your template site.
How are you login on the template site: https://static-cms-gatsby.netlify.app
because on admin path -> netlify-identity-widget doesn't open

Ah good point. The template appears to be broken. Will look into it tomorrow.

Okay, the issue was it needed to use app (which includes react and react dom) vs core (which does not). The template has been updated.
To fix it in your setup you will need to switch to<EMAIL_ADDRESS>and<EMAIL_ADDRESS>

Yes sir, now it's working


DragItemStartCallback parameters

Hi. I've noticed when logging endDrag that startItemPos shows the column position, and startColumnPos shows the Item position. So in that sense, they're twisted.  My temporary workaround was to switch the order like this :
@Override
            public void endDrag(View view, int startColumnPos, int startItemPos, int endItemPos, int endColumnPos) {...}

Both startDrag and endDrag are affected. changedPosition seems ok
Also endItemPos and endColumnPos are ok. Only start positions are affected

Sorry it took so long to fix this little issue. This is fixed as of the latest commit!
Thanks!


PHI Network

 https://docs.phi.network
Chainlist.org/chain/144
Chainlist.org/chain/4181
Description
Decentralized social entertainment economy

Name: PHI

HD Derivation Scheme:

Symbol: PHI

Documentation: docs.phi.network

Reason: fastest growing blockchain with the lowest transaction fees with very fast transaction times. The worlds first and only decentralized social entertainment economy
Checklist
Finish check list here.

Hello, we have an issue to simplify the listing of ETH chains here - closing for now

Looked into this there's no proper instructions how do we integrate custom evm chain. Also why can't users add custom chains manually to trust wallet.


todo items are not rendered

Hi, the following change seems to resolve the item rendering issue:
// common/shadow_dom.ts

export const shadowDomInjectables: Array<any> = !isNativeShadowDOMSupported ? [] : [
  //bind(ShadowDomStrategy).toClass(NativeShadowDomStrategy)
  NativeShadowDomStrategy
];

And this change resolved a related issue caused by this.el.shadowRoot being null:
// app/components/icon/icon.ts

set src(src: string) {
  //let root;
  //if (isNativeShadowDOMSupported) root = this.el.shadowRoot;
  //else root = this.el;
  this.icon.get(src).then((svg) => {
    //root.appendChild(svg);
    this.el.appendChild(svg);
  });
}

@r-park that doesn't really solve the issue. It just doesn't use NativeShadowDomStrategy anymore which makes the icons work again, but that is not really what I am looking for.
I would still like to have Shadow DOM used if supported and the icons work properly no matter if Shadow DOM is used or not.
I will have to take a look into it, but I also reported it as #3222 and hopefully I will get some insight on what is going on.


Add poll_result to EmbedType

https://github.com/discord/discord-api-docs/pull/7050

There's a lot more to it than just an embed type

I was looking about the embed fields of type "poll_result", then I decided to use the getMessage method, and apparently, it already returns an array of embeds with the corresponding fields 🤔
[
  { inline: false, name: 'poll_question_text', value: 'test' },
  { inline: false, name: 'victor_answer_votes', value: '1' },
  { inline: false, name: 'total_votes', value: '1' },
  { inline: false, name: 'victor_answer_id', value: '1' },
  { inline: false, name: 'victor_answer_text', value: '1' }
]

So, that's why I decided to add only that type of embed 😅
You can try to get a message of that type and you will see that it will possibly return an embed of type "poll_result"


[DEFECT] Genetic Algorithm doesn't recognize constants and functions

Defect Description
Genetic Algorithm optimizer doesn't recognize constants or functions.
What did you expect to see happen?
Expected the optimizer node to pass constants via multirun that could be accessed by an external model.
What did you see instead?
External model doesn't receive constants and throws an error when trying to access the constants.
Do you have a suggested fix for the development team?
Have GA send constants like gradient descent
Describe how to Reproduce
Steps to reproduce the behavior:

Put constant node into genetic algorithm optimization node/ MC sampler node in any of the GA tests
Have external model manipulate the constant
Get error AttributeError: 'Object' object has no attribute '[constant name]'

Screenshots and Input Files
Please attach the input file(s) that generate this error.  The simpler the input, the faster we can find the issue.
Added Constant:

Manipulated in external model:

Error:

Platform (please complete the following information):

OS: Windows
Version: [e.g. 22]
Dependencies Installation: CONDA

For Change Control Board: Issue Review
This review should occur before any development is performed as a response to this issue.

