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keras-team/keras | data-science | 20,622 | Key space/depth operations commonly used in SISR models are missing | Hi! I would like to ask if it would be possible to add support for the `depth to space` and `space to depth` operations commonly found on many SISR models.
While you can achieve the same result with some clever usage of `keras.ops.reshape` and `keras.ops.transpose`, both TF and Pytorch offer them as easy to use functions:
https://www.tensorflow.org/api_docs/python/tf/nn/depth_to_space
https://www.tensorflow.org/api_docs/python/tf/nn/space_to_depth
https://pytorch.org/docs/stable/generated/torch.nn.PixelShuffle.html
https://pytorch.org/docs/stable/generated/torch.nn.PixelUnshuffle.html
I've been able to find the same operations in the PIX library as well:
https://dm-pix.readthedocs.io/en/latest/api.html#depth-and-space-transformations
This exact same depth to space transformation can be found in the following example:
https://keras.io/examples/vision/super_resolution_sub_pixel/
Thanks in advance =) | open | 2024-12-10T15:21:59Z | 2025-01-15T15:55:09Z | https://github.com/keras-team/keras/issues/20622 | [
"type:feature",
"stat:awaiting keras-eng"
] | Artoriuz | 1 |
strawberry-graphql/strawberry | fastapi | 3,788 | OpenTelemetry Extension groups all resolver in one old span | <!-- Provide a general summary of the bug in the title above. -->
<!--- This template is entirely optional and can be removed, but is here to help both you and us. -->
<!--- Anything on lines wrapped in comments like these will not show up in the final text. -->
## Describe the Bug
With the OpenTelemetry extension enabled, we get distributed tracing telemetry with Azure (or other telemetry viewer), but it seems like all the resolvers use the same SPAN parent, created on the first operation ran on the service. All subsequent query will use the same span for the resolver, but not for the Parsing and Validation Lifecycle
These "GraphQL Resolving: events" are all seperate GraphQL queries made to the service; the timestamp of the "GraphQL Query: historicalData" server span is "07:40:00" and the last "GraphQL Resolving: events" is "08:01:28". There's also other spans for "GraphQL Parsing" and "Validation" that appear in the telemetry, but they are missing the resolvers
This trace is the "08:01:28" that should include the last "GraphQL Resolving: events" of the previous screenshot.
## System Information
- Operating system: Linux
- Strawberry version (if applicable): 0.260.2
## Additional Context
https://github.com/strawberry-graphql/strawberry/blob/main/strawberry/extensions/tracing/opentelemetry.py#L172
It seems like that line, the `self_span_holder[LifecycleStep.OPERATION]` is always the same object, the object created during the first operation ever run on the service.
I'm not too keen on the details of Python's coroutine and async stuff, but it feels like the `_span_holder` used by the `async resolve` coroutine might be a memory copy of the initial invocation. Both the `on_parse` and `on_validate` method seems to resolve the correct span and these are not async.
| open | 2025-02-19T13:21:55Z | 2025-03-24T17:54:41Z | https://github.com/strawberry-graphql/strawberry/issues/3788 | [
"bug"
] | pgelinas | 3 |
plotly/dash | data-science | 2,300 | [BUG] Renderer can't find element that exists in DOM - `nonexistent object ` | **Describe your context**
Please provide us your environment, so we can easily reproduce the issue.
- replace the result of `pip list | grep dash` below
```
aiohttp 3.8.1
aiosignal 1.2.0
algoliasearch 1.15.3
amqp 5.1.1
aplus 0.11.0
asn1crypto 1.5.1
astroid 2.11.7
async-timeout 4.0.2
attrs 22.1.0
beautifulsoup4 4.11.1
billiard 3.6.4.0
biopython 1.79
black 22.3.0
blake3 0.2.1
bleach 5.0.1
bokeh 2.4.3
Brotli 1.0.9
cachetools 5.2.0
celery 5.2.7
certifi 2021.5.30
cffi 1.15.1
chardet 4.0.0
charset-normalizer 2.1.1
click 8.1.3
click-didyoumean 0.3.0
click-plugins 1.1.1
click-repl 0.2.0
cloudpickle 2.2.0
colorcet 3.0.0
coloredlogs 15.0.1
colorlover 0.3.0
colour 0.1.5
commonmark 0.9.1
cryptography 38.0.1
cycler 0.11.0
dash 2.6.1
dash-ag-grid 1.3.1
dash-arcgis 0.4.0
dash-auth 1.3.2
dash-bio 1.0.1
dash-bootstrap-components 0.12.2
dash-canvas 0.1.0
dash-cool-components 0.1.7
dash-core-components 2.0.0
dash-cytoscape 0.2.0
dash-dangerously-set-inner-html 0.0.2
dash-daq 0.5.0
dash-design-kit 1.6.8
dash-design-kit-docs 1.6.8
dash-embedded 2.6.0
dash-enterprise-auth 0.1.0
dash-flow-example 0.0.5
dash-html-components 2.0.0
dash-notes 0.0.3
dash-pro-components 0.1.0
dash-slicer 0.3.0
dash-snapshots 2.2.2
dash-table 5.0.0
dash-user-analytics 0.0.2
dash-user-guide-components 0.0.8
dash-vtk 0.0.9
dashboard-engine 1.1.1
dashboard-engine-docs 1.0.2
dask 1.2.0
datashader 0.14.2
datashape 0.5.2
dill 0.3.5.1
diskcache 5.4.0
et-xmlfile 1.1.0
fakeredis 1.0.3
filelock 3.8.0
fire 0.4.0
flake8 3.9.2
flaky 3.7.0
Flask 2.0.1
Flask-Caching 1.10.1
Flask-Compress 1.10.1
Flask-Cors 3.0.10
flask-request-id 0.1
Flask-SeaSurf 1.1.1
Flask-SQLAlchemy 2.5.1
flask-talisman 1.0.0
fonttools 4.37.1
frozendict 2.3.4
frozenlist 1.3.1
future 0.18.2
GEOparse 2.0.3
greenlet 1.1.3
gunicorn 20.1.0
h5py 3.7.0
holoviews 1.14.5
humanfriendly 10.0
humanize 4.3.0
idna 2.10
imageio 2.21.2
importlib-metadata 4.12.0
importlib-resources 5.9.0
iniconfig 1.1.1
isort 5.10.1
itsdangerous 2.1.2
Jinja2 3.1.2
joblib 1.1.0
jsonschema 4.15.0
kiwisolver 1.4.4
kombu 5.2.4
lazy-object-proxy 1.7.1
llvmlite 0.39.1
lxml 4.6.3
Markdown 3.2.1
MarkupSafe 2.1.1
matplotlib 3.5.3
mccabe 0.7.0
mimesis 6.0.0
mock 4.0.3
morph 0.1.5
multidict 6.0.2
multipledispatch 0.6.0
mypy-extensions 0.4.3
nest-asyncio 1.5.5
nested-lookup 0.2.22
networkx 2.8.6
numba 0.56.2
numpy 1.20.0
openpyxl 3.0.10
orjson 3.6.7
packaging 20.9
pandas 1.3.0
pandas-datareader 0.10.0
panel 0.13.1
param 1.12.2
ParmEd 3.4.3
pathspec 0.10.1
percy 2.0.2
periodictable 1.6.1
pg8000 1.29.1
Pillow 9.2.0
pip 20.2.3
pkgutil-resolve-name 1.3.10
platformdirs 2.5.2
plotly 5.3.1
pluggy 1.0.0
preconditions 0.1
progressbar2 4.0.0
prompt-toolkit 3.0.31
py 1.11.0
pyarrow 9.0.0
pycodestyle 2.7.0
pycparser 2.21
pyct 0.4.8
pydantic 1.10.2
pyflakes 2.3.1
Pygments 2.13.0
PyJWT 2.4.0
pylint 2.13.5
pyOpenSSL 22.0.0
pyorbital 1.3.1
pyparsing 3.0.9
pyrsistent 0.18.1
pytest 7.1.3
pytest-mock 3.8.2
pytest-rerunfailures 10.2
pytest-sugar 0.9.4
python-dateutil 2.8.2
python-dotenv 0.21.0
python-utils 3.3.3
pytz 2022.2.1
pyviz-comms 2.2.1
PyWavelets 1.3.0
PyYAML 6.0
redis 3.5.3
requests 2.25.1
retrying 1.3.3
rich 12.5.1
scikit-image 0.18.2
scikit-learn 1.1.2
scipy 1.9.1
scramp 1.4.1
selenium 3.141.0
setuptools 49.2.1
six 1.16.0
sortedcontainers 2.4.0
soupsieve 2.3.2.post1
SQLAlchemy 1.4.41
tabulate 0.8.10
tenacity 8.0.1
termcolor 2.0.1
threadpoolctl 3.1.0
tifffile 2022.8.12
tomli 2.0.1
toolz 0.12.0
tornado 6.2
tqdm 4.64.1
typing-extensions 4.3.0
ua-parser 0.16.1
urllib3 1.26.6
vaex-core 4.12.0
vaex-hdf5 0.11.0
vine 5.0.0
vtk 9.1.0
waitress 2.1.2
wcwidth 0.2.5
webencodings 0.5.1
Werkzeug 2.0.1
wrapt 1.14.1
wsgi-request-id 0.2
wslink 1.8.2
xarray 0.16.2
xlrd 2.0.1
XlsxWriter 1.4.4
yarl 1.8.1
zipp 3.8.1
```
- if frontend related, tell us your Browser, Version and OS
- OS: MacOS 12.6
- Browser: Chrome and Firefox
- Version 106
**Describe the bug**
While working on a feature for the docs, I created a container called `dropdown-container` with a dropdown and this container is visible on only some pages. On pages where it isn't visible, the callback updates the style to `style={'display': 'none'}`.
After going to a number of pages in a row (about 10) that don't display the container, the container can no longer be found. It throws an error:
```A nonexistent object was used in an `Output` of a Dash callback. The id of this object is `dropdown-container` and the property is `style`.```
It does however exist in the DOM.
And exists in the layout: `store.getState().layout`
It doesn't exist in the paths though: `store.getState().paths `
Steps to reproduce:
1. Clone the docs repo and check out the de-versioning-2 branch (https://github.com/plotly/ddk-dash-docs/tree/de-versioning-2)
2. Run the docs with `python index.py`
3. Go to the a path that does display the container: `/dash-enterprise/redis-database`
4. From the menu on the left, start clicking on the different pages in the Dash Tutorial and Dash Callbacks sections.
<img width="328" alt="image" src="https://user-images.githubusercontent.com/12749831/200054372-8bc03d96-7dc4-4925-87c5-7b51ac9cc29a.png">
After clicking on around 10 different pages, the error is displayed:
<img width="567" alt="image" src="https://user-images.githubusercontent.com/12749831/200054695-802986e2-af01-47ae-940d-14544b4fa7d1.png">
**Expected behavior**
That it would be able to find the `dropdown-container`, and not throw an error.
@alexcjohnson | closed | 2022-11-04T19:11:11Z | 2024-07-24T15:10:04Z | https://github.com/plotly/dash/issues/2300 | [] | LiamConnors | 2 |
numpy/numpy | numpy | 28,011 | BUG: build failure for loongarch in Highway cpu-generic code | ### Describe the issue:
Building crashs for loongarch.
### Reproduce the code example:
```python
pip3 install -U numpy
```
### Error message:
```shell
hint: See above for details.
(.pyvenv) larry@loong0:~/Git/larryw3i/funingschool$ pip3 install -U numpy
Looking in indexes: https://mirror.nju.edu.cn/pypi/web/simple
Requirement already satisfied: numpy in /home/larry/.pyvenv/lib/python3.12/site-packages (1.26.4)
Collecting numpy
Using cached https://mirror.nju.edu.cn/pypi/web/packages/47/1b/1d565e0f6e156e1522ab564176b8b29d71e13d8caf003a08768df3d5cec5/numpy-2.2.0.tar.gz (20.2 MB)
Installing build dependencies ... done
Getting requirements to build wheel ... done
Installing backend dependencies ... done
Preparing metadata (pyproject.toml) ... error
error: subprocess-exited-with-error
× Preparing metadata (pyproject.toml) did not run successfully.
│ exit code: 1
╰─> [6649 lines of output]
+ /home/larry/.pyvenv/bin/python3 /tmp/pip-install-e4n3et1f/numpy_4dbb960615344a389d1eafc1d2c289b0/vendored-meson/meson/meson.py setup /tmp/pip-install-e4n3et1f/numpy_4dbb960615344a389d1eafc1d2c289b0 /tmp/pip-install-e4n3et1f/numpy_4dbb960615344a389d1eafc1d2c289b0/.mesonpy-lk99d3x7 -Dbuildtype=release -Db_ndebug=if-release -Db_vscrt=md --native-file=/tmp/pip-install-e4n3et1f/numpy_4dbb960615344a389d1eafc1d2c289b0/.mesonpy-lk99d3x7/meson-python-native-file.ini
The Meson build system
Version: 1.5.2
Source dir: /tmp/pip-install-e4n3et1f/numpy_4dbb960615344a389d1eafc1d2c289b0
Build dir: /tmp/pip-install-e4n3et1f/numpy_4dbb960615344a389d1eafc1d2c289b0/.mesonpy-lk99d3x7
Build type: native build
Project name: NumPy
Project version: 2.2.0
C compiler for the host machine: cc (gcc 14.2.0 "cc (Debian 14.2.0-11) 14.2.0")
C linker for the host machine: cc ld.bfd 2.43.50.20241215
C++ compiler for the host machine: c++ (gcc 14.2.0 "c++ (Debian 14.2.0-11) 14.2.0")
C++ linker for the host machine: c++ ld.bfd 2.43.50.20241215
Cython compiler for the host machine: cython (cython 3.0.11)
Host machine cpu family: loongarch64
Host machine cpu: loongarch64
Program python found: YES (/home/larry/.pyvenv/bin/python3)
Found pkg-config: YES (/usr/bin/pkg-config) 1.8.1
Run-time dependency python found: YES 3.12
Has header "Python.h" with dependency python-3.12: YES
Compiler for C supports arguments -fno-strict-aliasing: YES
Message: Disabling CPU feature detection due to unsupported architecture: "loongarch64"
Configuring npy_cpu_dispatch_config.h using configuration
Message:
CPU Optimization Options
baseline:
Requested : none
Enabled :
dispatch:
Requested : none
Enabled :
Library m found: YES
Run-time dependency scipy-openblas found: NO (tried pkgconfig)
Found CMake: /usr/bin/cmake (3.31.2)
WARNING: CMake Toolchain: Failed to determine CMake compilers state
Run-time dependency openblas found: NO (tried pkgconfig, pkgconfig, pkgconfig, system and cmake)
Run-time dependency flexiblas found: NO (tried pkgconfig and cmake)
Run-time dependency blis found: NO (tried pkgconfig and cmake)
Run-time dependency blas found: YES 3.12.0
../numpy/meson.build:135: WARNING: Project targets '>=1.2.99' but uses feature introduced in '1.3.0': dep 'blas' custom lookup.
Message: BLAS symbol suffix:
Run-time dependency openblas found: NO (tried pkgconfig, pkgconfig, pkgconfig, system and cmake)
Run-time dependency flexiblas found: NO (tried pkgconfig and cmake)
Run-time dependency lapack found: YES 3.12.0
../numpy/meson.build:198: WARNING: Project targets '>=1.2.99' but uses feature introduced in '1.3.0': dep 'lapack' custom lookup.
