repo_name stringlengths 9 75 | topic stringclasses 30
values | issue_number int64 1 203k | title stringlengths 1 976 | body stringlengths 0 254k | state stringclasses 2
values | created_at stringlengths 20 20 | updated_at stringlengths 20 20 | url stringlengths 38 105 | labels listlengths 0 9 | user_login stringlengths 1 39 | comments_count int64 0 452 |
|---|---|---|---|---|---|---|---|---|---|---|---|
slackapi/python-slack-sdk | asyncio | 1,313 | Add support for admin_roles_{addAssignments|listAssignments|removeAssignments} methods | Not sure if this is a bug or not. Slack API documentation lists methods with the admin_roles prefix that contain some pretty important functions that I need to be able to do via Python:
https://api.slack.com/methods/admin.roles.addAssignments
https://api.slack.com/methods/admin.roles.listAssignments
https://api.slack.com/methods/admin.roles.removeAssignments
However, looking at the slack-sdk code, I don't see any references to these methods even though the API documentation says they exist. Do they have yet to be implemented? | closed | 2022-12-14T18:45:25Z | 2023-04-07T04:16:16Z | https://github.com/slackapi/python-slack-sdk/issues/1313 | [
"enhancement",
"web-client",
"Version: 3x"
] | csallen1204 | 5 |
n0kovo/fb_friend_list_scraper | web-scraping | 6 | won't load with pyopenssl update, force install old version and it works? | First, forgive the lack of correct terminology - I'm a journalist and barely know my way around this stuff.
Running after install gave an error:
AttributeError: module 'OpenSSL.SSL' has no attribute 'SSLv2_METHOD'
Turns out pyopenssl 22.1.0 has Backward-incompatible changes: Remove support for SSLv2 and SSLv3
forced install of 22.0.0 and now it works!
| closed | 2022-12-09T12:49:38Z | 2023-07-28T06:00:14Z | https://github.com/n0kovo/fb_friend_list_scraper/issues/6 | [] | smarmitako | 3 |
microsoft/nni | data-science | 5,742 | Pruning Yolov8m model | **Describe the issue**:
**Environment**:
- NNI version:
- Training service (local|remote|pai|aml|etc):
- Client OS:
- Server OS (for remote mode only):
- Python version:
- PyTorch/TensorFlow version:
- Is conda/virtualenv/venv used?:
- Is running in Docker?:
**Configuration**:
- Experiment config (remember to remove secrets!):
- Search space:
**Log message**:
- nnimanager.log:
- dispatcher.log:
- nnictl stdout and stderr:
<!--
Where can you find the log files:
LOG: https://github.com/microsoft/nni/blob/master/docs/en_US/Tutorial/HowToDebug.md#experiment-root-director
STDOUT/STDERR: https://nni.readthedocs.io/en/stable/reference/nnictl.html#nnictl-log-stdout
-->
**How to reproduce it?**:
```
import torch
from nni.common.concrete_trace_utils import concrete_trace
from nni.compression.pruning import L1NormPruner
from nni.compression.utils import auto_set_denpendency_group_ids
from nni.compression.speedup import ModelSpeedup
from ultralytics import YOLO
model = YOLO("/content/yolov8n.pt")
model(torch.rand([1, 3, 640, 640]))
config_list = [{
'sparsity': 0.5,
'op_types': ['Conv2d'],
'exclude_op_names_re': ['model.model.model.24.*'], # this layer is detector head
}]
config_list = auto_set_denpendency_group_ids(model, config_list, torch.rand([1, 3, 640, 640]))
pruner = L1NormPruner(model, config_list)
masked_model, masks = pruner.compress()
pruner.unwrap_model()
graph_module = concrete_trace(model, (torch.rand([1, 3, 640, 640]), None, None, None))
ModelSpeedup(model, torch.rand([1, 3, 640, 640]), masks, graph_module=graph_module).speedup_model()
model(torch.rand([1, 3, 640, 640])
```
i tried to prune yolov8m model using the same code which is used to prune yolov5s model. But it is retraining in "config_list = auto_set_denpendency_group_ids(model, config_list, torch.rand([1, 3, 640, 640]))" this step and giving error like
```
/usr/local/lib/python3.10/dist-packages/ultralytics/data/loaders.py:456: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
if im.shape[2] % stride or im.shape[3] % stride:
/usr/local/lib/python3.10/dist-packages/ultralytics/data/loaders.py:458: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
if im.max() > 1.0 + torch.finfo(im.dtype).eps: # torch.float32 eps is 1.2e-07
/usr/local/lib/python3.10/dist-packages/ultralytics/data/loaders.py:442: TracerWarning: Iterating over a tensor might cause the trace to be incorrect. Passing a tensor of different shape won't change the number of iterations executed (and might lead to errors or silently give incorrect results).
self.paths = [getattr(im, "filename", f"image{i}.jpg") for i, im in enumerate(im0)]
/usr/local/lib/python3.10/dist-packages/ultralytics/nn/modules/head.py:53: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
if self.dynamic or self.shape != shape:
/usr/local/lib/python3.10/dist-packages/ultralytics/utils/ops.py:408: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
assert x.shape[-1] == 4, f"input shape last dimension expected 4 but input shape is {x.shape}"
/usr/local/lib/python3.10/dist-packages/ultralytics/utils/ops.py:231: TracerWarning: Iterating over a tensor might cause the trace to be incorrect. Passing a tensor of different shape won't change the number of iterations executed (and might lead to errors or silently give incorrect results).
for xi, x in enumerate(prediction): # image index, image inference
/usr/local/lib/python3.10/dist-packages/ultralytics/utils/ops.py:245: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
if not x.shape[0]:
/usr/local/lib/python3.10/dist-packages/ultralytics/utils/ops.py:829: TracerWarning: Converting a tensor to a NumPy array might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
return (batch.permute(0, 2, 3, 1).contiguous() * 255).clamp(0, 255).to(torch.uint8).cpu().numpy()
/usr/local/lib/python3.10/dist-packages/ultralytics/utils/ops.py:108: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
gain = min(img1_shape[0] / img0_shape[0], img1_shape[1] / img0_shape[1]) # gain = old / new
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
[<ipython-input-8-a46380595ef0>](https://localhost:8080/#) in <cell line: 20>()
18 }]
19
---> 20 config_list = auto_set_denpendency_group_ids(model, config_list, torch.rand([1, 3, 640, 640]))
21
22 pruner = L1NormPruner(model, config_list)
14 frames
[/usr/local/lib/python3.10/dist-packages/ultralytics/utils/ops.py](https://localhost:8080/#) in scale_boxes(img1_shape, boxes, img0_shape, ratio_pad, padding, xywh)
108 gain = min(img1_shape[0] / img0_shape[0], img1_shape[1] / img0_shape[1]) # gain = old / new
109 pad = (
--> 110 round((img1_shape[1] - img0_shape[1] * gain) / 2 - 0.1),
111 round((img1_shape[0] - img0_shape[0] * gain) / 2 - 0.1),
112 ) # wh padding
TypeError: type Tensor doesn't define __round__ method
``` | open | 2024-02-09T16:28:22Z | 2024-02-22T01:17:23Z | https://github.com/microsoft/nni/issues/5742 | [] | hafeelnm19 | 1 |
stanfordnlp/stanza | nlp | 989 | argument tensor problem (dev branch) | This is a known problem with pytorch (I guess).
I got this while working with several text files in different directory (different languages). It occurs just with some directories, usually after having processed the first file, then my script just passes to another directory. I suspect there is something with the models, maybe some 'exotic' processors like NER or constituency. So far, problematic languages are da, en, it with their default models...
```
Traceback (most recent call last):
File "/home/ec2-user/tools/process/ud-stanza.py", line 236, in <module>
main()
File "/home/ec2-user/tools/process/ud-stanza.py", line 231, in main
udparser(nlp,text,filename)
File "/home/ec2-user/tools/process/ud-stanza.py", line 173, in udparser
doc = nlp(text)
File "/home/ec2-user/.local/lib/python3.9/site-packages/stanza/pipeline/core.py", line 386, in __call__
return self.process(doc, processors)
File "/home/ec2-user/.local/lib/python3.9/site-packages/stanza/pipeline/core.py", line 382, in process
doc = process(doc)
File "/home/ec2-user/.local/lib/python3.9/site-packages/stanza/pipeline/constituency_processor.py", line 66, in process
trees = trainer.parse_tagged_words(self._model.model, words, self._batch_size)
File "/home/ec2-user/.local/lib/python3.9/site-packages/stanza/models/constituency/trainer.py", line 717, in parse_tagged_wor
ds
treebank = parse_sentences(sentence_iterator, build_batch_from_tagged_words, batch_size, model)
File "/opt/conda/envs/pytorch/lib/python3.9/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "/home/ec2-user/.local/lib/python3.9/site-packages/stanza/models/constituency/trainer.py", line 692, in parse_sentences
horizon_batch = build_batch_fn(batch_size, data_iterator, model)
File "/home/ec2-user/.local/lib/python3.9/site-packages/stanza/models/constituency/trainer.py", line 637, in build_batch_from
_tagged_words
tree_batch = parse_transitions.initial_state_from_words(tree_batch, model)
File "/home/ec2-user/.local/lib/python3.9/site-packages/stanza/models/constituency/parse_transitions.py", line 130, in initia
l_state_from_words
return initial_state_from_preterminals(preterminal_lists, model, gold_trees=None)
File "/home/ec2-user/.local/lib/python3.9/site-packages/stanza/models/constituency/parse_transitions.py", line 110, in initia
l_state_from_preterminals
word_queues = model.initial_word_queues(preterminal_lists)
File "/home/ec2-user/.local/lib/python3.9/site-packages/stanza/models/constituency/lstm_model.py", line 648, in initial_word_
queues
partitioned_embeddings = self.partitioned_transformer_module(None, all_word_inputs)
File "/opt/conda/envs/pytorch/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/home/ec2-user/.local/lib/python3.9/site-packages/stanza/models/constituency/partitioned_transformer.py", line 302, in
forward
encoder_in = self.add_timing(self.pattention_morpho_emb_dropout(extra_content_annotations))
File "/opt/conda/envs/pytorch/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/home/ec2-user/.local/lib/python3.9/site-packages/stanza/models/constituency/positional_encoding.py", line 48, in forward
out = torch.cat([x, timing], dim=-1)
RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! (when checking argument for argument tensors in method wrapper___cat)
```
I am on a AWS EC2 machine with a Tesla n60: Deep Learning AMI GPU PyTorch 1.11.0 (Amazon Linux 2) , Python 3 .9.4
| closed | 2022-04-04T15:03:23Z | 2022-10-11T07:07:44Z | https://github.com/stanfordnlp/stanza/issues/989 | [
"bug",
"fixed on dev"
] | rahonalab | 8 |
yihong0618/running_page | data-visualization | 81 | Garmin: Something went wrong when loading GPX. | 请问有没有哪位在运行garmin_sync.py时，出现“Something went wrong when loading GPX. for file 6171184463.gpx”这种错误的情况？因为人在国外，用的是“python3(python) scripts/garmin_sync.py ${your email} ${your password}”这个命令。目前卡在这一步，希望有人能帮忙解答。谢谢！
| closed | 2021-01-27T00:03:29Z | 2021-01-27T13:04:19Z | https://github.com/yihong0618/running_page/issues/81 | [
"enhancement"
] | wh1994 | 9 |
slackapi/python-slack-sdk | asyncio | 874 | Getting JSONDecodeError for actions when using slackeventsapi | (Filling out the following details about bugs will help us solve your issue sooner.)
### Reproducible in:
#### The Slack SDK version
slack-sdk -- 3.0.0rc3
Output of `pip freeze | grep slack`
slack-sdk==3.0.0rc3
slackeventsapi==2.2.1
#### Python runtime version
Python 3.7.6
#### OS info
Ubuntu 18.04.5 LTS
#### Steps to reproduce:
Working on the tutorial code provided in the repo. The app works fine for simple text messages. Tried to add a button element to the app responses and getting the JSONDecodeError.
Here's the JSON for the button :
```
Actions = {
"type": "actions",
"block_id": "actions1",
"elements": [
{
"type": "button",
"text": {
"type": "plain_text",
"text": "Okay"
},
"value": "got this",
"action_id": "button_1"
}
]
}
```
When I click on the button, I get the JSONDecode error at the app
### Expected result:
I expected the buttons payload to reach the app, which I can further use to implement the business logic.
### Actual result:
```
127.0.0.1 - - [10/Nov/2020 05:57:01] "POST /slack/events HTTP/1.1" 500 -
Traceback (most recent call last):
File "/home/bottest1/anaconda3/envs/slack/lib/python3.7/json/decoder.py", line 353, in raw_decode
obj, end = self.scan_once(s, idx)
StopIteration: 0
```
During handling of the above exception, another exception occurred:
```
Traceback (most recent call last):
File "/home/bottest1/anaconda3/envs/slack/lib/python3.7/site-packages/flask/app.py", line 2464, in __call__
return self.wsgi_app(environ, start_response)
File "/home/bottest1/anaconda3/envs/slack/lib/python3.7/site-packages/flask/app.py", line 2450, in wsgi_app
response = self.handle_exception(e)
File "/home/bottest1/anaconda3/envs/slack/lib/python3.7/site-packages/flask/app.py", line 1867, in handle_exception
reraise(exc_type, exc_value, tb)
File "/home/bottest1/anaconda3/envs/slack/lib/python3.7/site-packages/flask/_compat.py", line 39, in reraise
raise value
File "/home/bottest1/anaconda3/envs/slack/lib/python3.7/site-packages/flask/app.py", line 2447, in wsgi_app
response = self.full_dispatch_request()
File "/home/bottest1/anaconda3/envs/slack/lib/python3.7/site-packages/flask/app.py", line 1952, in full_dispatch_request
rv = self.handle_user_exception(e)
File "/home/bottest1/anaconda3/envs/slack/lib/python3.7/site-packages/flask/app.py", line 1821, in handle_user_exception
reraise(exc_type, exc_value, tb)
File "/home/bottest1/anaconda3/envs/slack/lib/python3.7/site-packages/flask/_compat.py", line 39, in reraise
raise value
File "/home/bottest1/anaconda3/envs/slack/lib/python3.7/site-packages/flask/app.py", line 1950, in full_dispatch_request
rv = self.dispatch_request()
File "/home/bottest1/anaconda3/envs/slack/lib/python3.7/site-packages/flask/app.py", line 1936, in dispatch_request
return self.view_functions[rule.endpoint](**req.view_args)
File "/home/bottest1/anaconda3/envs/slack/lib/python3.7/site-packages/slackeventsapi/server.py", line 106, in event
event_data = json.loads(request.data.decode('utf-8'))
File "/home/bottest1/anaconda3/envs/slack/lib/python3.7/json/__init__.py", line 348, in loads
return _default_decoder.decode(s)
File "/home/bottest1/anaconda3/envs/slack/lib/python3.7/json/decoder.py", line 337, in decode
obj, end = self.raw_decode(s, idx=_w(s, 0).end())
File "/home/bottest1/anaconda3/envs/slack/lib/python3.7/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)
``` | closed | 2020-11-10T06:12:11Z | 2020-11-24T11:02:10Z | https://github.com/slackapi/python-slack-sdk/issues/874 | [
"question",
"Version: 3x"
] | Harish099 | 2 |
lanpa/tensorboardX | numpy | 681 | How can i read tensorboard by python ? | hi,
i find event_accumulator.EventAccumulator() can help me read a tensorboard, and i know how to read scalar, but how can i read Tensors/text ? i use writer.add_text('A',B) in my pytorch code, and i want to read A and B only by python, because tensoard is very slow to load my item. And i find A/B are in Tensors.
i think it is a easy thing, but i do not know how to do it.
Thanks! | open | 2023-01-10T10:50:21Z | 2023-02-20T10:26:45Z | https://github.com/lanpa/tensorboardX/issues/681 | [] | Mr-bor | 2 |
wger-project/wger | django | 1,928 | err 500 - possible migration failure? | ## Steps to Reproduce
<!-- Please include as many steps to reproduce so that we can replicate the problem. -->
Navigate on self-hosted wger page
**Expected results:** <!-- what did you expect to see? -->
HTTP 200
**Actual results:** <!-- what did you see? -->
HTTP 500
<details>
<summary>Logs</summary>
Can't see anything in wger logs, but seeing this in postgres logs:
```
2025-03-21 03:57:43.239 CET [709] ERROR: relation "exercises_translation" does not exist at character 108
2025-03-21 03:57:43.239 CET [709] STATEMENT: SELECT COUNT(*) FROM (SELECT "exercises_exercise"."id" AS "col1" FROM "exercises_exercise" LEFT OUTER JOIN "exercises_translation" ON ("exercises_exercise"."id" = "exercises_translation"."exercise_id") GROUP BY 1 HAVING COUNT("exercises_translation"."id") = 0) subquery
2025-03-21 03:57:45.177 CET [710] ERROR: relation "exercises_translation" does not exist at character 108
2025-03-21 03:57:45.177 CET [710] STATEMENT: SELECT COUNT(*) FROM (SELECT "exercises_exercise"."id" AS "col1" FROM "exercises_exercise" LEFT OUTER JOIN "exercises_translation" ON ("exercises_exercise"."id" = "exercises_translation"."exercise_id") GROUP BY 1 HAVING COUNT("exercises_translation"."id") = 0) subquery
2025-03-21 03:59:55.954 CET [26] LOG: checkpoint starting: time
2025-03-21 03:59:56.187 CET [26] LOG: checkpoint complete: wrote 3 buffers (0.0%); 0 WAL file(s) added, 0 removed, 0 recycled; write=0.205 s, sync=0.008 s, total=0.234 s; sync files=3, longest=0.004 s, average=0.003 s; distance=0 kB, estimate=18 kB
2025-03-22 03:58:16.516 CET [6473] ERROR: relation "exercises_translation" does not exist at character 108
2025-03-22 03:58:16.516 CET [6473] STATEMENT: SELECT COUNT(*) FROM (SELECT "exercises_exercise"."id" AS "col1" FROM "exercises_exercise" LEFT OUTER JOIN "exercises_translation" ON ("exercises_exercise"."id" = "exercises_translation"."exercise_id") GROUP BY 1 HAVING COUNT("exercises_translation"."id") = 0) subquery
2025-03-22 03:58:18.482 CET [6474] ERROR: relation "exercises_translation" does not exist at character 108
2025-03-22 03:58:18.482 CET [6474] STATEMENT: SELECT COUNT(*) FROM (SELECT "exercises_exercise"."id" AS "col1" FROM "exercises_exercise" LEFT OUTER JOIN "exercises_translation" ON ("exercises_exercise"."id" = "exercises_translation"."exercise_id") GROUP BY 1 HAVING COUNT("exercises_translation"."id") = 0) subquery
2025-03-22 04:00:18.493 CET [26] LOG: checkpoint starting: time
2025-03-22 04:00:18.617 CET [26] LOG: checkpoint complete: wrote 2 buffers (0.0%); 0 WAL file(s) added, 0 removed, 0 recycled; write=0.103 s, sync=0.005 s, total=0.121 s; sync files=2, longest=0.004 s, average=0.003 s; distance=0 kB, estimate=16 kB
2025-03-23 18:44:08.218 CET [15778] ERROR: column core_userprofile.weight_rounding does not exist at character 466
2025-03-23 18:44:08.218 CET [15778] STATEMENT: SELECT "core_userprofile"."id", "core_userprofile"."user_id", "core_userprofile"."gym_id", "core_userprofile"."email_verified", "core_userprofile"."is_temporary", "core_userprofile"."show_comments", "core_userprofile"."show_english_ingredients", "core_userprofile"."workout_reminder_active", "core_userprofile"."workout_reminder", "core_userprofile"."workout_duration", "core_userprofile"."last_workout_notification", "core_userprofile"."notification_language_id", "core_userprofile"."weight_rounding", "core_userprofile"."repetitions_rounding", "core_userprofile"."age", "core_userprofile"."birthdate", "core_userprofile"."height", "core_userprofile"."gender", "core_userprofile"."sleep_hours", "core_userprofile"."work_hours", "core_userprofile"."work_intensity", "core_userprofile"."sport_hours", "core_userprofile"."sport_intensity", "core_userprofile"."freetime_hours", "core_userprofile"."freetime_intensity", "core_userprofile"."calories", "core_userprofile"."weight_unit", "core_userprofile"."ro_access", "core_userprofile"."num_days_weight_reminder", "core_userprofile"."added_by_id", "core_userprofile"."can_add_user" FROM "core_userprofile" WHERE "core_userprofile"."user_id" = 2 LIMIT 21
```
</details>
I suspect it might be caused by https://github.com/wger-project/react/pull/975 | closed | 2025-03-23T17:49:37Z | 2025-03-23T19:01:48Z | https://github.com/wger-project/wger/issues/1928 | [] | laur89 | 6 |
sinaptik-ai/pandas-ai | data-visualization | 1,183 | when i note "direct_sql": True, error:Not an executable object: "\nSELECT \n ELECTRY_NAME,\n ...... | ### System Info
2.0.43
### 🐛 Describe the bug
code:
```
elect = MySQLConnector(
config={
"host": "180.101.226.110",
"port": 4414,
"database": "jssp-server",
"username": "jssp",
"password": "aaaaa",
"table": "M_Y_ENERGYELECTRY"
}, field_descriptions=prompt_config.ENERGYELECTRY
)
agent = Agent(elect, config={"llm":llm,"save_logs": False, "open_charts": False,"memory_size":0,
"enable_cache": False, "save_charts": True, "direct_sql": True,"dataframe_serializer":4,
"data_viz_library": "plotly","lazy_load_connector":False,"max_retries":1,"use_error_correction_framework":False,"use_error_correction":False})
chat = agent.chat(user_question)
print(chat)
````
erro: Not an executable object: "\nSELECT \n ELECTRY_NAME,\n METER_READING_READING\nFROM \n M_Y_ENERGYELECTRY\nWHERE \n BUILDING_NAME LIKE '%12号楼%'\nORDER BY \n METER_READING_READING DESC\nLIMIT 5;\n"
debug:
```
2024-05-29 13:57:31,470 - logger.py[line:75] - INFO:
Code running:
```
result = {}
sql_query = """
SELECT
ELECTRY_NAME,
METER_READING_READING
FROM
M_Y_ENERGYELECTRY
WHERE
BUILDING_NAME LIKE '%12号楼%'
ORDER BY
METER_READING_READING DESC
LIMIT 5;
"""
top_meters_df = execute_sql_query(sql_query)
if not top_meters_df.empty:
result = {'type': 'dataframe', 'value': top_meters_df}
else:
result = {'type': 'string', 'value': 'No data found for Building 12 meters.'}
```
2024-05-29 13:57:31,471 - logger.py[line:75] - INFO: Executing Step 6: CodeExecution
{'M_Y_ENERGYELECTRY': 'M_Y_ENERGYELECTRY', '"M_Y_ENERGYELECTRY"': 'M_Y_ENERGYELECTRY'}
['M_Y_ENERGYELECTRY']
2024-05-29 13:57:31,478 - logger.py[line:79] - ERROR: Failed with error: Traceback (most recent call last):
File "D:\Anaconda3\envs\pytorch\Lib\site-packages\sqlalchemy\engine\base.py", line 1414, in execute
meth = statement._execute_on_connection
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
AttributeError: 'str' object has no attribute '_execute_on_connection'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "D:\Anaconda3\envs\pytorch\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
result = self.execute_code(code_to_run, code_context)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\Anaconda3\envs\pytorch\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
exec(code, environment)
File "<string>", line 14, in <module>
File "D:\Anaconda3\envs\pytorch\Lib\site-packages\pandasai\connectors\sql.py", line 443, in execute_direct_sql_query
return pd.read_sql(sql_query, self._connection)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\Anaconda3\envs\pytorch\Lib\site-packages\pandas\io\sql.py", line 590, in read_sql
return pandas_sql.read_query(
^^^^^^^^^^^^^^^^^^^^^^
File "D:\Anaconda3\envs\pytorch\Lib\site-packages\pandas\io\sql.py", line 1560, in read_query
result = self.execute(*args)
^^^^^^^^^^^^^^^^^^^
File "D:\Anaconda3\envs\pytorch\Lib\site-packages\pandas\io\sql.py", line 1405, in execute
return self.connectable.execution_options().execute(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\Anaconda3\envs\pytorch\Lib\site-packages\sqlalchemy\engine\base.py", line 1416, in execute
raise exc.ObjectNotExecutableError(statement) from err
sqlalchemy.exc.ObjectNotExecutableError: Not an executable object: "\nSELECT \n ELECTRY_NAME,\n METER_READING_READING\nFROM \n M_Y_ENERGYELECTRY\nWHERE \n BUILDING_NAME LIKE '%12号楼%'\nORDER BY \n METER_READING_READING DESC\nLIMIT 5;\n"
2024-05-29 13:57:31,478 - logger.py[line:79] - ERROR: Pipeline failed on step 6: Not an executable object: "\nSELECT \n ELECTRY_NAME,\n METER_READING_READING\nFROM \n M_Y_ENERGYELECTRY\nWHERE \n BUILDING_NAME LIKE '%12号楼%'\nORDER BY \n METER_READING_READING DESC\nLIMIT 5;\n"
Traceback (most recent call last):
File "D:\Anaconda3\envs\pytorch\Lib\site-packages\sqlalchemy\engine\base.py", line 1414, in execute
meth = statement._execute_on_connection
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
AttributeError: 'str' object has no attribute '_execute_on_connection'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "D:\Anaconda3\envs\pytorch\Lib\site-packages\pandasai\pipelines\chat\generate_chat_pipeline.py", line 307, in run
output = (self.code_generation_pipeline | self.code_execution_pipeline).run(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\Anaconda3\envs\pytorch\Lib\site-packages\pandasai\pipelines\pipeline.py", line 137, in run
raise e
File "D:\Anaconda3\envs\pytorch\Lib\site-packages\pandasai\pipelines\pipeline.py", line 101, in run
step_output = logic.execute(
^^^^^^^^^^^^^^
File "D:\Anaconda3\envs\pytorch\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 113, in execute
raise e
File "D:\Anaconda3\envs\pytorch\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
result = self.execute_code(code_to_run, code_context)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\Anaconda3\envs\pytorch\Lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
exec(code, environment)
File "<string>", line 14, in <module>
File "D:\Anaconda3\envs\pytorch\Lib\site-packages\pandasai\connectors\sql.py", line 443, in execute_direct_sql_query
return pd.read_sql(sql_query, self._connection)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\Anaconda3\envs\pytorch\Lib\site-packages\pandas\io\sql.py", line 590, in read_sql
return pandas_sql.read_query(
^^^^^^^^^^^^^^^^^^^^^^
File "D:\Anaconda3\envs\pytorch\Lib\site-packages\pandas\io\sql.py", line 1560, in read_query
result = self.execute(*args)
^^^^^^^^^^^^^^^^^^^
File "D:\Anaconda3\envs\pytorch\Lib\site-packages\pandas\io\sql.py", line 1405, in execute
return self.connectable.execution_options().execute(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\Anaconda3\envs\pytorch\Lib\site-packages\sqlalchemy\engine\base.py", line 1416, in execute
raise exc.ObjectNotExecutableError(statement) from err
sqlalchemy.exc.ObjectNotExecutableError: Not an executable object: "\nSELECT \n ELECTRY_NAME,\n METER_READING_READING\nFROM \n M_Y_ENERGYELECTRY\nWHERE \n BUILDING_NAME LIKE '%12号楼%'\nORDER BY \n METER_READING_READING DESC\nLIMIT 5;\n"
Unfortunately, I was not able to answer your question, because of the following error:
Not an executable object: "\nSELECT \n ELECTRY_NAME,\n METER_READING_READING\nFROM \n M_Y_ENERGYELECTRY\nWHERE \n BUILDING_NAME LIKE '%12号楼%'\nORDER BY \n METER_READING_READING DESC\nLIMIT 5;\n"
``` | closed | 2024-05-29T06:25:20Z | 2024-09-04T16:05:58Z | https://github.com/sinaptik-ai/pandas-ai/issues/1183 | [
"bug"
] | colorwlof | 2 |
pandas-dev/pandas | python | 60,903 | BUG: Adding DataFrames with misaligned MultiIndex produces NaN despite fill_value=0 | ### Pandas version checks
- [x] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [x] I have confirmed this bug exists on the [main branch](https://pandas.pydata.org/docs/dev/getting_started/install.html#installing-the-development-version-of-pandas) of pandas.