[x] 1. Is it tagged with a type: defect or task?
[x] 2. Is it tagged with a priority: critical, normal or minor?
[x] 3. If it will impact requirements or requirements tests, is it tagged with requirements?
[x] 4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users.
[x] 5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

For Change Control Board: Issue Closure
This review should occur when the issue is imminently going to be closed.

[x] 1. If the issue is a defect, is the defect fixed?
[x] 2. If the issue is a defect, is the defect tested for in the regression test system?  (If not explain why not.)
[x] 3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
[x] 4. If the issue is a defect, does it impact the latest release branch? If yes, is there any issue tagged with release (create if needed)?
[x] 5. If the issue is being closed without a pull request, has an explanation of why it is being closed been provided?

@aalfonsi can you send an email to the user regarding the fix for this issue in PR #1666?

@wangcj05  is this okay? if so, can you send it?
Dear users, An issue has been identified with the genetic algorithms. That optimizer did not accept constants, functions and correlated variables. As for PR  #1666 (merged in the devel/master branches), the optimizer now behaves similarly to other optimizers and samplers.


Update --allow-root and --allow-other documentation

Description of change
Using --allow-root and --allow-other together resulted in unexpected results. This makes a documentation change to improve understanding.
Relevant issues: N/A
Does this change impact existing behavior?
No functionality changes.

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license and I agree to the terms of the Developer Certificate of Origin (DCO).

Hi Alex, thanks for your contribution. I tested that these two options really conflict each other, but I think we prefer to make changes to the CliArgs to make sure people can't use them together. Created https://github.com/awslabs/mountpoint-s3/pull/475 for that.

Thanks @monthonk - Makes sense!


1.0.0 rc3

Changes
Closes #17.
This PR updates Northstar-PHP to automatically parse and store the user's role when it's returned as part of the access token (DoSomething/northstar#375). This allows client applications to automatically use the user role stored in Northstar rather than having to duplicate that logic everywhere.
By using the role:admin or role:staff scope (DoSomething/northstar#382), this also allows apps like Aurora can request a token that can only be used by users with those Northstar roles. So Aurora is no longer responsible for acting as the gatekeeper for allowing people to view/edit user records! It'll check the access token to see if a user is authorized so it can show a pretty error screen, but even if the user got hold of their token it wouldn't grant them any additional privileges they didn't already have.
This pull request aaaaaalso changes the included user provider to verify credentials within the retrieveByCredentials method, since it was otherwise stuck making two HTTP requests which is kinda crummy. TBH, it might make more sense to just have a custom NorthstarAuth class to handle all this rather than trying to fit it into the user provider contract, but idk. That's for a future PR (#18). 😆

For review: @weerd @angaither

ahh, lovely!

post-merge 👍


Add PinInput component

Please check the styles/types as this is my first "bigger" contribution and I'm not yet that familar with them. Could you additionaly check the tests "itSupportsSystemProps" whether there could be more added.

Please add component documentation

Thanks!


cant stop process

cant easily stop this process and open the port

ive tried everything to turn off your app but cant seem to get it to work.  no matter what localhost:9000 will always be TETRYS.  maybe you want to add some documentation on how to turn this off?

i found out what it was.  it was the service worker.  please add documentation around this.

Hey @adriaanbalt, thanks for raising this! Yeah the ServiceWorker is quite persistent to be honest. I have the same issue with similar projects, and always had to do a hard refresh.
I should probably disable the SW on a dev environments.


Bottom banner on top of content

The bottom banner showing Nexus version etc. is overlaid on top of the content, and hides some of my gargoyle switches.
Screenshot:

Just commenting out the position:aboslute in the nexus css is enough for me.
#footer {
    background-color: #ffffff;
    border-top: 1px solid #d5d9db;
    padding: 20px 0;
    //position: absolute;
...

This was already fixed in #56 / 86e3ce58f0459607cbda4111b53d15fa42979af3 but hasn't been released - sorry about that, will release now.

1.4.0 just released on PyPI, enjoy.

Cheers!


