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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
paperless-ngx/paperless-ngx | django | 9,480 | [BUG] Consumer losing connection to redis behind HA proxy | ### Description
Hello, I have a redis cluster behind haproxy in kubernetes. The consumer seems to regularly lose connection to redis and recovers connection immediately after the following error message. The cycle continues indefinitely spamming the log file. It doesn't seem to cause other disruptions and the app seems to be otherwise working ok.
Thanks for looking into this.
```
[2025-03-24 08:12:59,761] [INFO] [celery.worker.consumer.connection] Connected to redis://:**@redis-prod-redis-ha-haproxy.database.svc.cluster.local:6379//
[2025-03-24 08:13:29,888] [WARNING] [celery.worker.consumer.consumer] consumer: Connection to broker lost. Trying to re-establish the connection...
Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/celery/worker/consumer/consumer.py", line 340, in start
blueprint.start(self)
File "/usr/local/lib/python3.12/site-packages/celery/bootsteps.py", line 116, in start
step.start(parent)
File "/usr/local/lib/python3.12/site-packages/celery/worker/consumer/consumer.py", line 746, in start
c.loop(*c.loop_args())
File "/usr/local/lib/python3.12/site-packages/celery/worker/loops.py", line 97, in asynloop
next(loop)
File "/usr/local/lib/python3.12/site-packages/kombu/asynchronous/hub.py", line 373, in create_loop
cb(*cbargs)
File "/usr/local/lib/python3.12/site-packages/kombu/transport/redis.py", line 1352, in on_readable
self.cycle.on_readable(fileno)
File "/usr/local/lib/python3.12/site-packages/kombu/transport/redis.py", line 569, in on_readable
chan.handlers[type]()
File "/usr/local/lib/python3.12/site-packages/kombu/transport/redis.py", line 918, in _receive
ret.append(self._receive_one(c))
^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/kombu/transport/redis.py", line 928, in _receive_one
response = c.parse_response()
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/redis/client.py", line 865, in parse_response
response = self._execute(conn, try_read)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/redis/client.py", line 841, in _execute
return conn.retry.call_with_retry(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/redis/retry.py", line 65, in call_with_retry
fail(error)
File "/usr/local/lib/python3.12/site-packages/redis/client.py", line 843, in <lambda>
lambda error: self._disconnect_raise_connect(conn, error),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/redis/client.py", line 830, in _disconnect_raise_connect
raise error
File "/usr/local/lib/python3.12/site-packages/redis/retry.py", line 62, in call_with_retry
return do()
^^^^
File "/usr/local/lib/python3.12/site-packages/redis/client.py", line 842, in <lambda>
lambda: command(*args, **kwargs),
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/redis/client.py", line 863, in try_read
return conn.read_response(disconnect_on_error=False, push_request=True)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/redis/connection.py", line 592, in read_response
response = self._parser.read_response(disable_decoding=disable_decoding)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/redis/_parsers/hiredis.py", line 128, in read_response
self.read_from_socket()
File "/usr/local/lib/python3.12/site-packages/redis/_parsers/hiredis.py", line 90, in read_from_socket
raise ConnectionError(SERVER_CLOSED_CONNECTION_ERROR)
redis.exceptions.ConnectionError: Connection closed by server.
[2025-03-24 08:13:32,175] [WARNING] [py.warnings] /usr/local/lib/python3.12/site-packages/celery/worker/consumer/consumer.py:391: CPendingDeprecationWarning:
In Celery 5.1 we introduced an optional breaking change which
on connection loss cancels all currently executed tasks with late acknowledgement enabled.
These tasks cannot be acknowledged as the connection is gone, and the tasks are automatically redelivered
back to the queue. You can enable this behavior using the worker_cancel_long_running_tasks_on_connection_loss
setting. In Celery 5.1 it is set to False by default. The setting will be set to True by default in Celery 6.0.
warnings.warn(CANCEL_TASKS_BY_DEFAULT, CPendingDeprecationWarning)
[2025-03-24 08:13:32,175] [INFO] [celery.worker.consumer.consumer] Temporarily reducing the prefetch count to 4 to avoid over-fetching since 8 tasks are currently being processed.
The prefetch count will be gradually restored to 16 as the tasks complete processing.
```
### Steps to reproduce
1. Set up paperless to connect to redis cluster behind haproxy
2. Check logs
### Webserver logs
```bash
[2025-03-24 08:12:59,687] [INFO] [celery.worker.consumer.consumer] Temporarily reducing the prefetch count to 4 to avoid over-fetching since 8 tasks are currently being processed.
The prefetch count will be gradually restored to 16 as the tasks complete processing.
[2025-03-24 08:12:59,761] [INFO] [celery.worker.consumer.connection] Connected to redis://:**@redis-prod-redis-ha-haproxy.database.svc.cluster.local:6379//
[2025-03-24 08:13:29,888] [WARNING] [celery.worker.consumer.consumer] consumer: Connection to broker lost. Trying to re-establish the connection...
Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/celery/worker/consumer/consumer.py", line 340, in start
blueprint.start(self)
File "/usr/local/lib/python3.12/site-packages/celery/bootsteps.py", line 116, in start
step.start(parent)
File "/usr/local/lib/python3.12/site-packages/celery/worker/consumer/consumer.py", line 746, in start
c.loop(*c.loop_args())
File "/usr/local/lib/python3.12/site-packages/celery/worker/loops.py", line 97, in asynloop
next(loop)
File "/usr/local/lib/python3.12/site-packages/kombu/asynchronous/hub.py", line 373, in create_loop
cb(*cbargs)
File "/usr/local/lib/python3.12/site-packages/kombu/transport/redis.py", line 1352, in on_readable
self.cycle.on_readable(fileno)
File "/usr/local/lib/python3.12/site-packages/kombu/transport/redis.py", line 569, in on_readable
chan.handlers[type]()
File "/usr/local/lib/python3.12/site-packages/kombu/transport/redis.py", line 918, in _receive
ret.append(self._receive_one(c))
^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/kombu/transport/redis.py", line 928, in _receive_one
response = c.parse_response()
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/redis/client.py", line 865, in parse_response
response = self._execute(conn, try_read)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/redis/client.py", line 841, in _execute
return conn.retry.call_with_retry(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/redis/retry.py", line 65, in call_with_retry
fail(error)
File "/usr/local/lib/python3.12/site-packages/redis/client.py", line 843, in <lambda>
lambda error: self._disconnect_raise_connect(conn, error),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/redis/client.py", line 830, in _disconnect_raise_connect
raise error
File "/usr/local/lib/python3.12/site-packages/redis/retry.py", line 62, in call_with_retry
return do()
^^^^
File "/usr/local/lib/python3.12/site-packages/redis/client.py", line 842, in <lambda>
lambda: command(*args, **kwargs),
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/redis/client.py", line 863, in try_read
return conn.read_response(disconnect_on_error=False, push_request=True)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/redis/connection.py", line 592, in read_response
response = self._parser.read_response(disable_decoding=disable_decoding)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/redis/_parsers/hiredis.py", line 128, in read_response
self.read_from_socket()
File "/usr/local/lib/python3.12/site-packages/redis/_parsers/hiredis.py", line 90, in read_from_socket
raise ConnectionError(SERVER_CLOSED_CONNECTION_ERROR)
redis.exceptions.ConnectionError: Connection closed by server.
[2025-03-24 08:13:32,175] [WARNING] [py.warnings] /usr/local/lib/python3.12/site-packages/celery/worker/consumer/consumer.py:391: CPendingDeprecationWarning:
In Celery 5.1 we introduced an optional breaking change which
on connection loss cancels all currently executed tasks with late acknowledgement enabled.
These tasks cannot be acknowledged as the connection is gone, and the tasks are automatically redelivered
back to the queue. You can enable this behavior using the worker_cancel_long_running_tasks_on_connection_loss
setting. In Celery 5.1 it is set to False by default. The setting will be set to True by default in Celery 6.0.
warnings.warn(CANCEL_TASKS_BY_DEFAULT, CPendingDeprecationWarning)
[2025-03-24 08:13:32,175] [INFO] [celery.worker.consumer.consumer] Temporarily reducing the prefetch count to 4 to avoid over-fetching since 8 tasks are currently being processed.
The prefetch count will be gradually restored to 16 as the tasks complete processing.
[2025-03-24 08:13:32,259] [INFO] [celery.worker.consumer.connection] Connected to redis://:**@redis-prod-redis-ha-haproxy.database.svc.cluster.local:6379//
```
### Browser logs
```bash
```
### Paperless-ngx version
2.14.7
### Host OS
docker official image
### Installation method
Docker - official image
### System status
```json
```
### Browser
_No response_
### Configuration changes
_No response_
### Please confirm the following
- [x] I believe this issue is a bug that affects all users of Paperless-ngx, not something specific to my installation.
- [x] This issue is not about the OCR or archive creation of a specific file(s). Otherwise, please see above regarding OCR tools.
- [x] I have already searched for relevant existing issues and discussions before opening this report.
- [x] I have updated the title field above with a concise description. | closed | 2025-03-24T15:18:49Z | 2025-03-24T15:32:16Z | https://github.com/paperless-ngx/paperless-ngx/issues/9480 | [
"not a bug"
] | fcarucci | 2 |
InstaPy/InstaPy | automation | 6,747 | Candra | closed | 2023-08-22T07:18:10Z | 2023-08-22T07:18:34Z | https://github.com/InstaPy/InstaPy/issues/6747 | [] | Persia48 | 0 | |
voila-dashboards/voila | jupyter | 865 | New release with PR [#841]? | Hi everyone. I would like to use the multi_kernel_manager_class configuration, in combination with the [hotpot_km](https://github.com/voila-dashboards/hotpot_km) library in order to warm up kernels. Unfortunately, I've found that the latest release (0.2.7) available from PyPI doesn't contain it. Would it be possible to do a new release of voilà including PR [#841](https://github.com/voila-dashboards/voila/pull/841/files)? | closed | 2021-03-30T07:48:35Z | 2021-04-12T14:55:46Z | https://github.com/voila-dashboards/voila/issues/865 | [] | mcornudella | 6 |
remsky/Kokoro-FastAPI | fastapi | 124 | [Solved] Docker container crashes on generation | **Describe the bug**
Attempting to generate any output the docker container just crashes without any error message.
Doesn't make a difference if you use the integrated Web UI or the Gradio UI.
**Screenshots or console output**
```
==========
== CUDA ==
==========
CUDA Version 12.4.1
Container image Copyright (c) 2016-2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
This container image and its contents are governed by the NVIDIA Deep Learning Container License.
By pulling and using the container, you accept the terms and conditions of this license:
https://developer.nvidia.com/ngc/nvidia-deep-learning-container-license
A copy of this license is made available in this container at /NGC-DL-CONTAINER-LICENSE for your convenience.
11:18:54 AM | INFO | Loading TTS model and voice packs...
11:18:54 AM | INFO | Initializing Kokoro V1 on cuda
11:18:54 AM | DEBUG | Searching for model in path: /app/api/src/models
11:18:54 AM | INFO | Loading Kokoro model on cuda
11:18:54 AM | INFO | Config path: /app/api/src/models/v1_0/config.json
11:18:54 AM | INFO | Model path: /app/api/src/models/v1_0/kokoro-v1_0.pth
11:18:56 AM | DEBUG | Scanning for voices in path: /app/api/src/voices/v1_0
11:18:56 AM | DEBUG | Searching for voice in path: /app/api/src/voices/v1_0
11:18:56 AM | DEBUG | Generating audio for text: 'Warmup text for initialization....'
11:18:56 AM | DEBUG | Got audio chunk with shape: torch.Size([57600])
11:18:56 AM | INFO | Warmup completed in 1993ms
11:18:56 AM | INFO |
░░░░░░░░░░░░░░░░░░░░░░░░
╔═╗┌─┐┌─┐┌┬┐
╠╣ ├─┤└─┐ │
╚ ┴ ┴└─┘ ┴
╦╔═┌─┐┬┌─┌─┐
╠╩╗│ │├┴┐│ │
╩ ╩└─┘┴ ┴└─┘
░░░░░░░░░░░░░░░░░░░░░░░░
Model warmed up on cuda: kokoro_v1CUDA: True
67 voice packs loaded
Beta Web Player: http://0.0.0.0:8880/web/
░░░░░░░░░░░░░░░░░░░░░░░░
11:19:04 AM | INFO | Created global TTSService instance
11:19:04 AM | DEBUG | Scanning for voices in path: /app/api/src/voices/v1_0
INFO: xxx:51832 - "GET /v1/audio/voices HTTP/1.1" 200 OK
11:19:17 AM | DEBUG | Scanning for voices in path: /app/api/src/voices/v1_0
INFO: xxx:46778 - "GET /v1/audio/voices HTTP/1.1" 200 OK
11:19:17 AM | DEBUG | Scanning for voices in path: /app/api/src/voices/v1_0
INFO: xxx:46792 - "POST /v1/audio/speech HTTP/1.1" 200 OK
11:19:17 AM | DEBUG | Scanning for voices in path: /app/api/src/voices/v1_0
11:19:17 AM | DEBUG | Searching for voice in path: /app/api/src/voices/v1_0
11:19:17 AM | DEBUG | Using single voice path: /app/api/src/voices/v1_0/af_heart.pt
11:19:17 AM | DEBUG | Using voice path: /app/api/src/voices/v1_0/af_heart.pt
11:19:17 AM | INFO | Starting smart split for 4 chars
** Press ANY KEY to close this window **
```
**Branch / Deployment used**
Docker container for `kokoro-fastapi-gpu:v0.2.0`
**Operating System**
Linux w/ Nvidia GPU | closed | 2025-02-07T11:30:55Z | 2025-02-08T05:20:58Z | https://github.com/remsky/Kokoro-FastAPI/issues/124 | [] | 0pac1ty | 2 |
lux-org/lux | pandas | 107 | Widget can not show in jupyter notebook | I used follow commend to instal lux widget.
pip install git+https://github.com/lux-org/lux-widget
jupyter nbextension install --py luxWidget
jupyter nbextension enable --py luxWidget
It's ok but the widget is not appear in Jupyter notebook. My environment is conda 4.8.5. and Python is 3.7.8. | closed | 2020-10-06T09:12:27Z | 2020-10-15T12:34:40Z | https://github.com/lux-org/lux/issues/107 | [] | Jack-ee | 11 |
apachecn/ailearning | python | 647 | 第11章_Apriori算法 | # Apriori 算法的使用
Typo: ”燃尽后对生下来的集合进行组合以声场包含两个元素的项集。“
应为 ”然后对剩下来的集合进行组合以生成包含两个元素的项集。“
| closed | 2023-12-15T16:54:46Z | 2024-01-03T01:51:23Z | https://github.com/apachecn/ailearning/issues/647 | [] | SydCS | 2 |
python-restx/flask-restx | api | 381 | Swagger Topbar Missing from Swagger UI | Swagger UI have a topbar, that is generally used as a search bar for all the APIs that are in the API documentation. Is there any roadmap to include that topbar in Restx Swagger UI? | open | 2021-10-25T08:42:27Z | 2022-07-21T13:39:03Z | https://github.com/python-restx/flask-restx/issues/381 | [
"enhancement"
] | anandtripathi5 | 1 |
JoeanAmier/TikTokDownloader | api | 425 | [功能异常] Tiktok连接超时，无法下载视频 | **问题描述**
设置了代理地址还是无法下载TK视频
我不知道是不是我设置错了
我只是打开翻墙软件后启动程序，不知道少了步骤没有
 | open | 2025-03-10T08:25:08Z | 2025-03-10T11:25:44Z | https://github.com/JoeanAmier/TikTokDownloader/issues/425 | [] | oyoy131 | 2 |
TheKevJames/coveralls-python | pytest | 20 | Nothing gets reported to coveralls.io | I think I have set up everything correctly. As you can see in Travis-CI's logs coveralls gets called and it returns 200:
https://travis-ci.org/rubik/radon
However, on coveralls.io dashboard the coverage percentage does not get displayed!
https://coveralls.io/r/rubik/radon
How is that possible?
Thanks,
rubik
| closed | 2013-05-31T15:27:44Z | 2013-06-11T13:12:01Z | https://github.com/TheKevJames/coveralls-python/issues/20 | [] | rubik | 7 |
ARM-DOE/pyart | data-visualization | 1,408 | BUG: read_odim_hdf5 - TypeError: 'numpy.float32' object cannot be interpreted as an integer | * Py-ART version: 1.14.6
* Python version: 3.11 (same with 3.10)
* Operating System: Linux / Ubuntu
### Description
An error is raised when using `pyart.aux_io.odim_hdf5.read_odim_hdf5`:
`TypeError: 'numpy.float32' object cannot be interpreted as an integer`
The line to blame is
https://github.com/ARM-DOE/pyart/blob/75cb88466a74b48680c0cdf1400e3ed8a92d35f1/pyart/aux_io/odim_h5.py#L333
The `datetime.datetime.utcfromtimestamp` function doesn't seem to like `numpy.float32` dtype anymore.
A fix (that worked for me) is to specify "float64" in the dtype of `t_data`, instead of "float32":
https://github.com/ARM-DOE/pyart/blob/75cb88466a74b48680c0cdf1400e3ed8a92d35f1/pyart/aux_io/odim_h5.py#L327
| closed | 2023-03-29T17:07:27Z | 2023-05-03T18:47:35Z | https://github.com/ARM-DOE/pyart/issues/1408 | [
"Bug"
] | Vforcell | 7 |
ExpDev07/coronavirus-tracker-api | rest-api | 251 | Add docker compatibility | Hello everyone!!!
To get the benefit of run the api with one command (with isolation), how about add the dockerfile and docker-compose to this project?
Do you see some problem about this? | closed | 2020-04-01T21:06:26Z | 2020-04-07T17:33:18Z | https://github.com/ExpDev07/coronavirus-tracker-api/issues/251 | [
"enhancement",
"dev"
] | GabrielDS | 8 |
kubeflow/katib | scikit-learn | 2,175 | Error "Objective metric accuracy is not found in training logs, unavailable value is reported. metric:<name:"accuracy" value:"unavailable" | /kind bug
**What steps did you take and what happened:**
I have been trying to create a simple Katib experiment with sklearn iris dataset but am facing an error "Objective metric accuracy is not found in training logs, unavailable value is reported. metric:<name:"accuracy" value:"unavailable"
**Below is my code:**
import argparse
import os
import hypertune
import logging
import pandas as pd
# YOUR IMPORTS HERE
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--neighbors', type=int, default=3,
help='value of k')
parser.add_argument("--log-path", type=str, default="",
help="Path to save logs. Print to StdOut if log-path is not set")
parser.add_argument("--logger", type=str, choices=["standard", "hypertune"],
help="Logger", default="standard")
args = parser.parse_args()
if args.log_path == "" or args.logger == "hypertune":
logging.basicConfig(
format="%(asctime)s %(levelname)-8s %(message)s",
datefmt="%Y-%m-%dT%H:%M:%SZ",
level=logging.DEBUG)
else:
logging.basicConfig(
format="%(asctime)s %(levelname)-8s %(message)s",
datefmt="%Y-%m-%dT%H:%M:%SZ",
level=logging.DEBUG,
filename=args.log_path)
if args.logger == "hypertune" and args.log_path != "":
os.environ['CLOUD_ML_HP_METRIC_FILE'] = args.log_path
# For JSON logging
hpt = hypertune.HyperTune()
# LOAD DATA HERE
iris_data = load_iris()
iris_df = pd.DataFrame(data=iris_data['data'], columns=iris_data['feature_names'])
iris_df['Iris type'] = iris_data['target']
iris_df['Iris name'] = iris_df['Iris type'].apply(
lambda x: 'sentosa' if x == 0 else ('versicolor' if x == 1 else 'virginica'))
def f(x):
if x == 0:
val = 'setosa'
elif x == 1:
val = 'versicolor'
else:
val = 'virginica'
return val
iris_df['test'] = iris_df['Iris type'].apply(f)
iris_df.drop(['test'], axis=1, inplace=True)
X = iris_df[['sepal length (cm)', 'sepal width (cm)', 'petal length (cm)', 'petal width (cm)']]
y = iris_df['Iris name']
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)
knn = KNeighborsClassifier(n_neighbors=args.neighbors)
knn.fit(X_train, y_train)
accuracy = knn.score(X_test, y_test)
logging.info("{{metricName: accuracy, metricValue: {:.4f}}}\n".format(accuracy))
if args.logger == "hypertune":
hpt.report_hyperparameter_tuning_metric(
hyperparameter_metric_tag='accuracy',
metric_value=accuracy)
if __name__ == '__main__':
main()
**Below is my yaml file:**
---
apiVersion: kubeflow.org/v1beta1
kind: Experiment
metadata:
namespace: kubeflow
name: iris-1
spec:
parallelTrialCount: 1
maxTrialCount: 2
maxFailedTrialCount: 3
objective:
type: maximize
goal: 0.99
objectiveMetricName: accuracy
metricsCollectorSpec:
collector:
kind: StdOut
algorithm:
algorithmName: random
parameters:
- name: neighbors
parameterType: int
feasibleSpace:
min: "3"
max: "5"
trialTemplate:
primaryContainerName: training-container
trialParameters:
- name: neighbors
description: KNN neighbors
reference: neighbors
trialSpec:
apiVersion: batch/v1
kind: Job
spec:
template:
metadata:
annotations:
sidecar.istio.io/inject: "false"
spec:
containers:
- name: training-container
image: e-dpiac-docker-local.docker.lowes.com/katib-sklearn:v3
command:
- "python3"
- "/app/iris.py"
- "--neighbors=${trialParameters.neighbors}"
- "--logger=hypertune"
resources:
requests:
memory: "6Gi"
cpu: "2"
limits:
memory: "10Gi"
cpu: "4"
restartPolicy: Never
**What did you expect to happen:** The metrics should have been collected and the trials should have succeeded..
**Anything else you would like to add:**
[Miscellaneous information that will assist in solving the issue.]