### Reproducible Example
```python
import pandas as pd
# Create two DataFrames with MultiIndex
index1 = pd.MultiIndex.from_tuples([('A', 'one'), ('A', 'two')])
index2 = pd.MultiIndex.from_tuples([('B', 'one'), ('B', 'two')])
df1 = pd.DataFrame([[1, 2]], columns=index1)
df2 = pd.DataFrame([[3, 4]], columns=index2)
# Adding DataFrames with different MultiIndex
result = df1.add(df2, fill_value=0)
print(result)
```
### Issue Description
I have two data frames with unaligned multi-indices. When adding the two data frames, with fill_value=0, I'd expect the missing values to be replaced with zero before performing the addition operation, as described in the documentation of `DataFrame.add`. However, the above example produces this output:
```
A B
one two one two
0 NaN NaN NaN NaN
```
The problem affects the current main branch (tested with commit https://github.com/pandas-dev/pandas/commit/e557039fda7d4325184cf76520892b3a635ec2dd). No released version is affected (yet). The behavior was introduced by https://github.com/pandas-dev/pandas/pull/60538. Before this PR, the code was producing the expected output.
### Expected Behavior
I'd expect this output:
```
A B
one two one two
0 1.0 2.0 3.0 4.0
```
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 72fd708761f1598f1a8ce9b693529b81fd8ca252
python : 3.10.8
python-bits : 64
OS : Linux
OS-release : 5.15.0-130-generic
Version : #140-Ubuntu SMP Wed Dec 18 17:59:53 UTC 2024
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : en_US.UTF-8
pandas : 3.0.0.dev0+1839.g72fd708761
numpy : 1.26.4
dateutil : 2.9.0.post0
pip : 24.2
Cython : 3.0.11
sphinx : 8.1.3
IPython : 8.30.0
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
blosc : None
bottleneck : 1.4.2
fastparquet : 2024.11.0
fsspec : 2024.10.0
html5lib : 1.1
hypothesis : 6.122.4
gcsfs : 2024.10.0
jinja2 : 3.1.4
lxml.etree : 5.3.0
matplotlib : 3.10.0
numba : 0.60.0
numexpr : 2.10.2
odfpy : None
openpyxl : 3.1.5
psycopg2 : 2.9.10
pymysql : 1.4.6
pyarrow : 18.1.0
pyreadstat : 1.2.8
pytest : 8.3.4
python-calamine : None
pytz : 2024.2
pyxlsb : 1.0.10
s3fs : 2024.10.0
scipy : 1.14.1
sqlalchemy : 2.0.36
tables : 3.10.1
tabulate : 0.9.0
xarray : 2024.9.0
xlrd : 2.0.1
xlsxwriter : 3.2.0
zstandard : 0.23.0
tzdata : 2024.2
qtpy : None
pyqt5 : None
</details>
| closed | 2025-02-10T09:23:10Z | 2025-02-10T18:23:28Z | https://github.com/pandas-dev/pandas/issues/60903 | [
"Bug",
"Indexing",
"Numeric Operations",
"MultiIndex"
] | michaelpradel | 3 |
taverntesting/tavern | pytest | 641 | how to save response from list of dictionary if response like this ? I want to save data1 from first dictionary from list using tavern | [
{
"data1": 2,
"data2": "bbbbb",
"data3": "cccc",
"data4": 1,
"data5": "Andersta gård",
"data6": "aaaaa"
},
{
"data1": 2,
"data2": "bbbbb",
"data3": "cccc",
"data4": 1,
"data5": "Andersta gård",
"data6": "aaaaa"
}
] | closed | 2021-02-11T13:22:03Z | 2021-05-16T10:31:30Z | https://github.com/taverntesting/tavern/issues/641 | [] | Tinku9090 | 1 |
localstack/localstack | python | 11,873 | Incompatibility with aws-cdk >= 2.167.0 | Due to a change in the used JavaScript AWS SDK from v2 to v3, newer `aws-cdk` versions (`2.167.0`) are currently incompatible and will produce an error like this:
```
❌ Environment aws://000000000000/us-east-1 failed bootstrapping: InvalidClientTokenId: The security token included in the request is invalid.
...
```
We're working on a fix to make newer versions compatible with LocalStack.
In the meantime the last compatible version of aws-cdk is `2.166.0`.
We'll update the issue here once this has been resolved! | closed | 2024-11-19T08:12:23Z | 2024-11-20T19:11:24Z | https://github.com/localstack/localstack/issues/11873 | [] | dominikschubert | 1 |
django-oscar/django-oscar | django | 3,875 | Performance issue in cases where selecting strategy for product | Found a bug? Please fill out the sections below.
### Issue Summary
In Oscar 2.1, Selecting a strategy for product in [`UseFirstStockRecord`](https://github.com/django-oscar/django-oscar/blob/2.1.0b0/src/oscar/apps/partner/strategy.py#L188) used to (correctly, for performance reasons) index on the related stock records for a product to get the first. This meant, of course, that the `prefetch_related` call to `stockrecords` on `Product` was used and no additional queries generated.
Now, in Oscar 3.1 [this was changed to use the queryset's `first` method](https://github.com/django-oscar/django-oscar/blob/3.1/src/oscar/apps/partner/strategy.py#L188), which unfortunately makes the prefetch invalid and causes a new query each time a product shows price info (for various reasons, this has a huge performance impact on my use case).
This change was introduced in [this commit](https://github.com/django-oscar/django-oscar/commit/3a826796d01e5cba345aa646dbc5c8ae466cbf4a), which also implemented the same pattern over various related queries, and therefore I assume has similar performance implications (but I haven't checked).
### Steps to Reproduce
Try to render a page with various snippets of pricing info for a collection of hundreds of products - use a tool like Django Debug Toolbar to see the query multiplication :)
### Technical details
* Python version: Run `python --version`: 3.10
* Django version: Look in your requirements.txt, or run `pip show django | grep Version` 3.2.12
* Oscar version: Look in your requirements.txt, or run `pip show django-oscar | grep Version`. 3.1
| closed | 2022-02-25T15:45:50Z | 2022-03-02T11:39:04Z | https://github.com/django-oscar/django-oscar/issues/3875 | [] | pwalsh | 5 |
kizniche/Mycodo | automation | 1,042 | AtlasScientificI2C raised an exception when initializing: [Errno 2] No such file or directory: '/dev/i2c-1' | Following your hydroponics tutorial I'm trying to set new i2c addresses for my EZO_PMP's .. unfortunately I'm encountering an error:
pi@raspberrypi:~ $ ~/Mycodo/env/bin/python ~/Mycodo/mycodo/devices/atlas_scientific_i2c.py
AtlasScientificI2C raised an exception when initializing: [Errno 2] No such file or directory: '/dev/i2c-1'
Traceback (most recent call last):
File "/home/pi/Mycodo/mycodo/devices/atlas_scientific_i2c.py", line 35, in __init__
self.file_read = io.open("/dev/i2c-" + str(i2c_bus), "rb", buffering=0)
FileNotFoundError: [Errno 2] No such file or directory: '/dev/i2c-1'
>> Atlas Scientific sample code
>> Any commands entered are passed to the board via I2C except:
>> List_addr lists the available I2C addresses.
>> Address,xx changes the I2C address the Raspberry Pi communicates with.
>> Poll,xx.x command continuously polls the board every xx.x seconds
where xx.x is longer than the 1.50 second timeout.
>> Pressing ctrl-c will stop the polling
Enter command: list_addr
Traceback (most recent call last):
File "/home/pi/Mycodo/mycodo/devices/atlas_scientific_i2c.py", line 187, in <module>
main()
File "/home/pi/Mycodo/mycodo/devices/atlas_scientific_i2c.py", line 141, in main
devices = device.list_i2c_devices()
File "/home/pi/Mycodo/mycodo/devices/atlas_scientific_i2c.py", line 116, in list_i2c_devices
self.set_i2c_address(i)
File "/home/pi/Mycodo/mycodo/devices/atlas_scientific_i2c.py", line 61, in set_i2c_address
fcntl.ioctl(self.file_read, i2c_slave, addr)
AttributeError: 'AtlasScientificI2C' object has no attribute 'file_read'
Here's my setup.log.
[setup.log](https://github.com/kizniche/Mycodo/files/6743108/setup.log)
please help :)
| closed | 2021-06-30T18:13:15Z | 2021-06-30T18:31:32Z | https://github.com/kizniche/Mycodo/issues/1042 | [] | Ikzy | 2 |
coqui-ai/TTS | python | 3,617 | [Bug] atttributeError: 'Tacotron2' object has no attribute 'args' | ### Describe the bug
Traceback (most recent call last):
File "/home/mariah/.local/bin/tts", line 8, in <module>
sys.exit(main())
^^^^^^
File "/home/mariah/Applications/tts/TTS/bin/synthesize.py", line 468, in main
wav = synthesizer.tts(
^^^^^^^^^^^^^^^^
File "/home/mariah/Applications/tts/TTS/utils/synthesizer.py", line 463, in tts
outputs = transfer_voice(
^^^^^^^^^^^^^^^
File "/home/mariah/Applications/tts/TTS/tts/utils/synthesis.py", line 319, in transfer_voice
reference_wav, sr=model.args.encoder_sample_rate if model.args.encoder_sample_rate else model.ap.sample_rate
^^^^^^^^^^
File "/home/mariah/.local/pipx/venvs/tts/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1688, in __getattr__
raise AttributeError(f"'{type(self).__name__}' object has no attribute '{name}'")
AttributeError: 'Tacotron2' object has no attribute 'args'
### To Reproduce
<pre>\ 9-year-old\ Doctor\ Who\ fan\ \[VS0iFWwvDbs\].wav --text "test" --pipe_out --out_path t.wav > error.txt
### Expected behavior
_No response_
### Logs
_No response_
### Environment
```shell
I tried running collect_env_info.py but it says no module found torch
```
### Additional context
_No response_ | closed | 2024-03-01T19:40:43Z | 2025-01-03T09:47:59Z | https://github.com/coqui-ai/TTS/issues/3617 | [
"bug",
"wontfix"
] | MariahWest01 | 1 |
fastapi/sqlmodel | pydantic | 196 | from __future__ import annotation and many to many example | ### First Check
- [X] I added a very descriptive title to this issue.
- [X] I used the GitHub search to find a similar issue and didn't find it.
- [X] I searched the SQLModel documentation, with the integrated search.
- [X] I already searched in Google "How to X in SQLModel" and didn't find any information.
- [X] I already read and followed all the tutorial in the docs and didn't find an answer.
- [X] I already checked if it is not related to SQLModel but to [Pydantic](https://github.com/samuelcolvin/pydantic).
- [X] I already checked if it is not related to SQLModel but to [SQLAlchemy](https://github.com/sqlalchemy/sqlalchemy).
### Commit to Help
- [X] I commit to help with one of those options 👆
### Example Code
```python
from __future__ import annotations
from typing import List, Optional
from sqlmodel import Field, Relationship, Session, SQLModel, create_engine
class HeroTeamLink(SQLModel, table=True):
team_id: Optional[int] = Field(
default=None, foreign_key="team.id", primary_key=True
)
hero_id: Optional[int] = Field(
default=None, foreign_key="hero.id", primary_key=True
)
class Team(SQLModel, table=True):
id: Optional[int] = Field(default=None, primary_key=True)
name: str
headquarters: str
heroes: List[Hero] = Relationship(back_populates="teams", link_model=HeroTeamLink)
class Hero(SQLModel, table=True):
id: Optional[int] = Field(default=None, primary_key=True)
name: str
secret_name: str
age: Optional[int] = None
teams: List[Team] = Relationship(back_populates="heroes", link_model=HeroTeamLink)
sqlite_url = f"sqlite://"
engine = create_engine(sqlite_url, echo=True)
def create_db_and_tables():
SQLModel.metadata.create_all(engine)
def create_heroes():
with Session(engine) as session:
team_preventers = Team(name="Preventers", headquarters="Sharp Tower")
team_z_force = Team(name="Z-Force", headquarters="Sister Margaret’s Bar")
hero_deadpond = Hero(
name="Deadpond",
secret_name="Dive Wilson",
teams=[team_z_force, team_preventers],
)
hero_rusty_man = Hero(
name="Rusty-Man",
secret_name="Tommy Sharp",
age=48,
teams=[team_preventers],
)
hero_spider_boy = Hero(
name="Spider-Boy", secret_name="Pedro Parqueador", teams=[team_preventers]
)
session.add(hero_deadpond)
session.add(hero_rusty_man)
session.add(hero_spider_boy)
session.commit()
session.refresh(hero_deadpond)
session.refresh(hero_rusty_man)
session.refresh(hero_spider_boy)
print("Deadpond:", hero_deadpond)
print("Deadpond teams:", hero_deadpond.teams)
print("Rusty-Man:", hero_rusty_man)
print("Rusty-Man Teams:", hero_rusty_man.teams)
print("Spider-Boy:", hero_spider_boy)
print("Spider-Boy Teams:", hero_spider_boy.teams)
def main():
create_db_and_tables()
create_heroes()
if __name__ == "__main__":
main()
```
### Description
all what i have done is use the example from the [docs](https://sqlmodel.tiangolo.com/tutorial/many-to-many/create-models-with-link/) about many to many relationships and tried to fit them with `from __future__ import annotation` by adding the import in the first line and changing `List["Hero"]` to `List[Hero]`. and i get this error
```text
sqlalchemy.exc.InvalidRequestError: When initializing mapper mapped class Team->team, expression 'List[Hero]' failed to locate a name ('List[Hero]'). If this is a class name, consider adding this relationship() to the <class '__main__.Team'> class after both dependent classes have been defined.
```
also `update_forward_refs()` did not help for both classes.
### Operating System
Linux
### Operating System Details
_No response_
### SQLModel Version
0.0.4
### Python Version
Python 3.9.9
### Additional Context
_No response_ | open | 2021-12-18T04:52:09Z | 2024-09-23T05:39:29Z | https://github.com/fastapi/sqlmodel/issues/196 | [
"question",
"investigate"
] | 5cat | 16 |
apachecn/ailearning | nlp | 187 | 为这个仓库的内容生成了电子书 | [机器学习实战（ApacheCN）.pdf](https://github.com/apachecn/MachineLearning/files/1438794/ApacheCN.pdf)
| closed | 2017-11-02T17:57:40Z | 2017-11-03T03:35:17Z | https://github.com/apachecn/ailearning/issues/187 | [] | wizardforcel | 2 |
adamerose/PandasGUI | pandas | 214 | Grapher does not render images | The grapher in pandasgui does not work: the image does not render. Neither empty axes, nor any graphs with data.
**Environment**
OS: Ubuntu 22.04
Python: 3.9.13 (but tested on 3.8.* and 3.10.* too)
IDE: Pycharm (but tested in plain teriminal, either python, or ipython)
**Package versions**
```
ipython==8.5.0
pandasgui==0.2.13
plotly==5.10.0
PyQt5==5.15.7
PyQt5-Qt5==5.15.2
PyQt5-sip==12.11.0
PyQtWebEngine==5.15.6
PyQtWebEngine-Qt5==5.15.2
```
| open | 2022-10-19T06:35:56Z | 2024-04-17T15:57:28Z | https://github.com/adamerose/PandasGUI/issues/214 | [
"bug"
] | mficek | 4 |
dmlc/gluon-cv | computer-vision | 1,021 | Does HardSwish cost much more memory than ReLU6? | I just change the `ReLU6()` to `HardSwish()` based on MobileNetv2.
The already wored program (which left almost 1G gpu memory) now out of memory?
I'm wondering does Does HardSwish cost much more memory than ReLU6 in theory
or
I just have some bug in my code?
I also test the `ReLU` relative to the `ReLU6`; and the `nn.Activation('relu')` costs 2G memory less than `ReLU6`. Maybe the implementation of the `ReLU6` of Gluoncv can be improved? | closed | 2019-11-01T04:26:52Z | 2019-11-10T14:04:35Z | https://github.com/dmlc/gluon-cv/issues/1021 | [] | ShoufaChen | 2 |
netbox-community/netbox | django | 18,606 | UI Racks Table View Performance Scaling Problem - Loading time increases with large number of racks - django N+1 query issue | ### Deployment Type
Self-hosted
### NetBox Version
v4.2.3
### Python Version
3.10
### Steps to Reproduce
1. Starts with a clean NetBox Database
2. Create a site (ex: site) and a rack type (ex: Rack)
3. Batch import 10000 racks on this site (sample csv import file below - you may perform partial upload to avoid server timeout)
[Rack import.txt](https://github.com/user-attachments/files/18719135/Rack.import.txt)
4. Click on Racks -> Racks
It will take several seconds to load. In our case, with about 20K racks instances on NetBox Database, it takes about 15 seconds to load.
5. Enable database debug on configuration.py
6. Click on Racks -> Racks
7. Look at database log
### Expected Behavior
The Rack View loads with a few miliseconds, and the database log may show about <10 SQL querys to render the view.
### Observed Behavior
In Database debug log we can see that for **Each Rack row displayed in NetBox UI** was performed another 3 SQLs querys, to fetch dcim_device, dcim_devicetype and dcim_rackreservation objects, filtered by current rack. It appears to be an django N+1 query issue:
I assume that those additional query was to fetch the device count by rack, and available rack U space stats.