Checking if "Check atomic builtins without -latomic" : links: NO
Library atomic found: YES
Checking if "Check atomic builtins with -latomic" with dependency -latomic: links: NO
Program _build_utils/process_src_template.py found: YES (/home/larry/.pyvenv/bin/python3 /tmp/pip-install-e4n3et1f/numpy_4dbb960615344a389d1eafc1d2c289b0/numpy/_build_utils/process_src_template.py)
Program _build_utils/tempita.py found: YES (/home/larry/.pyvenv/bin/python3 /tmp/pip-install-e4n3et1f/numpy_4dbb960615344a389d1eafc1d2c289b0/numpy/_build_utils/tempita.py)
Configuring __config__.py using configuration
Checking for size of "short" : 2
Checking for size of "int" : 4
Checking for size of "long" : 8
Checking for size of "long long" : 8
Checking for size of "float" : 4
Checking for size of "double" : 8
Checking for size of "long double" : 16
Checking for size of "size_t" : 8
Checking for size of "size_t" : 8 (cached)
Checking for size of "wchar_t" : 4
Checking for size of "off_t" : 8
Checking for size of "Py_intptr_t" with dependency python-3.12: 8
Checking for size of "PY_LONG_LONG" with dependency python-3.12: 8
Has header "complex.h" : YES
Checking for type "complex float" : YES
Checking for size of "complex float" : 8
Checking for type "complex double" : YES
Checking for size of "complex double" : 16
Checking for type "complex long double" : YES
Checking for size of "complex long double" : 32
Checking for function "sin" with dependency -lm: YES
Checking for function "cos" with dependency -lm: YES
Checking for function "tan" with dependency -lm: YES
Checking for function "sinh" with dependency -lm: YES
Checking for function "cosh" with dependency -lm: YES
Checking for function "tanh" with dependency -lm: YES
Checking for function "fabs" with dependency -lm: YES
Checking for function "floor" with dependency -lm: YES
Checking for function "ceil" with dependency -lm: YES
Checking for function "sqrt" with dependency -lm: YES
Checking for function "log10" with dependency -lm: YES
Checking for function "log" with dependency -lm: YES
Checking for function "exp" with dependency -lm: YES
Checking for function "asin" with dependency -lm: YES
Checking for function "acos" with dependency -lm: YES
Checking for function "atan" with dependency -lm: YES
Checking for function "fmod" with dependency -lm: YES
Checking for function "modf" with dependency -lm: YES
Checking for function "frexp" with dependency -lm: YES
Checking for function "ldexp" with dependency -lm: YES
Checking for function "expm1" with dependency -lm: YES
Checking for function "log1p" with dependency -lm: YES
Checking for function "acosh" with dependency -lm: YES
Checking for function "asinh" with dependency -lm: YES
Checking for function "atanh" with dependency -lm: YES
Checking for function "rint" with dependency -lm: YES
Checking for function "trunc" with dependency -lm: YES
Checking for function "exp2" with dependency -lm: YES
Checking for function "copysign" with dependency -lm: YES
Checking for function "nextafter" with dependency -lm: YES
Checking for function "cbrt" with dependency -lm: YES
Checking for function "log2" with dependency -lm: YES
Checking for function "pow" with dependency -lm: YES
Checking for function "hypot" with dependency -lm: YES
Checking for function "atan2" with dependency -lm: YES
Checking for function "csin" with dependency -lm: YES
Checking for function "csinh" with dependency -lm: YES
Checking for function "ccos" with dependency -lm: YES
Checking for function "ccosh" with dependency -lm: YES
Checking for function "ctan" with dependency -lm: YES
Checking for function "ctanh" with dependency -lm: YES
Checking for function "creal" with dependency -lm: YES
Checking for function "cimag" with dependency -lm: YES
Checking for function "conj" with dependency -lm: YES
Checking for function "strtoll" : YES
Checking for function "strtoull" : YES
Checking for function "cabs" with dependency -lm: YES
Checking for function "cabsf" with dependency -lm: YES
Checking for function "cabsl" with dependency -lm: YES
Checking for function "cacos" with dependency -lm: YES
Checking for function "cacosf" with dependency -lm: YES
Checking for function "cacosl" with dependency -lm: YES
Checking for function "cacosh" with dependency -lm: YES
Checking for function "cacoshf" with dependency -lm: YES
Checking for function "cacoshl" with dependency -lm: YES
Checking for function "carg" with dependency -lm: YES
Checking for function "cargf" with dependency -lm: YES
Checking for function "cargl" with dependency -lm: YES
Checking for function "casin" with dependency -lm: YES
Checking for function "casinf" with dependency -lm: YES
Checking for function "casinl" with dependency -lm: YES
Checking for function "casinh" with dependency -lm: YES
Checking for function "casinhf" with dependency -lm: YES
Checking for function "casinhl" with dependency -lm: YES
Checking for function "catan" with dependency -lm: YES
Checking for function "catanf" with dependency -lm: YES
Checking for function "catanl" with dependency -lm: YES
Checking for function "catanh" with dependency -lm: YES
Checking for function "catanhf" with dependency -lm: YES
Checking for function "catanhl" with dependency -lm: YES
Checking for function "cexp" with dependency -lm: YES
Checking for function "cexpf" with dependency -lm: YES
Checking for function "cexpl" with dependency -lm: YES
Checking for function "clog" with dependency -lm: YES
Checking for function "clogf" with dependency -lm: YES
Checking for function "clogl" with dependency -lm: YES
Checking for function "cpow" with dependency -lm: YES
Checking for function "cpowf" with dependency -lm: YES
Checking for function "cpowl" with dependency -lm: YES
Checking for function "csqrt" with dependency -lm: YES
Checking for function "csqrtf" with dependency -lm: YES
Checking for function "csqrtl" with dependency -lm: YES
Checking for function "csin" with dependency -lm: YES (cached)
Checking for function "csinf" with dependency -lm: YES
Checking for function "csinl" with dependency -lm: YES
Checking for function "csinh" with dependency -lm: YES (cached)
Checking for function "csinhf" with dependency -lm: YES
Checking for function "csinhl" with dependency -lm: YES
Checking for function "ccos" with dependency -lm: YES (cached)
Checking for function "ccosf" with dependency -lm: YES
Checking for function "ccosl" with dependency -lm: YES
Checking for function "ccosh" with dependency -lm: YES (cached)
Checking for function "ccoshf" with dependency -lm: YES
Checking for function "ccoshl" with dependency -lm: YES
Checking for function "ctan" with dependency -lm: YES (cached)
Checking for function "ctanf" with dependency -lm: YES
Checking for function "ctanl" with dependency -lm: YES
Checking for function "ctanh" with dependency -lm: YES (cached)
Checking for function "ctanhf" with dependency -lm: YES
Checking for function "ctanhl" with dependency -lm: YES
Checking for function "isfinite" with dependency -lm: YES
Header "Python.h" has symbol "isfinite" with dependency python-3.12: YES
Checking for function "isinf" with dependency -lm: YES
Header "Python.h" has symbol "isinf" with dependency python-3.12: YES
Checking for function "isnan" with dependency -lm: YES
Header "Python.h" has symbol "isnan" with dependency python-3.12: YES
Checking for function "signbit" with dependency -lm: YES
Header "Python.h" has symbol "signbit" with dependency python-3.12: YES
Checking if "thread_local" compiles: NO
Checking if "_Thread_local" compiles: YES
Checking if "__thread" compiles: YES
Checking if "__declspec(thread)" compiles: NO
Checking for function "fallocate" : YES
Header "Python.h" has symbol "HAVE_FTELLO" with dependency python-3.12: YES
Header "Python.h" has symbol "HAVE_FSEEKO" with dependency python-3.12: YES
Checking for function "backtrace" : YES
Checking for function "madvise" : YES
Has header "features.h" : YES
Has header "xlocale.h" : NO
Has header "dlfcn.h" : YES
Has header "execinfo.h" : YES
Has header "libunwind.h" : NO
Has header "sys/mman.h" : YES
Checking for function "strtold_l" : YES
Compiler for C supports arguments -O3: YES
Has header "endian.h" : YES
Has header "sys/endian.h" : NO
Compiler for C supports function attribute visibility:hidden: YES
Configuring config.h using configuration
Configuring _numpyconfig.h using configuration
Configuring npymath.ini using configuration
Configuring mlib.ini using configuration
Configuring numpy.pc using configuration
Generating multi-targets for "_umath_tests.dispatch.h"
Enabled targets: baseline
Generating multi-targets for "argfunc.dispatch.h"
Enabled targets: baseline
Generating multi-targets for "x86_simd_argsort.dispatch.h"
Enabled targets:
Generating multi-targets for "x86_simd_qsort.dispatch.h"
Enabled targets:
Generating multi-targets for "x86_simd_qsort_16bit.dispatch.h"
Enabled targets:
Generating multi-targets for "highway_qsort.dispatch.h"
Enabled targets:
Generating multi-targets for "highway_qsort_16bit.dispatch.h"
Enabled targets:
Generating multi-targets for "loops_arithm_fp.dispatch.h"
Enabled targets: baseline
Generating multi-targets for "loops_arithmetic.dispatch.h"
Enabled targets: baseline
Generating multi-targets for "loops_comparison.dispatch.h"
Enabled targets: baseline
Generating multi-targets for "loops_exponent_log.dispatch.h"
Enabled targets: baseline
Generating multi-targets for "loops_hyperbolic.dispatch.h"
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Generating multi-targets for "loops_logical.dispatch.h"
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Generating multi-targets for "loops_minmax.dispatch.h"
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Generating multi-targets for "loops_modulo.dispatch.h"
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Generating multi-targets for "loops_trigonometric.dispatch.h"
Enabled targets: baseline
Generating multi-targets for "loops_umath_fp.dispatch.h"
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Generating multi-targets for "loops_unary.dispatch.h"
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Generating multi-targets for "loops_unary_fp.dispatch.h"
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Generating multi-targets for "loops_unary_fp_le.dispatch.h"
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Generating multi-targets for "loops_unary_complex.dispatch.h"
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Generating multi-targets for "loops_autovec.dispatch.h"
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Generating multi-targets for "_simd.dispatch.h"
Enabled targets: baseline
Build targets in project: 60
WARNING: Project specifies a minimum meson_version '>=1.2.99' but uses features which were added in newer versions:
* 1.3.0: {'dep 'blas' custom lookup', 'dep 'lapack' custom lookup'}
NumPy 2.2.0
User defined options
Native files: /tmp/pip-install-e4n3et1f/numpy_4dbb960615344a389d1eafc1d2c289b0/.mesonpy-lk99d3x7/meson-python-native-file.ini
buildtype : release
b_ndebug : if-release
b_vscrt : md
Found ninja-1.12.1 at /usr/bin/ninja
+ /usr/bin/ninja
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[115/310] Compiling Cython source /tmp/pip-install-e4n3et1f/numpy_4dbb960615344a389d1eafc1d2c289b0/numpy/random/_philox.pyx
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[125/310] Compiling C++ object numpy/_core/libloops_trigonometric.dispatch.h_baseline.a.p/src_umath_loops_trigonometric.dispatch.cpp.o
FAILED: numpy/_core/libloops_trigonometric.dispatch.h_baseline.a.p/src_umath_loops_trigonometric.dispatch.cpp.o
c++ -Inumpy/_core/libloops_trigonometric.dispatch.h_baseline.a.p -Inumpy/_core -I../numpy/_core -Inumpy/_core/include -I../numpy/_core/include -I../numpy/_core/src/common -I../numpy/_core/src/multiarray -I../numpy/_core/src/npymath -I../numpy/_core/src/umath -I../numpy/_core/src/highway -I/usr/include/python3.12 -I/usr/include/loongarch64-linux-gnu/python3.12 -I/tmp/pip-install-e4n3et1f/numpy_4dbb960615344a389d1eafc1d2c289b0/.mesonpy-lk99d3x7/meson_cpu -fdiagnostics-color=always -DNDEBUG -Wall -Winvalid-pch -std=c++17 -O3 -fPIC -DNPY_INTERNAL_BUILD -DHAVE_NPY_CONFIG_H -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -fno-exceptions -fno-rtti -O3 -DNPY_MTARGETS_BASELINE -MD -MQ numpy/_core/libloops_trigonometric.dispatch.h_baseline.a.p/src_umath_loops_trigonometric.dispatch.cpp.o -MF numpy/_core/libloops_trigonometric.dispatch.h_baseline.a.p/src_umath_loops_trigonometric.dispatch.cpp.o.d -o numpy/_core/libloops_trigonometric.dispatch.h_baseline.a.p/src_umath_loops_trigonometric.dispatch.cpp.o -c ../numpy/_core/src/umath/loops_trigonometric.dispatch.cpp
In file included from ../numpy/_core/src/highway/hwy/highway.h:623,
from ../numpy/_core/src/umath/loops_trigonometric.dispatch.cpp:6:
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:34:23: error: expected constructor, destructor, or type conversion before ‘;’ token
34 | HWY_BEFORE_NAMESPACE();
| ^
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:66:9: error: ‘VFromD’ does not name a type
66 | HWY_API VFromD<D> CombineShiftRightLanes(D d, VFromD<D> hi, VFromD<D> lo) {
| ^~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h: In function ‘hwy::HWY_NAMESPACE::Vec<D> hwy::HWY_NAMESPACE::SignBit(D)’:
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:77:9: error: ‘RebindToUnsigned’ does not name a type
77 | const RebindToUnsigned<decltype(d)> du;
| ^~~~~~~~~~~~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:78:25: error: ‘du’ was not declared in this scope; did you mean ‘d’?
78 | return BitCast(d, Set(du, SignMask<TFromD<D>>()));
| ^~
| d
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:78:38: error: ‘TFromD’ was not declared in this scope
78 | return BitCast(d, Set(du, SignMask<TFromD<D>>()));
| ^~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:78:29: error: parse error in template argument list
78 | return BitCast(d, Set(du, SignMask<TFromD<D>>()));
| ^~~~~~~~~~~~~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:78:49: error: expected primary-expression before ‘)’ token
78 | return BitCast(d, Set(du, SignMask<TFromD<D>>()));
| ^
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h: In function ‘hwy::HWY_NAMESPACE::Vec<D> hwy::HWY_NAMESPACE::NaN(D)’:
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:84:9: error: ‘RebindToSigned’ does not name a type
84 | const RebindToSigned<D> di;
| ^~~~~~~~~~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:87:25: error: ‘di’ was not declared in this scope; did you mean ‘d’?
87 | return BitCast(d, Set(di, LimitsMax<TFromD<decltype(di)>>()));
| ^~
| d
......
6832 | return InterleaveUpper(d, v, v);
| ^
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h: In function ‘V hwy::HWY_NAMESPACE::detail::Per4LaneBlockShuffle(hwy::SizeTag<kIdx3210>, V)’:
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6837:9: error: ‘DFromV’ does not name a type
6837 | const DFromV<decltype(v)> d;
| ^~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6838:65: error: ‘TFromV’ was not declared in this scope
6838 | return Per4LaneBlockShuffle(idx_3210_tag, hwy::SizeTag<sizeof(TFromV<V>)>(),
| ^~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6838:73: error: expected primary-expression before ‘>’ token
6838 | return Per4LaneBlockShuffle(idx_3210_tag, hwy::SizeTag<sizeof(TFromV<V>)>(),
| ^
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6838:74: error: expected primary-expression before ‘)’ token
6838 | return Per4LaneBlockShuffle(idx_3210_tag, hwy::SizeTag<sizeof(TFromV<V>)>(),
| ^
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6838:75: error: template argument 1 is invalid
6838 | return Per4LaneBlockShuffle(idx_3210_tag, hwy::SizeTag<sizeof(TFromV<V>)>(),
| ^
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6839:44: error: ‘d’ was not declared in this scope
6839 | hwy::SizeTag<d.MaxBytes()>(), v);
| ^
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6839:56: error: template argument 1 is invalid
6839 | hwy::SizeTag<d.MaxBytes()>(), v);
| ^
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h: At global scope:
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6846:11: error: ‘HWY_IF_LANES_D’ has not been declared
6846 | HWY_IF_LANES_D(DFromV<V>, 1)>
| ^~~~~~~~~~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6846:32: error: expected ‘)’ before ‘<’ token
6846 | HWY_IF_LANES_D(DFromV<V>, 1)>
| ~ ^
| )
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6846:32: error: expected ‘>’ before ‘<’ token
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6846:38: error: expected unqualified-id before ‘)’ token
6846 | HWY_IF_LANES_D(DFromV<V>, 1)>
| ^
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6858:11: error: ‘HWY_IF_LANES_D’ has not been declared
6858 | HWY_IF_LANES_D(DFromV<V>, 2)>
| ^~~~~~~~~~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6858:32: error: expected ‘)’ before ‘<’ token
6858 | HWY_IF_LANES_D(DFromV<V>, 2)>
| ~ ^
| )
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6858:32: error: expected ‘>’ before ‘<’ token
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6858:38: error: expected unqualified-id before ‘)’ token
6858 | HWY_IF_LANES_D(DFromV<V>, 2)>
| ^
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6875:11: error: ‘HWY_IF_LANES_GT_D’ has not been declared
6875 | HWY_IF_LANES_GT_D(DFromV<V>, 2)>
| ^~~~~~~~~~~~~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6875:35: error: expected ‘)’ before ‘<’ token
6875 | HWY_IF_LANES_GT_D(DFromV<V>, 2)>
| ~ ^
| )
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6875:35: error: expected ‘>’ before ‘<’ token
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6875:41: error: expected unqualified-id before ‘)’ token
6875 | HWY_IF_LANES_GT_D(DFromV<V>, 2)>
| ^
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h: In function ‘size_t hwy::HWY_NAMESPACE::Blocks(D)’:
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6892:57: error: ‘TFromD’ was not declared in this scope
6892 | return (d.MaxBytes() <= 16) ? 1 : ((Lanes(d) * sizeof(TFromD<D>) + 15) / 16);
| ^~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6892:65: error: expected primary-expression before ‘>’ token
6892 | return (d.MaxBytes() <= 16) ? 1 : ((Lanes(d) * sizeof(TFromD<D>) + 15) / 16);
| ^
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6892:66: error: expected primary-expression before ‘)’ token
6892 | return (d.MaxBytes() <= 16) ? 1 : ((Lanes(d) * sizeof(TFromD<D>) + 15) / 16);
| ^
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h: At global scope:
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6903:35: error: ‘HWY_IF_V_SIZE_LE_V’ has not been declared
6903 | template <int kBlockIdx, class V, HWY_IF_V_SIZE_LE_V(V, 16)>
| ^~~~~~~~~~~~~~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6903:57: error: expected identifier before numeric constant
6903 | template <int kBlockIdx, class V, HWY_IF_V_SIZE_LE_V(V, 16)>
| ^~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6903:57: error: expected ‘,’ or ‘...’ before numeric constant
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6909:35: error: ‘HWY_IF_V_SIZE_LE_V’ has not been declared
6909 | template <int kBlockIdx, class V, HWY_IF_V_SIZE_LE_V(V, 16)>
| ^~~~~~~~~~~~~~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6909:57: error: expected identifier before numeric constant
6909 | template <int kBlockIdx, class V, HWY_IF_V_SIZE_LE_V(V, 16)>
| ^~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6909:57: error: expected ‘,’ or ‘...’ before numeric constant
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6915:35: error: ‘HWY_IF_V_SIZE_LE_V’ has not been declared
6915 | template <int kBlockIdx, class V, HWY_IF_V_SIZE_LE_V(V, 16)>
| ^~~~~~~~~~~~~~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6915:57: error: expected identifier before numeric constant
6915 | template <int kBlockIdx, class V, HWY_IF_V_SIZE_LE_V(V, 16)>
| ^~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6915:57: error: expected ‘,’ or ‘...’ before numeric constant
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6931:31: error: ‘HWY_IF_V_SIZE_LE_V’ has not been declared
6931 | template <int kLane, class V, HWY_IF_V_SIZE_LE_V(V, 16)>
| ^~~~~~~~~~~~~~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6931:53: error: expected identifier before numeric constant
6931 | template <int kLane, class V, HWY_IF_V_SIZE_LE_V(V, 16)>
| ^~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6931:53: error: expected ‘,’ or ‘...’ before numeric constant
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h: In function ‘V hwy::HWY_NAMESPACE::BroadcastLane(V)’:
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6933:10: error: ‘Broadcast’ was not declared in this scope; did you mean ‘BroadcastLane’?