**Environment:**
- Katib version (check the Katib controller image version): katib-controller:v0.12.0
- Kubernetes version: (`kubectl version`):
- OS (`uname -a`):
---
<!-- Don't delete this message to encourage users to support your issue! -->
Impacted by this bug? Give it a 👍 We prioritize the issues with the most 👍
| closed | 2023-07-19T16:45:32Z | 2023-07-24T20:34:25Z | https://github.com/kubeflow/katib/issues/2175 | [
"kind/bug"
] | mChowdhury-91 | 23 |
junyanz/pytorch-CycleGAN-and-pix2pix | deep-learning | 1,593 | poor quality for testing with a custom dataset | Hello,
I want to train pix2pix on cityscape and test on a segmentation masks from another dataset.
This is my train command:
`python train.py --name label2city_1024p --label_nc 0 --no_instance
`
And my test command:
`python test.py --name label2city_1024p --label_nc 0 --no_instance`
These are the results:
Thank you for helping | open | 2023-07-31T10:08:28Z | 2023-07-31T10:08:28Z | https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix/issues/1593 | [] | At-Walid | 0 |
jupyterhub/repo2docker | jupyter | 1,272 | Packagemanager.rstudio.com migration broke R buildpack | <!-- Thank you for contributing. These HTML commments will not render in the issue, but you can delete them once you've read them if you prefer! -->
### Bug description
Per https://status.posit.co/ Rstudio-now-Posit PackageManager server was migrated from https://packagemanager.rstudio.com to https://packagemanager.posit.co/. `RBuildPack.get_rspm_snapshot_url` doesn't handle the redirect properly.
<!-- Use this section to clearly and concisely describe the bug. -->
#### Expected behaviour
r2d outputs Dockerfile to stdout
<!-- Tell us what you thought would happen. -->
#### Actual behaviour
```
[Repo2Docker] Looking for repo2docker_config in /tmp/a
Picked Local content provider.
Using local repo ..
Traceback (most recent call last):
File "/home/xarth/codes/jupyterhub/repo2docker/venv/lib/python3.10/site-packages/requests/models.py", line 971, in json
return complexjson.loads(self.text, **kwargs)
File "/usr/lib/python3.10/json/__init__.py", line 346, in loads
return _default_decoder.decode(s)
File "/usr/lib/python3.10/json/decoder.py", line 340, in decode
raise JSONDecodeError("Extra data", s, end)
json.decoder.JSONDecodeError: Extra data: line 1 column 5 (char 4)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/xarth/codes/jupyterhub/repo2docker/venv/bin/jupyter-repo2docker", line 33, in <module>
sys.exit(load_entry_point('jupyter-repo2docker', 'console_scripts', 'jupyter-repo2docker')())
File "/home/xarth/codes/jupyterhub/repo2docker/repo2docker/__main__.py", line 469, in main
r2d.start()
File "/home/xarth/codes/jupyterhub/repo2docker/repo2docker/app.py", line 850, in start
self.build()
File "/home/xarth/codes/jupyterhub/repo2docker/repo2docker/app.py", line 799, in build
print(picked_buildpack.render(build_args))
File "/home/xarth/codes/jupyterhub/repo2docker/repo2docker/buildpacks/base.py", line 464, in render
for user, script in self.get_build_scripts():
File "/home/xarth/codes/jupyterhub/repo2docker/repo2docker/buildpacks/r.py", line 278, in get_build_scripts
cran_mirror_url = self.get_cran_mirror_url(self.checkpoint_date)
File "/home/xarth/codes/jupyterhub/repo2docker/repo2docker/buildpacks/r.py", line 241, in get_cran_mirror_url
return self.get_rspm_snapshot_url(snapshot_date)
File "/home/xarth/codes/jupyterhub/repo2docker/repo2docker/buildpacks/r.py", line 209, in get_rspm_snapshot_url
).json()
File "/home/xarth/codes/jupyterhub/repo2docker/venv/lib/python3.10/site-packages/requests/models.py", line 975, in json
raise RequestsJSONDecodeError(e.msg, e.doc, e.pos)
requests.exceptions.JSONDecodeError: Extra data: line 1 column 5 (char 4)
```
<!-- Tell us what you actually happens. -->
### How to reproduce
<!-- Use this section to describe the steps that a user would take to experience this bug. -->
1. `mkdir /tmp/foo`
2. `echo "r-2022-05-05" > /tmp/foo/runtime.txt`
3. `jupyter-repo2docker --no-build --debug /tmp/foo`
4. See error
### Your personal set up
<!-- Tell us a little about the system you're using. You can see the guidelines for setting up and reporting this information at https://repo2docker.readthedocs.io/en/latest/contributing/contributing.html#setting-up-for-local-development. -->
- OS: Linux
- Docker version: 24.0.0
- repo2docker version: 2022.10.0+69.g364bf2e.dirty (dirty cause I already tested a patch)
| closed | 2023-05-22T17:51:50Z | 2023-05-30T14:29:03Z | https://github.com/jupyterhub/repo2docker/issues/1272 | [] | Xarthisius | 1 |
svc-develop-team/so-vits-svc | pytorch | 59 | Not saving checkpoints | I am running the Colab 4.0 notebook and everything works very well but when I ran the actual training step I notice that it's not saving any of the checkpoints. It does so at the beginning but then it just doesn't at all. I've run it for over 80 epochs now with absolutely no updates. | closed | 2023-03-19T20:59:54Z | 2023-03-23T08:39:19Z | https://github.com/svc-develop-team/so-vits-svc/issues/59 | [] | Wacky817 | 1 |
yihong0618/running_page | data-visualization | 195 | TODO List | @geekplux @ben-29 @shaonianche what we can do.
- [x] 地图上虚线作为可选项
- [ ] 考虑换成 next.js
- [x] fix all alert
- [ ] python code refactor
- [ ] pnpm consider?
- [ ] 性能提升
- [x] doc improve
- [ ] geojson support
- [ ] rss3 maybe
- [ ] #122
- [ ] more status char
- [ ] iOS app new --> GitHubPoster
- [ ] oppo
- [x] #187
- [x] dockerfile | open | 2022-01-07T05:25:52Z | 2023-11-11T14:54:57Z | https://github.com/yihong0618/running_page/issues/195 | [
"help wanted"
] | yihong0618 | 0 |
dsdanielpark/Bard-API | api | 250 | How do I use cookies with ChatBard | i can only use bard with full cookie dict | closed | 2023-12-12T22:02:54Z | 2023-12-23T12:08:09Z | https://github.com/dsdanielpark/Bard-API/issues/250 | [] | tinker1234 | 2 |
lepture/authlib | flask | 409 | in v0.15.5, flask_client do not contain UserInfo in `authorize_access_token()` method | I used pipenv to install authlib, the lastest version is `v.0.15.5`
however, when I read the document, it said
```
when .authorize_access_token, the provider will include a id_token in the response. This id_token contains the UserInfo we need so that we don’t have to fetch userinfo endpoint again.
```
but when I look into the source code of authlib, I don't think it contains the UserInfo
https://github.com/lepture/authlib/blob/d8e428c9350c792fc3d25dbaaffa3bfefaabd8e3/authlib/integrations/flask_client/remote_app.py#L67
is the source code in the master branch will be tagged in the future? | closed | 2021-12-07T09:25:37Z | 2022-01-14T06:53:59Z | https://github.com/lepture/authlib/issues/409 | [] | tan-i-ham | 1 |
JaidedAI/EasyOCR | machine-learning | 614 | ModuleNotFoundError: No module named 'easyocr' | Hey,
I tried every method to install easyocr. I installed PyTorch without GPU
`pip3 install torch torchvision torchaudio`
and then I tried `pip install easyocr` but still I got an error, afterwards from one of the solved issues I tried
`pip uninstall easyocr`
`pip install git+git://github.com/jaidedai/easyocr.git` but still unable to import easyocr.
And also firstly when I run the command `pip uninstall easyocr`, it showed me **WARNING: Skipping easyocr as it is not installed.**
@rkcosmos please help through this problem | closed | 2021-12-09T06:57:13Z | 2022-08-07T05:01:26Z | https://github.com/JaidedAI/EasyOCR/issues/614 | [] | harshitkd | 4 |
pyeve/eve | flask | 1,097 | Application does not work when I upload photos to an eve dict schema properties | Hi:
I have an eve schema set up as such:
``` python
'schema': {
'email': {
'type': 'string',
'unique': True,
},
'isEmailVerified': {
'type': 'boolean',
'default': False,
'readonly': True,
},
'profile': {
'type': 'dict',
'schema': {
'avatar': {
'type': 'media',
},
'bio': {
'type': 'string',
'minlength': 1,
'maxlength': 30,
},
'location': {
'type': 'dict',
'schema': {
'state': {
'type': 'string',
},
'city': {
'type': 'string',
},
},
},
'birth': {
'type': 'datetime',
},
'gender': {
'type': 'string',
'allowed': ["male", "famale"],
}
},
},
}
```
And I'm using cURL to make a PATCH request:
```cURL
curl -X PATCH "http://127.0.0.1:5000/api/v1/accounts/5a461646b2fcb841401ea437" -H 'If-Match: a1944717f279751875f6f6794147b258df7e2af1' -F "profile.avatar=@WechatIMG21.jpeg"
```
Application is not responding and blocking other requests. How can I upload the photo? | closed | 2017-12-29T12:17:22Z | 2018-07-04T14:01:13Z | https://github.com/pyeve/eve/issues/1097 | [
"stale"
] | zzzhouuu | 1 |
nltk/nltk | nlp | 2,666 | Encountered an old issue #1387 with the latest version | I've got the same error after doing similar stuff. (See #1387.)
```
---------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
G:\Anaconda3\lib\site-packages\IPython\core\formatters.py in __call__(self, obj)
343 method = get_real_method(obj, self.print_method)
344 if method is not None:
--> 345 return method()
346 return None
347 else:
G:\Anaconda3\lib\site-packages\nltk\tree.py in _repr_png_(self)
817 raise LookupError
818
--> 819 with open(out_path, "rb") as sr:
820 res = sr.read()
821 os.remove(in_path)
FileNotFoundError: [Errno 2] No such file or directory: 'G:\\Users\\01\\AppData\\Local\\Temp\\tmpkyszdc9g.png'
```
(Python)
```
Error: /syntaxerror in (binary token, type=155)
Operand stack:
--nostringval-- 寰蒋?Execution stack:
%interp_exit .runexec2 --nostringval-- --nostringval-- --nostringval-
- 2 %stopped_push --nostringval-- --nostringval-- --nostringval-- fa
lse 1 %stopped_push 1926 1 3 %oparray_pop 1925 1 3 %oparray_
pop --nostringval-- 1909 1 3 %oparray_pop 1803 1 3 %oparray_po
p --nostringval-- %errorexec_pop .runexec2 --nostringval-- --nostringv
al-- --nostringval-- 2 %stopped_push
Dictionary stack:
--dict:1173/1684(ro)(G)-- --dict:0/20(G)-- --dict:82/200(L)-- --dict:23
/50(L)--
Current allocation mode is local
Last OS error: No such file or directory
GPL Ghostscript 9.05: Unrecoverable error, exit code 1
```
(commmand line)
Seems the problem is that ghostscript failed - strange.
It is reproducible as https://github.com/nltk/nltk/issues/1387#issuecomment-216426399:
(in ipython notebook)
```
import nltk
nltk.tree.Tree.fromstring("(test (this tree))")
```
This old issue is closed and referenced by some PRs, so I thought it was fixed - or this is a problem of Jupyter Notebook? | open | 2021-02-08T14:02:44Z | 2021-10-27T20:06:50Z | https://github.com/nltk/nltk/issues/2666 | [] | yanhuihang | 1 |
scikit-optimize/scikit-optimize | scikit-learn | 1,127 | Bug with using n_calls, n_initial_points and (x0, y0) | This is regarding `gp_minimize` method from skopt. The problem is using the `n_calls` and `n_initial_points` parameters when the (x0, y0) is already present.
From the documentation I find,
`The total number of evaluations, n_calls, are performed like the following. If x0 is provided but not y0, then the elements of x0 are first evaluated, followed by n_initial_points evaluations. Finally, n_calls - len(x0) - n_initial_points evaluations are made guided by the surrogate model. If x0 and y0 are both provided then n_initial_points evaluations are first made then n_calls - n_initial_points subsequent evaluations are made guided by the surrogate model.`
This works well when `(x0, y0)` is not provided. However, when we provide `(x0, y0)` along with `n_calls` and `n_initial_points`, it does not behave the way it's supposed to be.
**Scenario 1**
(x0, y0) are provided.
len(x0)=10
n_initial_points=5
n_calls=20
Expected: According to above documentation, 10 provided points are evaluated --> 5 initial random points are evaluated --> (20-5)=15 optimization steps are taken guided by surrogate model.
Observed: 10 provided points are evaluated --> (len(x0) + n_initial_points) = 10+5 = 15 initial random points are evaluated --> (20-15) = 5 optimization steps are evaluated. If I had provided n_calls < (len(x0) + n_initial_points) e.g. n_calls=10, it complains that `n_calls` should be higher than `len(x0)` + `n_initial_points`.
**Scenario 2 (hack)**
(x0, y0) are provided.
len(x0)=10
n_initial_points= -len(x0) + 5 = -10 + 5 = -5
n_calls=20
Expected: 10 provided points are evaluated --> -5 initial random points are evaluated (which is basically no new points are evaluated) --> (20-(-5)) = 25 optimization steps are taken guided by surrogate model.
Observed: 10 provided points are evaluated --> -len(x0) + 5) = -10+5 = -5 initial random points are evaluated which means it should not evaluate anything but it takes -5 as 5 (absolute value) and evaluates 5 random points --> (20 - 10 - (-5)) = 15 optimization steps are evaluated.
Would be great if you kindly fix the number or explain what is expected in reality. | open | 2022-10-04T12:00:53Z | 2024-01-19T15:34:33Z | https://github.com/scikit-optimize/scikit-optimize/issues/1127 | [] | skshahidur | 2 |
SALib/SALib | numpy | 131 | Add new method - New Sampling Strategy for Method of Morris | [Khare et al. (2015)](http://www.sciencedirect.com/science/article/pii/S1364815214003399) describe an improved method for sampling for the method of morris. | open | 2017-01-20T11:03:46Z | 2019-05-22T17:09:09Z | https://github.com/SALib/SALib/issues/131 | [
"enhancement",
"add_method"
] | willu47 | 2 |
graphql-python/graphene-sqlalchemy | sqlalchemy | 320 | How to convert a json response to graphql SQLAlchemyObjectType | I am trying to build an application with graphene_sqlalchemy to manage quite a few micro-services. I have the data models (SQLAlchemyObjectType) of each micro-service, and want to reuse them so that I don't need to duplicate data models. But the challenge is how to convert json responses from micro-services to graphql SQLAlchemyObjectType. Is there any reference? Or do I have to redefine data models for graphql? Thank you! | open | 2021-10-25T13:40:07Z | 2022-04-27T19:18:42Z | https://github.com/graphql-python/graphene-sqlalchemy/issues/320 | [
"question"
] | zhaoxwei | 0 |
apify/crawlee-python | automation | 662 | Memory usage average periodically printed from `AutoscaledPool` seems wrong | This issue was observed on the Apify platform - see for example https://api.apify.com/v2/logs/g7piQaNbAdteXnkFC. The problem is that the average memory usage starts at 0 and suddenly hops to 1.0. I can testify that the increase was way more gradual :slightly_smiling_face:
```
2024-11-06T15:11:50.471Z [crawlee._autoscaling.autoscaled_pool] INFO current_concurrency = 1; desired_concurrency = 1; cpu = 0.581; mem = 0.0; event_loop = 0.227; client_info = 0.0
2024-11-06T15:12:50.474Z [crawlee._autoscaling.autoscaled_pool] INFO current_concurrency = 0; desired_concurrency = 1; cpu = 0.491; mem = 0.0; event_loop = 0.1; client_info = 0.0
2024-11-06T15:13:50.487Z [crawlee._autoscaling.autoscaled_pool] INFO current_concurrency = 0; desired_concurrency = 1; cpu = 0.671; mem = 0.0; event_loop = 0.104; client_info = 0.0
2024-11-06T15:14:50.496Z [crawlee._autoscaling.autoscaled_pool] INFO current_concurrency = 0; desired_concurrency = 3; cpu = 0.451; mem = 0.206; event_loop = 0.039; client_info = 0.0
2024-11-06T15:15:50.491Z [crawlee._autoscaling.autoscaled_pool] INFO current_concurrency = 0; desired_concurrency = 1; cpu = 0.242; mem = 1.0; event_loop = 0.0; client_info = 0.0
``` | closed | 2024-11-06T16:37:13Z | 2024-11-15T16:23:43Z | https://github.com/apify/crawlee-python/issues/662 | [
"bug",
"t-tooling"
] | janbuchar | 15 |
sigmavirus24/github3.py | rest-api | 792 | Latest PyPI wheel not installing all dependencies | Is it possible that the recently released version 1.0.0 does not install all required dependencies. On Linux and Windows environments (Python 3.6.3, 3.6.4) we get an error like this during our unit test execution, which involves calling into the package API:
```
2018-03-14 10:39:11.684617 | node | ImportError while importing test module '/workspace/test/test_github.py'.
2018-03-14 10:39:11.684809 | node | Hint: make sure your test modules/packages have valid Python names.
2018-03-14 10:39:11.684862 | node | Traceback:
2018-03-14 10:39:11.684974 | node | test/test_github.py:1: in <module>
2018-03-14 10:39:11.685046 | node | import github3
2018-03-14 10:39:11.685267 | node | /usr/local/lib/python3.6/site-packages/github3/__init__.py:18: in <module>
2018-03-14 10:39:11.685349 | node | from .api import (
2018-03-14 10:39:11.686490 | node | /usr/local/lib/python3.6/site-packages/github3/api.py:11: in <module>
2018-03-14 10:39:11.686651 | node | from .github import GitHub, GitHubEnterprise
2018-03-14 10:39:11.686855 | node | /usr/local/lib/python3.6/site-packages/github3/github.py:10: in <module>
2018-03-14 10:39:11.686939 | node | from . import auths
2018-03-14 10:39:11.687134 | node | /usr/local/lib/python3.6/site-packages/github3/auths.py:6: in <module>
2018-03-14 10:39:11.687243 | node | from .models import GitHubCore
2018-03-14 10:39:11.687441 | node | /usr/local/lib/python3.6/site-packages/github3/models.py:8: in <module>
2018-03-14 10:39:11.687557 | node | import dateutil.parser
2018-03-14 10:39:11.687711 | node | E ModuleNotFoundError: No module named 'dateutil'
```
On the ``develop`` branch (is this where you released from?) ``setup.py`` does contain the required dependency ``python-dateutil``, however, it is not installed on Windows nor Linux. While not sure, I just noticed that ``setup.cfg`` does _not_ mention the new package in ``requires-dist``. Maybe this overrides the settings? | closed | 2018-03-14T12:05:50Z | 2018-03-14T17:24:49Z | https://github.com/sigmavirus24/github3.py/issues/792 | [] | moltob | 1 |
iperov/DeepFaceLab | deep-learning | 932 | Error extracting frames from data_src in deepfacelab colab | I was trying to run DFL_Colab, i imported the workspace folder successfully but got this error when i ran the extract frames cell
"/content
/!\ input file not found.
Done. "
please, any help regarding this? | open | 2020-10-30T00:34:27Z | 2023-06-08T21:51:12Z | https://github.com/iperov/DeepFaceLab/issues/932 | [] | jamesbright | 2 |
hpcaitech/ColossalAI | deep-learning | 6,091 | [BUG]: Got nan during backward with zero2 | ### Is there an existing issue for this bug?
- [X] I have searched the existing issues
### 🐛 Describe the bug
My code is based on Open-Sora, and can run without any issue on 32 gpus, using zero2.
However, when using 64 gpus, nan appears in the tensor gradients after the second backward step.
I have made a workaround to patch [`colossalai/zero/low_level/low_level_optim.py`](https://github.com/hpcaitech/ColossalAI/blob/89a9a600bc4802c912b0ed48d48f70bbcdd8142b/colossalai/zero/low_level/low_level_optim.py#L315) with
```python
# line 313, in _run_reduction
flat_grads = bucket_store.get_flatten_grad()
flat_grads /= bucket_store.world_size
if torch.isnan(flat_grads).any(): # here
raise RuntimeError(f"rank {dist.get_rank()} got nan on flat_grads") # here
...
if received_grad.dtype != grad_dtype:
received_grad = received_grad.to(grad_dtype)
if torch.isnan(received_grad).any(): # here
raise RuntimeError(f"rank {dist.get_rank()} got nan on received_grad") # here
...