Since in the rack UI view we are only interested on the totals, I am suggesting that a query refactoring, using SQL COUNT/GROUP BY, may solve this optimization/performance issue. It appears to have several django examples on mitigation the N+1 problem [https://dev.to/herchila/how-to-avoid-n1-queries-in-django-tips-and-solutions-2ajo](url)
Query #1
``
(0.006) SELECT "dcim_device"."id", "dcim_device"."created", "dcim_device"."last_updated", "dcim_device"."custom_field_data", "dcim_device"."description", "dcim_device"."comments", "dcim_device"."local_context_data", "dcim_device"."config_template_id", "dcim_device"."device_type_id", "dcim_device"."role_id", "dcim_device"."tenant_id", "dcim_device"."platform_id", "dcim_device"."name", "dcim_device"."serial", "dcim_device"."asset_tag", "dcim_device"."site_id", "dcim_device"."location_id", "dcim_device"."rack_id", "dcim_device"."position", "dcim_device"."face", "dcim_device"."status", "dcim_device"."airflow", "dcim_device"."primary_ip4_id", "dcim_device"."primary_ip6_id", "dcim_device"."oob_ip_id", "dcim_device"."cluster_id", "dcim_device"."virtual_chassis_id", "dcim_device"."vc_position", "dcim_device"."vc_priority", "dcim_device"."latitude", "dcim_device"."longitude", "dcim_device"."console_port_count", "dcim_device"."console_server_port_count", "dcim_device"."power_port_count", "dcim_device"."power_outlet_count", "dcim_device"."interface_count", "dcim_device"."front_port_count", "dcim_device"."rear_port_count", "dcim_device"."device_bay_count", "dcim_device"."module_bay_count", "dcim_device"."inventory_item_count" FROM "dcim_device" INNER JOIN "dcim_devicetype" ON ("dcim_device"."device_type_id" = "dcim_devicetype"."id") WHERE ("dcim_device"."rack_id" = 1327 AND "dcim_device"."position" >= 1 AND NOT ("dcim_devicetype"."exclude_from_utilization")) ORDER BY "dcim_device"."name" ASC, "dcim_device"."id" ASC; args=(1327, Decimal('1')); alias=default
``
Query #2
``
(0.001) SELECT "dcim_devicetype"."id", "dcim_devicetype"."created", "dcim_devicetype"."last_updated", "dcim_devicetype"."custom_field_data", "dcim_devicetype"."description", "dcim_devicetype"."comments", "dcim_devicetype"."weight", "dcim_devicetype"."weight_unit", "dcim_devicetype"."_abs_weight", "dcim_devicetype"."manufacturer_id", "dcim_devicetype"."model", "dcim_devicetype"."slug", "dcim_devicetype"."default_platform_id", "dcim_devicetype"."part_number", "dcim_devicetype"."u_height", "dcim_devicetype"."exclude_from_utilization", "dcim_devicetype"."is_full_depth", "dcim_devicetype"."subdevice_role", "dcim_devicetype"."airflow", "dcim_devicetype"."front_image", "dcim_devicetype"."rear_image", "dcim_devicetype"."console_port_template_count", "dcim_devicetype"."console_server_port_template_count", "dcim_devicetype"."power_port_template_count", "dcim_devicetype"."power_outlet_template_count", "dcim_devicetype"."interface_template_count", "dcim_devicetype"."front_port_template_count", "dcim_devicetype"."rear_port_template_count", "dcim_devicetype"."device_bay_template_count", "dcim_devicetype"."module_bay_template_count", "dcim_devicetype"."inventory_item_template_count" FROM "dcim_devicetype" WHERE "dcim_devicetype"."id" IN (504, 397); args=(504, 397); alias=default
``
Query #3
``
(0.001) SELECT "dcim_rackreservation"."id", "dcim_rackreservation"."created", "dcim_rackreservation"."last_updated", "dcim_rackreservation"."custom_field_data", "dcim_rackreservation"."comments", "dcim_rackreservation"."rack_id", "dcim_rackreservation"."units", "dcim_rackreservation"."tenant_id", "dcim_rackreservation"."user_id", "dcim_rackreservation"."description" FROM "dcim_rackreservation" WHERE "dcim_rackreservation"."rack_id" = 1327 ORDER BY "dcim_rackreservation"."created" ASC, "dcim_rackreservation"."id" ASC; args=(1327,); alias=default
``
| open | 2025-02-08T14:44:57Z | 2025-02-14T21:41:33Z | https://github.com/netbox-community/netbox/issues/18606 | [
"type: bug",
"status: accepted",
"severity: low"
] | marcusyuri | 0 |
polakowo/vectorbt | data-visualization | 592 | how to combine two indicator | how tow combine two indicator to make test buy signal like this ema 20 cross ema40 and rsi >20 how to make this work | open | 2023-05-02T02:32:29Z | 2023-05-02T10:25:08Z | https://github.com/polakowo/vectorbt/issues/592 | [] | ahmed159159 | 1 |
junyanz/pytorch-CycleGAN-and-pix2pix | computer-vision | 1,295 | Colab RAM dies on edges2shoes data | I am loading the edges2shoes data on [pix2pix Colab notebook](https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/tutorials/generative/pix2pix.ipynb), but when the training process starts, it dies in the first epoch without any progress. I have also tried to download the data and store it in my Drive then unzip the files, but it also killed the RAM. What would you suggest if I want to train on more than 40k images? - I don't have a computer with a good GPU
Here are the app.log outputs:
```
Jun 30, 2021, 11:55:32 AM | WARNING | WARNING:root:kernel 471f5f6b-3964-42e6-94cd-da04316b808d restarted
Jun 30, 2021, 11:55:32 AM | INFO | KernelRestarter: restarting kernel (1/5), keep random ports
Jun 30, 2021, 11:55:20 AM | WARNING | 2021-06-30 08:55:20.288908: I tensorflow/core/kernels/data/shuffle_dataset_op.cc:177] Filling up shuffle buffer (this may take a while): 3963 of 49825
Jun 30, 2021, 11:55:10 AM | WARNING | 2021-06-30 08:55:10.291234: I tensorflow/core/kernels/data/shuffle_dataset_op.cc:177] Filling up shuffle buffer (this may take a while): 2744 of 49825
Jun 30, 2021, 11:55:00 AM | WARNING | 2021-06-30 08:55:00.290578: I tensorflow/core/kernels/data/shuffle_dataset_op.cc:177] Filling up shuffle buffer (this may take a while): 1394 of 49825
Jun 30, 2021, 11:54:41 AM | WARNING | 2021-06-30 08:54:41.180137: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcublasLt.so.11
Jun 30, 2021, 11:54:38 AM | WARNING | 2021-06-30 08:54:38.609917: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcublas.so.11
Jun 30, 2021, 11:54:14 AM | WARNING | 2021-06-30 08:54:14.321466: I tensorflow/stream_executor/cuda/cuda_dnn.cc:359] Loaded cuDNN version 8004
Jun 30, 2021, 11:54:12 AM | WARNING | 2021-06-30 08:54:12.143131: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudnn.so.8
Jun 30, 2021, 11:53:53 AM | WARNING | 2021-06-30 08:53:53.985869: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2199995000 Hz
```
| open | 2021-06-30T09:15:51Z | 2021-12-08T21:21:09Z | https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix/issues/1295 | [] | kemalcim | 2 |
pydantic/FastUI | fastapi | 104 | More PageEvent Triggers | I think we need more ways to trigger PageEvents like
- OnPageLoad
- OnFormSubmit
- FromJSScript? | closed | 2023-12-17T19:17:22Z | 2023-12-18T05:31:37Z | https://github.com/pydantic/FastUI/issues/104 | [] | shroominic | 2 |
Kludex/mangum | asyncio | 15 | Example project for AWS | Need to create a full example project to link to for AWS at some point, potentially including how to use with other services and more advanced configurations. | closed | 2019-01-27T10:58:57Z | 2019-01-28T13:15:55Z | https://github.com/Kludex/mangum/issues/15 | [
"docs"
] | jordaneremieff | 1 |
Lightning-AI/pytorch-lightning | pytorch | 20,075 | ModelCheckpoint save ckpts at the end of every epoch even in step-saving strategy | ### Bug description
When `ModelCheckpoint` is enabled and **no validation set is given**, the trainer still save the model checkpoint at the end of every epoch.
I have turn on the `every_n_train_steps=1000` and `every_n_epochs=None`. And the expected behavior according to the docs of [ModelCheckpoint API](https://lightning.ai/docs/pytorch/stable/api/lightning.pytorch.callbacks.ModelCheckpoint.html#lightning.pytorch.callbacks.ModelCheckpoint) should **only save the checkpoints at every 1000 steps, and should not save at the end of each epoch**.
This slows down the training process especially when the training dataset is small. And it has cost me 10TBW of my SSDs.
A quick solution is to pass `save_on_train_epoch_end=False` to the `ModelCheckpoint`.
I believe this bug is caused by the failure of checking the `_should_save_on_train_epoch_end` at L320.
https://github.com/Lightning-AI/pytorch-lightning/blob/bf25167bbf64f50ba335aa759318946b21775cd2/src/lightning/pytorch/callbacks/model_checkpoint.py#L318-L324
And the logic at L432-437 triggers the bug when **no validation dataset is given**.
https://github.com/Lightning-AI/pytorch-lightning/blob/bf25167bbf64f50ba335aa759318946b21775cd2/src/lightning/pytorch/callbacks/model_checkpoint.py#L423-L441
### What version are you seeing the problem on?
master
### How to reproduce the bug
```python
Run lightning with following callback, with a relative small dataset (e.g., a dataset with only 100 batch in one epoch)
ModelCheckpoint(
monitor="train_loss",
every_n_train_steps=10,
dirpath="checkpoints",
filename="{step}-{train_loss:.3f}",
save_top_k=1,
mode="min",
save_last=True,
)
```
### Error messages and logs
_No response_
### Environment
<details>
<summary>Current environment</summary>
* CUDA:
- GPU:
- NVIDIA A800 80GB PCIe
- NVIDIA A800 80GB PCIe
- NVIDIA A800 80GB PCIe
- NVIDIA A800 80GB PCIe
- available: True
- version: 12.1
* Lightning:
- lightning: 2.3.0
- lightning-utilities: 0.11.2
- pytorch-lightning: 2.3.0
- torch: 2.3.1+cu121
- torchaudio: 2.3.1+cu121
- torchmetrics: 1.4.0.post0
- torchvision: 0.18.1+cu121
* Packages:
- absl-py: 2.1.0
- aiohttp: 3.9.5
- aiosignal: 1.3.1
- annotated-types: 0.7.0
- antlr4-python3-runtime: 4.9.3
- anyio: 4.4.0
- argon2-cffi: 23.1.0
- argon2-cffi-bindings: 21.2.0
- arrow: 1.3.0
- asttokens: 2.4.1
- async-lru: 2.0.4
- attrs: 23.2.0
- babel: 2.15.0
- beautifulsoup4: 4.12.3
- bleach: 6.1.0
- certifi: 2024.6.2
- cffi: 1.16.0
- cfgv: 3.4.0
- charset-normalizer: 3.3.2
- comm: 0.2.2
- contourpy: 1.2.1
- cycler: 0.12.1
- debugpy: 1.8.1
- decorator: 5.1.1
- deepspeed: 0.14.4
- defusedxml: 0.7.1
- dill: 0.3.8
- distlib: 0.3.8
- einops: 0.8.0
- executing: 2.0.1
- fastjsonschema: 2.20.0
- filelock: 3.15.1
- flash-attn: 2.5.9.post1
- fonttools: 4.53.0
- fqdn: 1.5.1
- frozenlist: 1.4.1
- fsspec: 2024.6.0
- grpcio: 1.64.1
- h11: 0.14.0
- hjson: 3.1.0
- httpcore: 1.0.5
- httpx: 0.27.0
- huggingface-hub: 0.23.4
- hydra-core: 1.3.2
- identify: 2.5.36
- idna: 3.7
- ipykernel: 6.29.4
- ipython: 8.25.0
- isoduration: 20.11.0
- jedi: 0.19.1
- jinja2: 3.1.4
- json5: 0.9.25
- jsonpointer: 3.0.0
- jsonschema: 4.22.0
- jsonschema-specifications: 2023.12.1
- jupyter-client: 8.6.2
- jupyter-core: 5.7.2
- jupyter-events: 0.10.0
- jupyter-lsp: 2.2.5
- jupyter-server: 2.14.1
- jupyter-server-terminals: 0.5.3
- jupyterlab: 4.2.2
- jupyterlab-pygments: 0.3.0
- jupyterlab-server: 2.27.2
- kiwisolver: 1.4.5
- lightning: 2.3.0
- lightning-utilities: 0.11.2
- markdown: 3.6
- markupsafe: 2.1.5
- matplotlib: 3.9.0
- matplotlib-inline: 0.1.7
- mistune: 3.0.2
- mpmath: 1.3.0
- multidict: 6.0.5
- nbclient: 0.10.0
- nbconvert: 7.16.4
- nbformat: 5.10.4
- nest-asyncio: 1.6.0
- networkx: 3.3
- ninja: 1.11.1.1
- nodeenv: 1.9.1
- notebook-shim: 0.2.4
- numpy: 1.26.4
- nvidia-cublas-cu12: 12.1.3.1
- nvidia-cuda-cupti-cu12: 12.1.105
- nvidia-cuda-nvrtc-cu12: 12.1.105
- nvidia-cuda-runtime-cu12: 12.1.105
- nvidia-cudnn-cu12: 8.9.2.26
- nvidia-cufft-cu12: 11.0.2.54
- nvidia-curand-cu12: 10.3.2.106
- nvidia-cusolver-cu12: 11.4.5.107
- nvidia-cusparse-cu12: 12.1.0.106
- nvidia-ml-py: 12.555.43
- nvidia-nccl-cu12: 2.20.5
- nvidia-nvjitlink-cu12: 12.5.40
- nvidia-nvtx-cu12: 12.1.105
- omegaconf: 2.3.0
- overrides: 7.7.0
- packaging: 24.1
- pandas: 2.2.2
- pandocfilters: 1.5.1
- parso: 0.8.4
- pexpect: 4.9.0
- pillow: 10.3.0
- pip: 24.0
- platformdirs: 4.2.2
- pre-commit: 3.7.1
- prometheus-client: 0.20.0
- prompt-toolkit: 3.0.47
- protobuf: 4.25.3
- psutil: 6.0.0
- ptyprocess: 0.7.0
- pure-eval: 0.2.2
- py-cpuinfo: 9.0.0
- pycparser: 2.22
- pydantic: 2.7.4
- pydantic-core: 2.18.4
- pyfunctional: 1.5.0
- pygments: 2.18.0
- pyparsing: 3.1.2
- python-dateutil: 2.9.0.post0
- python-json-logger: 2.0.7
- pytorch-lightning: 2.3.0
- pytz: 2024.1
- pyyaml: 6.0.1
- pyzmq: 26.0.3
- referencing: 0.35.1
- regex: 2024.5.15
- requests: 2.32.3
- rfc3339-validator: 0.1.4
- rfc3986-validator: 0.1.1
- rpds-py: 0.18.1
- safetensors: 0.4.3
- send2trash: 1.8.3
- setuptools: 69.5.1
- six: 1.16.0
- sniffio: 1.3.1
- soupsieve: 2.5
- stack-data: 0.6.3
- sympy: 1.12.1
- tabulate: 0.9.0
- tensorboard: 2.17.0
- tensorboard-data-server: 0.7.2
- tensorboardx: 2.6.2.2
- termcolor: 2.4.0
- terminado: 0.18.1
- tinycss2: 1.3.0
- tokenizers: 0.19.1
- torch: 2.3.1+cu121
- torchaudio: 2.3.1+cu121
- torchmetrics: 1.4.0.post0
- torchvision: 0.18.1+cu121
- tornado: 6.4.1
- tqdm: 4.66.4
- traitlets: 5.14.3
- transformers: 4.42.3
- triton: 2.3.1
- types-python-dateutil: 2.9.0.20240316
- typing-extensions: 4.12.2
- tzdata: 2024.1
- uri-template: 1.3.0
- urllib3: 2.2.2
- virtualenv: 20.26.2
- wcwidth: 0.2.13
- webcolors: 24.6.0
- webencodings: 0.5.1
- websocket-client: 1.8.0
- werkzeug: 3.0.3
- wheel: 0.43.0
- yarl: 1.9.4
* System:
- OS: Linux
- architecture:
- 64bit
- ELF
- processor: x86_64
- python: 3.11.9
- release: 5.15.0-67-generic
- version: #74~20.04.1-Ubuntu SMP Wed Feb 22 14:52:34 UTC 2023
</details>
### More info
_No response_ | open | 2024-07-12T09:53:49Z | 2024-07-12T09:54:03Z | https://github.com/Lightning-AI/pytorch-lightning/issues/20075 | [
"bug",
"needs triage",
"ver: 2.2.x"
] | leonardodalinky | 0 |
LibreTranslate/LibreTranslate | api | 72 | Front-end interface is not 100% self-hosted | As includes remote dependencies, for example:
```
<link href="https://fonts.googleapis.com/icon?family=Material+Icons" rel="stylesheet">
<script src="https://cdn.jsdelivr.net/npm/vue@2"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/prism/1.22.0/prism.min.js"></script>
``` | closed | 2021-04-01T13:45:10Z | 2021-04-02T11:38:42Z | https://github.com/LibreTranslate/LibreTranslate/issues/72 | [] | ghost | 5 |
ivy-llc/ivy | tensorflow | 28,419 | Fix Frontend Failing Test: torch - math.paddle.floor | To-do List: https://github.com/unifyai/ivy/issues/27498 | closed | 2024-02-25T14:26:02Z | 2024-03-06T09:54:21Z | https://github.com/ivy-llc/ivy/issues/28419 | [
"Sub Task"
] | Sai-Suraj-27 | 0 |
ultralytics/ultralytics | pytorch | 18,857 | Accuracy and performance difference between self-GPU-Train and using ultralytics platform GPU | ### Search before asking
- [x] I have searched the Ultralytics YOLO [issues](https://github.com/ultralytics/ultralytics/issues) and [discussions](https://github.com/orgs/ultralytics/discussions) and found no similar questions.
### Question
Hello,
I am having an issue using my own 4090 to do the training result in worse result compared to the model trained with ultralytics platform with credit.
Same parameter, and data set.
The accuracy and performance from ultralytics platform with credit does much better than my own 4090 result.
Does anyone experience the same issue?
How do I fix this issue?
### Additional
_No response_ | open | 2025-01-24T04:57:52Z | 2025-01-24T08:30:22Z | https://github.com/ultralytics/ultralytics/issues/18857 | [
"question",
"HUB"
] | felixho789 | 2 |
jupyter-book/jupyter-book | jupyter | 1,639 | Jupyter Book can't compile using Github Workflow: "The 'black' distribution was not found and is required by the application" | ### Describe the bug
**context**
I have a [repository](https://github.com/whyjz/pejzero) with a couple of Notebooks that I want to render as HTML using Jupyter Book and Github Actions.
**expectation**
I have tested `jupyter book build ./jupyter-book` on my local machine, and it worked out well as expected.
**bug**
But when I apply the sample workflow using Github Actions, an error message shows and says
`pkg_resources.DistributionNotFound: The 'black' distribution was not found and is required by the application`.
Here's the [full report of the error message on Github Actions](https://github.com/whyjz/pejzero/runs/5225413065?check_suite_focus=true).
Honestly, I am not sure whether this is a dependency issue or not, or whether this is a Jupyter Book issue or Sphinx's.
### Reproduce the bug
You can reproduce the bug by [re-running the Github Action job](https://github.com/whyjz/pejzero/runs/5225413065?check_suite_focus=true).
### List your environment
My local environment is
```
Jupyter Book : 0.12.1
External ToC : 0.2.3
MyST-Parser : 0.15.2
MyST-NB : 0.13.1
Sphinx Book Theme : 0.1.10
Jupyter-Cache : 0.4.3
NbClient : 0.5.3
```
which worked well for compiling HTML. The `environment.yml` that Github Action uses is
```
name: jme
channels:
- conda-forge
- defaults
dependencies:
- python=3.8
- geopandas
- h5py
- jupyter-book=0.12
- matplotlib
- netcdf4
- numpy
- pandas
- pip
- rasterio
- scipy
- seaborn
- sphinx=4.3.2
```
which gives the error message.
Thanks in advance for any thoughts you have... | closed | 2022-02-17T01:29:38Z | 2022-07-14T22:02:00Z | https://github.com/jupyter-book/jupyter-book/issues/1639 | [
"bug"
] | whyjz | 4 |
docarray/docarray | fastapi | 918 | docs: code snippet needed: DocumentArray construct | In [this section](https://docarray.jina.ai/fundamentals/documentarray/construct/#construct-from-local-files) there's no snippet for `read_mode`.