6933 | return Broadcast<kLane>(v);
| ^~~~~~~~~
| BroadcastLane
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h: At global scope:
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6946:20: error: ‘HWY_IF_LANES_D’ has not been declared
6946 | template <class D, HWY_IF_LANES_D(D, 1)>
| ^~~~~~~~~~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6946:38: error: expected identifier before numeric constant
6946 | template <class D, HWY_IF_LANES_D(D, 1)>
| ^
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6946:38: error: expected ‘,’ or ‘...’ before numeric constant
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6947:9: error: ‘VFromD’ does not name a type
6947 | HWY_API VFromD<D> Slide1Up(D d, VFromD<D> /*v*/) {
| ^~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6950:20: error: ‘HWY_IF_LANES_D’ has not been declared
6950 | template <class D, HWY_IF_LANES_D(D, 1)>
| ^~~~~~~~~~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6950:38: error: expected identifier before numeric constant
6950 | template <class D, HWY_IF_LANES_D(D, 1)>
| ^
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6950:38: error: expected ‘,’ or ‘...’ before numeric constant
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6951:9: error: ‘VFromD’ does not name a type
6951 | HWY_API VFromD<D> Slide1Down(D d, VFromD<D> /*v*/) {
| ^~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6956:20: error: ‘HWY_IF_V_SIZE_LE_D’ has not been declared
6956 | template <class D, HWY_IF_V_SIZE_LE_D(D, 16), HWY_IF_LANES_GT_D(D, 1)>
| ^~~~~~~~~~~~~~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6956:42: error: expected identifier before numeric constant
6956 | template <class D, HWY_IF_V_SIZE_LE_D(D, 16), HWY_IF_LANES_GT_D(D, 1)>
| ^~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6956:42: error: expected ‘,’ or ‘...’ before numeric constant
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6956:47: error: ‘HWY_IF_LANES_GT_D’ has not been declared
6956 | template <class D, HWY_IF_V_SIZE_LE_D(D, 16), HWY_IF_LANES_GT_D(D, 1)>
| ^~~~~~~~~~~~~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6956:68: error: expected identifier before numeric constant
6956 | template <class D, HWY_IF_V_SIZE_LE_D(D, 16), HWY_IF_LANES_GT_D(D, 1)>
| ^
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6956:68: error: expected ‘,’ or ‘...’ before numeric constant
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6957:9: error: ‘VFromD’ does not name a type
6957 | HWY_API VFromD<D> Slide1Up(D d, VFromD<D> v) {
| ^~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6960:20: error: ‘HWY_IF_V_SIZE_LE_D’ has not been declared
6960 | template <class D, HWY_IF_V_SIZE_LE_D(D, 16), HWY_IF_LANES_GT_D(D, 1)>
| ^~~~~~~~~~~~~~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6960:42: error: expected identifier before numeric constant
6960 | template <class D, HWY_IF_V_SIZE_LE_D(D, 16), HWY_IF_LANES_GT_D(D, 1)>
| ^~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6960:42: error: expected ‘,’ or ‘...’ before numeric constant
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6960:47: error: ‘HWY_IF_LANES_GT_D’ has not been declared
6960 | template <class D, HWY_IF_V_SIZE_LE_D(D, 16), HWY_IF_LANES_GT_D(D, 1)>
| ^~~~~~~~~~~~~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6960:68: error: expected identifier before numeric constant
6960 | template <class D, HWY_IF_V_SIZE_LE_D(D, 16), HWY_IF_LANES_GT_D(D, 1)>
| ^
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6960:68: error: expected ‘,’ or ‘...’ before numeric constant
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6961:9: error: ‘VFromD’ does not name a type
6961 | HWY_API VFromD<D> Slide1Down(D d, VFromD<D> v) {
| ^~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6970:33: error: ‘HWY_IF_V_SIZE_LE_D’ has not been declared
6970 | template <int kBlocks, class D, HWY_IF_V_SIZE_LE_D(D, 16)>
| ^~~~~~~~~~~~~~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6970:55: error: expected identifier before numeric constant
6970 | template <int kBlocks, class D, HWY_IF_V_SIZE_LE_D(D, 16)>
| ^~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6970:55: error: expected ‘,’ or ‘...’ before numeric constant
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6971:9: error: ‘VFromD’ does not name a type
6971 | HWY_API VFromD<D> SlideUpBlocks(D /*d*/, VFromD<D> v) {
| ^~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6988:33: error: ‘HWY_IF_V_SIZE_LE_D’ has not been declared
6988 | template <int kBlocks, class D, HWY_IF_V_SIZE_LE_D(D, 16)>
| ^~~~~~~~~~~~~~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6988:55: error: expected identifier before numeric constant
6988 | template <int kBlocks, class D, HWY_IF_V_SIZE_LE_D(D, 16)>
| ^~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6988:55: error: expected ‘,’ or ‘...’ before numeric constant
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:6989:9: error: ‘VFromD’ does not name a type
6989 | HWY_API VFromD<D> SlideDownBlocks(D /*d*/, VFromD<D> v) {
| ^~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:7046:49: error: ‘HWY_IF_UI8_D’ has not been declared
7046 | template <int kAOffset, int kBOffset, class V8, HWY_IF_UI8_D(DFromV<V8>)>
| ^~~~~~~~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:7046:68: error: expected ‘)’ before ‘<’ token
7046 | template <int kAOffset, int kBOffset, class V8, HWY_IF_UI8_D(DFromV<V8>)>
| ~ ^
| )
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:7046:68: error: expected ‘>’ before ‘<’ token
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:7046:72: error: expected unqualified-id before ‘)’ token
7046 | template <int kAOffset, int kBOffset, class V8, HWY_IF_UI8_D(DFromV<V8>)>
| ^
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:7150:11: error: ‘HWY_IF_UI8_D’ has not been declared
7150 | HWY_IF_UI8_D(DFromV<V8>)>
| ^~~~~~~~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:7150:30: error: expected ‘)’ before ‘<’ token
7150 | HWY_IF_UI8_D(DFromV<V8>)>
| ~ ^
| )
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:7150:30: error: expected ‘>’ before ‘<’ token
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:7150:34: error: expected unqualified-id before ‘)’ token
7150 | HWY_IF_UI8_D(DFromV<V8>)>
| ^
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h: In function ‘uint64_t hwy::HWY_NAMESPACE::detail::BitsFromMask(M)’:
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:7366:30: error: ‘BitsFromMask’ is not a member of ‘hwy::HWY_NAMESPACE’; did you mean ‘hwy::HWY_NAMESPACE::detail::BitsFromMask’?
7366 | return hwy::HWY_NAMESPACE::BitsFromMask(m);
| ^~~~~~~~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:7365:10: note: ‘hwy::HWY_NAMESPACE::detail::BitsFromMask’ declared here
7365 | uint64_t BitsFromMask(M m) {
| ^~~~~~~~~~~~
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h: At global scope:
../numpy/_core/src/highway/hwy/ops/generic_ops-inl.h:7374:22: error: expected constructor, destructor, or type conversion before ‘;’ token
7374 | HWY_AFTER_NAMESPACE();
| ^
[126/310] Compiling Cython source numpy/random/_bounded_integers.pyx
[127/310] Compiling C object numpy/_core/_umath_tests.cpython-312-loongarch64-linux-gnu.so.p/src_common_npy_cpu_features.c.o
[128/310] Compiling C++ object numpy/_core/_multiarray_tests.cpython-312-loongarch64-linux-gnu.so.p/src_common_npy_hashtable.cpp.o
[129/310] Compiling C object numpy/_core/_umath_tests.cpython-312-loongarch64-linux-gnu.so.p/meson-generated__umath_tests.c.o
[130/310] Compiling C object numpy/_core/_multiarray_tests.cpython-312-loongarch64-linux-gnu.so.p/meson-generated__multiarray_tests.c.o
[131/310] Compiling Cython source /tmp/pip-install-e4n3et1f/numpy_4dbb960615344a389d1eafc1d2c289b0/numpy/random/_common.pyx
[132/310] Compiling Cython source numpy/random/mtrand.pyx
warning: numpy/random/mtrand.pyx:4966:29: the result of using negative indices inside of code sections marked as 'wraparound=False' is undefined
[133/310] Compiling Cython source numpy/random/_generator.pyx
[134/310] Compiling C object numpy/_core/libloops_autovec.dispatch.h_baseline.a.p/meson-generated_loops_autovec.dispatch.c.o
ninja: build stopped: subcommand failed.
[end of output]
note: This error originates from a subprocess, and is likely not a problem with pip.
error: metadata-generation-failed
× Encountered error while generating package metadata.
╰─> See above for output.
note: This is an issue with the package mentioned above, not pip.
hint: See above for details.
```
### Python and NumPy Versions:
In [2]: import sys, numpy; print(numpy.__version__); print(sys.version)
1.26.4
3.12.8 (main, Dec 13 2024, 13:19:48) [GCC 14.2.0]
### Runtime Environment:
_No response_
### Context for the issue:
_No response_ | open | 2024-12-16T06:29:29Z | 2025-01-03T10:00:20Z | https://github.com/numpy/numpy/issues/28011 | [
"00 - Bug",
"component: SIMD"
] | larryw3i | 2 |
robotframework/robotframework | automation | 5,226 | Add `MATCH/CASE` syntax similarly as in Python | Hello everyone,
I would like to suggest to add match statement in robot framework.
Match statement is support in python [Match Statement](https://docs.python.org/3/tutorial/controlflow.html#match-statements)
This suggestion is to add another method besides IF / ELSE block. | open | 2024-10-02T18:30:12Z | 2024-11-16T07:35:17Z | https://github.com/robotframework/robotframework/issues/5226 | [
"enhancement",
"priority: high",
"effort: extra large"
] | rarajabs | 24 |
keras-team/keras | tensorflow | 20,804 | Results of the Conv2D layer are not identical across backends | The [docs](https://keras.io/keras_3/) state:
> numerics are identical across backends [...]
> [...] up to 1e-7 precision in float32, per function execution
However, this minimal example does not confirm this:
```python3
import os.path
import numpy as np
from keras import layers, Model
from keras.src.saving import load_model
np.random.seed(0)
data = np.random.rand(1, 256, 256, 1024)
if os.path.isfile("model.keras"):
model = load_model("model.keras")
else:
inputs = layers.Input(shape=(256, 256, 1024))
outputs = layers.Conv2D(1024, kernel_size=(4, 7), padding="same", dilation_rate=(3, 2))(inputs)
model = Model(inputs=[inputs], outputs=outputs)
model.save("model.keras")
print(np.sum([data]))
print(os.environ["KERAS_BACKEND"])
print(np.sum(np.array(model([data]))))
```
Output with `tensorflow` backend:
```bash
KERAS_BACKEND=tensorflow python main.py
```
```
33550919.07926151
tensorflow
58094.56
```
Output with `jax` backend:
```bash
KERAS_BACKEND=jax python main.py
```
```
33550919.07926151
jax
58094.523
```
Versions used:
```bash
python -c "import keras; import tensorflow; import jax; print(keras.__version__); print(tensorflow.__version__); print(jax.__version__)"
```
```
3.8.0
2.18.0
0.5.0
``` | closed | 2025-01-23T17:35:53Z | 2025-02-06T20:34:55Z | https://github.com/keras-team/keras/issues/20804 | [
"type:Bug"
] | Dobiasd | 6 |
mckinsey/vizro | data-visualization | 290 | Replace all `html.P()` with `html.Label()` in all form components | ### Question
Context why this is beneficial: https://teamtreehouse.com/community/labels-vs-paragraphs#:~:text=The%20tag%20is%20just,in%20the%20CSS.
### Code/Examples
Replace `html.P(self.title)` with `html.Label(self.title)` for all form components (dropdown, checklist, etc.) and where applicable
### Other information
_No response_
### Which package?
vizro
### Package version
0.1.9
### Python version
3.9
### OS
_No response_
### Code of Conduct
- [X] I agree to follow the [Code of Conduct](https://github.com/mckinsey/vizro/blob/main/CODE_OF_CONDUCT.md). | closed | 2024-01-26T10:57:27Z | 2024-01-29T12:52:24Z | https://github.com/mckinsey/vizro/issues/290 | [
"Nice to have :cherries:"
] | huong-li-nguyen | 3 |
CorentinJ/Real-Time-Voice-Cloning | pytorch | 931 | Speeding up Loading Time of encoder in ``encoder/inference.py`` | Original comment from @CorentinJ:
TODO: I think the slow loading of the encoder might have something to do with the device it was saved on. Worth investigating.
This refers to the ``load_model`` function in the named module. | open | 2021-12-01T19:45:04Z | 2021-12-01T19:45:04Z | https://github.com/CorentinJ/Real-Time-Voice-Cloning/issues/931 | [] | ghost | 0 |
graphql-python/graphene | graphql | 728 | How to create a subscription with graphene relay so i can be used in front end | Hello I need someone to explain to me on how to create a subscription type with graphene relay. Thank you :) | closed | 2018-05-19T20:56:09Z | 2019-12-16T15:44:04Z | https://github.com/graphql-python/graphene/issues/728 | [] | bellomusodiq | 8 |
apragacz/django-rest-registration | rest-api | 159 | Add ‘REGISTER_RETRIEVE_TOKEN’ | ### Checklist
* [x] I read [Contribution Guidelines](https://github.com/apragacz/django-rest-registration/blob/master/CONTRIBUTING.md#issues)
* [x] I searched [the documentation](https://django-rest-registration.readthedocs.io/) to ensure that the requested feature is not already implemented and described
* [x] I searched existing issues before opening this one
There should be an option so successful user registration returns an auth token, similar to how login works.
| closed | 2021-07-23T17:27:42Z | 2021-08-17T22:29:49Z | https://github.com/apragacz/django-rest-registration/issues/159 | [
"type:feature-request",
"state:needs-answer"
] | trentmercer | 3 |
replicate/cog | tensorflow | 1,591 | Error while finding module specification for 'cog.server.http' (ModuleNotFoundError: No module named 'cog') | ****Error:** Error while finding module specification for 'cog.server.http' (ModuleNotFoundError: No module named 'cog')**
Not able to use run command inside build section in cog.yaml
Below is my cog yaml.
```
build:
gpu: false
python_packages:
- "pandas==1.4.3"
- "scikit-learn==1.3.0"
- "numpy==1.23.2"
- "nltk==3.7"
- "gensim==4.2.0"
- "sentence-transformers==2.5.1"
- "joblib==1.2.0"
- "Flask==3.0.2"
- "torch==1.12.1"
python_version: "3.10.6"
run:
- command: "python -m pip install nltk && python -m nltk.downloader all"
predict: "predict.py:Predictor"
```
instead of
```
run:
- command: "python -m pip install nltk && python -m nltk.downloader all"
```
tried
```
build:
run:
- "python -m nltk.downloader stopwords && \
python -m nltk.downloader punkt && \
python -m nltk.downloader wordnet && \
python -m nltk.downloader omw-1.4"
```
If I try to run only cog build -t tagname
**Error:
Validating model schema...
/usr/local/bin/python: Error while finding module specification for 'cog.command.openapi_schema' (ModuleNotFoundError: No module named 'cog')**
Is RUN command not supported? If so how I can install below commands in cog.yaml
python -m nltk.downloader stopwords
python -m nltk.downloader punkt
python -m nltk.downloader wordnet
python -m nltk.downloader omw-1.4 | open | 2024-03-22T07:47:08Z | 2024-09-06T00:06:10Z | https://github.com/replicate/cog/issues/1591 | [] | Aparna29T | 4 |
deeppavlov/DeepPavlov | tensorflow | 887 | Requirements installation | Hello!
Now installation of additional requirements can be done either through `python -m deeppavlov install <config-name>` or `pip install -r DeepPavlov/deeppavlov/requirements/fasttext.txt`. This variant is not appropriate when you installed library with `pip` and trying to use it from `python`.
So, it would be nice to make the following:
`python -m deeppavlov.requirements` shows available requirements,
`python -m deeppavlov.requiremets tf-gpu spacy gensim` installs additional listed requirements from corresponding files in `DeepPavlov/deeppavlov/requirements/` folder.
Thank you in advance. | open | 2019-06-19T12:10:19Z | 2022-04-05T07:44:45Z | https://github.com/deeppavlov/DeepPavlov/issues/887 | [
"enhancement"
] | dilyararimovna | 1 |
mirumee/ariadne-codegen | graphql | 115 | Test failure on Windows. | `test_read_graphql_file_with_invalid_file_raises_invalid_graphql_syntax_exception()` checks for the file path in the expected exception message, but this gets escaped on Windows.
I don't think that this check is necessary and suggest removing it.
```python
assert str(incorrect_schema_file) in str(exc)
``` | open | 2023-03-30T15:03:07Z | 2023-03-30T15:04:39Z | https://github.com/mirumee/ariadne-codegen/issues/115 | [] | strue36 | 1 |
learning-at-home/hivemind | asyncio | 312 | [BUG] Tests freeze without increasing `ulimit -n` | **Describe the bug**
Tests freeze when the value of `ulimit -n` is 1024, a default for some operating systems (including Ubuntu).
**To Reproduce**
```bash
ulimit -n 1024 && pytest tests/
```
**Environment**
* Python 3.8.5
* hivemind 21fda756c12712a3bfeaca843fac53f846974881 (master)
**Possible solutions**
1. Make tests lighter
2. Increase `ulimit -n` automatically | closed | 2021-07-10T07:56:17Z | 2021-07-13T22:37:18Z | https://github.com/learning-at-home/hivemind/issues/312 | [
"bug"
] | borzunov | 0 |
pydantic/logfire | pydantic | 938 | Format the console log | ### Description
I want to format the console log like loguru
i can't find any function that allow me to change the format
also when i integrate logfire with loguru
I can't format the console log
i want the console log to be the same as default loguru
```python
LOGURU_FORMAT = (
"<green>{time:YYYY-MM-DD HH:mm:ss.SSS Z}</green> | "
"<level>{level: <8}</level> | "
"<cyan>{name}</cyan>:<cyan>{function}</cyan>:<cyan>{line}</cyan> - <level>{message}</level>"
)
```
```python
import logfire
from loguru import logger
from pathlib import Path
logfire.configure()
logger.configure(handlers=[logfire.loguru_handler()])
LOG_DIR = Path("logs")
logger.add(
LOG_DIR / "transcriber.log",
level="INFO",
rotation="1 week",
backtrace=True,
diagnose=True,
)
``` | open | 2025-03-19T17:30:38Z | 2025-03-22T20:41:46Z | https://github.com/pydantic/logfire/issues/938 | [
"Feature Request"
] | NourEldin-Osama | 5 |
nikitastupin/clairvoyance | graphql | 29 | TypeError: __init__() got an unexpected keyword argument 'allowed_methods' | ```
Traceback (most recent call last):
File "/usr/local/Cellar/python@3.9/3.9.7_1/Frameworks/Python.framework/Versions/3.9/lib/python3.9/runpy.py", line 197, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/usr/local/Cellar/python@3.9/3.9.7_1/Frameworks/Python.framework/Versions/3.9/lib/python3.9/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/Users/xxx/Code/Python/clairvoyance/clairvoyance/__main__.py", line 96, in <module>
schema = oracle.clairvoyance(
File "/Users/xxx/Code/Python/clairvoyance/clairvoyance/oracle.py", line 435, in clairvoyance
root_typenames = fetch_root_typenames(config)
File "/Users/xxx/Code/Python/clairvoyance/clairvoyance/oracle.py", line 412, in fetch_root_typenames
response = graphql.post(
File "/Users/xxx/Code/Python/clairvoyance/clairvoyance/graphql.py", line 18, in post
retries = urllib3.util.Retry(
TypeError: __init__() got an unexpected keyword argument 'allowed_methods'
```
Is this expected? | closed | 2021-11-04T16:18:56Z | 2023-03-18T12:29:36Z | https://github.com/nikitastupin/clairvoyance/issues/29 | [] | thistehneisen | 1 |
wkentaro/labelme | computer-vision | 587 | Fast Way For Converting To New Json Format | I have a lot of labelme annotations that use the old labelme format (3.18.0).