✨ Add gitlab shortcode

#639 PR with prototype implementation of the proposed shortcode.
It is a simple adaptation of the current github shortcode.

@DiogoM1 thanks Diogo
Could you please also add this to the docs shortcode page?

@nunocoracao Hey, hope it addresses your request. I added a GitLab instance URL as there are many institutes like the one I was at that host their packages in public self hosted instances. Hope the documentation also covers everything fully.

hey
template for shortcode "github" not found
how fix that?


Change require to require_relative for dep file in ruby_generator.cc

Normally we use require when requiring library. In this case we are generating local file which should be required as require_relative.

@donnadionne

@stanley-cheung @apolcyn Can one of you please take a look. This PR looks like a fix for a bug with a lot of attention.

Any update for this ?


Redraw map after width change by div

From @JoergPf on December 4, 2014 12:28
Hi, I have a map in a bootstrap div:
<div class="col-xs-10 col-xs-offset-1" id="kartencol">
          <leaflet defaults="defaults" center="center" paths="meinePfade" bounds="bounds"     decorations="decorations" width="100%" height="480px" markers="markers"></leaflet>
</div>

Then I use jquery and css animation to change the width of the col div and put a form next to it.
$('#kartencol').toggleClass('col-xs-10 col-xs-7')
$('#formcol').toggleClass('col-xs-0 col-xs-3')

It works great, but when I now do something with the map like setting bounds, angular still thinks I have the old map width.
How do I do a redraw or anything else with the map, to let angular know about the new width?
Best
Joerg
Copied from original issue: tombatossals/angular-leaflet-directive#556

From @sebasrodriguez on December 8, 2014 0:33
One way to solve this is by calling map.invalidateSize();
That recalculates the new map size and redraws it on screen.

I've got a similar problem with angular-material. It uses flexbox and I think that leaflet directive drew it before angular-material resizes the boxes on page. Then I got some 404 errors on leaflet and the map don't get renderized.


pre releases should not tag to "latest"

one more suggestion/feature request :)
right now if you use the preid option it will publish to npm as latest, meaning it will be the package shows up on npmjs.com, and what is installed when you npm install. Generally I think this is not what folks want as a default for alpha's or beta's. Perhaps we can decide on a default tag (such as "next", or "alpha"/"beta") and tag the release when there is a prelease. It should probably be something it prompts you for when releasing though.
in terms of technical needs it should just be as simple as running npm publish --tag [your-tag]
I could maybe put together a PR if that's helpful.

Yeah... I totally agree. It's a must have feature.
I'll do it :sparkle:

Closed by #14
I've checked it https://github.com/AlexKVal/es6-prototype-proj/releases
I've published it with: release --preid beta --tag canary

Command
> npm install es6-prototype-proj@canary

will install "version": "0.0.87-beta.0",

https://github.com/AlexKVal/release-script/releases/tag/v0.3.0 version has been published :tada:


Code in the middle is missing a parameter

Hello,
The main code here to create the database is missing a location parameter and should read:
    # Create PostgreSQL Flexible Server
    server_params = Server(
        location=location,
        sku=Sku(name='Standard_D4s_v3', tier='GeneralPurpose'),
        administrator_login='pgadmin',
        administrator_login_password='mySecurePassword',
        version="14",
        storage=Storage(storage_size_gb=32),
        create_mode="Create"
    )

Cheers
Josh

Document Details
⚠ Do not edit this section. It is required for learn.microsoft.com ➟ GitHub issue linking.

ID: ca709567-ffa5-f525-e264-ed5e2d913a2c
Version Independent ID: 6d4814d1-98b2-7b60-814b-33d5a589ce9c
Content: Quickstart: Create an Azure Database for PostgreSQL Flexible Server - Azure libraries (SDK) for Python
Content Source: articles/postgresql/flexible-server/quickstart-create-server-python-sdk.md
Service: postgresql
Sub-service: flexible-server
GitHub Login: @AwdotiaRomanowna
Microsoft Alias: alkuchar

@joshuafernandes
Thanks for your feedback! We will investigate and update as appropriate.

Hi @AwdotiaRomanowna,
Could you please look into this document request, thanks.