Note: Please leave snippet as comment, don't fix directly. I'm working on docs right now and don't want merge conflicts. | closed | 2022-12-08T13:40:08Z | 2023-04-22T09:38:35Z | https://github.com/docarray/docarray/issues/918 | [] | alexcg1 | 0 |
ray-project/ray | machine-learning | 51,416 | [Ray Data | Core ] | ### What happened + What you expected to happen
I am running SAC on a custom environment, and use Ray Data to load a small csv file for training. I keep encountering the following error message about having too many positional arguments:
Exception occurred in Ray Data or Ray Core internal code. If you continue to see this error, please open an issue on the Ray project GitHub page with the full stack trace below:
https://github.com/ray-project/ray/issues/new/choose
```
Full stack trace:
Traceback (most recent call last):
File "C:\Users\[username]\AppData\Local\Programs\Python\Python312\Lib\site-packages\ray\data\exceptions.py", line 49, in handle_trace
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File "C:\Users\[username]\AppData\Local\Programs\Python\Python312\Lib\site-packages\ray\data\_internal\plan.py", line 429, in execute_to_iterator
bundle_iter = itertools.chain([next(gen)], gen)
^^^^^^^^^
File "C:\Users\[username]\AppData\Local\Programs\Python\Python312\Lib\site-packages\ray\data\_internal\execution\interfaces\executor.py", line 37, in __next__
return self.get_next()
^^^^^^^^^^^^^^^
File "C:\Users\[username]\AppData\Local\Programs\Python\Python312\Lib\site-packages\ray\data\_internal\execution\legacy_compat.py", line 76, in get_next
bundle = self._base_iterator.get_next(output_split_idx)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\[username]\AppData\Local\Programs\Python\Python312\Lib\site-packages\ray\data\_internal\execution\streaming_executor.py", line 168, in get_next
self._outer.shutdown(
File "C:\Users\[username]\AppData\Local\Programs\Python\Python312\Lib\site-packages\ray\data\_internal\execution\streaming_executor.py", line 229, in shutdown
self._autoscaler.on_executor_shutdown()
File "C:\Users\[username]\AppData\Local\Programs\Python\Python312\Lib\site-packages\ray\data\_internal\execution\autoscaler\default_autoscaler.py", line 185, in on_executor_shutdown
actor.request_resources.remote({}, self._execution_id)
File "C:\Users\[username]\AppData\Local\Programs\Python\Python312\Lib\site-packages\ray\actor.py", line 206, in remote
return self._remote(args, kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\[username]\AppData\Local\Programs\Python\Python312\Lib\site-packages\ray\_private\auto_init_hook.py", line 21, in auto_init_wrapper
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File "C:\Users\[username]\AppData\Local\Programs\Python\Python312\Lib\site-packages\ray\util\tracing\tracing_helper.py", line 422, in _start_span
return method(self, args, kwargs, *_args, **_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\[username]\AppData\Local\Programs\Python\Python312\Lib\site-packages\ray\actor.py", line 366, in _remote
return invocation(args, kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\[username]\AppData\Local\Programs\Python\Python312\Lib\site-packages\ray\actor.py", line 347, in invocation
return actor._actor_method_call(
^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\[username]\AppData\Local\Programs\Python\Python312\Lib\site-packages\ray\actor.py", line 1479, in _actor_method_call
list_args = signature.flatten_args(function_signature, args, kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\[username]\AppData\Local\Programs\Python\Python312\Lib\site-packages\ray\_private\signature.py", line 126, in flatten_args
validate_args(signature_parameters, args, kwargs)
File "C:\Users\[username]\AppData\Local\Programs\Python\Python312\Lib\site-packages\ray\_private\signature.py", line 99, in validate_args
raise TypeError(str(exc)) from None
TypeError: too many positional arguments
```
### Versions / Dependencies
Ray: 2.43
Python: 3.12.6
OS: Windows 11
### Reproduction script
[I am not entirely sure which part of my script led to the error - I just posted below as a starting point and happy to take further hints.]
```
import os
import ray
data_dir = ospath.join(ospath.dirname(os.path.realpath(__file__)), "Data")
ticker = env_config.get("ticker")
ticker_file_stream = os.path.join(f"{data_dir}", f"{ticker}.csv")
assert os.path.isfile(
ticker_file_stream
), f"Historical data file stream not found at: {ticker_file_stream}"
ds = ray.data.read_csv(ticker_file_stream)
print("Finished loading dataset.")
```
### Issue Severity
High: It blocks me from completing my task. | open | 2025-03-17T07:11:48Z | 2025-03-18T18:35:11Z | https://github.com/ray-project/ray/issues/51416 | [
"bug",
"triage",
"data"
] | teen4ever | 0 |
jackmpcollins/magentic | pydantic | 222 | Allow custom_llm_parameter with LiteLLM backend | LiteLLM supports an optional `custom_llm_provider` parameter which we make use of.
[This PR](https://github.com/jackmpcollins/magentic/pull/221) adds support for passing it through. | closed | 2024-05-22T13:25:27Z | 2024-05-23T12:15:30Z | https://github.com/jackmpcollins/magentic/issues/222 | [] | entropi | 2 |
adamerose/PandasGUI | pandas | 161 | Output signal and specified cell contents when a row is clicked, and make possible to embed in a section of a PYQT5 main window | Hello,
I first want to thank you for a great tool, which has made things much easier for a project I am working on. There is a feature in PyQt5 QTableView that I am hoping can be implemented in pandas gui, if it is not already. In QTableView I can set it so that when I click anywhere in a row, it will highlight the whole row like a big single button and it will return the contents of the cell in a particular pre-set column, which I can then use as a variable for further searching. for example: if I have a dataframe in a table with 5 rows and 3 columns, titled A, B, C, I can click on any row have have it return only what is in column B.
| open | 2021-07-22T19:09:03Z | 2021-07-22T22:15:13Z | https://github.com/adamerose/PandasGUI/issues/161 | [
"enhancement"
] | Animalwithstix | 2 |
CorentinJ/Real-Time-Voice-Cloning | python | 1,063 | Consistent "Numpy Is Not Available" error | I install numpy version 1.19 or really any version under 1.21, and I get a constant "numpy not available" issue. The program launches but is stuck on this screen:
This is what the CLI looks like
I'm not sure why I'd be getting this error since numpy is installed and it is less than 1.21 | open | 2022-05-08T00:31:25Z | 2022-06-11T04:30:09Z | https://github.com/CorentinJ/Real-Time-Voice-Cloning/issues/1063 | [] | BeepyDataCenter | 2 |
brightmart/text_classification | tensorflow | 60 | text rcnn 模型，反向拼接[left_context,embedded,right_context]，right_context有错误 | 您的代码在处理反向的上下文后，未对context_right_list进行反转处理，那么新的输入则会拼接为[cl0,x1,cr0],其中cr0是xn的反向上文。实际论文中需要的是x1的反向上文。 | closed | 2018-06-15T02:54:43Z | 2018-06-25T10:12:16Z | https://github.com/brightmart/text_classification/issues/60 | [] | PeterMao11 | 1 |
automl/auto-sklearn | scikit-learn | 1,444 | smac 1.3 broke auto-sklearn, "cannot import name 'BetaFloatHyperparameter'" | ## Describe the bug ##
As smac 1.3 got released, auto-sklearn started to fail in import autosklearn.classification.
## To Reproduce ##
Steps to reproduce the behavior:
1. pip install auto-sklearn
2. import autosklearn.classification
This can be fixed by downgrading smac to 1.2.
## Expected behavior ##
No import error.
## Actual behavior, stacktrace or logfile ##
ImportError: cannot import name 'BetaFloatHyperparameter' from 'ConfigSpace.hyperparameters' (/home/tmielika/venv/lib/python3.8/site-packages/ConfigSpace/hyperparameters.cpython-38-x86_64-linux-gnu.so)
## Environment and installation: ##
Please give details about your installation:
* RHEL8 + Ubuntu 20.04
* With and without virtual environment.
* 3.8, 3.9, 3.10
* Auto-sklearn version: current and all earlier I tried.
| closed | 2022-04-20T22:34:59Z | 2022-04-22T23:28:52Z | https://github.com/automl/auto-sklearn/issues/1444 | [] | tmielika | 4 |
scikit-learn/scikit-learn | data-science | 30,371 | Meson Build system error | ### Describe the bug
I am [building from source](https://scikit-learn.org/stable/developers/advanced_installation.html#building-from-source) with Miniforge3. This previously worked in `1.6.dev0`, but when I tried this time I got a Segmentation fault
### Steps/Code to Reproduce
```
$ conda create -n sklearn-env -c conda-forge python numpy scipy cython meson-python ninja
$ conda activate sklearn-env
$ pip install --editable . \
--verbose --no-build-isolation \
--config-settings editable-verbose=true
```
### Expected Results
```
$ python -c "import sklearn; sklearn.show_versions()"
1.7.dev0
```
### Actual Results
```
Using pip 24.3.1 from /home/success/miniforge3/envs/sklearn-env/lib/python3.13/site-packages/pip (python 3.13)
Obtaining file:///home/success/Desktop/scikit-learn
Running command Checking if build backend supports build_editable
Checking if build backend supports build_editable ... done
Running command Preparing editable metadata (pyproject.toml)
+ meson setup /home/success/Desktop/scikit-learn /home/success/Desktop/scikit-learn/build/cp313 -Dbuildtype=release -Db_ndebug=if-release -Db_vscrt=md --native-file=/home/success/Desktop/scikit-learn/build/cp313/meson-python-native-file.ini
The Meson build system
Version: 1.6.0
Source dir: /home/success/Desktop/scikit-learn
Build dir: /home/success/Desktop/scikit-learn/build/cp313
Build type: native build
Project name: scikit-learn
Project version: 1.7.dev0
../../meson.build:1:0: ERROR: Unable to get gcc pre-processor defines:
Compiler stdout:
-----
Compiler stderr:
<built-in>: internal compiler error: Segmentation fault
0x7e8c4244531f ???
./signal/../sysdeps/unix/sysv/linux/x86_64/libc_sigaction.c:0
0x7e8c4242a1c9 __libc_start_call_main
../sysdeps/nptl/libc_start_call_main.h:58
0x7e8c4242a28a __libc_start_main_impl
../csu/libc-start.c:360
Please submit a full bug report, with preprocessed source (by using -freport-bug).
Please include the complete backtrace with any bug report.
See <file:///usr/share/doc/gcc-13/README.Bugs> for instructions.
-----
A full log can be found at /home/success/Desktop/scikit-learn/build/cp313/meson-logs/meson-log.txt
error: subprocess-exited-with-error
× Preparing editable metadata (pyproject.toml) did not run successfully.
│ exit code: 1
╰─> See above for output.
note: This error originates from a subprocess, and is likely not a problem with pip.
full command: /home/success/miniforge3/envs/sklearn-env/bin/python3.13 /home/success/miniforge3/envs/sklearn-env/lib/python3.13/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py prepare_metadata_for_build_editable /tmp/tmpdr9o_eip
cwd: /home/success/Desktop/scikit-learn
Preparing editable metadata (pyproject.toml) ... error
error: metadata-generation-failed
× Encountered error while generating package metadata.
╰─> See above for output.
note: This is an issue with the package mentioned above, not pip.
hint: See above for details.
```
### Versions
```shell
Ubuntu 24.04.1 LTS
```
| closed | 2024-11-29T09:38:29Z | 2024-11-29T11:52:20Z | https://github.com/scikit-learn/scikit-learn/issues/30371 | [
"Bug",
"Needs Triage"
] | SuccessMoses | 2 |
deezer/spleeter | tensorflow | 465 | [Feature] Instrumental Music model (piano / drums / bass / other ) | ## Description
Please consider add Only Instrumental model
like that :
drums / bass / other
piano / drums / bass / other
| open | 2020-08-03T15:31:39Z | 2022-01-19T03:52:02Z | https://github.com/deezer/spleeter/issues/465 | [
"enhancement",
"feature"
] | Kitami | 2 |
JoeanAmier/TikTokDownloader | api | 156 | 运行程序就出现要扫码二维码获取 cookies | 已通过 git pull 更新最新版
已经把 cookies 写入到 json 文件，运行时出现要扫码二维码获取 cookies
扫码获取不可行，一直报错。通过复制粘贴cookies,显示写入成功，但是下一次运行，还是出现要扫码二维码获取 cookies
| closed | 2024-02-23T07:23:46Z | 2024-02-23T09:00:20Z | https://github.com/JoeanAmier/TikTokDownloader/issues/156 | [] | jerryc127 | 0 |
keras-team/keras | tensorflow | 20,529 | Cannot access accuracy in results with keras 3 | Hi, I am new to Keras and TensorFlow. I am using `keras==3.6.0` and `tensorflow==2.18.0`.
I created a sequential model and added layers to it. Here is a pseudocode of what I did:
```
from keras.models import Sequential
from keras.layers import Conv2D
from keras.layers import Dense
from keras.layers import Flatten
from keras import metrics
def build_model(self,
input_shape,
num_classes,
conv_kernel_size=(4, 4),
conv_strides=(2, 2),
conv1_channels_out=16,
conv2_channels_out=32,
final_dense_inputsize=100):
model = Sequential()
model.add(Conv2D(conv1_channels_out,
kernel_size=conv_kernel_size,
strides=conv_strides,
activation='relu',
input_shape=input_shape))
model.add(Conv2D(conv2_channels_out,
kernel_size=conv_kernel_size,
strides=conv_strides,
activation='relu'))
model.add(Flatten())
model.add(Dense(final_dense_inputsize, activation='relu'))
model.add(Dense(num_classes, activation='softmax'))
model.compile(loss="categorical_crossentropy",
optimizer="adam",
metrics=["accuracy"])
return model
```
while evaluating the model, I am getting the results as shown below.
```
print(model.evaluate(self.data_loader.get_valid_loader(batch_size), verbose=1))
print(new_model.metrics_names)
```
Result:
```
157/157 ━━━━━━━━━━━━━━━━━━━━ 0s 1ms/step - accuracy: 0.0788 - loss: 2.3034
[2.3036301136016846, 0.07720000296831131]
['loss', 'compile_metrics']
```
Expected Result:
```
157/157 ━━━━━━━━━━━━━━━━━━━━ 0s 1ms/step - accuracy: 0.0788 - loss: 2.3034
[2.3036301136016846, 0.07720000296831131]
['loss', 'accuracy']
```
Is my expectation correct, or do I need to access accuracy differently? Also, the results do not change even if I change the metrics while compiling the model. Any guidance would be appreciated.
eg.
```
model.compile(loss="categorical_crossentropy",
optimizer="adam",
metrics=[metrics.MeanSquaredError(name='my_mse'),
metrics.AUC(name='my_auc'),
metrics.BinaryAccuracy(),
metrics.Accuracy(),])
```
| closed | 2024-11-21T09:08:21Z | 2024-11-26T16:43:45Z | https://github.com/keras-team/keras/issues/20529 | [
"type:support",
"stat:awaiting response from contributor"
] | tanwarsh | 5 |
holoviz/panel | jupyter | 7,666 | Event discrepancy in FastAPI vs `panel serve` with Tabulator: `TableEditEvent` | #### ALL software version info
<details>
<summary>Software Version Info</summary>
panel 1.6.0, bokeh_fastapi 0.1.3, fastapi 0.115.7, bokeh 3.6.2 (in a virtual environment created just before issue submission)
```
$ python -V
Python 3.13.1
$ pip list
Package Version
------------------------- --------------
annotated-types 0.7.0
anyio 4.8.0
appnope 0.1.4
argon2-cffi 23.1.0
argon2-cffi-bindings 21.2.0
arrow 1.3.0
asttokens 3.0.0
async-lru 2.0.4
attrs 24.3.0
babel 2.16.0
beautifulsoup4 4.12.3
bleach 6.2.0
bokeh 3.6.2
bokeh_fastapi 0.1.3
certifi 2024.12.14
cffi 1.17.1
charset-normalizer 3.4.1
click 8.1.8
colorcet 3.1.0
comm 0.2.2
contourpy 1.3.1
cycler 0.12.1
debugpy 1.8.12
decorator 5.1.1
defusedxml 0.7.1
dnspython 2.7.0
email_validator 2.2.0
executing 2.2.0
fastapi 0.115.7
fastapi-cli 0.0.7
fastjsonschema 2.21.1
fonttools 4.55.6
fqdn 1.5.1
h11 0.14.0
holoviews 1.20.0
httpcore 1.0.7
httptools 0.6.4
httpx 0.28.1
idna 3.10
ipykernel 6.29.5
ipython 8.31.0
isoduration 20.11.0
jedi 0.19.2
Jinja2 3.1.5
json5 0.10.0
jsonpointer 3.0.0
jsonschema 4.23.0
jsonschema-specifications 2024.10.1
jupyter_client 8.6.3
jupyter_core 5.7.2
jupyter-events 0.11.0
jupyter-lsp 2.2.5
jupyter_server 2.15.0
jupyter_server_terminals 0.5.3
jupyterlab 4.3.4
jupyterlab_pygments 0.3.0
jupyterlab_server 2.27.3
kiwisolver 1.4.8
linkify-it-py 2.0.3
Markdown 3.7
markdown-it-py 3.0.0
MarkupSafe 3.0.2
matplotlib 3.10.0
matplotlib-inline 0.1.7
mdit-py-plugins 0.4.2
mdurl 0.1.2
mistune 3.1.0
nbclient 0.10.2
nbconvert 7.16.5
nbformat 5.10.4
nest-asyncio 1.6.0
notebook_shim 0.2.4
numpy 2.2.2
overrides 7.7.0
packaging 24.2
pandas 2.2.3
pandocfilters 1.5.1
panel 1.6.0
param 2.2.0
parso 0.8.4
pexpect 4.9.0
pillow 11.1.0
pip 24.3.1
platformdirs 4.3.6
plotly 5.24.1
prometheus_client 0.21.1
prompt_toolkit 3.0.50
psutil 6.1.1
ptyprocess 0.7.0
pure_eval 0.2.3
pycparser 2.22
pydantic 2.10.6
pydantic_core 2.27.2
Pygments 2.19.1
pyparsing 3.2.1
python-dateutil 2.9.0.post0
python-dotenv 1.0.1
python-json-logger 3.2.1
python-multipart 0.0.20
pytz 2024.2
pyviz_comms 3.0.4
PyYAML 6.0.2
pyzmq 26.2.0
referencing 0.36.1
requests 2.32.3
rfc3339-validator 0.1.4
rfc3986-validator 0.1.1
rich 13.9.4
rich-toolkit 0.13.2
rpds-py 0.22.3
Send2Trash 1.8.3
setuptools 75.8.0
shellingham 1.5.4
six 1.17.0
sniffio 1.3.1
soupsieve 2.6
stack-data 0.6.3
starlette 0.45.3
tenacity 9.0.0
terminado 0.18.1
tinycss2 1.4.0
tornado 6.4.2
tqdm 4.67.1
traitlets 5.14.3
typer 0.15.1
types-python-dateutil 2.9.0.20241206
typing_extensions 4.12.2
tzdata 2025.1
uc-micro-py 1.0.3
uri-template 1.3.0
urllib3 2.3.0
uvicorn 0.34.0
uvloop 0.21.0
watchfiles 1.0.4
wcwidth 0.2.13
webcolors 24.11.1
webencodings 0.5.1
websocket-client 1.8.0
websockets 14.2
xyzservices 2025.1.0
```
Firefox 134.0.1 (aarch64)
MacOS Sequoia 15.1.1
</details>
#### Description of expected behavior and the observed behavior
Expected behavior:
1. Use Tabulator with a simple Pandas `DataFrame`
2. Subscribe to `TableEditEvent`s via `Tabulator.on_edit`
3. Change the Tabulator cell "Element"-"key" in the browser, changing from a blank string to "foobar" (for this example)
4. See `TableEditEvent(column=Element, row=0, value=foobar, old=)`
<img width="245" alt="Image" src="https://github.com/user-attachments/assets/105b3d88-4e3a-4343-b2ae-2ec82d164f79" />
Actual behavior when using different server backends:
* `panel serve`: `panel serve table_edit_event_issue.py`, the correct event is shown
* FastAPI integration: `python table_edit_event_issue.py fastapi`, the event `TableEditEvent(column=Units, row=0, value=, old=None)` is shown instead
This is consistent/repeatable on my end.
#### Complete, minimal, self-contained example code that reproduces the issue
`table_edit_event_issue.py`
```python
from __future__ import annotations
import pandas as pd
import panel as pn
import sys
from panel.models.tabulator import TableEditEvent
def panel():
tab = pn.widgets.Tabulator(
value=pd.DataFrame(
{
"Element": {
"key": "",
},
"Units": {
"key": "",
},
}
)
)
def user_edited_table(event: TableEditEvent):
print(f"\nUser edited table: {event.row=} {event.column=} {event.old=} {event.value=}")
print(f"{event=}")
print(tab.value)
tab.on_edit(user_edited_table)
return tab
if "fastapi" in sys.argv:
print("** FastAPI mode **")
import uvicorn
from fastapi import FastAPI
from panel.io.fastapi import add_application
app = FastAPI()
add_application(path="/", app=app)(panel)
if __name__ == "__main__":
uvicorn.run("table_edit_event_issue:app", reload=True)
else:
print("** Panel mode **")
info = panel()
info.servable()
```
#### Stack traceback and/or browser JavaScript console output
_Correct output_ with `panel serve`:
```
$ panel serve table_edit_event_issue.py
2025-01-24 13:02:16,520 Starting Bokeh server version 3.6.2 (running on Tornado 6.4.2)
2025-01-24 13:02:16,522 User authentication hooks NOT provided (default user enabled)
2025-01-24 13:02:16,523 Bokeh app running at: http://localhost:5006/min
2025-01-24 13:02:16,523 Starting Bokeh server with process id: 75798
** Panel mode **
2025-01-24 13:02:24,909 WebSocket connection opened
2025-01-24 13:02:24,909 ServerConnection created
User edited table: event.row=0 event.column='Element' event.old='' event.value='foobar'
event=TableEditEvent(column=Element, row=0, value=foobar, old=)
Element Units
key foobar
```
Under the hood, the server receives/sends these messages over the websocket:
<details>
```
<- Message 'PATCH-DOC' content: {'events': [{'kind': 'MessageSent', 'msg_type': 'bokeh_event', 'msg_data': {'type': 'event', 'name': 'cell-click', 'values': {'type': 'map', 'entries': [['model', {'id': 'p1026'}], ['column', 'Element'], ['row', 0]]}}}]}
-> Message 'OK' content: {}
<- Message 'PATCH-DOC' content: {'events': [{'kind': 'MessageSent', 'msg_type': 'bokeh_event', 'msg_data': {'type': 'event', 'name': 'cell-click', 'values': {'type': 'map', 'entries': [['model', {'id': 'p1026'}], ['column', 'Element'], ['row', 0]]}}}]}
-> Message 'OK' content: {}
<- Message 'PATCH-DOC' content: {'events': [{'kind': 'ModelChanged', 'model': {'id': 'p1024'}, 'attr': 'indices', 'new': [0]}]}
-> Message 'OK' content: {}
<- Message 'PATCH-DOC' content: {'events': [{'kind': 'MessageSent', 'msg_type': 'bokeh_event', 'msg_data': {'type': 'event', 'name': 'selection-change', 'values': {'type': 'map', 'entries': [['model', {'id': 'p1026'}], ['indices', [0]], ['selected', True], ['flush', True]]}}}]}
-> Message 'OK' content: {}
<- Message 'PATCH-DOC' content: {'events': [{'kind': 'MessageSent', 'msg_type': 'bokeh_event', 'msg_data': {'type': 'event', 'name': 'table-edit', 'values': {'type': 'map', 'entries': [['model', {'id': 'p1026'}], ['column', 'Element'], ['row', 0], ['pre', True]]}}}]}
-> Message 'OK' content: {}
<- Message 'PATCH-DOC' content: {'events': [{'kind': 'ColumnsPatched', 'attr': 'data', 'model': {'id': 'p1023'}, 'patches': {'type': 'map', 'entries': [['Element', [[0, 'foobar']]]]}}]}
-> Message 'OK' content: {}
<- Message 'PATCH-DOC' content: {'events': [{'kind': 'MessageSent', 'msg_type': 'bokeh_event', 'msg_data': {'type': 'event', 'name': 'table-edit', 'values': {'type': 'map', 'entries': [['model', {'id': 'p1026'}], ['column', 'Element'], ['row', 0], ['pre', False]]}}}]}
User edited table: event.row=0 event.column='Element' event.old='' event.value='foobar'
event=TableEditEvent(column=Element, row=0, value=foobar, old=)
Element Units
key foobar
-> Message 'OK' content: {}
```
</details>
_Incorrect output with FastAPI_:
```
$ python table_edit_event_issue.py fastapi
** FastAPI mode **
INFO: Will watch for changes in these directories: ['...']