Since the recent update, some keys have disappeared while some new keys have been added to the dictionary.
I am aware that you can convert to the new format (4.2.5) by opening each image one-by-one and doing a 'Save As', but this is too time consuming.
Is there a script where I can just specify the image directory and the json directory and have it automatically convert all of the annotations over to the new format without opening the GUI? | closed | 2020-02-07T02:53:07Z | 2020-03-15T00:00:39Z | https://github.com/wkentaro/labelme/issues/587 | [] | cm107 | 3 |
amidaware/tacticalrmm | django | 1,494 | Ability to automate the installation of software through web interface | **Is your feature request related to a problem? Please describe.**
A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
Inability to auto-install software on newly added agents so that admins can make sure all machines have necessary software and if a user of said machine attempts to remove it. It would re-install it. To expand further on this maybe make a policy/template that admins can assign to agents such as workforce agents need to install office automatically, but development agents need to install a different set of tools automatically.
**Describe the solution you'd like**
A clear and concise description of what you want to happen.
The ability for Tactical RMM to check if a piece of software is installed and if not attempt to install it through chocolatey automatically.
**Describe alternatives you've considered**
A clear and concise description of any alternative solutions or features you've considered.
The ability to have a condition for a script to run that would install said application. Such as:
if not google chrome installed:
choco install googlechrome
**Additional context**
Add any other context or screenshots about the feature request here.
I am not sure if this is already available and I am missing it. I did go through documentation, but all I found were scripts on how to check if x application is installed where I was hoping something more through the web interface. If this is not possible I understand, and thank you for all your hard work. | closed | 2023-04-25T15:39:50Z | 2023-04-26T01:33:44Z | https://github.com/amidaware/tacticalrmm/issues/1494 | [] | dcwalker3 | 2 |
keras-team/keras | machine-learning | 20,873 | Inconsistencies with the behavior of bias initializers, leading to poor performance in some cases | Hello,
I've noticed some (potentially harmful) inconsistencies in bias initializers when running a simple test of the keras package, i.e. using a shallow MLP to learn a sine wave function in the [-1, 1] interval.
# Context
Most of the times (or for deep enough networks), using the default zero-initialization for biases is fine. However, for this simple problem having randomized biases is essential, since without them the neurons end up being too similar (redundant) and training converges to a very poor local optimum.
The [official guide](https://keras.io/api/layers/initializers/#variancescaling-class) suggests to use weight initializers for biases as well.
Now:
* The default initialization from _native_ PyTorch leads to good results that improve as expected as the network size grows.
* Several keras initializers are expected to be similar or identical to the PyTorch behavior (i.e. `VarianceScaling` and all its subclasses), but they fail to produce good results, regardless of the number of neurons in the hidden layer.
# Issues
The issues are due to the fact that all [RandomInitializer](https://github.com/keras-team/keras/blob/fbf0af76130beecae2273a513242255826b42c04/keras/src/initializers/random_initializers.py#L10) subclasses in their `__call__` function only have access to the shape they need to fill.
In case of bias vectors for `Dense` layers, this shape is a one element tuple, i.e. `(n,)` where `n` is the number of units in the current layer.
The [compute_fans function](https://github.com/keras-team/keras/blob/fbf0af76130beecae2273a513242255826b42c04/keras/src/initializers/random_initializers.py#L612) in this case reports a fan in of `n`, which is actually the number of units, i.e. the fan out.
Unfortunately, the correct fan in is not accessible, since the number of layer inputs is not included in the shape of the bias vector.
This makes the [official description of the VarianceScaling initializer](https://keras.io/api/layers/initializers/#variancescaling-class) incorrect when applied to neuron biases. The same holds for the description of the Glorot, He, LeCun initializers, which are implemented as `VarianceScaling` subclasses.
In my simple example, as soon as the shallow network has more than very few neurons, all size-dependent initializers have so little variability that they behave very similar to a zero initialization (i.e. incredibly poorly). What stumped me (before understanding the problem) is that the larger is the network, the worse the behavior.
# About possible fixes
I can now easily fix the issue by computing bounds for `RandomUniform` initializers externally so as to replicate the default PyTorch behavior, but this is not an elegant solution -- and I am worried other users may have encountered similar problems without noticing.
If the goal is correctly computing the fan in, I am afraid that I see no easy fix, short of restructuring the `RandomInitializer` API and giving it access to more information.
However, the real goal here is not actually computing the fan in, but preserving the properties that the size-dependent initializers were attempting to enforce. I would need to read more literature on the topic before suggesting a theoretically sound fix from this perspective. I would be willing to do that, in case the keras teams is fine with going in this direction. | open | 2025-02-07T13:44:16Z | 2025-03-07T15:35:08Z | https://github.com/keras-team/keras/issues/20873 | [
"type:bug/performance"
] | lompabo | 4 |
flasgger/flasgger | rest-api | 486 | GET /apispec_example/random in the example returns 500 | After building the example, I started running the docker container of it. However, calling GET /apispec_example/random would result in the following error:
```
172.17.0.1 - - [07/Jun/2021 01:19:51] "GET /apispec_example/random HTTP/1.1" 500 -
[2021-06-07 01:19:52,130] ERROR in app: Exception on /random [GET]
Traceback (most recent call last):
File "/usr/local/lib/python3.6/site-packages/flask/app.py", line 2070, in wsgi_app
response = self.full_dispatch_request()
File "/usr/local/lib/python3.6/site-packages/flask/app.py", line 1515, in full_dispatch_request
rv = self.handle_user_exception(e)
File "/usr/local/lib/python3.6/site-packages/flask/app.py", line 1513, in full_dispatch_request
rv = self.dispatch_request()
File "/usr/local/lib/python3.6/site-packages/flask/app.py", line 1499, in dispatch_request
return self.ensure_sync(self.view_functions[rule.endpoint])(**req.view_args)
File "/flasgger/examples/apispec_example.py", line 50, in random_pet
return jsonify(PetSchema().dump(pet).data)
AttributeError: 'dict' object has no attribute 'data'
``` | open | 2021-06-07T01:26:58Z | 2021-06-07T01:26:58Z | https://github.com/flasgger/flasgger/issues/486 | [] | johnlinp | 0 |
django-import-export/django-import-export | django | 1,648 | Field / Widget interface issues | **Describe the bug**
Both the `row` and `instance` object gets passed into `Widget`. Ideally the widget should not know about either the row or the instance, and should be concerned only with rendering or cleaning the value.
There is an issue with ForeignKeyWidget which doesn't fit this pattern. In general, `Field` and `Widget` should be looked at because there is a crossover between their roles. Would Django forms or DRF be a better fit?
Perhaps a future major release could address this.
| closed | 2023-10-02T19:13:49Z | 2024-01-11T19:40:02Z | https://github.com/django-import-export/django-import-export/issues/1648 | [
"enhancement"
] | matthewhegarty | 2 |
sherlock-project/sherlock | python | 2,399 | sherlock installation error | ### Installation method
Other (indicate below)
### Package version
current version
### Description
i clone sherlock then run requirements command after that i'm facing error like this
──(root㉿Kali)-[/opt/sherlock]
└─# python3 -m pip install -r requirements.txt
error: externally-managed-environment
× This environment is externally managed
╰─> To install Python packages system-wide, try apt install
python3-xyz, where xyz is the package you are trying to
install.
If you wish to install a non-Kali-packaged Python package,
create a virtual environment using python3 -m venv path/to/venv.
Then use path/to/venv/bin/python and path/to/venv/bin/pip. Make
sure you have pypy3-venv installed.
If you wish to install a non-Kali-packaged Python application,
it may be easiest to use pipx install xyz, which will manage a
virtual environment for you. Make sure you have pipx installed.
For more information, refer to the following:
* https://www.kali.org/docs/general-use/python3-external-packages/
* /usr/share/doc/python3.12/README.venv
note: If you believe this is a mistake, please contact your Python installation or OS distribution provider. You can override this, at the risk of breaking your Python installation or OS, by passing --break-system-packages.
hint: See PEP 668 for the detailed specification.
### Steps to reproduce
.
### Additional information
_No response_
### Code of Conduct
- [x] I agree to follow this project's Code of Conduct | closed | 2025-01-27T14:29:26Z | 2025-01-29T03:51:58Z | https://github.com/sherlock-project/sherlock/issues/2399 | [] | aamirejaz1 | 1 |
autogluon/autogluon | scikit-learn | 4,241 | Error occur while using kaggle notebook | 
The folder "aiohttp-3.9.5.dist-info" is already in this path :\opt\.conda\envs\myenv\Lib\site-packages\aiohttp-3.9.5.dist-info
I tried re-install anaconda, miniconda and install anaconda in macbook, but it doesn't work. Could anyone help me to fix this issue? | closed | 2024-06-01T05:15:17Z | 2024-06-27T09:23:22Z | https://github.com/autogluon/autogluon/issues/4241 | [
"bug",
"env: kaggle"
] | EXEDENN | 3 |
ray-project/ray | python | 51,260 | [core][gpu-objects] CollectiveGroupManager | ### Description
It is used to initialize the NCCL group, and the driver process should know the mapping from actor ID to rank. In addition, the `CollectiveGroupManager` is also responsible for ordering the collective calls across actors.
### Use case
_No response_ | open | 2025-03-11T18:32:56Z | 2025-03-11T22:05:44Z | https://github.com/ray-project/ray/issues/51260 | [
"enhancement",
"P0",
"core",
"gpu-objects"
] | kevin85421 | 0 |
jeffknupp/sandman2 | sqlalchemy | 208 | How to use this with ForeignKey table | How to use this with ForeignKey table ,Just like join or inner Sql | open | 2021-03-24T14:44:45Z | 2021-03-24T14:44:45Z | https://github.com/jeffknupp/sandman2/issues/208 | [] | hzjux001 | 0 |
recommenders-team/recommenders | deep-learning | 2,193 | [BUG] Authentication error breaking AzureML tests | ### Description
<!--- Describe your issue/bug/request in detail -->
```
Pytest logs
DefaultAzureCredential failed to retrieve a token from the included credentials.
Attempted credentials:
EnvironmentCredential: EnvironmentCredential authentication unavailable. Environment variables are not fully configured.
Visit https://aka.ms/azsdk/python/identity/environmentcredential/troubleshoot to troubleshoot this issue.
ManagedIdentityCredential: ManagedIdentityCredential authentication unavailable, no response from the IMDS endpoint. invalid_request
SharedTokenCacheCredential: SharedTokenCacheCredential authentication unavailable. No accounts were found in the cache.
AzureCliCredential: Please run 'az login' to set up an account
AzurePowerShellCredential: Az.Account module >= 2.2.0 is not installed
AzureDeveloperCliCredential: Azure Developer CLI could not be found. Please visit https://aka.ms/azure-dev for installation instructions and then,once installed, authenticate to your Azure account using 'azd auth login'.
To mitigate this issue, please refer to the troubleshooting guidelines here at https://aka.ms/azsdk/python/identity/defaultazurecredential/troubleshoot.
Traceback (most recent call last):
File "/home/runner/work/recommenders/recommenders/tests/ci/azureml_tests/post_pytest.py", line 60, in <module>
client = get_client(
File "/home/runner/work/recommenders/recommenders/tests/ci/azureml_tests/aml_utils.py", line 32, in get_client
workspace = client.workspaces.get(workspace_name)
File "/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/azure/ai/ml/_telemetry/activity.py", line 292, in wrapper
return f(*args, **kwargs)
File "/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/azure/core/tracing/decorator.py", line 105, in wrapper_use_tracer
return func(*args, **kwargs)
File "/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/azure/ai/ml/operations/_workspace_operations.py", line 141, in get
return super().get(workspace_name=name, **kwargs)
File "/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/azure/ai/ml/operations/_workspace_operations_base.py", line [88](https://github.com/recommenders-team/recommenders/actions/runs/12190267762/job/34007064737#step:3:94), in get
obj = self._operation.get(resource_group, workspace_name)
File "/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/azure/core/tracing/decorator.py", line 105, in wrapper_use_tracer
return func(*args, **kwargs)
File "/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/azure/ai/ml/_restclient/v2024_07_01_preview/operations/_workspaces_operations.py", line 947, in get
pipeline_response = self._client._pipeline.run( # pylint: disable=protected-access
File "/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/azure/core/pipeline/_base.py", line 240, in run
return first_node.send(pipeline_request)
File "/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/azure/core/pipeline/_base.py", line 96, in send
response = self.next.send(request)
File "/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/azure/core/pipeline/_base.py", line 96, in send
response = self.next.send(request)
File "/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/azure/core/pipeline/_base.py", line 96, in send
response = self.next.send(request)
[Previous line repeated 2 more times]
File "/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/azure/mgmt/core/policies/_base.py", line 95, in send
response = self.next.send(request)
File "/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/azure/core/pipeline/policies/_redirect.py", line 204, in send
response = self.next.send(request)
File "/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/azure/core/pipeline/policies/_retry.py", line 551, in send
response = self.next.send(request)
File "/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/azure/core/pipeline/policies/_authentication.py", line 157, in send
self.on_request(request)
File "/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/azure/core/pipeline/policies/_authentication.py", line 132, in on_request
self._request_token(*self._scopes)
File "/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/azure/core/pipeline/policies/_authentication.py", line 108, in _request_token
self._token = self._get_token(*scopes, **kwargs)
File "/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/azure/core/pipeline/policies/_authentication.py", line 98, in _get_token
return cast(SupportsTokenInfo, self._credential).get_token_info(*scopes, options=options)
File "/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/azure/identity/_credentials/default.py", line 255, in get_token_info
token_info = cast(SupportsTokenInfo, super()).get_token_info(*scopes, options=options)
File "/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/azure/identity/_credentials/chained.py", line 219, in get_token_info
raise ClientAuthenticationError(message=message)
azure.core.exceptions.ClientAuthenticationError: DefaultAzureCredential failed to retrieve a token from the included credentials.
Attempted credentials:
EnvironmentCredential: EnvironmentCredential authentication unavailable. Environment variables are not fully configured.
Visit https://aka.ms/azsdk/python/identity/environmentcredential/troubleshoot to troubleshoot this issue.
ManagedIdentityCredential: ManagedIdentityCredential authentication unavailable, no response from the IMDS endpoint. invalid_request
SharedTokenCacheCredential: SharedTokenCacheCredential authentication unavailable. No accounts were found in the cache.
AzureCliCredential: Please run 'az login' to set up an account
AzurePowerShellCredential: Az.Account module >= 2.2.0 is not installed
AzureDeveloperCliCredential: Azure Developer CLI could not be found. Please visit https://aka.ms/azure-dev for installation instructions and then,once installed, authenticate to your Azure account using 'azd auth login'.
To mitigate this issue, please refer to the troubleshooting guidelines here at https://aka.ms/azsdk/python/identity/defaultazurecredential/troubleshoot.
Error: Process completed with exit code 1.
```
### In which platform does it happen?
<!--- Describe the platform where the issue is happening (use a list if needed) -->
<!--- For example: -->
<!--- * Azure Data Science Virtual Machine. -->
<!--- * Azure Databricks. -->
<!--- * Other platforms. -->
### How do we replicate the issue?
<!--- Please be specific as possible (use a list if needed). -->
<!--- For example: -->
<!--- * Create a conda environment for pyspark -->
<!--- * Run unit test `test_sar_pyspark.py` with `pytest -m 'spark'` -->
<!--- * ... -->
See https://github.com/recommenders-team/recommenders/actions/runs/12190267762/job/34007064737
### Expected behavior (i.e. solution)
<!--- For example: -->
<!--- * The tests for SAR PySpark should pass successfully. -->
### Willingness to contribute
<!--- Go over all the following points, and put an `x` in the box that apply. -->
- [ ] Yes, I can contribute for this issue independently.
- [ ] Yes, I can contribute for this issue with guidance from Recommenders community.
- [ ] No, I cannot contribute at this time.