Hi @joshuafernandes, location is defined up here:
if name == 'main':
subscription_id = '<subscription_id>'
resource_group = '<resource_group>'
server_name = ''
location = 'eastus'

Hello @AwdotiaRomanowna , the location is defined but never passed as an argument to server_params = Server( thats where this is breaking. Try running the sample code with up to date python3 libs and you'll see. It is only passed to the resource group but not to the psql object to create

location=location,

thank you @joshuafernandes, the change will be live soon

Hi @AwdotiaRomanowna,
Could you please look into this document request, thanks.

I did the change, please close


Remove unused debug helpers

Replaces #49. /cc @pzuraq
This was an easy one, as it turned out actually none of those helpers were in use anymore! 😝
Also removed unused babel-plugin-filter-imports.

Thanks @simonihmig!


Add AMD, CommonJS and Plain Browser Support, add typings for TypeScript

Add AMD, CommonJS and Plain Browser Support therefore it would load without an issue in some scenarios
Create typings therefore the types can be used in typescript

Thank you for your contribution. I have been away from my open source projects for a while so it took me some time to check it out, but I really appreciate it.
Cheers!


Lecture Request - CKA

Lecture Addition Request for CRD's, Operators, Stateful Sets and Admission Controllers

Hi @tarunarora20
CRDs and Admission Controllers are covered by CKAD/CKS
You can raise requests for new courses by going to the following link. If something similar to what you're looking for is already present in the list, simply upvote it else add a new request.
Thanks.
https://kodekloud.com/request-a-course/


email signature

The analytics should try to recognize an email signature and typical "tasks" associated with it on  every email and not associate a task with it. Examples include "Please consider the environment before printing," "If you are not the intendedrecipient, please forward the message to<EMAIL_ADDRESS>and delete it from your computer and network"
[Enter feedback here]

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: 74c447e0-fae6-a016-c6bf-01438701ce17
Version Independent ID: b6d82917-aee4-2808-00ce-df6c20b75766
Content: Insights Outlook add-in - Workplace Analytics Office 365
Content Source: WorkplaceAnalytics/MyAnalytics/Use/add-in.md
Product: mya
GitHub Login: @paul9955
Microsoft Alias: v-midehm

@bcrogs --I'll pass this on to the team. Thanks for your feedback!


bring-wasm-filters-back

Description
This PR fixes #1304
Notes for Reviewers

Signed commits

[ ] Yes, I signed my commits.

Ah great 👍!
Are we looking to add "Wasm filter" name as well to top-right corner of the card like other cards are having?
@vishalvivekm

Ah great 👍! Are we looking to add "Wasm filter" name as well to top-right corner of the card like other cards are having? @vishalvivekm

OH yes
Thanks @GaganpreetKaurKalsi 😄

Good @vishalvivekm

Thank you @Chadha93 @GaganpreetKaurKalsi :)


Auto-generate icons for assets with no icon file

As a user, I want to see a placeholder icon for tokens with no icon that includes up to 5 characters of the token's symbol
AC:

If an asset doesn’t have an icon, an icon is auto-generated using up to 6 characters of the token's symbol from the contract.
The Icon looks good with 3-6 characters

I can take this up, I have done this before for user avatars in a project of my own before

I can take this up, I have done this before for user avatars in a project of my own before

@amitojsingh366 I just changed the AC for this from using jdenticon to auto-generating an icon using the token's symbol (ie. FOX). Do you still want to take this on?

I can take this up, I have done this before for user avatars in a project of my own before

@amitojsingh366 I just changed the AC for this from using jdenticon to auto-generating an icon using the token's symbol (ie. FOX). Do you still want to take this on?

wait I thought that's how you wanted it in the first place 🤣
so yeah sure, I can still take this

awesome :D cc @0xdef1cafe to bountify this

@willyogo could you put a few assets that have no icons in the issue description, it'd be a big help for when I start working on this

@willyogo @amitojsingh366 Moving conversation for this over to here because it appears to be more of a lib bounty.
https://github.com/shapeshift/lib/issues/354

@theoboldfrazier @willyogo the way I was thinking of doing this was just making a circular div an positioning the symbol as text in it accordingly, not sure how that is suited for lib 😕. Unless you had a different implementation in mind?

@amitojsingh366 Yes. That makes sense to me. You will need some code in web. The idea behind moving it as a lib issue is that we want to make sure the icon generation is happening there.