organization string | repo_name string | base_commit string | iss_html_url string | iss_label string | title string | body string | code null | pr_html_url string | commit_html_url string | file_loc string | own_code_loc list | ass_file_loc list | other_rep_loc list | analysis dict | loctype dict | iss_has_pr int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
keras-team | keras | da86250e5a95a7adccabd8821b0d51508c82bddc | https://github.com/keras-team/keras/issues/18439 | stat:awaiting response from contributor
stale
type:Bug | Problem with framework agnostic KerasVariable slicing with another KerasVariable | I defined a KerasVariable with shape (n,d) in a `keras.Layer()` using `self.add_weight()`. I've also defined another KerasVariable with shape (1) , dtype="int32", and value 0.
```
self.first_variable = self.add_weight(
initializer="zeros", shape=(self.N,input_shape[-1]), trainable=False
)
self.second_variable = self.add_weight(initializer="zeros",shape=(1), trainable=False, dtype="int32")
```
During a call to this custom layer, I'm trying to retrieve a specific index of the first variable using the 2nd variable with:
`self.first_variable[self.second_variable.value]`
This works as expected in pytorch backend, but throws an error in tensorflow backend.
```
Only integers, slices (`:`), ellipsis (`...`), tf.newaxis (`None`) and scalar tf.int32/tf.int64 tensors are valid indices, got <tf.Variable 'custom_layer/variable_1:0' shape=(1,) dtype=int32>
Arguments received by CustomLayer.call():
• x=tf.Tensor(shape=(None, 1600), dtype=float32)
• training=True
``` | null | null | null | {'base_commit': 'da86250e5a95a7adccabd8821b0d51508c82bddc', 'files': [{'path': 'keras/src/ops/core.py', 'Loc': {"(None, 'slice', 388)": {'mod': []}}, 'status': 'modified'}]} | [] | [] | [] | {
"iss_type": "1",
"iss_reason": "3",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"keras/src/ops/core.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null |
nvbn | thefuck | 09d9f63c98f9c4fc0953dd3fd6fb4589e9e1f6f3 | https://github.com/nvbn/thefuck/issues/376 | Shell history polution | I haven't used this, but I just thought maybe this is not such a good idea because it's going to make traversing shell history really irritating. Does this do anything to get around that, or are there any workarounds?
If not, I know in zsh you can just populate the command line with whatever you want using LBUFFER and RBUFFER. What if you made it an option to type "fuck" then hit ctrl-F (for "fuck"), and it would just replace your command line with the correction, and if there's multiple candidates cycle through them by hitting ctrl-F again. That also lets you edit the correction however you want as well.
| null | null | null | {} | [] | [] | [
{
"org": "ohmyzsh",
"pro": "ohmyzsh",
"path": [
"plugins/thefuck"
]
}
] | {
"iss_type": "4",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "2",
"info_type": "Code"
} | {
"code": [],
"doc": [],
"test": [],
"config": [],
"asset": [
"plugins/thefuck"
]
} | null | |
nvbn | thefuck | 6975d30818792f1b37de702fc93c66023c4c50d5 | https://github.com/nvbn/thefuck/issues/1087 | Thinks 'sl' is install python softlayer |
Ah, yes. This wasn't a mis-spelling of ls at all, but me installing Python-Softlayer.
The output of `thefuck --version` (something like `The Fuck 3.1 using Python
3.5.0 and Bash 4.4.12(1)-release`):
The Fuck 3.30 using Python 3.8.2 and Bash 5.0.16(1)-release
Your system (Debian 7, ArchLinux, Windows, etc.):
Manjaro
How to reproduce the bug:
Type sl in the terminal, then fuck
<!-- It's only with enough information that we can do something to fix the problem. -->
| null | null | null | {'base_commit': '6975d30818792f1b37de702fc93c66023c4c50d5', 'files': [{'path': 'thefuck/rules/sl_ls.py', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "3",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"thefuck/rules/sl_ls.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null | |
hiyouga | LLaMA-Factory | 921778a7cfa442409d17ab946c5f579e308c4f2b | https://github.com/hiyouga/LLaMA-Factory/issues/404 | invalid | api调用时，回答的内容中出现莫名其妙的自动问答 | 使用的baichuan-13b模型
使用的scr/api_demo.py
提问内容为：你好
回答会如图
不明白为什么会出现自动的多轮自我问答 | null | null | null | {'base_commit': '921778a7cfa442409d17ab946c5f579e308c4f2b', 'files': [{'path': 'README.md', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "2",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0\nreadme中提及",
"info_type": "Doc"
} | {
"code": [],
"doc": [
"README.md"
],
"test": [],
"config": [],
"asset": []
} | null |
hiyouga | LLaMA-Factory | 984b202f835d6f3f4869cbb1f0460bb2d9163fc1 | https://github.com/hiyouga/LLaMA-Factory/issues/6562 | solved | Batch Inference Error for qwen2vl Model After Full Fine-Tuning | ### Reminder
- [X] I have read the README and searched the existing issues.
### System Info
- `llamafactory` version: 0.9.2.dev0
- Python version: 3.8.20
- PyTorch version: 2.4.1+cu121 (GPU)
- Transformers version: 4.46.1
- Datasets version: 3.1.0
- Accelerate version: 1.0.1
- PEFT version: 0.12.0
- TRL version: 0.9.6
### Reproduction
I have fine-tuned the qwen2vl model using the command:
```python
llamafactory-cli train examples/train_full/qwen2vl_full_sft.yaml
```
After saving the model in the "saves" directory, I attempted to perform batch inference using the provided script:
```python
python scripts/vllm_infer.py --model_name_or_path path_to_merged_model --dataset alpaca_en_demo
```
However, I encountered the following error:
```python
ValueError: This model does not support image input.
```
1.The model_path I used points to the model saved after running the full fine-tuning script.
2.I have successfully used the LoRA fine-tuned model (trained with the lora_sft script and merged with merge_lora script), which allows for inference using the method provided in the qwen2vl documentation.
3.However, the model saved after full fine-tuning does not seem to support direct inference in the same way.
### Others
_No response_ | null | null | null | {'base_commit': '984b202f835d6f3f4869cbb1f0460bb2d9163fc1', 'files': [{'path': 'scripts/vllm_infer.py', 'Loc': {"(None, 'vllm_infer', 38)": {'mod': [43]}}, 'status': 'modified'}]} | [] | [] | [] | {
"iss_type": "1",
"iss_reason": "3",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"scripts/vllm_infer.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null |
hiyouga | LLaMA-Factory | 4ed2b629a51ef58d229c795e85238d40346ecb58 | https://github.com/hiyouga/LLaMA-Factory/issues/5478 | solved | Can we set default_system in yaml file when training? | ### Reminder
- [X] I have read the README and searched the existing issues.
### System Info
- `llamafactory` version: 0.8.4.dev0
- Platform: Linux-5.4.0-125-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyTorch version: 2.4.0+cu121 (GPU)
- Transformers version: 4.44.2
- Datasets version: 2.21.0
- Accelerate version: 0.33.0
- PEFT version: 0.12.0
- TRL version: 0.9.6
- GPU type: NVIDIA A800-SXM4-80GB
- DeepSpeed version: 0.15.0
### Reproduction
llamafactory-cli train
### Expected behavior
We do not need the `default_system` in `template.py`.
Set `default_system` in training yaml file to overwrite so we do not need to modify the source code in `template.py`.
### Others
_No response_ | null | null | null | {'base_commit': '4ed2b629a51ef58d229c795e85238d40346ecb58', 'files': [{'path': 'data/', 'Loc': {}}, {'path': 'data/', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "3",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [],
"doc": [],
"test": [],
"config": [],
"asset": [
"data/"
]
} | null |
hiyouga | LLaMA-Factory | 18c6e6fea9dcc77c03b36301efe2025a87e177d5 | https://github.com/hiyouga/LLaMA-Factory/issues/1971 | solved | llama'response repeat input then the answer | ### Reminder
- [ ] I have read the README and searched the existing issues.
### Reproduction
input_ids = tokenizer(["[INST] " +{text}" + " [/INST]"], return_tensors="pt", add_special_tokens=False).input_ids.to('cuda')
generate_input = {
"input_ids": input_ids,
"max_new_tokens": 512,
"do_sample": True,
"top_k": 10,
"top_p": 0.95,
"temperature": 0.01,
"repetition_penalty": 1.3,
"eos_token_id": tokenizer.eos_token_id,
"bos_token_id": tokenizer.bos_token_id,
"pad_token_id": tokenizer.pad_token_id
}
generate_ids = model.generate(**generate_input)
response = tokenizer.decode(generate_ids[0], skip_special_tokens=True)
print(response)
### Expected behavior
I expect that llama just response the answer. for example,
input is "[INST] how are you [/INST]", output "**I am fine**"
but it repeat the input, the output is "**[INST] how are you [/INST] I am fine**"
### System Info
_No response_
### Others
Do you have any suggestions? This behaviour will limit the speed of the output and I wonder why this happen? | null | null | null | {'base_commit': '18c6e6fea9dcc77c03b36301efe2025a87e177d5', 'files': [{'path': 'src/llmtuner/chat/chat_model.py', 'Loc': {"('ChatModel', 'chat', 88)": {'mod': [102]}}, 'status': 'modified'}]} | [] | [] | [] | {
"iss_type": "2",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"src/llmtuner/chat/chat_model.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null |
hiyouga | LLaMA-Factory | 13eb365eb768f30d46967dd5ba302ab1106a96b6 | https://github.com/hiyouga/LLaMA-Factory/issues/1443 | solved | deepspeed进行一机八卡断点续训时，直接配置--checkpoint_dir参数，仅加载model权重，无法加载optimizer权重 | 在配置baichuan2模型在固定 `step` 进行断点续训时，希望同时加载mp_rank_00_model_states.pt以及zero_pp_rank_*_mp_rank_00_optim_states.pt
然而，在使用如下命令 `--checkpoint_dir` 启动断点续训时，并没有载入优化器zero_pp_rank_*_mp_rank_00_optim_states.pt
`
deepspeed --num_gpus ${NUM_GPUS_PER_WORKER} src/train_bash.py \
--stage sft \
--model_name_or_path /xxxxxxxxxx/model_weight \
--deepspeed ./ds_config.json \
--do_train \
--dataset alpaca_gpt4_en \
--template default \
--checkpoint_dir /xxxxxxxxxxxxxxxxx/output_sft/checkpoint-1 \
--finetuning_type full \
--output_dir ./output_sft \
--overwrite_cache \
--overwrite_output_dir \
--per_device_train_batch_size 2 \
--gradient_accumulation_steps 16 \
--lr_scheduler_type cosine \
--logging_steps 1 \
--save_steps 10000 \
--learning_rate 5e-5 \
--num_train_epochs 10.0 \
--plot_loss \
--fp16 | tee logs/train_g16_lr5e.log
`
请问如何才能顺利加载所有权重与状态？ | null | null | null | {'base_commit': '13eb365eb768f30d46967dd5ba302ab1106a96b6', 'files': [{'path': 'src/llmtuner/tuner/sft/workflow.py', 'Loc': {"(None, 'run_sft', 19)": {'mod': [67]}}, 'status': 'modified'}]} | [] | [] | [] | {
"iss_type": "3",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"src/llmtuner/tuner/sft/workflow.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null |
hiyouga | LLaMA-Factory | 5377d0bf95f2fc79b75b253e956a7945f3030ad3 | https://github.com/hiyouga/LLaMA-Factory/issues/908 | solved | 评估指标除了BLEU 分数和汉语 ROUGE 分数还能使用其他的评估指标吗？ | 我想把模型用于意图词槽的提取，一般这个任务的评价指标是准确率和F1 score等，请问在这个项目里能使用准确率和F1 score作为评价指标吗？应该怎么做呢？谢谢大佬解答~ | null | null | null | {'base_commit': '5377d0bf95f2fc79b75b253e956a7945f3030ad3', 'files': [{'path': 'src/llmtuner/tuner/sft/metric.py', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "3",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"src/llmtuner/tuner/sft/metric.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null |
hiyouga | LLaMA-Factory | 93809d1c3b73898a89cbdd99061eeeed5fd4f6a7 | https://github.com/hiyouga/LLaMA-Factory/issues/1120 | solved | 系统提示词 | 想请教下大佬，“系统提示词（非必填）“框传入的内容怎么输入给模型的，怎么和”输入。。“框传入的内容拼接的？对应的代码在哪里？
感谢感谢 | null | null | null | {'base_commit': '93809d1c3b73898a89cbdd99061eeeed5fd4f6a7', 'files': [{'path': 'src/llmtuner/extras/template.py', 'Loc': {"('Template', '_encode', 93)": {'mod': [109]}}, 'status': 'modified'}]} | [] | [] | [] | {
"iss_type": "5",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"src/llmtuner/extras/template.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null |
hiyouga | LLaMA-Factory | 757564caa1a0e83d184100604e43efe3c5030c0e | https://github.com/hiyouga/LLaMA-Factory/issues/2584 | solved | 请教llama pro应该怎么用？是可以用来微调吗？ | ### Reminder
- [X] I have read the README and searched the existing issues.
### Reproduction
请教llama pro应该怎么用？是可以用来做pt和SFT吗？
### Expected behavior
_No response_
### System Info
_No response_
### Others
_No response_ | null | null | null | {'base_commit': '757564caa1a0e83d184100604e43efe3c5030c0e', 'files': [{'path': 'tests/llama_pro.py', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "3",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"tests/llama_pro.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null |
hiyouga | LLaMA-Factory | e678c1ccb2583e7b3e9e5bf68b58affc1a71411c | https://github.com/hiyouga/LLaMA-Factory/issues/5011 | solved | Compute_Accuracy | ### Reminder
- [X] I have read the README and searched the existing issues.
### System Info
I'm curious about this metrics for and how could i use this? and when? ( ComputeAccuracy )
and I saw llama-factory paper's metrics ( multi-choice ) and I wonder if this metrics are match with ComputeAccuracy
anyone can answer me ?
please tell me how can i use this metrics, give me some example commands
thank you!
### Reproduction
.
### Expected behavior
_No response_
### Others
_No response_ | null | null | null | {'base_commit': 'e678c1ccb2583e7b3e9e5bf68b58affc1a71411c', 'files': [{'path': 'examples/train_lora/llama3_lora_eval.yaml', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "3",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "配置"
} | {
"code": [],
"doc": [],
"test": [],
"config": [
"examples/train_lora/llama3_lora_eval.yaml"
],
"asset": []
} | null |
hiyouga | LLaMA-Factory | 955e01c038ccc708def77f392b0e342f2f51dc9b | https://github.com/hiyouga/LLaMA-Factory/issues/4787 | solved | 全量微调BaiChuan2-7B-Chat的yaml文件中如何修改超参数能在三张A6000上运行 | ### Reminder
- [X] I have read the README and searched the existing issues.
### System Info
- `llamafactory` version: 0.8.2.dev0
- Platform: Linux-3.10.0-1160.88.1.el7.x86_64-x86_64-with-glibc2.17
- Python version: 3.8.19
- PyTorch version: 2.3.0+cu121 (GPU)
- Transformers version: 4.41.2
- Datasets version: 2.20.0
- Accelerate version: 0.31.0
- PEFT version: 0.11.1
- TRL version: 0.9.4
- GPU type: NVIDIA RTX A6000
- DeepSpeed version: 0.14.0
- vLLM version: 0.4.3
### Reproduction
```yaml
### model
model_name_or_path: /data/Baichuan2-7B-Chat
### method
stage: sft
do_train: true
finetuning_type: full
### ddp
ddp_timeout: 180000000
deepspeed: examples/deepspeed/ds_z3_config.json
### dataset
dataset: entity
template: baichuan2
cutoff_len: 1024
max_samples: 1000
overwrite_cache: true
preprocessing_num_workers: 16
### output
output_dir: saves/baichuan2-7b/full/sft
logging_steps: 10
save_steps: 500
plot_loss: true
overwrite_output_dir: true
### train
per_device_train_batch_size: 1
gradient_accumulation_steps: 2
learning_rate: 1.0e-4
num_train_epochs: 3.0
lr_scheduler_type: cosine
warmup_ratio: 0.1
pure_bf16: true
### eval
val_size: 0.1
per_device_eval_batch_size: 1
eval_strategy: steps
eval_steps: 500
```
### Expected behavior
您的项目中给出7B模型能在120G的显存上运行，现在我在3张A6000上运行会出现OOM，希望您能告诉我怎么修改超参数能让它跑起来。我也参考了之前的issue，设置了pure_bf16，仍然不能运行。
### Others
_No response_ | null | null | null | {'base_commit': '955e01c038ccc708def77f392b0e342f2f51dc9b', 'files': [{'path': 'examples/deepspeed/ds_z3_offload_config.json', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "3",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"examples/deepspeed/ds_z3_offload_config.json"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null |
hiyouga | LLaMA-Factory | 955e01c038ccc708def77f392b0e342f2f51dc9b | https://github.com/hiyouga/LLaMA-Factory/issues/4803 | solved | predict_oom | ### Reminder
- [X] I have read the README and searched the existing issues.
### System Info
model_name_or_path: llm/Qwen2-72B-Instruct
# adapter_name_or_path: saves/qwen2_7b_errata_0705/lora_ace04_instruction_v1_savesteps_10/sft
### method
stage: sft
do_predict: true
finetuning_type: lora
### dataset
dataset: prompt_to_get_cot_normal
template: qwen
cutoff_len: 2048
max_samples: 1000
overwrite_cache: true
preprocessing_num_workers: 16
### output
output_dir: saves/qwen2_72b_errata_0712/lora/predict
overwrite_output_dir: true
### eval
per_device_eval_batch_size: 1
predict_with_generate: true
ddp_timeout: 180000000
### Reproduction
8卡A100 80G 在 72b 的基座 predict 1k的数据显示oom, 所有的显卡同时加载整个模型参数, 导致oom
据官方 160G 即可, 我这80*8 都不够, 请问是bug还是需要设置什么参数;
### Expected behavior
_No response_
### Others
_No response_ | null | null | null | {'base_commit': '955e01c038ccc708def77f392b0e342f2f51dc9b', 'files': [{'path': 'Examples/train_lora/', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "1",
"iss_reason": "3\n用户配置错误",
"loc_way": "comment",
"loc_scope": "3",
"info_type": "config"
} | {
"code": [],
"doc": [],
"test": [],
"config": [],
"asset": [
"Examples/train_lora/"
]
} | null |
hiyouga | LLaMA-Factory | 3f11ab800f7dcf4b61a7c72ead4e051db11a8091 | https://github.com/hiyouga/LLaMA-Factory/issues/4178 | solved | glm-4-9b-chat-1m do_predict得到的generated_predictions.jsonl中的label出现了\n和一些非数据集中的结果。 | ### Reminder
- [X] I have read the README and searched the existing issues.
### System Info
llamafactory 0.7.2.dev0
Python 3.10.14
ubuntu 20.04
### Reproduction
$llamafactory-cli train glm_predict.yaml
generated_predictions.jsonl 输出
{"label": "\n[S,137.0]", "predict": "\n[S,137.0]"}
{"label": "\n", "predict": "\n"}
{"label": "\n", "predict": "\n"}
{"label": "\n[S,593", "predict": "\n[S,593"}
{"label": "\n[H,593", "predict": "\n[S,593"}
glm_predict.yaml 内容
### model
model_name_or_path: ./THUDM_glm-4-9b-chat-1m
adapter_name_or_path: saves/glm/lora/sft
### method
stage: sft
do_predict: true
finetuning_type: lora
### dataset
dataset: data_v0.1
template: glm4
overwrite_cache: true
preprocessing_num_workers: 16
### output
output_dir: saves/glm/lora/predict
### eval
per_device_eval_batch_size: 4
predict_with_generate: true
### Expected behavior
期望输出
generated_predictions.jsonl 输出
{"label": "[S,137.0]", "predict": "[S,137.0]"}
{"label": "[S,593]", "predict": "[S,593]"}
{"label": "[H,593]", "predict": "[S,593]"}
只包含"\n"的结果都没有出现在数据集中。
### Others
_No response_ | null | null | null | {'base_commit': '3f11ab800f7dcf4b61a7c72ead4e051db11a8091', 'files': [{'path': 'src/llamafactory/data/template.py', 'Loc': {'(None, None, None)': {'mod': [663, 664]}}, 'status': 'modified'}]} | [] | [] | [] | {
"iss_type": "2",
"iss_reason": "3",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"src/llamafactory/data/template.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null |
hiyouga | LLaMA-Factory | d46c136c0e104c50999df18a88c42658b819f71f | https://github.com/hiyouga/LLaMA-Factory/issues/230 | solved | 使用本项目训练baichuan-13b之后，如何在baichuan-13b中加载训练完的模型 | 训练完成后如何应该如何在baichuan-13b的项目中修改加载训练完成后的模型？ | null | null | null | {'base_commit': 'd46c136c0e104c50999df18a88c42658b819f71f', 'files': [{'path': 'src/export_model.py', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "3",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"src/export_model.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null |
hiyouga | LLaMA-Factory | 024b0b1ab28d3c3816f319370ed79a4f26d40edf | https://github.com/hiyouga/LLaMA-Factory/issues/1995 | solved | Phi-1.5跑RM lora 出现'NoneType' object is not subcriptable | ### Reminder
- [X] I have read the README and searched the existing issues.
### Reproduction
sh脚本：
```
deepspeed --num_gpus 8 --master_port=9901 src/train_bash.py \
--stage rm \
--model_name_or_path Phi-1.5 \
--deepspeed ds_config.json \
--adapter_name_or_path sft_lora \
--create_new_adapter \
--do_train \
--dataset comparision_gpt4_en \
--template default \
--finetuning_type lora \
--lora_target Wqkv \
--overwrite_ouput_dir \
--output_dir rm_lora \
--per_device_train_batch_size 2 \
--gradient_accumulation_steps 4 \
--lr_scheduler_type cosine \
--logging_steps 1 \
--save_steps 200 \
--learning_rate 1e-6 \
--num_train_epochs 1.0 \
--max_steps 200 \
--fp16 > rm.log 2>&1 &
wait
```
### Expected behavior
期望结果：成功读取权重并进入训练
### System Info
设备：NPU
包版本：
```
transformers==4.36.1
deepspeed==0.12.4
peft==0.7.1
trl==0.7.4
torch==2.1.0
accelerate==0.25.0
```
### Others
报错信息：
Traceback
File "src/train_bash.py" line 14
main()
File "src/train_bash.py" line 5
run_exp()
File "LLaMA-Factory/src/llmtuner/train/tuner.py", line 28 in run_exp
run_rm(model_args, data_args, training_args, finetuning_args, callbacks)
File "LLaMA-Factory/src/llmtuner/train/rm/workflow.py", line 50, in run_rm
train_result = trainer.train(resume_from_checkpoint=training_args.resume_from_checkpoint)
File "transformers/trainer.py" line 2728
loss = self.compute_loss(model, inputs)
File "LLaMA-Factory/src/llmtuner/train/rm/trainer.py" in line 41, in compute_loss
_, _, values = model(**inputs, output_hidden_states=True, return_dict=True)
File ".../trl/models/modeling_value_head.py", in line 175. in forward
last_hidden_state = base_model_output.hidden_state[-1]
TypeError: 'NoneType' object is not subscriptable
我一开始怀疑是权重问题，重新下载了权重依然报该错误，尝试将Phi-1.5换成Phi-2同样报错
| null | null | null | {} | [] | [] | [
{
"org": "docs",
"pro": "transformers",
"path": [
"model_doc/phi"
]
}
] | {
"iss_type": "1",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "2",
"info_type": "Doc"
} | {
"code": [],
"doc": [
"model_doc/phi"
],
"test": [],
"config": [],
"asset": []
} | null |
hiyouga | LLaMA-Factory | d46c136c0e104c50999df18a88c42658b819f71f | https://github.com/hiyouga/LLaMA-Factory/issues/226 | solved | 请问项目中对多轮对话语料的处理方式 | 是用多个历史对话拼接后作为input来预测最后一轮的回答吗？还是把历史对话拆分成多个轮次的训练语料比如5轮次对话可以拆分成1 2 3 4 5轮次对话样本。关于具体的处理过程代码 能否请作者指出一下 我想学习学习。谢谢。 | null | null | null | {'base_commit': 'd46c136c0e104c50999df18a88c42658b819f71f', 'files': [{'path': 'src/llmtuner/dsets/preprocess.py', 'Loc': {"(None, 'preprocess_supervised_dataset', 50)": {'mod': []}}, 'status': 'modified'}]} | [] | [] | [] | {
"iss_type": "5",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"src/llmtuner/dsets/preprocess.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null |
zylon-ai | private-gpt | 2f3aab9cfdc139f399387dbb90300d5a8bf8d2f1 | https://github.com/zylon-ai/private-gpt/issues/375 | bug | ValueError: Requested tokens exceed context window of 1000 | After I ingest a file, run privateGPT and try to ask anything, I get following error:
```
Traceback (most recent call last):
File "C:\Stable_Diffusion\privateGPT\privateGPT.py", line 75, in <module>
main()
File "C:\Stable_Diffusion\privateGPT\privateGPT.py", line 47, in main
res = qa(query)
File "C:\Users\olegt\AppData\Local\Programs\Python\Python310\lib\site-packages\langchain\chains\base.py", line 140, in __call__
raise e
File "C:\Users\olegt\AppData\Local\Programs\Python\Python310\lib\site-packages\langchain\chains\base.py", line 134, in __call__
self._call(inputs, run_manager=run_manager)
File "C:\Users\olegt\AppData\Local\Programs\Python\Python310\lib\site-packages\langchain\chains\retrieval_qa\base.py", line 120, in _call
answer = self.combine_documents_chain.run(
File "C:\Users\olegt\AppData\Local\Programs\Python\Python310\lib\site-packages\langchain\chains\base.py", line 239, in run
return self(kwargs, callbacks=callbacks)[self.output_keys[0]]
File "C:\Users\olegt\AppData\Local\Programs\Python\Python310\lib\site-packages\langchain\chains\base.py", line 140, in __call__
raise e
File "C:\Users\olegt\AppData\Local\Programs\Python\Python310\lib\site-packages\langchain\chains\base.py", line 134, in __call__
self._call(inputs, run_manager=run_manager)
File "C:\Users\olegt\AppData\Local\Programs\Python\Python310\lib\site-packages\langchain\chains\combine_documents\base.py", line 84, in _call
output, extra_return_dict = self.combine_docs(
File "C:\Users\olegt\AppData\Local\Programs\Python\Python310\lib\site-packages\langchain\chains\combine_documents\stuff.py", line 87, in combine_docs
return self.llm_chain.predict(callbacks=callbacks, **inputs), {}
File "C:\Users\olegt\AppData\Local\Programs\Python\Python310\lib\site-packages\langchain\chains\llm.py", line 213, in predict
return self(kwargs, callbacks=callbacks)[self.output_key]
File "C:\Users\olegt\AppData\Local\Programs\Python\Python310\lib\site-packages\langchain\chains\base.py", line 140, in __call__
raise e
File "C:\Users\olegt\AppData\Local\Programs\Python\Python310\lib\site-packages\langchain\chains\base.py", line 134, in __call__
self._call(inputs, run_manager=run_manager)
File "C:\Users\olegt\AppData\Local\Programs\Python\Python310\lib\site-packages\langchain\chains\llm.py", line 69, in _call
response = self.generate([inputs], run_manager=run_manager)
File "C:\Users\olegt\AppData\Local\Programs\Python\Python310\lib\site-packages\langchain\chains\llm.py", line 79, in generate
return self.llm.generate_prompt(
File "C:\Users\olegt\AppData\Local\Programs\Python\Python310\lib\site-packages\langchain\llms\base.py", line 134, in generate_prompt
return self.generate(prompt_strings, stop=stop, callbacks=callbacks)
File "C:\Users\olegt\AppData\Local\Programs\Python\Python310\lib\site-packages\langchain\llms\base.py", line 191, in generate
raise e
File "C:\Users\olegt\AppData\Local\Programs\Python\Python310\lib\site-packages\langchain\llms\base.py", line 185, in generate
self._generate(prompts, stop=stop, run_manager=run_manager)
File "C:\Users\olegt\AppData\Local\Programs\Python\Python310\lib\site-packages\langchain\llms\base.py", line 405, in _generate
self._call(prompt, stop=stop, run_manager=run_manager)
File "C:\Users\olegt\AppData\Local\Programs\Python\Python310\lib\site-packages\langchain\llms\llamacpp.py", line 225, in _call
for token in self.stream(prompt=prompt, stop=stop, run_manager=run_manager):
File "C:\Users\olegt\AppData\Local\Programs\Python\Python310\lib\site-packages\langchain\llms\llamacpp.py", line 274, in stream
for chunk in result:
File "C:\Users\olegt\AppData\Local\Programs\Python\Python310\lib\site-packages\llama_cpp\llama.py", line 618, in _create_completion
raise ValueError(
ValueError: Requested tokens exceed context window of 1000
```
I tried it with docx and pdf, used models are ggml-vic13b-q5_1.bin and stable-vicuna-13B.ggml.q4_0.bin.