### Other Comments
| closed | 2024-12-06T07:48:03Z | 2024-12-09T19:36:53Z | https://github.com/recommenders-team/recommenders/issues/2193 | [
"bug"
] | miguelgfierro | 1 |
nteract/papermill | jupyter | 621 | KeyError: (None, None) | ## 🐛 Bug
OS: Windows 10
Python: 3.8.5
Papermill: 2.3.3
`!jupyter --version`
```
jupyter core : 4.6.3
jupyter-notebook : 6.1.4
qtconsole : not installed
ipython : 7.18.1
ipykernel : 5.3.4
jupyter client : 6.1.7
jupyter lab : 3.0.14
nbconvert : 6.0.7
ipywidgets : 7.5.1
nbformat : 5.0.8
traitlets : 5.0.5
```
Input notebook (`papermill_input.ipynb`):
In another notebook in the same directory:
```
import papermill as pm
pm.inspect_notebook('papermill_input.ipynb')
```
throws the following error (`pm.execute_notebook` throws a similar error):
```
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
<ipython-input-28-96887fc45c45> in <module>
----> 1 pm.inspect_notebook(notebook_path=path.with_suffix('.ipynb'))
~\AppData\Local\Continuum\anaconda3\envs\my_env\lib\site-packages\papermill\inspection.py in inspect_notebook(notebook_path, parameters)
118 notebook_path = str(notebook_path)
119
--> 120 nb = _open_notebook(notebook_path, parameters)
121
122 params = _infer_parameters(nb)
~\AppData\Local\Continuum\anaconda3\envs\my_env\lib\site-packages\papermill\inspection.py in _open_notebook(notebook_path, parameters)
17
18 with local_file_io_cwd():
---> 19 return load_notebook_node(input_path)
20
21
~\AppData\Local\Continuum\anaconda3\envs\my_env\lib\site-packages\papermill\iorw.py in load_notebook_node(notebook_path)
409 """
410 nb = nbformat.reads(papermill_io.read(notebook_path), as_version=4)
--> 411 nb_upgraded = nbformat.v4.upgrade(nb)
412 if nb_upgraded is not None:
413 nb = nb_upgraded
~\AppData\Local\Continuum\anaconda3\envs\my_env\lib\site-packages\nbformat\v4\convert.py in upgrade(nb, from_version, from_minor)
37 if from_version == 3:
38 # Validate the notebook before conversion
---> 39 _warn_if_invalid(nb, from_version)
40
41 # Mark the original nbformat so consumers know it has been converted
~\AppData\Local\Continuum\anaconda3\envs\my_env\lib\site-packages\nbformat\v4\convert.py in _warn_if_invalid(nb, version)
19 from nbformat import validate, ValidationError
20 try:
---> 21 validate(nb, version=version)
22 except ValidationError as e:
23 get_logger().error("Notebook JSON is not valid v%i: %s", version, e)
~\AppData\Local\Continuum\anaconda3\envs\my_env\lib\site-packages\nbformat\validator.py in validate(nbdict, ref, version, version_minor, relax_add_props, nbjson)
258 version, version_minor = 1, 0
259
--> 260 for error in iter_validate(nbdict, ref=ref, version=version,
261 version_minor=version_minor,
262 relax_add_props=relax_add_props):
~\AppData\Local\Continuum\anaconda3\envs\my_env\lib\site-packages\nbformat\validator.py in iter_validate(nbdict, ref, version, version_minor, relax_add_props, nbjson)
282 version, version_minor = get_version(nbdict)
283
--> 284 validator = get_validator(version, version_minor, relax_add_props=relax_add_props)
285
286 if validator is None:
~\AppData\Local\Continuum\anaconda3\envs\my_env\lib\site-packages\nbformat\validator.py in get_validator(version, version_minor, relax_add_props)
54 if version_tuple not in validators:
55 try:
---> 56 schema_json = _get_schema_json(v, version=version, version_minor=version_minor)
57 except AttributeError:
58 return None
~\AppData\Local\Continuum\anaconda3\envs\my_env\lib\site-packages\nbformat\validator.py in _get_schema_json(v, version, version_minor)
88 elif version_minor > v.nbformat_minor:
89 # load the latest schema
---> 90 schema_path = os.path.join(os.path.dirname(v.__file__), v.nbformat_schema[(None, None)])
91 else:
92 raise AttributeError('Cannot find appropriate nbformat schema file.')
KeyError: (None, None)
```
Any ideas? | closed | 2021-07-20T05:07:34Z | 2021-08-19T20:21:43Z | https://github.com/nteract/papermill/issues/621 | [
"bug",
"help wanted"
] | roger-yu-ds | 4 |
apify/crawlee-python | automation | 963 | Add support for launching Playwright with a persistent browser context | ### Description
It looks like our current Python implementation always uses an incognito context when launching Playwright ([launch](https://playwright.dev/python/docs/api/class-browsertype#browser-type-launch), which is the default behavior. However, in JavaScript, the default is a persistent context unless explicitly set otherwise ([launch_persistent_context](https://playwright.dev/python/docs/api/class-browsertype#browser-type-launch-persistent-context)).
This will probably be a breaking change (it's changing the default behaviour).
### Relevant code
- https://github.com/apify/crawlee-python/blob/v0.5.4/src/crawlee/browsers/_playwright_browser_controller.py#L142:L155
- https://github.com/apify/crawlee-python/blob/v0.5.4/src/crawlee/browsers/_playwright_browser_plugin.py#L156:L163 | closed | 2025-02-06T15:03:30Z | 2025-02-25T09:11:57Z | https://github.com/apify/crawlee-python/issues/963 | [
"enhancement",
"t-tooling"
] | vdusek | 2 |
CanopyTax/asyncpgsa | sqlalchemy | 98 | Typings? | Hi,
I was wondering if there were/are typings for the library? I'm trying to reduce the number of mypy exceptions I carve out, and this is one of the ones that mypy yells at me for.
Thanks for the great library! | closed | 2019-03-15T17:50:20Z | 2019-03-20T17:17:44Z | https://github.com/CanopyTax/asyncpgsa/issues/98 | [] | arusahni | 2 |
PaddlePaddle/models | computer-vision | 4,776 | arcface loss | 请问度量学习中的arcmargin loss是arcface loss么？？ | closed | 2020-07-29T14:14:35Z | 2020-07-30T02:36:21Z | https://github.com/PaddlePaddle/models/issues/4776 | [
"user"
] | endy-see | 2 |
errbotio/errbot | automation | 1,573 | type BinaryIO declaration missing | I got this error when i start errbot 6.1.9
`10:49:26 INFO errbot.bootstrap Found Storage plugin: Shelf.
10:49:26 INFO errbot.bootstrap Found Backend plugin: Telegram
10:49:26 DEBUG errbot.storage Opening storage 'repomgr'
10:49:26 DEBUG errbot.storage.shelf Open shelf storage /bot/errbot-ve/data/repomgr.db
10:49:26 ERROR errbot.bootstrap Unable to load or configure the backend.
Traceback (most recent call last):
File "/bot//python3.8/site-packages/errbot/bootstrap.py", line 181, in setup_bot
bot = backendpm.load_plugin()
File "/bot//python3.8/site-packages/errbot/backend_plugin_manager.py", line 62, in load_plugin
plugin_classes = self.plugin_info.load_plugin_classes(
File "/bot//python3.8/site-packages/errbot/plugin_info.py", line 100, in load_plugin_classes
spec.loader.exec_module(modu1e)
File "<frozen importlib._bootstrap_external>", line 848, in exec_module
File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
File "/bot//python3.8/site-packages/errbot/backends/telegram_messenger.py", line 189, in <module>
class TelegramBackend(ErrBot):
File "/bot//python3.8/site-packages/errbot/backends/telegram_messenger.py", line 418, in TelegramBackend
fsource: Union[str, dict, BinaryIO],
NameError: name 'BinaryIO' is not define`
In the file errbot/backends/telegram_messenger.py it seem a declaration is missing
I have replace the line
from typing import Any, Optional, Union
by
from typing import Any, Optional, Union, BinaryIO, List, Optional
And now it's worked
| closed | 2022-06-13T09:20:51Z | 2022-07-20T13:40:20Z | https://github.com/errbotio/errbot/issues/1573 | [
"type: bug"
] | futex | 2 |
lukas-blecher/LaTeX-OCR | pytorch | 30 | Feature extraction | Hi,
Can we use your trained model, to extract math features from an image. I mean can we take the layer before the prediction layer for feature extractions?
| closed | 2021-08-13T18:12:49Z | 2021-08-14T09:40:01Z | https://github.com/lukas-blecher/LaTeX-OCR/issues/30 | [] | GopinathCool | 1 |
wiseodd/generative-models | tensorflow | 12 | WGAN Wasserstein algorithm | In the code , did you use Wasserstein to count the distance between discriminator and generator ?
I can't see the algorithm of it, could you shed a light ? Thanks | closed | 2017-03-21T13:45:04Z | 2017-05-08T05:18:13Z | https://github.com/wiseodd/generative-models/issues/12 | [] | tcglarry | 5 |
microsoft/hummingbird | scikit-learn | 134 | add SKL Feature Selectors | add SKL **Feature Selectors**
- SelectKBest
- VarianceThreshold
- SelectPercentile | closed | 2020-06-13T00:23:47Z | 2020-08-29T21:58:00Z | https://github.com/microsoft/hummingbird/issues/134 | [] | ksaur | 2 |
ultralytics/yolov5 | pytorch | 13,086 | Modifying YOLOv5 model for a common backbone but "2 different heads" | ### Search before asking
- [X] I have searched the YOLOv5 [issues](https://github.com/ultralytics/yolov5/issues) and [discussions](https://github.com/ultralytics/yolov5/discussions) and found no similar questions.
### Question
Hi, I was curious to know that if I wish to modify the YOLOv5 model, for a new model that has a common backbone but 2 different heads, then which all files require changes/modifications?
In my knowledge, I guess the yaml file will have 2 heads defined now and then we might have to change common.py and yolo.py
But please I would really appreciate if you give a detailed clarity about what all needs to be modified in these files. Thanks in anticipation.
### Additional
_No response_ | closed | 2024-06-13T09:29:33Z | 2024-10-20T19:47:46Z | https://github.com/ultralytics/yolov5/issues/13086 | [
"question",
"Stale"
] | jain-abhay | 13 |
abhiTronix/vidgear | dash | 255 | Dropped support for Python 3.6.x legacy | Hello folks,
VidGear as of now supports all python 3.6+ legacies. **☠️ However python 3.6 goes out of support, e.g. security updates plus general widespread availability, at the end of this year: https://endoflife.date/python ☠️**
Therefore, we have decided that `3.6.x` legacy will not be supported from upcoming version `v0.2.5`. This means that vidgear `v0.2.5` or higher might fail to work on `3.6.x` legacy, and any related bugs will not be fixed.
**⚠️Therefore, everyone using vidgear should consider upgrading to Python 3.7+ legacies as soon as possible.⚠️**
Thank you.
**EDIT:** Also, the support for python [3.10](https://docs.python.org/3.10/whatsnew/3.10.html) will be officially added in this version.
| closed | 2021-10-20T06:18:30Z | 2022-02-11T14:16:41Z | https://github.com/abhiTronix/vidgear/issues/255 | [
"ENHANCEMENT :zap:",
"SOLVED :checkered_flag:",
"ANNOUNCEMENT :loudspeaker:",
"META :thought_balloon:"
] | abhiTronix | 1 |
strawberry-graphql/strawberry | fastapi | 3,125 | Operation directive not working on QUERY | Operation directive is not called for location QUERY.
## Describe the Bug
I have written an operation directive which should be available for use on QUERY, similar to this reduced example:
```
@strawberry.directive(locations=[DirectiveLocation.QUERY])
async def my_directive(value: Any):
"""
Adds contextual information to node like content language.
"""
print('called')
return value
schema = strawberry.Schema(
directives=[my_directive],
query=RootQuery,
)
```
When running a query like
```
query @myDirective {
someData {
id
}
}
```
the directive method isn't called at all. If running the directive on a field like `someData` or `id` however, the function gets called, event though FIELD is not in the list of locations. I tried defining a root value but this didn't make any difference.
## System Information
- Operating system: macOS 14.0
- Strawberry version (if applicable): 0.209.2 | open | 2023-09-30T20:08:54Z | 2025-03-20T15:56:24Z | https://github.com/strawberry-graphql/strawberry/issues/3125 | [
"bug"
] | mritzerfeld | 7 |
AutoGPTQ/AutoGPTQ | nlp | 148 | 请教一下，部署falcon-40b-autogpt需要什么配置的硬件,我用的80g的a100，感觉还是好慢啊，是我的使用方式不对么 | ```
(base) root@autodl-container-78a811a500-698bb59c:~/autodl-tmp/text-generation-webui# python3 server.py --autogptq --trust-remote-code
WARNING:--autogptq has been deprecated and will be removed soon. AutoGPTQ is now used by default for GPTQ models.
WARNING:trust_remote_code is enabled. This is dangerous.
bin /root/miniconda3/lib/python3.10/site-packages/bitsandbytes/libbitsandbytes_cuda118.so
INFO:Loading falcon-40b-instruct-GPTQ...
INFO:The AutoGPTQ params are: {'model_basename': 'gptq_model-4bit--1g', 'device': 'cuda:0', 'use_triton': False, 'use_safetensors': True, 'trust_remote_code': True, 'max_memory': None, 'quantize_config': None}
WARNING:The safetensors archive passed at models/falcon-40b-instruct-GPTQ/gptq_model-4bit--1g.safetensors does not contain metadata. Make sure to save your model with the `save_pretrained` method. Defaulting to 'pt' metadata.
WARNING:can't get model's sequence length from model config, will set to 4096.
WARNING:RWGPTQForCausalLM hasn't fused attention module yet, will skip inject fused attention.
WARNING:RWGPTQForCausalLM hasn't fused mlp module yet, will skip inject fused mlp.
INFO:Loaded the model in 12.03 seconds.
Running on local URL: http://127.0.0.1:7860
To create a public link, set `share=True` in `launch()`.
Output generated in 69.83 seconds (0.80 tokens/s, 56 tokens, context 19, seed 1735575912)
Output generated in 76.68 seconds (0.51 tokens/s, 39 tokens, context 30, seed 214429420)
Output generated in 82.28 seconds (0.47 tokens/s, 39 tokens, context 66, seed 1502719057)
``` | open | 2023-06-08T06:41:49Z | 2023-06-08T06:41:49Z | https://github.com/AutoGPTQ/AutoGPTQ/issues/148 | [] | benyuereal | 0 |
ranaroussi/yfinance | pandas | 1,239 | Can't get history for index fund | Example:
```
In [1]: import yfinance as yf
In [2]: yf.download(tickers='FXAIX', prepost=True, period='1d', interval='1m')
[*********************100%***********************] 1 of 1 completed
1 Failed download:
- FXAIX: No data found for this date range, symbol may be delisted
Out[2]:
Empty DataFrame
Columns: [Open, High, Low, Close, Adj Close, Volume]
Index: []
In [3]: yf.__version__
Out[3]: '0.1.87'
```
Though yahoo finance has this listed: https://finance.yahoo.com/quote/FXAIX/
| closed | 2022-12-13T18:53:37Z | 2022-12-13T19:33:42Z | https://github.com/ranaroussi/yfinance/issues/1239 | [] | csm10495 | 7 |
Farama-Foundation/PettingZoo | api | 387 | What is the expected behaviour of agents in ParallelEnv | I'm trying to use PettingZoo interface to create my own custom environment. I did look through the dev docs [here](https://www.pettingzoo.ml/dev_docs). While it is clear on how to implement a simple game like RPS where agents terminate at the same time, I am not sure about the intended behaviour of ParallelEnv.
Particularly, when an agent is terminated (done flag is true), is that agent expected to be removed from the observation dict entirely? Is it ok to have some agents skip some timesteps (waiting but not terminated) and then come back and interact again? Or is it possible to resurrect terminated agents?
I try to see the [test code](https://github.com/PettingZoo-Team/PettingZoo/blob/master/pettingzoo/test/parallel_test.py) but I guess it makes some assumptions about the termination/observation behavior which I'm not certain what they are. For example, it tests that `env.agents` has the same number of agents as the observation dict. What's the implication of that? Can `env.agents` add/remove agents during an episode? Can you please clarify the assumptions about ParallelEnv or, even better, compared it against the behavior of AECEnv?
Btw, thank you for such a cool lib for MARL :)
Edit: `env_done` is checked in the test but not mentioned in the doc as well. Also, isn't `live_agents` in the test supposed to be updated before checking `assert par_env.agents == live_agents`? | closed | 2021-05-27T10:24:57Z | 2021-05-30T10:07:06Z | https://github.com/Farama-Foundation/PettingZoo/issues/387 | [] | 51616 | 1 |
aminalaee/sqladmin | asyncio | 887 | Ability to display data from several tables. | ### Checklist
- [x] There are no similar issues or pull requests for this yet.
### Is your feature related to a problem? Please describe.
I want to display data from two tables on one page, now I can't do it because of hardcode for one table on one page.
### Describe the solution you would like.
_No response_
### Describe alternatives you considered
_No response_
### Additional context
_No response_ | open | 2025-03-10T00:58:10Z | 2025-03-10T00:58:10Z | https://github.com/aminalaee/sqladmin/issues/887 | [] | sheldygg | 0 |
pytest-dev/pytest-cov | pytest | 577 | Missing line in coverage, even when hit | # Summary
In `for` loop, when there is a condition ending with `False` (directly or evaluated from function) and then there is just `continue` in the indented block, this line is not recognized as hit. In the example below, if you uncomment the print function, coverage hit 100%. Tests pas with 100% also when `continue` directly behind `:` (not separate line).
# Reproducer
Run `pytest --cov --cov-report term-missing --cov-fail-under 100` with code snippet bellow.
## CLI output
```bash
pytest --cov --cov-report term-missing --cov-fail-under 100
=========================================================================================================================== test session starts ============================================================================================================================
platform linux -- Python 3.8.16, pytest-7.2.0, pluggy-1.0.0
rootdir: /home/tomasman/work/coverage_test
plugins: anyio-3.6.2, Faker-15.3.4, requests-mock-1.9.3, lazy-fixture-0.6.3, asyncio-0.16.0, cov-4.0.0
collected 1 item
test_foo.py . [100%]
---------- coverage: platform linux, python 3.8.16-final-0 -----------
Name Stmts Miss Cover Missing
-------------------------------------------
foo.py 5 1 80% 5
test_foo.py 8 0 100%
-------------------------------------------
TOTAL 13 1 92%
FAIL Required test coverage of 100% not reached. Total coverage: 92.31%
```
## Code
```python
# code in file foo.py
def foo(A, B):
for i in A:
if i in B or False:
# print("hit")
continue
return True
```
```python
# code in file test_foo.py
from foo import foo
def test_foo():
# hit 'continue' 4 times
A = [1, 2, 3, 4]
B = [1, 2, 3, 4]
assert foo(A, B)
# never hit continue
A = [1, 2, 3, 4]
B = [5]
assert foo(A, B)
```
| closed | 2023-01-06T16:50:11Z | 2023-01-06T18:31:52Z | https://github.com/pytest-dev/pytest-cov/issues/577 | [] | mantomas | 1 |
graphdeco-inria/gaussian-splatting | computer-vision | 783 | Does the images have to be updated in specific order? How big can the scene be? Can it be a whole stadium? | Hi, first of all congrats on this amazing project.
My question comes into trying to make something so great as possible. My idea is to use hundreds and hundreds of photos of one big area and trying to make it work with Gaussian Splatting.