```
With the patch above, my code run normally and the loss seems fine.
I think it may related to asynchronized state between cuda streams. I do not the exact reason and I do not think my workaround could really solve the issue.
Any idea from the team member?
### Environment
Nvidia H20
ColossalAI version: 0.4.3
cuda 12.4
pytorch 2.4 | open | 2024-10-16T06:39:10Z | 2024-10-29T01:40:58Z | https://github.com/hpcaitech/ColossalAI/issues/6091 | [
"bug"
] | flymin | 9 |
huggingface/datasets | nlp | 7,297 | wrong return type for `IterableDataset.shard()` | ### Describe the bug
`IterableDataset.shard()` has the wrong typing for its return as `"Dataset"`. It should be `"IterableDataset"`. Makes my IDE unhappy.
### Steps to reproduce the bug
look at [the source code](https://github.com/huggingface/datasets/blob/main/src/datasets/iterable_dataset.py#L2668)?
### Expected behavior
Correct return type as `"IterableDataset"`
### Environment info
datasets==3.1.0 | closed | 2024-11-22T17:25:46Z | 2024-12-03T14:27:27Z | https://github.com/huggingface/datasets/issues/7297 | [] | ysngshn | 1 |
jina-ai/serve | machine-learning | 5,898 | Streaming for HTTP for Deployment | closed | 2023-05-30T07:13:50Z | 2023-06-19T08:23:38Z | https://github.com/jina-ai/serve/issues/5898 | [] | alaeddine-13 | 0 | |
graphql-python/graphene-sqlalchemy | sqlalchemy | 111 | How to generate GraphiQL documentation? | Hello,
I'm trying to figure out how to provide descriptions to for the attributes of my SQLAlchemy class used to define my Graphene `ObjectType`:
```python
from graphene_sqlalchemy import SQLAlchemyObjectType
from database.model_people import ModelPeople
import graphene
class People(SQLAlchemyObjectType):
"""People node."""
class Meta:
model = ModelPeople
interfaces = (graphene.relay.Node,)
```
My "People node." docstring get displayed properly in GraphiQL but I'm not able to get a description for the attributes of my node which come from the ModelPeople class defined by SQLAlchemy.
Any idea?
Thank you
| closed | 2018-02-09T05:27:15Z | 2023-02-25T06:58:45Z | https://github.com/graphql-python/graphene-sqlalchemy/issues/111 | [] | alexisrolland | 3 |
waditu/tushare | pandas | 1,033 | 最近2天一直出现Read Time Out的exception | #使用tushare的pro.query失败：HTTPConnectionPool(host='api.tushare.pro', port=80): Read timed out. (read timeout=10)
我使用pro.query执行查询，基本最近2天都有遇到这个出错。 | closed | 2019-05-07T22:55:49Z | 2019-05-08T04:28:23Z | https://github.com/waditu/tushare/issues/1033 | [] | yyxochen | 1 |
Johnserf-Seed/TikTokDownload | api | 374 | 你们会经常出现”获取作品数据失败，正在重新获取“吗？ | 经常出现提示”获取作品数据失败，正在重新获取“
然后几次之后又能获取到。
就是说，能用，但是老是出这种提示。
你们也这样吗？ | open | 2023-03-28T04:52:20Z | 2023-03-28T04:52:21Z | https://github.com/Johnserf-Seed/TikTokDownload/issues/374 | [
"故障(bug)",
"额外求助(help wanted)",
"无效(invalid)"
] | zhengjinzhj | 0 |
sczhou/CodeFormer | pytorch | 273 | scripts/crop_align_face.py broken | Hello. This file uses some deprecated function, which can be fixed (like ANTIALIAS). The other big problem is that if -o is anything other than "." is defined the whole thing breaks. it combines input and output and then uses that.
Another thing is why save only the biggest picture? any tags to save everything? | open | 2023-07-22T06:18:49Z | 2023-07-22T06:18:49Z | https://github.com/sczhou/CodeFormer/issues/273 | [] | Astra060 | 0 |
plotly/dash | jupyter | 2,975 | add new persistence_type: history_state | When basing the app around internal links which add entries to the browser history it could be useful with a persistence type which stores the values in the history state entries (`history.pushState(state, ...)`).
I know that _ideally_ most/all such state would be part of the URL as this has more advantages beyond preserving the state on back/forward. But sometimes this can be a bit tricky - using URL parameters for state does require a certain app architecture - so I think it could be useful to easily add some state to the history entry "under the hood".
I think this could be reasonable easy to implement. Do a `replaceState({...history.state, ...historyProps}, ...)` each time a "history-state persisted" property is changed. Then restore these in a "popstate" event handler.
(I could not find any previous discussion on this topic) | open | 2024-09-03T18:23:57Z | 2024-09-04T13:22:42Z | https://github.com/plotly/dash/issues/2975 | [
"feature",
"P3"
] | olejorgenb | 0 |
keras-team/keras | data-science | 20,857 | Several Problems when using Keras Image Augmentation Layers to Augment Images and Masks for a Semantic Segmentation Dataset | In the following, I will try to tell you a bit of my “story” about how I read through the various layers and (partly outdated) tutorials on image augmentation for semantic segmentation, what problems and bugs I encountered and how I was able to solve them, at least for my use case. I hope that I am reporting these issue(s) in the right place and that I can help the developers responsible with my “story”.
I am currently using the latest versions of Keras (3.8) and Tensorflow (2.18.0) on an Ubuntu 23.10 machine, but have also observed the issues with other setups.
My goal was to use some of the Image Augmentation Layers from Keras to augment the images AND masks in my semantic segmentation dataset. To do this I followed the [segmentation tutorial from Tensarflow](https://www.tensorflow.org/tutorials/images/segmentation) where a custom `Augment` class is used for augmentation.
This code works fine because the `Augment` class uses only a single augmentation layer. But, for my custom code I wanted to use more augmentations. Therefore, I "combined" several of the augmentation layers trying both the normal [Pipeline layer](https://keras.io/api/layers/preprocessing_layers/image_augmentation/pipeline/) but also my preferred [RandomAugmentationPipeline layer from keras_cv](https://github.com/keras-team/keras-cv/blob/master/keras_cv/src/layers/preprocessing/random_augmentation_pipeline.py).
I provide an example implementation in [this gist](https://colab.research.google.com/gist/RabJon/9f27d600301dcf6a734e8b663c802c7f/modification_of_segmentation.ipynb). The gist is a modification of the aforementioned [image segmentation tutorial from Tensorflow](https://www.tensorflow.org/tutorials/images/segmentation) where I intended to only change the `Augment` class slightly to fit my use case and to remove all the unnecessary parts. Unfortunately, I also had to touch the code that loads the dataset, because the dataset version used in the notebook was no longer supported. But, this is another issue.
Anyway, at the bottom of the notebook you can see some example images and masks from the data pipeline and if you inspect the in more detail you can see that for some examples images and masks do not match because they were augmented differently, which is obviously not the expected behaviour. You can also see that these mismatches already happen from the first epoch on. On my system with my custom use case (where I was using the RandomAugmentationPipeline layer) it happend only from the second epoch onward, which made debugging much more difficult.
I first assumed that it was one specific augmentation layer that caused the problems, but after trying them one-by-one I found out that it is the combination of layers that makes the problems. So, I started to think about possible solutions and I also tried to use the Sequential model from keras to combine the layers instead of the Pipeline layer, but the result remained the same.
I found that the random seed is the only parameter which can be used to "control and sync" the augmentation of the images and masks, but I already had ensured that I always used the same seed. So, I started digging into the source code of the different augmentation layers and I found that most of the ones that I was using implement a `transform_segmentation_masks()` method which is however not used if the layers are called as described in the tutorial. This is because, in order to enforce the call of this method, images and masks must be passed to the same augmentation layer object as a dictionary with the keys “images” and “segmentation_masks” instead of using two different augmentation layer objects for images and masks. However, I had not seen this type of call using a dictionary in any tutorial, neither for Tensorflow nor for Keras. Nevertheless, I decided to change my code to make use of the `transform_segmentation_masks()` method, as I hoped that if such a method already existed, it would also process the images and masks correctly and thus avoid the mismatches.
Unfortunately, this was not directly the case, because some of the augmentation layers changed the masks to float32 data types although the input was uint8. Even with layers such as “RandomFlip”, which should not change or interpolate the data at all, but only shift it. So, I had to wrap all layers again in a custom layer, which castes the data back to the input data type before returning it:
```python
class ApplyAndCastAugmenter(BaseImageAugmentationLayer):
def __init__(self, other_augmenter, **kwargs):
super().__init__(**kwargs)
self.other_augmenter = other_augmenter
def call(self, inputs):
output_dtypes = {}
is_dict = isinstance(inputs, dict)
if is_dict:
for key, value in inputs.items():
output_dtypes[key] = value.dtype
else:
output_dtypes = inputs.dtype
outputs = self.other_augmenter(inputs)
if is_dict:
for key in outputs.keys():
outputs[key] = keras.ops.cast(outputs[key], output_dtypes[key])
else:
outputs = keras.ops.cast(outputs, output_dtypes)
return outputs
```
With this (admittedly unpleasant) work-around, I was able to fix all the remaining problems. Images and masks finally matched perfectly after augmentation and this was immediately noticeable in a significant performance improvement in the training of my segmentation model.
For the future I would now like to see that wrapping with my custom `ApplyAndCastAugmenter` is no longer necessary but is handled directly by the `transform_segmentation_masks()` method and it would also be good to have a proper tutorial on image augmentation for semantic segmentation or to update the old tutorials. | open | 2025-02-04T11:08:42Z | 2025-03-12T08:32:24Z | https://github.com/keras-team/keras/issues/20857 | [
"type:Bug"
] | RabJon | 3 |
jschneier/django-storages | django | 567 | The root folder is unsupported | I run the following code:
```
from django.core.management import call_command
def create_db_backup():
call_command('dbbackup', compress=True, clean=True)
```
the backup creates and is uploaded to my dropbox account but at the end I get the following error:
```
[2018-08-25 17:18:13,416: INFO/ForkPoolWorker-2] Writing file to default-2018-08-25-17-17-50.psql.gz
[2018-08-25 17:18:13,417: INFO/ForkPoolWorker-2] Request to files/get_metadata
[2018-08-25 17:18:13,951: INFO/ForkPoolWorker-2] Request to files/upload_session/start
[2018-08-25 17:18:32,623: INFO/ForkPoolWorker-2] Request to files/upload_session/append_v2
[2018-08-25 17:18:50,764: INFO/ForkPoolWorker-2] Request to files/upload_session/append_v2
[2018-08-25 17:21:52,031: INFO/ForkPoolWorker-2] Request to files/upload_session/finish
[2018-08-25 17:21:54,395: INFO/ForkPoolWorker-2] Request to files/get_metadata
BadInputError: BadInputError('d8e906319f920d75ffc769f3fe86fba4', 'Error in call to API function "files/get_metadata": request body: path: The root folder is unsupported.')
```
If I set any directory in root_path of DBBACKUP_STORAGE_OPTIONS, e.g.:
```
DBBACKUP_STORAGE_OPTIONS = {
'oauth2_access_token': 'token',
'root_path': '/dir/'
}
```
then the error changes to: TypeError: 'FolderMetadata' object is not subscriptable. The same as in the issue: https://github.com/jschneier/django-storages/issues/396
Do you have any idea what may be wrong? Below I enclose information about my configuration.
Requirements:
```
dropbox==9.0.0
django-dbbackup==3.2.0
django-storages==1.6.6
```
Settings:
```
DBBACKUP_STORAGE = 'storages.backends.dropbox.DropBoxStorage'
DBBACKUP_STORAGE_OPTIONS = {
'oauth2_access_token': 'token'
}
``` | closed | 2018-08-25T17:45:17Z | 2019-09-08T04:49:31Z | https://github.com/jschneier/django-storages/issues/567 | [
"dropbox"
] | pwierzgala | 3 |
davidsandberg/facenet | tensorflow | 459 | Is SVM a good choice for large amount class classification? | I am trying to use SVM to classify unknown image. In my use case, I have almost 1400 classes of people to classify. But when I apply SVM on my pipeline the performance is so bad that I really doubt that if SVM is the best choice.
My pipeline is shown as below.
1. Collect images in each class
The amount of face of each person is not fixed, from about max 600 to min 20. But the angle of face is not fixed also.
2. Embed by facenet & remove outlier
After collecting all class image, input all of them to facenet class by class. I remove outlier in each class using [Local Outlier Factor](http://scikit-learn.org/stable/modules/generated/sklearn.neighbors.LocalOutlierFactor.html) and set n_neighbors=10
3. Apply SVM as final classifier
Here is the most difficult stage I meet. After survey on the internet I think maybe the reason is that output of facenet 128 dimension vector which is much less than the number of classes.
Apart from the reason I mentioned (dimension difference between embedding vector & amount of classes) I think there are still somewhere may cause such problem.
- the size of bounding box is too small or resolution may too low
- the algorithm I choose or some parameter can be tuned
I hope I describe my problem well enough for everyone to understand. If there is still some information I need to provide, please let me know. Thank you.
| closed | 2017-09-17T09:53:56Z | 2017-11-07T02:49:00Z | https://github.com/davidsandberg/facenet/issues/459 | [] | posutsai | 4 |
google-research/bert | nlp | 609 | Order of classes in test_results.tsv | When using BERT to make a prediction, I can see the prediction probabilities in the output file test_results.tsv, but I am not sure which is the order of the classes. How can I determine that? | open | 2019-04-28T20:03:57Z | 2019-07-25T18:47:59Z | https://github.com/google-research/bert/issues/609 | [] | Crista23 | 1 |
dpgaspar/Flask-AppBuilder | flask | 1,645 | How can a flask Addon overwrite a template? | Sorry to post here but no result in other places like Stack Overflow or the mailing list.
I created a flask addon using "flask fab create-addon".
I would like to change the template appbuilder/general/security/login_oauth.html of a third-party app so I have in my addon:
```
templates
appbuilder
general
security
login_oauth.html
```
But when I load the third-party application my version of login_oauth.html is not loaded. I tried registering a blueprint as in [this post](https://stackoverflow.com/questions/32415245/how-to-load-templates-from-flask-extension) with the following code:
```
from flask import Blueprint
bp = Blueprint('fab_addon_fslogin', __name__, template_folder='templates')
class MyAddOnManager(BaseManager):
def __init__(self, appbuilder):
"""
Use the constructor to setup any config keys specific for your app.
"""
super(MyAddOnManager, self).__init__(appbuilder)
self.appbuilder.get_app.config.setdefault("MYADDON_KEY", "SOME VALUE")
self.appbuilder.register_blueprint(bp)
def register_views(self):
"""
This method is called by AppBuilder when initializing, use it to add you views
"""
pass
def pre_process(self):
pass
def post_process(self):
pass
```
But register_blueprint(bp) return:
```
File "/home/cquiros/data/projects2017/personal/software/superset/addons/fab_addon_fslogin/fab_addon_fslogin/manager.py", line 24, in __init__
self.appbuilder.register_blueprint(bp)
File "/home/cquiros/data/projects2017/personal/software/superset/env_superset/lib/python3.8/site-packages/Flask_AppBuilder-3.3.0-py3.8.egg/flask_appbuilder/base.py", line 643, in register_blueprint
baseview.create_blueprint(
AttributeError: 'Blueprint' object has no attribute 'create_blueprint'
``` | closed | 2021-05-25T11:14:46Z | 2021-09-06T20:42:00Z | https://github.com/dpgaspar/Flask-AppBuilder/issues/1645 | [
"stale"
] | qlands | 2 |
deeppavlov/DeepPavlov | nlp | 896 | Bert_Squad context length longer than 512 tokens sequences | Hi,
Currently I have a long context and the answer cannot be extracted from the context when the context exceeds a certain length. Is there any python code to deal with long length context.
P.S. I am using BERT-based model for context question answering. | closed | 2019-06-23T14:37:55Z | 2020-05-13T11:41:45Z | https://github.com/deeppavlov/DeepPavlov/issues/896 | [] | Chunglwc | 2 |
python-arq/arq | asyncio | 220 | New release? | Hello,
Seems arq wasn't updated since October. Also, there's some good PR's to be reviewed.
@samuelcolvin do you plan any updates to project? | closed | 2020-12-21T21:51:04Z | 2021-04-26T11:55:53Z | https://github.com/python-arq/arq/issues/220 | [] | erakli | 7 |
modelscope/modelscope | nlp | 581 | AttributeError: SiameseUiePipeline: 'torch.device' object has no attribute 'lower' | ModelScope中我在使用'damo/nlp_structbert_siamese-uninlu_chinese-base'模型时，根据模型示例finetune微调代码测试，报错：AttributeError: SiameseUiePipeline: 'torch.device' object has no attribute 'lower' | closed | 2023-10-10T06:22:25Z | 2023-12-20T13:18:23Z | https://github.com/modelscope/modelscope/issues/581 | [] | CourseAI2015 | 5 |
blacklanternsecurity/bbot | automation | 1,533 | HTTP_RESPONSE header_dict cant handle multiple headers with the same value | This is most impactful with set-cookie headers, where only the last set-cookie cookie will end up in the dict, and multiple headers are often expected | closed | 2024-07-07T18:32:19Z | 2024-07-08T00:52:57Z | https://github.com/blacklanternsecurity/bbot/issues/1533 | [
"bug"
] | liquidsec | 1 |
pytest-dev/pytest-cov | pytest | 425 | pytest and local pytest plugin running in two separate processes, talking over http | This is first general approach, I can go to details, but that would require some time since I need to filter out some sensitive data/code. But I summarise the best I can for the moment.
Essentially, we have a local pytest plugin api in `tests/fix_api.py` (snippet):
```python
"""
Pytest plugin to interact with the api at http level
"""
import json
from urllib.parse import urljoin
import pytest
import requests
def pytest_addoption(parser):
@pytest.fixture(scope="session")
def api_url(request):
@pytest.fixture(scope="function")
def api(api_url):
# Users readily available in the test suite
users = {
"demo": "demo123",
}
class Api:
def __init__(self, url=None):
def get(self, user, url, data=None, headers=None):
return self._request("get", user, url, data=data, headers=headers)
def put(self, user, url, data=None, headers=None):
def post(self, user, url, data=None, headers=None):
def patch(self, user, url, data=None, headers=None):
def delete(self, user, url, data=None, headers=None):
def _request(self, method_name, user, url, data=None, headers=None):
def login(self, user, password=None):
def logout(self, user):
```
And our `conftest.py`:
```python
import pytest
pytest_plugins = ("tests.fix_api",)
```
Then, a test example `test_auth.py`:
```python
def test_login_logout(api):
resp = api.get(None, "/is_logged_in")
assert resp.status_code == 401
assert resp.json() == {"error": "Unauthenticated"}
resp = api.post(None, "/login", {"user": "demo", "password": "demo1234"})
assert resp.status_code == 401
assert resp.json() == {"error": "Invalid Credentials. Please try again."}
resp = api.get(None, "/is_logged_in")
assert resp.status_code == 401
resp = api.post(None, "/login", {"user": "demo", "password": "demo123"})
assert resp.status_code == 200
assert resp.json() == {"success": "Authenticated", "username": "demo"}
resp = api.get(None, "/is_logged_in")
assert resp.status_code == 200
assert resp.json() == {"username": "demo"}
resp = api.post(None, "/logout")
assert resp.status_code == 200
assert resp.json() == {"success": "logged out"}
resp = api.get(None, "/is_logged_in")
assert resp.status_code == 401
```
Running `pytest tests/test_auth.py --cov --cov-report term-missing` and I got:
```
views/auth.py 45 26 42% 20-24, 30-39, 48-55, 63-65, 71
```
Basically, none of the functions `def login()`, `def logout()` and `def is_logged_in()` is being reported as covered.
Since pytest and local pytest plugin are running in two separate processes and talking over http, I'm wondering how could I make, if possible, coverage to work here.
| closed | 2020-08-17T20:29:23Z | 2020-09-06T07:03:52Z | https://github.com/pytest-dev/pytest-cov/issues/425 | [] | alanwilter | 13 |
robotframework/robotframework | automation | 4,523 | Unit test `test_parse_time_with_now_and_utc` fails around DST change | Very minor but reporting as it was creating me headaches, running tests just exactly _today_.
It seems to me that the `test_parse_time_with_now_and_utc` test will fail if run just on the day of DST change (ie. **today**) or the day before as they are doing comparisons with +/- 1 day and a hardcoded seconds difference value, which is incorrect if the DST happens between the two cases compared.
Specifically today (last night DST changed here) I see failing those tests:
```
('now - 1 day 100 seconds',-86500),
('NOW - 1D 10H 1MIN 10S', -122470)]:
```
Probably yesterday (so just before DST change) would be the ones with `+`.
As written above I'm not sure this is worth investigating and fixing, but just wanted to report as it gave me by chance some worries while rebuilding and retesting the new version of Robotframework. I will just redo the tests tomorrow ;-)
**Version Information:**
Tried with both 6.0 and 5.0.1
**Steps to reproduce:**
Run the unit tests, specifically on the day immediately before or after DST change.