During ingestion or loading privateGPT I get no error.
OS: Windows 10
CPU: Ryzen 7 3700
RAM: 32gb
| null | null | null | {'base_commit': '2f3aab9cfdc139f399387dbb90300d5a8bf8d2f1', 'files': [{'path': 'ingest.py', 'Loc': {"(None, 'process_documents', 114)": {'mod': [124]}}, 'status': 'modified'}]} | [] | [
".env"
] | [] | {
"iss_type": "1",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0\nor\n1",
"info_type": "Code"
} | {
"code": [
"ingest.py"
],
"doc": [],
"test": [],
"config": [
".env"
],
"asset": []
} | null |
zylon-ai | private-gpt | 24cfddd60f74aadd2dade4c63f6012a2489938a1 | https://github.com/zylon-ai/private-gpt/issues/1125 | LLM mock donot gives any output | i have downloaded the llm models
used this
poetry install --with local
poetry run python scripts/setup
still i get this output
| null | null | null | {'base_commit': '24cfddd60f74aadd2dade4c63f6012a2489938a1', 'files': [{'path': 'settings.yaml', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "2",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Config\nCode"
} | {
"code": [],
"doc": [],
"test": [],
"config": [
"settings.yaml"
],
"asset": []
} | null | |
zylon-ai | private-gpt | dd1100202881a01b6b013b7bc1faad8b5c63fec9 | https://github.com/zylon-ai/private-gpt/issues/850 | primordial | privateGPT中文提问显示token超出限制，英文提问不存在这个问题 |
token的计算方式很奇怪五个字指令的token比七个字多
| null | null | null | {} | [] | [
".env"
] | [] | {
"iss_type": "1",
"iss_reason": "4",
"loc_way": "comment",
"loc_scope": "1",
"info_type": "config"
} | {
"code": [],
"doc": [],
"test": [],
"config": [
".env"
],
"asset": []
} | null |
zylon-ai | private-gpt | d17c34e81a84518086b93605b15032e2482377f7 | https://github.com/zylon-ai/private-gpt/issues/1724 | Error in Model Download and Tokenizer Fetching During Setup Script Execution | ### Environment
Operating System: Macbook Pro M1
Python Version: 3.11
Description
I'm encountering an issue when running the setup script for my project. The script is supposed to download an embedding model and an LLM model from Hugging Face, followed by their respective tokenizers. While the script successfully downloads the embedding and LLM models, it fails when attempting to download the tokenizer with a 404 Client Error.
### Steps to Reproduce
Run `poetry run python scripts/setup`
Embedding model (BAAI/bge-small-en-v1.5) and the LLM model (mistral-7b-instruct-v0.2.Q4_K_M.gguf) are downloaded successfully.
The script then attempts to download a tokenizer and fails.
### Actual Behavior
The script throws an error when trying to download the tokenizer. The error message indicates a 404 Client Error: Not Found for url: https://huggingface.co/None/resolve/main/tokenizer_config.json. This suggests that either the tokenizer's name is not being correctly passed (as indicated by the 'None' in the URL) or there's an issue with the tokenizer's availability on Hugging Face.
### Logs
```bash
22:02:47.207 [INFO ] private_gpt.settings.settings_loader - Starting application with profiles=['default']
Downloading embedding BAAI/bge-small-en-v1.5
Fetching 14 files: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████| 14/14 [00:00<00:00, 14.81it/s]
Embedding model downloaded!
Downloading LLM mistral-7b-instruct-v0.2.Q4_K_M.gguf
LLM model downloaded!
Downloading tokenizer None
Traceback (most recent call last):
File "/Users/User/Projects/Tests/privateGPT/.venv/lib/python3.11/site-packages/huggingface_hub/utils/_errors.py", line 270, in hf_raise_for_status
response.raise_for_status()
File "/Users/User/Projects/Tests/privateGPT/.venv/lib/python3.11/site-packages/requests/models.py", line 1021, in raise_for_status
raise HTTPError(http_error_msg, response=self)
requests.exceptions.HTTPError: 404 Client Error: Not Found for url: https://huggingface.co/None/resolve/main/tokenizer_config.json
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/Users/User/Projects/Tests/privateGPT/.venv/lib/python3.11/site-packages/transformers/utils/hub.py", line 398, in cached_file
resolved_file = hf_hub_download(
^^^^^^^^^^^^^^^^
File "/Users/User/Projects/Tests/privateGPT/.venv/lib/python3.11/site-packages/huggingface_hub/utils/_validators.py", line 118, in _inner_fn
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File "/Users/User/Projects/Tests/privateGPT/.venv/lib/python3.11/site-packages/huggingface_hub/file_download.py", line 1374, in hf_hub_download
raise head_call_error
File "/Users/User/Projects/Tests/privateGPT/.venv/lib/python3.11/site-packages/huggingface_hub/file_download.py", line 1247, in hf_hub_download
metadata = get_hf_file_metadata(
^^^^^^^^^^^^^^^^^^^^^
File "/Users/User/Projects/Tests/privateGPT/.venv/lib/python3.11/site-packages/huggingface_hub/utils/_validators.py", line 118, in _inner_fn
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File "/Users/User/Projects/Tests/privateGPT/.venv/lib/python3.11/site-packages/huggingface_hub/file_download.py", line 1624, in get_hf_file_metadata
r = _request_wrapper(
^^^^^^^^^^^^^^^^^
File "/Users/User/Projects/Tests/privateGPT/.venv/lib/python3.11/site-packages/huggingface_hub/file_download.py", line 402, in _request_wrapper
response = _request_wrapper(
^^^^^^^^^^^^^^^^^
File "/Users/User/Projects/Tests/privateGPT/.venv/lib/python3.11/site-packages/huggingface_hub/file_download.py", line 426, in _request_wrapper
hf_raise_for_status(response)
File "/Users/User/Projects/Tests/privateGPT/.venv/lib/python3.11/site-packages/huggingface_hub/utils/_errors.py", line 320, in hf_raise_for_status
raise RepositoryNotFoundError(message, response) from e
huggingface_hub.utils._errors.RepositoryNotFoundError: 404 Client Error. (Request ID: Root=1-65f21479-09e39977255bdb72502d4b8c;66371627-2d02-44c6-8f25-d115820c1986)
Repository Not Found for url: https://huggingface.co/None/resolve/main/tokenizer_config.json.
Please make sure you specified the correct `repo_id` and `repo_type`.
If you are trying to access a private or gated repo, make sure you are authenticated.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/Users/User/Projects/Tests/privateGPT/scripts/setup", line 43, in <module>
AutoTokenizer.from_pretrained(
File "/Users/User/Projects/Tests/privateGPT/.venv/lib/python3.11/site-packages/transformers/models/auto/tokenization_auto.py", line 767, in from_pretrained
tokenizer_config = get_tokenizer_config(pretrained_model_name_or_path, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/User/Projects/Tests/privateGPT/.venv/lib/python3.11/site-packages/transformers/models/auto/tokenization_auto.py", line 600, in get_tokenizer_config
resolved_config_file = cached_file(
^^^^^^^^^^^^
File "/Users/User/Projects/Tests/privateGPT/.venv/lib/python3.11/site-packages/transformers/utils/hub.py", line 421, in cached_file
raise EnvironmentError(
OSError: None is not a local folder and is not a valid model identifier listed on 'https://huggingface.co/models'
If this is a private repository, make sure to pass a token having permission to this repo either by logging in with `huggingface-cli login` or by passing `token=<your_token>`
```
### Additional Information
It seems like the script is not correctly fetching the name or identifier for the tokenizer.
The issue might be related to how the tokenizer's name is being resolved or passed in the script (None).
I also tried with docker compose, yielding same results. Maybe it is just some setting that I am missing from the docs?
Thank you
| null | null | null | {'base_commit': 'd17c34e81a84518086b93605b15032e2482377f7', 'files': [{'path': 'settings.yaml', 'Loc': {'(None, None, 42)': {'mod': [42]}}, 'status': 'modified'}]} | [] | [] | [] | {
"iss_type": "1",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Config\nCode"
} | {
"code": [],
"doc": [],
"test": [],
"config": [
"settings.yaml"
],
"asset": []
} | null | |
zylon-ai | private-gpt | 026b9f895cfb727da523a20c59773146801236ba | https://github.com/zylon-ai/private-gpt/issues/13 | gpt_tokenize: unknown token '?' | gpt_tokenize: unknown token '?'
gpt_tokenize: unknown token '?'
gpt_tokenize: unknown token '?'
gpt_tokenize: unknown token '?'
gpt_tokenize: unknown token '?'
gpt_tokenize: unknown token '?'
gpt_tokenize: unknown token '?'
gpt_tokenize: unknown token '?'
gpt_tokenize: unknown token '?'
gpt_tokenize: unknown token '?'
gpt_tokenize: unknown token '?'
gpt_tokenize: unknown token '?'
gpt_tokenize: unknown token '?'
gpt_tokenize: unknown token '?'
gpt_tokenize: unknown token '?'
gpt_tokenize: unknown token '?'
gpt_tokenize: unknown token '?'
gpt_tokenize: unknown token '?'
[1] 32658 killed python3 privateGPT.py | null | null | null | {} | [] | [
".env"
] | [] | {
"iss_type": "1",
"iss_reason": "3\n？？？",
"loc_way": "comment",
"loc_scope": "1",
"info_type": "Code"
} | {
"code": [],
"doc": [],
"test": [],
"config": [
".env"
],
"asset": []
} | null | |
zylon-ai | private-gpt | d3acd85fe34030f8cfd7daf50b30c534087bdf2b | https://github.com/zylon-ai/private-gpt/issues/1514 | LLM Chat only returns "#" characters | No matter the prompt, privateGPT only returns hashes as the response. This doesn't occur when not using CUBLAS.
<img width="745" alt="image" src="https://github.com/imartinez/privateGPT/assets/6668593/b4ef137f-0122-44fe-864a-eef246066ec3">
Set up info:
NVIDIA GeForce RTX 4080
Windows 11
<img width="924" alt="image" src="https://github.com/imartinez/privateGPT/assets/6668593/35c2233d-ae28-40c9-a018-d9590f85908d">
<img width="1141" alt="image" src="https://github.com/imartinez/privateGPT/assets/6668593/750e4006-cd97-4b4f-848d-5598f09697f3">
accelerate==0.25.0
aiofiles==23.2.1
aiohttp==3.9.1
aiosignal==1.3.1
aiostream==0.5.2
altair==5.2.0
annotated-types==0.6.0
anyio==3.7.1
attrs==23.1.0
beautifulsoup4==4.12.2
black==22.12.0
boto3==1.34.2
botocore==1.34.2
build==1.0.3
CacheControl==0.13.1
certifi==2023.11.17
cfgv==3.4.0
charset-normalizer==3.3.2
cleo==2.1.0
click==8.1.7
colorama==0.4.6
coloredlogs==15.0.1
contourpy==1.2.0
coverage==7.3.3
crashtest==0.4.1
cycler==0.12.1
dataclasses-json==0.5.14
datasets==2.14.4
Deprecated==1.2.14
dill==0.3.7
diskcache==5.6.3
distlib==0.3.8
distro==1.8.0
dnspython==2.4.2
dulwich==0.21.7
email-validator==2.1.0.post1
evaluate==0.4.1
fastapi==0.103.2
fastjsonschema==2.19.1
ffmpy==0.3.1
filelock==3.13.1
flatbuffers==23.5.26
fonttools==4.46.0
frozenlist==1.4.1
fsspec==2023.12.2
gradio==4.10.0
gradio_client==0.7.3
greenlet==3.0.2
grpcio==1.60.0
grpcio-tools==1.60.0
h11==0.14.0
h2==4.1.0
hpack==4.0.0
httpcore==1.0.2
httptools==0.6.1
httpx==0.25.2
huggingface-hub==0.19.4
humanfriendly==10.0
hyperframe==6.0.1
identify==2.5.33
idna==3.6
importlib-resources==6.1.1
iniconfig==2.0.0
injector==0.21.0
installer==0.7.0
itsdangerous==2.1.2
jaraco.classes==3.3.0
Jinja2==3.1.2
jmespath==1.0.1
joblib==1.3.2
jsonschema==4.20.0
jsonschema-specifications==2023.11.2
keyring==24.3.0
kiwisolver==1.4.5
llama-index==0.9.3
llama_cpp_python==0.2.29
markdown-it-py==3.0.0
MarkupSafe==2.1.3
marshmallow==3.20.1
matplotlib==3.8.2
mdurl==0.1.2
more-itertools==10.2.0
mpmath==1.3.0
msgpack==1.0.7
multidict==6.0.4
multiprocess==0.70.15
mypy==1.7.1
mypy-extensions==1.0.0
nest-asyncio==1.5.8
networkx==3.2.1
nltk==3.8.1
nodeenv==1.8.0
numpy==1.26.3
onnx==1.15.0
onnxruntime==1.16.3
openai==1.5.0
optimum==1.16.1
orjson==3.9.10
packaging==23.2
pandas==2.1.4
pathspec==0.12.1
pexpect==4.9.0
Pillow==10.1.0
pkginfo==1.9.6
platformdirs==4.1.0
pluggy==1.3.0
poetry==1.7.1
poetry-core==1.8.1
poetry-plugin-export==1.6.0
portalocker==2.8.2
pre-commit==2.21.0
-e git+https://github.com/imartinez/privateGPT@d3acd85fe34030f8cfd7daf50b30c534087bdf2b#egg=private_gpt
protobuf==4.25.1
psutil==5.9.6
ptyprocess==0.7.0
pyarrow==14.0.1
pydantic==2.5.2
pydantic-extra-types==2.2.0
pydantic-settings==2.1.0
pydantic_core==2.14.5
pydub==0.25.1
Pygments==2.17.2
pyparsing==3.1.1
pypdf==3.17.2
pyproject_hooks==1.0.0
pyreadline3==3.4.1
pytest==7.4.3
pytest-asyncio==0.21.1
pytest-cov==3.0.0
python-dateutil==2.8.2
python-dotenv==1.0.0
python-multipart==0.0.6
pytz==2023.3.post1
pywin32==306
pywin32-ctypes==0.2.2
PyYAML==6.0.1
qdrant-client==1.7.0
rapidfuzz==3.6.1
referencing==0.32.0
regex==2023.10.3
requests==2.31.0
requests-toolbelt==1.0.0
responses==0.18.0
rich==13.7.0
rpds-py==0.14.1
ruff==0.1.8
s3transfer==0.9.0
safetensors==0.4.1
scikit-learn==1.3.2
scipy==1.11.4
semantic-version==2.10.0
sentence-transformers==2.2.2
sentencepiece==0.1.99
shellingham==1.5.4
six==1.16.0
sniffio==1.3.0
soupsieve==2.5
SQLAlchemy==2.0.23
starlette==0.27.0
sympy==1.12
tenacity==8.2.3
threadpoolctl==3.2.0
tiktoken==0.5.2
tokenizers==0.15.0
tomlkit==0.12.0
toolz==0.12.0
torch==2.1.2+cu121
torchaudio==2.1.2+cu121
torchvision==0.16.2+cu121
tqdm==4.66.1
transformers==4.36.1
trove-classifiers==2024.1.8
typer==0.9.0
types-PyYAML==6.0.12.12
typing-inspect==0.9.0
typing_extensions==4.9.0
tzdata==2023.3
ujson==5.9.0
urllib3==1.26.18
uvicorn==0.24.0.post1
virtualenv==20.25.0
watchdog==3.0.0
watchfiles==0.21.0
websockets==11.0.3
wrapt==1.16.0
xxhash==3.4.1
yarl==1.9.4 | null | null | null | {'base_commit': 'd3acd85fe34030f8cfd7daf50b30c534087bdf2b', 'files': [{'path': 'private_gpt/components/llm/llm_component.py', 'Loc': {"('LLMComponent', '__init__', 21)": {'mod': [45]}}, 'status': 'modified'}]} | [] | [] | [] | {
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zylon-ai | private-gpt | c4b247d696c727c1da6d993ce4f6c3a557e91b42 | https://github.com/zylon-ai/private-gpt/issues/685 | enhancement
primordial | CPU utilization | CPU utilization appears to be capped at 20%
Is there a way to increase CPU utilization and thereby enhance performance?
| null | null | null | {'base_commit': 'c4b247d696c727c1da6d993ce4f6c3a557e91b42', 'files': [{'path': 'privateGPT.py', 'Loc': {"(None, 'main', 23)": {'mod': [36]}}, 'status': 'modified'}]} | [] | [] | [] | {
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zylon-ai | private-gpt | 7ae80e662936bd946a231d1327bde476556c5d61 | https://github.com/zylon-ai/private-gpt/issues/181 | primordial | Segfault : not enough space in the context's memory pool | ggml_new_tensor_impl: not enough space in the context's memory pool (needed 3779301744, available 3745676000)
zsh: segmentation fault python3.11 privateGPT.py
Whats context memory pool? can i configure it? i actually have a lot of excess memory | null | null | null | {'base_commit': '7ae80e662936bd946a231d1327bde476556c5d61', 'files': [{'path': 'ingest.py', 'Loc': {"(None, 'main', 37)": {'mod': [47]}}, 'status': 'modified'}]} | [] | [] | [] | {
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zylon-ai | private-gpt | 9d47d03d183685c675070d47ad3beb67446d6580 | https://github.com/zylon-ai/private-gpt/issues/630 | bug
primordial | Use falcon model in privategpt | Hi how can i use Falcon model in privategpt?
https://huggingface.co/tiiuae/falcon-40b-instruct
Thanks | null | null | null | {'base_commit': '9d47d03d183685c675070d47ad3beb67446d6580', 'files': [{'path': 'privateGPT.py', 'Loc': {"(None, 'main', 23)": {'mod': [32]}}, 'status': 'modified'}]} | [] | [] | [] | {
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zylon-ai | private-gpt | 380b119581d2afcd24948f1108507b138490aec6 | https://github.com/zylon-ai/private-gpt/issues/235 | bug
primordial | Need help on in some errors | File "F:\privateGPT\Lib\site-packages\langchain\embeddings\llamacpp.py", line 79, in validate_environment
values["client"] = Llama(
^^^^^^
File "F:\privateGPT\Lib\site-packages\llama_cpp\llama.py", line 155, in __init__
self.ctx = llama_cpp.llama_init_from_file(
^^^^^^^^^^^^^^^^^^^^^
File "F:\privateGPT\Lib\site-packages\llama_cpp\llama_cpp.py", line 182, in llama_init_from_file
return _lib.llama_init_from_file(path_model, params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
OSError: [WinError -1073741795] Windows Error 0xc000001d
During handling of the above exception, another exception occurred:
File "F:\privateGPT\ingest.py", line 62, in <module>
main()
File "F:\privateGPT\ingest.py", line 53, in main
llama = LlamaCppEmbeddings(model_path=llama_embeddings_model, n_ctx=model_n_ctx)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "pydantic\main.py", line 339, in pydantic.main.BaseModel.__init__
File "pydantic\main.py", line 1102, in pydantic.main.validate_model
File "F:\privateGPT\Lib\site-packages\langchain\embeddings\llamacpp.py", line 99, in validate_environment
raise NameError(f"Could not load Llama model from path: {model_path}")
NameError: Could not load Llama model from path: F:/privateGPT/models/ggml-model-q4_0.bin
Exception ignored in: <function Llama.__del__ at 0x000002307F085E40>
Traceback (most recent call last):
File "F:\privateGPT\Lib\site-packages\llama_cpp\llama.py", line 978, in __del__
if self.ctx is not None:
^^^^
AttributeError: 'Llama' object has no attribute 'ctx'
| null | null | null | {'base_commit': '380b119581d2afcd24948f1108507b138490aec6', 'files': [{'path': 'README.md', 'Loc': {}}]} | [] | [] | [] | {
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zylon-ai | private-gpt | b1057afdf8f65fdb10e4160adbd8462be0c08271 | https://github.com/zylon-ai/private-gpt/issues/796 | primordial | Unable to instantiate model (type=value_error) | Installed on Ubuntu 20.04 with Python3.11-venv
Error on line 38:
https://github.com/imartinez/privateGPT/blob/b1057afdf8f65fdb10e4160adbd8462be0c08271/privateGPT.py#L38C7-L38C7
Error:
Using embedded DuckDB with persistence: data will be stored in: db
Found model file at models/ggml-gpt4all-j-v1.3-groovy.bin
Invalid model file
Traceback (most recent call last):
File "/home/kk/Documents/privateGPT/privateGPT.py", line 83, in <module>
main()
File "/home/kk/Documents/privateGPT/privateGPT.py", line 38, in main
llm = GPT4All(model=model_path, n_ctx=model_n_ctx, backend='gptj', n_batch=model_n_batch, callbacks=callbacks, verbose=False)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "pydantic/main.py", line 341, in pydantic.main.BaseModel.__init__
pydantic.error_wrappers.ValidationError: 1 validation error for GPT4All
__root__
Unable to instantiate model (type=value_error) | null | null | null | {} | [] | [
"ggml-gpt4all-j-v1.3-groovy.bin"
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zylon-ai | private-gpt | dd1100202881a01b6b013b7bc1faad8b5c63fec9 | https://github.com/zylon-ai/private-gpt/issues/839 | bug
primordial | ERROR: The prompt size exceeds the context window size and cannot be processed. | Enter a query，
It show:
ERROR: The prompt size exceeds the context window size and cannot be processed.GPT-J ERROR: The prompt is2614tokens and the context window is2048!
ERROR: The prompt size exceeds the context window size and cannot be processed. | null | null | null | {} | [] | [
".env"
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zylon-ai | private-gpt | 6bbec79583b7f28d9bea4b39c099ebef149db843 | https://github.com/zylon-ai/private-gpt/issues/1598 | Performance bottleneck using GPU | Hi Guys,
I am running the default Mistral model, and when running queries I am seeing 100% CPU usage (so single core), and up to 29% GPU usage which drops to have 15% mid answer.
I am using a MacBook Pro with M3 Max. I have set: model_kwargs={"n_gpu_layers": -1, "offload_kqv": True},
I am curious as LM studio runs the same model with low CPU usage and 80%+ GPU | null | null | null | {'base_commit': '6bbec79583b7f28d9bea4b39c099ebef149db843', 'files': [{'path': 'private_gpt/ui/ui.py', 'Loc': {"('PrivateGptUi', 'yield_deltas', 81)": {'mod': []}}, 'status': 'modified'}]} | [] | [] | [] | {
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yt-dlp | yt-dlp | 87ebab0615b1bf9b14b478b055e7059d630b4833 | https://github.com/yt-dlp/yt-dlp/issues/6007 | question | How to limit YouTube Music search to tracks only? | ### DO NOT REMOVE OR SKIP THE ISSUE TEMPLATE
- [X] I understand that I will be **blocked** if I remove or skip any mandatory\* field
### Checklist
- [X] I'm asking a question and **not** reporting a bug or requesting a feature
- [X] I've looked through the [README](https://github.com/yt-dlp/yt-dlp#readme)
- [X] I've verified that I'm running yt-dlp version **2023.01.06** ([update instructions](https://github.com/yt-dlp/yt-dlp#update)) or later (specify commit)
- [X] I've searched the [bugtracker](https://github.com/yt-dlp/yt-dlp/issues?q=) for similar questions **including closed ones**. DO NOT post duplicates
- [X] I've read the [guidelines for opening an issue](https://github.com/yt-dlp/yt-dlp/blob/master/CONTRIBUTING.md#opening-an-issue)
### Please make sure the question is worded well enough to be understood
Is there a way to return only tracks in a YTmusic search? Sometimes music videos have sound effects, while I'm only interested in the original song.
I'm using this command:
`yt-dlp -f bestaudio --playlist-items 1 --default-search "https://music.youtube.com/search?q=" -a list-of-tracks.txt`
### Provide verbose output that clearly demonstrates the problem
- [ ] Run **your** yt-dlp command with **-vU** flag added (`yt-dlp -vU <your command line>`)
- [ ] Copy the WHOLE output (starting with `[debug] Command-line config`) and insert it below
### Complete Verbose Output
_No response_ | null | null | null | {'base_commit': '87ebab0615b1bf9b14b478b055e7059d630b4833', 'files': [{'path': 'yt_dlp/extractor/youtube.py', 'Loc': {"('YoutubeMusicSearchURLIE', None, 6647)": {'mod': [6676]}}, 'status': 'modified'}, {'path': 'yt_dlp/extractor/youtube.py', 'Loc': {"('YoutubeMusicSearchURLIE', None, 6647)": {'mod': [6659]}}, 'status': 'modified'}]} | [] | [] | [] | {
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yt-dlp | yt-dlp | 91302ed349f34dc26cc1d661bb45a4b71f4417f7 | https://github.com/yt-dlp/yt-dlp/issues/7436 | question | Is YT-DLP capacity of downloading/displaying Automatic caption? | ### DO NOT REMOVE OR SKIP THE ISSUE TEMPLATE
- [X] I understand that I will be **blocked** if I *intentionally* remove or skip any mandatory\* field
### Checklist
- [X] I'm asking a question and **not** reporting a bug or requesting a feature
- [X] I've looked through the [README](https://github.com/yt-dlp/yt-dlp#readme)
- [X] I've verified that I'm running yt-dlp version **2023.06.22** ([update instructions](https://github.com/yt-dlp/yt-dlp#update)) or later (specify commit)
- [X] I've searched [known issues](https://github.com/yt-dlp/yt-dlp/issues/3766) and the [bugtracker](https://github.com/yt-dlp/yt-dlp/issues?q=) for similar questions **including closed ones**. DO NOT post duplicates
- [X] I've read the [guidelines for opening an issue](https://github.com/yt-dlp/yt-dlp/blob/master/CONTRIBUTING.md#opening-an-issue)
### Please make sure the question is worded well enough to be understood
**Similar Issue:**
- #5733
---
I may have missed one or 2 that could answer my question. These discussions and answers are not clear to my understanding, so here i am
**Details**
There are many videos that have "auto-generated subtitles | automatic captions" and no non-generated subtitles. I've ran `yt-dlp --list-subs URL` and discover that it said `URL has no subtitles`.
**QUESTION:**
1. Is it possible for yt-dlp to display the automatic caption while I am streaming the video to MPV?
2. Does yt-dlp preferred "non auto-generated caption"?
I'm not sure if this is intentional or not due to one discussion via issues that a guy mentioned that yt-dlp preferred non-autogenerated subtitles.