To achieve this what should I take into consideration to get the best of it?
Does the photos need to have a specific order? Can it be done with an unordered folder of photos of the place?
What should I take into consideration by trying to make it on a big space (a stadium). BTW I can walk on all areas from the stadium).
My intention is after that to be able to navigate to most parts of it the place.
Appreciate your work, and also a lot your time.
Best. | open | 2024-04-30T12:09:15Z | 2024-04-30T12:09:15Z | https://github.com/graphdeco-inria/gaussian-splatting/issues/783 | [] | venturaEffect | 0 |
dynaconf/dynaconf | fastapi | 1,253 | [RFC] inspect command must include validators for a key | Currently, the inspect command output is
```console
# dynaconf inspect -k DATA --format=yaml
header:
env_filter: None
key_filter: DATA
new_first: 'True'
history_limit: None
include_internal: 'False'
current:
- 0
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
history:
- loader: standard_settings_loader
identifier: /etc/ansible-automation-platform/awx/settings.yaml
env: default
merged: true
value: '@merge 7,8,9'
- loader: load_file@/awx_devel/awx/settings/__init__.py:47
identifier: /etc/tower/conf.d/foo
env: DEVELOPMENT
merged: true
value: '@merge 4,5,6'
- loader: set_method
identifier: lambda_-5654759955135124529@instance
env: global
merged: true
value: '@merge 1, 2, 3'
- loader: settings_loader
identifier: /awx_devel/awx/settings/defaults
env: global
merged: false
value:
- 0
```
I think it would be useful to include validators for the key.
E.g:
```py
validators = [
Validator("DATA", len_min=3),
Validator("DATA__0", ne=10),
]
```
Then when inspect is called with `-k DATA` it can loop the `settings.validators` collection and take every validator that matches `DATA` or `DATA__.*`
```console
# dynaconf inspect -k DATA --format=yaml
header:
env_filter: None
key_filter: DATA
new_first: 'True'
history_limit: None
include_internal: 'False'
current:
- 0
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
history:
- loader: standard_settings_loader
identifier: /etc/ansible-automation-platform/awx/settings.yaml
env: default
merged: true
value: '@merge 7,8,9'
- loader: load_file@/awx_devel/awx/settings/__init__.py:47
identifier: /etc/tower/conf.d/foo
env: DEVELOPMENT
merged: true
value: '@merge 4,5,6'
- loader: set_method
identifier: lambda_-5654759955135124529@instance
env: global
merged: true
value: '@merge 1, 2, 3'
- loader: settings_loader
identifier: /awx_devel/awx/settings/defaults
env: global
merged: false
value:
- 0
validators:
DATA:
- "Validator("DATA", len_min=3)"
- "Validator("DATA__0", ne=10)"
```
It must include the `repr` of the validator.
| closed | 2025-02-14T12:43:55Z | 2025-03-07T17:29:54Z | https://github.com/dynaconf/dynaconf/issues/1253 | [
"Not a Bug",
"RFC"
] | rochacbruno | 0 |
piskvorky/gensim | data-science | 2,786 | Recent versions of smart-open (1.11.0 and 1.11.1) break gensim in Python 2.7 | ### Problem description
What are you trying to achieve? What is the expected result? What are you seeing instead?
Using gensim with Python2.7
#### Steps/code/corpus to reproduce
```
pip install gensim
...
python
>>> import gensim
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/brukau/tmp/gensim/local/lib/python2.7/site-packages/gensim/__init__.py", line 5, in <module>
from gensim import parsing, corpora, matutils, interfaces, models, similarities, summarization, utils # noqa:F401
File "/home/brukau/tmp/gensim/local/lib/python2.7/site-packages/gensim/parsing/__init__.py", line 4, in <module>
from .preprocessing import (remove_stopwords, strip_punctuation, strip_punctuation2, # noqa:F401
File "/home/brukau/tmp/gensim/local/lib/python2.7/site-packages/gensim/parsing/preprocessing.py", line 42, in <module>
from gensim import utils
File "/home/brukau/tmp/gensim/local/lib/python2.7/site-packages/gensim/utils.py", line 45, in <module>
from smart_open import open
File "/home/brukau/tmp/gensim/local/lib/python2.7/site-packages/smart_open/__init__.py", line 28, in <module>
from .smart_open_lib import open, parse_uri, smart_open, register_compressor
File "/home/brukau/tmp/gensim/local/lib/python2.7/site-packages/smart_open/smart_open_lib.py", line 23, in <module>
import pathlib
ImportError: No module named pathlib
>>>
```
#### Versions
Please provide the output of:
```python
import platform; print(platform.platform())
import sys; print("Python", sys.version)
import numpy; print("NumPy", numpy.__version__)
import scipy; print("SciPy", scipy.__version__)
import gensim; print("gensim", gensim.__version__)
from gensim.models import word2vec;print("FAST_VERSION", word2vec.FAST_VERSION)
```
Linux-5.3.0-45-generic-x86_64-with-Ubuntu-19.10-eoan
('Python', '2.7.17 (default, Nov 7 2019, 10:07:09) \n[GCC 9.2.1 20191008]')
('NumPy', '1.16.1')
('SciPy', '1.2.3')
gensim import fails
| closed | 2020-04-09T09:42:49Z | 2020-05-01T02:17:16Z | https://github.com/piskvorky/gensim/issues/2786 | [
"bug",
"impact HIGH",
"reach HIGH"
] | brukau | 19 |
mljar/mercury | data-visualization | 118 | Enhancement: Delete apps from within the user interface | Thank you for the great package!
Apps can currently be deleted from the command line `mercury delete app.ipynb`.
It would be nice to simply delete apps from the website via clicking on a delete button next to the individual app. | closed | 2022-07-01T11:37:37Z | 2022-07-01T12:00:56Z | https://github.com/mljar/mercury/issues/118 | [
"enhancement",
"help wanted"
] | jonaslandsgesell | 2 |
albumentations-team/albumentations | deep-learning | 2,029 | ToTensorV2 return always a CHW image | In contrast to the docstring, where it is specified that if an image in HW format is passed ToTensorV2 will return a HW image
https://github.com/albumentations-team/albumentations/blob/759d8de18732881a9e12c56f313fe84e35558841/albumentations/pytorch/transforms.py#L16
the method apply() returns always a CHW images:
https://github.com/albumentations-team/albumentations/blob/759d8de18732881a9e12c56f313fe84e35558841/albumentations/pytorch/transforms.py#L41 | closed | 2024-10-25T16:22:31Z | 2024-10-25T16:41:33Z | https://github.com/albumentations-team/albumentations/issues/2029 | [
"bug"
] | rmarconzini | 1 |
pydantic/logfire | fastapi | 849 | How can I use logfire with Sentry to let logfire.error can trigger Sentry issue by Default? | ### Question
Hi team,
I love logfire so much and trying to replace all my current loggings with logfire. But some problem I met is that before with the configuration, if we do `logger.error` in code, it will automatcally trigger a Sentry issue. But now if logifire we lose it.
I checked the docs of logfire but didn't find out how to achieve the same goal with logfire. Can you help me with this?
Here's my sentry configuration.
Thank you!
```
sentry_logging = LoggingIntegration(
level=logging.WARNING, # Minimum logging level to capture
event_level=logging.WARNING, # Set to logging.WARNING to capture warning and above
)
if settings.SENTRY_DSN:
sentry_sdk.init(
dsn=str(settings.SENTRY_DSN),
integrations=[sentry_logging],
enable_tracing=True,
traces_sample_rate=1.0,
_experiments={
# Set continuous_profiling_auto_start to True
# to automatically start the profiler on when
# possible.
"continuous_profiling_auto_start": True,
},
)
``` | open | 2025-02-08T07:41:07Z | 2025-02-08T07:41:07Z | https://github.com/pydantic/logfire/issues/849 | [
"Question"
] | dealexchen | 0 |
plotly/dash-table | plotly | 552 | [FEATURE] Allow className for column | If a `className` could be specified to a column, and it would be applied to all `td` and/or `th` elements for that column, then this would allow using CSS to control the layout of such columns (width, right vs. left justification of values, etc.). | open | 2019-08-20T08:38:00Z | 2019-09-18T21:30:38Z | https://github.com/plotly/dash-table/issues/552 | [] | orenbenkiki | 3 |
marshmallow-code/apispec | rest-api | 239 | Feedback on error message | Hello. I had a strange bug that caused me a lot of frustration. This may be solved by the new plugin work you've been doing but here is my setup:
1. apispec - v0.38.0 (I'm doing something weird and haven't fixed it to update yet)
2. Using tornado
I was intermittently failing when calling `add_path`. The error I was getting was:
```python
APISpecError('Path template is not specified')
```
The core problem was, I had a method definition as the following:
```python
@coroutine
def post(self, *args, **kwargs):
pass
```
The `*args` and `**kwargs` should never have been there but got populated by my editor automatically. At any rate, this came down to line 95 in `ext/tornado.py`. The type error that was generated was swallowed during the `add_path` call masking the problem a bit.
Even more curious is the fact that the failure was not consistent. It might be something wonky with my environment, but at some point, the following line was returning different output:
```python
args = list(inspect.signature(method).parameters.keys())[1:]
```
Sometimes the output of this function would be `['args', 'kwargs']` and other times it would be `[]`. I did some initial testing to try to replicate the problem in a stripped down environment, but could never reproduce.
This turned out to be a little longer than I expected. Honestly, I'm not sure what I would expect you to do about it, except maybe point me more in the right direction with a more helpful error message?
Thanks so much for the library! It makes my life much easier, and I appreciate all the hard work. Let me know if I can help fix this problem. | closed | 2018-07-08T15:08:05Z | 2018-07-16T09:23:32Z | https://github.com/marshmallow-code/apispec/issues/239 | [] | loganasherjones | 1 |
piskvorky/gensim | data-science | 3,207 | has anyone tried changing this codes to inverted dirchlet instead of just dirchlet? | would like to ask if has anyone tried changing this codes to inverted dirchlet instead of just dirchlet?
[dirichlet_expectation.txt](https://github.com/RaRe-Technologies/gensim/files/6910689/dirichlet_expectation.txt)
[update_dir_prior.txt](https://github.com/RaRe-Technologies/gensim/files/6910690/update_dir_prior.txt)
| closed | 2021-07-31T04:45:23Z | 2021-07-31T07:29:46Z | https://github.com/piskvorky/gensim/issues/3207 | [] | iamnothingCC | 1 |
the0demiurge/ShadowSocksShare | flask | 5 | 请问我可以pc单机运行吗？ | 系统win10，已经装了python3.6
最好是能在我的路由器上部署，路由器是最新的lede，python好像有路由器的版本，希望能得到方法来部署，谢谢 | closed | 2017-10-09T08:04:44Z | 2019-08-21T03:49:39Z | https://github.com/the0demiurge/ShadowSocksShare/issues/5 | [] | zasl | 9 |
deepfakes/faceswap | deep-learning | 1,039 | "Failed to get convolution algorithm" while Trainning | Just installed Faceswap on my computer using the script provided and, when tried the Training function, got this error:
[crash_report.2020.07.28.003102128162.log](https://github.com/deepfakes/faceswap/files/4985835/crash_report.2020.07.28.003102128162.log)
I don't have CUDA nor CUDNN installed.
Can you guys help?
Thanks in advance. | closed | 2020-07-28T03:39:57Z | 2020-08-02T17:56:17Z | https://github.com/deepfakes/faceswap/issues/1039 | [] | pjosalgado | 3 |
fastapi/fastapi | pydantic | 12,313 | Required with Ellipsis may not work | ### Privileged issue
- [ ] I'm @tiangolo or he asked me directly to create an issue here.
### Issue Content
https://fastapi.tiangolo.com/tutorial/query-params-str-validations/#required-parameters
python interpreter:3.12.4
fastapi version:0.115.0
my codes:
```
from __future__ import annotations
from typing import Annotated
import uvicorn
from fastapi import FastAPI, Query
app = FastAPI()
@app.get("/items/")
async def read_items(q: Annotated[str, Query(min_length = 3)] = ...):
"""
curl -X 'GET' 'http://127.0.0.1:18081/items/' -H 'accept: application/json'
ValueError: [TypeError("'ellipsis' object is not iterable"), TypeError('vars() argument must have __dict__ attribute')]
"""
results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
if q:
results.update({"q": q})
return results
if __name__ == '__main__':
uvicorn.run(app, host = '127.0.0.1', port = 18081)
```
swagger docs:
ValueError: [TypeError("'ellipsis' object is not iterable"), TypeError('vars() argument must have __dict__ attribute')]
| closed | 2024-09-29T07:24:07Z | 2025-02-15T16:25:44Z | https://github.com/fastapi/fastapi/issues/12313 | [
"docs",
"confirmed"
] | bowenerchen | 15 |
tqdm/tqdm | jupyter | 1,511 | GUI shows up after completion of first iteration of loop | - [x] I have marked all applicable categories:
+ [x] visual output bug
- [x] I have visited the [source website], and in particular
read the [known issues]
- [x] I have searched through the [issue tracker] for duplicates
- [x] I have mentioned version numbers, operating system and
environment, where applicable: tdqm version : 4.66.1 , python version: 3.8.15 64 bit on Windows 10
I am using tqdm.gui / tqdm.tk to show a GUI progress bar in my application, but there is this small issue where the GUI only shows up after the first iteration of loop/range is completed.
Example Code:
```
from time import sleep
from tqdm.gui import tqdm
for i in tqdm(range(1,5)):
print(i)
sleep(5)
```
In the above example, the GUI progress bar shows up 5 seconds after printing 1 in the console, ideally it should show up with 0% progress before 1 is printed to the console.
| open | 2023-09-13T06:37:27Z | 2023-09-13T06:37:43Z | https://github.com/tqdm/tqdm/issues/1511 | [] | koolkunz | 0 |
horovod/horovod | machine-learning | 3,861 | Build error with latest Tensorflow head commit | **Environment:**
1. Framework: TensorFlow
3. Framework version: head commit
4. Horovod version: head commit
5. MPI version:
6. CUDA version:
7. NCCL version:
8. Python version: 3.9
9. Spark / PySpark version:
10. Ray version:
11. OS and version: Ubuntu 20.04
12. GCC version: 9.4.0
13. CMake version: 3.16.3
**Checklist:**
1. Did you search issues to find if somebody asked this question before?
Yes
3. If your question is about hang, did you read [this doc](https://github.com/horovod/horovod/blob/master/docs/running.rst)?
4. If your question is about docker, did you read [this doc](https://github.com/horovod/horovod/blob/master/docs/docker.rst)?
5. Did you check if you question is answered in the [troubleshooting guide](https://github.com/horovod/horovod/blob/master/docs/troubleshooting.rst)?
**Bug report:**
Please describe erroneous behavior you're observing and steps to reproduce it.
Horovod build fails with latest Tensorflow head commit. [This TF commit](https://github.com/intel-innersource/frameworks.ai.tensorflow.private-tensorflow/commit/980747f3fba63b847c39c774f3201c3e69248552) seems causing below error:
` /tmp/pip-req-build-w5l58v3a/horovod/tensorflow/mpi_ops.cc:1104:55: error: cannot convert ‘const bool’ to ‘tensorflow::Var**’
1104 | sparse, &var);
| ^~~~~~
| |
| const bool` | closed | 2023-03-13T19:13:20Z | 2023-04-04T16:16:48Z | https://github.com/horovod/horovod/issues/3861 | [
"bug"
] | mahmoud-abuzaina | 0 |
amfoss/cms | graphql | 40 | Create College App & StudentProfile Model, Migrate fields from Profile field | Migrate college-level details like roll no, admission year, branch etc. to a new model `StudentProfile` under a new `College` App.
**StudentProfileModel**
- User: One To One to User Model
- Roll Number: String
- Branch: ENUM / String
- Division: Char
- Admission Year: YEAR
*Please dont remove existing fields and add new fields in the same PR, as we wouldn't be able to merge it. As in that case, it will be difficult for us to migrate existing data in production. We will phase out the old fields as unused moving the associated functionalities to the new fields, and later on remove them though another PR.* | closed | 2019-09-22T06:34:20Z | 2019-11-13T12:43:48Z | https://github.com/amfoss/cms/issues/40 | [
"help wanted",
"maintenance"
] | aswinshenoy | 2 |
CorentinJ/Real-Time-Voice-Cloning | pytorch | 786 | Sumvip. Clup | Nuốt qua | closed | 2021-07-02T11:55:51Z | 2021-08-25T10:26:07Z | https://github.com/CorentinJ/Real-Time-Voice-Cloning/issues/786 | [] | Tivieosidi | 0 |
plotly/dash-table | plotly | 692 | Table content does not resize correctly in certain circumstances | ```
.cell-1-1 {
flex: 1 0 auto;
}
```
should be:
```
.cell-1-1 {
flex: 1 1 auto;
}
```
to respect its parent's size instead of only respecting its parent's size on growth. | open | 2020-02-17T20:55:16Z | 2020-04-02T21:06:22Z | https://github.com/plotly/dash-table/issues/692 | [
"dash-type-bug",
"dash-stage-in_review"
] | Marc-Andre-Rivet | 0 |
gee-community/geemap | streamlit | 781 | Add multiple layers using cartoee.add_layer() together with eemont? | <!-- Please search existing issues to avoid creating duplicates. -->
### Environment Information
- geemap version: 0.10.0
- Python version: 3.8.12
- Operating System: Scientific Linux 7.9 (Nitrogen)
- eemont: 0.2.5
- earthengine-api: 0.1.256
- cartopy: 0.20.1
### Description
I am interesting in using `cartoee` to make some nice plots. However, I find that a latter `cartoee.add_layer()` does not keep the previous `cartoee.add_layer()` and inconsistent with `eemont`? I will explain what I did and found detailed as below.
First, the following scripts will give me a nice plot with a point placed on an image.