**Error message and traceback:**
```
======================================================================
FAIL: test_parse_time_with_now_and_utc (test_robottime.TestTime)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/foo/rpmbuild/BUILD/robotframework-6.0/utest/utils/test_robottime.py", line 341, in test_parse_time_with_now_and_utc
assert_true(expected <= parsed <= expected + 1),
File "/home/foo/rpmbuild/BUILD/robotframework-6.0/utest/../src/robot/utils/asserts.py", line 115, in assert_true
_report_failure(msg)
File "/home/foo/rpmbuild/BUILD/robotframework-6.0/utest/../src/robot/utils/asserts.py", line 218, in _report_failure
raise AssertionError()
AssertionError
----------------------------------------------------------------------
```
| closed | 2022-10-30T11:37:08Z | 2022-10-30T18:36:13Z | https://github.com/robotframework/robotframework/issues/4523 | [
"bug",
"priority: low"
] | fedepell | 1 |
polarsource/polar | fastapi | 4,782 | Subscription (Webhook): Renewal event | ### Description
Currently, you need to listen to `order.created` with `billing_reason=subscription_cycle` to get notified about subscription renewals. Trigger a `subscription.renewed` event to offer a more intuitive and self-explanatory webhook event. | open | 2025-01-03T15:25:39Z | 2025-01-03T15:25:43Z | https://github.com/polarsource/polar/issues/4782 | [
"feature",
"changelog",
"dx"
] | birkjernstrom | 0 |
tflearn/tflearn | data-science | 928 | IOError: [Errno socket error] [Errno 110] Connection timed out | hello, When I run `python convnet_mnist.py`, it still shows error:
```
File "/home/xxx/local/anaconda2/lib/python2.7/socket.py", line 575, in create_connection
raise err
IOError: [Errno socket error] [Errno 110] Connection timed out
```
is the url bad?
| open | 2017-10-10T04:07:16Z | 2017-10-10T04:07:16Z | https://github.com/tflearn/tflearn/issues/928 | [] | PapaMadeleine2022 | 0 |
aimhubio/aim | data-visualization | 3,286 | Remove or prune artifacts along with the run | ## 🚀 Feature
When deleting a run, artifacts should be removed too.
If that is not possible, maybe `aim storage prune` could remove dangling artifacts ?
### Motivation
Not filling up my hard drive with checkpoints.
### Additional context
https://github.com/aimhubio/aim/pull/3164 https://github.com/aimhubio/aim/issues/3234 | open | 2025-02-07T15:57:52Z | 2025-02-22T21:48:00Z | https://github.com/aimhubio/aim/issues/3286 | [
"type / enhancement"
] | nlgranger | 2 |
PaddlePaddle/models | computer-vision | 5,696 | 希望能够给这个页面加一个目录，要不然从上往下翻非常不方便 | https://github.com/PaddlePaddle/models/blob/release/2.4/docs/official/README.md
祝好~ | open | 2023-01-03T06:37:34Z | 2024-02-26T05:07:48Z | https://github.com/PaddlePaddle/models/issues/5696 | [] | we-enjoy-today | 0 |
numba/numba | numpy | 9,598 | NumPy 2.0 incompatibility - A use of `np.complex_` still remains | When using `np.corrcoef`, the following error is produced with NumPy 2.0:
```
AttributeError: `np.complex_` was removed in the NumPy 2.0 release. Use `np.complex128` instead.
```
This is because its implementation still uses `np.complex_`: https://github.com/numba/numba/blob/556545c5b2b162574c600490a855ba8856255154/numba/np/arraymath.py#L2904 | closed | 2024-05-31T12:04:16Z | 2024-06-10T11:33:03Z | https://github.com/numba/numba/issues/9598 | [
"bug - failure to compile",
"NumPy 2.0"
] | gmarkall | 0 |
python-security/pyt | flask | 46 | Trim the "Reassigned in:" nodes to the ones that are relevant | So if we have the following code:
```python
@app.route('/menu', methods=['POST'])
def menu():
param = request.form['suggestion']
command = 'echo ' + param + ' >> ' + 'menu.txt'
hey = 'echo ' + param + ' >> ' + 'menu.txt'
yo = 'echo ' + hey + ' >> ' + 'menu.txt'
subprocess.call(command, shell=True)
with open('menu.txt','r') as f:
menu = f.read()
return render_template('command_injection.html', menu=menu)
```
We show the vulnerability output as:
```
1 vulnerability found:
Vulnerability 1:
File: example/vulnerable_code/command_injection.py
> User input at line 15, trigger word "form[":
param = request.form['suggestion']
Reassigned in:
File: example/vulnerable_code/command_injection.py
> Line 16: command = 'echo ' + param + ' >> ' + 'menu.txt'
File: example/vulnerable_code/command_injection.py
> Line 17: hey = 'echo ' + param + ' >> ' + 'menu.txt'
File: example/vulnerable_code/command_injection.py
> Line 18: yo = 'echo ' + hey + ' >> ' + 'menu.txt'
File: example/vulnerable_code/command_injection.py
> reaches line 20, trigger word "subprocess.call(":
subprocess.call(command,shell=True)
```
Where we don't really care about Line 17 and 18 in the output, right?
I ran into this while doing https://github.com/python-security/pyt/issues/45, once I fix this then I can make the PR fixing both of them. | closed | 2017-05-22T23:36:39Z | 2017-06-05T17:36:28Z | https://github.com/python-security/pyt/issues/46 | [] | KevinHock | 5 |
awtkns/fastapi-crudrouter | fastapi | 184 | Overriding GET route does not properly remove existing route | Just stumbled upon this (and admit I haven't actually tested it yet, apologies for that) but it _looks_ like `CRUDGenerator.get` would not properly remove its existing GET route when overriding it:
https://github.com/awtkns/fastapi-crudrouter/blob/9b829865d85113a3f16f94c029502a9a584d47bb/fastapi_crudrouter/core/_base.py#L149
Looks like a typo to me - shouldn't it rather be `"GET"` instead of `"Get"` here?
The corresponding removal code compares to `route.methods` and IIRC FastAPI does uppercase all the methods:
https://github.com/awtkns/fastapi-crudrouter/blob/26702027aa0b823c105ee1b96e1b2b3f46a3b742/fastapi_crudrouter/core/_base.py#L170-L178
Best regards,
Holger
| open | 2023-03-29T14:19:07Z | 2023-03-29T14:19:07Z | https://github.com/awtkns/fastapi-crudrouter/issues/184 | [] | hjoukl | 0 |
keras-team/autokeras | tensorflow | 1,466 | How to furnish AutoKeras in Anaconda on M1-chip MacBook Air? | First, sorry for my basic question.
This is my first time to use MacOS 11.1, and I wonder how to install and build up a new AutoKeras-compatible virtual environment.
Could you kindly let me about it?
During a "usual" formalities below, the kernel dies :<
I'm using Jupyter Notebook in Anaconda, and the environment is virtual one.
---
import pandas as pd
import gc
import random
import numpy as np
from datetime import datetime, date, timedelta
import math
import re
import sys
import codecs
import pickle
import autokeras as ak
| closed | 2020-12-18T11:12:49Z | 2021-09-28T22:06:35Z | https://github.com/keras-team/autokeras/issues/1466 | [
"wontfix"
] | jisho-iemoto | 9 |
huggingface/transformers | pytorch | 36,045 | Optimization -OO crashes docstring handling | ### System Info
transformers = 4.48.1
Python = 3.12
### Who can help?
_No response_
### Information
- [ ] The official example scripts
- [x] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)
### Reproduction
Use the `pipeline_flux.calculate_shift` function with` python -OO`
Code runs fine with no Python interpreter optimization but crashes with `-OO` with:
```
File "/home/me/Documents/repo/train.py", line 25, in <module>
from diffusers.pipelines.flux.pipeline_flux import calculate_shift
File "/home/me/Documents/repo/.venv/lib/python3.12/site-packages/diffusers/pipelines/flux/pipeline_flux.py", line 20, in <module>
from transformers import (
File "<frozen importlib._bootstrap>", line 1412, in _handle_fromlist
File "/home/me/Documents/repo/.venv/lib/python3.12/site-packages/transformers/utils/import_utils.py", line 1806, in __getattr__
value = getattr(module, name)
^^^^^^^^^^^^^^^^^^^^^
File "/home/me/Documents/repo/.venv/lib/python3.12/site-packages/transformers/utils/import_utils.py", line 1805, in __getattr__
module = self._get_module(self._class_to_module[name])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/me/Documents/repo/.venv/lib/python3.12/site-packages/transformers/utils/import_utils.py", line 1819, in _get_module
raise RuntimeError(
RuntimeError: Failed to import transformers.models.clip.modeling_clip because of the following error (look up to see its traceback):
'NoneType' object has no attribute 'split'
```
This is related to the removal of docstrings with `-OO`.
### Expected behavior
I'd expect no crash.
I assume
`lines = func_doc.split("\n")`
could be replaced with:
`lines = func_doc.split("\n") if func_doc else []` | closed | 2025-02-05T11:31:43Z | 2025-02-06T15:31:24Z | https://github.com/huggingface/transformers/issues/36045 | [
"bug"
] | donthomasitos | 3 |
ultralytics/ultralytics | deep-learning | 18,769 | Can yolo11 count objects in Classification? | ### 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
Hi! I want to know if a classification model can count the classes. Like there are multiple bottles in a picture and classification only return "bottle". Can the classification model be use to count how many bottles are present. Thanks.
### Additional
_No response_ | open | 2025-01-20T06:05:16Z | 2025-01-20T08:40:11Z | https://github.com/ultralytics/ultralytics/issues/18769 | [
"question",
"classify"
] | Taimoor505 | 6 |
sczhou/CodeFormer | pytorch | 384 | Macos Video Enhancement Issue | Enviroment:
MacOS Monterey 12.2.1
Command:
sudo python inference_codeformer.py --bg_upsampler realesrgan --face_upsample -w 0.1 --input_path /Users/justinhan/Desktop/test/7.mp4
Error info:
[vost#0:0/rawvideo @ 0x7fb4824118c0] Error submitting a packet to the muxer: Broken pipe
Last message repeated 1 times
[out#0/rawvideo @ 0x7fb48240e840] Error muxing a packet
[out#0/rawvideo @ 0x7fb48240e840] Task finished with error code: -32 (Broken pipe)
[out#0/rawvideo @ 0x7fb48240e840] Terminating thread with return code -32 (Broken pipe)
zsh: killed sudo python inference_codeformer.py --bg_upsampler realesrgan --face_upsample
[out#0/rawvideo @ 0x7fb48240e840] Error writing trailer: Broken pipe
[out#0/rawvideo @ 0x7fb48240e840] Error closing file: Broken pipe | open | 2024-07-01T07:39:46Z | 2024-07-01T07:39:46Z | https://github.com/sczhou/CodeFormer/issues/384 | [] | qunge5211314 | 0 |
google-research/bert | nlp | 725 | how to view the prediction result of each sample？ | Bert is used for text prediction. In the output result, only the accuracy rate, how to view the prediction result of each sample？ | open | 2019-06-27T08:01:21Z | 2019-08-29T15:28:56Z | https://github.com/google-research/bert/issues/725 | [] | zhangrenjie666666 | 1 |
developmentseed/lonboard | jupyter | 632 | Pass color to `.viz` for a given table | Not sure if the title is the best description but this is what I'd like to do.
At the moment I have two different tables (minor_lines and power_lines) that have more than one type of geometry (lines and polygons) in their geometry column. I'd like to plot both tables with different colors that I can choose. At the moment these colors are different but assigned automatically.
```
lonboard.viz([minor_lines, power_lines])
```
I want everything related to `minor_lines` to be one color, and for `power_lines` a different one. | closed | 2024-09-13T20:03:28Z | 2024-09-16T19:57:34Z | https://github.com/developmentseed/lonboard/issues/632 | [] | ncclementi | 4 |
Sanster/IOPaint | pytorch | 304 | 嗨，作者你好，我希望通过有效的方式支持你，但kofi不允许同样来自中国的用户向你付款 | 按照paypal的说法，它认为同样来自中国的支持者违反了“国际法”，这让我很无奈，希望你能够提供可以供中国用户付款的方式，例如支付宝或微信。如果你认为这是可以的，请回复。特别对你的辛苦工作与付出表示衷心感谢！
| closed | 2023-05-09T20:51:50Z | 2023-05-10T17:42:24Z | https://github.com/Sanster/IOPaint/issues/304 | [] | ieatchili2024 | 2 |
dbfixtures/pytest-postgresql | pytest | 540 | Unable to connect to Postgresql in a docker | ### What action do you want to perform
Connect to a postgresql db in a docker container
### What are the results
I copied the example from the README.md:
```python
postgresql_in_docker = factories.postgresql_noproc()
postresql = factories.postgresql("postgresql_in_docker", db_name="test")
def test_postgres_docker(postresql):
"""Run test."""
cur = postgresql.cursor()
cur.execute("CREATE TABLE test (id serial PRIMARY KEY, num integer, data varchar);")
postgresql.commit()
cur.close()
```
First of all, there are 2 mistakes in this example, the first one is the name of the fixture which has to be postgresql instead of postresql,
the second mistake is the argument db_name which has to be dbname.
After I made the changes and the code is syntactically correct and compiles, I got the error:
AttributeError: 'function' object has no attribute 'cursor'
### What are the expected results
Get a cursor and use it to insert some data in the database in the docker container | closed | 2021-12-28T10:05:24Z | 2022-01-10T11:11:25Z | https://github.com/dbfixtures/pytest-postgresql/issues/540 | [] | igondiu | 1 |
babysor/MockingBird | pytorch | 794 | PPG训练时的报错，请帮忙看看 | PPG预处理很顺利，ppg2mel.yaml路径也改了，但是这个错误提示怎么都解决不了，请大家帮忙看看能否有经验分享下。
D:\MockingBird-main>python ppg2mel_train.py --config .\ppg2mel\saved_models\ppg2mel.yaml --oneshotvc
Traceback (most recent call last):
File "D:\MockingBird-main\ppg2mel_train.py", line 67, in <module>
main()
File "D:\MockingBird-main\ppg2mel_train.py", line 50, in main
config = HpsYaml(paras.config)
File "D:\MockingBird-main\utils\load_yaml.py", line 44, in __init__
hps = load_hparams(yaml_file)
File "D:\MockingBird-main\utils\load_yaml.py", line 8, in load_hparams
for doc in docs:
File "C:\Users\benny\AppData\Local\Programs\Python\Python39\lib\site-packages\yaml\__init__.py", line 127, in load_all
loader = Loader(stream)
File "C:\Users\benny\AppData\Local\Programs\Python\Python39\lib\site-packages\yaml\loader.py", line 34, in __init__
Reader.__init__(self, stream)
File "C:\Users\benny\AppData\Local\Programs\Python\Python39\lib\site-packages\yaml\reader.py", line 85, in __init__
self.determine_encoding()
File "C:\Users\benny\AppData\Local\Programs\Python\Python39\lib\site-packages\yaml\reader.py", line 124, in determine_encoding
self.update_raw()
File "C:\Users\benny\AppData\Local\Programs\Python\Python39\lib\site-packages\yaml\reader.py", line 178, in update_raw
data = self.stream.read(size)
UnicodeDecodeError: 'gbk' codec can't decode byte 0x86 in position 176: illegal multibyte sequence | open | 2022-12-01T14:03:43Z | 2022-12-03T02:45:27Z | https://github.com/babysor/MockingBird/issues/794 | [] | benny1227 | 1 |
AirtestProject/Airtest | automation | 1,103 | airtest报告问题 | 生成报告的时候,用了--export到出静态文件,发现/staic相关的文件导出了,但是截图文件没有导出来 | open | 2023-02-08T06:49:48Z | 2023-02-08T06:49:48Z | https://github.com/AirtestProject/Airtest/issues/1103 | [] | jinx0321 | 0 |
Yorko/mlcourse.ai | plotly | 664 | jupyter_russian/project_alice/week2_analysis_hypotheses.ipynb Специализация Курсеры | На курсере отличается первый вопрос от указанного в файле. Вместо количества уникальных длин новых разреженных матриц там спрашивается:
Вопрос 1. Каковы длины (число сессий) новых 16 разреженных матриц?
Эти длины нужно вывести в файл через пробел. Проверить можно здесь:
https://www.coursera.org/learn/data-analysis-project/programming/lWVOk/podghotovka-i-piervichnyi-analiz-dannykh/submission
Также можно добавить во втором вопросе, что грейдер в качестве ответов "да/нет" принимает только "YES/NO", регистр важен. | closed | 2020-04-21T12:16:17Z | 2020-04-21T13:20:09Z | https://github.com/Yorko/mlcourse.ai/issues/664 | [] | eye-shield-77 | 1 |
explosion/spaCy | machine-learning | 12,659 | FIXED: Pydantic issubclass error for python 3.8 and 3.9 | **UPDATE**: This is now fixed for spacy v3.4 and v3.5 with the release of Pydantic v1.10.8.
New installs with `pip install spacy` should work without issue.
To fix an existing venv for spacy v3.4 or v3.5, please upgrade Pydantic to the latest compatible version with:
```shell
python -m pip install -U pydantic spacy
```
Or for a specific version of spacy:
```shell
python -m pip install -U pydantic spacy==3.4.4
```
For spacy v3.2 and v3.3, we have published patch releases with fixes for the `typing_extension` requirement. Upgrade to spacy v3.2.6+ or v3.3.3+:
```shell
python -m pip install 'spacy~=3.2.6'
```
```shell
python -m pip install 'spacy~=3.3.3'
```
---------
Original report:
There appears to be a bug in Pydantic v1.10.7 and earlier related to the recent release of `typing_extensions` v4.6.0 that causes errors for `import spacy` and any other spacy commands for python 3.8 and python 3.9.
We're hoping that there will be an upstream fix soon. You can follow this issue for more details: https://github.com/pydantic/pydantic/issues/5821
As a workaround, you can add `typing_extensions<4.6.0` to your requirements.
----------
The error traceback looks like this:
```
File "pydantic/main.py", line 197, in pydantic.main.ModelMetaclass.__new__
File "pydantic/fields.py", line 506, in pydantic.fields.ModelField.infer
File "pydantic/fields.py", line 436, in pydantic.fields.ModelField.__init__
File "pydantic/fields.py", line 552, in pydantic.fields.ModelField.prepare
File "pydantic/fields.py", line 661, in pydantic.fields.ModelField._type_analysis
File "pydantic/fields.py", line 668, in pydantic.fields.ModelField._type_analysis
File "/usr/lib/python3.8/typing.py", line 774, in __subclasscheck__
return issubclass(cls, self.__origin__)
TypeError: issubclass() arg 1 must be a class
```
| closed | 2023-05-23T08:43:17Z | 2023-08-19T00:02:05Z | https://github.com/explosion/spaCy/issues/12659 | [
"bug",
"third-party"
] | adrianeboyd | 13 |
aiortc/aiortc | asyncio | 112 | Issues using together with Janus gateway | Hello,
thanks again for the great lib!
I am trying to use an aiortc based client to send video via [Janus gateway](https://janus.conf.meetecho.com/). However, I am encountering an issue:
When connecting with the client, ICE etc always goes through fine. However, it takes up towards 1-2 minutes before video starts streaming.
Looking into `chrome://webrtc-internals`, it seems like the reason is that chrome in the beginning cannot determine which encoding is used. In the stats for the aiortc peerconnection it says `codecImplementationName: unknown` and there are lots of PLI:s sent back to the client. After 1-2 minutes it changes to `libvpx` and video starts streaming, as can be seen in the PLI graph:
Streaming video directly from browser to browser via Janus works fine. Also streaming aiortc to browser works fine.
aiortc SDP: https://pastebin.com/4v6JRALa
Janus SDP: https://pastebin.com/gmJdgs5b
My aiortc code: https://gist.github.com/tobiasfriden/736d62cd103d70936558e967463fa8f5
Using this to run Janus with docker: https://github.com/linagora/docker-janus-gateway
Greatly appreciate any help!
Edit:
The issue seems to be that the PLI packets are not forwarded to the `RTCRtpSender` correctly. If I add some prints I can see PLI:s recieved in the `RTCDtlsTransport` but it cannot find the corresponding reciever. Printing `self._rtp_router.ssrc_tables` prints an empty dict so seems like the reciever is never registered. | closed | 2018-12-21T16:34:27Z | 2018-12-25T12:08:40Z | https://github.com/aiortc/aiortc/issues/112 | [] | tobiasfriden | 4 |
widgetti/solara | jupyter | 508 | task decorator & cancelled error | Hello! Nice work on this. very cool.
I am using (potentially misusing) the task decorator functionality, and I am getting the errors below. Using bleeding edge version. You can see it takes a few times of sliding the slider until it errors. Maybe because Im creating so many tasks? Tried wrapping different parts of the code in try/excepts to no avail.