**Command for using MPV with yt-dlp**
the command was `mpv "https://youtu.be/i6kccBc-FBQ" --ytdl-raw-options=write-auto-subs=,write-subs=,sub-lang=en`
EDIT: added the double quote to the URL in the command line
### Provide verbose output that clearly demonstrates the problem
- [X] Run **your** yt-dlp command with **-vU** flag added (`yt-dlp -vU <your command line>`)
- [ ] If using API, add `'verbose': True` to `YoutubeDL` params instead
- [X] Copy the WHOLE output (starting with `[debug] Command-line config`) and insert it below
### Complete Verbose Output
```shell
[debug] Command-line config: ['-vU', '--list-subs', 'https://youtu.be/i6kccBc-FBQ']
[debug] Portable config "C:\Program Scoop\apps\yt-dlp\current\yt-dlp.conf": []
[debug] Encodings: locale cp1252, fs utf-8, pref cp1252, out utf-8, error utf-8, screen utf-8
[debug] yt-dlp version stable@2023.06.22 [812cdfa06] (win_exe)
[debug] Python 3.8.10 (CPython AMD64 64bit) - Windows-10-10.0.19045-SP0 (OpenSSL 1.1.1k 25 Mar 2021)
[debug] exe versions: none
[debug] Optional libraries: Cryptodome-3.18.0, brotli-1.0.9, certifi-2023.05.07, mutagen-1.46.0, sqlite3-2.6.0, websockets-11.0.3
[debug] Proxy map: {}
[debug] Loaded 1851 extractors
[debug] Fetching release info: https://api.github.com/repos/yt-dlp/yt-dlp/releases/latest
Available version: stable@2023.06.22, Current version: stable@2023.06.22
Current Build Hash: 37e7ffe204309357cfd1388b0e2c782a30e293ddd0f2761a9a8f6afa185b3566
yt-dlp is up to date (stable@2023.06.22)
[youtube] Extracting URL: https://youtu.be/i6kccBc-FBQ
[youtube] i6kccBc-FBQ: Downloading webpage
[youtube] i6kccBc-FBQ: Downloading ios player API JSON
[youtube] i6kccBc-FBQ: Downloading android player API JSON
[debug] Loading youtube-nsig.b7910ca8 from cache
[debug] [youtube] Decrypted nsig ftRL4j1AuTut8ZV => WMPfJf_eWd71gQ
[youtube] i6kccBc-FBQ: Downloading m3u8 information
[debug] Sort order given by extractor: quality, res, fps, hdr:12, source, vcodec:vp9.2, channels, acodec, lang, proto
[debug] Formats sorted by: hasvid, ie_pref, quality, res, fps, hdr:12(7), source, vcodec:vp9.2(10), channels, acodec, lang, proto, size, br, asr, vext, aext, hasaud, id
[info] Available automatic captions for i6kccBc-FBQ:
Language Name Formats
af Afrikaans vtt, ttml, srv3, srv2, srv1, json3
ak Akan vtt, ttml, srv3, srv2, srv1, json3
sq Albanian vtt, ttml, srv3, srv2, srv1, json3
am Amharic vtt, ttml, srv3, srv2, srv1, json3
ar Arabic vtt, ttml, srv3, srv2, srv1, json3
hy Armenian vtt, ttml, srv3, srv2, srv1, json3
as Assamese vtt, ttml, srv3, srv2, srv1, json3
ay Aymara vtt, ttml, srv3, srv2, srv1, json3
az Azerbaijani vtt, ttml, srv3, srv2, srv1, json3
bn Bangla vtt, ttml, srv3, srv2, srv1, json3
eu Basque vtt, ttml, srv3, srv2, srv1, json3
be Belarusian vtt, ttml, srv3, srv2, srv1, json3
bho Bhojpuri vtt, ttml, srv3, srv2, srv1, json3
bs Bosnian vtt, ttml, srv3, srv2, srv1, json3
bg Bulgarian vtt, ttml, srv3, srv2, srv1, json3
my Burmese vtt, ttml, srv3, srv2, srv1, json3
ca Catalan vtt, ttml, srv3, srv2, srv1, json3
ceb Cebuano vtt, ttml, srv3, srv2, srv1, json3
zh-Hans Chinese (Simplified) vtt, ttml, srv3, srv2, srv1, json3
zh-Hant Chinese (Traditional) vtt, ttml, srv3, srv2, srv1, json3
co Corsican vtt, ttml, srv3, srv2, srv1, json3
hr Croatian vtt, ttml, srv3, srv2, srv1, json3
cs Czech vtt, ttml, srv3, srv2, srv1, json3
da Danish vtt, ttml, srv3, srv2, srv1, json3
dv Divehi vtt, ttml, srv3, srv2, srv1, json3
nl Dutch vtt, ttml, srv3, srv2, srv1, json3
en-orig English (Original) vtt, ttml, srv3, srv2, srv1, json3
en English vtt, ttml, srv3, srv2, srv1, json3
eo Esperanto vtt, ttml, srv3, srv2, srv1, json3
et Estonian vtt, ttml, srv3, srv2, srv1, json3
ee Ewe vtt, ttml, srv3, srv2, srv1, json3
fil Filipino vtt, ttml, srv3, srv2, srv1, json3
fi Finnish vtt, ttml, srv3, srv2, srv1, json3
fr French vtt, ttml, srv3, srv2, srv1, json3
gl Galician vtt, ttml, srv3, srv2, srv1, json3
lg Ganda vtt, ttml, srv3, srv2, srv1, json3
ka Georgian vtt, ttml, srv3, srv2, srv1, json3
de German vtt, ttml, srv3, srv2, srv1, json3
el Greek vtt, ttml, srv3, srv2, srv1, json3
gn Guarani vtt, ttml, srv3, srv2, srv1, json3
gu Gujarati vtt, ttml, srv3, srv2, srv1, json3
ht Haitian Creole vtt, ttml, srv3, srv2, srv1, json3
ha Hausa vtt, ttml, srv3, srv2, srv1, json3
haw Hawaiian vtt, ttml, srv3, srv2, srv1, json3
iw Hebrew vtt, ttml, srv3, srv2, srv1, json3
hi Hindi vtt, ttml, srv3, srv2, srv1, json3
hmn Hmong vtt, ttml, srv3, srv2, srv1, json3
hu Hungarian vtt, ttml, srv3, srv2, srv1, json3
is Icelandic vtt, ttml, srv3, srv2, srv1, json3
ig Igbo vtt, ttml, srv3, srv2, srv1, json3
id Indonesian vtt, ttml, srv3, srv2, srv1, json3
ga Irish vtt, ttml, srv3, srv2, srv1, json3
it Italian vtt, ttml, srv3, srv2, srv1, json3
ja Japanese vtt, ttml, srv3, srv2, srv1, json3
jv Javanese vtt, ttml, srv3, srv2, srv1, json3
kn Kannada vtt, ttml, srv3, srv2, srv1, json3
kk Kazakh vtt, ttml, srv3, srv2, srv1, json3
km Khmer vtt, ttml, srv3, srv2, srv1, json3
rw Kinyarwanda vtt, ttml, srv3, srv2, srv1, json3
ko Korean vtt, ttml, srv3, srv2, srv1, json3
kri Krio vtt, ttml, srv3, srv2, srv1, json3
ku Kurdish vtt, ttml, srv3, srv2, srv1, json3
ky Kyrgyz vtt, ttml, srv3, srv2, srv1, json3
lo Lao vtt, ttml, srv3, srv2, srv1, json3
la Latin vtt, ttml, srv3, srv2, srv1, json3
lv Latvian vtt, ttml, srv3, srv2, srv1, json3
ln Lingala vtt, ttml, srv3, srv2, srv1, json3
lt Lithuanian vtt, ttml, srv3, srv2, srv1, json3
lb Luxembourgish vtt, ttml, srv3, srv2, srv1, json3
mk Macedonian vtt, ttml, srv3, srv2, srv1, json3
mg Malagasy vtt, ttml, srv3, srv2, srv1, json3
ms Malay vtt, ttml, srv3, srv2, srv1, json3
ml Malayalam vtt, ttml, srv3, srv2, srv1, json3
mt Maltese vtt, ttml, srv3, srv2, srv1, json3
mi Māori vtt, ttml, srv3, srv2, srv1, json3
mr Marathi vtt, ttml, srv3, srv2, srv1, json3
mn Mongolian vtt, ttml, srv3, srv2, srv1, json3
ne Nepali vtt, ttml, srv3, srv2, srv1, json3
nso Northern Sotho vtt, ttml, srv3, srv2, srv1, json3
no Norwegian vtt, ttml, srv3, srv2, srv1, json3
ny Nyanja vtt, ttml, srv3, srv2, srv1, json3
or Odia vtt, ttml, srv3, srv2, srv1, json3
om Oromo vtt, ttml, srv3, srv2, srv1, json3
ps Pashto vtt, ttml, srv3, srv2, srv1, json3
fa Persian vtt, ttml, srv3, srv2, srv1, json3
pl Polish vtt, ttml, srv3, srv2, srv1, json3
pt Portuguese vtt, ttml, srv3, srv2, srv1, json3
pa Punjabi vtt, ttml, srv3, srv2, srv1, json3
qu Quechua vtt, ttml, srv3, srv2, srv1, json3
ro Romanian vtt, ttml, srv3, srv2, srv1, json3
ru Russian vtt, ttml, srv3, srv2, srv1, json3
sm Samoan vtt, ttml, srv3, srv2, srv1, json3
sa Sanskrit vtt, ttml, srv3, srv2, srv1, json3
gd Scottish Gaelic vtt, ttml, srv3, srv2, srv1, json3
sr Serbian vtt, ttml, srv3, srv2, srv1, json3
sn Shona vtt, ttml, srv3, srv2, srv1, json3
sd Sindhi vtt, ttml, srv3, srv2, srv1, json3
si Sinhala vtt, ttml, srv3, srv2, srv1, json3
sk Slovak vtt, ttml, srv3, srv2, srv1, json3
sl Slovenian vtt, ttml, srv3, srv2, srv1, json3
so Somali vtt, ttml, srv3, srv2, srv1, json3
st Southern Sotho vtt, ttml, srv3, srv2, srv1, json3
es Spanish vtt, ttml, srv3, srv2, srv1, json3
su Sundanese vtt, ttml, srv3, srv2, srv1, json3
sw Swahili vtt, ttml, srv3, srv2, srv1, json3
sv Swedish vtt, ttml, srv3, srv2, srv1, json3
tg Tajik vtt, ttml, srv3, srv2, srv1, json3
ta Tamil vtt, ttml, srv3, srv2, srv1, json3
tt Tatar vtt, ttml, srv3, srv2, srv1, json3
te Telugu vtt, ttml, srv3, srv2, srv1, json3
th Thai vtt, ttml, srv3, srv2, srv1, json3
ti Tigrinya vtt, ttml, srv3, srv2, srv1, json3
ts Tsonga vtt, ttml, srv3, srv2, srv1, json3
tr Turkish vtt, ttml, srv3, srv2, srv1, json3
tk Turkmen vtt, ttml, srv3, srv2, srv1, json3
uk Ukrainian vtt, ttml, srv3, srv2, srv1, json3
ur Urdu vtt, ttml, srv3, srv2, srv1, json3
ug Uyghur vtt, ttml, srv3, srv2, srv1, json3
uz Uzbek vtt, ttml, srv3, srv2, srv1, json3
vi Vietnamese vtt, ttml, srv3, srv2, srv1, json3
cy Welsh vtt, ttml, srv3, srv2, srv1, json3
fy Western Frisian vtt, ttml, srv3, srv2, srv1, json3
xh Xhosa vtt, ttml, srv3, srv2, srv1, json3
yi Yiddish vtt, ttml, srv3, srv2, srv1, json3
yo Yoruba vtt, ttml, srv3, srv2, srv1, json3
zu Zulu vtt, ttml, srv3, srv2, srv1, json3
i6kccBc-FBQ has no subtitles
```
| null | null | null | {'base_commit': '91302ed349f34dc26cc1d661bb45a4b71f4417f7', 'files': [{'path': 'yt_dlp/options.py', 'Loc': {"(None, 'create_parser', 216)": {'mod': [853, 857, 861]}}, 'status': 'modified'}]} | [] | [] | [] | {
"iss_type": "3",
"iss_reason": "3",
"loc_way": "comment",
"loc_scope": "0\n这个可不算，因为user知道命令只是引号问题",
"info_type": "Code"
} | {
"code": [
"yt_dlp/options.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null |
yt-dlp | yt-dlp | 6075a029dba70a89675ae1250e7cdfd91f0eba41 | https://github.com/yt-dlp/yt-dlp/issues/10356 | question | Unable to install curl_cffi | ### DO NOT REMOVE OR SKIP THE ISSUE TEMPLATE
- [X] I understand that I will be **blocked** if I *intentionally* remove or skip any mandatory\* field
### Checklist
- [X] I'm asking a question and **not** reporting a bug or requesting a feature
- [X] I've looked through the [README](https://github.com/yt-dlp/yt-dlp#readme)
- [X] I've verified that I have **updated yt-dlp to nightly or master** ([update instructions](https://github.com/yt-dlp/yt-dlp#update-channels))
- [X] I've searched [known issues](https://github.com/yt-dlp/yt-dlp/issues/3766) and the [bugtracker](https://github.com/yt-dlp/yt-dlp/issues?q=) for similar questions **including closed ones**. DO NOT post duplicates
- [X] I've read the [guidelines for opening an issue](https://github.com/yt-dlp/yt-dlp/blob/master/CONTRIBUTING.md#opening-an-issue)
### Please make sure the question is worded well enough to be understood
I am trying to install `curl_cffi` in order to get around Vimeo's new TLS fingerprinting anti-bot protection. I have run the command `pipx install 'yt-dlp[default,curl_cffi]' --force'`, which gives the output:
```
Installing to existing venv 'yt-dlp'
⚠️ Note: yt-dlp was already on your PATH at /opt/homebrew/bin/yt-dlp
installed package yt-dlp 2024.7.2, installed using Python 3.12.4
These apps are now globally available
- yt-dlp
These manual pages are now globally available
- man1/yt-dlp.1
⚠️ Note: '/Users/username-hidden/.local/bin' is not on your PATH environment variable. These apps will not be globally accessible until your PATH is updated. Run `pipx ensurepath` to automatically add it,
or manually modify your PATH in your shell's config file (e.g. ~/.bashrc).
done! ✨ 🌟 ✨
```
From this output, I understand that `curl_cffi` would have been installed. However, running `yt-dlp --list-impersonate-targets -vU` does not show it.
I intend to use `--impersonate chrome` but I am stuck at `curl_cffi` installation. Any help would be **greatly** appreciated. Thank you.
### Provide verbose output that clearly demonstrates the problem
- [X] Run **your** yt-dlp command with **-vU** flag added (`yt-dlp -vU <your command line>`)
- [X] If using API, add `'verbose': True` to `YoutubeDL` params instead
- [X] Copy the WHOLE output (starting with `[debug] Command-line config`) and insert it below
### Complete Verbose Output
```shell
[debug] Command-line config: ['--list-impersonate-targets', '-vU']
[debug] Encodings: locale UTF-8, fs utf-8, pref UTF-8, out utf-8, error utf-8, screen utf-8
[debug] yt-dlp version stable@2024.07.02 from yt-dlp/yt-dlp [93d33cb29] (pip)
[debug] Python 3.12.4 (CPython arm64 64bit) - macOS-14.5-arm64-arm-64bit (OpenSSL 3.3.1 4 Jun 2024)
[debug] exe versions: ffmpeg 7.0.1 (setts), ffprobe 7.0.1
[debug] Optional libraries: Cryptodome-3.20.0, brotli-1.1.0, certifi-2024.06.02, mutagen-1.47.0, requests-2.32.3, sqlite3-3.46.0, urllib3-2.2.2, websockets-12.0
[debug] Proxy map: {}
[debug] Request Handlers: urllib, requests, websockets
[debug] Loaded 1831 extractors
[debug] Fetching release info: https://api.github.com/repos/yt-dlp/yt-dlp/releases/latest
Latest version: stable@2024.07.02 from yt-dlp/yt-dlp
yt-dlp is up to date (stable@2024.07.02 from yt-dlp/yt-dlp)
[info] Available impersonate targets
Client OS Source
---------------------------------------
Chrome - curl_cffi (not available)
Edge - curl_cffi (not available)
Safari - curl_cffi (not available)
```
| null | null | null | {} | [] | [
".zshrc",
".bash_profile"
] | [] | {
"iss_type": "1",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "1",
"info_type": "Code"
} | {
"code": [],
"doc": [],
"test": [],
"config": [
".bash_profile",
".zshrc"
],
"asset": []
} | null |
yt-dlp | yt-dlp | 4a601c9eff9fb42e24a4c8da3fa03628e035b35b | https://github.com/yt-dlp/yt-dlp/issues/8479 | question
NSFW | OUTPUT TEMPLATE --output %(title)s.%(ext)s | ### DO NOT REMOVE OR SKIP THE ISSUE TEMPLATE
- [X] I understand that I will be **blocked** if I *intentionally* remove or skip any mandatory\* field
### Checklist
- [X] I'm asking a question and **not** reporting a bug or requesting a feature
- [X] I've looked through the [README](https://github.com/yt-dlp/yt-dlp#readme)
- [X] I've verified that I'm running yt-dlp version **2023.10.13** ([update instructions](https://github.com/yt-dlp/yt-dlp#update)) or later (specify commit)
- [X] I've searched [known issues](https://github.com/yt-dlp/yt-dlp/issues/3766) and the [bugtracker](https://github.com/yt-dlp/yt-dlp/issues?q=) for similar questions **including closed ones**. DO NOT post duplicates
- [X] I've read the [guidelines for opening an issue](https://github.com/yt-dlp/yt-dlp/blob/master/CONTRIBUTING.md#opening-an-issue)
### Please make sure the question is worded well enough to be understood
I'm using the latest yt-dlp which states does not support website https://sfmcompile.club/. Understood.
Issue: The pages appear to just be playlist of others' posts. A series of pages may take the format below:
**_### LINKS ARE NSFW_**
https://sfmcompile.club/category/overwatch/dva/page/2/
https://sfmcompile.club/category/overwatch/dva/page/3/
https://sfmcompile.club/category/overwatch/dva/page/4/
**_### LINKS ARE NSFW_**
I'm copying/pasting to a text file, the link's base, adding the page number, then the trailing slash. After having a series of these weblinks, I run yt-dlp against this text file. Each weblink contains about 8 posts per page. yt-dlp downloads the 8 posts for that page.
DVA (1)
DVA (2)
DVA (3)
DVA (4)
DVA (5)
DVA (6)
DVA (7)
DVA (8)
yt-dlp then goes to the next weblink in the text file and "reports" the file has already been downloaded:
DVA (1)
DVA (2)
etc.
and again,
DVA (1)
DVA (2)
etc.
and again,
DVA (1)
DVA (2)
etc.
It repeats with whatever number of weblinks in the text file until exhausted. I might be trying to download 8 weblinks multiplied by 8 posts which should be 64, but is instead only the original 8 from the first page.
I understand I can add something like %(autonumber)s to the output but each of these posts in the playlists do have an actual title to them.
DVA eating lunch
DVA at the park
DVA at work
(lol)
I'd prefer to use the original title of the post rather than repeating title with a follow-on count.
DVA (1) 00001
DVA (2) 00002
DVA (3) 00003
DVA (4) 00004
DVA (5) 00005
DVA (6) 00006
DVA (7) 00007
DVA (8) 00008
DVA (1) 00009
DVA (2) 00010
etc.
I've experimented with using most of the OUTPUT TEMPLATE options on the yt-dlp page but can't for the life of me seem to figure out which output string is going to give me the output I desire. Most of them give me **NA**.
id (string): Video identifier
title (string): Video title
fulltitle (string): Video title ignoring live timestamp and generic title
ext (string): Video filename extension
alt_title (string): A secondary title of the video
description (string): The description of the video
display_id (string): An alternative identifier for the video
Even tried %(original_url)s w/ no luck, thinking I could at least get the https://www.blahblahblah.com, and then afterward use a mass filename editor to edit out the unwanted https:// and .com. Nope, get an NA.
**If there is a way to "poll" a weblink to see "keywords" that would be great!**
In advance, any help is appreciated.