INFO: Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
INFO: Started reloader process [79978] using WatchFiles
** FastAPI mode **
** FastAPI mode **
INFO: Started server process [79987]
INFO: Waiting for application startup.
INFO: Application startup complete.
INFO: ('127.0.0.1', 62539) - "WebSocket /ws" [accepted]
INFO: connection open
User edited table: event.row=0 event.column='Element' event.old=None event.value=''
event=TableEditEvent(column=Element, row=0, value=, old=None)
Element Units
key
```
Under the hood, the server receives/sends these messages over the websocket:
<details>
```
<- Message 'PATCH-DOC' content: {'events': [{'kind': 'MessageSent', 'msg_type': 'bokeh_event', 'msg_data': {'type': 'event', 'name': 'cell-click', 'values': {'type': 'map', 'entries': [['model', {'id': 'p1026'}], ['column', 'Element'], ['row', 0]]}}}]}
-> Message 'OK' content: {}
<- Message 'PATCH-DOC' content: {'events': [{'kind': 'ModelChanged', 'model': {'id': 'p1024'}, 'attr': 'indices', 'new': [0]}]}
-> Message 'OK' content: {}
<- Message 'PATCH-DOC' content: {'events': [{'kind': 'MessageSent', 'msg_type': 'bokeh_event', 'msg_data': {'type': 'event', 'name': 'selection-change', 'values': {'type': 'map', 'entries': [['model', {'id': 'p1026'}], ['indices', [0]], ['selected', True], ['flush', True]]}}}]}
-> Message 'OK' content: {}
<- Message 'PATCH-DOC' content: {'events': [{'kind': 'MessageSent', 'msg_type': 'bokeh_event', 'msg_data': {'type': 'event', 'name': 'table-edit', 'values': {'type': 'map', 'entries': [['model', {'id': 'p1026'}], ['column', 'Element'], ['row', 0], ['pre', True]]}}}]}
-> Message 'OK' content: {}
<- Message 'PATCH-DOC' content: {'events': [{'kind': 'ColumnsPatched', 'attr': 'data', 'model': {'id': 'p1023'}, 'patches': {'type': 'map', 'entries': [['Element', [[0, 'foobar']]]]}}]}
-> Message 'OK' content: {}
<- Message 'PATCH-DOC' content: {'events': [{'kind': 'MessageSent', 'msg_type': 'bokeh_event', 'msg_data': {'type': 'event', 'name': 'table-edit', 'values': {'type': 'map', 'entries': [['model', {'id': 'p1026'}], ['column', 'Element'], ['row', 0], ['pre', False]]}}}]}
User edited table: event.row=0 event.column='Element' event.old=None event.value=''
event=TableEditEvent(column=Element, row=0, value=, old=None)
Element Units
key
-> Message 'OK' content: {}
```
</details>
To my untrained eye, the messages sent over the websocket appear equivalent. Where could this discrepancy come in?
#### Screenshots or screencasts of the bug in action
- [x] I may be interested in making a pull request to address this
I failed to get to the source of the issue, but I'd be happy to help fix it if I can. I expect the problem may also potentially lie in bokeh-fastapi or elsewhere. | open | 2025-01-24T21:40:40Z | 2025-03-20T23:15:28Z | https://github.com/holoviz/panel/issues/7666 | [] | ken-lauer | 3 |
modelscope/modelscope | nlp | 1,162 | RuntimeError: "LayerNormKernelImpl" not implemented for 'Half' | 使用以下代码在cpu部署GTE文本向量-中文-通用领域-small
`model_id = "iic/nlp_gte_sentence-embedding_chinese-small"
pipeline_se = pipeline(Tasks.sentence_embedding, model=model_id, sequence_length=512, device="cpu")
user_query = ["This is a test example"]
eb_input = {
"source_sentence": user_query
}
user_query_embeddings = pipeline_se(input=eb_input)['text_embedding']`
会报错RuntimeError: "LayerNormKernelImpl" not implemented for 'Half'
看起来是半精度的问题，所以这个模型只能在gpu部署吗 | closed | 2024-12-30T07:54:49Z | 2025-01-02T13:45:50Z | https://github.com/modelscope/modelscope/issues/1162 | [] | WangXuCh | 6 |
MaartenGr/BERTopic | nlp | 1,444 | joblib.externals.loky.process_executor. TerminatedWorkerError: | bertopic = 0.15.0
joblib = 1.2.0
>>> # train the model
>>> topic_model = BERTopic(
... n_gram_range=(1,2),
... verbose=True,
... calculate_probabilities=True,
... )
>>>
>>> topics, probs = topic_model.fit_transform(text)
**Batches: 100%|██████████| 1050/1050 [07:47<00:00, 2.24it/s]
2023-07-31 14:37:25,655 - BERTopic - Transformed documents to Embeddings
2023-07-31 14:38:07,059 - BERTopic - Reduced dimensionality
.......
joblib.externals.loky.process_executor.TerminatedWorkerError: A worker process managed by the executor was unexpectedly terminated. This could be caused by a segmentation fault while calling the function or by an excessive memory usage causing the Operating System to kill the worker.**
please help @MaartenGr | open | 2023-07-31T18:46:30Z | 2023-08-01T17:19:48Z | https://github.com/MaartenGr/BERTopic/issues/1444 | [] | GeezCode | 1 |
ivy-llc/ivy | numpy | 28,266 | Fix Frontend Failing Test: paddle - creation_ops.torch.full | ToDo List: https://github.com/unifyai/ivy/issues/27500 | closed | 2024-02-12T20:56:55Z | 2024-02-25T10:57:03Z | https://github.com/ivy-llc/ivy/issues/28266 | [
"Sub Task"
] | marvlyngkhoi | 0 |
pallets-eco/flask-sqlalchemy | flask | 1,171 | add docs about testing | Mainly, show how to isolated the database per test, so that changes are rolled back without having to re-create the database each time. The [pytest-flask-sqlalchemy](https://github.com/jeancochrane/pytest-flask-sqlalchemy) package provided this, but [stopped working](https://github.com/jeancochrane/pytest-flask-sqlalchemy/issues/63) when Flask-SQAlchemy 3 changed how engines and the session were handled. After investigation, it seems like there's a much simpler way to do this.
I'll at least document the following code, but it's probably better to include it as a patch function in a `flask_sqlalchemy.test` module. Could possibly add pytest fixtures as well that used it.
```python
with a.app_context():
engines = db.engines
engine_cleanup = []
for key, engine in engines.items():
connection = engine.connect()
transaction = connection.begin()
engines[key] = connection
engine_cleanup.append((key, engine, connection, transaction))
yield a
for key, engine, connection, transaction in engine_cleanup:
transaction.rollback()
connection.close()
engines[key] = engine
```
Unlike the linked package, this is all that's needed and supports the multiple binds feature. | open | 2023-02-28T22:49:59Z | 2025-01-06T19:50:22Z | https://github.com/pallets-eco/flask-sqlalchemy/issues/1171 | [] | davidism | 20 |
healthchecks/healthchecks | django | 67 | Disable Alert | We use Chef as our configuration management tool, and provide the healthchecks.io url for a particular server instance as part of the config for that machine (it's an attribute in a node file).
The problem is we will bring machines up and down periodically, so if a machine is up, a cron job will run and then hit the healthcheck.io url, but if we then shut the machine down we continually get alerts for that machine until we boot it up again.
It'd be nice if you could disable (not delete) a healthcheck.io url, as deleting it means that you'll have to create a new url and change the config for that node in your config management tool.
| closed | 2016-07-07T03:30:54Z | 2016-08-01T19:53:55Z | https://github.com/healthchecks/healthchecks/issues/67 | [] | pzelnip | 3 |
python-gino/gino | sqlalchemy | 435 | SQLAlchemy Core events | * GINO version: 0.8.1
* Python version: 3.6.6
* asyncpg version: 0.18.2
* aiocontextvars version: 0.2.1
* PostgreSQL version: 10.6
### Description
Hello, I would like to know if it is possible to use [SQLAlchemy Core Events](https://docs.sqlalchemy.org/en/latest/core/events.html) with Gino.
It would be really great to use [DDLEvents](https://docs.sqlalchemy.org/en/latest/core/events.html#sqlalchemy.events.DDLEvents)
events.py
```python
from sqlalchemy import event
from app.models import UserModel
def after_create_method(target, connection, **kw):
print('some routine...')
event.listen(UserModel.__table__, "after_create", after_create_method)
```
create_user_example.py
```python
async def create_user(validated_data):
instance = await UserModel.create(**validated_data)
return instance
```
I've managed to register a listener by passing __table__ attribute, but unfortunately the function doesn't get invoked once the ```UserModel.create``` gets called. Can someone help me on that?
I've seen ```gino.Crud.CRUDModel.create``` is the class responsible for creating a record on the database. In case we are moving forward with this issue, is it possible to come up with SQLAlchemy events on this method/class?
Thanks in advance!
| open | 2019-02-06T17:17:49Z | 2019-02-25T15:17:47Z | https://github.com/python-gino/gino/issues/435 | [
"feature request"
] | tng10 | 9 |
kennethreitz/records | sqlalchemy | 166 | how to bulk_query? | i saw:
https://docs.sqlalchemy.org/en/latest/core/connections.html?highlight=multiparams#sqlalchemy.engine.Connection.execute.params.object
but it not work, please tell me how to use `bulk_query`? | closed | 2018-11-05T06:52:57Z | 2018-11-14T03:47:31Z | https://github.com/kennethreitz/records/issues/166 | [] | mouday | 12 |
scikit-optimize/scikit-optimize | scikit-learn | 371 | Optimizing over a list defining points in the search space? | Is there a feature where, instead of using dimensions to define the search space, skopt will optimize on a list of points which define the search space?
This would be a useful feature if I wanted to optimize in a subset of the possible points of a space (rather than the entire space). | open | 2017-05-01T22:46:03Z | 2017-05-05T06:21:35Z | https://github.com/scikit-optimize/scikit-optimize/issues/371 | [
"API"
] | ardunn | 5 |
Lightning-AI/pytorch-lightning | machine-learning | 20,105 | What happens during training with HuggingFace models in eval mode? | ### Bug description
I'm using huggingface models with lightning, a use case that seems to be part of the [lightning examples](https://lightning.ai/lightning-ai/studios/finetune-hugging-face-bert-with-pytorch-lightning). However, a subtlety of the huggingface API is that models are loaded by default in `eval` mode, as [documented](https://huggingface.co/docs/transformers/en/main_classes/model#transformers.PreTrainedModel.from_pretrained). There is currently no check that within `LightningModule.training_step`, models are in `train` mode. If a `LightningModule.validation_step` is defined, lightning will put the model in `train` mode at the end of the validation step, however this is only after the first training epoch completes. If no validation step is defined, all of training is done in `eval` mode. The below example only crashes because of the assertion at the start of `training_step`.
While training in eval mode is not a bug that leads to a crash and is technically allowed when using pure pytorch, in lightning, where the details of training a pytorch model are supposed to be abstracted, enforcing such a constraint feels like it ought to be the default.
### What version are you seeing the problem on?
v2.2
### How to reproduce the bug
```python
import os
import torch
from lightning.pytorch import LightningModule, Trainer
from torch.utils.data import DataLoader, Dataset
from transformers import AutoModelForCausalLM, AutoTokenizer
hf_model = AutoModelForCausalLM.from_pretrained("openai-community/gpt2")
tok = AutoTokenizer.from_pretrained("openai-community/gpt2")
class MyDataset(Dataset):
def __getitem__(self, index):
return tok("hello world", return_tensors="pt")
def __len__(self):
return 1
class MyModel(LightningModule):
def __init__(self):
super().__init__()
self.model = hf_model
def training_step(self, batch, batch_idx):
assert self.model.training
loss = self.model(**batch).loss
return loss
def configure_optimizers(self):
return torch.optim.SGD(self.model.parameters(), lr=0.1)
def run():
train_data = DataLoader(MyDataset(), batch_size=1)
model = MyModel()
trainer = Trainer(
default_root_dir=os.getcwd(),
limit_train_batches=1,
num_sanity_val_steps=0,
max_epochs=1,
enable_model_summary=False,
)
trainer.fit(model, train_dataloaders=train_data)
if __name__ == "__main__":
run()
```
### Error messages and logs
Rather insidious as everything runs without crashing, I only discovered this because I was making a hybrid model with an RNN where cudnn RNN requires the model be in train mode, all my other models without RNN components trained to completion
### Environment
<details>
<summary>Current environment</summary>
```
#- PyTorch Lightning Version: 2.2.4
#- PyTorch Version: 2.1.1+cu121
#- Python version: 3.10.13
#- OS: Ubuntu 20.04.6 LTS
#- CUDA/cuDNN version: 12.1
#- GPU models and configuration: NVIDIA A100 80GB PCIe
#- How you installed Lightning(`conda`, `pip`, source): pip
```
</details>
### More info
_No response_ | closed | 2024-07-19T13:44:28Z | 2024-07-19T19:07:07Z | https://github.com/Lightning-AI/pytorch-lightning/issues/20105 | [
"bug"
] | StevenSong | 2 |
KaiyangZhou/deep-person-reid | computer-vision | 561 | can you tell me , why i am getting this kind of erros | Here I used the osnet_ain_x1_0 model,
I got many errors and problems re-identifying the same persons
Link : https://drive.google.com/file/d/1Vf58-oLO2OhS1Av44My6Y0ekmJOeNdmA/view?usp=sharing
**1) the same person came into the frame from a different side in another frame's time stamps
2) if collations occur I get another ID or else for some time is can't identify persons
3) Environment changes then identity also changes for the same person**
How can I calculate the accuracy of this output?
Can you tell me how can i solve this or which type of drawback occurs for particular things, so I can improve it and do better?
Will expect a positive response quickly.
If you solve this error, it would be a great help
| open | 2023-11-06T06:16:59Z | 2023-11-06T06:16:59Z | https://github.com/KaiyangZhou/deep-person-reid/issues/561 | [] | Arjunvankani | 0 |
gee-community/geemap | jupyter | 427 | Add GUI support for creating sankee plots | Reference: https://github.com/aazuspan/sankee
 | closed | 2021-04-15T01:30:10Z | 2021-05-11T15:42:42Z | https://github.com/gee-community/geemap/issues/427 | [
"Feature Request"
] | giswqs | 1 |
microsoft/JARVIS | pytorch | 9 | 建议发展一个替代chatgpt的选择，避免过早被拒访问而影响开源进展 | 据以往经验，为chatgpt这种在国内访问已被拒的生态组件做项目，如果做得好，都会受到审查牵连，影响后面的商业化进程，不是能翻就ok的，望重视早日落地成功 | closed | 2023-04-03T07:42:48Z | 2023-04-04T23:42:48Z | https://github.com/microsoft/JARVIS/issues/9 | [] | rexiyz | 6 |
huggingface/datasets | tensorflow | 6,882 | Connection Error When Using By-pass Proxies | ### Describe the bug
I'm currently using Clash for Windows as my proxy tunnel, after exporting HTTP_PROXY and HTTPS_PROXY to the port that clash provides🤔, it runs into a connection error saying "Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/2.19.1/metrics/seqeval/seqeval.py (ConnectionError(MaxRetryError("HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/2.19.1/metrics/seqeval/seqeval.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f969d391870>: Failed to establish a new connection: [Errno 111] Connection refused'))")))"
I have already read the documentation provided on the hugginface, but I think I didn't see the detailed instruction on how to set up proxies for this library.
### Steps to reproduce the bug
1. Turn on any proxy software like Clash / ShadosocksR etc.
2. export system varibles to the port provided by your proxy software in wsl (It's ok for other applications to use proxy expect dataset-library)
3. load any dataset from hugginface online
### Expected behavior
---------------------------------------------------------------------------
ConnectionError Traceback (most recent call last)
Cell In[33], [line 3](vscode-notebook-cell:?execution_count=33&line=3)
[1](vscode-notebook-cell:?execution_count=33&line=1) from datasets import load_metric
----> [3](vscode-notebook-cell:?execution_count=33&line=3) metric = load_metric("seqeval")
File ~/.local/lib/python3.10/site-packages/datasets/utils/deprecation_utils.py:46, in deprecated.<locals>.decorator.<locals>.wrapper(*args, **kwargs)
[44](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/utils/deprecation_utils.py:44) warnings.warn(warning_msg, category=FutureWarning, stacklevel=2)
[45](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/utils/deprecation_utils.py:45) _emitted_deprecation_warnings.add(func_hash)
---> [46](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/utils/deprecation_utils.py:46) return deprecated_function(*args, **kwargs)
File ~/.local/lib/python3.10/site-packages/datasets/load.py:2104, in load_metric(path, config_name, process_id, num_process, cache_dir, experiment_id, keep_in_memory, download_config, download_mode, revision, trust_remote_code, **metric_init_kwargs)
[2101](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2101) warnings.filterwarnings("ignore", message=".*https://huggingface.co/docs/evaluate$", category=FutureWarning)
[2103](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2103) download_mode = DownloadMode(download_mode or DownloadMode.REUSE_DATASET_IF_EXISTS)
-> [2104](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2104) metric_module = metric_module_factory(
[2105](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2105) path,
[2106](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2106) revision=revision,
[2107](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2107) download_config=download_config,
[2108](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2108) download_mode=download_mode,
[2109](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2109) trust_remote_code=trust_remote_code,
[2110](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2110) ).module_path
[2111](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2111) metric_cls = import_main_class(metric_module, dataset=False)
[2112](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2112) metric = metric_cls(
[2113](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2113) config_name=config_name,
[2114](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2114) process_id=process_id,
...
--> [633](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/utils/file_utils.py:633) raise ConnectionError(f"Couldn't reach {url} ({repr(head_error)})")
[634](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/utils/file_utils.py:634) elif response is not None:
[635](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/utils/file_utils.py:635) raise ConnectionError(f"Couldn't reach {url} (error {response.status_code})")
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/2.19.1/metrics/seqeval/seqeval.py (SSLError(MaxRetryError("HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/2.19.1/metrics/seqeval/seqeval.py (Caused by SSLError(SSLEOFError(8, '[SSL: UNEXPECTED_EOF_WHILE_READING] EOF occurred in violation of protocol (_ssl.c:1007)')))")))
### Environment info
- `datasets` version: 2.19.1
- Platform: Linux-5.10.102.1-microsoft-standard-WSL2-x86_64-with-glibc2.35
- Python version: 3.10.12
- `huggingface_hub` version: 0.23.0
- PyArrow version: 16.0.0
- Pandas version: 2.2.2
- `fsspec` version: 2024.2.0 | open | 2024-05-08T06:40:14Z | 2024-05-17T06:38:30Z | https://github.com/huggingface/datasets/issues/6882 | [] | MRNOBODY-ZST | 1 |
bmoscon/cryptofeed | asyncio | 357 | Support Crypto.com exchange | **Is your feature request related to a problem? Please describe.**
Crypto.com is a relevant exchange in the cryptocurrency space
**Describe the solution you'd like**
L2 Book, Ticker, Trades
**Describe alternatives you've considered**
n/a
**Additional context**
Add any other context or screenshots about the feature request here.
API docs look pretty solid. Supports REST and Websocket
https://exchange-docs.crypto.com/ | closed | 2020-12-14T18:46:50Z | 2021-11-23T23:44:22Z | https://github.com/bmoscon/cryptofeed/issues/357 | [
"Feature Request"
] | AlgoTrader5 | 2 |
huggingface/datasets | nlp | 7,168 | sd1.5 diffusers controlnet training script gives new error | ### Describe the bug
This will randomly pop up during training now
```
Traceback (most recent call last):
File "/workspace/diffusers/examples/controlnet/train_controlnet.py", line 1192, in <module>
main(args)
File "/workspace/diffusers/examples/controlnet/train_controlnet.py", line 1041, in main
for step, batch in enumerate(train_dataloader):
File "/usr/local/lib/python3.11/dist-packages/accelerate/data_loader.py", line 561, in __iter__
next_batch = next(dataloader_iter)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/torch/utils/data/dataloader.py", line 630, in __next__
data = self._next_data()
^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/torch/utils/data/dataloader.py", line 673, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/torch/utils/data/_utils/fetch.py", line 50, in fetch
data = self.dataset.__getitems__(possibly_batched_index)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/datasets/arrow_dataset.py", line 2746, in __getitems__
batch = self.__getitem__(keys)
^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/datasets/arrow_dataset.py", line 2742, in __getitem__
return self._getitem(key)
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/datasets/arrow_dataset.py", line 2727, in _getitem
formatted_output = format_table(
^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/datasets/formatting/formatting.py", line 639, in format_table
return formatter(pa_table, query_type=query_type)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/datasets/formatting/formatting.py", line 407, in __call__
return self.format_batch(pa_table)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/datasets/formatting/formatting.py", line 521, in format_batch
batch = self.python_features_decoder.decode_batch(batch)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/datasets/formatting/formatting.py", line 228, in decode_batch
return self.features.decode_batch(batch) if self.features else batch
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/datasets/features/features.py", line 2084, in decode_batch
[
File "/usr/local/lib/python3.11/dist-packages/datasets/features/features.py", line 2085, in <listcomp>
decode_nested_example(self[column_name], value, token_per_repo_id=token_per_repo_id)
File "/usr/local/lib/python3.11/dist-packages/datasets/features/features.py", line 1403, in decode_nested_example
return schema.decode_example(obj, token_per_repo_id=token_per_repo_id)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/datasets/features/image.py", line 188, in decode_example
image.load() # to avoid "Too many open files" errors
```
### Steps to reproduce the bug
Train on diffusers sd1.5 controlnet example script
This will pop up randomly, you can see in wandb below when i manually resume run everytime this error appears
### Expected behavior
Training to continue without above error
### Environment info
- datasets version: 3.0.0
- Platform: Linux-6.5.0-44-generic-x86_64-with-glibc2.35
- Python version: 3.11.9
- huggingface_hub version: 0.25.1
- PyArrow version: 17.0.0
- Pandas version: 2.2.3
- fsspec version: 2024.6.1
Training on 4090 | closed | 2024-09-25T01:42:49Z | 2024-09-30T05:24:03Z | https://github.com/huggingface/datasets/issues/7168 | [] | Night1099 | 3 |
junyanz/pytorch-CycleGAN-and-pix2pix | computer-vision | 911 | Edges shifted and mirrored in edge images after batch_hed.py and PostprocessHED.m | I am **reproducing the edges2shoes dataset for learning how to extract edges from image object by using HED**, it almost success expect a little strange problem: **part of the edges shifed and mirrored**. It looks like below, they are different from the pix2pix paper.