```python
from solara.lab import task
from reacton import use_state
import numpy as np
import solara
@task()
async def debounce_update(value):
await asyncio.sleep(1)
return value
@solara.component
def Page():
im_idx, set_im_idx = use_state(0)
plotly_im_idx, set_plotly_im_idx = use_state(0)
def on_slider_change(value):
set_im_idx(value)
if debounce_update.pending:
debounce_update.cancel()
debounce_update(value)
if debounce_update.finished:
new_idx = debounce_update.value
if new_idx == im_idx:
set_plotly_im_idx(new_idx)
slider = solara.SliderInt(
label="Image Index",
min=0,
max=len(image_data) - 1,
step=1,
value=im_idx,
on_value=on_slider_change,
)
with solara.Card() as main:
solara.VBox([slider])
if debounce_update.finished:
print("finished")
if debounce_update.cancelled:
print("cancelled")
if debounce_update.pending:
print("pending")
if debounce_update.error:
print("ERRRRRROOOOOOOR")
return main
```
<details><summary>Details</summary>
<p>
pending
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Future exception was never retrieved
future: <Future finished exception=CancelledError()>
Traceback (most recent call last):
File "/Users/swelborn/miniconda3/envs/tomopyui-dev/lib/python3.11/site-packages/solara/tasks.py", line 235, in runs_in_thread
thread_event_loop.run_until_complete(current_task)
File "/Users/swelborn/miniconda3/envs/tomopyui-dev/lib/python3.11/asyncio/base_events.py", line 654, in run_until_complete
return future.result()
^^^^^^^^^^^^^^^
File "/Users/swelborn/miniconda3/envs/tomopyui-dev/lib/python3.11/site-packages/solara/tasks.py", line 292, in _async_run
await runner()
File "/Users/swelborn/miniconda3/envs/tomopyui-dev/lib/python3.11/site-packages/solara/tasks.py", line 266, in runner
self._last_value = value = await self.function(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/swelborn/Documents/gits/tomopyui/sol.py", line 36, in debounce_update
await asyncio.sleep(1)
File "/Users/swelborn/miniconda3/envs/tomopyui-dev/lib/python3.11/asyncio/tasks.py", line 649, in sleep
return await future
^^^^^^^^^^^^
asyncio.exceptions.CancelledError
Future exception was never retrieved
future: <Future finished exception=CancelledError()>
Traceback (most recent call last):
File "/Users/swelborn/miniconda3/envs/tomopyui-dev/lib/python3.11/site-packages/solara/tasks.py", line 235, in runs_in_thread
thread_event_loop.run_until_complete(current_task)
File "/Users/swelborn/miniconda3/envs/tomopyui-dev/lib/python3.11/asyncio/base_events.py", line 654, in run_until_complete
return future.result()
^^^^^^^^^^^^^^^
File "/Users/swelborn/miniconda3/envs/tomopyui-dev/lib/python3.11/site-packages/solara/tasks.py", line 292, in _async_run
await runner()
File "/Users/swelborn/miniconda3/envs/tomopyui-dev/lib/python3.11/site-packages/solara/tasks.py", line 266, in runner
self._last_value = value = await self.function(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/swelborn/Documents/gits/tomopyui/sol.py", line 36, in debounce_update
await asyncio.sleep(1)
File "/Users/swelborn/miniconda3/envs/tomopyui-dev/lib/python3.11/asyncio/tasks.py", line 649, in sleep
return await future
^^^^^^^^^^^^
asyncio.exceptions.CancelledError
Future exception was never retrieved
future: <Future finished exception=CancelledError()>
Traceback (most recent call last):
File "/Users/swelborn/miniconda3/envs/tomopyui-dev/lib/python3.11/site-packages/solara/tasks.py", line 235, in runs_in_thread
thread_event_loop.run_until_complete(current_task)
File "/Users/swelborn/miniconda3/envs/tomopyui-dev/lib/python3.11/asyncio/base_events.py", line 654, in run_until_complete
return future.result()
^^^^^^^^^^^^^^^
File "/Users/swelborn/miniconda3/envs/tomopyui-dev/lib/python3.11/site-packages/solara/tasks.py", line 292, in _async_run
await runner()
File "/Users/swelborn/miniconda3/envs/tomopyui-dev/lib/python3.11/site-packages/solara/tasks.py", line 266, in runner
self._last_value = value = await self.function(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/swelborn/Documents/gits/tomopyui/sol.py", line 36, in debounce_update
await asyncio.sleep(1)
File "/Users/swelborn/miniconda3/envs/tomopyui-dev/lib/python3.11/asyncio/tasks.py", line 649, in sleep
return await future
^^^^^^^^^^^^
asyncio.exceptions.CancelledError
finished
finished
</p>
</details>
| open | 2024-02-18T05:51:34Z | 2024-02-19T18:21:23Z | https://github.com/widgetti/solara/issues/508 | [
"bug",
"good first issue",
"help wanted"
] | swelborn | 3 |
fastapi-admin/fastapi-admin | fastapi | 22 | 什么时候支持postgress | git@github.com:tiangolo/full-stack-fastapi-postgresql.git | closed | 2020-11-27T06:31:18Z | 2020-12-01T01:24:09Z | https://github.com/fastapi-admin/fastapi-admin/issues/22 | [] | harrywu001 | 1 |
PokeAPI/pokeapi | graphql | 542 | API's slow response | I am using this api since some weeks and it was working perfectly and i am using Pokepy moduke of it but today the api response time is taking 6min to get a pokemon or anything i have tested alot i used pokebase and pokepy to check but noth taking time to get the data from website please check to it since my discord bot is totally shutdown due to this. Here is the Proof of output when i try in console it takes 6 Minutes to response
Thank you | closed | 2020-12-02T10:46:50Z | 2020-12-04T18:50:29Z | https://github.com/PokeAPI/pokeapi/issues/542 | [
"invalid",
"cloudflare"
] | AryanXdProYT | 11 |
miguelgrinberg/python-socketio | asyncio | 131 | Async send() not working | Hi all,
I have a small app which I want to read a log file on disk and send its contents live to connected web clients.
I can `socketio.send()` messages successfully in a connect handler, but when I add my `follow_file()` loop nothing is sent, before/during/after the loop. I understand file I/O is blocking and I hope to have accounted for that, but I am clearly missing something.
In `on_connect_send_logs()`, each time a client connects I see the contents of `build.log` printed to stdout, and when the end of the file is reached the app prints the following continuously every second:
```
follow_file - for
follow_file - blocking/sleep
```
If I append something to `build.log` it gets printed to stdout, so `on_connect_send_logs()` seems to work but the `ws.send()` calls never seem to have any effect. If I remove the `for line in follow_file('/build.log'):` loop my client receives the frames 'A', 'B', 'C'.
I am running this via uWSGI in single threaded mode, with `gevent_uwsgi`. Nginx is acting as a reverse proxy using `proxy_pass`.
This file is the app logic. `project/views.py`
```project/views.py
from flask_cas import CAS
from flask_cas import login_required
import flask_socketio as ws
from project import app, socketio
from project.util import is_admin
# Initialize SSO provider
cas = CAS(app)
[...] TRIMMED [...]
@socketio.on('connect', namespace='/logs')
@login_required
def on_connect_send_logs():
user = cas.username
if is_admin(user):
ws.send("A")
for line in follow_file('/build.log'):
print("for line")
print(line)
ws.send(line)
sys.stdout.flush()
socketio.sleep(0)
ws.send("B")
ws.send("C")
else:
ws.disconnect()
'''
Follow the live contents of a text file.
https://code.activestate.com/recipes/578424-tailing-a-live-log-file-with-python/
'''
def follow_file(filename):
stream = open(filename, 'r')
line = ''
for block in iter(lambda:stream.read(1024), None):
print("follow_file - for")
if '\n' in block:
print("follow_file - newline")
# Only enter this block if we have at least one line to yield.
# The +[''] part is to catch the corner case of when a block
# ends in a newline, in which case it would repeat a line.
for line in (line+block).splitlines(True)+['']:
if line.endswith('\n'):
yield line
# When exiting the for loop, 'line' has any remaninig text.
elif not block:
# Wait for data.
print("follow_file - blocking/sleep")
socketio.sleep(1)
```
This file starts the Flask and SocketIO server, and loads the logic. `project/__init__.py`
```project/__init__.py
from flask import Flask
from flask_socketio import SocketIO
app = Flask(__name__)
app.config.from_object('config')
app.secret_key = app.config['SECRET_KEY']
socketio = SocketIO(app, async_mode="gevent_uwsgi", allow_upgrades=True, debug=True)
# app.config is now an object containing the values of config.py
from project import views
```
This file is called by uWSGI. `project/wsgi.py`
```project/wsgi.py
"""This is for running a production server via uWSGI"""
from project import app, socketio
application = app
# Don't start the built-in uwsgi server when called from uWSGI
# Start the app by calling socketio's own run method, which starts the app too
if __name__ == '__main__':
socketio.run(debug=True)
```
Thanks in advance! Would love to get this working. | closed | 2017-08-18T16:42:57Z | 2019-01-13T22:21:11Z | https://github.com/miguelgrinberg/python-socketio/issues/131 | [
"question"
] | vladionescu | 12 |
wkentaro/labelme | deep-learning | 1,564 | Does not launch after installing with pip on windows11 | ### Provide environment information
```
(labelme_env) PS C:\Users\irema> python --version
Python 3.12.9
(labelme_env) PS C:\Users\irema> python -m pip list
Package Version
------------------ -----------
annotated-types 0.7.0
beautifulsoup4 4.13.3
certifi 2025.1.31
charset-normalizer 3.4.1
click 8.1.8
colorama 0.4.6
coloredlogs 15.0.1
contourpy 1.3.1
cycler 0.12.1
filelock 3.18.0
flatbuffers 25.2.10
fonttools 4.56.0
gdown 5.2.0
humanfriendly 10.0
idna 3.10
imageio 2.37.0
imgviz 1.7.6
kiwisolver 1.4.8
labelme 5.8.0
lazy_loader 0.4
loguru 0.7.3
matplotlib 3.10.1
mpmath 1.3.0
natsort 8.4.0
networkx 3.4.2
numpy 2.2.4
onnxruntime 1.21.0
onnxruntime-gpu 1.21.0
osam 0.2.3
packaging 24.2
pillow 11.1.0
pip 25.0.1
protobuf 6.30.1
pydantic 2.10.6
pydantic_core 2.27.2
pyparsing 3.2.1
PyQt5 5.15.11
PyQt5-Qt5 5.15.2
PyQt5_sip 12.17.0
pyreadline3 3.5.4
PySocks 1.7.1
python-dateutil 2.9.0.post0
PyYAML 6.0.2
QtPy 2.4.3
requests 2.32.3
scikit-image 0.25.2
scipy 1.15.2
six 1.17.0
soupsieve 2.6
sympy 1.13.3
termcolor 2.5.0
tifffile 2025.3.13
tqdm 4.67.1
typing_extensions 4.12.2
urllib3 2.3.0
win32_setctime 1.2.0
```
### What OS are you using?
Windows 11 Pro 10.0.26100
### Describe the Bug
I'm using powershell on windows 11. I do the following:
```
python -m venv labelme_env
.\labelme_env\Scripts\activate
pip install labelme
python -m labelme
```
and this is the output:
```
Traceback (most recent call last):
File "<frozen runpy>", line 198, in _run_module_as_main
File "<frozen runpy>", line 88, in _run_code
File "C:\Users\irema\labelme_env\Lib\site-packages\labelme\__main__.py", line 15, in <module>
from labelme.app import MainWindow
File "C:\Users\irema\labelme_env\Lib\site-packages\labelme\app.py", line 21, in <module>
from labelme._automation import bbox_from_text
File "C:\Users\irema\labelme_env\Lib\site-packages\labelme\_automation\bbox_from_text.py", line 6, in <module>
import osam
from . import apis # noqa: F401
^^^^^^^^^^^^^^^^^^
File "C:\Users\irema\labelme_env\Lib\site-packages\osam\apis.py", line 5, in <module>
import onnxruntime
File "C:\Users\irema\labelme_env\Lib\site-packages\onnxruntime\__init__.py", line 61, in <module>
raise import_capi_exception
File "C:\Users\irema\labelme_env\Lib\site-packages\onnxruntime\__init__.py", line 24, in <module>
from onnxruntime.capi._pybind_state import (
File "C:\Users\irema\labelme_env\Lib\site-packages\onnxruntime\capi\_pybind_state.py", line 32, in <module>
from .onnxruntime_pybind11_state import * # noqa
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ImportError: DLL load failed while importing onnxruntime_pybind11_state: A dynamic link library (DLL) initialization routine failed.
```
### Expected Behavior
The GUI to launch.
### To Reproduce
_No response_ | open | 2025-03-20T23:23:08Z | 2025-03-20T23:23:08Z | https://github.com/wkentaro/labelme/issues/1564 | [] | sodiumnitrate | 0 |
python-restx/flask-restx | api | 413 | Implement writeOnly for documentation purpose | This framework already has the readonly parameters for the swagger generation, while the writeonly is still missing. It's very important when implementing models like user while the password should only be assigned and shouldn't appear in any response body.
```
"password": fields.String(
required=True, writeonly=True, description="Password", example="password"
),
``` | closed | 2022-02-13T13:30:58Z | 2022-02-13T13:32:45Z | https://github.com/python-restx/flask-restx/issues/413 | [
"enhancement"
] | morland96 | 0 |
uriyyo/fastapi-pagination | fastapi | 564 | Create Params that allow for unlimited results in a single page by default | Hello everyone,
I'm using FastAPI Pagination in my API. It works like a charm. But I have a special request. I would like the results from my endpoints to be returned in a single page with an unlimited size by default. My first instance would be to achieve it like this:
```py
import sys
from fastapi import Query
from fastapi_pagination import Params
class DefaultPaginationConfiguration(Params):
page: int = Query(1, ge = 1, description = "Page number")
size: int = Query(sys.maxsize, ge = 1, description = "Page size")
```
But this seems like a rather crude approach to me. Is there some better way that I didn't spot in the documentation?
Thanks in advance!
Joshua | closed | 2023-03-07T14:45:40Z | 2023-04-12T08:24:10Z | https://github.com/uriyyo/fastapi-pagination/issues/564 | [
"question"
] | Joshua-Schroijen | 2 |
saulpw/visidata | pandas | 2,198 | Table view is blank when table saved from .tsv to .vds - I think there is data but it is invisible | **Brief Description**
When I save to .vds from an existing .tsv file the screen is blank
Version 2.11,1
**Expected result**
For data to be visible in the table view
**Actual result with screenshot**
If you get an unexpected error, please include the full stack trace that you get with `Ctrl-E`.
'Ctrl-E' only produces "no error" message
**Steps to reproduce with sample data and a .vd**
1. Make a database
2. Save it as a .tsv file
3. Close the file and quit
4. open the file
5. save the file as a .vds file
6. close the file
7. open the .vds file and there is no visible data in the table view
First try reproducing without any user configuration by using the flag `-N`.
e.g. `echo "abc" | vd -f txt -N`
Same result from visidata -N
Please attach the commandlog (saved with `Ctrl-D`) to show the steps that led to the issue.
See [here](http://visidata.org/docs/save-restore/) for more details.
No steps led to the issue except opening the .vds file after it was saved
**Additional context**
Please include the version of VisiData and Python.
Version 2.11,1
Python 3.10.12
-Shift O- changing the colors did not help
I could tell the data was there because I could enter the row view and read the data for each individual row
[RolfClients.txt](https://github.com/saulpw/visidata/files/13796900/RolfClients.txt)
| closed | 2023-12-30T02:19:16Z | 2023-12-30T22:14:14Z | https://github.com/saulpw/visidata/issues/2198 | [
"bug",
"fixed"
] | AaronFeldman | 2 |
dmlc/gluon-nlp | numpy | 688 | [DEMO] GluonNLP demos | Similar to https://demo.allennlp.org, it would be great to have online demo applications for various models available in gluonnlp.
List of demos from [AllenNLP](https://demo.allennlp.org/reading-comprehension) for reference:
Annotate a sentence
- Semantic Role Labeling
- Named Entity Recognition
- Constituency Parsing
- Dependency Parsing
- Open Information Extraction
- Sentiment Analysis
Annotate a passage
- Coreference Resolution
Answer a question
- Reading Comprehension
Semantic parsing
- WikiTableQuestions Semantic Parser
- Cornell NLVR Semantic Parser
- Text to SQL (ATIS)
- QuaRel Zero
Other
- Textual Entailment
- Event2Mind
- Language Modeling
- Masked Language Modeling | open | 2019-05-02T03:34:15Z | 2020-01-09T18:49:27Z | https://github.com/dmlc/gluon-nlp/issues/688 | [
"help wanted"
] | eric-haibin-lin | 7 |
mkhorasani/Streamlit-Authenticator | streamlit | 39 | Implementing a "register user" fails | I've added a widget to allow user to register (per the doc):
`try:`
` if authenticator.register_user('Register user', preauthorization=False):`
` st.success('User registered successfully')`
`except Exception as e:`
` st.error(e)`
But when loading the app, I get:
"Pre-authorization argument must not be None"
streamlit == 1.9.2
streamlit-authenticator == 0.2.1
OS == Ubuntu 16.04
Python == 3.6.13
| closed | 2022-12-01T00:20:34Z | 2022-12-01T17:29:45Z | https://github.com/mkhorasani/Streamlit-Authenticator/issues/39 | [] | daytonjones | 5 |
deezer/spleeter | deep-learning | 648 | Can we use this model to do VAD? | <!-- Please respect the title [Discussion] tag. -->
Hello, I found this model in VaD recently. At present, we use the voice audio separated from this model to make VAD (using neural network and LSTM). At present, I have an idea. Since this model can separate voice and background, this model should know whether this frame is voice or background, so we can make a VAD, At present, I have tried the mask matrix, but the effect is not very good. After the mask matrix is visualized, it is similar to the separated vocal spectrum. But I don't want to give up the idea. Where should I modify it
Thanks | open | 2021-08-24T12:14:29Z | 2021-08-25T06:13:50Z | https://github.com/deezer/spleeter/issues/648 | [
"question"
] | YLQY | 2 |
scikit-learn/scikit-learn | python | 30,281 | scipy.optimize._optimize.BracketError in some cases of power transformer | ### Describe the bug
Similar to #27499, in very few cases the power transformation fails.
Edit: Actually, it starts with a `RuntimeWarning: overflow encountered in power` because at this point the lambda is 292.8… And thus the out becomes `[inf, inf, inf]`.
### Steps/Code to Reproduce
```python
from sklearn.preprocessing import PowerTransformer
transformer = PowerTransformer()
transformer.fit([[23.81], [23.98], [23.97]])
```
### Expected Results
No error.
### Actual Results
```python
/tmp/test_venv/lib/python3.12/site-packages/sklearn/preprocessing/_data.py:3438: RuntimeWarning: overflow encountered in power
out[pos] = (np.power(x[pos] + 1, lmbda) - 1) / lmbda
---------------------------------------------------------------------------
BracketError Traceback (most recent call last)
Cell In[1], line 3
1 from sklearn.preprocessing import PowerTransformer
2 transformer = PowerTransformer()
----> 3 transformer.fit([[23.80762687], [23.97982808], [23.97586205]])
File /tmp/test_venv/lib/python3.12/site-packages/sklearn/base.py:1473, in _fit_context.<locals>.decorator.<locals>.wrapper(estimator, *args, **kwargs)
1466 estimator._validate_params()
1468 with config_context(
1469 skip_parameter_validation=(
1470 prefer_skip_nested_validation or global_skip_validation
1471 )
1472 ):
-> 1473 return fit_method(estimator, *args, **kwargs)
File /tmp/test_venv/lib/python3.12/site-packages/sklearn/preprocessing/_data.py:3251, in PowerTransformer.fit(self, X, y)
3231 @_fit_context(prefer_skip_nested_validation=True)
3232 def fit(self, X, y=None):
3233 """Estimate the optimal parameter lambda for each feature.
3234
3235 The optimal lambda parameter for minimizing skewness is estimated on
(...)
3249 Fitted transformer.
3250 """
-> 3251 self._fit(X, y=y, force_transform=False)
3252 return self
File /tmp/test_venv/lib/python3.12/site-packages/sklearn/preprocessing/_data.py:3304, in PowerTransformer._fit(self, X, y, force_transform)
3301 self.lambdas_[i] = 1.0
3302 continue
-> 3304 self.lambdas_[i] = optim_function(col)
3306 if self.standardize or force_transform:
3307 X[:, i] = transform_function(X[:, i], self.lambdas_[i])
File /tmp/test_venv/lib/python3.12/site-packages/sklearn/preprocessing/_data.py:3493, in PowerTransformer._yeo_johnson_optimize(self, x)
3491 x = x[~np.isnan(x)]
3492 # choosing bracket -2, 2 like for boxcox
-> 3493 return optimize.brent(_neg_log_likelihood, brack=(-2, 2))
File /tmp/test_venv/lib/python3.12/site-packages/scipy/optimize/_optimize.py:2625, in brent(func, args, brack, tol, full_output, maxiter)
2553 """
2554 Given a function of one variable and a possible bracket, return
2555 a local minimizer of the function isolated to a fractional precision
(...)