```
import ee, eemont, geemap
from geemap import cartoee
ee.Initialize()
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
fig = plt.figure()
ax = plt.axes(projection=ccrs.PlateCarree())
image = ee.Image('LANDSAT/LC08/C02/T1_L2/LC08_170048_20190130')#.preprocess()
vis = {"bands":['SR_B5','SR_B4','SR_B3'], "min":0}
lon = 38.388611111000046
lat = 17.828333333000046
poi = ee.Geometry.Point(lon, lat)
cartoee.add_layer(ax, image, vis_params=vis)
ax.scatter(lon, lat,color="red",transform=ccrs.PlateCarree())
```
I then change the last line of code to `cartoee.add_layer(ax, poi, vis_params=dict(color="red"))` as I think `cartoee.add_layer()` could be used as many times as I want. However, I only get the single point as below. Does this mean `cartoee.add_layer()` cannot keep previous adds? Or was it due to that I not showing a reasonable extent?
Second, I find that employing `eemont` to preprocess satellite images will impede adding it as a layer. Simply removing the `#preprocess()` from the `image = ee.Image('LANDSAT/LC08/C02/T1_L2/LC08_170048_20190130')#.preprocess()` I encountered the following error:
```
Geometry.bounds: Unable to perform this geometry operation. Please specify a non-zero error margin.
```
Weirdly, this error can be overcome if I clip the image to a smaller extent, that is to change `cartoee.add_layer(ax, image, vis_params=vis)` to `cartoee.add_layer(ax, image.clip(poi.buffer(100*30).bounds()), vis_params=vis)` for an example. Also rollback to use `ax.scatter()` to add the point to achieve the effect below.
I understand that these issues involve several packages beyond `geemap`. I'd be very grateful if you could have a check on these issues and/or invite other developers to identify a way to overcome these issues at your earliest convenience.
Many thanks in advance!
| closed | 2021-12-02T18:05:59Z | 2021-12-03T09:59:09Z | https://github.com/gee-community/geemap/issues/781 | [
"bug"
] | FeiYao-Edinburgh | 4 |
horovod/horovod | deep-learning | 3,475 | horovod build fails with oneccl and tensorflow | **Environment:**
1. Framework: TensorFlow
2. Framework version: 2.6 and 2.8
3. Horovod version: 0.22.1 and 0.24.2
4. MPI version: OneCCL
5. CUDA version: N/A
6. NCCL version: N/A
7. Python version: 3.8.10
8. Spark / PySpark version:
9. Ray version:
10. OS and version: Ubuntu 18.04.4 LTS
11. GCC version: 7.5
12. CMake version: 3.10.2
**Checklist:**
1. Did you search issues to find if somebody asked this question before? Yes
2. If your question is about hang, did you read [this doc](https://github.com/horovod/horovod/blob/master/docs/running.rst)? Yes
3. If your question is about docker, did you read [this doc](https://github.com/horovod/horovod/blob/master/docs/docker.rst)? Yes
4. Did you check if you question is answered in the [troubleshooting guide] Yes (https://github.com/horovod/horovod/blob/master/docs/troubleshooting.rst)?
**Bug report:**
Please describe erroneous behavior you're observing and steps to reproduce it.
I followed the steps provided in this link.
https://horovod.readthedocs.io/en/stable/oneccl_include.html
ERROR: Command errored out with exit status 1: ../../../oneCCL_venv/bin/python -u -c 'import io, os, sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-req-build-02_6xuky/setup.py'"'"'; __file__='"'"'/tmp/pip-req-build-02_6xuky/setup.py'"'"';f = getattr(tokenize, '"'"'open'"'"', open)(__file__) if os.path.exists(__file__) else io.StringIO('"'"'from setuptools import setup; setup()'"'"');code = f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record /tmp/pip-record-5vrb6pf6/install-record.txt --single-version-externally-managed --compile --install-headers ../../../oneCCL_venv/include/site/python3.8/horovod Check the logs for full command output.
| open | 2022-03-17T22:28:33Z | 2023-05-08T14:16:39Z | https://github.com/horovod/horovod/issues/3475 | [
"bug"
] | ashiqimranintel | 4 |
flavors/django-graphql-jwt | graphql | 181 | Could you please release a new version with a fixed cookies? | closed | 2020-03-18T18:33:11Z | 2020-04-04T10:21:47Z | https://github.com/flavors/django-graphql-jwt/issues/181 | [] | TitanFighter | 4 | |
gradio-app/gradio | machine-learning | 10,681 | The properties and event design of this UI are simply a piece of dog poop | The properties and event design of this UI are simply a piece of dog poop！ | closed | 2025-02-26T09:00:12Z | 2025-02-26T18:58:43Z | https://github.com/gradio-app/gradio/issues/10681 | [] | string199 | 0 |
dropbox/PyHive | sqlalchemy | 373 | Specifying Client Tags | Hi Guys, is there a way to specify Client Tags when connecting/submitting a query?
From query details:
<img width="896" alt="Screen Shot 2021-01-04 at 14 06 02" src="https://user-images.githubusercontent.com/13641958/103533750-5a2ea780-4e96-11eb-94db-fade4f5ebf5a.png">
| open | 2021-01-04T12:08:59Z | 2021-02-05T16:21:37Z | https://github.com/dropbox/PyHive/issues/373 | [] | AntonPeniaziev | 2 |
fbdesignpro/sweetviz | pandas | 27 | Installation not working | Installation via pip on linux 16 does not seem to work:
sudo pip3 install sweetviz
ERROR: Could not find a version that satisfies the requirement sweetviz (from versions: none) | closed | 2020-07-09T08:57:04Z | 2020-10-08T13:38:56Z | https://github.com/fbdesignpro/sweetviz/issues/27 | [
"install/setup"
] | Liwellyen | 1 |
marcomusy/vedo | numpy | 417 | Coloring meshes | Hello Marco,
I prefer to open my new issue,
I'm trying to do something similar to this in your comment here:
[Coloring](https://github.com/marcomusy/vedo/issues/4#issuecomment-549467944)
There are several problems, I'm not able to make these commands in `vedo`
`makeLUT` , `sc.mapper.InterpolateScalarsBeforeMappingOff()`
And to summarize what I need to do, is like the following:
I have regions that I would like to color, for now, I'm assuming it is `3`, I would appreciate it to give me a general concept, I mean for `regions = n`
each region consists like this:
```
[list([2, 3, 25, 26, 27, 28, 35, 36, 37, 38, 45, 46, 47, 48, 55, 56, 57, 58, 65, 66, 67, 68, 75, 76, 77, 78, 85, 86, 87, 88, 95, 96, 97, 98, 105, 106, 107, 108, 115, 116, 117, 118, 125, 126, 127, 128, 135, 136, 137, 138, 145, 146, 147, 148, 155, 156, 157, 158, 165, 166, 167, 168, 175, 176, 177, 178, 185, 186, 187, 188, 195, 196, 197, 198, 205, 206, 207, 208, 215, 216, 217, 218, 225, 226, 227, 228, 235, 236, 237, 238])
list([6, 7, 8, 30, 31, 32, 33, 40, 41, 42, 43, 50, 51, 52, 53, 60, 61, 62, 63, 70, 71, 72, 73, 80, 81, 82, 83, 90, 91, 92, 93, 100, 101, 102, 103, 110, 111, 112, 113, 120, 121, 122, 123, 130, 131, 132, 133, 140, 141, 142, 143, 150, 151, 152, 153, 160, 161, 162, 163, 170, 171, 172, 173, 180, 181, 182, 183, 190, 191, 192, 193, 200, 201, 202, 203, 210, 211, 212, 213, 220, 221, 222, 223, 230, 231, 232, 233, 240, 241])
list([0, 1, 4, 5, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 29, 34, 39, 44, 49, 54, 59, 64, 69, 74, 79, 84, 89, 94, 99, 104, 109, 114, 119, 124, 129, 134, 139, 144, 149, 154, 159, 164, 169, 174, 179, 184, 189, 194, 199, 204, 209, 214, 219, 224, 229, 234, 239])]
```
When I tried your suggestion in [This](https://github.com/marcomusy/vedo/issues/54)
I'm getting the problem in Visualization: [here](https://github.com/marcomusy/vedo/issues/54#issuecomment-862244357)
I tend to get typically what visualized in the main issue referenced, and the weird thing, is that I need for example to get three colors, but this is not the case I'm getting.
I appreciated again getting a generalized application where I may get different region colors depending on the region number I will obtain. | closed | 2021-06-18T09:39:13Z | 2021-09-17T16:28:21Z | https://github.com/marcomusy/vedo/issues/417 | [] | roaasoloh | 7 |
statsmodels/statsmodels | data-science | 8,609 | ENH: hc3 cov_type for GMM, GMMIVNonlinear | this article has pseudo-hatmatrix for small sample corrections for HC2, HC3, ...
moment condition `z (y - g(x, beta))` i.e. nonlinear IV, but not for generic nonlinear GMM
Lin, Eric S., and Ta-Sheng Chou. “Finite-Sample Refinement of GMM Approach to Nonlinear Models under Heteroskedasticity of Unknown Form.” Econometric Reviews 37, no. 1 (January 2, 2018): 1–28. https://doi.org/10.1080/07474938.2014.999499.
I did not find any HC3 equivalent for generic GMM, and nothing for more general non-gaussian MLE.
(Poisson, GLM use the IRLS, WLS hatmatrix)
| open | 2023-01-06T19:11:15Z | 2023-01-06T19:11:41Z | https://github.com/statsmodels/statsmodels/issues/8609 | [
"type-enh",
"comp-regression",
"topic-covtype"
] | josef-pkt | 0 |
reloadware/reloadium | django | 91 | PyCharm: New UI support | Reloadium 'Run' and 'Debug' buttons are not visible when 'New UI' option is enabled in 'PyCharm'
## To Reproduce
Steps to reproduce the behavior:
1. Go to 'Settings -> Appearance & Behavior -> New UI'
2. Check 'Enable new UI' box and restart the IDE
3. The reloadium 'run' and ' debug' buttons are absent beside the normal run button
## Expected behavior
Reloadium 'Run' and 'Debug' buttons should co-exist with the normal run button when 'New UI' option is enabled
## Screenshots
## Desktop or remote (please complete the following information):**
- OS: Windows
- OS version: 22H2
- Reloadium package version: 0.9.5
- PyCharm plugin version: 0.9.5
- Editor: PyCharm
- Python Version: 3.11
- Python Architecture: 64bit
- Run mode: Both
| closed | 2023-01-28T09:45:33Z | 2023-02-27T15:21:17Z | https://github.com/reloadware/reloadium/issues/91 | [] | hhharsha36 | 3 |
idealo/image-super-resolution | computer-vision | 246 | Converted to TFLITE. | I've converted the rrdn model to tflite. but dont how to do the same thing with tflite. iF anyone know, i will share the model | open | 2023-10-20T09:26:15Z | 2023-10-20T09:26:15Z | https://github.com/idealo/image-super-resolution/issues/246 | [] | md-rifatkhan | 0 |
dask/dask | numpy | 11,253 | Docstring mismatch of chunksize parameter with actual implementation in multiprocessing `get` scheduler function | https://github.com/dask/dask/blob/534cd7b7d546657339b260f3274b2d1016bc181a/dask/multiprocessing.py#L180-L185
**Describe the issue**:
As can be seen the docstring indicates a default value of 5 at line 182, whereas in reality it is set to 6 at line 185.
I'd be happy to quickly fix this with a pull request, but I'd need to know which of those two values is the correct/intended one.
This is really a minor thing, however, for months one of my CI builds ran out of memory, and for the live of me I couldn't figure out what changed. Well until now, it seems at some point the `chunksize` has been changed from 5 to 6, and since I ran already on the limit of my RAM, that pushed it over the cliff.
No big deal, I set it to 5 manually now, and everything is again as it should be.
Maybe this clears up some vexing memory issues for other people as well ;).
- Dask version: at least from 2024.2.0 onwards
- Python version: 3.10
| closed | 2024-07-25T13:28:12Z | 2024-07-26T12:53:48Z | https://github.com/dask/dask/issues/11253 | [
"documentation"
] | SwamyDev | 1 |
modin-project/modin | data-science | 7,072 | BUG: The H&M benchmark fails on Ray | ### Modin version checks
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the latest released version of Modin.
- [X] I have confirmed this bug exists on the main branch of Modin. (In order to do this you can follow [this guide](https://modin.readthedocs.io/en/stable/getting_started/installation.html#installing-from-the-github-master-branch).)
### Reproducible Example
```python
Run the benchmark
```
### Issue Description
The benchmark fails with TypeError: unsupported operand type(s) for +: 'int' and 'MetaListHook'
### Expected Behavior
Does not fail.
### Error Logs
<details>
```python-traceback
Exception while running benchmark: ray::remote_exec_func() (pid=1039, ip=[172.17.0.3)](http://172.17.0.3)/)
At least one of the input arguments for this task could not be computed:
[ray.exceptions.RayTaskError:](http://ray.exceptions.raytaskerror/) ray::_deploy_ray_func() (pid=1039, ip=[172.17.0.3)](http://172.17.0.3)/)
File "/_work/modin/modin/core/execution/ray/implementations/pandas_on_ray/partitioning/[virtual_partition.py](http://virtual_partition.py/)", line 322, in _deploy_ray_func
result = deployer(axis, f_to_deploy, f_args, f_kwargs, *deploy_args, **kwargs)
File "/_work/modin/modin/core/dataframe/pandas/partitioning/[axis_partition.py](http://axis_partition.py/)", line 426, in deploy_axis_func
result = func(dataframe, *f_args, **f_kwargs)
File "/_work/modin/modin/core/dataframe/pandas/dataframe/[dataframe.py](http://dataframe.py/)", line 1989, in _tree_reduce_func
series_result = func(df, *args, **kwargs)
File "/_work/modin/modin/core/storage_formats/pandas/[query_compiler.py](http://query_compiler.py/)", line 600, in _reset
stop = sum(axis_lengths[: partition_idx + 1])
TypeError: unsupported operand type(s) for +: 'int' and 'MetaListHook'
```
</details>
### Installed Versions
<details>
Replace this line with the output of pd.show_versions()
</details>
| closed | 2024-03-12T17:35:08Z | 2024-03-14T08:45:37Z | https://github.com/modin-project/modin/issues/7072 | [
"bug 🦗",
"Ray ⚡"
] | AndreyPavlenko | 0 |
flaskbb/flaskbb | flask | 512 | translations is not work | I set my lang to 'zh_CN', but it not translation chinese. | closed | 2019-01-06T05:10:24Z | 2019-02-19T20:22:01Z | https://github.com/flaskbb/flaskbb/issues/512 | [] | ppker | 2 |
TencentARC/GFPGAN | pytorch | 593 | Tot | open | 2024-12-25T09:50:26Z | 2025-01-15T16:14:59Z | https://github.com/TencentARC/GFPGAN/issues/593 | [] | inus69 | 1 | |
trevorstephens/gplearn | scikit-learn | 13 | How to limit the memory required by gplearn? | I think the gplearn wil use as much memory as possible.
One machine is equipped with 8GB memory.The gplearn eats off 7.85GB and no exception is raised.Everyhing works well.
Another machine has 12GB memory and this time the gplearn consumes 11.8GB.At the last round of the genetic-compution,python is crashed due to a MemoryError.
It's an ironical phenomenon.Why more memory dosen't satisfy the appetite of gplearn instead?
(PS:The paramters of gplearn are fixed.Both environments are WINDOWS)
| closed | 2016-04-29T12:37:20Z | 2017-11-11T03:13:36Z | https://github.com/trevorstephens/gplearn/issues/13 | [
"duplicate"
] | nicoJiang | 4 |
schemathesis/schemathesis | graphql | 2,474 | [FEATURE] Option to case sensitive compare response schema conformance | ### Is your feature request related to a problem? Please describe
We expose apis that are consumed in low level languages on embedded devices and hence we would like to validate compliance that the response schema matches the casing. So we can deploy more confidently knowing not breaking contract.
### Describe the solution you'd like
Provide an option to validate the response schema with case sensitivity eg: `--case-sensitive`
I think this could be handled here: https://github.com/schemathesis/schemathesis/blob/master/src/schemathesis/specs/openapi/schemas.py#L650
### Describe alternatives you've considered
Doing string comparison in tests for casing in schemas is a pain in the but.
### Additional context
N/A
| closed | 2024-09-26T13:21:16Z | 2024-09-27T07:58:27Z | https://github.com/schemathesis/schemathesis/issues/2474 | [
"Status: Needs Triage",
"Type: Feature"
] | pregress | 4 |
redis/redis-om-python | pydantic | 643 | Insecure setuptools | `redis-om` depends on `setuptools` <70.0.0 which has a high severity security vulnerability:
https://github.com/advisories/GHSA-cx63-2mw6-8hw5
This is preventing projects using `redis-om` from patching the vulnerability. Can this be remedied asap? | closed | 2024-08-06T08:26:37Z | 2024-08-07T13:06:14Z | https://github.com/redis/redis-om-python/issues/643 | [] | markedwards | 2 |
bauerji/flask-pydantic | pydantic | 26 | Pyright error report | if the `validate` decorator decorates a function that has multiple arguments, then PyRight will report a `reportGeneralTypeIssues` like the picture attached:
| closed | 2021-03-09T01:14:17Z | 2021-03-09T12:55:32Z | https://github.com/bauerji/flask-pydantic/issues/26 | [] | buildpeak | 0 |
ipython/ipython | data-science | 14,442 | Translations of ipython core project website | <!-- This is the repository for IPython command line, if you can try to make sure this question/bug/feature belong here and not on one of the Jupyter repositories.
If it's a generic Python/Jupyter question, try other forums or discourse.jupyter.org.
If you are unsure, it's ok to post here, though, there are few maintainer so you might not get a fast response.
-->
Hi IPython team,
With support from the CZI [Scientific Python Community and Communications Infrastructure](https://scientific-python.org/doc/scientific-python-community-and-communications-infrastructure-2022.pdf) grant, [Quansight Labs](https://labs.quansight.org/) is able to offer assistance with developing and publishing translations of the brochure websites for the [Scientific Python Core Project](https://scientific-python.org/specs/core-projects/). You may have seen that translations into some languages are already available for https://numpy.org/, with a version switcher in the top right corner; we're offering to help core projects integrate something similar into their websites. Our aim is to accomplish this in a way that requires minimal effort from the core project maintainers.
I've been tasked with setting up the software infrastructure for translations, and am posting issues today to ask core project teams if they would like to participate. I've published an FAQ here: https://scientific-python-translations.github.io/faq/, with more information. Please take a look and let me know if you have any questions. If you decide to participate, I can begin setting up the translation infrastructure, which will require no work or input from maintainer teams (See [here](https://scientific-python-translations.github.io/faq/#what-work-is-expected-from-project-maintainers) in the FAQ for more details on the process).