 
 
**My process followed the instruction strictly, which is at the top annotation of batch_hed.py and PostprocessHED.m**. such as in batch_hed.py:
HED batch processing script; modified from https://github.com/s9xie/hed/blob/master/examples/hed/HED-tutorial.ipynb
Step 1: download the hed repo: https://github.com/s9xie/hed
Step 2: download the models and protoxt, and put them under {caffe_root}/examples/hed/
Step 3: put this script under {caffe_root}/examples/hed/
Step 4: run the following script: python batch_hed.py --images_dir=/data/to/path/photos/ --hed_mat_dir=/data/to/path/hed_mat_files/
The code sometimes crashes after computation is done. Error looks like "Check failed: ... driver shutting down". You can just kill the job.
For large images, it will produce gpu memory issue. Therefore, you better resize the images before running this script.
Step 5: run the MATLAB post-processing script "PostprocessHED.m"
and in PostprocessHED.m:
HED batch processing script; modified from https://github.com/s9xie/hed/blob/master/examples/hed/HED-tutorial.ipynb
Step 1: download the hed repo: https://github.com/s9xie/hed
Step 2: download the models and protoxt, and put them under {caffe_root}/examples/hed/
Step 3: put this script under {caffe_root}/examples/hed/
Step 4: run the following script: python batch_hed.py --images_dir=/data/to/path/photos/ --hed_mat_dir=/data/to/path/hed_mat_files/
The code sometimes crashes after computation is done. Error looks like "Check failed: ... driver shutting down". You can just kill the job.
For large images, it will produce gpu memory issue. Therefore, you better resize the images before running this script.
Step 5: run the MATLAB post-processing script "PostprocessHED.m"
Some facts may help:
- I **used a offical caffe docker** for convenience;
- The images are form the edges2shoes dataset, and i cut the paired image in two: one edge image and one object;
- image size is 256x256;
- In PostprocessHED.m it error frist, said can't find 'predict' variable, I changed the code in function GetEdge, from load(filePath) to load(filePath, 'predict');
I got stuck here for a long time, searched many issues and can not find a similar one, so I opened a new issue for it. Could you please take a look at this issue ? Thanks a lot ! @junyanz
| closed | 2020-02-06T03:08:52Z | 2020-02-14T19:01:09Z | https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix/issues/911 | [] | diaosiji | 10 |
jina-ai/serve | deep-learning | 5,399 | What is the order of multi-replicas flow's result? | **Describe the bug**
Hi there i have a flow like clip-as-service as below
```python
class Inference(Executor):
def _preproc_texts(self, docs: 'DocumentArray'):
with self.monitor(
name='preprocess_texts_seconds',
documentation='texts preprocess time in seconds',
):
return preproc_text(docs, tokenizer=self.per_tokenizer, device=self.per_device, args=self.per_args)
@requests
async def inference(self, docs: DocumentArray, parameters, **kwargs):
with torch.no_grad():
for minibatch, batch_data in docs.map_batch(self._preproc_texts, batch_size=200, pool=pool):
minibatch.tensors = (model(**batch_data).cpu().numpy())
return docs
if __name__ == "__main__":
torch.multiprocessing.set_start_method("spawn")
f = Flow(port=8888).add(uses=Inference, replicas=2)
with f:
f.block()
```
**Here i have a docArray with 180 samples. And then i found that one replicas has been given 100 samples and the other one has been given 80 samples.**
#### There are two questions or bugs
1. What's your load-balance strategy? Because the batch_size i set is 200. It does not reach the upper bound. Why it will use all of two replicas?
2. After i request too many times, i find that there will be two results for the same docArray.tensors.
- [80 samples results,100 samples results]
- [100 samples results,80 samples results]
So it seems like you will divide the docArray into two partitions.And they will inference at the same time with two replicas.
The final result is a combination of the results of each partition.The order is according to which partition can be competed faster.
So is there any way to keep the order of result as the same as the input docArray? Or i need to reorganize the result according to the text after querying?
**Environment**
<!-- Run `jina --version-full` and copy paste the output here -->
- jina 3.10.1
- docarray 0.17.0
- jcloud 0.0.35
- jina-hubble-sdk 0.19.1
- jina-proto 0.1.13
- protobuf 3.20.0
- proto-backend cpp
- grpcio 1.48.0
- pyyaml 5.3.1
- python 3.7.0
- platform Linux
- platform-release 3.10.0-862.14.1.5.h442.eulerosv2r7.x86_64
- platform-version #1 SMP Fri May 15 22:01:58 UTC 2020
- architecture x86_64
- processor x86_64
- uid 171880166524263
- session-id 22b0ff44-65b2-11ed-8def-9c52f8450567
- uptime 2022-11-16T21:25:27.563941
- ci-vendor (unset)
- internal False
* JINA_DEFAULT_HOST (unset)
* JINA_DEFAULT_TIMEOUT_CTRL (unset)
* JINA_DEPLOYMENT_NAME (unset)
* JINA_DISABLE_UVLOOP (unset)
* JINA_EARLY_STOP (unset)
* JINA_FULL_CLI (unset)
* JINA_GATEWAY_IMAGE (unset)
* JINA_GRPC_RECV_BYTES (unset)
* JINA_GRPC_SEND_BYTES (unset)
* JINA_HUB_NO_IMAGE_REBUILD (unset)
* JINA_LOG_CONFIG (unset)
* JINA_LOG_LEVEL (unset)
* JINA_LOG_NO_COLOR (unset)
* JINA_MP_START_METHOD (unset)
* JINA_OPTOUT_TELEMETRY (unset)
* JINA_RANDOM_PORT_MAX (unset)
* JINA_RANDOM_PORT_MIN (unset)
**Screenshots**
<!-- If applicable, add screenshots to help explain your problem. --> | closed | 2022-11-16T13:56:47Z | 2022-11-18T10:10:47Z | https://github.com/jina-ai/serve/issues/5399 | [
"area/community"
] | wqh17101 | 18 |
autokey/autokey | automation | 3 | AutoKey - Collaboration ... | Hi. I'm an active AutoKey user (original version). I just found your project. It's good to see someone advancing AutoKey.
Would any of your code be useful to the original AutoKey?
Chris Deckter (one of the original developers) left the project a couple of years ago.
We currently have a volunteer developer, Jordan Metzmeier, who has fixed some bugs (for which we are very grateful!), but isn't otherwise very active. His code is at the address below. You may find some fixes you can use with your version.
https://github.com/jmetzmeier/autokey
Would you have any interest in getting involved?
It's my impression that a lot of people have yet to move to Python 3, so there still is a need for the Python 2.7 version.
Thanks.
Joe
| closed | 2014-09-22T22:44:02Z | 2016-11-08T03:28:54Z | https://github.com/autokey/autokey/issues/3 | [] | josephj11 | 3 |
yeongpin/cursor-free-vip | automation | 162 | 注册新账号，提示成功，但是cursor没有登录的信息 | 
macbook pro，注册新账号，打开的chrome是无痕模式，导致登录信息没有保存，怎么获取注册的账号密码？ | closed | 2025-03-08T05:33:14Z | 2025-03-09T03:35:02Z | https://github.com/yeongpin/cursor-free-vip/issues/162 | [] | ztever | 0 |
OFA-Sys/Chinese-CLIP | nlp | 215 | fairseq包的版本是多少？ | `Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/kemove/anaconda3/envs/nlp/lib/python3.11/site-packages/modelscope/pipelines/builder.py", line 147, in pipeline
pipeline_props = {'type': pipeline_name}
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/kemove/anaconda3/envs/nlp/lib/python3.11/site-packages/modelscope/pipelines/builder.py", line 59, in build_pipeline
Args:
File "/home/kemove/anaconda3/envs/nlp/lib/python3.11/site-packages/modelscope/utils/registry.py", line 184, in build_from_cfg
LazyImportModule.import_module(sig)
File "/home/kemove/anaconda3/envs/nlp/lib/python3.11/site-packages/modelscope/utils/import_utils.py", line 459, in import_module
requirements = LazyImportModule.AST_INDEX[REQUIREMENT_KEY][
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/kemove/anaconda3/envs/nlp/lib/python3.11/importlib/__init__.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "<frozen importlib._bootstrap>", line 1204, in _gcd_import
File "<frozen importlib._bootstrap>", line 1176, in _find_and_load
File "<frozen importlib._bootstrap>", line 1147, in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 690, in _load_unlocked
File "<frozen importlib._bootstrap_external>", line 940, in exec_module
File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed
File "/home/kemove/anaconda3/envs/nlp/lib/python3.11/site-packages/modelscope/pipelines/multi_modal/multi_modal_embedding_pipeline.py", line 9, in <module>
from modelscope.preprocessors.multi_modal import CLIPPreprocessor, Preprocessor
File "/home/kemove/anaconda3/envs/nlp/lib/python3.11/site-packages/modelscope/preprocessors/multi_modal.py", line 29, in <module>
from .ofa import * # noqa
^^^^^^^^^^^^^^^^^^
File "/home/kemove/anaconda3/envs/nlp/lib/python3.11/site-packages/modelscope/preprocessors/ofa/__init__.py", line 2, in <module>
from .asr import OfaASRPreprocessor
File "/home/kemove/anaconda3/envs/nlp/lib/python3.11/site-packages/modelscope/preprocessors/ofa/asr.py", line 13, in <module>
from fairseq.data.audio.speech_to_text_dataset import S2TDataConfig
File "/home/kemove/anaconda3/envs/nlp/lib/python3.11/site-packages/fairseq/data/audio/speech_to_text_dataset.py", line 19, in <module>
from fairseq.data import ConcatDataset, Dictionary, FairseqDataset, ResamplingDataset
File "/home/kemove/anaconda3/envs/nlp/lib/python3.11/site-packages/fairseq/__init__.py", line 20, in <module>
from fairseq.distributed import utils as distributed_utils
File "/home/kemove/anaconda3/envs/nlp/lib/python3.11/site-packages/fairseq/distributed/__init__.py", line 7, in <module>
from .fully_sharded_data_parallel import (
File "/home/kemove/anaconda3/envs/nlp/lib/python3.11/site-packages/fairseq/distributed/fully_sharded_data_parallel.py", line 10, in <module>
from fairseq.dataclass.configs import DistributedTrainingConfig
File "/home/kemove/anaconda3/envs/nlp/lib/python3.11/site-packages/fairseq/dataclass/configs.py", line 1104, in <module>
@dataclass
^^^^^^^^^
File "/home/kemove/anaconda3/envs/nlp/lib/python3.11/dataclasses.py", line 1230, in dataclass
return wrap(cls)
^^^^^^^^^
File "/home/kemove/anaconda3/envs/nlp/lib/python3.11/dataclasses.py", line 1220, in wrap
return _process_class(cls, init, repr, eq, order, unsafe_hash,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/kemove/anaconda3/envs/nlp/lib/python3.11/dataclasses.py", line 958, in _process_class
cls_fields.append(_get_field(cls, name, type, kw_only))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/kemove/anaconda3/envs/nlp/lib/python3.11/dataclasses.py", line 815, in _get_field
raise ValueError(f'mutable default {type(f.default)} for field '
ValueError: mutable default <class 'fairseq.dataclass.configs.CommonConfig'> for field common is not allowed: use default_factory` | closed | 2023-09-28T09:52:26Z | 2023-10-08T02:10:12Z | https://github.com/OFA-Sys/Chinese-CLIP/issues/215 | [] | AnitaSherry | 2 |
PokemonGoF/PokemonGo-Bot | automation | 5,585 | what is the password for | I cant log in now there is a password insert for the prompt screen
STOP ! ! !
Read the following before creating anything (or you will have your issue/feature request closed without notice)
1. Please only create an ISSUE or a FEATURE REQUEST - don't mix the two together in one item
2. For a Feature Request please only fill out the FEATURE REQUEST section
3. For a Issue please only fill out the ISSUE section
4. Issues are NOT to be used for help/config problems/support - use the relevant slack channels as per the README
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6. Delete all irrelevant sections not related to your issue/feature request (including this top section)
===============ISSUE SECTION===============
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1. Have you validated that your config.json is valid JSON? Use http://jsonlint.com/ to check.
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4. All Issue sections MUST be completed to help us determine the actual problem and find its cause
-->
### Expected Behavior
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### Actual Behavior
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### Your FULL config.json (remove your username, password, gmapkey and any other private info)
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<!-- dev or master -->
Git Commit:
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Any other relevant files/configs (eg: path files)
<!-- Anything else which may be of relevance -->
<!-- ===============END OF ISSUE SECTION=============== -->
<!-- Note: Delete these lines and everything BELOW if creating an Issue -->
<!-- ===============FEATURE REQUEST SECTION===============
Before you create a Feature Request, please check the following:
1. Have you [searched our feature tracker](https://github.com/PokemonGoF/PokemonGo-Bot/labels/Feature%20Request) first to ensure someone else hasn't already come up with the same great idea. If so then be sure to +1 it
2. While you're there, be sure to vote on other feature requests to let the devs know what is important to you.
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<!-- Note: Delete this line and everything ABOVE if creating a Feature Request -->
### Short Description
<!-- Tell us a short description of your request -->
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| closed | 2016-09-21T03:37:46Z | 2016-09-21T05:56:14Z | https://github.com/PokemonGoF/PokemonGo-Bot/issues/5585 | [] | ammohawk | 1 |
iterative/dvc | machine-learning | 10,194 | pull: "No file hash info found" and checkout fails when pulling frozen imported url that is a directory that has subsequently changed | # Bug Report
## Description
I have used `dvc import-url` to track a GCS directory that is updated daily with incremental new data. [The documentation](https://dvc.org/doc/user-guide/data-management/importing-external-data#how-external-outputs-work) suggests that once the data is imported, it is frozen and DVC should not attempt to download changes from the tracked URL unless `dvc update` is run.
It also says that
> During [dvc push](https://dvc.org/doc/command-reference/push), DVC will upload the version of the data tracked by [the .dvc file] to the [DVC remote](https://dvc.org/doc/user-guide/data-management/remote-storage) so that it is backed up in case you need to recover it.
Instead, when I `dvc push`, the log messages suggest the files were uploaded, but nothing shows up in the remote. y imported data to remote, `dvc pull` from a fresh checkout downloads all the files from the remote url (including updated ones), and fails to check out the frozen version of the data as expected.
### Reproduce
I created a minimal example using a public GCS bucket in my account:
1. mkdir dvc-import-issue & cd dvc-import-issue
2. git init
3. dvc init
4. dvc import-url gs://hasha-ds-public/test_dir/ test_dir
5. dvc remote add origin gs://hasha-ds-public/test_remote/
6. dvc push -r origin
Output from `dvc push` is
```
Collecting |5.00 [00:00, 441entry/s]
Pushing |0.00 [00:01, ?file/s]
Collecting hasha-ds-public/test_remote/ on gs |5.00 [00:01, 3.29entry/s]
4 files pushed
```
However I later noticed that no files had been pushed to the remote at all despite the misleading log message. I was able to correct this by running `dvc import-url gs://hasha-ds-public/test_dir --to-remote`, but this feels like another bug.
8. git add .dvc/config test_dir.dvc .gitignore
9. git commit -m "Committed and pushed"
Now set up a fresh clone of the project
10. cd ..
11. git clone dvc-import-url-pull-issue dvc-import-url-pull-issue2
Add another file to the tracked URL
12. echo "more stuff" > blah.txt & gsutil cp blah.txt gs://hasha-ds-public/test_dir/
Finally, try pulling the frozen data associated with the imported URL from remote into the fresh clone
13. cd dvc-import-issue2
14. dvc pull -r origin
### Result
```
Collecting |5.00 [00:00, 11.3entry/s]
Fetching
Building workspace index |0.00 [00:00, ?entry/s]
Comparing indexes |6.00 [00:00, 14.9entry/s]
WARNING: No file hash info found for '/Users/alexhasha/repos/dvc-import-issue2/test_dir/baz.txt'. It won't be created.
WARNING: No file hash info found for '/Users/alexhasha/repos/dvc-import-issue2/test_dir/blah.txt'. It won't be created.
WARNING: No file hash info found for '/Users/alexhasha/repos/dvc-import-issue2/test_dir/bar.txt'. It won't be created.
WARNING: No file hash info found for '/Users/alexhasha/repos/dvc-import-issue2/test_dir/foo.txt'. It won't be created.
Applying changes |0.00 [00:00, ?file/s]
4 files fetched
ERROR: failed to pull data from the cloud - Checkout failed for following targets:
test_dir
Is your cache up to date?
<https://error.dvc.org/missing-files>
```
Note that it's trying to checkout `blah.txt` in the error message, though that file wasn't present when the directory was imported and test_dir.dvc suggests there should only be 3 files in the directory.*-
I have pushed this repository to https://github.com/ahasha/dvc-import-url-pull-issue . You should be able to reproduce the error message by cloning it and running `dvc pull -r origin`.
### Expected
1. After running `dvc import-url`, `dvc push` should upload the version of the data tracked by the created .dvc file to the remote
2. In a fresh clone of the repository, `dvc pull` should retrieve the version of the data tracked by the .dvc file from the remote, and not download anything new from the tracked URL.
### Environment information
**Output of `dvc doctor`:**
```console
DVC version: 3.36.0 (pip)
-------------------------
Platform: Python 3.11.4 on macOS-14.1.2-x86_64-i386-64bit
Subprojects:
dvc_data = 3.2.0
dvc_objects = 3.0.0
dvc_render = 1.0.0
dvc_task = 0.3.0
scmrepo = 2.0.2
Supports:
gs (gcsfs = 2023.12.2.post1),
http (aiohttp = 3.9.1, aiohttp-retry = 2.8.3),
https (aiohttp = 3.9.1, aiohttp-retry = 2.8.3)
Config:
Global: /Users/alexhasha/Library/Application Support/dvc
System: /Library/Application Support/dvc
Cache types: reflink, hardlink, symlink
Cache directory: apfs on /dev/disk1s3s1
Caches: local
Remotes: gs
Workspace directory: apfs on /dev/disk1s3s1
Repo: dvc, git
Repo.site_cache_dir: /Library/Caches/dvc/repo/a48422a1ed3a65e3efe064e5b18830a7
```
| closed | 2023-12-22T18:09:31Z | 2024-01-03T11:14:18Z | https://github.com/iterative/dvc/issues/10194 | [
"bug",
"regression",
"A: data-sync"
] | ahasha | 10 |
Sanster/IOPaint | pytorch | 423 | [BUG] [iopaint] with local_files_only parm, sd model failed to load | **Model**
"Sanster/PowerPaint-V1-stable-diffusion-inpainting"
"kandinsky-community/kandinsky-2-2-decoder-inpaint"
"diffusers/stable-diffusion-xl-1.0-inpainting-0.1"
**Describe the bug**
starting the iopaint app with ` local_files_only=True`, and the parm will not be passed to huggingface model, which causes the model fails to load.
**Screenshots**
**System Info**
Software version used
- lama-cleaner:
- pytorch:
- CUDA:
| closed | 2024-01-16T03:00:58Z | 2024-01-16T15:24:24Z | https://github.com/Sanster/IOPaint/issues/423 | [] | huangzhike | 6 |
quokkaproject/quokka | flask | 167 | Error on instalation in OSX 10.8 | Well, i try installing and got these erros after run the command $ pip install -r requirements.txt
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/_imaging.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/decode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/encode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/map.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/display.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/outline.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/path.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Access.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/AlphaComposite.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Antialias.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Bands.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/BitDecode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Blend.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Chops.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Convert.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/ConvertYCbCr.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Copy.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Crc32.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Crop.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Dib.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Draw.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Effects.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/EpsEncode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/File.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Fill.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Filter.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/FliDecode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Geometry.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/GetBBox.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/GifDecode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/GifEncode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/HexDecode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Histo.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/JpegDecode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/JpegEncode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/LzwDecode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Matrix.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/ModeFilter.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/MspDecode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Negative.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Offset.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Pack.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/PackDecode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Palette.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Paste.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Quant.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/QuantOctree.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/QuantHash.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/QuantHeap.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/PcdDecode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/PcxDecode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/PcxEncode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Point.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/RankFilter.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/RawDecode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/RawEncode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Storage.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/SunRleDecode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/TgaRleDecode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Unpack.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/UnpackYCC.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/UnsharpMask.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/XbmDecode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/XbmEncode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/ZipDecode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/ZipEncode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/TiffDecode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Incremental.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Jpeg2KDecode.o'
clang: error: no such file or directory: 'build/temp.macosx-10.8-intel-2.7/libImaging/Jpeg2KEncode.o'
error: command 'clang' failed with exit status 1
---
Cleaning up...
Command /usr/bin/python -c "import setuptools, tokenize;**file**='/private/var/folders/m5/t7lxkrz95d34s1qkqljd_4n80000gn/T/pip_build_londerson/Pillow/setup.py';exec(compile(getattr(tokenize, 'open', open)(**file**).read().replace('\r\n', '\n'), **file**, 'exec'))" install --record /var/folders/m5/t7lxkrz95d34s1qkqljd_4n80000gn/T/pip-COqmtB-record/install-record.txt --single-version-externally-managed --compile failed with error code 1 in /private/var/folders/m5/t7lxkrz95d34s1qkqljd_4n80000gn/T/pip_build_londerson/Pillow
Storing debug log for failure in /Users/londerson/Library/Logs/pip.log
| closed | 2014-10-21T00:30:06Z | 2015-07-16T02:56:26Z | https://github.com/quokkaproject/quokka/issues/167 | [] | londerson | 5 |
Gozargah/Marzban | api | 767 | درخواست اضافه شدن Shadowsocks 2022 | سلام، Shadowsocks 2022 از Xray-core v1.6.0 اضافه شده اما تو مرزبان هنوز پشتیبانی نمیشه
تستهایی که کردم کیفیت بهتری نسبت به Shadowsocks AEAD داره و به این راحتیها بسته نمیشه ( حداقل فعلا روی روشهای tlsدار زوم کردن)
با توجه به اینکه هسته Xray این قابلیت رو ساپورت میکنه لطفا اضافه شدن این مورد رو بررسی و در صورت امکان در اولویت قرار بدین ممنون میشم.
https://github.com/XTLS/Xray-examples/tree/main/Shadowsocks-2022
| closed | 2024-01-31T07:57:43Z | 2024-01-31T17:15:06Z | https://github.com/Gozargah/Marzban/issues/767 | [
"Duplicate"
] | 123asd321dsa | 1 |
KevinMusgrave/pytorch-metric-learning | computer-vision | 723 | Bug in MultiSimilarityMiner? | Hi,
is it expected that the MultiSimilarityMiner will produce positive pairs that don't actually have the same label?