2621
2622 """
2623 options = {'xtol': tol,
2624 'maxiter': maxiter}
-> 2625 res = _minimize_scalar_brent(func, brack, args, **options)
2626 if full_output:
2627 return res['x'], res['fun'], res['nit'], res['nfev']
File /tmp/test_venv/lib/python3.12/site-packages/scipy/optimize/_optimize.py:2662, in _minimize_scalar_brent(func, brack, args, xtol, maxiter, disp, **unknown_options)
2659 brent = Brent(func=func, args=args, tol=tol,
2660 full_output=True, maxiter=maxiter, disp=disp)
2661 brent.set_bracket(brack)
-> 2662 brent.optimize()
2663 x, fval, nit, nfev = brent.get_result(full_output=True)
2665 success = nit < maxiter and not (np.isnan(x) or np.isnan(fval))
File /tmp/test_venv/lib/python3.12/site-packages/scipy/optimize/_optimize.py:2432, in Brent.optimize(self)
2429 def optimize(self):
2430 # set up for optimization
2431 func = self.func
-> 2432 xa, xb, xc, fa, fb, fc, funcalls = self.get_bracket_info()
2433 _mintol = self._mintol
2434 _cg = self._cg
File /tmp/test_venv/lib/python3.12/site-packages/scipy/optimize/_optimize.py:2401, in Brent.get_bracket_info(self)
2399 xa, xb, xc, fa, fb, fc, funcalls = bracket(func, args=args)
2400 elif len(brack) == 2:
-> 2401 xa, xb, xc, fa, fb, fc, funcalls = bracket(func, xa=brack[0],
2402 xb=brack[1], args=args)
2403 elif len(brack) == 3:
2404 xa, xb, xc = brack
File /tmp/test_venv/lib/python3.12/site-packages/scipy/optimize/_optimize.py:3031, in bracket(func, xa, xb, args, grow_limit, maxiter)
3029 e = BracketError(msg)
3030 e.data = (xa, xb, xc, fa, fb, fc, funcalls)
-> 3031 raise e
3033 return xa, xb, xc, fa, fb, fc, funcalls
BracketError: The algorithm terminated without finding a valid bracket. Consider trying different initial points.
```
### Versions
```shell
System:
python: 3.12.6 (main, Sep 8 2024, 13:18:56) [GCC 14.2.1 20240805]
executable: /usr/bin/python
machine: Linux-6.6.54-2-MANJARO-x86_64-with-glibc2.40
Python dependencies:
sklearn: 1.5.2
pip: 24.2
setuptools: 69.5.1
numpy: 2.1.3
scipy: 1.14.1
Cython: 3.0.11
pandas: 2.2.2
matplotlib: 3.9.2
joblib: 1.4.2
threadpoolctl: 3.5.0
Built with OpenMP: True
threadpoolctl info:
user_api: blas
internal_api: openblas
num_threads: 4
prefix: libscipy_openblas
filepath: /tmp/test_venv/lib/python3.12/site-packages/numpy.libs/libscipy_openblas64_-ff651d7f.so
version: 0.3.27
threading_layer: pthreads
architecture: Haswell
user_api: blas
internal_api: openblas
num_threads: 4
prefix: libscipy_openblas
filepath: /tmp/test_venv/lib/python3.12/site-packages/scipy.libs/libscipy_openblas-c128ec02.so
version: 0.3.27.dev
threading_layer: pthreads
architecture: Haswell
user_api: openmp
internal_api: openmp
num_threads: 4
prefix: libgomp
filepath: /tmp/test_venv/lib/python3.12/site-packages/scikit_learn.libs/libgomp-a34b3233.so.1.0.0
version: None
```
| closed | 2024-11-15T14:41:56Z | 2024-11-15T16:25:05Z | https://github.com/scikit-learn/scikit-learn/issues/30281 | [
"Bug"
] | mahlzahn | 2 |
onnx/onnx | scikit-learn | 6,550 | Is it possible to customize wrapPerspective operator in Opencv with Onnx? | I'm currently using yolov11s-obb and want to rotate the result to front-view. Is there a way to create my own wrapPerspective operator?
| open | 2024-11-21T03:51:50Z | 2024-11-21T03:52:06Z | https://github.com/onnx/onnx/issues/6550 | [
"question"
] | lehoangHUST | 0 |
onnx/onnx | machine-learning | 6,380 | Invalid protobuf error when loading successfully exported onnx model | # Bug Report
### Is the issue related to model conversion?
<!-- If the ONNX checker reports issues with this model then this is most probably related to the converter used to convert the original framework model to ONNX. Please create this bug in the appropriate converter's GitHub repo (pytorch, tensorflow-onnx, sklearn-onnx, keras-onnx, onnxmltools) to get the best help. -->
Error reported in the after-stage of model conversion but can possibly be caused by unreported flaws during conversion.
### Describe the bug
<!-- Please describe the bug clearly and concisely -->
On GCP Vertex VM, my UNet classifier model has been successfully exported to onnx format without raising a warning:
```
import torch
import torch.onnx
from model.UNet3D import UNETCLF
model = UNETCLF(in_channels=7 ,out_channels=1, features=[64, 128, 256, 512, 1024])
model.load_state_dict(torch.load('clf.pth'))
model.eval()
model = model.to('cuda')
dummy_input = torch.randn(1, 7, 16, 64, 64, device='cuda')
torch.onnx.export(model,
dummy_input,
"clf.onnx",
export_params=True,
opset_version=18,
do_constant_folding=True,
input_names=['input'],
output_names=['output'],
dynamic_axes={'input': {0: 'batch_size'},
'output': {0: 'batch_size'}})
```
I then tried to load it locally on VCS with:
```
def get_model():
client = storage.Client()
bucket = client.get_bucket('model-storage-bucket')
blob = bucket.blob('clf.onnx')
model = io.BytesIO()
blob.download_to_file(model)
model.seek(0)
return InferenceSession(model.read(), providers=["CPUExecutionProvider"])
```
It threw an invalid protobuf error:
```
onnxruntime.capi.onnxruntime_pybind11_state.InvalidProtobuf: [ONNXRuntimeError] : 7 : INVALID_PROTOBUF : Failed to load model because protobuf parsing failed.
```
When I looked more closely by:
```
onnx_model = onnx.load(local_file_path)
onnx.checker.check_model(onnx_model)
```
It threw this error message:
```
Error parsing message with type 'onnx.ModelProto'
```
### System information
- OS Platform and Distribution (*e.g. Linux Ubuntu 20.04*): Ubuntu 22.04.4 LTS
- ONNX version (*e.g. 1.13*): 1.16.2 (same on both GCP VM and local device)
- Python version: 3.10.13
- GCC/Compiler version (if compiling from source):
- CMake version:
- Protobuf version: 3.20.2 (same on both GCP VM and local device)
- Visual Studio version (if applicable): 1.89.1
### Reproduction instructions
<!--
Please let me know how you would reproduce the bug if required. I am happy to provide more information and instructions.
- Describe the code to reproduce the behavior.
```
import onnx
model = onnx.load('model.onnx')
...
```
- Attach the ONNX model to the issue (where applicable)-->
### Expected behavior
<!-- A clear and concise description of what you expected to happen. -->
The model to be successfully loaded locally with the above `get_model` function.
### Notes
<!-- Any additional information -->
I have spent quite some time modifying the model so that onnx export finally worked without throwing a warning. It might help if I provide the model here
```
class DoubleConv(nn.Module):
def __init__(self, in_channels, out_channels):
super(DoubleConv, self).__init__()
self.conv = nn.Sequential(
nn.Conv3d(in_channels, out_channels, 3, 1, 1, bias=False),
nn.BatchNorm3d(out_channels),
nn.ReLU(inplace=True),
nn.Conv3d(out_channels, out_channels, 3, 1, 1, bias=False),
nn.BatchNorm3d(out_channels),
nn.ReLU(inplace=True),
)
def forward(self, x):
return self.conv(x)
class UNETCLF(nn.Module):
def __init__(self, in_channels=7, out_channels=1, features=[64, 128, 256, 512, 1024]):
super(UNETCLF, self).__init__()
self.downs = nn.ModuleList()
self.ups = nn.ModuleList()
self.pool = nn.MaxPool3d(kernel_size=(1, 2, 2))
# Down Part of UNET
for feature in features:
self.downs.append(DoubleConv(in_channels, feature))
in_channels = feature
# Up Part of UNET
for feature in reversed(features):
self.ups.append(
nn.ConvTranspose3d(feature*2, feature, kernel_size=(1, 2, 2), stride=(1, 2, 2))
)
self.ups.append(DoubleConv(feature*2, feature))
self.bottleneck = DoubleConv(features[-1], features[-1]*2)
self.final_cov = nn.Conv3d(features[0], out_channels, kernel_size=1)
def forward(self, x):
skip_connections = []
for down in self.downs:
x = down(x)
skip_connections.append(x)
x = self.pool(x)
x = self.bottleneck(x)
skip_connections = skip_connections[::-1]
for idx in range(0, len(self.ups), 2):
x = self.ups[idx](x)
skip_connection = skip_connections[idx//2]
# Use padding instead of dynamic resizing
x = F.pad(x, [0, skip_connection.shape[4] - x.shape[4],
0, skip_connection.shape[3] - x.shape[3],
0, skip_connection.shape[2] - x.shape[2]])
concat_skip = torch.cat((skip_connection, x), dim=1)
x = self.ups[idx+1](concat_skip)
x = self.final_cov(x)
# Use a fixed index for the time dimension
o = x[:, :, x.shape[2]//2, :, :]
return o
``` | closed | 2024-09-21T00:27:56Z | 2024-11-01T14:57:29Z | https://github.com/onnx/onnx/issues/6380 | [] | DagonArises | 2 |
ufoym/deepo | jupyter | 140 | Custom CPU version | MacOs | I am using the CPU version on MacOs but I don't want to import all the DL libraries (just want Keras and Pytroch only).
I tried this command `docker pull ufoym/deepo:keras pytorch` I get an error message:
```
macs-MBP-606:docker_machine macbook$ docker pull ufoym/deepo:keras pytorch
"docker pull" requires exactly 1 argument.
See 'docker pull --help'.
Usage: docker pull [OPTIONS] NAME[:TAG|@DIGEST]
Pull an image or a repository from a registry
```
I also tried to follow the instructions of this [customization section](https://github.com/ufoym/deepo#build-your-own-customized-image-with-lego-like-modules) but I got another error
```
macs-MBP-606:docker_machine macbook$ docker build -t deepo/ .
invalid argument "deepo/" for "-t, --tag" flag: invalid reference format
See 'docker build --help'.
```
any help on this, please?
| closed | 2020-10-18T09:39:45Z | 2020-10-18T13:06:52Z | https://github.com/ufoym/deepo/issues/140 | [] | SoufianeDataFan | 1 |
dgtlmoon/changedetection.io | web-scraping | 1,695 | [feature] cron or exact time scheduler / or trigger check via webhook | **Version and OS**
newest docker image
**Is your feature request related to a problem? Please describe.**
i have an automations that run at exact time, so i need to run www site check at exact time only once a day. current setup doesn't meet my needs
**Describe the solution you'd like**
to have an option to:
1. provide exact time the check will run or
2. invoke check using webhook (for instance from home assistant)
**Describe the use-case and give concrete real-world examples**
i check some sites in the morning and want to run some automations now ots.more or less random run time.. | closed | 2023-07-16T09:46:19Z | 2023-07-17T15:20:43Z | https://github.com/dgtlmoon/changedetection.io/issues/1695 | [
"enhancement"
] | MG-Sky | 4 |
modelscope/data-juicer | streamlit | 224 | Potential performance Issue: Slow read_csv() Function with pandas 2.0.0 | **Issue Description:**
Hello.
I have discovered a performance degradation in the `read_csv` function of pandas version below 2.0.1. And I notice some parts of the repository depend on pandas 2.0.0 in `environments/minimal_requires.txt` and some other dependencies require pandas below 2.0.1. I am not sure whether this performance problem in pandas will affect this repository. I found some discussions on pandas GitHub related to this issue, including [#52546](https://github.com/pandas-dev/pandas/issues/52546) and [#52548](https://github.com/pandas-dev/pandas/pull/52548).
I also found that `app.py` and `demos/data_process_loop/app.py` used the influenced api. There may be more files using the influenced api.
**Suggestion**
I would recommend considering an upgrade to a different version of pandas >= 2.0.1 or exploring other solutions to optimize the performance of `read_csv`.
Any other workarounds or solutions would be greatly appreciated.
Thank you! | closed | 2024-03-02T08:26:50Z | 2024-05-18T09:32:02Z | https://github.com/modelscope/data-juicer/issues/224 | [
"stale-issue"
] | TendouArisu | 5 |
Nemo2011/bilibili-api | api | 516 | [需求] 增加验证码识别 | 使用该库提交视频发现每隔20分钟提交1个视频，提交10个左右就出现了验证码，如果可以解决验证码的问题，上传功能的实用性会大大提高。 | closed | 2023-09-23T21:03:08Z | 2023-09-28T10:08:32Z | https://github.com/Nemo2011/bilibili-api/issues/516 | [
"need",
"feature",
"GUGU"
] | HowHsu | 9 |
streamlit/streamlit | data-visualization | 10,231 | `st.code` is not displayed correctly if the code block is not in the viewport when the page loads | ### Checklist
- [x] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar issues.
- [x] I added a very descriptive title to this issue.
- [x] I have provided sufficient information below to help reproduce this issue.
### Summary
Please go to https://docs.streamlit.io/develop/api-reference/text/st.code to see the issue.
The code block will display:
as long as the code block is not in the viewport when page reload.
### Reproducible Code Example
```Python
import streamlit as st
code = '''def hello():
print("Hello, Streamlit!")'''
st.code(code, language="python")
```
### Steps To Reproduce
1. Go to https://docs.streamlit.io/develop/api-reference/text/st.code
2. make sure the code block is not in the current viewport:
3. Scroll down to see what's going on.
### Expected Behavior
In Chrome, the browser remembers the scroll position, so just reload, and the code block will diplay correctly as it is in the viewport now.
### Current Behavior
`st.code` is not displayed correctly if the code block is not in the viewport when the page loads.
It shows:
```py
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
```
the copy function is correct.
```py
def hello():
print("Hello, Streamlit!")
```
### Is this a regression?
- [x] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: 1.41.1
- Python version:
- Operating System: Windows 10
- Browser: Chrome
### Additional Information
_No response_ | closed | 2025-01-22T17:41:57Z | 2025-01-24T16:19:34Z | https://github.com/streamlit/streamlit/issues/10231 | [
"type:bug",
"status:confirmed",
"priority:P1",
"feature:st.code"
] | Lexachoc | 5 |
babysor/MockingBird | deep-learning | 259 | 模型训练时有 Creating a tensor from a list of numpy.ndarrays is extremely slow.警告会影响训练吗 | 
| closed | 2021-12-10T03:49:55Z | 2021-12-26T03:35:02Z | https://github.com/babysor/MockingBird/issues/259 | [] | luobingit | 11 |
Avaiga/taipy | automation | 2,292 | Have Menu expanded by default or not | ### Description
The goal would be to have like the expandable, a property to expand or not the menu *expanded*.
This will allow users to choose the default look of the menu: either be expanded or not.
This was asked here: https://stackoverflow.com/questions/79234418/taipy-menu-open-by-default
### Acceptance Criteria
- [ ] Any new code is covered by a unit tested.
- [ ] Check code coverage is at least 90%.
### Code of Conduct
- [X] I have checked the [existing issues](https://github.com/Avaiga/taipy/issues?q=is%3Aissue+).
- [ ] I am willing to work on this issue (optional) | open | 2024-11-29T09:53:11Z | 2025-03-19T12:57:24Z | https://github.com/Avaiga/taipy/issues/2292 | [
"📈 Improvement",
"🖰 GUI",
"🟨 Priority: Medium"
] | FlorianJacta | 6 |
coleifer/sqlite-web | flask | 105 | MacBook air | It is not working on my MacBook. It says:
> Traceback (most recent call last):
> File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/peewee.py", line 3133, in connect
> self._state.set_connection(self._connect())
> File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/peewee.py", line 3478, in _connect
> conn = sqlite3.connect(self.database, timeout=self._timeout,
> sqlite3.OperationalError: unable to open database file
>
> During handling of the above exception, another exception occurred:
>
> Traceback (most recent call last):
> File "/Library/Frameworks/Python.framework/Versions/3.10/bin/sqlite_web", line 33, in <module>
> sys.exit(load_entry_point('sqlite-web==0.4.0', 'console_scripts', 'sqlite_web')())
> File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/sqlite_web/sqlite_web.py", line 870, in main
> initialize_app(args[0], options.read_only, password, options.url_prefix,
> File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/sqlite_web/sqlite_web.py", line 837, in initialize_app
> dataset = SqliteDataSet('sqlite:///%s' % filename, bare_fields=True)
> File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/playhouse/dataset.py", line 44, in __init__
> self._database.connect(reuse_if_open=True)
> File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/peewee.py", line 3132, in connect
> with __exception_wrapper__:
> File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/peewee.py", line 2970, in __exit__
> reraise(new_type, new_type(exc_value, *exc_args), traceback)
> File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/peewee.py", line 191, in reraise
> raise value.with_traceback(tb)
> File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/peewee.py", line 3133, in connect
> self._state.set_connection(self._connect())
> File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/peewee.py", line 3478, in _connect
> conn = sqlite3.connect(self.database, timeout=self._timeout,
> peewee.OperationalError: unable to open database file
I am not sure if it me or something else. But when I try to use the >sqlite_web /path/to/database.db it gives me this error message. | closed | 2022-07-29T14:54:23Z | 2022-07-29T15:01:35Z | https://github.com/coleifer/sqlite-web/issues/105 | [] | HerodinSSS | 1 |
tflearn/tflearn | data-science | 840 | How to get the true labels corresponding to 'net' within the graph? | with tf.Graph().as_default():
net = tflearn.input_data(shape=[None, 27, 27, 1])
**# As I understand, a mini-batch of 'train_data' is fed into 'net'**
**# How can I get the true labels (train_label) corresponding to 'net' here ?**
net = tflearn.fully_connected(net, 128, activation='relu')
net = tflearn.fully_connected(net, 2, activation='softmax')
mom = tflearn.Momentum(0.1, lr_decay=0.1, decay_step=7200, staircase=True)
net = tflearn.regression(net, optimizer=mom, loss='categorical_crossentropy')
model = tflearn.DNN(net, tensorboard_verbose=0,clip_gradients=0.)
model.fit(train_data, train_label, n_epoch=10,
batch_size=128, snapshot_epoch=False, snapshot_step=None, shuffle=True, run_id='nn') | open | 2017-07-15T21:52:26Z | 2017-07-20T19:31:17Z | https://github.com/tflearn/tflearn/issues/840 | [] | zhao62 | 2 |
JaidedAI/EasyOCR | pytorch | 759 | TypeError: 'NoneType' object is not iterable in recognize method | I am using the recognize method provided with my own preset horizontal_list_agg list.
The documentation says that free_list by default is None and that I only need either one of horizontal or free list, yet I get this error as seen below:
```
for bbox in free_list:
TypeError: 'NoneType' object is not iterable in recognize method
```
| closed | 2022-06-19T11:45:26Z | 2022-11-29T19:59:57Z | https://github.com/JaidedAI/EasyOCR/issues/759 | [] | amroghoneim | 1 |
noirbizarre/flask-restplus | api | 456 | Issue with @api.representation('application/xml') | I was following the example in help doc to create the below decorator.
```python
@api.representation('application/xml')
def xml(data, code, headers=None):
resp = make_response(dicttoxml.dicttoxml(data), code)
resp.headers.extend(headers or {})
return resp
```
And I also set up
```
api = Api(app, default_mediatype='application/json' )
```
The problem is when I launched swagger dev portal and clicked link: http://localhost:5000/swagger.json ,it returned xml format rather than json format, which doesn't make sense.
| closed | 2018-06-01T15:02:18Z | 2018-06-03T21:19:17Z | https://github.com/noirbizarre/flask-restplus/issues/456 | [] | manbeing | 0 |
openapi-generators/openapi-python-client | fastapi | 176 | Add a note about supported OpenAPI versions | **Describe the bug**
The configuration I'm generating a client for declares `parameters` with `in: body`, the generation fails with openapi-python-client version: 0.5.4 however:
```
ERROR parsing POST /alerts within alert. Endpoint will not be generated.
Parameter must be declared in path or query
Parameter(name='alerts', param_in='body', description='The alerts to create', required=True, deprecated=False, allowEmptyValue=False, style=None, explode=False, allowReserved=False, param_schema=Reference(ref='#/definitions/postableAlerts'), example=None, examples=None, content=None)
```
**To Reproduce**
Steps to reproduce the behavior:
`openapi-python-client generate --url https://raw.githubusercontent.com/prometheus/alertmanager/master/api/v2/openapi.yaml`
I'm not familiar with OpenAPI specs and versions, e.g. if this is relevant? https://swagger.io/docs/specification/2-0/describing-request-body/
| closed | 2020-09-02T17:42:17Z | 2020-09-26T14:07:33Z | https://github.com/openapi-generators/openapi-python-client/issues/176 | [
"📝 documentation",
"✨ enhancement"
] | filippog | 4 |
huggingface/diffusers | pytorch | 10,315 | cogvideo training error | ### Describe the bug
Fine tuning the model on both Gpus reports the following error： RuntimeError: CUDA driver error: invalid argument
Do you know what the problem is?