My yt-dlp.conf
```
--no-download-archive
--no-clean-info-json
--windows-filenames
--trim-filenames 140
--ffmpeg-location "..\..\..\..\ffmpeg\bin\ffmpeg.exe"
--audio-format "mp3"
--format "bestvideo[ext=mp4]+bestaudio[ext=m4a]/mp4"
--output "D:\11Downloadz\bTorrents Complete\Podcasts\tmp in\%(title)s.%(ext)s"
```
```
G:\00OSz\12win10b zEnt-LTSC 1809 x64\05Apps\Multimedia\Video\Installed\yt-dlp Singles\Support\Folder Prep\aX Drive Source>"..\..\..\yt-dlp.exe" --config-location "..\..\..\yt-dlp.conf" --batch-file ".\aBatch URLs.txt" --verbose
[debug] Command-line config: ['--config-location', '..\\..\\..\\yt-dlp.conf', '--batch-file', '.\\aBatch URLs.txt', '--verbose']
[debug] | Config "..\..\..\yt-dlp.conf": ['--no-download-archive', '--no-clean-info-json', '--windows-filenames', '--trim-filenames', '140', '--ffmpeg-location', '..\\..\\..\\..\\ffmpeg\\bin\\ffmpeg.exe', '--audio-format', 'mp3', '--format', 'bestvideo[ext=mp4]+bestaudio[ext=m4a]/mp4', '--output', 'D:\\11Downloadz\\bTorrents Complete\\Podcasts\\tmp in\\%(title)s.%(ext)s']
[debug] Batch file urls: ['https://sfmcompile.club/tag/lazyprocrastinator/page/1/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/2/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/3/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/4/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/5/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/6/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/7/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/8/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/9/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/10/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/11/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/12/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/13/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/14/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/15/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/16/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/17/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/18/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/19/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/20/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/21/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/22/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/23/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/24/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/25/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/26/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/27/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/28/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/29/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/30/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/31/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/32/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/33/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/34/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/35/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/36/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/37/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/38/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/39/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/40/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/41/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/42/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/43/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/44/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/45/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/46/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/47/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/48/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/49/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/50/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/51/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/52/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/53/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/54/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/55/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/56/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/57/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/58/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/59/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/60/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/61/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/62/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/63/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/64/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/65/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/66/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/67/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/68/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/69/', 'https://sfmcompile.club/tag/lazyprocrastinator/page/70/']
[debug] Encodings: locale cp1252, fs utf-8, pref cp1252, out utf-8, error utf-8, screen utf-8
[debug] yt-dlp version nightly@2023.09.24.003044 [de015e930] (win_exe)
[debug] Python 3.8.10 (CPython AMD64 64bit) - Windows-10-10.0.19044-SP0 (OpenSSL 1.1.1k 25 Mar 2021)
[debug] exe versions: ffmpeg N-110072-g073ec3b9da-20230325 (setts), ffprobe N-110072-g073ec3b9da-20230325
[debug] Optional libraries: Cryptodome-3.19.0, brotli-1.1.0, certifi-2023.07.22, mutagen-1.47.0, sqlite3-3.35.5, websockets-11.0.3
[debug] Proxy map: {}
[debug] Loaded 1886 extractors
[generic] Extracting URL: https://sfmcompile.club/tag/lazyprocrastinator/page/1/
[generic] 1: Downloading webpage
[redirect] Following redirect to https://sfmcompile.club/tag/lazyprocrastinator/
[generic] Extracting URL: https://sfmcompile.club/tag/lazyprocrastinator/
[generic] lazyprocrastinator: Downloading webpage
WARNING: [generic] Falling back on generic information extractor
[generic] lazyprocrastinator: Extracting information
[debug] Looking for embeds
[debug] Identified 8 html5 embeds
[download] Downloading playlist: LazyProcrastinator Archives
[generic] Playlist LazyProcrastinator Archives: Downloading 8 items of 8
[download] Downloading item 1 of 8
[debug] Formats sorted by: hasvid, ie_pref, lang, quality, res, fps, hdr:12(7), vcodec:vp9.2(10), channels, acodec, size, br, asr, proto, vext, aext, hasaud, source, id
[info] lazyprocrastinator-1: Downloading 1 format(s): 0
[debug] Invoking http downloader on "https://sfmcompile.club/wp-content/uploads/2023/10/Infected-2B-blowjob-pov-Sound-update.mp4"
[debug] File locking is not supported. Proceeding without locking
[download] Destination: D:\11Downloadz\bTorrents Complete\Podcasts\tmp in\LazyProcrastinator Archives (1).mp4
[download] 100% of 2.66MiB in 00:00:00 at 5.05MiB/s
[download] Downloading item 2 of 8
[debug] Formats sorted by: hasvid, ie_pref, lang, quality, res, fps, hdr:12(7), vcodec:vp9.2(10), channels, acodec, size, br, asr, proto, vext, aext, hasaud, source, id
[info] lazyprocrastinator-2: Downloading 1 format(s): 0
[debug] Invoking http downloader on "https://sfmcompile.club/wp-content/uploads/2023/10/Red-Riding-Hood-Lunafreya-spooning-fuck-Sound-update.mp4"
[download] Destination: D:\11Downloadz\bTorrents Complete\Podcasts\tmp in\LazyProcrastinator Archives (2).mp4
[download] 100% of 3.53MiB in 00:00:00 at 6.47MiB/s
[download] Downloading item 3 of 8
[debug] Formats sorted by: hasvid, ie_pref, lang, quality, res, fps, hdr:12(7), vcodec:vp9.2(10), channels, acodec, size, br, asr, proto, vext, aext, hasaud, source, id
[info] lazyprocrastinator-3: Downloading 1 format(s): 0
[debug] Invoking http downloader on "https://sfmcompile.club/wp-content/uploads/2023/10/Bunny-Serah-Farron-sideway-proneboned.mp4"
[download] Destination: D:\11Downloadz\bTorrents Complete\Podcasts\tmp in\LazyProcrastinator Archives (3).mp4
[download] 100% of 3.09MiB in 00:00:00 at 6.05MiB/s
[download] Downloading item 4 of 8
[debug] Formats sorted by: hasvid, ie_pref, lang, quality, res, fps, hdr:12(7), vcodec:vp9.2(10), channels, acodec, size, br, asr, proto, vext, aext, hasaud, source, id
[info] lazyprocrastinator-4: Downloading 1 format(s): 0
[debug] Invoking http downloader on "https://sfmcompile.club/wp-content/uploads/2023/10/Bunny-Serah-Farron-sideway-fucked.mp4"
[download] Destination: D:\11Downloadz\bTorrents Complete\Podcasts\tmp in\LazyProcrastinator Archives (4).mp4
[download] 100% of 2.97MiB in 00:00:00 at 5.50MiB/s
[download] Downloading item 5 of 8
[debug] Formats sorted by: hasvid, ie_pref, lang, quality, res, fps, hdr:12(7), vcodec:vp9.2(10), channels, acodec, size, br, asr, proto, vext, aext, hasaud, source, id
[info] lazyprocrastinator-5: Downloading 1 format(s): 0
[debug] Invoking http downloader on "https://sfmcompile.club/wp-content/uploads/2023/10/Sadako-caught-on-tape.mp4"
[download] Destination: D:\11Downloadz\bTorrents Complete\Podcasts\tmp in\LazyProcrastinator Archives (5).mp4
[download] 100% of 1.77MiB in 00:00:00 at 4.34MiB/s
[download] Downloading item 6 of 8
[debug] Formats sorted by: hasvid, ie_pref, lang, quality, res, fps, hdr:12(7), vcodec:vp9.2(10), channels, acodec, size, br, asr, proto, vext, aext, hasaud, source, id
[info] lazyprocrastinator-6: Downloading 1 format(s): 0
[debug] Invoking http downloader on "https://sfmcompile.club/wp-content/uploads/2023/10/Red-Riding-Hood-Lunafreya-mating-press-Sound-update.mp4"
[download] Destination: D:\11Downloadz\bTorrents Complete\Podcasts\tmp in\LazyProcrastinator Archives (6).mp4
[download] 100% of 2.65MiB in 00:00:00 at 4.40MiB/s
[download] Downloading item 7 of 8
[debug] Formats sorted by: hasvid, ie_pref, lang, quality, res, fps, hdr:12(7), vcodec:vp9.2(10), channels, acodec, size, br, asr, proto, vext, aext, hasaud, source, id
[info] lazyprocrastinator-7: Downloading 1 format(s): 0
[debug] Invoking http downloader on "https://sfmcompile.club/wp-content/uploads/2023/10/Infected-2B-hand-holding-cowgirl.mp4"
[download] Destination: D:\11Downloadz\bTorrents Complete\Podcasts\tmp in\LazyProcrastinator Archives (7).mp4
[download] 100% of 1.67MiB in 00:00:00 at 4.73MiB/s
[download] Downloading item 8 of 8
[debug] Formats sorted by: hasvid, ie_pref, lang, quality, res, fps, hdr:12(7), vcodec:vp9.2(10), channels, acodec, size, br, asr, proto, vext, aext, hasaud, source, id
[info] lazyprocrastinator-8: Downloading 1 format(s): 0
[debug] Invoking http downloader on "https://sfmcompile.club/wp-content/uploads/2023/10/Infected-2B-dangerous-handjob-pov.mp4"
[download] Destination: D:\11Downloadz\bTorrents Complete\Podcasts\tmp in\LazyProcrastinator Archives (8).mp4
[download] 100% of 4.85MiB in 00:00:00 at 4.86MiB/s
[download] Finished downloading playlist: LazyProcrastinator Archives
[generic] Extracting URL: https://sfmcompile.club/tag/lazyprocrastinator/page/2/
[generic] 2: Downloading webpage
WARNING: [generic] Falling back on generic information extractor
[generic] 2: Extracting information
[debug] Looking for embeds
[debug] Identified 8 html5 embeds
[download] Downloading playlist: LazyProcrastinator Archives
[generic] Playlist LazyProcrastinator Archives: Downloading 8 items of 8
[download] Downloading item 1 of 8
[debug] Formats sorted by: hasvid, ie_pref, lang, quality, res, fps, hdr:12(7), vcodec:vp9.2(10), channels, acodec, size, br, asr, proto, vext, aext, hasaud, source, id
[info] 2-1: Downloading 1 format(s): 0
[debug] Invoking http downloader on "https://sfmcompile.club/wp-content/uploads/2023/10/Infected-2B-dangerous-thighjob-pov.mp4"
[download] D:\11Downloadz\bTorrents Complete\Podcasts\tmp in\LazyProcrastinator Archives (1).mp4 has already been downloaded
[download] 100% of 2.66MiB
[download] Downloading item 2 of 8
[debug] Formats sorted by: hasvid, ie_pref, lang, quality, res, fps, hdr:12(7), vcodec:vp9.2(10), channels, acodec, size, br, asr, proto, vext, aext, hasaud, source, id
[info] 2-2: Downloading 1 format(s): 0
[debug] Invoking http downloader on "https://sfmcompile.club/wp-content/uploads/2023/10/Infected-2B-face-sitting-and-feetjob.mp4"
[download] D:\11Downloadz\bTorrents Complete\Podcasts\tmp in\LazyProcrastinator Archives (2).mp4 has already been downloaded
[download] 100% of 3.53MiB
[download] Downloading item 3 of 8
[debug] Formats sorted by: hasvid, ie_pref, lang, quality, res, fps, hdr:12(7), vcodec:vp9.2(10), channels, acodec, size, br, asr, proto, vext, aext, hasaud, source, id
[info] 2-3: Downloading 1 format(s): 0
[debug] Invoking http downloader on "https://sfmcompile.club/wp-content/uploads/2023/10/Infected-2B-heel-torture-pov.mp4"
[download] D:\11Downloadz\bTorrents Complete\Podcasts\tmp in\LazyProcrastinator Archives (3).mp4 has already been downloaded
[download] 100% of 3.09MiB
[download] Downloading item 4 of 8
[debug] Formats sorted by: hasvid, ie_pref, lang, quality, res, fps, hdr:12(7), vcodec:vp9.2(10), channels, acodec, size, br, asr, proto, vext, aext, hasaud, source, id
[info] 2-4: Downloading 1 format(s): 0
[debug] Invoking http downloader on "https://sfmcompile.club/wp-content/uploads/2023/10/Ashley-Graham-cowgirl-riding-pov.mp4"
[download] D:\11Downloadz\bTorrents Complete\Podcasts\tmp in\LazyProcrastinator Archives (4).mp4 has already been downloaded
[download] 100% of 2.97MiB
[download] Downloading item 5 of 8
[debug] Formats sorted by: hasvid, ie_pref, lang, quality, res, fps, hdr:12(7), vcodec:vp9.2(10), channels, acodec, size, br, asr, proto, vext, aext, hasaud, source, id
[info] 2-5: Downloading 1 format(s): 0
[debug] Invoking http downloader on "https://sfmcompile.club/wp-content/uploads/2023/10/Red-Riding-Lunafreya-lifted-anal-Sound-update.mp4"
[download] D:\11Downloadz\bTorrents Complete\Podcasts\tmp in\LazyProcrastinator Archives (5).mp4 has already been downloaded
[download] 100% of 1.77MiB
[download] Downloading item 6 of 8
[debug] Formats sorted by: hasvid, ie_pref, lang, quality, res, fps, hdr:12(7), vcodec:vp9.2(10), channels, acodec, size, br, asr, proto, vext, aext, hasaud, source, id
[info] 2-6: Downloading 1 format(s): 0
[debug] Invoking http downloader on "https://sfmcompile.club/wp-content/uploads/2023/10/Infected-2B-sucking-nip-and-handjob-pov.mp4"
[download] D:\11Downloadz\bTorrents Complete\Podcasts\tmp in\LazyProcrastinator Archives (6).mp4 has already been downloaded
[download] 100% of 2.65MiB
[download] Downloading item 7 of 8
[debug] Formats sorted by: hasvid, ie_pref, lang, quality, res, fps, hdr:12(7), vcodec:vp9.2(10), channels, acodec, size, br, asr, proto, vext, aext, hasaud, source, id
[info] 2-7: Downloading 1 format(s): 0
[debug] Invoking http downloader on "https://sfmcompile.club/wp-content/uploads/2023/10/Infected-2B-reverse-cowgirl-ride-pov.mp4"
[download] D:\11Downloadz\bTorrents Complete\Podcasts\tmp in\LazyProcrastinator Archives (7).mp4 has already been downloaded
[download] 100% of 1.67MiB
[download] Downloading item 8 of 8
[debug] Formats sorted by: hasvid, ie_pref, lang, quality, res, fps, hdr:12(7), vcodec:vp9.2(10), channels, acodec, size, br, asr, proto, vext, aext, hasaud, source, id
[info] 2-8: Downloading 1 format(s): 0
[debug] Invoking http downloader on "https://sfmcompile.club/wp-content/uploads/2023/10/2B-thighs-crushing-and-handjob.mp4"
[download] D:\11Downloadz\bTorrents Complete\Podcasts\tmp in\LazyProcrastinator Archives (8).mp4 has already been downloaded
```
### Provide verbose output that clearly demonstrates the problem
- [x] Run **your** yt-dlp command with **-vU** flag added (`yt-dlp -vU <your command line>`)
- [x] If using API, add `'verbose': True` to `YoutubeDL` params instead
- [x] Copy the WHOLE output (starting with `[debug] Command-line config`) and insert it below
### Complete Verbose Output
_No response_ | null | null | null | {} | [] | [
"yt-dlp.conf"
] | [] | {
"iss_type": "2",
"iss_reason": "3",
"loc_way": "comment",
"loc_scope": "1",
"info_type": "Code"
} | {
"code": [
"yt-dlp.conf"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null |
yt-dlp | yt-dlp | a903d8285c96b2c7ac7915f228a17e84cbfe3ba4 | https://github.com/yt-dlp/yt-dlp/issues/1238 | question | [Question] How to use Sponsorblock as part of Python script | <!--
######################################################################
WARNING!
IGNORING THE FOLLOWING TEMPLATE WILL RESULT IN ISSUE CLOSED AS INCOMPLETE
######################################################################
-->
## Checklist
<!--
Carefully read and work through this check list in order to prevent the most common mistakes and misuse of yt-dlp:
- Look through the README (https://github.com/yt-dlp/yt-dlp)
- Read "opening an issue" section in CONTRIBUTING.md: https://github.com/yt-dlp/yt-dlp/blob/master/CONTRIBUTING.md#opening-an-issue
- Search the bugtracker for similar questions: https://github.com/yt-dlp/yt-dlp/issues
- Finally, put x into all relevant boxes like this [x] (Dont forget to delete the empty space)
-->
- [x] I'm asking a question
- [x] I've looked through the README
- [x] I've read the opening an issue section in CONTRIBUTING.md
- [x] I've searched the bugtracker for similar questions including closed ones
- [x] I have given an appropriate title to the issue
## Question
<!--
Ask your question in an arbitrary form. Please make sure it's worded well enough to be understood, see https://github.com/yt-dlp/yt-dlp.
-->
What are the relevant `ydl_opts` to use Sponsorblock with yt-dlp as part of a Python script?
[README.md](https://github.com/yt-dlp/yt-dlp/blob/master/README.md#sponsorblock-options) documents usage on the command line and [yt_dlp/YoutubeDL.py](https://github.com/yt-dlp/yt-dlp/blob/master/yt_dlp/YoutubeDL.py) doesn't mention Sponsorblock at all.
| null | null | null | {'base_commit': 'a903d8285c96b2c7ac7915f228a17e84cbfe3ba4', 'files': [{'path': 'yt_dlp/__init__.py', 'Loc': {"(None, '_real_main', 62)": {'mod': [427, 501]}}, 'status': 'modified'}, {'path': 'README.md', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "3",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"yt_dlp/__init__.py"
],
"doc": [
"README.md"
],
"test": [],
"config": [],
"asset": []
} | null |
yt-dlp | yt-dlp | 8531d2b03bac9cc746f2ee8098aaf8f115505f5b | https://github.com/yt-dlp/yt-dlp/issues/10462 | question | Cookie not loading when downloading instagram videos | ### DO NOT REMOVE OR SKIP THE ISSUE TEMPLATE
- [X] I understand that I will be **blocked** if I *intentionally* remove or skip any mandatory\* field
### Checklist
- [X] I'm asking a question and **not** reporting a bug or requesting a feature
- [X] I've looked through the [README](https://github.com/yt-dlp/yt-dlp#readme)
- [X] I've verified that I have **updated yt-dlp to nightly or master** ([update instructions](https://github.com/yt-dlp/yt-dlp#update-channels))
- [X] I've searched [known issues](https://github.com/yt-dlp/yt-dlp/issues/3766) and the [bugtracker](https://github.com/yt-dlp/yt-dlp/issues?q=) for similar questions **including closed ones**. DO NOT post duplicates
- [X] I've read the [guidelines for opening an issue](https://github.com/yt-dlp/yt-dlp/blob/master/CONTRIBUTING.md#opening-an-issue)
### Please make sure the question is worded well enough to be understood
I tried to download instagram videos with this code but the cookie does not load.
But with ```yt-dlp --cookies instagram_cookie.txt "https://www.instagram.com/p/C9SEsmYCx_M/?hl=ja"``` it does.
Is there something wrong with my code? If so, please let me know the solution.
Sorry if I have missed something.
```
from yt_dlp import YoutubeDL
import subprocess
def download_video(url):
if url in ".m3u8":
subprocess.run(f'ffmpeg -i {url} -c copy "%name%.mp4"', shell=True)
print("m3u8ファイルをダウンロードました")
else:
ydl_opts = {
'format': 'best[ext=mp4]',
'outtmpl': '%(title)s.%(ext)s',
'verbose': True,
}
if "instagram.com" in url:
ydl_opts["cookies"] = "instagram_cookie.txt"
print(ydl_opts)
with YoutubeDL(ydl_opts) as ydl:
result = ydl.extract_info(url, download=True)
file_path = ydl.prepare_filename(result)
print(f"{file_path}をダウンロードました")
return file_path
if __name__ == "__main__":
download_video(input("URL:"))
```
### Provide verbose output that clearly demonstrates the problem
- [ ] Run **your** yt-dlp command with **-vU** flag added (`yt-dlp -vU <your command line>`)
- [X] If using API, add `'verbose': True` to `YoutubeDL` params instead
- [X] Copy the WHOLE output (starting with `[debug] Command-line config`) and insert it below
### Complete Verbose Output
```shell
URL:https://www.instagram.com/p/C9SEsmYCx_M/?hl=ja
{'format': 'best[ext=mp4]', 'outtmpl': '%(title)s.%(ext)s', 'verbose': True, 'cookies': 'instagram_cookie.txt'}
[debug] Encodings: locale UTF-8, fs utf-8, pref UTF-8, out utf-8, error utf-8, screen utf-8
[debug] yt-dlp version nightly@2024.07.13.232701 from yt-dlp/yt-dlp-nightly-builds [150ecc45d] (pip) API
[debug] params: {'format': 'best[ext=mp4]', 'outtmpl': '%(title)s.%(ext)s', 'verbose': True, 'cookies': 'instagram_cookie.txt', 'compat_opts': set(), 'http_headers': {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/95.0.4638.74 Safari/537.36', 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8', 'Accept-Language': 'en-us,en;q=0.5', 'Sec-Fetch-Mode': 'navigate'}}
[debug] Python 3.10.14 (CPython x86_64 64bit) - Linux-6.5.0-1023-gcp-x86_64-with-glibc2.39 (OpenSSL 3.0.13 30 Jan 2024, glibc 2.39)
[debug] exe versions: none
[debug] Optional libraries: Cryptodome-3.20.0, brotli-1.1.0, certifi-2024.07.04, mutagen-1.47.0, requests-2.32.3, sqlite3-3.45.3, urllib3-2.2.2, websockets-12.0
[debug] Proxy map: {}
[debug] Request Handlers: urllib, requests, websockets
[debug] Loaded 1834 extractors
[Instagram] Extracting URL: https://www.instagram.com/p/C9SEsmYCx_M/?hl=ja
[Instagram] C9SEsmYCx_M: Setting up session
[Instagram] C9SEsmYCx_M: Downloading JSON metadata
WARNING: [Instagram] C9SEsmYCx_M: General metadata extraction failed (some metadata might be missing).
[Instagram] C9SEsmYCx_M: Downloading webpage
WARNING: [Instagram] unable to extract shared data; please report this issue on https://github.com/yt-dlp/yt-dlp/issues?q= , filling out the appropriate issue template. Confirm you are on the latest version using yt-dlp -U
WARNING: [Instagram] Main webpage is locked behind the login page. Retrying with embed webpage (some metadata might be missing).
[Instagram] C9SEsmYCx_M: Downloading embed webpage
WARNING: [Instagram] unable to extract additional data; please report this issue on https://github.com/yt-dlp/yt-dlp/issues?q= , filling out the appropriate issue template. Confirm you are on the latest version using yt-dlp -U
ERROR: [Instagram] C9SEsmYCx_M: Requested content is not available, rate-limit reached or login required. Use --cookies, --cookies-from-browser, --username and --password, --netrc-cmd, or --netrc (instagram) to provide account credentials
File "/home/runner/moive-download-exe/.pythonlibs/lib/python3.10/site-packages/yt_dlp/extractor/common.py", line 740, in extract
ie_result = self._real_extract(url)
File "/home/runner/moive-download-exe/.pythonlibs/lib/python3.10/site-packages/yt_dlp/extractor/instagram.py", line 460, in _real_extract
self.raise_login_required('Requested content is not available, rate-limit reached or login required')
File "/home/runner/moive-download-exe/.pythonlibs/lib/python3.10/site-packages/yt_dlp/extractor/common.py", line 1245, in raise_login_required
raise ExtractorError(msg, expected=True)
Traceback (most recent call last):
File "/home/runner/moive-download-exe/.pythonlibs/lib/python3.10/site-packages/yt_dlp/YoutubeDL.py", line 1622, in wrapper
return func(self, *args, **kwargs)
File "/home/runner/moive-download-exe/.pythonlibs/lib/python3.10/site-packages/yt_dlp/YoutubeDL.py", line 1757, in __extract_info
ie_result = ie.extract(url)
File "/home/runner/moive-download-exe/.pythonlibs/lib/python3.10/site-packages/yt_dlp/extractor/common.py", line 740, in extract
ie_result = self._real_extract(url)
File "/home/runner/moive-download-exe/.pythonlibs/lib/python3.10/site-packages/yt_dlp/extractor/instagram.py", line 460, in _real_extract
self.raise_login_required('Requested content is not available, rate-limit reached or login required')
File "/home/runner/moive-download-exe/.pythonlibs/lib/python3.10/site-packages/yt_dlp/extractor/common.py", line 1245, in raise_login_required
raise ExtractorError(msg, expected=True)
yt_dlp.utils.ExtractorError: [Instagram] C9SEsmYCx_M: Requested content is not available, rate-limit reached or login required. Use --cookies, --cookies-from-browser, --username and --password, --netrc-cmd, or --netrc (instagram) to provide account credentials
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/runner/moive-download-exe/main.py", line 27, in <module>
download_video(input("URL:"))
File "/home/runner/moive-download-exe/main.py", line 20, in download_video
result = ydl.extract_info(url, download=True)
File "/home/runner/moive-download-exe/.pythonlibs/lib/python3.10/site-packages/yt_dlp/YoutubeDL.py", line 1611, in extract_info
return self.__extract_info(url, self.get_info_extractor(key), download, extra_info, process)
File "/home/runner/moive-download-exe/.pythonlibs/lib/python3.10/site-packages/yt_dlp/YoutubeDL.py", line 1640, in wrapper
self.report_error(str(e), e.format_traceback())
File "/home/runner/moive-download-exe/.pythonlibs/lib/python3.10/site-packages/yt_dlp/YoutubeDL.py", line 1088, in report_error
self.trouble(f'{self._format_err("ERROR:", self.Styles.ERROR)} {message}', *args, **kwargs)
File "/home/runner/moive-download-exe/.pythonlibs/lib/python3.10/site-packages/yt_dlp/YoutubeDL.py", line 1027, in trouble
raise DownloadError(message, exc_info)
yt_dlp.utils.DownloadError: ERROR: [Instagram] C9SEsmYCx_M: Requested content is not available, rate-limit reached or login required. Use --cookies, --cookies-from-browser, --username and --password, --netrc-cmd, or --netrc (instagram) to provide account credentials
```
| null | null | null | {'base_commit': '8531d2b03bac9cc746f2ee8098aaf8f115505f5b', 'files': [{'path': 'yt_dlp/YoutubeDL.py', 'Loc': {"('YoutubeDL', None, 189)": {'mod': [335]}}, 'status': 'modified'}, {'path': 'yt_dlp/__init__.py', 'Loc': {"(None, 'parse_options', 737)": {'mod': [901]}}, 'status': 'modified'}]} | [] | [] | [] | {
"iss_type": "1",
"iss_reason": "3",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"yt_dlp/__init__.py",
"yt_dlp/YoutubeDL.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null |
yt-dlp | yt-dlp | e59c82a74cda5139eb3928c75b0bd45484dbe7f0 | https://github.com/yt-dlp/yt-dlp/issues/11152 | question | How to use --merge-output-format? | ### DO NOT REMOVE OR SKIP THE ISSUE TEMPLATE
- [X] I understand that I will be **blocked** if I *intentionally* remove or skip any mandatory\* field
### Checklist
- [X] I'm asking a question and **not** reporting a bug or requesting a feature
- [X] I've looked through the [README](https://github.com/yt-dlp/yt-dlp#readme)
- [X] I've verified that I have **updated yt-dlp to nightly or master** ([update instructions](https://github.com/yt-dlp/yt-dlp#update-channels))
- [X] I've searched [known issues](https://github.com/yt-dlp/yt-dlp/issues/3766) and the [bugtracker](https://github.com/yt-dlp/yt-dlp/issues?q=) for similar questions **including closed ones**. DO NOT post duplicates
- [X] I've read the [guidelines for opening an issue](https://github.com/yt-dlp/yt-dlp/blob/master/CONTRIBUTING.md#opening-an-issue)
### Please make sure the question is worded well enough to be understood
Hello,
This is the first time I'm trying to use the "--merge-output-format" option to download and merge a video stream with an audio stream… and it failed:
```
youtube-dlp.exe -qF
youtube-dlp.exe -f '160+140' --merge-output-format mp4 https://www.youtube.com/watch?v=123ABC
Requested format is not available. Use --list-formats for a list of available formats
```
What is the right way to use that switch?
Thank you.
### Provide verbose output that clearly demonstrates the problem
- [X] Run **your** yt-dlp command with **-vU** flag added (`yt-dlp -vU <your command line>`)
- [ ] If using API, add `'verbose': True` to `YoutubeDL` params instead
- [X] Copy the WHOLE output (starting with `[debug] Command-line config`) and insert it below
### Complete Verbose Output
```shell
[debug] Command-line config: ['-vU']
[debug] Encodings: locale cp1252, fs utf-8, pref cp1252, out utf-8, error utf-8, screen utf-8
[debug] yt-dlp version stable@2024.08.06 from yt-dlp/yt-dlp [4d9231208] (win_exe)
[debug] Python 3.8.10 (CPython AMD64 64bit) - Windows-10-10.0.19045-SP0 (OpenSSL 1.1.1k 25 Mar 2021)
[debug] exe versions: ffmpeg 2024-06-13-git-0060a368b1-essentials_build-www.gyan.dev (setts), ffprobe 2024-06-13-git-0060a368b1-essentials_build-www.gyan.dev
[debug] Optional libraries: Cryptodome-3.20.0, brotli-1.1.0, certifi-2024.07.04, curl_cffi-0.5.10, mutagen-1.47.0, requests-2.32.3, sqlite3-3.35.5, urllib3-2.2.2, websockets-12.0
[debug] Proxy map: {}
[debug] Request Handlers: urllib, requests, websockets, curl_cffi
[debug] Loaded 1830 extractors
[debug] Fetching release info: https://api.github.com/repos/yt-dlp/yt-dlp/releases/latest
[debug] Downloading _update_spec from https://github.com/yt-dlp/yt-dlp/releases/latest/download/_update_spec
[debug] Downloading SHA2-256SUMS from https://github.com/yt-dlp/yt-dlp/releases/download/2024.09.27/SHA2-256SUMS
Current version: stable@2024.08.06 from yt-dlp/yt-dlp
Latest version: stable@2024.09.27 from yt-dlp/yt-dlp
Current Build Hash: 468a6f8bf1d156ad173e000a40f696d4fbd69c5aa7360229329b9063a388e7d0
Updating to stable@2024.09.27 from yt-dlp/yt-dlp ...
[debug] Downloading yt-dlp.exe from https://github.com/yt-dlp/yt-dlp/releases/download/2024.09.27/yt-dlp.exe
Updated yt-dlp to stable@2024.09.27 from yt-dlp/yt-dlp
```
| null | null | null | {'base_commit': 'e59c82a74cda5139eb3928c75b0bd45484dbe7f0', 'files': [{'path': 'README.md', 'Loc': {'(None, None, 1430)': {'mod': [1430]}}, 'status': 'modified'}, {'path': 'yt_dlp/options.py', 'Loc': {"(None, 'create_parser', 219)": {'mod': [786, 790]}}, 'status': 'modified'}]} | [] | [] | [] | {
"iss_type": "3",
"iss_reason": "3",
"loc_way": "comment",
"loc_scope": "",
"info_type": "Code"
} | {
"code": [
"yt_dlp/options.py"
],
"doc": [
"README.md"
],
"test": [],
"config": [],
"asset": []
} | null |
comfyanonymous | ComfyUI | f18ebbd31645437afaa9738fcf2b5ed8b48cb021 | https://github.com/comfyanonymous/ComfyUI/issues/6177 | Feature | Workflow that can follow different paths and skip some of them. | ### Feature Idea
Hi.
I am very interested in the ability to create a workflow that can follow different paths and skip some if they are not needed.
For example, I want to create an image and save it under a fixed name (unique). But tomorrow (or after restart) I want to run this workflow again and work with the already created image, which I created and saved earlier, and not waste time on its creation (upscale, modification, etc.), but just check if this image is in my folder, and if it is, then just load it and work with the loaded image, and the branch that creates the image will not run at all (skip this branch).
But it's important that the script does this by itself (without MUTE or BYPASS).
Example
This will help save a lot of time on complex workflows that need to be improved or modernized. And it can also save resources in case of a break or lack of memory - it will be possible to skip large parts of the scheme if they have already been made and saved (without keeping in memory models that have already worked).
### Existing Solutions
I've been trying for a long time to find out if such a possibility exists, but I couldn't find it. If such a feature is already implemented, where can I find it? Thanks.
### Other
_No response_ | null | null | null | {} | [] | [] | [
{
"org": "ltdrdata",
"pro": "ComfyUI-extension-tutorials",
"path": [
"ComfyUI-Impact-Pack/tutorial/switch.md"
]
}
] | {
"iss_type": "4",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Doc"
} | {
"code": [],
"doc": [
"ComfyUI-Impact-Pack/tutorial/switch.md"
],
"test": [],
"config": [],
"asset": []
} | null |
comfyanonymous | ComfyUI | 834ab278d2761c452f8e76c83fb62d8f8ce39301 | https://github.com/comfyanonymous/ComfyUI/issues/1064 | Error occurred when executing CLIPVisionEncode | Hi there,
somehow i cant get unCLIP to work
The .png has the unclip example workflow i tried out, but it gets stuck in the CLIPVisionEncode Module.
What can i do to solve this?