For example one of my batches has items with the following labels (this is with a small batch size of only 8 just to illustrate the problem):
`tensor([ 15, 15, 15, 15, 169, 169, 169, 169], device='mps:0')`
I use the MultiSimilarityMiner to mine pairs for MultiSimilarityLoss. If i print out the values of mat, pos_mask, and neg_mask in the compute_loss function of MultiSimilarityLoss, they are
```
tensor([[1.0000, 0.9996, 0.9975, 0.9994, 0.9948, 0.9836, 0.9968, 0.9975],
[0.9996, 1.0000, 0.9952, 0.9981, 0.9919, 0.9798, 0.9950, 0.9963],
[0.9975, 0.9952, 1.0000, 0.9991, 0.9977, 0.9879, 0.9993, 0.9980],
[0.9994, 0.9981, 0.9991, 1.0000, 0.9974, 0.9876, 0.9979, 0.9975],
[0.9948, 0.9919, 0.9977, 0.9974, 1.0000, 0.9960, 0.9947, 0.9917],
[0.9836, 0.9798, 0.9879, 0.9876, 0.9960, 1.0000, 0.9823, 0.9767],
[0.9968, 0.9950, 0.9993, 0.9979, 0.9947, 0.9823, 1.0000, 0.9992],
[0.9975, 0.9963, 0.9980, 0.9975, 0.9917, 0.9767, 0.9992, 1.0000]],
device='mps:0', grad_fn=<MmBackward0>)
tensor([[0., 1., 1., 1., 1., 1., 1., 1.],
[1., 0., 1., 1., 1., 1., 1., 1.],
[1., 1., 0., 1., 1., 1., 1., 1.],
[1., 1., 1., 0., 1., 1., 1., 1.],
[1., 1., 1., 1., 0., 1., 1., 1.],
[1., 1., 1., 1., 1., 0., 1., 1.],
[1., 1., 1., 1., 1., 1., 0., 1.],
[1., 1., 1., 1., 1., 1., 1., 0.]], device='mps:0')
tensor([[0., 0., 0., 0., 1., 1., 1., 1.],
[0., 0., 0., 0., 1., 1., 1., 1.],
[0., 0., 0., 0., 1., 1., 1., 1.],
[0., 0., 0., 0., 1., 1., 1., 1.],
[1., 1., 1., 1., 0., 0., 0., 0.],
[1., 1., 1., 1., 0., 0., 0., 0.],
[1., 1., 1., 1., 0., 0., 0., 0.],
[1., 1., 1., 1., 0., 0., 0., 0.]], device='mps:0')
```
This is right at the beginning of training so the similarity scores in mat are total garbage, but the pos_mask looks wrong to me. It has selected every pair as positive, including those that don't share the same ID. Is that expected for some reason?
| open | 2024-10-21T17:09:12Z | 2024-10-23T20:25:12Z | https://github.com/KevinMusgrave/pytorch-metric-learning/issues/723 | [] | kazimpal87 | 6 |
PedroBern/django-graphql-auth | graphql | 72 | Package does not support custom user model. | I have been using this package for a little while now and I have some issues.
My customer user models have the following fields defined.
1. Full name.
2. Email
But when I installed this package I was given this error which states.
Unknown field(s) (last_name, first_name) specified for User
I do not have a last name and first name field specified in my custom user model, How do I override this ??? | open | 2020-10-10T22:20:00Z | 2021-01-25T03:10:40Z | https://github.com/PedroBern/django-graphql-auth/issues/72 | [] | udemezue01 | 5 |
tox-dev/tox | automation | 3,095 | doc building broken on Python 3.11 | Looks like we have an issue in combination with the `furo` theme
```
Extension error (furo):
Handler <function _html_page_context at 0x7fbb82980ae0> for event 'html-page-context' threw an exception (exception: This documentation is not using `furo.css` as the stylesheet. If you have set `html_style` in your conf.py file, remove it.)
```
FWIW, we do not use `html_style` in our `conf.py`.
@pradyunsg Do you have an idea why this breaks now? It looks like it still worked a couple of days ago, and curiously both the failing and the working build was with `furo==2023.7.26`, and our `conf.py` did not change in the last 3 months.
_Originally posted by @jugmac00 in https://github.com/tox-dev/tox/issues/3094#issuecomment-1681987647_
| closed | 2023-08-17T13:07:09Z | 2023-08-17T15:10:51Z | https://github.com/tox-dev/tox/issues/3095 | [
"help:wanted"
] | jugmac00 | 2 |
MagicStack/asyncpg | asyncio | 1,181 | fails to build with Python 3.13 | * **asyncpg version**: 0.29.0
* **Python version**: 3.13.0rc2
* **Platform**: Linux
* **Did you install asyncpg with pip?**: Yes
* **If you built asyncpg locally, which version of Cython did you use?**: n/a
* **Can the issue be reproduced under both asyncio and
[uvloop](https://github.com/magicstack/uvloop)?**: yes
Fails to build on Python 3.13. There's been various API changes.
```
asyncpg/pgproto/pgproto.c:23886:18: warning: ‘__pyx_f_7asyncpg_7pgproto_7pgproto_json_encode’ defined but not used [-Wunused-function]
23886 | static PyObject *__pyx_f_7asyncpg_7pgproto_7pgproto_json_encode(struct __pyx_obj_7asyncpg_7pgproto_7pgproto_CodecContext *__pyx_v_settings, struct __pyx_obj_7asyncpg_7pgproto_7pgproto_WriteBuffer *__pyx_v_buf, PyObject *__pyx_v_obj) {
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
```
```
/home/username/.pyenv/versions/3.13.0rc2/include/python3.13/cpython/longobject.h:111:17: note: declared here
111 | PyAPI_FUNC(int) _PyLong_AsByteArray(PyLongObject* v,
| ^~~~~~~~~~~~~~~~~~~
```
Read more: https://github.com/MagicStack/uvloop/issues/603 | closed | 2024-09-15T09:26:09Z | 2024-10-24T04:29:22Z | https://github.com/MagicStack/asyncpg/issues/1181 | [] | Cikmo | 13 |
slackapi/python-slack-sdk | asyncio | 712 | Add timeout support to API calls | ### It isn't possible to set timeout for API calls
I couldn't find timeout option in WebhookClient `__init__` or it's `send` method.
For any reason maybe API calls takes much time to be received and responded.
It can be performed with asking user to set timeout when instantiating client(absolutely with default value for backward compatibility).
| closed | 2020-06-03T13:18:21Z | 2020-06-05T01:11:33Z | https://github.com/slackapi/python-slack-sdk/issues/712 | [
"Version: 2x",
"enhancement",
"web-client"
] | DanialErfanian | 2 |
kizniche/Mycodo | automation | 1,127 | I reinstall the mycodo,there is a new Issues run out. | pi@raspberrypi:~ $ journalctl -u mycodoflask | tail -n 50
-- Logs begin at Thu 2019-02-14 18:11:59 CST, end at Tue 2021-12-21 22:26:23 CST. --
12月 21 22:22:32 raspberrypi systemd[1]: Started gunicorn daemon for Mycodo flask web user interface.
12月 21 22:22:36 raspberrypi gunicorn[507]: Traceback (most recent call last):
12月 21 22:22:36 raspberrypi gunicorn[507]: File "/var/mycodo-root/env/bin/gunicorn", line 5, in <module>
12月 21 22:22:36 raspberrypi gunicorn[507]: from gunicorn.app.wsgiapp import run
12月 21 22:22:36 raspberrypi gunicorn[507]: ModuleNotFoundError: No module named 'gunicorn'
12月 21 22:22:36 raspberrypi systemd[1]: mycodoflask.service: Main process exited, code=exited, status=1/FAILURE
12月 21 22:22:36 raspberrypi systemd[1]: mycodoflask.service: Failed with result 'exit-code'.
| closed | 2021-12-21T14:39:47Z | 2022-01-28T22:50:21Z | https://github.com/kizniche/Mycodo/issues/1127 | [] | anyunfeifei | 3 |
RobertCraigie/prisma-client-py | asyncio | 124 | Global aliases cause confusing error message | <!--
Thanks for helping us improve Prisma Client Python! 🙏 Please follow the sections in the template and provide as much information as possible about your problem, e.g. by enabling additional logging output.
See https://prisma-client-py.readthedocs.io/en/latest/logging/ for how to enable additional logging output.
-->
## Bug description
<!-- A clear and concise description of what the bug is. -->
When a field overlaps with a global alias used for query building, a confusing error message is shown
## How to reproduce
<!--
Steps to reproduce the behavior:
1. Go to '...'
2. Change '....'
3. Run '....'
4. See error
-->
```py
import asyncio
from prisma import Client
async def main() -> None:
client = Client()
await client.connect()
user = await client.user.create(
data={
'name': 'Robert',
'order_by': 'age',
}
)
print(user)
if __name__ == '__main__':
asyncio.run(main())
```
Running the above script raises the following error:
```
prisma.errors.MissingRequiredValueError: Failed to validate the query: `Unable to match input value to any allowed input type for the field. Parse errors: [Query parsing/validation error at `Mutation.createOneUser.data.UserCreateInput.order_by`: A value is required but not set., Query parsing/validation error at `Mutation.createOneUser.data.UserUncheckedCreateInput.order_by`: A value is required but not set.]` at `Mutation.createOneUser.data`
```
## Expected behavior
<!-- A clear and concise description of what you expected to happen. -->
This should be a valid query, however supporting this would require a massive refactor of our query builder.
The part of this issue that is considered a bug is the confusing error message, we should disallow generating a client that will result in an invalid internal query being generated.
## Prisma information
<!-- Your Prisma schema, Prisma Client Python queries, ...
Do not include your database credentials when sharing your Prisma schema! -->
```prisma
datasource db {
provider = "sqlite"
url = "file:tmp.db"
}
generator db {
provider = "prisma-client-py"
interface = "asyncio"
recursive_type_depth = -1
}
model User {
id String @id @default(cuid())
name String
order_by String
}
``` | closed | 2021-11-16T12:56:09Z | 2021-11-18T08:23:05Z | https://github.com/RobertCraigie/prisma-client-py/issues/124 | [
"bug/2-confirmed",
"kind/bug"
] | RobertCraigie | 0 |
graphql-python/graphene-django | graphql | 792 | 2.5.0 to 2.6.0 error: TypeError: issubclass() arg 1 must be a class | Hello,
Thanks for all the work on the new release.
I am however getting this error when upgrading to 2.6.0 from 2.5.0 and I just wanted to make sure I understand the change.
```py
Traceback (most recent call last):
File "src/manage.py", line 22, in <module>
execute_from_command_line(sys.argv)
File "/root/.local/share/virtualenvs/app-4PlAip0Q/lib/python3.7/site-packages/django/core/management/__init__.py", line 381, in execute_from_command_line
utility.execute()
File "/root/.local/share/virtualenvs/app-4PlAip0Q/lib/python3.7/site-packages/django/core/management/__init__.py", line 375, in execute
self.fetch_command(subcommand).run_from_argv(self.argv)
File "/root/.local/share/virtualenvs/app-4PlAip0Q/lib/python3.7/site-packages/django/core/management/base.py", line 323, in run_from_argv
self.execute(*args, **cmd_options)
File "/root/.local/share/virtualenvs/app-4PlAip0Q/lib/python3.7/site-packages/django/core/management/base.py", line 361, in execute
self.check()
File "/root/.local/share/virtualenvs/app-4PlAip0Q/lib/python3.7/site-packages/django/core/management/base.py", line 390, in check
include_deployment_checks=include_deployment_checks,
File "/root/.local/share/virtualenvs/app-4PlAip0Q/lib/python3.7/site-packages/django/core/management/commands/migrate.py", line 65, in _run_checks
issues.extend(super()._run_checks(**kwargs))
File "/root/.local/share/virtualenvs/app-4PlAip0Q/lib/python3.7/site-packages/django/core/management/base.py", line 377, in _run_checks
return checks.run_checks(**kwargs)
File "/root/.local/share/virtualenvs/app-4PlAip0Q/lib/python3.7/site-packages/django/core/checks/registry.py", line 72, in run_checks
new_errors = check(app_configs=app_configs)
File "/root/.local/share/virtualenvs/app-4PlAip0Q/lib/python3.7/site-packages/django/contrib/admin/checks.py", line 111, in check_dependencies
if not _contains_subclass('django.contrib.auth.middleware.AuthenticationMiddleware', settings.MIDDLEWARE):
File "/root/.local/share/virtualenvs/app-4PlAip0Q/lib/python3.7/site-packages/django/contrib/admin/checks.py", line 43, in _contains_subclass
candidate_cls = import_string(path)
File "/root/.local/share/virtualenvs/app-4PlAip0Q/lib/python3.7/site-packages/django/utils/module_loading.py", line 17, in import_string
module = import_module(module_path)
File "/root/.local/share/virtualenvs/app-4PlAip0Q/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "<frozen importlib._bootstrap>", line 1006, in _gcd_import
File "<frozen importlib._bootstrap>", line 983, in _find_and_load
File "<frozen importlib._bootstrap>", line 967, in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 677, in _load_unlocked
File "<frozen importlib._bootstrap_external>", line 728, in exec_module
File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
File "/app/src/ems_api/middleware.py", line 5, in <module>
from ems.schema import loaders as ems_loaders, nodes
File "/app/src/ems/schema/nodes.py", line 44, in <module>
class BenefitSetNode(graphene_django.DjangoObjectType):
File "/app/src/ems/schema/nodes.py", line 48, in BenefitSetNode
benefits = fields.DjangoListField("ems.schema.nodes.BenefitNode")
File "/root/.local/share/virtualenvs/app-4PlAip0Q/lib/python3.7/site-packages/graphene_django/fields.py", line 23, in __init__
_type, DjangoObjectType
TypeError: issubclass() arg 1 must be a class
```
Does this mean I can no longer pass strings into `DjangoListField`?
e.g. `benefits = fields.DjangoListField("ems.schema.nodes.BenefitNode")` | closed | 2019-10-01T22:05:00Z | 2020-03-13T10:05:36Z | https://github.com/graphql-python/graphene-django/issues/792 | [] | kayluhb | 4 |
JaidedAI/EasyOCR | pytorch | 657 | combine Arabic with bengali in same image | easyocr works with images containing english+any other language with it,but i have samples where bengali and arabic both are present in same image and this approach doesn't work : `reader = easyocr.Reader(['en','bn','ar'])` or even `reader = easyocr.Reader(['bn','ar'])`
is there any way to use easyocr on samples where both bengali and arabic are present? | closed | 2022-02-03T15:02:38Z | 2024-04-16T09:59:38Z | https://github.com/JaidedAI/EasyOCR/issues/657 | [] | mobassir94 | 5 |
AirtestProject/Airtest | automation | 1,200 | 安装完最新的appium的wda，airtest无法连接IOS | :bulb:**相关项目:** Airtest
**标题:** [BUG提交]安装完最新的appium的wda，airtest无法连接IOS
**AirtestIDE版本:** 1.2.17
**未使用本地Pyhton环境运行脚本**
**报错描述:**
wda安装成功，服务也已经启动了，浏览器ios信息也能输出。airtest就是连接不上，每次都报这个。只有16.2系统那台设备能正常连接。IOS14.3、13.3设备都不行。
**相关截图:**
无
**报错Log:**
```
[17:10:23][DEBUG]<airtest.core.android.adb> C:\Users\zhangzhanwei\Desktop\AirtestIDE-win-1.2.15\AirtestIDE\airtest\core\android\static\adb\windows\adb.exe devices
[I 240305 17:10:23 _device:984] BundleID: com.facebook.WebDriverAgentRunnerZZwaa.xctrunner
[I 240305 17:10:23 _device:1000] ProductVersion: 13.6
[I 240305 17:10:23 _device:1001] DeviceIdentifier: 00008030-000E656C1403802E
[I 240305 17:10:24 _device:1122] xctrunner quited
[17:10:28][ERROR]<airtest> Traceback (most recent call last):
File "site-packages\urllib3\connectionpool.py", line 600, in urlopen
File "site-packages\urllib3\connectionpool.py", line 384, in _make_request
File "<string>", line 2, in raise_from
File "site-packages\urllib3\connectionpool.py", line 380, in _make_request
File "http\client.py", line 1331, in getresponse
File "http\client.py", line 297, in begin
File "http\client.py", line 266, in _read_status
http.client.RemoteDisconnected: Remote end closed connection without response
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "site-packages\requests\adapters.py", line 449, in send
File "site-packages\urllib3\connectionpool.py", line 638, in urlopen
File "site-packages\urllib3\util\retry.py", line 367, in increment
File "site-packages\urllib3\packages\six.py", line 685, in reraise
File "site-packages\urllib3\connectionpool.py", line 600, in urlopen
File "site-packages\urllib3\connectionpool.py", line 384, in _make_request
File "<string>", line 2, in raise_from
File "site-packages\urllib3\connectionpool.py", line 380, in _make_request
File "http\client.py", line 1331, in getresponse
File "http\client.py", line 297, in begin
File "http\client.py", line 266, in _read_status
urllib3.exceptions.ProtocolError: ('Connection aborted.', RemoteDisconnected('Remote end closed connection without response',))
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "app\plugins\devicepool\abstract\device.py", line 84, in run
File "app\plugins\devicepool\ios\device.py", line 157, in connect
File "C:\Users\zhangzhanwei\Desktop\AirtestIDE-win-1.2.15\AirtestIDE\airtest\core\ios\ios.py", line 536, in display_info
self._display_info()
File "C:\Users\zhangzhanwei\Desktop\AirtestIDE-win-1.2.15\AirtestIDE\airtest\core\ios\ios.py", line 545, in _display_info
snapshot = self.snapshot()
File "C:\Users\zhangzhanwei\Desktop\AirtestIDE-win-1.2.15\AirtestIDE\airtest\core\ios\ios.py", line 47, in wrapper
return func(self, *args, **kwargs)
File "C:\Users\zhangzhanwei\Desktop\AirtestIDE-win-1.2.15\AirtestIDE\airtest\core\ios\ios.py", line 633, in snapshot
data = self._neo_wda_screenshot()
File "C:\Users\zhangzhanwei\Desktop\AirtestIDE-win-1.2.15\AirtestIDE\airtest\core\ios\ios.py", line 618, in _neo_wda_screenshot
value = self.driver.http.get('screenshot').value
File "site-packages\wda\utils.py", line 47, in _inner
File "site-packages\wda\__init__.py", line 454, in _fetch
File "site-packages\wda\__init__.py", line 124, in httpdo
File "site-packages\wda\__init__.py", line 154, in _unsafe_httpdo
File "site-packages\requests\sessions.py", line 530, in request
File "site-packages\requests\sessions.py", line 643, in send
File "site-packages\requests\adapters.py", line 498, in send
requests.exceptions.ConnectionError: ('Connection aborted.', RemoteDisconnected('Remote end closed connection without response',))
```
**连接设备信息:**
设备类型 | 设备型号 | 系统版本号 | apk名称/下载链接 | 使用的wda版本 | wda更新到最新
------------ | ------------- | ------------- | ------------- | ------------- | -------------
iOS | iPhone 12 | IOS 14.2 | | Appium/WebDriverAgent | 是
**提供最小可复现此BUG的代码:**
```
无
``` | open | 2024-03-05T10:33:46Z | 2024-04-16T10:03:25Z | https://github.com/AirtestProject/Airtest/issues/1200 | [] | zhangruejun | 1 |
huggingface/datasets | pytorch | 7,448 | `datasets.disable_caching` doesn't work | When I use `Dataset.from_generator(my_gen)` to load my dataset, it simply skips my changes to the generator function.
I tried `datasets.disable_caching`, but it doesn't work! | open | 2025-03-13T06:40:12Z | 2025-03-22T04:37:07Z | https://github.com/huggingface/datasets/issues/7448 | [] | UCC-team | 2 |
davidsandberg/facenet | tensorflow | 258 | Import facenet and detect_face by myself while running align_dataset_mecnn.py? | when I run align_dataset_mecnn.py,I found facenet and detect_face are not under the folder.Should I import them by myself?
| closed | 2017-04-27T12:59:35Z | 2017-05-09T11:08:48Z | https://github.com/davidsandberg/facenet/issues/258 | [] | OneMorea | 1 |
dbfixtures/pytest-postgresql | pytest | 189 | pscyopg2-binary | ### What action do you want to perform
Install this alongside `psycopg2-binary` instead of `psycopg2`, because it's a pre-compiled wheel.
### What are the results
Since `pytest-postgresql` depends directly on `psycopg2`, this isn't possible.
### What are the expected results
Can install just fine. | closed | 2019-04-05T14:29:41Z | 2019-04-09T09:19:36Z | https://github.com/dbfixtures/pytest-postgresql/issues/189 | [] | adamchainz | 0 |
man-group/arctic | pandas | 338 | how to resolve below error while running python using cntk | #### Arctic Version
```
# Arctic version here
```
#### Arctic Store
```
# VersionStore, TickStore, or ChunkStore
```
#### Platform and version
Put here
#### Description of problem and/or code sample that reproduces the issue
Put Here
| closed | 2017-03-23T16:51:43Z | 2017-03-24T00:30:26Z | https://github.com/man-group/arctic/issues/338 | [] | jincyjojy | 1 |
vitalik/django-ninja | pydantic | 1,157 | [BUG] `models.URLField` serialized & validated as `str` | **Describe the bug**
When using a `URLField` in a Django model and then using a `ModelSchema` for serialization/validation on a `POST` request, the url is just validated as a `str`. Most other fields are covered in Ninja, but this one seems to be missing.
**Versions (please complete the following information):**
- Python version: [e.g. 3.6] 3.11.9
- Django version: [e.g. 4.0] 5.0
- Django-Ninja version: [e.g. 0.16.2] 1.1.0
- Pydantic version: [e.g. 1.9.0] 2.7.1
| open | 2024-05-09T02:58:38Z | 2024-05-16T15:18:59Z | https://github.com/vitalik/django-ninja/issues/1157 | [] | mpeyfuss | 1 |
google-research/bert | tensorflow | 944 | NotFoundError: ./dev.tsv | When I'm running `run_classifier.py`, even though the `do_eval` is `false`, this class still looks for the `dev.tsv` file. This happens when I change the batch size from 32, which is the default, to 16 (since I don't have enough memory on my GPU, I'm just trying to reduce the batch size to see if I can train my model.) I'm wondering why this is happening? I don't want to create a dev set. | open | 2019-12-01T05:21:48Z | 2019-12-01T05:21:48Z | https://github.com/google-research/bert/issues/944 | [] | phosseini | 0 |
zappa/Zappa | flask | 913 | [Migrated] Error: Warning! Status check on the deployed lambda failed. A GET request to '/' yielded a 500 response code | Originally from: https://github.com/Miserlou/Zappa/issues/2178 by [lightmagic1](https://github.com/lightmagic1)
<!--- Provide a general summary of the issue in the Title above -->
## Context
I'm having issues deploying my project using Zappa
## Expected Behavior
1) Cloned my project
2) python -m venv venv
3) pip install -r requirements.txt --no-cache-dir
4) zappa update dev
5) Success!