### Reproduction
[rank1]: ^^^^^^
[rank1]: File "/home/conda_env/controlnet/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
[rank1]: return self._call_impl(*args, **kwargs)
[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank1]: File "/home/conda_env/controlnet/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
[rank1]: return forward_call(*args, **kwargs)
[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank1]: File "/home/conda_env/controlnet/lib/python3.11/site-packages/diffusers-0.32.0.dev0-py3.11.egg/diffusers/models/transformers/cogvideox_transformer_3d.py", line 148, in forward
[rank1]: ff_output = self.ff(norm_hidden_states)
[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank1]: File "/home/conda_env/controlnet/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
[rank1]: return self._call_impl(*args, **kwargs)
[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank1]: File "/home/conda_env/controlnet/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
[rank1]: return forward_call(*args, **kwargs)
[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank1]: File "/home/conda_env/controlnet/lib/python3.11/site-packages/diffusers-0.32.0.dev0-py3.11.egg/diffusers/models/attention.py", line 1242, in forward
[rank1]: hidden_states = module(hidden_states)
[rank1]: ^^^^^^^^^^^^^^^^^^^^^
[rank1]: File "/home/conda_env/controlnet/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
[rank1]: return self._call_impl(*args, **kwargs)
[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank1]: File "/home/conda_env/controlnet/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
[rank1]: return forward_call(*args, **kwargs)
[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank1]: File "/home/conda_env/controlnet/lib/python3.11/site-packages/diffusers-0.32.0.dev0-py3.11.egg/diffusers/models/activations.py", line 88, in forward
[rank1]: hidden_states = self.proj(hidden_states)
[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^
[rank1]: File "/home/conda_env/controlnet/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
[rank1]: return self._call_impl(*args, **kwargs)
[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank1]: File "/home/conda_env/controlnet/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
[rank1]: return forward_call(*args, **kwargs)
[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank1]: File "/home/conda_env/controlnet/lib/python3.11/site-packages/torch/nn/modules/linear.py", line 125, in forward
[rank1]: return F.linear(input, self.weight, self.bias)
[rank1]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank1]: RuntimeError: CUDA driver error: invalid argument
Steps: 0%| | 0/133600000 [00:12<?, ?it/s]
[rank0]:[W1220 14:39:33.155016577 ProcessGroupNCCL.cpp:1250] Warning: WARNING: process group has NOT been destroyed before we destruct ProcessGroupNCCL. On normal program exit, the application should call destroy_proce ss_group to ensure that any pending NCCL operations have finished in this process. In rare cases this process can exit before this point and block the progress of another member of the process group. This constraint ha s always been present, but this warning has only been added since PyTorch 2.4 (function operator())
W1220 14:39:35.723000 381051 site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 381224 closing signal SIGTERM
E1220 14:39:36.039000 381051 site-packages/torch/distributed/elastic/multiprocessing/api.py:869] failed (exitcode: 1) local_rank: 0 (pid: 381223) of binary: /home/conda_env/controlnet/bin/python
Traceback (most recent call last):
File "/home/conda_env/controlnet/bin/accelerate", line 8, in <module>
sys.exit(main())
^^^^^^
File "/home/conda_env/controlnet/lib/python3.11/site-packages/accelerate/commands/accelerate_cli.py", line 48, in main
args.func(args)
File "/home/conda_env/controlnet/lib/python3.11/site-packages/accelerate/commands/launch.py", line 1159, in launch_command
multi_gpu_launcher(args)
File "/home/conda_env/controlnet/lib/python3.11/site-packages/accelerate/commands/launch.py", line 793, in multi_gpu_launcher
distrib_run.run(args)
File "/home/conda_env/controlnet/lib/python3.11/site-packages/torch/distributed/run.py", line 910, in run
elastic_launch(
File "/home/conda_env/controlnet/lib/python3.11/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
return launch_agent(self._config, self._entrypoint, list(args))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/conda_env/controlnet/lib/python3.11/site-packages/torch/distributed/launcher/api.py", line 269, in launch_agent
raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
============================================================
train_controlnet.py FAILED
------------------------------------------------------------
Failures:
<NO_OTHER_FAILURES>
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
time : 2024-12-20_14:39:35
host : robot
rank : 0 (local_rank: 0)
exitcode : 1 (pid: 381223)
error_file: <N/A>
traceback : To enable traceback see: https:/pytorch.org/docs/stable/elastic/errors.html
============================================================
### Logs
_No response_
### System Info
ubuntu20.04
cuda 12.0
torch 2.5
diffusers 0.32.0.dev0
### Who can help?
_No response_ | closed | 2024-12-20T06:47:32Z | 2025-01-12T05:44:35Z | https://github.com/huggingface/diffusers/issues/10315 | [
"bug",
"training"
] | linwenzhao1 | 4 |
sktime/pytorch-forecasting | pandas | 1,178 | How to make the model use partial future known information | PyTorch-Forecasting version: 0.10.2
PyTorch version:
Python version: 3.8.5
Operating System: Windows
The TFT accepts 3 inputs: static, observed (known up to t), future (known up to t+k), where k is the final point.
Now, assume you want a forecast up to t+10.
I have a some time series as Xs, which are known up to t, other up to t+1, other up to t+4 ecc, but my Y only up to t.
I have so far only one choice, thus, to drop those additional values in the future a take the series back to t as Y. Then I plug these Xs into the bucket of observed input.
In my opinion, it is a waste of information so I suppose there is a solution to this.
On the other hand I could try to insert these variable into the known future, but they are not known up to the end t+10, only t+2, so I may zero-pad from t+3 to t+10.
Would this work? I am concerned that this might run til the end somehow, but can I trust this? is there another workaround?
This feature can be also useful for scenario analysis:
what if gdp (x variable) drop of 5% in the next two samples (t+2), how my t+10 forecast of Y is affected by this?
Can anybody advice?
| open | 2022-11-10T10:21:55Z | 2022-12-12T16:58:19Z | https://github.com/sktime/pytorch-forecasting/issues/1178 | [] | LuigiSimeone | 1 |
aio-libs/aiohttp | asyncio | 10,141 | 403 "Please enable cookies." when Request a Special Cloudflare Website | ### Describe the bug
When I access the website using aiohttp, a 403 "Please enable cookies" error occurs. But when I use other clients to access it, it works fine.
### To Reproduce
```python
import sys
import asyncio
import aiohttp # ```pip install aiohttp[speedups]``` # https://docs.aiohttp.org/en/stable/index.html#installing-all-speedups-in-one-command
# 版本常量
USER_AGENT = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36 Edg/131.0.0.0 LightnovelSpider/5' # 客户端用户代理：前部与最新的Edge浏览器保持一致，尾部标记了本程序的版本。
# 环境常量：根据实际环境，可能需要在每次运行前手动变更的常量。
PROXY = 'http://127.0.0.1:7897' # 必填。如果连接到一个代理池，注意检查代理池中各个代理节点的可用性。
COOKIES = '''Hidden for Privacy''' # 必填。需要提供一组COOKIES供会话初始化。
async def fetch(url:str, referer:str=None, callback=lambda*args:None, cb_kwargs:dict=dict()) -> None:
headers = {
'User-Agent': USER_AGENT
}
async with aiohttp.ClientSession(
proxy= PROXY,
cookies= {i.split("=")[0]:i.split("=")[-1] for i in COOKIES.split("; ")},
) as session:
async with session.get(url, headers=headers, ssl=False) as response:
print(response.status)
async def main():
await fetch('https://tw.linovelib.com/novel/1.html')
await asyncio.sleep(1) # https://docs.aiohttp.org/en/stable/client_advanced.html#graceful-shutdown
if __name__ == '__main__':
# https://github.com/aio-libs/aiodns?tab=readme-ov-file#note-for-windows-users
# https://github.com/aio-libs/aiodns/issues/86#issuecomment-1674906449
# https://github.com/nathom/streamrip/issues/729#issuecomment-2388503896
if sys.platform == 'win32':
asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy())
asyncio.run(main())
```
`403`
```html
<!DOCTYPE html>
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<style>body{margin:0;padding:0}</style>
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if (!navigator.cookieEnabled) {
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var cookieEl = document.getElementById('cookie-alert');
cookieEl.style.display = 'block';
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}
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</html>
```
### Expected behavior
```python
import urllib3
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
import requests
# 版本常量
USER_AGENT = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36 Edg/131.0.0.0 LightnovelSpider/5' # 客户端用户代理：前部与最新的Edge浏览器保持一致，尾部标记了本程序的版本。
# 环境常量：根据实际环境，可能需要在每次运行前手动变更的常量。
PROXY = 'http://127.0.0.1:7897' # 必填。如果连接到一个代理池，注意检查代理池中各个代理节点的可用性。
COOKIES = '''Hidden for Privacy''' # 必填。需要提供一组COOKIES供会话初始化。
if __name__ == '__main__':
headers = {
'User-Agent': USER_AGENT
}
response = requests.get(
url= 'https://tw.linovelib.com/novel/1.html',
cookies= {i.split("=")[0]:i.split("=")[-1] for i in COOKIES.split("; ")},
proxies= {
'http': PROXY,
'https': PROXY
},
headers= headers,
verify= False
)
print(response.status_code)
```
`200`
```html
<!DOCTYPE html>
<html lang="zh-Hant">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
<title>惡魔高校DxD線上看_嗶哩輕小說</title>
<meta name="keywords" content="惡魔高校DxD(High School DxD)在線閱讀,惡魔高校DxD(High School DxD)輕小說,石踏一榮,富士見文庫,嗶哩輕小說">
<meta name="description" content="惡魔高校DxD(High School DxD)是石踏一榮所寫的富士見文庫輕小說,嗶哩輕小說免費提供惡魔高校DxD(High School DxD)最新清爽乾淨的文字章節在線閱讀">
<meta name="applicable-device" content="mobile" />
<meta name="apple-mobile-web-app-capable" content="yes" />
<meta name="viewport" content="initial-scale=1.0,maximum-scale=1.0,minimum-scale=1.0,user-scalable=0,width=device-width" />
<meta name="theme-color" content="#232323" media="(prefers-color-scheme: dark)" />
<meta property="og:type" content="novel" />
<meta property="og:title" content="惡魔高校DxD" />
<meta property="og:description" content="我，兵藤一誠是個年齡＝沒女朋友經歷的高二生。這樣的我也交到女朋友了！抱歉了朋友，我要先你們一步踏上大人的階梯！照理來說應該是這樣才對，為什麼我會被女朋友殺死？
明明什麼甜頭都沒嘗到，這個世界還有天理嗎？
然而全校第一美少女，莉雅絲·吉蒙里學姊救了這樣的我。自稱是惡魔的她，告訴我一個衝擊的事實。
「你已經轉生變成惡魔了。為我工作吧！」
在學姊的胸部和獎勵的引誘之下，我身為惡魔僕人的人生就此展開。
純粹靠著氣勢與煩惱，校園奇幻戰鬥戀愛物語第一集！" />
<meta property="og:image" content="https://tw.linovelib.com/files/article/image/0/1/1s.jpg" />
<meta property="og:novel:category" content="富士見文庫" />
<meta property="og:novel:author" content="石踏一榮" />
<meta property="og:novel:book_name" content="惡魔高校DxD" />
<meta property="og:novel:read_url" content="https://tw.linovelib.com/novel/1/catalog" />
<meta property="og:url" content="https://tw.linovelib.com/novel/1.html" />
<meta property="og:novel:status" content="完結" />
<meta property="og:novel:author_link" content="https://tw.linovelib.com/authorarticle/石踏一榮.html" />
<meta property="og:novel:update_time" content='2024-02-25 23:45:52' />
<meta property="og:novel:latest_chapter_name" content="短篇集 DX.4 學生會與利維坦 後記" />
<meta property="og:novel:latest_chapter_url" content="/novel/1/225508.html" />
<link rel="stylesheet" href="https://tw.linovelib.com/themes/zhmb/css/info.css?v0118b5">
<link rel="alternate" hreflang="zh-Hans" href="https://www.bilinovel.com/novel/1.html" />
<script src="https://tw.linovelib.com/themes/zhmb/js/jquery-3.3.1.js"></script>
<script type="text/javascript" src="/scripts/darkmode.js"></script>
<script src="https://tw.linovelib.com/themes/zhmb/js/core.js?v0821b2"></script>
<script async src="https://tw.linovelib.com/themes/zhmb/js/lazysizes.min.js"></script>
<script type="text/javascript" src="https://tw.linovelib.com/scripts/common.js?v0316b1" charset="UTF-8"></script>
<script type="text/javascript">var ual = navigator.language.toLowerCase();if(ual == 'zh-cn'){window.location.replace("https://w.linovelib.com/novel/1.html");}</script>
<style>}.guide-content{backdrop-filter: blur(50px);-webkit-backdrop-filter: blur(50px);background-color: rgba(255, 255, 255, 0.1);}.sp-dark-mode .guide-content{background-color: rgba(0, 0, 0, 0.1);color: #eee;}.sp-dark-mode .header{background-color: unset;}.book-detail-btn .icon {margin-right: 0.25rem;}.score-tip{position: relative;display: flex; justify-content: space-between; align-items: center;color: rgba(255,255,255,.7);line-height: .65rem; font-size: .6rem;}.orange{color:rgba(255,126,0,.65);}@media (prefers-color-scheme: dark){.guide-content{color: #eee;}}@media screen and (max-width: 600px){.header a, .header-operate>.icon, .header-operate-a{color: rgba(255,57,85, .15);}}</style>
<style>@media screen and (min-width:768px){.page-fans .book-ol li, .trigger-book-comment .book-ol li{width: calc(50% - 6px);display: inline-block;vertical-align: top;}.trigger-book-comment .book-li:nth-child(3)::after, .page-fans .book-ol-comment .book-li:nth-child(3)::after{border-bottom: none;}.module-slide-ol{white-space: normal;padding-bottom: .75rem;}.module-slide-li {width: calc(19% - 5px);}.module-slide-a {width: 6.125rem;padding: 0.75rem 1.45rem 0.5rem;}.module-slide-img {height: 8.5rem;}.book-comment-p{min-height: 2.5625rem;}.corner{width: 45px;height: 45px;}.corner>em{right: -20px;line-height: 22px;font-size: 15px;}}</style>
</head>
<body id="scroll">
<script src="https://tw.linovelib.com/themes/zhmb/js/sprite.js"></script>
<div class="page page-book-detail">
<div class="content">
<header id="header" class="header"><a href="/" class="header-back jsBack"><svg class="icon icon-arrow-l"><title>返回</title><use xlink:href="#icon-arrow-l"></use></svg></a>
<!--<span class="header-back-title">惡魔高校DxD</span>-->
<div class="header-operate">
<a id="openSearchPopup" href="javascript:" class="icon icon-search" title="搜索"><svg><use xlink:href="#icon-search"></use></svg></a>
<a id="openGuide" href="javascript:" class="icon icon-more" title="更多" data-rel="guide"></a>
</div>
</header>
<!-- 更多內容的導航 S -->
<div id="guide" class="guide">
<i id="guideOverlay1" class="guide-overlay"></i>
<div class="guide-content">
<nav class="guide-nav">
<a href="/" class="guide-nav-a">
<i class="icon icon-home"></i>
<h4 class="guide-nav-h">首頁</h4>
</a>
<a href="/alltopics" class="guide-nav-a">
<i class="icon icon-sort"></i>
<h4 class="guide-nav-h">圈子</h4>
</a>
<a href="/top.html" class="guide-nav-a">
<i class="icon icon-rank"></i>
<h4 class="guide-nav-h">排行榜</h4>
</a>
<a href="/wenku/" class="guide-nav-a">
<i class="icon icon-fuli"></i>
<h4 class="guide-nav-h">文庫</h4>
</a>
<a href="/topfull/postdate/1.html" class="guide-nav-a">
<i class="icon icon-end"></i>
<h4 class="guide-nav-h">完本</h4>
</a>
<a href="/user.php" class="guide-nav-a ">
<i class="icon icon-account"></i>
<h4 class="guide-nav-h">賬戶</h4>
</a>
</nav>
<div class="guide-footer">
<a href="/bookcase.php" class="btn-primary" data-size="14">我的收藏</a>
</div>
</div>
</div>
<!-- 更多內容的導航 E -->
<!-- 公用頭部 E -->
<div id="bookDetailWrapper" class="module module-merge book-detail-x">
<img src="https://tw.linovelib.com/files/article/image/0/1/1s.jpg?1708873318" class="book-cover-blur" alt="惡魔高校DxD">
<div class="book-detail-info">
<div class="book-layout">
<div class="module-book-cover">
<div class="module-item-cover">
<img src="https://tw.linovelib.com/files/article/image/0/1/1s.jpg?1708873318" class="book-cover" alt="惡魔高校DxD">
</div>
</div>
<div class="book-cell">
<h1 class="book-title">惡魔高校DxD</h1>
<div class="book-rand-a">
<span class="authorname"><a href="/authorarticle/石踏一榮.html">石踏一榮</a></span><i class="char-pipe">,</i><span class="illname"><a href="/illustratorarticle/みやま零.html"><ruby>みやま零<rt>(插畫)</rt></ruby></a></span> 著
</div>
<p class="book-meta book-layout-inline"><!-- 次閱讀<span class="char-pipe">/</span> -->26733 人收藏<span class="char-pipe">/</span>4361 次推薦<b class="dot-pipe">/</b></p><p class="book-meta book-layout-inline">398.1 萬字<span class="char-pipe">|</span>完結<span class="char-pipe">|</span>已動畫化</p>
<p class="book-meta">
<span class="tag-small-group origin-left">
<em class="tag-small red"><a href="/tagarticle/63/1.html">校園</a></em><em class="tag-small red"><a href="/tagarticle/15/1.html">奇幻</a></em><em class="tag-small red"><a href="/tagarticle/18/1.html">戰鬥</a></em><em class="tag-small red"><a href="/tagarticle/48/1.html">後宮</a></em><em class="tag-small red"><a href="/tagarticle/225/1.html"> 青梅竹馬</a></em><em class="tag-small red"><a href="/tagarticle/223/1.html">人外</a></em><em class="tag-small orange"><a href="/wenku/lastupdate_223_0_0_0_0_0_0_1_0.html">富士見文庫</a></em><em class="tag-small gray"><a href="/wenku/lastupdate_0_0_0_1_0_0_0_1_0.html">日本輕小說</a></em>
</span>
</p>
</div>
</div>
<div class="book-detail-btn" data-read-status="" data-bookshelf-status="">
<ul class="btn-group">
<li class="btn-group-cell"><a href="/novel/1/catalog" class="btn-normal red" id="btnReadBook">開始閱讀</a></li>
<li class="btn-group-cell"><a href="javascript:" id="a_addbookcase" onclick="toggleBookcaseStatus(this, 1);" class="btn-normal white"><svg class="icon blue"><use xlink:href="#icon-booklist-star"></use></svg>書架</a></li>
<li class="btn-group-cell"><a href="/download/1.html" class="btn-normal white"><svg class="icon blue"><use xlink:href="#icon-down"></use></svg>下載</a></li>
<li class="btn-group-cell"><a href="/wiki/1.html" class="btn-normal purple"><svg class="icon white"><use xlink:href="#icon-qi"></use></svg>詳解</a></li>
</ul><input id="shareurl" type="text" readonly style='opacity: 0;position:fixed;z-index: -1000;' value="share.linovelib.net/1-0" />
</div>
</div>
</div>
<div class="module module-merge">
<section id="bookSummary" class="book-summary">
<content>我，兵藤一誠是個年齡＝沒女朋友經歷的高二生。這樣的我也交到女朋友了！抱歉了朋友，我要先你們一步踏上大人的階梯！照理來說應該是這樣才對，為什麼我會被女朋友殺死？<br />
明明什麼甜頭都沒嘗到，這個世界還有天理嗎？<br />
然而全校第一美少女，莉雅絲·吉蒙里學姊救了這樣的我。自稱是惡魔的她，告訴我一個衝擊的事實。<br />
「你已經轉生變成惡魔了。為我工作吧！」<br />
在學姊的胸部和獎勵的引誘之下，我身為惡魔僕人的人生就此展開。<br />
純粹靠著氣勢與煩惱，校園奇幻戰鬥戀愛物語第一集！</content>
<div class="backupname"><em>別名</em><span class="bkname-body gray">High School DxD</span></div>
<span class="book-summary-more"><svg class="icon icon-arrow-r"><use xlink:href="#icon-arrow-r"></use></svg></span></section>
<a href="/novel/1/catalog" class="book-meta book-status">
<div class="book-meta-l"><strong class="book-spt">最后更新</strong><span class="char-dot">·</span>2024-02-25</div>
<div class="book-meta-r">
<p class="gray ell">短篇集 DX.4 學生會與利維坦 後記</p>
<svg class="icon icon-arrow-r"><use xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="#icon-arrow-r"></use></svg>
</div>
</a>
</div>
<!-- 互動區 -->
<div class="module">
<ul id="payTicketsX" class="btn-group">
<li class="btn-group-cell">
<a href="/gift.php?id=1" id="a_gift" class="book-pay book-pay-a">
<i class="icon icon-gift"></i>
<h5 class="book-pay-h">鮮花</h5>
<p class="book-pay-p"><span class="month-ticket-cnt">8547</span>束</p>
</a>
</li>
<li class="btn-group-cell">
<a href="javascript:" id="a_uservote" onclick="Ajax.Tip('https://tw.linovelib.com/modules/article/uservote.php?id=1', {method: 'POST'});" class="book-pay book-pay-a">
<i class="icon icon-pay-like"></i>
<h5 class="book-pay-h">推薦票</h5>
<p class="book-pay-p">本週<span class="recomm-ticket-cnt">12</span>推薦</p>
</a>
</li>
<li class="btn-group-cell">
<a href="/gift.php?id=1&type=egg" class="book-pay book-pay-a">
<i class="icon icon-checkin-egg"></i>