Error occurred when executing CLIPVisionEncode:
'NoneType' object has no attribute 'encode_image'
File "D:\ComfyUI_windows_portable_nvidia_cu118_or_cpu\ComfyUI_windows_portable\ComfyUI\execution.py", line 144, in recursive_execute
output_data, output_ui = get_output_data(obj, input_data_all)
File "D:\ComfyUI_windows_portable_nvidia_cu118_or_cpu\ComfyUI_windows_portable\ComfyUI\execution.py", line 74, in get_output_data
return_values = map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True)
File "D:\ComfyUI_windows_portable_nvidia_cu118_or_cpu\ComfyUI_windows_portable\ComfyUI\execution.py", line 67, in map_node_over_list
results.append(getattr(obj, func)(**slice_dict(input_data_all, i)))
File "D:\ComfyUI_windows_portable_nvidia_cu118_or_cpu\ComfyUI_windows_portable\ComfyUI\nodes.py", line 742, in encode
output = clip_vision.encode_image(image)
| null | null | null | {'base_commit': '834ab278d2761c452f8e76c83fb62d8f8ce39301', 'files': [{'path': 'README.md', 'Loc': {'(None, None, 30)': {'mod': [30]}}, 'status': 'modified'}]} | [] | [] | [] | {
"iss_type": "1",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "2",
"info_type": "model\n+\nDoc"
} | {
"code": [],
"doc": [
"README.md"
],
"test": [],
"config": [],
"asset": []
} | null | |
comfyanonymous | ComfyUI | 3c60ecd7a83da43d694e26a77ca6b93106891251 | https://github.com/comfyanonymous/ComfyUI/issues/5229 | User Support | Problem with ComfyUI workflow "ControlNetApplySD3 'NoneType' object has no attribute 'copy'" | ### Your question
I get the following error when running the workflow
I leave a video of what I am working on as a reference.
https://www.youtube.com/watch?v=MbQv8zoNEfY
video of reference
### Logs
```powershell
# ComfyUI Error Report
## Error Details
- **Node Type:** ControlNetApplySD3
- **Exception Type:** AttributeError
- **Exception Message:** 'NoneType' object has no attribute 'copy'
## Stack Trace
File "D:\ComfyUI_windows_portable\ComfyUI\execution.py", line 323, in execute
output_data, output_ui, has_subgraph = get_output_data(obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\ComfyUI_windows_portable\ComfyUI\execution.py", line 198, in get_output_data
return_values = _map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\ComfyUI_windows_portable\ComfyUI\execution.py", line 169, in _map_node_over_list
process_inputs(input_dict, i)
File "D:\ComfyUI_windows_portable\ComfyUI\execution.py", line 158, in process_inputs
results.append(getattr(obj, func)(**inputs))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\ComfyUI_windows_portable\ComfyUI\nodes.py", line 848, in apply_controlnet
c_net = control_net.copy().set_cond_hint(control_hint, strength, (start_percent, end_percent), vae=vae, extra_concat=extra_concat)
^^^^^^^^^^^^^^^^
```
## System Information
- **ComfyUI Version:** v0.2.3-3-g6632365
- **Arguments:** ComfyUI\main.py --windows-standalone-build
- **OS:** nt
- **Python Version:** 3.11.9 (tags/v3.11.9:de54cf5, Apr 2 2024, 10:12:12) [MSC v.1938 64 bit (AMD64)]
- **Embedded Python:** true
- **PyTorch Version:** 2.4.1+cu124
## Devices
- **Name:** cuda:0 NVIDIA GeForce RTX 3090 : cudaMallocAsync
- **Type:** cuda
- **VRAM Total:** 25769148416
- **VRAM Free:** 19327837688
- **Torch VRAM Total:** 5100273664
- **Torch VRAM Free:** 57107960
## Logs
```
2024-10-12 11:47:24,318 - root - INFO - Total VRAM 24575 MB, total RAM 65461 MB
2024-10-12 11:47:24,318 - root - INFO - pytorch version: 2.4.1+cu124
2024-10-12 11:47:24,318 - root - INFO - Set vram state to: NORMAL_VRAM
2024-10-12 11:47:24,318 - root - INFO - Device: cuda:0 NVIDIA GeForce RTX 3090 : cudaMallocAsync
2024-10-12 11:47:26,738 - root - INFO - Using pytorch cross attention
2024-10-12 11:47:32,778 - root - INFO - [Prompt Server] web root: D:\ComfyUI_windows_portable\ComfyUI\web
2024-10-12 11:47:36,818 - root - INFO - Total VRAM 24575 MB, total RAM 65461 MB
2024-10-12 11:47:36,818 - root - INFO - pytorch version: 2.4.1+cu124
2024-10-12 11:47:36,818 - root - INFO - Set vram state to: NORMAL_VRAM
2024-10-12 11:47:36,818 - root - INFO - Device: cuda:0 NVIDIA GeForce RTX 3090 : cudaMallocAsync
2024-10-12 11:47:37,468 - root - INFO -
Import times for custom nodes:
2024-10-12 11:47:37,468 - root - INFO - 0.0 seconds: D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\websocket_image_save.py
2024-10-12 11:47:37,468 - root - INFO - 0.0 seconds: D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\cg-use-everywhere
2024-10-12 11:47:37,468 - root - INFO - 0.0 seconds: D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\ComfyUI_UltimateSDUpscale
2024-10-12 11:47:37,468 - root - INFO - 0.0 seconds: D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\rgthree-comfy
2024-10-12 11:47:37,468 - root - INFO - 0.0 seconds: D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\ComfyUI-KJNodes
2024-10-12 11:47:37,468 - root - INFO - 0.1 seconds: D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\ComfyUI_essentials
2024-10-12 11:47:37,468 - root - INFO - 0.1 seconds: D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\comfyui_controlnet_aux
2024-10-12 11:47:37,468 - root - INFO - 0.3 seconds: D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\ComfyUI-eesahesNodes
2024-10-12 11:47:37,468 - root - INFO - 0.4 seconds: D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\ComfyUI-Manager
2024-10-12 11:47:37,468 - root - INFO - 0.4 seconds: D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\ComfyUI-Impact-Pack
2024-10-12 11:47:37,468 - root - INFO - 1.1 seconds: D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\ComfyUI-AdvancedLivePortrait
2024-10-12 11:47:37,468 - root - INFO -
2024-10-12 11:47:37,478 - root - INFO - Starting server
2024-10-12 11:47:37,478 - root - INFO - To see the GUI go to: http://127.0.0.1:8188
2024-10-12 12:16:10,093 - root - INFO - got prompt
2024-10-12 12:16:10,103 - root - ERROR - Failed to validate prompt for output 147:
2024-10-12 12:16:10,103 - root - ERROR - * UpscaleModelLoader 83:
2024-10-12 12:16:10,103 - root - ERROR - - Value not in list: model_name: '4x-ClearRealityV1.pth' not in ['ClearRealityV1\\4x-ClearRealityV1.pth', 'ClearRealityV1\\4x-ClearRealityV1_Soft.pth', 'ClearRealityV1\\BROKEN_NCNN\\4x-ClearRealityV1-fp16.bin', 'ClearRealityV1\\BROKEN_NCNN\\4x-ClearRealityV1-fp32.bin', 'ClearRealityV1\\BROKEN_NCNN\\4x-ClearRealityV1_Soft-fp16.bin', 'ClearRealityV1\\BROKEN_NCNN\\4x-ClearRealityV1_Soft-fp32.bin']
2024-10-12 12:16:10,103 - root - ERROR - Output will be ignored
2024-10-12 12:16:10,103 - root - ERROR - Failed to validate prompt for output 321:
2024-10-12 12:16:10,103 - root - ERROR - Output will be ignored
2024-10-12 12:16:10,103 - root - ERROR - Failed to validate prompt for output 311:
2024-10-12 12:16:10,103 - root - ERROR - * InstantX Flux Union ControlNet Loader 334:
2024-10-12 12:16:10,103 - root - ERROR - - Value not in list: control_net_name: 'flux\InstantX_flux.safetensors' not in ['flux-canny-controlnet-v3.safetensors', 'flux-canny-controlnet.safetensors', 'flux-canny-controlnet_v2.safetensors', 'flux-depth-controlnet-v3.safetensors', 'flux-depth-controlnet.safetensors', 'flux-depth-controlnet_v2.safetensors', 'flux-hed-controlnet-v3.safetensors', 'flux-hed-controlnet.safetensors', 'flux\\diffusion_pytorch_model.safetensors']
2024-10-12 12:16:10,103 - root - ERROR - Output will be ignored
2024-10-12 12:16:10,103 - root - ERROR - Failed to validate prompt for output 301:
2024-10-12 12:16:10,103 - root - ERROR - Output will be ignored
2024-10-12 12:16:10,108 - root - ERROR - Failed to validate prompt for output 140:
2024-10-12 12:16:10,108 - root - ERROR - Output will be ignored
2024-10-12 12:16:10,108 - root - ERROR - Failed to validate prompt for output 320:
2024-10-12 12:16:10,108 - root - ERROR - Output will be ignored
2024-10-12 12:16:10,108 - root - ERROR - Failed to validate prompt for output 145:
2024-10-12 12:16:10,108 - root - ERROR - Output will be ignored
2024-10-12 12:16:10,108 - root - ERROR - Failed to validate prompt for output 319:
2024-10-12 12:16:10,108 - root - ERROR - Output will be ignored
2024-10-12 12:16:10,108 - root - ERROR - Failed to validate prompt for output 179:
2024-10-12 12:16:10,108 - root - ERROR - Output will be ignored
2024-10-12 12:16:10,108 - root - ERROR - Failed to validate prompt for output 84:
2024-10-12 12:16:10,108 - root - ERROR - Output will be ignored
2024-10-12 12:16:10,108 - root - ERROR - Failed to validate prompt for output 258:
2024-10-12 12:16:10,108 - root - ERROR - Output will be ignored
2024-10-12 12:16:10,108 - root - ERROR - Failed to validate prompt for output 299:
2024-10-12 12:16:10,108 - root - ERROR - Output will be ignored
2024-10-12 12:16:10,113 - root - ERROR - Failed to validate prompt for output 138:
2024-10-12 12:16:10,113 - root - ERROR - Output will be ignored
2024-10-12 12:16:10,113 - root - ERROR - Failed to validate prompt for output 146:
2024-10-12 12:16:10,113 - root - ERROR - Output will be ignored
2024-10-12 12:16:10,113 - root - ERROR - Failed to validate prompt for output 322:
2024-10-12 12:16:10,113 - root - ERROR - Output will be ignored
2024-10-12 12:16:10,113 - root - ERROR - Failed to validate prompt for output 317:
2024-10-12 12:16:10,113 - root - ERROR - Output will be ignored
2024-10-12 12:16:10,113 - root - ERROR - Failed to validate prompt for output 323:
2024-10-12 12:16:10,113 - root - ERROR - Output will be ignored
2024-10-12 12:16:10,113 - root - ERROR - Failed to validate prompt for output 316:
2024-10-12 12:16:10,113 - root - ERROR - Output will be ignored
2024-10-12 12:16:10,113 - root - ERROR - Failed to validate prompt for output 300:
2024-10-12 12:16:10,113 - root - ERROR - Output will be ignored
2024-10-12 12:16:10,113 - root - ERROR - Failed to validate prompt for output 87:
2024-10-12 12:16:10,113 - root - ERROR - Output will be ignored
2024-10-12 12:16:10,113 - root - ERROR - Failed to validate prompt for output 318:
2024-10-12 12:16:10,113 - root - ERROR - Output will be ignored
2024-10-12 12:16:10,113 - root - ERROR - Failed to validate prompt for output 141:
2024-10-12 12:16:10,118 - root - ERROR - Output will be ignored
2024-10-12 12:16:10,647 - root - INFO - Using pytorch attention in VAE
2024-10-12 12:16:10,647 - root - INFO - Using pytorch attention in VAE
2024-10-12 12:16:18,202 - root - INFO - model weight dtype torch.float8_e4m3fn, manual cast: torch.bfloat16
2024-10-12 12:16:18,202 - root - INFO - model_type FLUX
2024-10-12 12:27:11,335 - root - ERROR - error could not detect control model type.
2024-10-12 12:27:11,335 - root - ERROR - error checkpoint does not contain controlnet or t2i adapter data D:\ComfyUI_windows_portable\ComfyUI\models\controlnet\flux\diffusion_pytorch_model.safetensors
2024-10-12 12:27:13,290 - root - INFO - Requested to load FluxClipModel_
2024-10-12 12:27:13,294 - root - INFO - Loading 1 new model
2024-10-12 12:27:13,301 - root - INFO - loaded completely 0.0 4777.53759765625 True
2024-10-12 12:27:51,099 - root - WARNING - clip missing: ['text_projection.weight']
2024-10-12 12:27:52,730 - root - ERROR - !!! Exception during processing !!! 'NoneType' object has no attribute 'copy'
2024-10-12 12:27:52,745 - root - ERROR - Traceback (most recent call last):
File "D:\ComfyUI_windows_portable\ComfyUI\execution.py", line 323, in execute
output_data, output_ui, has_subgraph = get_output_data(obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\ComfyUI_windows_portable\ComfyUI\execution.py", line 198, in get_output_data
return_values = _map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\ComfyUI_windows_portable\ComfyUI\execution.py", line 169, in _map_node_over_list
process_inputs(input_dict, i)
File "D:\ComfyUI_windows_portable\ComfyUI\execution.py", line 158, in process_inputs
results.append(getattr(obj, func)(**inputs))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\ComfyUI_windows_portable\ComfyUI\nodes.py", line 848, in apply_controlnet
c_net = control_net.copy().set_cond_hint(control_hint, strength, (start_percent, end_percent), vae=vae, extra_concat=extra_concat)
^^^^^^^^^^^^^^^^
AttributeError: 'NoneType' object has no attribute 'copy'
2024-10-12 12:27:52,750 - root - INFO - Prompt executed in 702.63 seconds
2024-10-12 12:44:26,904 - root - INFO - got prompt
2024-10-12 12:44:26,917 - root - ERROR - Failed to validate prompt for output 147:
2024-10-12 12:44:26,917 - root - ERROR - * UpscaleModelLoader 83:
2024-10-12 12:44:26,917 - root - ERROR - - Value not in list: model_name: '4x-ClearRealityV1.pth' not in ['ClearRealityV1\\4x-ClearRealityV1.pth', 'ClearRealityV1\\4x-ClearRealityV1_Soft.pth', 'ClearRealityV1\\BROKEN_NCNN\\4x-ClearRealityV1-fp16.bin', 'ClearRealityV1\\BROKEN_NCNN\\4x-ClearRealityV1-fp32.bin', 'ClearRealityV1\\BROKEN_NCNN\\4x-ClearRealityV1_Soft-fp16.bin', 'ClearRealityV1\\BROKEN_NCNN\\4x-ClearRealityV1_Soft-fp32.bin']
2024-10-12 12:44:26,917 - root - ERROR - Output will be ignored
2024-10-12 12:44:26,917 - root - ERROR - Failed to validate prompt for output 321:
2024-10-12 12:44:26,917 - root - ERROR - Output will be ignored
2024-10-12 12:44:26,917 - root - ERROR - Failed to validate prompt for output 311:
2024-10-12 12:44:26,917 - root - ERROR - * InstantX Flux Union ControlNet Loader 334:
2024-10-12 12:44:26,917 - root - ERROR - - Value not in list: control_net_name: 'flux\InstantX_flux.safetensors' not in ['flux-canny-controlnet-v3.safetensors', 'flux-canny-controlnet.safetensors', 'flux-canny-controlnet_v2.safetensors', 'flux-depth-controlnet-v3.safetensors', 'flux-depth-controlnet.safetensors', 'flux-depth-controlnet_v2.safetensors', 'flux-hed-controlnet-v3.safetensors', 'flux-hed-controlnet.safetensors', 'flux\\diffusion_pytorch_model.safetensors']
2024-10-12 12:44:26,917 - root - ERROR - Output will be ignored
2024-10-12 12:44:26,917 - root - ERROR - Failed to validate prompt for output 301:
2024-10-12 12:44:26,917 - root - ERROR - Output will be ignored
2024-10-12 12:44:26,917 - root - ERROR - Failed to validate prompt for output 140:
2024-10-12 12:44:26,922 - root - ERROR - Output will be ignored
2024-10-12 12:44:26,922 - root - ERROR - Failed to validate prompt for output 320:
2024-10-12 12:44:26,922 - root - ERROR - Output will be ignored
2024-10-12 12:44:26,922 - root - ERROR - Failed to validate prompt for output 145:
2024-10-12 12:44:26,922 - root - ERROR - Output will be ignored
2024-10-12 12:44:26,922 - root - ERROR - Failed to validate prompt for output 319:
2024-10-12 12:44:26,922 - root - ERROR - Output will be ignored
2024-10-12 12:44:26,922 - root - ERROR - Failed to validate prompt for output 179:
2024-10-12 12:44:26,922 - root - ERROR - Output will be ignored
2024-10-12 12:44:26,922 - root - ERROR - Failed to validate prompt for output 84:
2024-10-12 12:44:26,922 - root - ERROR - Output will be ignored
2024-10-12 12:44:26,922 - root - ERROR - Failed to validate prompt for output 258:
2024-10-12 12:44:26,922 - root - ERROR - Output will be ignored
2024-10-12 12:44:26,922 - root - ERROR - Failed to validate prompt for output 299:
2024-10-12 12:44:26,927 - root - ERROR - Output will be ignored
2024-10-12 12:44:26,927 - root - ERROR - Failed to validate prompt for output 138:
2024-10-12 12:44:26,927 - root - ERROR - Output will be ignored
2024-10-12 12:44:26,927 - root - ERROR - Failed to validate prompt for output 146:
2024-10-12 12:44:26,927 - root - ERROR - Output will be ignored
2024-10-12 12:44:26,927 - root - ERROR - Failed to validate prompt for output 322:
2024-10-12 12:44:26,927 - root - ERROR - Output will be ignored
2024-10-12 12:44:26,927 - root - ERROR - Failed to validate prompt for output 317:
2024-10-12 12:44:26,927 - root - ERROR - Output will be ignored
2024-10-12 12:44:26,927 - root - ERROR - Failed to validate prompt for output 323:
2024-10-12 12:44:26,927 - root - ERROR - Output will be ignored
2024-10-12 12:44:26,927 - root - ERROR - Failed to validate prompt for output 316:
2024-10-12 12:44:26,927 - root - ERROR - Output will be ignored
2024-10-12 12:44:26,927 - root - ERROR - Failed to validate prompt for output 300:
2024-10-12 12:44:26,927 - root - ERROR - Output will be ignored
2024-10-12 12:44:26,927 - root - ERROR - Failed to validate prompt for output 87:
2024-10-12 12:44:26,927 - root - ERROR - Output will be ignored
2024-10-12 12:44:26,927 - root - ERROR - Failed to validate prompt for output 318:
2024-10-12 12:44:26,927 - root - ERROR - Output will be ignored
2024-10-12 12:44:26,932 - root - ERROR - Failed to validate prompt for output 141:
2024-10-12 12:44:26,932 - root - ERROR - Output will be ignored
2024-10-12 12:44:26,992 - root - ERROR - !!! Exception during processing !!! 'NoneType' object has no attribute 'copy'
2024-10-12 12:44:26,992 - root - ERROR - Traceback (most recent call last):
File "D:\ComfyUI_windows_portable\ComfyUI\execution.py", line 323, in execute
output_data, output_ui, has_subgraph = get_output_data(obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\ComfyUI_windows_portable\ComfyUI\execution.py", line 198, in get_output_data
return_values = _map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\ComfyUI_windows_portable\ComfyUI\execution.py", line 169, in _map_node_over_list
process_inputs(input_dict, i)
File "D:\ComfyUI_windows_portable\ComfyUI\execution.py", line 158, in process_inputs
results.append(getattr(obj, func)(**inputs))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\ComfyUI_windows_portable\ComfyUI\nodes.py", line 848, in apply_controlnet
c_net = control_net.copy().set_cond_hint(control_hint, strength, (start_percent, end_percent), vae=vae, extra_concat=extra_concat)
^^^^^^^^^^^^^^^^
AttributeError: 'NoneType' object has no attribute 'copy'
2024-10-12 12:44:26,997 - root - INFO - Prompt executed in 0.06 seconds
```
## Attached Workflow
Please make sure that workflow does not contain any sensitive information such as API keys or passwords.
```
Workflow too large. Please manually upload the workflow from local file system.
```
## Additional Context
(Please add any additional context or steps to reproduce the error here)
```
### Other
| null | null | null | {} | [] | [] | [
{
"org": "Shakker-Labs",
"pro": "FLUX.1-dev-ControlNet-Union-Pro"
}
] | {
"iss_type": "1",
"iss_reason": "3",
"loc_way": "comment",
"loc_scope": "2",
"info_type": "Code"
} | {
"code": [],
"doc": [],
"test": [],
"config": [],
"asset": [
"FLUX.1-dev-ControlNet-Union-Pro"
]
} | null |
comfyanonymous | ComfyUI | 494cfe5444598f22eced91b6f4bfffc24c4af339 | https://github.com/comfyanonymous/ComfyUI/issues/96 | Feature Request: model and output path setting | Sym linking is not ideal, setting a model folder is pretty standard these days and most of us use more than one software that uses models.
The same for choosing where to put the output images, personally mine go to a portable drive, not sure how to do that with ComfyUI. | null | null | null | {'base_commit': '494cfe5444598f22eced91b6f4bfffc24c4af339', 'files': [{'path': 'extra_model_paths.yaml.example', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "4",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [],
"doc": [],
"test": [],
"config": [
"extra_model_paths.yaml.example"
],
"asset": []
} | null | |
comfyanonymous | ComfyUI | f18ebbd31645437afaa9738fcf2b5ed8b48cb021 | https://github.com/comfyanonymous/ComfyUI/issues/6186 | User Support
Custom Nodes Bug | error | ### Your question
[Errno 2] No such file or directory: 'D:\\ComfyUI_windows_portable_nvidia\\ComfyUI_windows_portable\\ComfyUI\\custom_nodes\\comfyui_controlnet_aux\\ckpts\\LiheYoung\\Depth-Anything\\.cache\\huggingface\\download\\checkpoints\\depth_anything_vitl14.pth.6c6a383e33e51c5fdfbf31e7ebcda943973a9e6a1cbef1564afe58d7f2e8fe63.incomplete' is:issue
### Logs
```powershell
.
```
### Other
_No response_ | null | null | null | {} | [] | [
".cache"
] | [] | {
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"iss_reason": "5",
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"code": [
".cache"
],
"doc": [],
"test": [],
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"asset": []
} | null |
ageitgey | face_recognition | e9df345a7853c52bfe98830bd2c9a07aaa7b81d9 | https://github.com/ageitgey/face_recognition/issues/159 | Raspberry Pi Memory Error | * face_recognition version: 02.1
* Python version: 2.7
* Operating System: Raspian
### Description
I installed to face_recognition my raspberry pi successfully for python 3. Now i am trying to install for Python2 because i need it. When i was trying install i am taking a Memory Error. I attached the images from my error. Please help me
| null | null | null | {'base_commit': 'e9df345a7853c52bfe98830bd2c9a07aaa7b81d9', 'files': [{'path': 'README.md', 'Loc': {}}]} | [] | [] | [] | {
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"README.md"
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ageitgey | face_recognition | 0961fd1aaf97336e544421318fcd4b55feeb1a79 | https://github.com/ageitgey/face_recognition/issues/533 | knn neighbors name list? | In **face_recognition_knn.py**
I want name list of 5 neighbors. So I change n_neighbors=5.
`closest_distances = knn_clf.kneighbors(faces_encodings, n_neighbors=5)`
And it returned just 5 values of **distance_threshold** from trained .clf file
I found that `knn_clf.predict(faces_encodings)` return only 1 best match name.
How can I get the name list of all that 5 people? | null | null | null | {} | [] | [] | [
{
"pro": "scikit-learn"
},
{
"pro": "scikit-learn",
"path": [
"sklearn/neighbors/_classification.py"
]
}
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],
"doc": [],
"test": [],
"config": [],
"asset": [
"scikit-learn"
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} | null | |
ageitgey | face_recognition | f21631401119e4af2e919dd662c3817b2c480c75 | https://github.com/ageitgey/face_recognition/issues/135 | face_recognization with python | * face_recognition version:
* Python version:3.5
* Operating System:windows
### Description
I am working with some python face reorganization code in which I want to compare sampleface.jpg which contains a sample face with facegrid.jpg. The facegrid.jpg itself has some 6 faces in it. I am getting results as true for every face while I should be getting only one. The code is below.
```python
import face_recognition
image = face_recognition.load_image_file("faceGrid.jpg")
sample_image = face_recognition.load_image_file("sampleface.jpg")
sample_face_encoding = face_recognition.face_encodings(sample_image)
face_locations = face_recognition.face_locations(image)
print (len(face_locations), " Faces")
for face_location in face_locations:
top, right, bottom, left = face_location
face_image = image[top:bottom, left:right]
face_encodings = face_recognition.face_encodings(face_image)[0]
if face_recognition.compare_faces(sample_face_encoding,face_encodings)[0]:
print ("Found!")
```
| null | null | null | {'base_commit': 'f21631401119e4af2e919dd662c3817b2c480c75', 'files': [{'path': 'README.md', 'Loc': {}}]} | [] | [] | [] | {
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ageitgey | face_recognition | cea177b75f74fe4e8ce73cf33da2e7e38e658ba4 | https://github.com/ageitgey/face_recognition/issues/726 | cv2.imshow error | Hi All,
with the help of docs i am trying to display image with below code and getting error. i tried all possible ways like file extension, path and python version to resolve this error and not able to rectify. So, please do needful,
Note:- 1.image present in the path.
2. print statement result None as output.
3. i am using python 3.6 & opencv-python-4.0.0.21
import numpy
import cv2
img = cv2.imread('C:\\Users\\Public\\Pictures\\Sample Pictures\\Penguins.jpeg',0) # to read an image
cv2.imshow('image',img) # to display image
cv2.waitKey(0)
cv2.destroyAllWindows()
Traceback (most recent call last):
File "C:/Users/rrmamidi/Desktop/old Desktop/compress_1/python/basic python scripts/about camera_opencv_cv2/about_img_read.py", line 11, in <module>
cv2.imshow('image',img) # to display image
cv2.error: OpenCV(4.0.0) C:\projects\opencv-python\opencv\modules\highgui\src\window.cpp:350: error: (-215:Assertion failed) size.width>0 && size.height>0 in function 'cv::imshow'
Thanks,
Raja | null | null | null | {} | [
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ageitgey | face_recognition | b8fed6f3c0ad5ab2dab72d6251c60843cad71386 | https://github.com/ageitgey/face_recognition/issues/643 | Train model with more than 1 image per person | * face_recognition version: 1.2.3
* Python version: 2.7.15
* Operating System: Windows 10
### Description
I Would like to train the model with more than 1 image per each person to achieve better recognition results. Is it possible?
One more question is what does [0] mean here:
```
known_face_encoding_user = face_recognition.face_encodings('image.jpg')[0]
```
If I put [1] here I receive "IndexError: list index out of range" error.
| null | null | null | {'base_commit': 'b8fed6f3c0ad5ab2dab72d6251c60843cad71386', 'files': [{'path': 'examples/face_recognition_knn.py', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "3",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "",
"info_type": "Code"
} | {
"code": [
"examples/face_recognition_knn.py"
],
"doc": [],
"test": [],
"config": [],
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} | null | |
ageitgey | face_recognition | aff06e965e895d8a6e781710e7c44c894e3011a3 | https://github.com/ageitgey/face_recognition/issues/68 | cv2.error: /home/pi/opencv-3.1.0/modules/imgproc/src/imgwarp.cpp:3229: error: (-215) ssize.area() > 0 in function resize | * face_recognition version:
* Python version: 3.4
* Operating System: Jesse Raspbian
### Description
Whenever I try to run facerec_from_webcam_faster.py, I get the error below. Note that I have checked my local files, the image to be recognized is place appropriately.