## Actual Behavior
1) Cloned my project
2) python -m venv venv
3) pip install -r requirements.txt --no-cache-dir
4) zappa update dev
5) I get the following error:
Error: Warning! Status check on the deployed lambda failed. A GET request to '/' yielded a 500 response code.
Using Zappa tail:
"Failed to find library: libmysqlclient.so.18...right filename?"
## Possible Fix
## Steps to Reproduce
## Your Environment
* Zappa version used: 0.51.0
* Operating System and Python version: Ubuntu 20.04 / Python 3.7.7
* The output of `pip freeze`:
```
alembic==1.0.8
aniso8601==6.0.0
argcomplete==1.9.3
astroid==2.2.5
autopep8==1.4.4
Babel==2.6.0
boto3==1.9.153
botocore==1.12.153
cachetools==3.1.1
certifi==2019.9.11
cfn-flip==1.2.0
chardet==3.0.4
Click==7.0
docutils==0.14
durationpy==0.5
emoji==0.5.4
Flask==1.0.2
Flask-Cors==3.0.7
Flask-Migrate==2.4.0
Flask-RESTful==0.3.7
Flask-SQLAlchemy==2.3.2
future==0.16.0
google-api-core==1.14.3
google-auth==1.7.0
google-cloud-speech==1.2.0
google-cloud-texttospeech==0.5.0
googleapis-common-protos==1.6.0
grpcio==1.25.0
hjson==3.0.1
idna==2.8
importlib-metadata==1.7.0
isort==4.3.16
itsdangerous==1.1.0
Jinja2==2.10
jmespath==0.9.3
kappa==0.6.0
lambda-packages==0.20.0
lazy-object-proxy==1.3.1
Mako==1.0.8
MarkupSafe==1.1.1
mccabe==0.6.1
mysql-connector-python==8.0.21
pip-tools==5.3.1
placebo==0.9.0
protobuf==3.10.0
pyasn1==0.4.7
pyasn1-modules==0.2.7
pycodestyle==2.5.0
pylint==2.3.1
python-dateutil==2.6.1
python-editor==1.0.4
python-slugify==1.2.4
pytz==2019.3
PyYAML==5.1
requests==2.22.0
rsa==4.0
s3transfer==0.2.0
six==1.13.0
SQLAlchemy==1.3.1
text-unidecode==1.3
toml==0.10.0
tqdm==4.19.1
troposphere==2.4.7
typed-ast==1.3.1
Unidecode==1.0.23
urllib3==1.24
Werkzeug==0.15.1
wrapt==1.11.1
wsgi-request-logger==0.4.6
zappa==0.51.0
zipp==3.1.0
```
* Link to your project (optional):
* Your `zappa_settings.json`:
```
"dev": {
"app_function": "app.app",
"aws_region": "us-east-1",
"profile_name": "default",
"project_name": "webhook",
"runtime": "python3.7",
"s3_bucket": "zappa-6132y6l",
"slim_handler": true
},
```
| closed | 2021-02-20T13:03:42Z | 2022-07-16T04:54:14Z | https://github.com/zappa/Zappa/issues/913 | [] | jneves | 1 |
Yorko/mlcourse.ai | pandas | 785 | Issue on page /book/topic01/topic01_pandas_data_analysis.html | Your issue content here. | closed | 2024-12-10T07:27:14Z | 2025-01-03T12:07:11Z | https://github.com/Yorko/mlcourse.ai/issues/785 | [
"invalid"
] | Kaiyrbek-data | 0 |
fedspendingtransparency/usaspending-api | pytest | 4,164 | `/api/v2/subawards/` does not respect Content-Type header | The`/api/v2/subawards/` route does not respect the Content-Type header. It will **only** accept requests with a content type header of `application/x-www-form-urlencoded`, regardless of the actual content. Disregarding this header will result in a default empty value akin to:
`{"page_metadata":{"page":1,"next":null,"previous":1,"hasNext":false,"hasPrevious":true},"results":[]}`
To be clear: if you do not use this header while maintaining the interface detailed in [api_contracts/contracts/v2/subawards.md](https://github.com/fedspendingtransparency/usaspending-api/blob/master/usaspending_api/api_contracts/contracts/v2/subawards.md) the request is seemingly rejected outright.
Example using the incorrect header:
```bash
curl 'https://api.usaspending.gov/api/v2/subawards/' \
-X POST \
-H 'Accept: application/json' \
-H 'Content-Type: application/x-www-form-urlencoded' \
-d '{
"page": 1,
"limit": 10,
"sort": "subaward_number",
"order": "asc",
"award_id": "W56KGU21C0050"
}'
```
Returns:
```json
{
"page_metadata": {
"page": 1,
"next": 2,
"previous": null,
"hasNext": true,
"hasPrevious": false
},
"results": [
{
"id": 148401622,
"subaward_number": "\u00a0\u00a0DLPH050233",
"description": "PAINT ABATEMENT \u00a0LABOR",
"action_date": "2017-04-20",
"amount": 52260.0,
"recipient_name": "IMIA, LLC"
},
{
"id": 154994152,
"subaward_number": "\u00a0MAKSPH-001-18",
"description": "SUPPORTED THE SCALING OFF-GRID ENERGY (SOGE) OFF-GRID SOLAR HOME SYSTEMS AND STORAGE TECHNOLOGY MARKET ASSESSMENTS",
"action_date": "2018-06-01",
"amount": 72025.0,
"recipient_name": "REGENTS OF THE UNIVERSITY OF CALIFORNIA, THE"
},
{
"id": 148595490,
"subaward_number": "\u00a0DLPH050607",
"description": "SCAFFFOLDING",
"action_date": "2017-05-09",
"amount": 32493.0,
"recipient_name": "TURN KEY SCAFFOLD LLC"
},
{
"id": 149488398,
"subaward_number": "\u00a0DLPH050232",
"description": "CONTROLS ENGINEER - LABOR",
"action_date": "2017-04-17",
"amount": 49035.2,
"recipient_name": "AEROTEK AFFILIATED SERVICES, INC."
},
{
"id": 152602401,
"subaward_number": "\u00a0ASUB00000454",
"description": "PREPARING RESEARCHERS IN EARLY INTERVENTION FOR CHILDREN WITH DISABILITIES FROM MULTICULTURAL ENVIRONMENTS",
"action_date": "2020-01-14",
"amount": 234778.0,
"recipient_name": "UNIVERSITY OF ARIZONA"
},
{
"id": 149918994,
"subaward_number": "ZZEMSP02",
"description": "TO PROVIDE FINANCIAL ASSISTANCE IN MEETING THE TRANSPORTATION NEEDS OF SENIORS AND INDIVIDUALS WITH DISABILITIES WHERE PUBLIC TRANSPORTATION SERVICES ARE UNAVAILABLE, INSUFFICIENT OR INAPPROPRIATE. THE SECTION 5310 PROGRAM IS DESIGNED TO SUPPLEMENT FTA'S OTHER CAPITAL ASSISTANCE PROGRAMS BY FUNDING TRANSPORTATION PROJECTS FOR SENIORS AND INDIVIDUALS WITH DISABILITIES IN ALL AREAS - URBANIZED, SMALL URBAN, AND RURAL. THE PROGRAM INCLUDES NEW FREEDOM PROGRAM ACTIVITIES AS ELIGIBLE PROJECTS.",
"action_date": "2021-09-23",
"amount": 54115.0,
"recipient_name": "EAST TENNESSEE HUMAN RESOURCE AGENCY, INC."
},
{
"id": 151427852,
"subaward_number": "ZZ8-K45",
"description": "SUPPORT THE OBJECTIVES AND DELIVERABLES OF DE-FE0032131. THE FRONT END ENGINEERING DESIGN STUDY AND PUBLIC POLICY CONSIDERATIONS",
"action_date": "2022-02-11",
"amount": 228913.0,
"recipient_name": "SOUTHERN COMPANY SERVICES, INC."
},
{
"id": 150144222,
"subaward_number": "ZZ-42-580",
"description": "CAREER AND TECHNICAL EDUCATION -- BASIC GRANTS",
"action_date": "2012-07-01",
"amount": 19245.0,
"recipient_name": "MARION COUNTY SCHOOL DISTRICT"
},
{
"id": 150236946,
"subaward_number": "ZZ2THS144",
"description": "ENFORCEMENT OF TN DUI LAWS",
"action_date": "2022-01-14",
"amount": 36600.0,
"recipient_name": "CITY OF JOHNSON CITY"
},
{
"id": 150029039,
"subaward_number": "ZZ2THS005",
"description": "CHOICES MATTER",
"action_date": "2021-12-29",
"amount": 50000.0,
"recipient_name": "ALLIANCE SPORT MARKETING LLC"
}
]
}
```
Example using the correct header:
```bash
curl 'https://api.usaspending.gov/api/v2/subawards/' \
-X POST \
-H 'Accept: application/json' \
-H 'Content-Type: application/json' \
-d '{
"page": 1,
"limit": 10,
"sort": "subaward_number",
"order": "asc",
"award_id": "W56KGU21C0050"
}'
```
Returns:
```json
{
"page_metadata": {
"page": 1,
"next": null,
"previous": null,
"hasNext": false,
"hasPrevious": false
},
"results": []
}
``` | open | 2024-08-19T04:56:33Z | 2024-08-19T04:58:26Z | https://github.com/fedspendingtransparency/usaspending-api/issues/4164 | [] | Ech0riginal | 0 |
pmaji/crypto-whale-watching-app | dash | 116 | Install erros - version conflicts | Trying to install with python 3.6.0 but got the following error. Modifying the version manually creates a lot more errors...
```
ERROR: Cannot install -r requirements.txt (line 3) and requests==2.21.0 because these package versions have conflicting dependencies.
The conflict is caused by:
The user requested requests==2.21.0
cbpro 1.1.4 depends on requests==2.13.0
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
``` | closed | 2020-12-12T02:48:29Z | 2021-01-25T02:42:53Z | https://github.com/pmaji/crypto-whale-watching-app/issues/116 | [] | silveur | 3 |
plotly/plotly.py | plotly | 5,050 | scattermapbox plot with cluster doesn't update with dataframe change in a callback | This is the issue described before with the newest dash version, 2.18.0.
> In version 2.11.1 of Dash, the dataframe is not being updated when clustering is set to True. However, it works properly when clustering is set to False.
_Originally posted by @wknjk in [#3631](https://github.com/plotly/plotly.py/issues/3631#issuecomment-1637136646)_
I found the dataframe do update, it's the graph not update correctly.
The console will log `Error: Source "plotly-trace-layer-xxxx-circle" cannot be removed while layer "plotly-trace-layer-xxxxx-cluster" is using it.`
Could anyone please tell me how to fix this issue? | closed | 2025-02-21T14:42:18Z | 2025-02-22T02:05:15Z | https://github.com/plotly/plotly.py/issues/5050 | [] | eatPizza311 | 0 |
CorentinJ/Real-Time-Voice-Cloning | deep-learning | 670 | ImportError: DLL load failed: Can't find module | Hi, I've tried to execute command; _python demo_cli.py_
after that I've get an error like;
([Test_Voice]) D:\voice>python demo_cli.py
Traceback (most recent call last):
File "demo_cli.py", line 4, in <module>
from synthesizer.inference import Synthesizer
File "D:\voice\synthesizer\inference.py", line 1, in <module>
import torch
File "C:\Users\damia\anaconda3\envs\[Test_Voice]\lib\site-packages\torch\__init__.py", line 190, in <module>
from torch._C import *
ImportError: DLL load failed: Can't find module
I am trying to fix this issue but don't have any idea
Thanks! | closed | 2021-02-17T22:39:17Z | 2021-02-18T12:16:23Z | https://github.com/CorentinJ/Real-Time-Voice-Cloning/issues/670 | [] | Avepy | 3 |
amdegroot/ssd.pytorch | computer-vision | 372 | index is out of bounds for dimension 0 with size | closed | 2019-07-02T08:52:24Z | 2019-07-02T08:52:31Z | https://github.com/amdegroot/ssd.pytorch/issues/372 | [] | herrickli | 0 | |
mwaskom/seaborn | data-visualization | 3,367 | `statsmodels` missing as a dependency | A normal `residplot` on the `mpg` data with `lowess=True` doesn't currently work, because `statsmodels` doesn't exist as a dependency. This is with a fresh `pip install --upgrade seaborn`.
```
---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
Cell In[16], line 1
----> 1 sns.residplot(data=mpg, x='horsepower', y='mpg', lowess=True)
File ~/anaconda3/lib/python3.10/site-packages/seaborn/regression.py:923, in residplot(data, x, y, x_partial, y_partial, lowess, order, robust, dropna, label, color, scatter_kws, line_kws, ax)
921 scatter_kws = {} if scatter_kws is None else scatter_kws.copy()
922 line_kws = {} if line_kws is None else line_kws.copy()
--> 923 plotter.plot(ax, scatter_kws, line_kws)
924 return ax
File ~/anaconda3/lib/python3.10/site-packages/seaborn/regression.py:368, in _RegressionPlotter.plot(self, ax, scatter_kws, line_kws)
365 self.scatterplot(ax, scatter_kws)
367 if self.fit_reg:
--> 368 self.lineplot(ax, line_kws)
370 # Label the axes
371 if hasattr(self.x, "name"):
File ~/anaconda3/lib/python3.10/site-packages/seaborn/regression.py:413, in _RegressionPlotter.lineplot(self, ax, kws)
411 """Draw the model."""
412 # Fit the regression model
--> 413 grid, yhat, err_bands = self.fit_regression(ax)
414 edges = grid[0], grid[-1]
416 # Get set default aesthetics
File ~/anaconda3/lib/python3.10/site-packages/seaborn/regression.py:212, in _RegressionPlotter.fit_regression(self, ax, x_range, grid)
210 elif self.lowess:
211 ci = None
--> 212 grid, yhat = self.fit_lowess()
213 elif self.robust:
214 from statsmodels.robust.robust_linear_model import RLM
File ~/anaconda3/lib/python3.10/site-packages/seaborn/regression.py:292, in _RegressionPlotter.fit_lowess(self)
290 def fit_lowess(self):
291 """Fit a locally-weighted regression, which returns its own grid."""
--> 292 from statsmodels.nonparametric.smoothers_lowess import lowess
293 grid, yhat = lowess(self.y, self.x).T
294 return grid, yhat
ModuleNotFoundError: No module named 'statsmodels'
```
| closed | 2023-05-17T13:13:05Z | 2023-08-27T19:45:01Z | https://github.com/mwaskom/seaborn/issues/3367 | [
"ux"
] | loftusa | 2 |
christabor/flask_jsondash | flask | 127 | Show a message for loading http when in https environment to allow overriding settings | ## Use case
For iframe types, I want to be able to load insecure content that I trust, without using CORS or other methods. I know the source but it may not be valid https, while my service (jsondash) is served over https.
E.g. for Chrome, this can be done the following way:
https://superuser.com/questions/487748/how-to-allow-chrome-browser-to-load-insecure-content
## Implementation
When loading the iframe, if the `dataSource` starts with `http://` and the `window.location.protocol === 'https:`, then it is considered "insecureOnSecure" or the like. When this is true, display an alert or some indication that content can be loaded (with caveats explained) insecurely by doing X, where X is either:
1. A generic message indicating that *somehow* the user can disable this blocking of iframe content
2. OR, a mapping of each browser type and example docs for that browser that indicate how to disable it).
The second option is much more involved and also can potentially become out-of-date as docs change or pages go stale. However, when it works properly, it can be much more useful for the user than expecting them to go out and look for these docs manually.
### Other ideas
* This can be enabled on a flask-app level (e.g. `JSONDASH_SHOW_INSECURE = True`) or similar.
## Caveats
1. The user can be exposed to unsafe environments
2. More work involved than just blocking insecure content.
| open | 2017-06-20T19:47:38Z | 2017-06-20T19:52:54Z | https://github.com/christabor/flask_jsondash/issues/127 | [
"enhancement",
"help wanted",
"ui/ux"
] | christabor | 0 |
huggingface/transformers | nlp | 36,743 | Model Card to include key information (e.g. max_sequence_length, etc.) | ### Feature request
It would be great to add a (non-optional) part in the model card page & when authors upload their models. Where all the main parameters of the model are highlighted (i.e. so that it can be used with model.generate() easily. & recommended parameters are indicated as well [optional]).
### Motivation
The reason for this feature, is that often models fail silently and at a later stage - when using them, because some key parameter is not set during model loading or model generation.
### Your contribution
Not sure, I would love to, but I think this is a request that only HF can fulfill. | open | 2025-03-15T15:20:03Z | 2025-03-19T13:39:10Z | https://github.com/huggingface/transformers/issues/36743 | [
"Feature request"
] | ai-nikolai | 1 |
polarsource/polar | fastapi | 4,612 | Metrics: Show contextual graphs on order & subscription pages | ### Description
Offer more contextual metrics to sellers when managing orders & subscriptions.
### Current Behavior
Currently, we only show the paginated table of orders & subscriptions.
### Expected Behavior
Show relevant graphs on the pages that both 1) shows the total amount & 2) paginated view amount.
E.g showing `Revenue` under `Orders` offering both:
1. Total revenue all-time across all orders
2. Revenue from the displayed orders in the paginated table
Similar for MRR on Subscriptions. | open | 2024-12-09T10:32:20Z | 2024-12-09T10:32:21Z | https://github.com/polarsource/polar/issues/4612 | [
"feature",
"changelog",
"frequent request"
] | birkjernstrom | 0 |
pennersr/django-allauth | django | 3,635 | not able to upgrade to django-allauth==0.56.0 | pip install django-allauth==0.56.0
ERROR: Could not find a version that satisfies the requirement django-allauth==0.56.0 (from versions: 0.1.0, 0.2.0, 0.3.0, 0.4.0, 0.5.0, 0.6.0, 0.7.0, 0.8.0, 0.8.1, 0.8.2, 0.8.3, 0.9.0, 0.10.0, 0.10.1, 0.11.0, 0.11.1, 0.12.0, 0.13.0, 0.14.0, 0.14.1, 0.14.2, 0.15.0, 0.16.0, 0.16.1, 0.17.0, 0.18.0, 0.19.0, 0.19.1, 0.20.0, 0.21.0, 0.22.0, 0.23.0, 0.24.0, 0.24.1, 0.25.0, 0.25.1, 0.25.2, 0.26.0.post1, 0.26.1, 0.27.0, 0.28.0, 0.29.0, 0.30.0, 0.31.0, 0.32.0, 0.33.0, 0.34.0, 0.35.0, 0.36.0, 0.37.0, 0.37.1, 0.38.0, 0.39.0, 0.39.1, 0.40.0, 0.41.0, 0.42.0, 0.43.0, 0.44.0, 0.45.0, 0.46.0, 0.47.0, 0.48.0, 0.49.0, 0.50.0, 0.51.0, 0.52.0, 0.53.0, 0.53.1)
ERROR: No matching distribution found for django-allauth==0.56.0 | closed | 2024-02-09T14:34:06Z | 2024-02-12T18:41:49Z | https://github.com/pennersr/django-allauth/issues/3635 | [] | sumit12311 | 3 |
jina-ai/clip-as-service | pytorch | 196 | jupyter notebook stack in 'Kernal starting, Please waiting'. | After I install the ```bert-serving-client```, my jupyter stack in 'Kernal starting, Please waiting'. Then i unistall it, everything work well. It only happen in my server machine with 'ubuntu 16.04', other machine with 'ubuntu 14.04' is ok. I am very confused. | closed | 2019-01-17T03:00:26Z | 2019-01-17T03:06:33Z | https://github.com/jina-ai/clip-as-service/issues/196 | [] | zhanfengchen | 1 |
marcomusy/vedo | numpy | 259 | How to render vedo to a Panel with a slider? | I've read in the notebook examples that you can embed vedo in Panel (https://panel.holoviz.org/). Is there a working example that shows how to enable that? I would like to have a UI with Panel driving the visualization with vedo. | closed | 2020-12-03T14:33:10Z | 2022-01-12T19:56:26Z | https://github.com/marcomusy/vedo/issues/259 | [
"unsolved"
] | nantille | 2 |
alpacahq/alpaca-trade-api-python | rest-api | 485 | get_bars .df Method on Result Fails Due to Undocumented Key | I was running the sample where you call the get_bars API, and turn the result into a dataframe. I get the below exception locally.
```
Traceback (most recent call last):
File "/Users/jbgrunewald/trade-bot/get_symbol.py", line 21, in <module>
print(api.get_bars("AAPL", TimeFrame.Minute, "2021-06-08", "2021-06-08", adjustment='raw').df)
File "/Users/jbgrunewald/trade-bot/venv/lib/python3.9/site-packages/alpaca_trade_api/entity_v2.py", line 61, in df
df.columns = [self.mapping[c] for c in df.columns]
File "/Users/jbgrunewald/trade-bot/venv/lib/python3.9/site-packages/alpaca_trade_api/entity_v2.py", line 61, in <listcomp>
df.columns = [self.mapping[c] for c in df.columns]
KeyError: 'n'
```
Example Bar from the response:
```
Bar({ 'c': 126.74,
'h': 126.74,
'l': 126.74,
'n': 17,
'o': 126.74,
't': '2021-06-08T23:56:00Z',
'v': 2199,
'vw': 126.738663})
```
It does contain an 'n' and a 'vw' key that are not documented in the API. Any advice on what those are, and can we add support for them? | closed | 2021-09-05T22:51:39Z | 2021-10-20T15:26:46Z | https://github.com/alpacahq/alpaca-trade-api-python/issues/485 | [] | jbgrunewald | 3 |
feature-engine/feature_engine | scikit-learn | 146 | function _define_variables should take only str or list of str | Current implementation can take list of tuples, this behaviour should not be allowed. Should expand the test to catch this up. | closed | 2020-10-06T14:00:14Z | 2020-10-20T15:49:43Z | https://github.com/feature-engine/feature_engine/issues/146 | [] | solegalli | 3 |
allenai/allennlp | pytorch | 5,379 | Cannot import name 'GradientDescentTrainer' from 'allennlp.training.trainer' | closed | 2021-08-26T07:49:22Z | 2021-08-26T08:22:58Z | https://github.com/allenai/allennlp/issues/5379 | [
"bug"
] | blackbirt-5 | 0 | |
sammchardy/python-binance | api | 1,010 | Two "await" phrase has been missed in AsyncClient methods |
as it is visible in the screenshot, there is no "await".
is that a bug or I'm wrong(Pardon my noobness)
| open | 2021-09-08T11:08:00Z | 2021-09-08T11:10:17Z | https://github.com/sammchardy/python-binance/issues/1010 | [] | AmoSobhan | 0 |
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