<h5 class="book-pay-h">臭雞蛋</h5>
<p class="book-pay-p"><span class="reward-week-cnt">20</span>個</p>
</a>
</li>
<li class="btn-group-cell">
<a href="/fansheat_1_1.html" class="book-pay">
<i class="icon icon-fans"></i>
<h5 class="book-pay-h">互動</h5>
<p class="book-pay-p"><span class="reward-week-cnt">99</span>⁺</p>
</a>
</li>
</ul>
<!-- 評分區 -->
<a href="javascript:" class="subject-rating-root" id="asideTrigger">
<div class="sub-score">
<div class="score-tip"><span>參與評價，表達對作品的態度</span><div class="myrating">我的評價<div class="star-display"><div class="rating"><div class="rating-stars"><div class="rateunit"><span style="width:calc(0/10*100%);" class="rpercent"></span></div></div></div></div><svg class="icon icon-arrow-r"><use xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="#icon-arrow-r"></use></svg></div></div>
<div class="sub-content" id="a_userate">
<div class="sub-rating">
<div class="score-num">9.9</div>
<div class="star-display"><div class="rating"><div class="rating-stars"><div class="rateunit"><span style="width:calc(9.9/10*100%);" class="rpercent"></span></div></div></div><p class="done-count"><em>1799 人評價</em></p></div></div>
<div class="sub-chart"><div class="star-stats"><div class="stars-wrap"><span class="rating-star-icon"></span><span class="rating-star-icon"></span><span class="rating-star-icon"></span><span class="rating-star-icon"></span><span class="rating-star-icon"></span></div><div class="chart-wrap"><span class="rating-progress" style="width: calc(1764/1799*100%);"></span></div></div><div class="star-stats"><div class="stars-wrap"><span class="rating-star-icon"></span><span class="rating-star-icon"></span><span class="rating-star-icon"></span><span class="rating-star-icon"></span></div><div class="chart-wrap"><span class="rating-progress" style="width: calc(19/1799*100%);"></span></div></div><div class="star-stats"><div class="stars-wrap"><span class="rating-star-icon"></span><span class="rating-star-icon"></span><span class="rating-star-icon"></span></div><div class="chart-wrap"><span class="rating-progress" style="width: calc(8/1799*100%);"></span></div></div><div class="star-stats"><div class="stars-wrap"><span class="rating-star-icon"></span><span class="rating-star-icon"></span></div><div class="chart-wrap"><span class="rating-progress" style="width: calc(3/1799*100%);"></span></div></div><div class="star-stats"><div class="stars-wrap"><span class="rating-star-icon"></span></div><div class="chart-wrap"><span class="rating-progress" style="width: calc(5/1799*100%);"></span></div></div>
</div>
</div>
</div>
</a>
<!-- 粉絲榜 -->
<style>.page-fans .book-ol-rank .book-layout {padding-top: 0.75rem;padding-bottom: 0.75rem;padding-left: 3.125rem;margin-left: -3.125rem;}.page-fans .book-title{font-size: .8125rem;}.fans-point {color: gray;font-size: .725rem;font-family: pingfang sc;}.page-fans .book-title-r img{position: absolute; top: 55%; bottom: 0; right: 1.125rem; width: 3.125rem;margin: auto; margin-top: -0.70625rem;}.book-ol-rank .book-li::before{font:1em/1.5em 'PingFang SC';position:absolute;top:50%;bottom:0;left:-2.125rem;margin:auto;margin-top:-.70625rem;content:counter(bookrank);counter-increment:bookrank;color:#b8b8b8;width:1.375rem;height:1.8125rem;text-align:center}.book-ol-rank 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.book-li-fou::before{left: -1.125rem;}}</style>
<div class="module-content page-fans">
<ol class="book-ol book-ol-comment book-ol-rank">
<li class="book-li book-li-fir"><!--<em></em>-->
<div class="book-layout">
<div class="book-author-vv fans-avatar">
<img class="book-author-avatar lazyload" data-src="https://tw.linovelib.com/files/system/avatar/334/334259.jpg" src="https://tw.linovelib.com/images/noavatar.jpg" data-expand='50' onerror="this.src='https://tw.linovelib.com/images/noavatar.jpg';this.onerror=null;" alt="國家隊-零貳頭像">
</div>
<div class="book-cell">
<div class="book-title-x">
<div class="book-title-r">
<img src="/images/fans/label_top01.png">
</div>
<div class="book-title-l">
<p class="book-title" title="粉絲榜第1位">國家隊-零貳</p>
<span class="fans-point">熱力值 4784</span>
</div>
</div>
</div>
</div>
</li>
<li class="book-li book-li-sec"><!--<em></em>-->
<div class="book-layout">
<div class="book-author-vv fans-avatar">
<img class="book-author-avatar lazyload" data-src="https://tw.linovelib.com/files/system/avatar/531/531512.jpg" src="https://tw.linovelib.com/images/noavatar.jpg" data-expand='50' onerror="this.src='https://tw.linovelib.com/images/noavatar.jpg';this.onerror=null;" alt="真尋歐尼醬頭像">
</div>
<div class="book-cell">
<div class="book-title-x">
<div class="book-title-r">
<img src="/images/fans/label_top03.png">
</div>
<div class="book-title-l">
<p class="book-title" title="粉絲榜第2位">真尋歐尼醬</p>
<span class="fans-point">熱力值 621</span>
</div>
</div>
</div>
</div>
</li>
<li class="book-li book-li-thi"><!--<em></em>-->
<div class="book-layout">
<div class="book-author-vv fans-avatar">
<img class="book-author-avatar lazyload" data-src="https://tw.linovelib.com/files/system/avatar/243/243404.jpg" src="https://tw.linovelib.com/images/noavatar.jpg" data-expand='50' onerror="this.src='https://tw.linovelib.com/images/noavatar.jpg';this.onerror=null;" alt="kinson72002頭像">
</div>
<div class="book-cell">
<div class="book-title-x">
<div class="book-title-r">
<img src="/images/fans/label_top03.png">
</div>
<div class="book-title-l">
<p class="book-title" title="粉絲榜第3位">kinson72002</p>
<span class="fans-point">熱力值 541</span>
</div>
</div>
</div>
</div>
</li>
<li class="book-li book-li-fou"><!--<em></em>-->
<div class="book-layout">
<div class="book-author-vv fans-avatar">
<img class="book-author-avatar lazyload" data-src="https://tw.linovelib.com/files/system/avatar/248/248331.jpg" src="https://tw.linovelib.com/images/noavatar.jpg" data-expand='50' onerror="this.src='https://tw.linovelib.com/images/noavatar.jpg';this.onerror=null;" alt="1051207658頭像">
</div>
<div class="book-cell">
<div class="book-title-x">
<div class="book-title-r">
<img src="/images/fans/label_top03.png">
</div>
<div class="book-title-l">
<p class="book-title" title="粉絲榜第4位">1051207658</p>
<span class="fans-point">熱力值 500</span>
</div>
</div>
</div>
</div>
</li>
</ol>
<a href="/fans/1" class="book-li-more book-li-more-comments">更多粉絲</a>
</div>
</div>
<!-- 書評區 -->
<div class="module trigger-book-comment">
</div>
<!-- 作者區 -->
<div class="module">
<div class="module-header">
<div class="module-header-l">
<h3 class="module-title">本書作者</h3>
</div>
</div>
<div class="module-content">
<ol class="book-ol book-ol-author">
<li class="book-li">
<a href="https://tw.linovelib.com/authorarticle/石踏一榮.html" class="book-layout books-author">
<div class="book-author-vv" role="option">
<img class="book-author-avatar" src="/images/noauthor.jpg" alt="石踏一榮的頭像">
<div><aria>作者等級：</aria><em class="tag-honor orange"><i>Lv.5</i></em></div>
</div>
<div class="book-cell">
<div class="book-title-x">
<h4 class="book-title">石踏一榮</h4>
</div>
<p class="book-desc">輕小說作家</p>
</div>
<svg class="icon icon-arrow-r" aria-hidden="true"><use xlink:href="#icon-arrow-r"></use></svg>
</a>
</li>
</ol>
<style>.page-book-detail .book-ol-author .books-author{padding-bottom:0}</style><div class="module-slide"><ol class="module-slide-ol" id="book-friend-list-container"><li class="module-slide-li"><a href="/novel/1.html" class="module-slide-a"><span class="corner orange"><em>9.9</em></span><img src="https://tw.linovelib.com/themes/zhmb/images/book-cover-no.svg" data-src="https://tw.linovelib.com/files/article/image/0/1/1s.jpg?1708873318" class="module-slide-img lazyload" data-expand='50' alt="惡魔高校DxD"><figcaption class="module-slide-caption">惡魔高校DxD</figcaption><p class="module-slide-author"></p></a></li><li class="module-slide-li"><a href="/novel/2570.html" class="module-slide-a"><span class="corner orange"><em>9.9</em></span><img src="https://tw.linovelib.com/themes/zhmb/images/book-cover-no.svg" data-src="https://tw.linovelib.com/files/article/image/2/2570/2570s.jpg?1717421328" class="module-slide-img lazyload" data-expand='50' alt="真惡魔高校DxD"><figcaption class="module-slide-caption">真惡魔高校DxD</figcaption><p class="module-slide-author"></p></a></li><li class="module-slide-li"><a href="/novel/2510.html" class="module-slide-a"><span class="corner orange"><em>9.9</em></span><img src="https://tw.linovelib.com/themes/zhmb/images/book-cover-no.svg" data-src="https://tw.linovelib.com/files/article/image/2/2510/2510s.jpg?1708879030" class="module-slide-img lazyload" data-expand='50' alt="墮天的狗神 -SLASHDOG-"><figcaption class="module-slide-caption">墮天的狗神 -SLASHDOG-</figcaption><p class="module-slide-author"></p></a></li></ol></div>
</div>
</div>
<!-- 譯者者區 -->
<!-- 標籤區 -->
<div class="module">
<div class="module-header">
<div class="module-header-l">
<h3 class="module-title">作品標籤</h3>
</div>
</div>
<div class="module-content">
<div class="search-tags">
<a href="/wenku/lastupdate_63_0_0_0_0_0_0_1_0.html" class="btn-line-gray">校園</a>
<a href="/wenku/lastupdate_15_0_0_0_0_0_0_1_0.html" class="btn-line-gray">奇幻</a>
<a href="/wenku/lastupdate_18_0_0_0_0_0_0_1_0.html" class="btn-line-gray">戰鬥</a>
<a href="/wenku/lastupdate_48_0_0_0_0_0_0_1_0.html" class="btn-line-gray">後宮</a>
<a href="/wenku/lastupdate_225_0_0_0_0_0_0_1_0.html" class="btn-line-gray">青梅竹馬</a>
<a href="/wenku/lastupdate_223_0_0_0_0_0_0_1_0.html" class="btn-line-gray">人外</a>
</div>
</div>
</div>
<!-- 推薦區 -->
<div class="module" data-load-status="wait">
<div class="module-header">
<div class="module-header-l">
<h3 class="module-title">富士見文庫輕小說推薦</h3>
</div>
</div>
<div class="module-content">
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```
### Logs/tracebacks
```python-traceback
None.
```
### Python Version
```console
$ python --version
Python 3.13.0
```
### aiohttp Version
```console
$ python -m pip show aiohttp
Name: aiohttp
Version: 3.11.8
Summary: Async http client/server framework (asyncio)
Home-page: https://github.com/aio-libs/aiohttp
Author:
Author-email:
License: Apache-2.0
Location: C:\Users\14485\AppData\Roaming\Python\Python313\site-packages
Requires: aiohappyeyeballs, aiosignal, attrs, frozenlist, multidict, propcache, yarl
Required-by:
```
### multidict Version
```console
$ python -m pip show multidict
Name: multidict
Version: 6.1.0
Summary: multidict implementation
Home-page: https://github.com/aio-libs/multidict
Author: Andrew Svetlov
Author-email: andrew.svetlov@gmail.com
License: Apache 2
Location: C:\Users\14485\AppData\Roaming\Python\Python313\site-packages
Requires:
Required-by: aiohttp, yarl
```
### propcache Version
```console
$ python -m pip show propcache
Name: propcache
Version: 0.2.0
Summary: Accelerated property cache
Home-page: https://github.com/aio-libs/propcache
Author: Andrew Svetlov
Author-email: andrew.svetlov@gmail.com
License: Apache-2.0
Location: C:\Users\14485\AppData\Roaming\Python\Python313\site-packages
Requires:
Required-by: aiohttp, yarl
```
### yarl Version
```console
$ python -m pip show yarl
Name: yarl
Version: 1.18.0
Summary: Yet another URL library
Home-page: https://github.com/aio-libs/yarl
Author: Andrew Svetlov
Author-email: andrew.svetlov@gmail.com
License: Apache-2.0
Location: C:\Users\14485\AppData\Roaming\Python\Python313\site-packages
Requires: idna, multidict, propcache
Required-by: aiohttp
```
### OS
Windows 11
### Related component
Client
### Additional context
_No response_
### Code of Conduct
- [X] I agree to follow the aio-libs Code of Conduct | closed | 2024-12-07T09:32:54Z | 2024-12-10T17:02:26Z | https://github.com/aio-libs/aiohttp/issues/10141 | [
"bug"
] | CodingMoeButa | 14 |
horovod/horovod | tensorflow | 2,940 | [MAC OS] libc++abi.dylib: terminating with uncaught exception of type gloo::EnforceNotMet | **Environment:**
1. Framework: (TensorFlow, Keras, PyTorch, MXNet) Tensorflow
2. Framework version: 2.4.1
3. Horovod version: 0.22.0
4. MPI version: (NO, with gloo)
5. CUDA version:
6. NCCL version:
7. Python version: 3.7
8. Spark / PySpark version:
9. Ray version:
10. OS and version: macOS Big Sur 11.2.3
11. GCC version:
```
Configured with: --prefix=/Library/Developer/CommandLineTools/usr --with-gxx-include-dir=/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/usr/include/c++/4.2.1
Apple clang version 12.0.0 (clang-1200.0.32.29)
Target: x86_64-apple-darwin20.3.0
Thread model: posix
```
12. CMake version: 3.20.1
**Bug report:**
Please describe erroneous behavior you're observing and steps to reproduce it.
```python
import horovod.tensorflow as hvd
hvd.init()
```
then, the python command line terminated, with the following exception message:
```
libc++abi.dylib: terminating with uncaught exception of type gloo::EnforceNotMet: [enforce fail at /private/var/folders/l3/18pljl2s6q3d3h_kk1y5nv8h0000gn/T/pip-install-xy0ow8d0/horovod_98a796e5f3cf40929f5431d36dccb56b/third_party/compatible_gloo/gloo/transport/uv/device.cc:129] rp != nullptr. Unable to find address for: 314159
```
In other platform: linux (cpu), linux(NCCL2 + GPU), works fine.
So why such error occurred in mac, and how to solve it? Any help will be highly appreciated.
| open | 2021-05-26T07:19:13Z | 2021-08-14T00:53:01Z | https://github.com/horovod/horovod/issues/2940 | [
"bug"
] | ericxsun | 4 |
feder-cr/Jobs_Applier_AI_Agent_AIHawk | automation | 682 | [HELP WANTED]: <Errno2 during job application: No such file or directory: 'data_folder\\output\\failed.json'> | ### Issue description
Everything works until it attempts to apply to a job, then I ger the following error:
2024-10-30 12:47:20.673 | DEBUG | src.aihawk_job_manager:extract_job_information_from_tile:459 - Job information extracted: Senior Quality Engineer at Brightpath Associates LLC
2024-10-30 12:47:20.694 | DEBUG | src.aihawk_job_manager:apply_jobs:310 - Starting applicant for job: Fire Protection Engineer at Insight Global
2024-10-30 12:47:20.694 | ERROR | src.aihawk_job_manager:start_applying:158 - Error during job application: [Errno 2] No such file or directory: 'data_folder\\output\\failed.json'
### Specific tasks
_No response_
### Additional resources
_No response_
### Additional context
_No response_ | closed | 2024-10-30T16:49:25Z | 2024-11-07T00:45:30Z | https://github.com/feder-cr/Jobs_Applier_AI_Agent_AIHawk/issues/682 | [
"help wanted"
] | LouisLeBoeuf | 5 |
Evil0ctal/Douyin_TikTok_Download_API | fastapi | 255 | [BUG] Cannot read property 'JS_MD5_NO_COMMON_JS' of null | ***Platform where the error occurred?***
`Douyin`
***The endpoint where the error occurred?***
`Web APP`
***Submitted input value?***
`https://v.douyin.com/iJoaujh1/`
***Have you tried again?***
Yes, the error still exists after X time after the error occurred.
***Have you checked the readme or interface documentation for this project?***
Yes, and it is very sure that the problem is caused by the program.
All parsing logs are as follows
```
Use http://10.1.1.2:80/ to access the application
当前链接平台为:douyin
正在获取视频ID...
正在通过抖音分享链接获取原始链接...
获取原始链接成功, 原始链接为: https://www.iesdouyin.com/share/video/7268837076525665596/
获取到的抖音视频ID为: 7268837076525665596
获取视频ID成功,视频ID为:7268837076525665596
正在获取视频数据...
正在获取抖音视频数据...
获取抖音视频数据失败！原因:TypeError: Cannot read property 'JS_MD5_NO_COMMON_JS' of null
正在获取抖音视频数据...
获取抖音视频数据失败！原因:TypeError: Cannot read property 'JS_MD5_NO_COMMON_JS' of null
正在获取抖音视频数据...
获取抖音视频数据失败！原因:TypeError: Cannot read property 'JS_MD5_NO_COMMON_JS' of null
正在获取抖音视频数据...
获取抖音视频数据失败！原因:TypeError: Cannot read property 'JS_MD5_NO_COMMON_JS' of null
exception calling callback for <Future at 0x10b8b3d90 state=finished raised RetryError>
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/tenacity/_asyncio.py", line 50, in __call__
result = await fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/Caelebs/Desktop/Douyin_TikTok_Download_API-main/scraper.py", line 268, in get_douyin_video_data
raise e
File "/Users/Caelebs/Desktop/Douyin_TikTok_Download_API-main/scraper.py", line 253, in get_douyin_video_data
api_url = self.generate_x_bogus_url(api_url)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/Caelebs/Desktop/Douyin_TikTok_Download_API-main/scraper.py", line 199, in generate_x_bogus_url
xbogus = execjs.compile(open('./X-Bogus.js').read()).call('sign', query, self.headers['User-Agent'])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/execjs/_abstract_runtime_context.py", line 37, in call
return self._call(name, *args)
^^^^^^^^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/execjs/_external_runtime.py", line 92, in _call
return self._eval("{identifier}.apply(this, {args})".format(identifier=identifier, args=args))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/execjs/_external_runtime.py", line 78, in _eval
return self.exec_(code)
^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/execjs/_abstract_runtime_context.py", line 18, in exec_
return self._exec_(source)
^^^^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/execjs/_external_runtime.py", line 88, in _exec_
return self._extract_result(output)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/execjs/_external_runtime.py", line 167, in _extract_result
raise ProgramError(value)
execjs._exceptions.ProgramError: TypeError: Cannot read property 'JS_MD5_NO_COMMON_JS' of null
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/concurrent/futures/_base.py", line 340, in _invoke_callbacks
callback(self)
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pywebio/session/coroutinebased.py", line 347, in _wakeup
self.step(future.result())
^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/concurrent/futures/_base.py", line 449, in result
return self.__get_result()
^^^^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/concurrent/futures/_base.py", line 401, in __get_result
raise self._exception
File "/Users/Caelebs/Desktop/Douyin_TikTok_Download_API-main/scraper.py", line 432, in hybrid_parsing
data = await self.get_douyin_video_data(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/tenacity/_asyncio.py", line 88, in async_wrapped
return await fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/tenacity/_asyncio.py", line 47, in __call__
do = self.iter(retry_state=retry_state)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/tenacity/__init__.py", line 326, in iter
raise retry_exc from fut.exception()
tenacity.RetryError: RetryError[<Future at 0x10b497d90 state=finished raised ProgramError>]
``` | closed | 2023-08-28T14:21:48Z | 2023-08-28T14:26:41Z | https://github.com/Evil0ctal/Douyin_TikTok_Download_API/issues/255 | [
"BUG",
"enhancement"
] | Caelebs | 1 |
pydata/pandas-datareader | pandas | 828 | Yahoo Finance data for an specific hour | Hi,
I want to download hystorical data of stock value **for an determinated hour**.
Does anyone know how to do?
I am using this code but extracts only to the end of the day. I want to extract data for a midday:
```
failed=[]
passed=[]
def collect_data(data):
mydata = pd.DataFrame()
for t in data:
try:
mydata[t] = wb.DataReader(t,data_source='yahoo',start='01-10-2019')['Adj Close']
passed.append(t)
except (IOError, KeyError):
msg= 'NaN'
failed.append(t)
print(mydata)
return mydata)
```
Tahank you! | open | 2020-09-22T17:25:17Z | 2021-08-08T22:32:34Z | https://github.com/pydata/pandas-datareader/issues/828 | [] | victorsm123 | 2 |
pydantic/logfire | pydantic | 859 | Add support to track disk usage | ### Description
Currently, there is no support for tracking disk usage. It will help to set up alerts where disk size grows beyond a set threshold. | open | 2025-02-12T13:49:37Z | 2025-02-14T09:42:27Z | https://github.com/pydantic/logfire/issues/859 | [
"Feature Request"
] | rishabhc32 | 2 |
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