###
```
OpenCV Error: Assertion failed (ssize.area() > 0) in resize, file /home/pi/opencv-3.1.0/modules/imgproc/src/imgwarp.cpp, line 3229
Traceback (most recent call last):
File "pj_webcam.py", line 31, in <module>
small_frame = cv2.resize(frame, (1, 1), fx=0.01, fy=0.01)
cv2.error: /home/pi/opencv-3.1.0/modules/imgproc/src/imgwarp.cpp:3229: error: (-215) ssize.area() > 0 in function resize
```
| null | null | null | {'base_commit': 'aff06e965e895d8a6e781710e7c44c894e3011a3', 'files': [{'path': 'examples/facerec_from_webcam_faster.py', 'Loc': {'(None, None, None)': {'mod': [14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31]}}, 'status': 'modified'}]} | [] | [] | [] | {
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],
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ageitgey | face_recognition | 6da4a2ff0f0183280cdc2bffa58ddae8bf93ac41 | https://github.com/ageitgey/face_recognition/issues/181 | does load_image_file have a version which read from byte[] not just from the disk file | does load_image_file have a version which read from byte array in memory not just from the disk file. | null | null | null | {'base_commit': '6da4a2ff0f0183280cdc2bffa58ddae8bf93ac41', 'files': [{'path': 'face_recognition/api.py', 'Loc': {"(None, 'load_image_file', 73)": {'mod': []}}, 'status': 'modified'}]} | [] | [] | [] | {
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"face_recognition/api.py"
],
"doc": [],
"test": [],
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} | null | |
ageitgey | face_recognition | 5f804870c14803c2664942c958f11112276a79cc | https://github.com/ageitgey/face_recognition/issues/209 | face_locations get wrong result but dlib is correct | * face_recognition version: 1.0.0
* Python version: 3.5
* Operating System: Ubuntu 16.04 LTS
### Description
I run the example find_faces_in_picture_cnn.py to process the image from this link.
https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1507896274082&di=824f7f59943a71e2e9904d22175ce92c&imgtype=0&src=http%3A%2F%2Fwww.moontalk.com.tw%2Fupload%2Fimages%2F20160606angelina-03.jpg
The program detect the hand as a face ,I check the code and run example in dlib from this link ,the result is correct.
http://dlib.net/cnn_face_detector.py.html
So the problem maybe occur in load_image_file ?
| null | null | null | {'base_commit': '5f804870c14803c2664942c958f11112276a79cc', 'files': [{'path': 'examples/find_faces_in_picture_cnn.py', 'Loc': {'(None, None, None)': {'mod': [12]}}, 'status': 'modified'}]} | [] | [] | [] | {
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"iss_reason": "5",
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"code": [
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],
"doc": [],
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ageitgey | face_recognition | a96484edc270697c666c1c32ba5163cf8e71b467 | https://github.com/ageitgey/face_recognition/issues/1004 | IndexError: list index out of range while attempting to automatically recognize faces | * face_recognition version: 1.2.3
* Python version: 3.7.3
* Operating System: Windows 10 x64
### Description
Hello everyone,
I was attempting to modify facerec_from_video_file.py in order to make it save the unknown faces in the video and recognize them based on the first frame they appear on for example if an unknown face appears on the frame 14 it should be recognized as "new 14" but i keep getting the error "IndexError: list index out of range" when a new face appears.
So here is my code and the traceback
### What I Did
```
import face_recognition
import cv2
input_movie = cv2.VideoCapture("video.mp4")
length = int(input_movie.get(cv2.CAP_PROP_FRAME_COUNT))
# Create an output movie file (make sure resolution/frame rate matches input video!)
fourcc = cv2.VideoWriter_fourcc(*'XVID')
output_movie = cv2.VideoWriter('output.avi', fourcc, 29.97, (640, 360))
newimage = face_recognition.load_image_file("anchor.png")
new_face_encoding = face_recognition.face_encodings(newimage)[0]
known_faces = [
new_face_encoding,
]
# Initialize some variables
face_locations = []
face_encodings = []
face_names = []
frame_number = 0
def recog(frame_number, known_faces, face_names):
toenc = []
torec = face_recognition.load_image_file(r"New\Unknown%s.jpg" %str(frame_number))
#if not len(torec):
# print("cannot find image")
#torec = face_recognition.load_image_file(r"New\Unknown%s.jpg" %str(frame_number))
toenc.append((face_recognition.face_encodings(torec))[0])
if not len(toenc):
print("can't be encoded")
known_faces.append(toenc.pop())
face_names.append("new %s" %str(frame_number))
# Load some sample pictures and learn how to recognize them.
while True:
# Grab a single frame of video
ret, frame = input_movie.read()
frame_number += 1
# Quit when the input video file ends
if not ret:
break
# Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)
rgb_frame = frame[:, :, ::-1]
# Find all the faces and face encodings in the current frame of video
face_locations = face_recognition.face_locations(rgb_frame)
face_encodings = face_recognition.face_encodings(rgb_frame, face_locations)
#face_names = []
for face_encoding in face_encodings:
# See if the face is a match for the known face(s)
match = face_recognition.compare_faces(known_faces, face_encoding)
# If you had more than 2 faces, you could make this logic a lot prettier
# but I kept it simple for the demo
name = "Unknown"
face_names.append(name)
# Label the results
for (top, right, bottom, left), name in zip(face_locations, face_names):
if not name:
continue
# Draw a box around the face
unface = cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
if name == "Unknown":
res = frame[top:bottom, left:right]
cv2.imwrite(r"New\Unknown%s.jpg" %str(frame_number), res)
recog(frame_number, known_faces, face_names)
cv2.rectangle(frame, (left, bottom - 25), (right, bottom), (0, 0, 255), cv2.FILLED)
font = cv2.FONT_HERSHEY_DUPLEX
cv2.putText(frame, name, (left + 6, bottom - 6), font, 0.5, (255, 255, 255), 1)
# Write the resulting image to the output video file
print("Processing frame {} / {}".format(frame_number, length))
#output_movie.write(frame)
cv2.imshow("frame", frame)
if( cv2.waitKey(27) & 0xFF == ord('q')):
break
# All done!
input_movie.release()
cv2.destroyAllWindows()
```
### Output
```
In [1]: runfile('D:/project_new/facerec_from_video_file.py', wdir='D:/project_new')
Processing frame 1 / 3291
Processing frame 2 / 3291
Processing frame 3 / 3291
Processing frame 4 / 3291
Processing frame 5 / 3291
Processing frame 6 / 3291
Processing frame 7 / 3291
Processing frame 8 / 3291
Processing frame 9 / 3291
Processing frame 10 / 3291
Processing frame 11 / 3291
Processing frame 12 / 3291
Traceback (most recent call last):
File "<ipython-input-1-4b2c69ca71f8>", line 1, in <module>
runfile('D:/project_new/facerec_from_video_file.py', wdir='D:/project_new')
File "C:\Users\saber\Anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 827, in runfile
execfile(filename, namespace)
File "C:\Users\saber\Anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 110, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)
File "D:/project_new/facerec_from_video_file.py", line 81, in <module>
recog(frame_number, known_faces, face_names)
File "D:/project_new/facerec_from_video_file.py", line 35, in recog
toenc.append((face_recognition.face_encodings(torec))[0])
IndexError: list index out of range
``` | null | null | null | {'base_commit': 'a96484edc270697c666c1c32ba5163cf8e71b467', 'files': [{'path': 'examples/facerec_from_video_file.py', 'Loc': {}}]} | [] | [] | [] | {
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ageitgey | face_recognition | a8830627e89bcfb9c9dda2c8f7cac5d2e5cfb6c0 | https://github.com/ageitgey/face_recognition/issues/178 | IndexError: list index out of range | IndexError: list index out of range
my code:
import face_recognition
known_image = face_recognition.load_image_file("D:/1.jpg")
unknown_image = face_recognition.load_image_file("D:/2.jpg")
biden_encoding = face_recognition.face_encodings(known_image)[0] | null | null | null | {} | [
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}
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"info_type": "Code"
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null
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"doc": [],
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ageitgey | face_recognition | 7f183afd9c848f05830c145890c04181dcc1c46b | https://github.com/ageitgey/face_recognition/issues/93 | how to do live face recognition with RPi | * Operating System: Debian
### Description
i want to use the example ```facerec_from_webcam_faster.py```
but i don't know how to change the video_output source to the PiCam
### What I Did
```
camera = picamera.PiCamera()
camera.resolution = (320, 240)
output = np.empty((240, 320, 3), dtype=np.uint8)
while True:
# Grab a single frame of video
ret, frame = camera.capture(output, format="rgb")
```
but i got erros, so how can i use the picam as source?
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PaddlePaddle | PaddleOCR | 14318e392fbe2d69511441edf5a172c4c72d6961 | https://github.com/PaddlePaddle/PaddleOCR/issues/7095 | status/close | 文本检测完的图片怎么进行文本识别啊？ | 是要把边界框框出的图片剪裁下来，送进识别模型吗？关于这个的代码在哪里啊 | null | null | null | {'base_commit': '14318e392fbe2d69511441edf5a172c4c72d6961', 'files': [{'path': 'tools/infer/predict_system.py', 'Loc': {"('TextSystem', '__call__', 67)": {'mod': [69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89]}}, 'status': 'modified'}]} | [] | [] | [] | {
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"iss_reason": "5",
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"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"tools/infer/predict_system.py"
],
"doc": [],
"test": [],
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} | null |
PaddlePaddle | PaddleOCR | db60893201ad07a8c20d938a8224799f932779ad | https://github.com/PaddlePaddle/PaddleOCR/issues/5641 | inference and deployment | PaddleServing怎样修改相关参数 | 根据 [**基于PaddleServing的服务部署**](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.4/deploy/pdserving/README_CN.md) 后，怎样对模型及服务的一些参数进行修改呢？
例如如下参数：
use_tensorrt
batch_size
det_limit_side_len
batch_num
total_process_num
...
疑惑：
1、[**PaddleHub Serving部署**](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.4/deploy/hubserving/readme.md)，支持一些参数修改
2、[**基于Python引擎的PP-OCR模型库推理**](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.4/doc/doc_ch/inference_ppocr.md)，也支持参数修改
上面列举的几个参数都极其重要，但是PaddleServing方法却不支持，请指示！是否是哪里可以设置而我没找到 | null | null | null | {'base_commit': 'db60893201ad07a8c20d938a8224799f932779ad', 'files': [{'path': 'deploy/pdserving/web_service.py', 'Loc': {"('DetOp', 'init_op', 30)": {'mod': [31]}}, 'status': 'modified'}]} | [] | [] | [] | {
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],
"doc": [],
"test": [],
"config": [],
"asset": []
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PaddlePaddle | PaddleOCR | 0afe6c3262babda2012074110520fe9d1a3c63c0 | https://github.com/PaddlePaddle/PaddleOCR/issues/2405 | status/close | 轻量模型的推断中，每隔几行就会出现一行识别为乱码 | 
就像这里蓝色圈起来的这行
但是通用模型就没有这个问题
这是什么原因引起的呢？ | null | null | null | {'base_commit': '0afe6c3262babda2012074110520fe9d1a3c63c0', 'files': [{'path': 'deploy/hubserving/readme_en.md', 'Loc': {'(None, None, 192)': {'mod': [192]}}, 'status': 'modified'}]} | [] | [] | [] | {
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} | {
"code": [],
"doc": [
"deploy/hubserving/readme_en.md"
],
"test": [],
"config": [],
"asset": []
} | null |
PaddlePaddle | PaddleOCR | 64edd41c277c60c672388be6d5764be85c1de43a | https://github.com/PaddlePaddle/PaddleOCR/issues/5427 | status/close
stale | rknn不支持DepthwiseSeparable模块中的ConvBNLayer层参数stride(p1, p2) p1与p2不一致算子 | rknn不支持DepthwiseSeparable模块中的ConvBNLayer层参数stride(p1, p2) p1与p2不一致算子，这样涉及到修改网络结构，我看了下stride(p1, p2)中p1与p2不一致的情况是为了做下采样的操作，请问我想保持p1与p2相等的情况下，该如何修改DepthwiseSeparable模块或者更上层模块的参数呢？ | null | null | null | {'base_commit': '64edd41c277c60c672388be6d5764be85c1de43a', 'files': [{'path': 'ppocr/modeling/backbones/rec_mobilenet_v3.py', 'Loc': {"('MobileNetV3', '__init__', 23)": {'mod': [48]}}, 'status': 'modified'}]} | [] | [] | [] | {
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],
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"asset": []
} | null |
PaddlePaddle | PaddleOCR | 2e352dcc06ba86159099ec6a2928c7ce556a7245 | https://github.com/PaddlePaddle/PaddleOCR/issues/7542 | status/close | PaddleOCR加载自己的识别模型进行图像检测+识别与仅使用识别模型时效果不一致 | 先用PaddleOCR的图像检测功能，按照得到的识别框带文字的小图裁剪出来，标注用做训练集，对文字识别模型进行了训练，然后推理测试了一下没有问题，于是使用PaddleOCR加载新训练的文字识别模型跑检测 + 识别的整体流程，结果发现出现了识别结果不一致的情况。
- 系统环境/System Environment：CenOS7
- 版本号/Version：Paddle：2.3.1.post112 PaddleOCR：2.6 问题相关组件/Related components：PaddleOCR
- python/Version: 3.9.12
- 使用模型ppocrv3
问题图片：
* 单用识别模型进行推理时：（有敏感信息此处我遮挡了）
`前言－客户（“甲方”）和XXXXX（“乙方”）所签订的业务约定书（“业务约定书”）及本业务条款其同构成`
* 使用PaddleOCR时：
`（，）（7，）是时（，）－`
- 推理命令：
```
python3 tools/infer/predict_rec.py --image_dir=/home/hr/projects/ppocr/PaddleOCR/data/train_data/rec/train/XXXXX.png --rec_model_dir=/home/hr/projects/ppocr/PaddleOCR/output/inference/rec_ppocr_v3_distillation/Teacher --rec_image_shape="3, 48, 640" --rec_char_dict_path=/home/hr/projects/ppocr/PaddleOCR/ppocr/utils/ppocr_keys_v1.txt
```
- 配置文件的参数：
```
# 对image_shape进行了更改
image_shape: [3, 48, 640]
```
- PaddleOCR的加载参数设置：
```
paddle_ocr_engine = PaddleOCR(
use_angle_cls=True,
lang="ch",
rec_model_dir="./output/inference/rec_ppocr_v3_distillation/Teacher",
rec_image_shape="3, 48, 640",
rec_char_dict_path="./ppocr/utils/ppocr_keys_v1.txt")
```
如果能够提供一些帮助或者建议，非常感谢！ | null | null | null | {'base_commit': '2e352dcc06ba86159099ec6a2928c7ce556a7245', 'files': [{'path': 'paddleocr.py', 'Loc': {"('PaddleOCR', '__init__', 445)": {'mod': [480]}}, 'status': 'modified'}]} | [] | [] | [] | {
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PaddlePaddle | PaddleOCR | 443de01526a1c7108934990c4b646ed992f0bce8 | https://github.com/PaddlePaddle/PaddleOCR/issues/5209 | status/close | pdserving 最后怎么返回文本以及文本坐标 | 目前pdserving 只返回了 文本没有返回文本坐标，请问如何返回文本坐标呢 | null | null | null | {'base_commit': '443de01526a1c7108934990c4b646ed992f0bce8', 'files': [{'path': 'deploy/pdserving/ocr_reader.py', 'Loc': {"('OCRReader', 'postprocess', 425)": {'mod': []}}, 'status': 'modified'}, {'path': 'deploy/pdserving/web_service.py', 'Loc': {"('DetOp', 'postprocess', 57)": {'mod': [63]}}, 'status': 'modified'}]} | [] | [] | [] | {
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"iss_reason": "5",
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"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"deploy/pdserving/web_service.py",
"deploy/pdserving/ocr_reader.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null |
PaddlePaddle | PaddleOCR | ab16f2e4f9a4eac2eeb5f0324ab950b2215780d0 | https://github.com/PaddlePaddle/PaddleOCR/issues/3735 | 做数字训练的图像。在把检测和识别串起来的时候，识别出来的为什么是中文？ | 自己训练数字模型，用到检测和识别，在转inference模型前，识别的是数字。但将检测和识别串联的时候，按照官方教程，转换成inference模型，为什么识别出来的是中文？ | null | null | null | {'base_commit': 'ab16f2e4f9a4eac2eeb5f0324ab950b2215780d0', 'files': [{'path': 'configs/det/det_mv3_db.yml', 'Loc': {'(None, None, 116)': {'mod': [116]}}, 'status': 'modified'}, {'path': 'tools/infer/predict_det.py', 'Loc': {"('TextDetector', '__init__', 38)": {'mod': [42]}}, 'status': 'modified'}]} | [] | [] | [] | {
"iss_type": "2",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"tools/infer/predict_det.py"
],
"doc": [],
"test": [],
"config": [
"configs/det/det_mv3_db.yml"
],
"asset": []
} | null | |
PaddlePaddle | PaddleOCR | efc01375c942d87dc1e20856c7159096db16a9ab | https://github.com/PaddlePaddle/PaddleOCR/issues/11715 | Can ch_PP-OCRv4_rec_server_infer's support for english be put into the documentation? | I notice if I am calling
```
from paddleocr import PaddleOCR
ocr = Paddle.OCR(
det_model_dir=ch_PP-OCRv4_det_server_infer,
rec_model_dir=ch_PP-OCRv4_rec_infer
lang='en')
...
result = ocr.ocr(my_image)
```
this works fine. However, If i set the rec model to the server version as well (`ch_PP-OCRv4_rec_server_infer`), then I get the following error:
```
File "/opt/conda/lib/python3.10/site-packages/paddleocr/paddleocr.py", line 661, in ocr
dt_boxes, rec_res, _ = self.__call__(img, cls)
File "/opt/conda/lib/python3.10/site-packages/paddleocr/tools/infer/predict_system.py", line 105, in __call__
rec_res, elapse = self.text_recognizer(img_crop_list)
File "/opt/conda/lib/python3.10/site-packages/paddleocr/tools/infer/predict_rec.py", line 628, in __call__
rec_result = self.postprocess_op(preds)
File "/opt/conda/lib/python3.10/site-packages/paddleocr/ppocr/postprocess/rec_postprocess.py", line 121, in __call__
text = self.decode(preds_idx, preds_prob, is_remove_duplicate=True)
File "/opt/conda/lib/python3.10/site-packages/paddleocr/ppocr/postprocess/rec_postprocess.py", line 83, in decode
char_list = [
File "/opt/conda/lib/python3.10/site-packages/paddleocr/ppocr/postprocess/rec_postprocess.py", line 84, in <listcomp>
self.character[text_id]
IndexError: list index out of range
```
Which I'm guessing is because it's trying to output Chinese, which has an 8000 character dict, whereas English only has 90 or so. Because it says english is supported by the server model (https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.7/doc/doc_ch/models_list.md), is it possible to get the ppocrv4 server model to output english successfully?
<img width="1274" alt="Screen Shot 2024-03-11 at 10 12 15 PM" src="https://github.com/PaddlePaddle/PaddleOCR/assets/21298347/f0b204ea-c7d3-4368-a939-4c9f99b111fb">
| null | null | null | {'base_commit': 'efc01375c942d87dc1e20856c7159096db16a9ab', 'files': [{'path': 'paddleocr.py', 'Loc': {'(None, None, None)': {'mod': [76, 80]}}, 'status': 'modified'}]} | [] | [] | [] | {
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} | null | |
PaddlePaddle | PaddleOCR | 9d44728da81e7d56ea5f437845d8d48bc278b086 | https://github.com/PaddlePaddle/PaddleOCR/issues/3248 | 检测和识别怎么连接 | 想用轻量化的检测模型配合RCNN识别，不知道怎么将两个阶段连接在一起。 | null | null | null | {'base_commit': '9d44728da81e7d56ea5f437845d8d48bc278b086', 'files': [{'path': 'doc/doc_ch/inference.md', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "3",
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"loc_way": "comment",
"loc_scope": "0",
"info_type": "Doc"
} | {
"code": [],
"doc": [
"doc/doc_ch/inference.md"
],
"test": [],
"config": [],
"asset": []
} | null | |
PaddlePaddle | PaddleOCR | 582e868cf84fca911e195596053f503f890b561b | https://github.com/PaddlePaddle/PaddleOCR/issues/8641 | status/close | 请制作PP-Structure的PaddleServing例子吧 | 要写PP-Structure在paddle_serving_server.web_service中的Op类，感觉我这个新手做不到啊。
有没有大神做好例子，让新手复用呢 | null | null | null | {'base_commit': '582e868cf84fca911e195596053f503f890b561b', 'files': [{'path': 'deploy/hubserving/readme.md', 'Loc': {}}]} | [] | [] | [] | {
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"info_type": "Doc"
} | {
"code": [],
"doc": [
"deploy/hubserving/readme.md"
],
"test": [],
"config": [],
"asset": []
} | null |
PaddlePaddle | PaddleOCR | 35449b5c7440f7706e5a4558e5b3efeb76944432 | https://github.com/PaddlePaddle/PaddleOCR/issues/3844 | HOW TO RESUME TRAINING FROM LAST CHECKPOINT? | Hi,
I have been training a model on my own dataset, How I can resume the training from last checkpoint saved? And also when I train the model does it save Best weights automatically to some path or we need to provide some argument to do it.
Please help me on this.
Thanks.. | null | null | null | {'base_commit': '35449b5c7440f7706e5a4558e5b3efeb76944432', 'files': [{'path': 'tools/program.py', 'Loc': {"('ArgsParser', '__init__', 39)": {'mod': [42, 42]}}, 'status': 'modified'}]} | [] | [] | [] | {
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"info_type": "Doc"
} | {
"code": [
"tools/program.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null | |
PaddlePaddle | PaddleOCR | adba814904eb4f0aeeec186f158cfb6c212a6e26 | https://github.com/PaddlePaddle/PaddleOCR/issues/3942 | 模型库404 | ch_ppocr_mobile_slim_v2.1_det 推理模型
ch_ppocr_mobile_v2.1_det 推理和训练模型
上面的到目前是404状态，无法下载 | null | null | null | {'base_commit': 'adba814904eb4f0aeeec186f158cfb6c212a6e26', 'files': [{'path': 'doc/doc_ch/models_list.md', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "1",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Doc"
} | {
"code": [],
"doc": [
"doc/doc_ch/models_list.md"
],
"test": [],
"config": [],
"asset": []
} | null | |
PaddlePaddle | PaddleOCR | c167df2f60d08085167cdc9431101f4b45a8a019 | https://github.com/PaddlePaddle/PaddleOCR/issues/6838 | status/close | Mac M1 Pro can't install paddleOCR2.0.1~2.5.0.3, but I can install paddleOCR 1.1.1 and run successful. | 请提供下述完整信息以便快速定位问题/Please provide the following information to quickly locate the problem
- 系统环境/System Environment：MacBook Pro（14英寸，2021年），Apple M1 Pro 16 GB，
- 版本号/Version：Pycharm2022.1.2 and Anaconda create Python 3.8 environment.
- Paddle： Monterey 12.3
- PaddleOCR：2.0.1~2.5.0.3
- 问题相关组件/Related components：PaddleOCR、Numpy
- 运行指令/Command Code：
1. python3 -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple （运行正常，Run OK !）
2. pip install "paddleocr>=2.0.1"（运行失败，报错，Too much ERROR！）（如果我不指定paddleOCR1的版本号，会自动安装paddleOCR 1.1.1，并且可以正常运行使用，即2.0.1版本开始全部安装失败）
- 完整报错/Complete Error Message（详见markdown文档，太长了，这里传不上来）
[【Error Log】Mac M1 Pro can't install paddleOCR2.0.1~2.5.0.3.md](https://github.com/PaddlePaddle/PaddleOCR/files/9075892/Error.Log.Mac.M1.Pro.can.t.install.paddleOCR2.0.1.2.5.0.3.md)
：
- `ERROR: Cannot install paddleocr==2.0.1, paddleocr==2.0.2, paddleocr==2.0.3, paddleocr==2.0.4, paddleocr==2.0.5, paddleocr==2.0.6, paddleocr==2.2, paddleocr==2.2.0.1, paddleocr==2.2.0.2, paddleocr==2.3, paddleocr==2.3.0.1, paddleocr==2.3.0.2, paddleocr==2.4, paddleocr==2.4.0.1, paddleocr==2.4.0.2, paddleocr==2.4.0.3, paddleocr==2.4.0.4, paddleocr==2.5, paddleocr==2.5.0.2 and paddleocr==2.5.0.3 because these package versions have conflicting dependencies.
The conflict is caused by:
paddleocr 2.5.0.3 depends on opencv-contrib-python==4.4.0.46
paddleocr 2.5.0.2 depends on opencv-contrib-python==4.4.0.46
paddleocr 2.5 depends on opencv-contrib-python==4.4.0.46
paddleocr 2.4.0.4 depends on opencv-contrib-python==4.4.0.46
paddleocr 2.4.0.3 depends on opencv-contrib-python==4.4.0.46
paddleocr 2.4.0.2 depends on opencv-contrib-python==4.4.0.46
paddleocr 2.4.0.1 depends on opencv-contrib-python==4.4.0.46
paddleocr 2.4 depends on opencv-contrib-python==4.4.0.46
paddleocr 2.3.0.2 depends on opencv-contrib-python==4.4.0.46
paddleocr 2.3.0.1 depends on opencv-contrib-python==4.4.0.46
paddleocr 2.3 depends on opencv-contrib-python==4.4.0.46
paddleocr 2.2.0.2 depends on opencv-contrib-python==4.4.0.46
paddleocr 2.2.0.1 depends on opencv-contrib-python==4.2.0.32
paddleocr 2.2 depends on opencv-contrib-python==4.2.0.32
paddleocr 2.0.6 depends on opencv-python==4.2.0.32
paddleocr 2.0.5 depends on opencv-python==4.2.0.32
paddleocr 2.0.4 depends on opencv-python==4.2.0.32
paddleocr 2.0.3 depends on opencv-python==4.2.0.32
paddleocr 2.0.2 depends on opencv-python==4.2.0.32
paddleocr 2.0.1 depends on opencv-python==4.2.0.32
To fix this you could try to:
1. loosen the range of package versions you've specified
2. remove package versions to allow pip attempt to solve the dependency conflict
ERROR: ResolutionImpossible: for help visit https://pip.pypa.io/en/latest/user_guide/#fixing-conflicting-dependencies`
<img width="1544" alt="image" src="https://user-images.githubusercontent.com/29346824/178091955-5d71f63b-6bd5-477e-88e4-cb29cb161124.png">
| null | null | null | {'base_commit': 'c167df2f60d08085167cdc9431101f4b45a8a019', 'files': [{'path': 'requirements.txt', 'Loc': {'(None, None, 10)': {'mod': [10]}}, 'status': 'modified'}, {'path': 'setup.py', 'Loc': {}}]} | [] | [] | [] | {
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"setup.py"
],
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"test": [],
"config": [
"requirements.txt"
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} | null |
PaddlePaddle | PaddleOCR | e44c2af7622c97d3faecd37b062e7f1cb922fd40 | https://github.com/PaddlePaddle/PaddleOCR/issues/10298 | status/close | train warning | 请提供下述完整信息以便快速定位问题/Please provide the following information to quickly locate the problem
- 系统环境/System Environment：ubantu
- 版本号/Version：Paddle： PaddleOCR： 问题相关组件/Related components：paddle develop 0.0.0.post116
- 运行指令/Command Code：
- 完整报错/Complete Error Message：
一直有好多这种警告
I0705 11:55:13.443581 28582 eager_method.cc:140] Warning:: 0D Tensor cannot be used as 'Tensor.numpy()[0]' . In order to avoid this problem, 0D Tensor will be changed to 1D numpy currently, but it's not correct and will be removed in release 2.6. For Tensor contain only one element, Please modify 'Tensor.numpy()[0]' to 'float(Tensor)' as soon as possible, otherwise 'Tensor.numpy()[0]' will raise error in release 2.6.
| null | null | null | {'base_commit': 'e44c2af7622c97d3faecd37b062e7f1cb922fd40', 'files': [{'path': 'tools/program.py', 'Loc': {"(None, 'train', 176)": {'mod': [349]}}, 'status': 'modified'}]} | [] | [] | [] | {
"iss_type": "1",
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"info_type": "Code"
} | {
"code": [
"tools/program.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null |
AntonOsika | gpt-engineer | dc866c91b9191bce083ec908c5665b7f2f40bd17 | https://github.com/AntonOsika/gpt-engineer/issues/201 | gpt 3 | hi
can we use gpt 3 api free key ? | null | null | null | {'base_commit': 'dc866c91b9191bce083ec908c5665b7f2f40bd17', 'files': [{'path': 'scripts/rerun_edited_message_logs.py', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "3",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"scripts/rerun_edited_message_logs.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null | |
AntonOsika | gpt-engineer | 5505ec41dd49eb1e86aa405335f40d7a8fa20b0a | https://github.com/AntonOsika/gpt-engineer/issues/497 | main.py is missing? | main.py is missing? | null | null | null | {'base_commit': '5505ec41dd49eb1e86aa405335f40d7a8fa20b0a', 'files': [{'path': 'gpt_engineer/', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "5\n询问文件的位置",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [],
"doc": [],
"test": [],
"config": [],
"asset": [
"gpt_engineer/"
]
} | null | |
AntonOsika | gpt-engineer | a55265ddb46462548a842dae914bb5fcb22181fa | https://github.com/AntonOsika/gpt-engineer/issues/509 | Error with Promtfile | When I try to run the example file I get this error even though there is something in the prompt file, which you can see from the screenshots is in the example folder. Does anyone know how I can solve this problem?
| null | null | null | {'base_commit': 'a55265ddb46462548a842dae914bb5fcb22181fa', 'files': [{'path': 'projects/example/prompt', 'Loc': {}}]} | [] | [] | [] | {
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"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [],
"doc": [],
"test": [],
"config": [],
"asset": [
"projects/example/prompt"
]
} | null | |
lllyasviel | Fooocus | cca0ca704a713ab153938e78de6787609c723cad | https://github.com/lllyasviel/Fooocus/issues/1147 | urllib.error.URLError: <urlopen error [WinError 10060] A connection attempt failed because the connected party.. | Hello Guys.
This is the error I'm getting when I am trying to use the image prompt issue
urllib.error.URLError: <urlopen error [WinError 10060] A connection attempt failed because the connected party did not properly respond after a period of time, or established connection failed because connected host has failed to respond>
Total time: 21.12 seconds
Do you happen to know what could be the problem?
thanks in advance!
| null | null | null | {'base_commit': 'cca0ca704a713ab153938e78de6787609c723cad', 'files': [{'path': 'troubleshoot.md', 'Loc': {'(None, None, 43)': {'mod': [43]}}, 'status': 'modified'}]} | [] | [] | [
{
"org": "lllyasviel",
"pro": "misc",
"path": [
"ip-adapter-plus-face_sdxl_vit-h.bin"
]
}
] | {
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"troubleshoot.md"
],
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"asset": [
"ip-adapter-plus-face_sdxl_vit-h.bin"
]
} | null | |
lllyasviel | Fooocus | fc3588875759328d715fa07cc58178211a894386 | https://github.com/lllyasviel/Fooocus/issues/602 | [BUG]Memory Issue when generating images for the second time | When I generate images first time with one image prompt, everything works fine.
However, at the second generation, the GPU memory run out.
Here is the error
`Preparation time: 19.46 seconds
loading new
ERROR diffusion_model.output_blocks.0.1.transformer_blocks.4.ff.net.0.proj.weight CUDA out of memory. Tried to allocate 50.00 MiB (GPU 0; 22.41 GiB total capacity; 21.52 GiB already allocated; 11.69 MiB free; 22.21 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
ERROR diffusion_model.output_blocks.0.1.transformer_blocks.5.attn1.to_v.weight CUDA out of memory. Tried to allocate 20.00 MiB (GPU 0; 22.41 GiB total capacity; 21.56 GiB already allocated; 11.69 MiB free; 22.21 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
ERROR diffusion_model.output_blocks.0.1.transformer_blocks.5.attn1.to_out.0.weight CUDA out of memory. Tried to allocate 20.00 MiB (GPU 0; 22.41 GiB total capacity; 21.56 GiB already allocated; 11.69 MiB free; 22.21 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
Traceback (most recent call last):
File "D:\Repos\Fooocus\modules\async_worker.py", line 551, in worker
handler(task)
File "D:\Repos\Fooocus\venv\Lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "D:\Repos\Fooocus\venv\Lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "D:\Repos\Fooocus\modules\async_worker.py", line 460, in handler
comfy.model_management.load_models_gpu([pipeline.final_unet])
File "D:\Repos\Fooocus\repositories\ComfyUI-from-StabilityAI-Official\comfy\model_management.py", line 397, in load_models_gpu
cur_loaded_model = loaded_model.model_load(lowvram_model_memory)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\Repos\Fooocus\repositories\ComfyUI-from-StabilityAI-Official\comfy\model_management.py", line 286, in model_load
raise e
File "D:\Repos\Fooocus\repositories\ComfyUI-from-StabilityAI-Official\comfy\model_management.py", line 282, in model_load
self.real_model = self.model.patch_model(device_to=patch_model_to) #TODO: do something with loras and offloading to CPU
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\Repos\Fooocus\repositories\ComfyUI-from-StabilityAI-Official\comfy\model_patcher.py", line 161, in patch_model
temp_weight = comfy.model_management.cast_to_device(weight, device_to, torch.float32, copy=True)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\Repos\Fooocus\repositories\ComfyUI-from-StabilityAI-Official\comfy\model_management.py", line 498, in cast_to_device
return tensor.to(device, copy=copy).to(dtype)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 50.00 MiB (GPU 0; 22.41 GiB total capacity; 21.56 GiB already allocated; 11.69 MiB free; 22.21 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
Total time: 209.24 seconds
Keyboard interruption in main thread... closing server.
Process finished with exit code -1
`
At my second attempt to track this error, I add an endpoint. When I clicked generate and it meet the endpoint, I found 6 models have been loaded into memory. May be this is the issue?
Thanks for help~
| null | null | null | {'base_commit': 'fc3588875759328d715fa07cc58178211a894386', 'files': [{'path': 'Version', 'Loc': {}}, {'path': 'Version', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "1",
"iss_reason": "1",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [],
"doc": [],
"test": [],
"config": [],
"asset": [
"Version"
]
} | null | |
lllyasviel | Fooocus | f3084894402a4c0b7ed9e7164466bcedd5f5428d | https://github.com/lllyasviel/Fooocus/issues/1508 | Problems with installation and correct operation. | Hello, I had problems installing Fooocus on a GNU/Linux system, many errors occurred during the installation and they were all different. I was not able to capture some of them, but in general terms the errors were as follows: "could not find versions of python packages that satisfy dependencies (error during installation)","(when clicking the "generate" button) "nvidia drivers were not available found, make sure you have them installed "link to official website".
I managed to save the output of the following errors:
ERROR: Could not find a version that satisfies the requirement accelerate==0.21.0 (from -r requirements_versions.txt (line 5)) (from versions: 0.0.1, 0.1.0, 0.2.0, 0.2.1, 0.3.0, 0.4.0, 0.5.0, 0.5.1, 0.6.0, 0.6.1, 0.6.2, 0.7.0, 0.7.1, 0.8.0, 0.9.0, 0.10.0, 0.11.0, 0.12.0, 0.13.0, 0.13.1, 0.13.2, 0.14.0, 0.15.0, 0.16.0, 0.17.0, 0.17.1, 0.18.0, 0.19.0, 0.20.0, 0.20.1, 0.20.2, 0.20.3)
ERROR: No matching distribution found for accelerate==0.21.0 (from -r requirements_versions.txt (line 5))
python entry_with_update.py
Already up-to-date
Update succeeded.
[System ARGV] ['entry_with_update.py']
Python 3.10.13 (main, Sep 11 2023, 13:44:35) [GCC 11.2.0]
Fooocus version: 2.1.853
Running on local URL: http://127.0.0.1:7865
To create a public link, set share=True in launch().
Total VRAM 12006 MB, total RAM 31850 MB
xformers version: 0.0.16
Traceback (most recent call last):
File "/home/dragon_flow/Fooocus/ldm_patched/modules/model_management.py", line 222, in <module>
import accelerate
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/site-packages/accelerate/__init__.py", line 3, in <module>
from .accelerator import Accelerator
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/site-packages/accelerate/accelerator.py", line 35, in <module>
from .checkpointing import load_accelerator_state, load_custom_state, save_accelerator_state, save_custom_state
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/site-packages/accelerate/checkpointing.py", line 24, in <module>
from .utils import (
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/site-packages/accelerate/utils/__init__.py", line 131, in <module>
from .bnb import has_4bit_bnb_layers, load_and_quantize_model
File "/home/dragon_flow/.local/lib/python3.10/site-packages/shiboken2/files.dir/shibokensupport/__feature__.py", line 142, in _import
return original_import(name, *args, **kwargs)
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/site-packages/accelerate/utils/bnb.py", line 42, in <module>
import bitsandbytes as bnb
File "/home/dragon_flow/.local/lib/python3.10/site-packages/shiboken2/files.dir/shibokensupport/__feature__.py", line 142, in _import
return original_import(name, *args, **kwargs)
File "/home/dragon_flow/.local/lib/python3.10/site-packages/bitsandbytes/__init__.py", line 6, in <module>
from .autograd._functions import (
File "/home/dragon_flow/.local/lib/python3.10/site-packages/shiboken2/files.dir/shibokensupport/__feature__.py", line 142, in _import
return original_import(name, *args, **kwargs)
File "/home/dragon_flow/.local/lib/python3.10/site-packages/bitsandbytes/autograd/_functions.py", line 5, in <module>
import bitsandbytes.functional as F
File "/home/dragon_flow/.local/lib/python3.10/site-packages/shiboken2/files.dir/shibokensupport/__feature__.py", line 142, in _import
return original_import(name, *args, **kwargs)
File "/home/dragon_flow/.local/lib/python3.10/site-packages/bitsandbytes/functional.py", line 13, in <module>
from .cextension import COMPILED_WITH_CUDA, lib
File "/home/dragon_flow/.local/lib/python3.10/site-packages/shiboken2/files.dir/shibokensupport/__feature__.py", line 142, in _import
return original_import(name, *args, **kwargs)
File "/home/dragon_flow/.local/lib/python3.10/site-packages/bitsandbytes/cextension.py", line 113, in <module>
lib = CUDASetup.get_instance().lib
File "/home/dragon_flow/.local/lib/python3.10/site-packages/bitsandbytes/cextension.py", line 109, in get_instance
cls._instance.initialize()
File "/home/dragon_flow/.local/lib/python3.10/site-packages/bitsandbytes/cextension.py", line 59, in initialize
binary_name, cudart_path, cuda, cc, cuda_version_string = evaluate_cuda_setup()
File "/home/dragon_flow/.local/lib/python3.10/site-packages/bitsandbytes/cuda_setup/main.py", line 125, in evaluate_cuda_setup
cuda_version_string = get_cuda_version(cuda, cudart_path)
File "/home/dragon_flow/.local/lib/python3.10/site-packages/bitsandbytes/cuda_setup/main.py", line 45, in get_cuda_version
check_cuda_result(cuda, cudart.cudaRuntimeGetVersion(ctypes.byref(version)))
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/ctypes/__init__.py", line 387, in getattr
func = self.getitem(name)
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/ctypes/__init__.py", line 392, in getitem
func = self._FuncPtr((name_or_ordinal, self))
AttributeError: python: undefined symbol: cudaRuntimeGetVersion
ERROR: LOW VRAM MODE NEEDS accelerate.
Set vram state to: NORMAL_VRAM
Always offload VRAM
Device: cuda:0 NVIDIA GeForce RTX 4070 :
VAE dtype: torch.float32
Using xformers cross attention
Exception in thread Thread-2 (worker):
Traceback (most recent call last):
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/site-packages/transformers/utils/import_utils.py", line 1086, in _get_module
return importlib.import_module("." + module_name, self.name)
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/importlib/__init__.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "<frozen importlib._bootstrap>", line 1050, in _gcd_import
File "<frozen importlib._bootstrap>", line 1027, in _find_and_load
File "<frozen importlib._bootstrap>", line 1006, in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 688, in _load_unlocked
File "<frozen importlib._bootstrap_external>", line 883, in exec_module
File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/site-packages/transformers/models/clip/modeling_clip.py", line 27, in <module>
from ...modeling_utils import PreTrainedModel
File "/home/dragon_flow/.local/lib/python3.10/site-packages/shiboken2/files.dir/shibokensupport/__feature__.py", line 142, in _import
return original_import(name, *args, **kwargs)
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/site-packages/transformers/modeling_utils.py", line 85, in <module>
from accelerate import version as accelerate_version
File "/home/dragon_flow/.local/lib/python3.10/site-packages/shiboken2/files.dir/shibokensupport/__feature__.py", line 142, in _import
return original_import(name, *args, **kwargs)
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/site-packages/accelerate/__init__.py", line 3, in <module>
from .accelerator import Accelerator
File "/home/dragon_flow/.local/lib/python3.10/site-packages/shiboken2/files.dir/shibokensupport/__feature__.py", line 142, in _import
return original_import(name, *args, **kwargs)
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/site-packages/accelerate/accelerator.py", line 35, in <module>
from .checkpointing import load_accelerator_state, load_custom_state, save_accelerator_state, save_custom_state
File "/home/dragon_flow/.local/lib/python3.10/site-packages/shiboken2/files.dir/shibokensupport/__feature__.py", line 142, in _import
return original_import(name, *args, **kwargs)
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/site-packages/accelerate/checkpointing.py", line 24, in <module>
from .utils import (
File "/home/dragon_flow/.local/lib/python3.10/site-packages/shiboken2/files.dir/shibokensupport/__feature__.py", line 142, in _import
return original_import(name, *args, **kwargs)
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/site-packages/accelerate/utils/__init__.py", line 131, in <module>
from .bnb import has_4bit_bnb_layers, load_and_quantize_model
File "/home/dragon_flow/.local/lib/python3.10/site-packages/shiboken2/files.dir/shibokensupport/__feature__.py", line 142, in _import
return original_import(name, *args, **kwargs)
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/site-packages/accelerate/utils/bnb.py", line 42, in <module>
import bitsandbytes as bnb
File "/home/dragon_flow/.local/lib/python3.10/site-packages/shiboken2/files.dir/shibokensupport/__feature__.py", line 142, in _import
return original_import(name, *args, **kwargs)
File "/home/dragon_flow/.local/lib/python3.10/site-packages/bitsandbytes/__init__.py", line 6, in <module>
from .autograd._functions import (
File "/home/dragon_flow/.local/lib/python3.10/site-packages/shiboken2/files.dir/shibokensupport/__feature__.py", line 142, in _import
return original_import(name, *args, **kwargs)
File "/home/dragon_flow/.local/lib/python3.10/site-packages/bitsandbytes/autograd/_functions.py", line 5, in <module>
import bitsandbytes.functional as F
File "/home/dragon_flow/.local/lib/python3.10/site-packages/shiboken2/files.dir/shibokensupport/__feature__.py", line 142, in _import
return original_import(name, *args, **kwargs)
File "/home/dragon_flow/.local/lib/python3.10/site-packages/bitsandbytes/functional.py", line 13, in <module>
from .cextension import COMPILED_WITH_CUDA, lib
File "/home/dragon_flow/.local/lib/python3.10/site-packages/shiboken2/files.dir/shibokensupport/__feature__.py", line 142, in _import
return original_import(name, *args, **kwargs)
File "/home/dragon_flow/.local/lib/python3.10/site-packages/bitsandbytes/cextension.py", line 113, in <module>
lib = CUDASetup.get_instance().lib
File "/home/dragon_flow/.local/lib/python3.10/site-packages/bitsandbytes/cextension.py", line 109, in get_instance
cls._instance.initialize()
File "/home/dragon_flow/.local/lib/python3.10/site-packages/bitsandbytes/cextension.py", line 59, in initialize
binary_name, cudart_path, cuda, cc, cuda_version_string = evaluate_cuda_setup()
File "/home/dragon_flow/.local/lib/python3.10/site-packages/bitsandbytes/cuda_setup/main.py", line 125, in evaluate_cuda_setup
cuda_version_string = get_cuda_version(cuda, cudart_path)
File "/home/dragon_flow/.local/lib/python3.10/site-packages/bitsandbytes/cuda_setup/main.py", line 45, in get_cuda_version
check_cuda_result(cuda, cudart.cudaRuntimeGetVersion(ctypes.byref(version)))
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/ctypes/__init__.py", line 387, in getattr
func = self.getitem(name)
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/ctypes/__init__.py", line 392, in getitem
func = self._FuncPtr((name_or_ordinal, self))
AttributeError: python: undefined symbol: cudaRuntimeGetVersion
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/threading.py", line 1016, in _bootstrap_inner
self.run()
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/threading.py", line 953, in run
self._target(*self._args, **self._kwargs)
File "/home/dragon_flow/Fooocus/modules/async_worker.py", line 25, in worker
import modules.default_pipeline as pipeline
File "/home/dragon_flow/Fooocus/modules/default_pipeline.py", line 1, in <module>
import modules.core as core
File "/home/dragon_flow/Fooocus/modules/core.py", line 1, in <module>
from modules.patch import patch_all
File "/home/dragon_flow/Fooocus/modules/patch.py", line 29, in <module>
from modules.patch_clip import patch_all_clip
File "/home/dragon_flow/.local/lib/python3.10/site-packages/shiboken2/files.dir/shibokensupport/__feature__.py", line 142, in _import
return original_import(name, *args, **kwargs)
File "/home/dragon_flow/Fooocus/modules/patch_clip.py", line 23, in <module>
from transformers import CLIPTextModel, CLIPTextConfig, modeling_utils, CLIPVisionConfig, CLIPVisionModelWithProjection
File "/home/dragon_flow/.local/lib/python3.10/site-packages/shiboken2/files.dir/shibokensupport/__feature__.py", line 142, in _import
return original_import(name, *args, **kwargs)
File "<frozen importlib._bootstrap>", line 1075, in _handle_fromlist
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/site-packages/transformers/utils/import_utils.py", line 1077, in getattr
value = getattr(module, name)
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/site-packages/transformers/utils/import_utils.py", line 1076, in getattr
module = self._get_module(self._class_to_module[name])
File "/home/dragon_flow/anaconda3/envs/fooocus/lib/python3.10/site-packages/transformers/utils/import_utils.py", line 1088, in _get_module
raise RuntimeError(
RuntimeError: Failed to import transformers.models.clip.modeling_clip because of the following error (look up to see its traceback):
python: undefined symbol: cudaRuntimeGetVersion
| null | null | null | {'base_commit': 'f3084894402a4c0b7ed9e7164466bcedd5f5428d', 'files': [{'path': 'requirements_versions.txt', 'Loc': {'(None, None, 5)': {'mod': [5]}}, 'status': 'modified'}, {'path': 'readme.md', 'Loc': {'(None, None, 152)': {'mod': [152]}}, 'status': 'modified'}, {'path': 'troubleshoot.md', 'Loc': {'(None, None, 107)': {'mod': [107]}}, 'status': 'modified'}]} | [] | [] | [] | {
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"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [],
"doc": [
"readme.md",
"troubleshoot.md"
],
"test": [],
"config": [
"requirements_versions.txt"
],
"asset": []
} | null | |
lllyasviel | Fooocus | 225947ac1a603124b0274da3e94d2c6cba65f732 | https://github.com/lllyasviel/Fooocus/issues/500 | is this a local model or not | is this a local model or not
i dont get how it could show someone elses promts if its local | null | null | null | {'base_commit': '225947ac1a603124b0274da3e94d2c6cba65f732', 'files': [{'path': 'models/checkpoints', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "5",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [],
"doc": [],
"test": [],
"config": [],
"asset": [
"models/checkpoints"
]
} | null | |
lllyasviel | Fooocus | d7439b2d6004d50a0fda19108603a8d1941a185e | https://github.com/lllyasviel/Fooocus/issues/3689 | bug
triage | [Bug]: Exits upon attempting to load a model on Windows | ### Checklist
- [X] The issue has not been resolved by following the [troubleshooting guide](https://github.com/lllyasviel/Fooocus/blob/main/troubleshoot.md)
- [X] The issue exists on a clean installation of Fooocus
- [X] The issue exists in the current version of Fooocus
- [X] The issue has not been reported before recently
- [ ] The issue has been reported before but has not been fixed yet
### What happened?
Attempting to run Fooocus on Windows 11 (and possibly 10, haven't tested) simply exits when attempting to load the default model, no error or nothing.
### Steps to reproduce the problem
1. Install Fooocus on Windows 11 with a NVIDIA GPU
2. Attempt to run it.
### What should have happened?
It should've loaded the model successfully.
### What browsers do you use to access Fooocus?
Mozilla Firefox
### Where are you running Fooocus?
Locally
### What operating system are you using?
Windows 11 (23H2)
### Console logs
```Shell
(fooocus_env) D:\Misc4\Fooocus>python entry_with_update.py
Already up-to-date
Update succeeded.
[System ARGV] ['entry_with_update.py']
Python 3.12.7 (tags/v3.12.7:0b05ead, Oct 1 2024, 03:06:41) [MSC v.1941 64 bit (AMD64)]
Fooocus version: 2.5.5
[Cleanup] Attempting to delete content of temp dir C:\Users\hkcu\AppData\Local\Temp\fooocus
[Cleanup] Cleanup successful
Total VRAM 12281 MB, total RAM 16317 MB
Set vram state to: NORMAL_VRAM
Always offload VRAM
Device: cuda:0 NVIDIA GeForce RTX 4070 : native
VAE dtype: torch.bfloat16
Using pytorch cross attention
Refiner unloaded.
IMPORTANT: You are using gradio version 3.41.2, however version 4.44.1 is available, please upgrade.
--------
Running on local URL: http://127.0.0.1:7865
To create a public link, set `share=True` in `launch()`.
(fooocus_env) D:\Misc4\Fooocus>
```
### Additional information
Using Fooocus on the exact same machine, with the exact same amount of swap configured (4Gb) works as normal. | null | null | null | {'base_commit': 'd7439b2d6004d50a0fda19108603a8d1941a185e', 'files': [{'path': 'presets/default.json', 'Loc': {'(None, None, 2)': {'mod': [2]}}, 'status': 'modified'}]} | [] | [
"config.txt",
"config_modification_tutorial.txt"
] | [] | {
"iss_type": "2",
"iss_reason": "5",
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"loc_scope": "0\n1",
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],
"doc": [],
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"config": [
"config.txt",
"config_modification_tutorial.txt"
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} | null |
binary-husky | gpt_academic | 6383113e8527e1c73049e26d2b3482a1b0f54b30 | https://github.com/binary-husky/gpt_academic/issues/376 | 关于public url | 
这个public url 是经过博主自己搭建的服务器的吗？我本地搭建之后在手机打开这个url也能用 | null | null | null | {'base_commit': '6383113e8527e1c73049e26d2b3482a1b0f54b30', 'files': [{'path': 'main.py', 'Loc': {'(None, None, None)': {'mod': [174]}}, 'status': 'modified'}]} | [] | [] | [] | {
"iss_type": "5",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"main.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null | |
binary-husky | gpt_academic | 6c13bb7b46519312222f9afacedaa16225b673a9 | https://github.com/binary-husky/gpt_academic/issues/1545 | ToDo | [Bug]: Qwen1.5-14B-chat 运行不了 | ### Installation Method | 安装方法与平台
OneKeyInstall (一键安装脚本-windows)
### Version | 版本
Latest | 最新版
### OS | 操作系统
Windows
### Describe the bug | 简述
Traceback (most recent call last):
File ".\request_llms\local_llm_class.py", line 158, in run
for response_full in self.llm_stream_generator(**kwargs):
File ".\request_llms\bridge_qwen_local.py", line 46, in llm_stream_generator
for response in self._model.chat_stream(self._tokenizer, query, history=history):
^^^^^^^^^^^^^^^^^^^^^^^
File "D:\anaconda3\envs\GPT_academic371\Lib\site-packages\torch\nn\modules\module.py", line 1688, in __getattr__
raise AttributeError(f"'{type(self).__name__}' object has no attribute '{name}'")
AttributeError: 'Qwen2ForCausalLM' object has no attribute 'chat_stream'
### Screen Shot | 有帮助的截图
Traceback (most recent call last):
File ".\request_llms\local_llm_class.py", line 158, in run
for response_full in self.llm_stream_generator(**kwargs):
File ".\request_llms\bridge_qwen_local.py", line 46, in llm_stream_generator
for response in self._model.chat_stream(self._tokenizer, query, history=history):
^^^^^^^^^^^^^^^^^^^^^^^
File "D:\anaconda3\envs\GPT_academic371\Lib\site-packages\torch\nn\modules\module.py", line 1688, in __getattr__
raise AttributeError(f"'{type(self).__name__}' object has no attribute '{name}'")
AttributeError: 'Qwen2ForCausalLM' object has no attribute 'chat_stream'
### Terminal Traceback & Material to Help Reproduce Bugs | 终端traceback（如有） + 帮助我们复现的测试材料样本（如有）
_No response_ | null | null | null | {'base_commit': '6c13bb7b46519312222f9afacedaa16225b673a9', 'files': [{'path': 'request_llms/bridge_qwen_local.py', 'Loc': {"('GetQwenLMHandle', 'llm_stream_generator', 34)": {'mod': []}}, 'status': 'modified'}]} | [] | [] | [] | {
"iss_type": "1",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"request_llms/bridge_qwen_local.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null |
binary-husky | gpt_academic | dd7a01cda53628ea07ef6192bf257f9ad51f5f47 | https://github.com/binary-husky/gpt_academic/issues/978 | [Bug]: 代理配置成功，代理所在地查询超时，代理可能无效 | ### Installation Method | 安装方法与平台
Docker（Windows/Mac）
### Version | 版本
Latest | 最新版
### OS | 操作系统
Mac
### Describe the bug | 简述
按照要求修改代理配置文件`config.py`，基于`Dockerfile`构建之后运行出现，`代理配置成功，代理所在地查询超时，代理可能无效`的警告⚠️，实际运行报错`ConnectionRefusedError: [Errno 111] Connection refused`，请帮帮我哪里配置可能有误
ps.代理服务地址端口配置正确，且运行正常，可以访问外网
### Screen Shot | 有帮助的截图
<img width="921" alt="截屏2023-07-21 21 12 53" src="https://github.com/binary-husky/gpt_academic/assets/97352201/5f54b0b4-a515-4ae6-8360-1b1504683688">
### Terminal Traceback & Material to Help Reproduce Bugs | 终端traceback（如有） + 帮助我们复现的测试材料样本（如有）
_No response_ | null | null | null | {'base_commit': 'dd7a01cda53628ea07ef6192bf257f9ad51f5f47', 'files': [{'path': 'check_proxy.py', 'Loc': {"(None, 'check_proxy', 2)": {'mod': [6]}}, 'status': 'modified'}]} | [] | [] | [] | {
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"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"check_proxy.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null | |
binary-husky | gpt_academic | ea4e03b1d892d462f71bab76ee0bec65d541f6b7 | https://github.com/binary-husky/gpt_academic/issues/1286 | [Feature]: 请问是否成功修改 api2d-gpt-3.5-turbo-16k 系列模型 max_token 为 16385 | ### Class | 类型
大语言模型
### Feature Request | 功能请求
_No response_ | null | null | null | {'base_commit': 'ea4e03b1d892d462f71bab76ee0bec65d541f6b7', 'files': [{'path': 'request_llms/bridge_all.py', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "3",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"request_llms/bridge_all.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null | |
binary-husky | gpt_academic | 526b4d8ecd1adbdcf97946b3bca4c89feda6ec04 | https://github.com/binary-husky/gpt_academic/issues/850 | cause of issue is clear | [Bug]: Json异常 “error”: | ### Installation Method | 安装方法与平台
Pip Install (I used latest requirements.txt)
### Version | 版本
Latest | 最新版
### OS | 操作系统
Mac
### Describe the bug | 简述
Traceback (most recent call last):
File "./request_llm/bridge_chatgpt.py", line 189, in predict
if ('data: [DONE]' in chunk_decoded) or (len(json.loads(chunk_decoded[6:])['choices'][0]["delta"]) == 0):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/zihengli/anaconda3/envs/gptac_venv/lib/python3.11/json/__init__.py", line 346, in loads
return _default_decoder.decode(s)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/zihengli/anaconda3/envs/gptac_venv/lib/python3.11/json/decoder.py", line 337, in decode
obj, end = self.raw_decode(s, idx=_w(s, 0).end())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/zihengli/anaconda3/envs/gptac_venv/lib/python3.11/json/decoder.py", line 355, in raw_decode
raise JSONDecodeError("Expecting value", s, err.value) from None
json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)
Json异常 “error”: { “message”: “”, “type”: “invalid_request_error”, “param”: null, “code”: “invalid_api_key” }}
### Screen Shot | 有帮助的截图
<img width="1341" alt="image" src="https://github.com/binary-husky/gpt_academic/assets/125801419/c448d538-e762-4bbe-b76a-05d921c34ded">
### Terminal Traceback & Material to Help Reproduce Bugs | 终端traceback（如有） + 帮助我们复现的测试材料样本（如有）
gpt-3.5-turbo : 0 : 1 ..........
Traceback (most recent call last):
File "/Users/zihengli/chatgpt_academic/request_llm/bridge_chatgpt.py", line 189, in predict
if ('data: [DONE]' in chunk_decoded) or (len(json.loads(chunk_decoded[6:])['choices'][0]["delta"]) == 0):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/zihengli/anaconda3/envs/gptac_venv/lib/python3.11/json/__init__.py", line 346, in loads
return _default_decoder.decode(s)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/zihengli/anaconda3/envs/gptac_venv/lib/python3.11/json/decoder.py", line 337, in decode
obj, end = self.raw_decode(s, idx=_w(s, 0).end())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/zihengli/anaconda3/envs/gptac_venv/lib/python3.11/json/decoder.py", line 355, in raw_decode
raise JSONDecodeError("Expecting value", s, err.value) from None
json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)
| null | null | null | {'base_commit': '526b4d8ecd1adbdcf97946b3bca4c89feda6ec04', 'files': [{'path': 'config.py', 'Loc': {'(None, None, None)': {'mod': [1]}}, 'status': 'modified'}, {'path': 'README.md', 'Loc': {'(None, None, 101)': {'mod': [101]}}, 'status': 'modified'}]} | [] | [] | [] | {
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"code": [
"config.py"
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"doc": [
"README.md"
],
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"asset": []
} | null |
binary-husky | gpt_academic | fdffbee1b02bd515ceb4519ae2a830a547b695b4 | https://github.com/binary-husky/gpt_academic/issues/1137 | [Bug]: Connection errored out | ### Installation Method | 安装方法与平台
Pip Install (I used latest requirements.txt)
### Version | 版本
Latest | 最新版
### OS | 操作系统
Linux
### Describe the bug | 简述
你好, 版本3.54
部署在vps上, os是ubuntu 20.04
挂在了公网, 此前均可正常使用
但是突然出现了这样的问题, 如下图
请问这是什么原因呢? 是该vps的ip不行, 被openai ban了么? 还是什么别的原因, 谢谢
### Screen Shot | 有帮助的截图
### Terminal Traceback & Material to Help Reproduce Bugs | 终端traceback（如有） + 帮助我们复现的测试材料样本（如有）
_No response_ | null | null | null | {'base_commit': 'fdffbee1b02bd515ceb4519ae2a830a547b695b4', 'files': [{'path': 'main.py', 'Loc': {"(None, 'main', 3)": {'mod': [287]}}, 'status': 'modified'}]} | [] | [
"nginx.conf"
] | [] | {
"iss_type": "1",
"iss_reason": "3",
"loc_way": "comment",
"loc_scope": "0\n2？",
"info_type": "Config"
} | {
"code": [
"main.py",
"nginx.conf"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null | |
binary-husky | gpt_academic | a2002ebd85f441b3cd563bae28e9966006068ad6 | https://github.com/binary-husky/gpt_academic/issues/462 | ERROR: Invalid requirement: '__pycache__/' (from line 2 of requirements.txt) | **Describe the bug 简述**
ERROR: Invalid requirement: '__pycache__/' (from line 2 of requirements.txt)
**Screen Shot 截图**
**Terminal Traceback 终端traceback（如果有）**
Before submitting an issue 提交issue之前：
- Please try to upgrade your code. 如果您的代码不是最新的，建议您先尝试更新代码
- Please check project wiki for common problem solutions.项目[wiki](https://github.com/binary-husky/chatgpt_academic/wiki)有一些常见问题的解决方法
| null | null | null | {'base_commit': 'a2002ebd85f441b3cd563bae28e9966006068ad6', 'files': [{'path': 'requirements.txt', 'Loc': {}}]} | [] | [] | [] | {
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"iss_reason": "3",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Doc\n依赖声明"
} | {
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"doc": [],
"test": [],
"config": [
"requirements.txt"
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} | null | |
binary-husky | gpt_academic | 0485d01d67d6a41bb0810d6112f40602af1167a9 | https://github.com/binary-husky/gpt_academic/issues/476 | cause of issue is clear | 上传文件时重复上传 |
上传文件时重复上传
样例文件[1.docx](https://github.com/binary-husky/chatgpt_academic/files/11230280/1.docx)
界面
| null | null | null | {'base_commit': '0485d01d67d6a41bb0810d6112f40602af1167a9', 'files': [{'path': 'requirements.txt', 'Loc': {'(None, None, 1)': {'mod': [1]}}, 'status': 'modified'}]} | [] | [] | [] | {
"iss_type": "2",
"iss_reason": "2",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Doc\n依赖声明"
} | {
"code": [],
"doc": [],
"test": [],
"config": [
"requirements.txt"
],
"asset": []
} | null |
binary-husky | gpt_academic | e594e1b928aadb36d291184bca1deee8601621a8 | https://github.com/binary-husky/gpt_academic/issues/1489 | [Bug]: 虽然PDF生成失败了, 但请查收结果（压缩包）, 内含已经翻译的Tex文档, 您可以到Github Issue区, 用该压缩包进行反馈。如系统是Linux，请检查系统字体（见Github wiki） ... | ### Installation Method | 安装方法与平台
Anaconda (I used latest requirements.txt)
### Version | 版本
Latest | 最新版
### OS | 操作系统
Windows
### Describe the bug | 简述
由于最为关键的转化PDF编译失败, 将根据报错信息修正tex源文件并重试, 当前报错的latex代码处于第[-1]行 ...
虽然PDF生成失败了, 但请查收结果（压缩包）, 内含已经翻译的Tex文档, 您可以到Github Issue区, 用该压缩包进行反馈。如系统是Linux，请检查系统字体（见Github wiki） ...
报告已经添加到右侧“文件上传区”（可能处于折叠状态），请查收。
[gpt_log\default_user\shared\2024-01-18-14-25-51-result.zip](http://localhost:50649/file=C:/Users/admin/gpt_academic/gpt_log/default_user/shared/2024-01-18-14-25-51-result.zip)
[gpt_log\default_user\shared\2024-01-18-14-25-41.trans.html](http://localhost:50649/file=C:/Users/admin/gpt_academic/gpt_log/default_user/shared/2024-01-18-14-25-41.trans.html)
### Screen Shot | 有帮助的截图
### Terminal Traceback & Material to Help Reproduce Bugs | 终端traceback（如有） + 帮助我们复现的测试材料样本（如有）
[2024-01-18-14-25-51-result.zip](https://github.com/binary-husky/gpt_academic/files/13973247/2024-01-18-14-25-51-result.zip)
| null | null | null | {} | [
{
"path": ".tex"
}
] | [] | [] | {
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"iss_reason": "3",
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"loc_scope": "3",
"info_type": "Code"
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"test": [],
"config": [],
"asset": [
".tex"
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} | null | |
binary-husky | gpt_academic | 9540cf9448026a1c8135c750866b63d320909718 | https://github.com/binary-husky/gpt_academic/issues/257 | Something went wrong Connection errored out. | ### Describe the bug
启动程序后，能打开页面正常显示，但是上传文档或者发送提问法会出错“Something went wrong Connection errored out.”
### Is there an existing issue for this?
- [ ] I have searched the existing issues
### Reproduction
按照正常步骤：
git clone https://github.com/binary-husky/chatgpt_academic.git
cd chatgpt_academic
python -m pip install -r requirements.txt
python main.py
config.py的配置是：
USE_PROXY = True
### Screenshot
<img width="1400" alt="image" src="https://user-images.githubusercontent.com/66538098/229296702-36166ed4-d077-4ee8-9af3-d263b3039dc5.png">
<img width="1320" alt="image" src="https://user-images.githubusercontent.com/66538098/229327959-e8d3857d-9495-4c28-8a3f-cf1a8d294248.png">
给出了正确的API key，却发现从没使用过
<img width="809" alt="image" src="https://user-images.githubusercontent.com/66538098/229331202-a1850a02-d1f2-4a69-97d1-cb5e285d8e8f.png">
### Logs
```shell
控制台报错[Error] WebSocket connection to 'ws://localhost:62694/queue/join' failed: There was a bad response from the server. (x4)
```
### System Info
```shell
gradio:3.24.1
ProductName:macOS
ProductVersion:13.3
BuildVersion:22E252
```
### Severity
annoying | null | null | null | {} | [] | [] | [
{
"org": "gradio-app",
"pro": "gradio",
"path": [
"gradio/routes.py"
]
}
] | {
"iss_type": "1",
"iss_reason": "1",
"loc_way": "comment",
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} | {
"code": [
"gradio/routes.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null | |
binary-husky | gpt_academic | bfa6661367b7592e82225515e5e4845c4aad95bb | https://github.com/binary-husky/gpt_academic/issues/252 | 能不能使用azure openai key? | 代理服务器不够稳定，更麻烦的是给openai续费，还要个美国信用卡
非常好的应用，希望出更多的插件功能，谢谢 | null | null | null | {'base_commit': 'bfa6661367b7592e82225515e5e4845c4aad95bb', 'files': [{'path': 'config.py', 'Loc': {}}]} | [] | [] | [] | {
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"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"config.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null | |
binary-husky | gpt_academic | 2d2e02040d7d91d2f2a4c34f4d0bf677873b5f4d | https://github.com/binary-husky/gpt_academic/issues/1328 | [Bug]: 精准翻译PDF文档(NOUGAT)功能出错， | ### Installation Method | 安装方法与平台
Others (Please Describe)
### Version | 版本
Please choose | 请选择
### OS | 操作系统
Please choose | 请选择
### Describe the bug | 简述
测试服务器，精准翻译PDF文档(NOUGAT)功能出错，但是可以使用精准翻译PDF的功能
报错信息如下
### Screen Shot | 有帮助的截图
Traceback (most recent call last):
File "./toolbox.py", line 159, in decorated
yield from f(main_input, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, *args, **kwargs)
File "./crazy_functions/批量翻译PDF文档_NOUGAT.py", line 93, in 批量翻译PDF文档
yield from 解析PDF_基于NOUGAT(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
File "./crazy_functions/批量翻译PDF文档_NOUGAT.py", line 111, in 解析PDF_基于NOUGAT
fpp = yield from nougat_handle.NOUGAT_parse_pdf(fp, chatbot, history)
File "./crazy_functions/crazy_utils.py", line 761, in NOUGAT_parse_pdf
raise RuntimeError("Nougat解析论文失败。")
RuntimeError: Nougat解析论文失败。
### Terminal Traceback & Material to Help Reproduce Bugs | 终端traceback（如有） + 帮助我们复现的测试材料样本（如有）
_No response_ | null | null | null | {'base_commit': '2d2e02040d7d91d2f2a4c34f4d0bf677873b5f4d', 'files': [{'path': 'crazy_functions/crazy_utils.py', 'Loc': {"('nougat_interface', 'NOUGAT_parse_pdf', 739)": {'mod': [752]}, "('nougat_interface', None, 719)": {'mod': [723]}}, 'status': 'modified'}]} | [] | [] | [] | {
"iss_type": "1",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
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],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null | |
binary-husky | gpt_academic | 17abd29d5035b5b227deaad69d32cf437b23e542 | https://github.com/binary-husky/gpt_academic/issues/94 | [一些建议]input框还是太小了 | RT 多行输入还是不方便，如果适当调整会更好用。
希望采纳，感谢分享。 | null | null | null | {'base_commit': '17abd29d5035b5b227deaad69d32cf437b23e542', 'files': [{'path': 'main.py', 'Loc': {'(None, None, None)': {'mod': [1]}}, 'status': 'modified'}]} | [] | [] | [] | {
"iss_type": "4",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"main.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null | |
binary-husky | gpt_academic | 37744a9cb173477398a2609f02d5e7cef47eb677 | https://github.com/binary-husky/gpt_academic/issues/1438 | [Bug]: 浮动输入框在拖至顶部后，无法重新移位 | ### Installation Method | 安装方法与平台
Others (Please Describe)
### Version | 版本
Please choose | 请选择
### OS | 操作系统
Mac
### Describe the bug | 简述
浮动输入框在拖至顶部后，无法重新移位
期望：重新勾选后，应该回到初始位置
### Screen Shot | 有帮助的截图
### Terminal Traceback & Material to Help Reproduce Bugs | 终端traceback（如有） + 帮助我们复现的测试材料样本（如有）
_No response_ | null | null | https://github.com/binary-husky/gradio-fix/commit/fb67dd12f58aa53c75a90378cddbc811ac3c01d2 | {} | [] | [] | [
{
"org": "binary-husky",
"pro": "gradio-fix",
"path": [
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]
}
] | {
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"loc_way": "commit",
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"info_type": "Code"
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"asset": [
"gradio-fix",
"js/app/src/components/Floating/StaticFloating.svelte"
]
} | null | |
binary-husky | gpt_academic | 6538c58b8e5a4a7ae08dfa1ae9970bc422158096 | https://github.com/binary-husky/gpt_academic/issues/620 | 想问问newbing的cookies怎么填写，我从javascript:alert(document.cookie)找到了cookies但是一直显示cookies有错 | 
| null | null | null | {'base_commit': '6538c58b8e5a4a7ae08dfa1ae9970bc422158096', 'files': [{'path': 'config.py', 'Loc': {'(None, None, None)': {'mod': [69]}}, 'status': 'modified'}]} | [] | [] | [] | {
"iss_type": "1",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "",
"info_type": "Other"
} | {
"code": [
"config.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null | |
binary-husky | gpt_academic | 6d8c8cd3f0b9d2b6fe8d412b83f902cbd43fa0bd | https://github.com/binary-husky/gpt_academic/issues/150 | documentation
high value issue | 有没有完全部署成功的大神出个详细的部署步骤呀？Windows 有截图，跪求 | Windows安装部署
基本环：安装anaconda
1.下载项目 CMD
选择路径
git clone https://github.com/binary-husky/chatgpt_academic.git
cd chatgpt_academic
我们建议将config.py复制为config_private.py并将后者用作个性化配置文件以避免config.py中的变更影响你的使用或不小心将包含你的OpenAI API KEY的config.py提交至本项目。
cp config.py config_private.py
2.创建虚拟环境 python 3.11
conda create -n chatgpt python=3.11.0 #新建环境、
3.进入项目下载路径
例如 cd G:\python\Program\chatgpt_academic
4.启动虚拟环境
conda activate chatgpt
5. 安装 gradio>=3.23
（1）到https://pypi.org/project/gradio/ 下载whl版本
（2）pip install G:\python\Program\chatgpt_academic\gradio-3.23.0-py3-none-any.whl
6.配置其他环境
（1）打开requirements.txt，注释掉gradio，然后保存
（2）运行 python -m pip install -r requirements.txt
7.启动代理
8. 配置config_private.py
（1）添加API_KEY
（2）修改USE_PROXY = Ture
（3）修改proxies
在浏览器输入: https://ipapi.co/json/
浏览器上右键->检查->网络->ctrl+r
打开json，将远程地址修改到proxies = { "http": "104.26.9.44:443", "https": "104.26.9.44:443", }
9.启动程序
python main.py | null | null | null | {'base_commit': '6d8c8cd3f0b9d2b6fe8d412b83f902cbd43fa0bd', 'files': [{'path': 'requirements.txt', 'Loc': {}}]} | [] | [] | [] | {
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"doc": [],
"test": [],
"config": [
"requirements.txt"
],
"asset": []
} | null |
binary-husky | gpt_academic | e20070939c6c7eeca33a8438041c9e038836957b | https://github.com/binary-husky/gpt_academic/issues/568 | enhancement | 能否增加聊天内容导出功能？ | null | null | null | null | {} | [] | [
"gpt_log/chat_secrets.log"
] | [] | {
"iss_type": "4",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "1",
"info_type": "Config"
} | {
"code": [],
"doc": [],
"test": [],
"config": [],
"asset": [
"gpt_log/chat_secrets.log"
]
} | null |
binary-husky | gpt_academic | 6c448b9a601ba4b9cc84e8bc625a3a91b1982ba4 | https://github.com/binary-husky/gpt_academic/issues/756 | [Bug]: | ### Installation Method | 安装方法与平台
Pip Install (I used latest requirements.txt and python>=3.8)
### Describe the bug | 简述
只有出去的消息，没有返回消息，试过了ap2id和newbing
### Screen Shot | 有帮助的截图
### Terminal Traceback & Material to Help Reproduce Bugs | 终端traceback（如有） + 帮助我们复现的测试材料样本（如有）
_No response_ | null | null | null | {'base_commit': '6c448b9a601ba4b9cc84e8bc625a3a91b1982ba4', 'files': [{'path': 'request_llms/requirements_newbing.txt', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "2",
"iss_reason": "3",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "依赖"
} | {
"code": [],
"doc": [],
"test": [],
"config": [
"request_llms/requirements_newbing.txt"
],
"asset": []
} | null | |
deepseek-ai | DeepSeek-V3 | 6a30b43249a5710a3adb18c11763222d3fca8756 | https://github.com/deepseek-ai/DeepSeek-V3/issues/566 | Please provide the code for your model architecture. | **Is your feature request related to a problem? Please describe.**
This repo only provides weights. It makes it difficult to confirm claims from the article.
**Describe the solution you'd like**
A repo where the code to the model architecture is provided.
**Describe alternatives you've considered**
Clearly state that the model is not open source.
**Additional context**
None
| null | null | null | {'base_commit': '6a30b43249a5710a3adb18c11763222d3fca8756', 'files': [{'path': 'inference/model.py', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "5",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"inference/model.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null | |
deepseek-ai | DeepSeek-V3 | 0d16ea24c8030a30d4fe8a75b28e05b03b4e0970 | https://github.com/deepseek-ai/DeepSeek-V3/issues/210 | [BUG]convert后运行错误 | **Describe the bug**
[rank0]: ValueError: Unrecognized model in ../DV3-hf-32/. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: albert, align, altclip, audio-spectrogram-transformer, autoformer, bark, bart, beit, bert, bert-generation, big_bird, bigbird_pegasus, biogpt, bit, blenderbot, blenderbot-small, blip, blip-2, bloom, bridgetower, bros, camembert, canine, chameleon, chinese_clip, chinese_clip_vision_model, clap, clip, clip_text_model, clip_vision_model, clipseg, clvp, code_llama, codegen, cohere, conditional_detr, convbert, convnext, convnextv2, cpmant, ctrl, cvt, dac, data2vec-audio, data2vec-text, data2vec-vision, dbrx, deberta, deberta-v2, decision_transformer, deformable_detr, deit, depth_anything, deta, detr, dinat, dinov2, distilbert, donut-swin, dpr, dpt, efficientformer, efficientnet, electra, encodec, encoder-decoder, ernie, ernie_m, esm, falcon, falcon_mamba, fastspeech2_conformer, flaubert, flava, fnet, focalnet, fsmt, funnel, fuyu, gemma, gemma2, git, glm, glpn, gpt-sw3, gpt2, gpt_bigcode, gpt_neo, gpt_neox, gpt_neox_japanese, gptj, gptsan-japanese, granite, granitemoe, graphormer, grounding-dino, groupvit, hiera, hubert, ibert, idefics, idefics2, idefics3, imagegpt, informer, instructblip, instructblipvideo, jamba, jetmoe, jukebox, kosmos-2, layoutlm, layoutlmv2, layoutlmv3, led, levit, lilt, llama, llava, llava_next, llava_next_video, llava_onevision, longformer, longt5, luke, lxmert, m2m_100, mamba, mamba2, marian, markuplm, mask2former, maskformer, maskformer-swin, mbart, mctct, mega, megatron-bert, mgp-str, mimi, mistral, mixtral, mllama, mobilebert, mobilenet_v1, mobilenet_v2, mobilevit, mobilevitv2, moshi, mpnet, mpt, mra, mt5, musicgen, musicgen_melody, mvp, nat, nemotron, nezha, nllb-moe, nougat, nystromformer, olmo, olmoe, omdet-turbo, oneformer, open-llama, openai-gpt, opt, owlv2, owlvit, paligemma, patchtsmixer, patchtst, pegasus, pegasus_x, perceiver, persimmon, phi, phi3, phimoe, pix2struct, pixtral, plbart, poolformer, pop2piano, prophetnet, pvt, pvt_v2, qdqbert, qwen2, qwen2_audio, qwen2_audio_encoder, qwen2_moe, qwen2_vl, rag, realm, recurrent_gemma, reformer, regnet, rembert, resnet, retribert, roberta, roberta-prelayernorm, roc_bert, roformer, rt_detr, rt_detr_resnet, rwkv, sam, seamless_m4t, seamless_m4t_v2, segformer, seggpt, sew, sew-d, siglip, siglip_vision_model, speech-encoder-decoder, speech_to_text, speech_to_text_2, speecht5, splinter, squeezebert, stablelm, starcoder2, superpoint, swiftformer, swin, swin2sr, swinv2, switch_transformers, t5, table-transformer, tapas, time_series_transformer, timesformer, timm_backbone, trajectory_transformer, transfo-xl, trocr, tvlt, tvp, udop, umt5, unispeech, unispeech-sat, univnet, upernet, van, video_llava, videomae, vilt, vipllava, vision-encoder-decoder, vision-text-dual-encoder, visual_bert, vit, vit_hybrid, vit_mae, vit_msn, vitdet, vitmatte, vits, vivit, wav2vec2, wav2vec2-bert, wav2vec2-conformer, wavlm, whisper, xclip, xglm, xlm, xlm-prophetnet, xlm-roberta, xlm-roberta-xl, xlnet, xmod, yolos, yoso, zamba, zoedepth
**To Reproduce**
Steps to reproduce the behavior.
**Expected behavior**
A clear and concise description of what you expected to happen.
**Screenshots**
If applicable, add screenshots to help explain your problem.
**Additional context**
Add any other context about the problem here.
| null | null | null | {} | [] | [
"tokenizer.json",
"tokenizer_config.json"
] | [] | {
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"code": [
"tokenizer_config.json",
"tokenizer.json"
],
"doc": [],
"test": [],
"config": [],
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} | null | |
deepfakes | faceswap | c529bd4f1cb3a8abc53574b7211fc0b887107073 | https://github.com/deepfakes/faceswap/issues/98 | wontfix | IndexError: list index out of range on training | ```
# python3.6 faceswap.py train -A ~/faceswap/data/trump -B ~/faceswap/data/stalone -m ~/faceswap/models/
Model A Directory: /root/faceswap/data/trump
Model B Directory: /root/faceswap/data/stalone
Training data directory: /root/faceswap/models
Loading data, this may take a while...
Loading Model from Model_Original plugin...
/usr/local/lib/python3.6/dist-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
from ._conv import register_converters as _register_converters
Using TensorFlow backend.
/usr/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.6
return f(*args, **kwds)
Failed loading existing training data.
Unable to open file (unable to open file: name = '/root/faceswap/models/encoder.h5', errno = 2, error message = 'No such file or directory', flags = 0, o_flags = 0)
Loading Trainer from Model_Original plugin...
Starting. Press "Enter" to stop training and save model
Exception in thread Thread-2:
Traceback (most recent call last):
File "/usr/lib/python3.6/threading.py", line 916, in _bootstrap_inner
self.run()
File "/root/faceswap/lib/utils.py", line 42, in run
for item in self.generator:
File "/root/faceswap/lib/training_data.py", line 43, in minibatch
rtn = numpy.float32([read_image(data[j]) for j in range(i,i+size)])
File "/root/faceswap/lib/training_data.py", line 43, in <listcomp>
rtn = numpy.float32([read_image(data[j]) for j in range(i,i+size)])
IndexError: list index out of range
```
## Expected behavior
There shouldn't be "IndexError: list index out of range"
## Actual behavior
*Describe, in some detail, what the program does instead. Be sure to include any error message or screenshots.*
## Steps to reproduce
## Other relevant information
H/W: 4 cores, 16GB, Nvidial P100
S/W: Ubuntu 16.04, NVIDIA binary driver - version 384.111
CUDA 8.0
CuDNN 6
Python 3.6
faceswap commit: 0f8d9db826d7588f9feb151ab234f2aaf0d8ecf2
| null | null | null | {'base_commit': 'c529bd4f1cb3a8abc53574b7211fc0b887107073', 'files': [{'path': 'lib/training_data.py', 'Loc': {"(None, 'minibatch', 33)": {'mod': [38]}}, 'status': 'modified'}, {'path': 'lib/cli/args_train.py', 'Loc': {"('TrainArgs', 'get_argument_list', 35)": {'mod': [140]}}, 'status': 'modified'}]} | [] | [] | [] | {
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"lib/training_data.py"
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} | null |
deepfakes | faceswap | 183aee37e93708c0ae73845face5b4469319ebd3 | https://github.com/deepfakes/faceswap/issues/1208 | [Question] Which part of code to implement 'Configure Settings' GUI? | Which part of code to implement 'Configure Settings' GUI?
| null | null | null | {'base_commit': '183aee37e93708c0ae73845face5b4469319ebd3', 'files': [{'path': 'lib/gui/popup_configure.py', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "5",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"lib/gui/popup_configure.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null | |
deepfakes | faceswap | 3ba44f75518e8010befab88042247e5147d0f212 | https://github.com/deepfakes/faceswap/issues/15 | question
data | do i have to rename the given training data to src? | if not, where to put the unzip data into directory. sorry for asking newby questions.
i am using pycharm and docker. thanks
| null | null | null | {'base_commit': '3ba44f75518e8010befab88042247e5147d0f212', 'files': [{'path': 'convert_trump_cage.py', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "5",
"iss_reason": "5",
"loc_way": "comment",
"loc_scope": "0",
"info_type": "Code"
} | {
"code": [
"convert_trump_cage.py"
],
"doc": [],
"test": [],
"config": [],
"asset": []
} | null |
deepfakes | faceswap | 68ef3b992674d87d0c73da9c29a4c5a0e735f04b | https://github.com/deepfakes/faceswap/issues/101 | help me | virtualenv '/home/test/Desktop/faceswap-master'
python3.5 '/home/test/Desktop/faceswap-master/faceswap.py' -h
test@ubuntu:~$ virtualenv '/home/test/Desktop/faceswap-master'
New python executable in /home/test/Desktop/faceswap-master/bin/python
Installing setuptools, pip, wheel...done.
test@ubuntu:~$ python3.5 '/home/test/Desktop/faceswap-master/faceswap.py' -h
Traceback (most recent call last):
File "/home/test/Desktop/faceswap-master/faceswap.py", line 8, in <module>
from lib.utils import FullHelpArgumentParser
File "/home/test/Desktop/faceswap-master/lib/utils.py", line 5, in <module>
from scandir import scandir
ImportError: No module named 'scandir'
test@ubuntu:~$
| null | null | null | {'base_commit': '68ef3b992674d87d0c73da9c29a4c5a0e735f04b', 'files': [{'path': 'requirements-gpu.txt', 'Loc': {}}]} | [] | [] | [] | {
"iss_type": "1",
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"loc_way": "comment",
"loc_scope": "0",
"info_type": "Doc\n依赖声明"
} | {
"code": [],
"doc": [],
"test": [],
"config": [
"requirements-gpu.txt"
],
"asset": []
} | null |
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