As a disclaimer, @Carreau also works at Quansight Labs and I briefly discussed this translation project with him last year. | open | 2024-05-23T17:01:31Z | 2024-05-31T18:06:37Z | https://github.com/ipython/ipython/issues/14442 | [] | steppi | 6 |
nerfstudio-project/nerfstudio | computer-vision | 3,451 | Installation error | **Describe the bug**
When doing the git install for nerfstudio as described in the Install nerfstudio step.
pip install -e . got this erro
Collecting pyliblzfse>=0.4.1 (from viser==0.2.7->nerfstudio==1.1.4)
Downloading pyliblzfse-0.4.1.tar.gz (47 kB)
Preparing metadata (setup.py) ... error
error: subprocess-exited-with-error
× python setup.py egg_info did not run successfully.
│ exit code: 1
╰─> [1 lines of output]
ERROR: Can not execute `setup.py` since setuptools is not available in the build environment.
[end of output]
note: This error originates from a subprocess, and is likely not a problem with pip.
error: metadata-generation-failed
× Encountered error while generating package metadata.
╰─> See above for output.
**Expected behavior**
Nerfstudio to install successfully. I have earlier installed the older version and I have not seen/encounter this error
**Screenshots**
If applicable, add screenshots to help explain your problem.
**Additional context**
Add any other context about the problem here.
| open | 2024-09-27T17:00:11Z | 2024-09-27T17:00:11Z | https://github.com/nerfstudio-project/nerfstudio/issues/3451 | [] | ML-learner79 | 0 |
recommenders-team/recommenders | machine-learning | 2,186 | [FEATURE] Replace the FastAI notebook by a cartesian product with PyTorch and remove the FastAI dependency | ### Description
<!--- Describe your expected feature in detail -->
We had some issues with the FastAI dependency #2182. And realised that the fastai notebook is just a fancy wrapper on [PyTorch cartesian product](https://pytorch.org/docs/stable/generated/torch.cartesian_prod.html) between user and item embeddings.
https://github.com/recommenders-team/recommenders/blob/main/examples/00_quick_start/fastai_movielens.ipynb
### Expected behavior with the suggested feature
<!--- For example: -->
<!--- *Adding algorithm xxx will help people understand more about xxx use case scenarios. -->
We want replace the FastAI notebook with a PyTorch version
### Willingness to contribute
<!--- Go over all the following points, and put an `x` in the box that apply. -->
- [ ] Yes, I can contribute for this issue independently.
- [ ] Yes, I can contribute for this issue with guidance from Recommenders community.
- [ ] No, I cannot contribute at this time.
### Other Comments
Related to #1713
| open | 2024-11-11T14:52:01Z | 2025-01-27T09:58:41Z | https://github.com/recommenders-team/recommenders/issues/2186 | [
"enhancement"
] | miguelgfierro | 8 |
seleniumbase/SeleniumBase | web-scraping | 3,247 | Documenting the `selenium-wire` "Wire Mode" REPLACEMENT | ## Documenting the `selenium-wire` "Wire Mode" **REPLACEMENT**.
As many of you know, there's a `selenium-wire` integration via [SeleniumBase **Wire Mode**](https://github.com/seleniumbase/SeleniumBase/issues/2145).
There are two main issues with it:
* [Wire Mode](https://github.com/seleniumbase/SeleniumBase/issues/2145) isn't compatible with [UC Mode](https://github.com/seleniumbase/SeleniumBase/blob/master/help_docs/uc_mode.md).
* [selenium-wire](https://github.com/wkeeling/selenium-wire) has been archived. (No more updates)
**Here's the good news:** `selenium-wire` features are included in the new [SeleniumBase **CDP Mode**](https://github.com/seleniumbase/SeleniumBase/blob/master/examples/cdp_mode/ReadMe.md), (a subset of [**UC Mode**](https://github.com/seleniumbase/SeleniumBase/blob/master/help_docs/uc_mode.md)).
Here's an example of that, ([SeleniumBase/examples/cdp_mode/raw_res_sb.py](https://github.com/seleniumbase/SeleniumBase/blob/master/examples/cdp_mode/raw_res_sb.py)), where network requests and responses are captured and displayed:
```python
"""Using CDP.network.ResponseReceived and CDP.network.RequestWillBeSent."""
import colorama
import mycdp
import sys
from seleniumbase import SB
c1 = colorama.Fore.BLUE + colorama.Back.LIGHTYELLOW_EX
c2 = colorama.Fore.BLUE + colorama.Back.LIGHTGREEN_EX
cr = colorama.Style.RESET_ALL
if "linux" in sys.platform:
c1 = c2 = cr = ""
async def send_handler(event: mycdp.network.RequestWillBeSent):
r = event.request
s = f"{r.method} {r.url}"
for k, v in r.headers.items():
s += f"\n\t{k} : {v}"
print(c1 + "*** ==> RequestWillBeSent <== ***" + cr)
print(s)
async def receive_handler(event: mycdp.network.ResponseReceived):
print(c2 + "*** ==> ResponseReceived <== ***" + cr)
print(event.response)
with SB(uc=True, test=True, locale_code="en") as sb:
sb.activate_cdp_mode("about:blank")
sb.cdp.add_handler(mycdp.network.RequestWillBeSent, send_handler)
sb.cdp.add_handler(mycdp.network.ResponseReceived, receive_handler)
url = "https://seleniumbase.io/apps/calculator"
sb.cdp.open(url)
sb.sleep(1)
```
Usage is different from regular Selenium-Wire, but it can do all the same things (and more) with better flexibility/control.
Here's another example, ([SeleniumBase/examples/cdp_mode/raw_req_sb.py](https://github.com/seleniumbase/SeleniumBase/blob/master/examples/cdp_mode/raw_req_sb.py)), where specific requests were filtered out (intercepted and blocked), to prevent images from loading:
```python
"""Using CDP.fetch.RequestPaused to filter content in real-time."""
import colorama
import mycdp
import sys
from seleniumbase import SB
c1 = colorama.Fore.RED + colorama.Back.LIGHTYELLOW_EX
c2 = colorama.Fore.BLUE + colorama.Back.LIGHTCYAN_EX
cr = colorama.Style.RESET_ALL
if "linux" in sys.platform:
c1 = c2 = cr = ""
async def request_paused_handler(event, tab):
r = event.request
is_image = ".png" in r.url or ".jpg" in r.url or ".gif" in r.url
if not is_image: # Let the data through
tab.feed_cdp(mycdp.fetch.continue_request(request_id=event.request_id))
else: # Block the data (images)
TIMED_OUT = mycdp.network.ErrorReason.TIMED_OUT
s = f"{c1}BLOCKING{cr} | {c2}{r.method}{cr} | {r.url}"
print(f" >>> ------------\n{s}")
tab.feed_cdp(mycdp.fetch.fail_request(event.request_id, TIMED_OUT))
with SB(uc=True, test=True, locale_code="en") as sb:
sb.activate_cdp_mode("about:blank")
sb.cdp.add_handler(mycdp.fetch.RequestPaused, request_paused_handler)
url = "https://gettyimages.com/photos/firefly-2003-nathan"
sb.cdp.open(url)
sb.sleep(5)
```
If people don't need the stealth features (or other improvements made to intercepting/handling network requests & responses), then they can continue using the existing Wire Mode as is. Or, if people want the upgrades, then they can use the new [CDP Mode](https://github.com/seleniumbase/SeleniumBase/blob/master/examples/cdp_mode), (as shown above).
| open | 2024-11-06T16:27:44Z | 2024-11-25T14:14:54Z | https://github.com/seleniumbase/SeleniumBase/issues/3247 | [
"enhancement",
"documentation",
"UC Mode / CDP Mode"
] | mdmintz | 3 |
tensorpack/tensorpack | tensorflow | 1,052 | FasterRCNN: how can i print out metrics (total_loss, bbox_loss, label) metrics on evaluation data | I am modifying the FasterRCNN example for my custom dataset which is NOT in Coco-format.
Then the evaluation is ran (say every 25 epochs) I'd like to see the loss-metrics computed on the evaluation dataset. I cannot use COCODetection because my annotations are in different format.
Any recommendations?
Thanks | closed | 2019-01-16T11:20:00Z | 2019-01-17T17:42:04Z | https://github.com/tensorpack/tensorpack/issues/1052 | [
"duplicate"
] | ColonelKassad | 2 |
zihangdai/xlnet | tensorflow | 205 | Xlnet performing poorly compared to BERT (SQUAD 2.0) | Context given:
Mr. Anand Mahindra is the Chairman of the US $20.7 billion Mahindra Group and the Executive Chairman of Mahindra & Mahindra Ltd. His tenure has seen the Group expand domestically and internationally into a range of major industrial sectors from automobiles and agriculture to IT and aerospace. The Group has also grown inorganically through acquisitions such as Ssangyong Motors, Reva Electric Car Company, Satyam Computer Services, Peugeot Motorcycles, Gippsland Aeronautics, Aerostaff Australia, Holiday Club Resorts, Pininfarina S.p.A. He has served on several influential bodies, national and international. These include the UN Global Compact Board, Global Board of Advisors of the Council on Foreign Relations, World Bank Group's Advisory Board for Doing Business and the International Advisory Council of Singapore's Economic Development Board. He has been the President of The Confederation of Indian Industry and served on the boards of the National Stock Exchange of India and the National Council of Applied Economic Research. He is currently on the board of Invest India, the National Investment Promotion and Facilitation Agency. Mr. Mahindra has been named in Barron's List of Top 30 CEOs worldwide (2016) and Fortune Magazine's list of the World's 50 Greatest Leaders (2014). He was a recipient of the Best Transformational Leader Award by the Asian Centre for Corporate Governance & Sustainability (2012). He was appointed 'Knight in the National Order of the Legion of Honour' by the President of the French Republic (2016) and conferred the 'Grand Officer of the Order of the Star of Italy', by the President of Italy (2013). Mr. Mahindra is an incisive business commentator and humanitarian with over 6 million followers on Twitter. Among his many social change initiatives is the Nanhi Kali programme, which, for the last two decades, has provided over 330,000 under-privileged girls access to high quality education. Mr. Mahindra is the Chairman of the Board of Naandi Foundation, India's leading NGO focused on educating girls, skilling youth and providing sustainable livelihoods to small farmers through biodynamic agriculture. Mr. Mahindra also serves on the Founders Board of The Rise Fund, a $2 billion impact fund. He is a strong votary of arts and culture. Mahindra Blues, Mahindra Excellence in Theatre Awards and Mahindra Sanatkada celebrate and nurture music, theatre culture, art and history in India. Mr. Mahindra serves on the Board of Trustees of the Natural History Museum of London and as Chairman of the India Advisory Council of the Lincoln Center. Mr. Mahindra graduated from Harvard College (1977) and secured an MBA from Harvard Business School (1981).
-------------------------------------
Who is the chairman of tech mahindra?
Answer: expand
----------------------
Who is Anand Mahindra?
Answer: expand
--------------------------
Who is Executive Chairman?
Answer: expand
----------------------------------------------------------------------------
Who serves on the Board of Trustees of the Natural History Museum of London?
Answer: expand
-------------------------------------------------------------------------------
BERT gave accurate answers while Xlnet did not.
BERT (SQUAD 2.0) has f1 score of 81 and Xlnet (SQUAD 2.0) has f1 score of 88.
I did use trained checkpoint.
I checked with this following part of SQUAD 2.0,
`{"question": "In what country is Normandy located?", "id": "56ddde6b9a695914005b9628", "answers": [{"text": "France", "answer_start": 159}, {"text": "France", "answer_start": 159}, {"text": "France", "answer_start": 159}, {"text": "France", "answer_start": 159}], "is_impossible": false}`
`"context": "The Normans (Norman: Nourmands; French: Normands; Latin: Normanni) were the people who in the 10th and 11th centuries gave their name to Normandy, a region in France. They were descended from Norse (\"Norman\" comes from \"Norseman\") raiders and pirates from Denmark, Iceland and Norway who, under their leader Rollo, agreed to swear fealty to King Charles III of West Francia. Through generations of assimilation and mixing with the native Frankish and Roman-Gaulish populations, their descendants would gradually merge with the Carolingian-based cultures of West Francia. The distinct cultural and ethnic identity of the Normans emerged initially in the first half of the 10th century, and it continued to evolve over the succeeding centuries."`
It performed absolutely fine and got the answers predicted accurately. | open | 2019-08-06T06:22:13Z | 2019-08-06T06:24:43Z | https://github.com/zihangdai/xlnet/issues/205 | [] | JeevaTM | 0 |
gradio-app/gradio | data-visualization | 10,675 | Themebuilder: Google font is displayed in Colab but not displayed in Huggingface Hub | ### Describe the bug
**Update: this is caused by the bug reported in #10101, setting `ssr_mode=False` in `launch()` is a workaround**
**Update 2: apparently `ssr_mode=False` works for a space that uses the theme but not for the Theme preview itself, see https://huggingface.co/spaces/crcdng/font_test**
When a Google font is set in the Gradio Themebuilder in Google Colab it is displayed correctly. When uploading the theme to Huggingface Hub as a Space though, the font is not displayed.
### Have you searched existing issues? 🔎
- [x] I have searched and found no existing issues
### Reproduction
Prerequisites: Google Colab, Huggingface account, Huggingface token
To reproduce, in Google Colab
```python
!pip install gradio
import gradio as gr
gr.themes.builder()
```
In `Main Font` -> `Core Fonts` -> `Font 1` enter a Google font, e.g. `Oxanium` and tick the `Google font` checkmark.
The font in the Themebuilder demo will change to the selected one as expected.
Then use `Upload to Huggingface Hub` feature.
In the Huggingface Hub Space, a default font is displayed instead of the selected one.
### Screenshot
Font displayed in Colab
<img width="619" alt="Image" src="https://github.com/user-attachments/assets/4a335c39-472b-4e20-bc70-d58edc61d5c1" />
Font displayed in the HF space
<img width="415" alt="Image" src="https://github.com/user-attachments/assets/90a5b35c-f0a5-4ec8-af16-0819126656d5" />
### Logs
example space uploaded from Colab: https://huggingface.co/spaces/crcdng/font_test
```shell
Log of the space
themes%2Ftheme_schema%400.0.1.json: 0%| | 0.00/17.7k [00:00<?, ?B/s]
themes%2Ftheme_schema%400.0.1.json: 100%|██████████| 17.7k/17.7k [00:00<00:00, 50.9MB/s]
/usr/local/lib/python3.10/site-packages/gradio/components/chatbot.py:285: UserWarning: You have not specified a value for the `type` parameter. Defaulting to the 'tuples' format for chatbot messages, but this is deprecated and will be removed in a future version of Gradio. Please set type='messages' instead, which uses openai-style dictionaries with 'role' and 'content' keys.
warnings.warn(
* Running on local URL: http://0.0.0.0:7860, with SSR ⚡ (experimental, to disable set `ssr=False` in `launch()`)
To create a public link, set `share=True` in `launch()`.
Console.log of the space
font_test:241 Unrecognized feature: 'ambient-light-sensor'.
font_test:241 Unrecognized feature: 'battery'.
font_test:241 Unrecognized feature: 'document-domain'.
font_test:241 Unrecognized feature: 'layout-animations'.
font_test:241 Unrecognized feature: 'legacy-image-formats'.
font_test:241 Unrecognized feature: 'oversized-images'.
font_test:241 Unrecognized feature: 'vr'.
font_test:241 Unrecognized feature: 'wake-lock'.
crcdng-font-test.hf.space/:109 Mixed Content: The page at 'https://crcdng-font-test.hf.space/?__theme=light' was loaded over HTTPS, but requested an insecure element 'http://0.0.0.0:7860/gradio_api/file=/tmp/gradio/48b677af1fdad2de16cd1796d9fef50b849f4511d3136ab6d517296fa90f3228/header-image.jpg'. This request was not upgraded to HTTPS because its URL's host is an IP address.
crcdng-font-test.hf.space/:109 Mixed Content: The page at 'https://huggingface.co/' was loaded over HTTPS, but requested an insecure image 'http://0.0.0.0:7860/gradio_api/file=/tmp/gradio/48b677af1fdad2de16cd1796d9fef50b849f4511d3136ab6d517296fa90f3228/header-image.jpg'. This request has been blocked; the content must be served over HTTPS.
crcdng-font-test.hf.space/:112 Mixed Content: The page at 'https://crcdng-font-test.hf.space/?__theme=light' was loaded over HTTPS, but requested an insecure element 'http://0.0.0.0:7860/gradio_api/file=/tmp/gradio/f9a4efe1b7296f259dd0db86bcf4f4658d4247da0230a467518feb61eacac174/world.mp4'. This request was not upgraded to HTTPS because its URL's host is an IP address.
crcdng-font-test.hf.space/:112 Mixed Content: The page at 'https://huggingface.co/' was loaded over HTTPS, but requested an insecure video 'http://0.0.0.0:7860/gradio_api/file=/tmp/gradio/f9a4efe1b7296f259dd0db86bcf4f4658d4247da0230a467518feb61eacac174/world.mp4'. This request has been blocked; the content must be served over HTTPS.
ui-sans-serif-Bold.woff2:1
Failed to load resource: the server responded with a status of 404 ()
ui-sans-serif-Regular.woff2:1
Failed to load resource: the server responded with a status of 404 ()
ui-monospace-Regular.woff2:1
Failed to load resource: the server responded with a status of 404 ()
system-ui-Bold.woff2:1
Failed to load resource: the server responded with a status of 404 ()
system-ui-Regular.woff2:1
Failed to load resource: the server responded with a status of 404 ()
Consolas-Regular.woff2:1
Failed to load resource: the server responded with a status of 404 ()
index.js:6 SSE Stream ended
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```
### System Info
```shell
Gradio Environment Information:
------------------------------
Operating System: Linux
gradio version: 5.18.0
gradio_client version: 1.7.2
------------------------------------------------
gradio dependencies in your environment:
aiofiles: 23.2.1
anyio: 3.7.1
audioop-lts is not installed.
fastapi: 0.115.8
ffmpy: 0.5.0
gradio-client==1.7.2 is not installed.
httpx: 0.28.1
huggingface-hub: 0.28.1
jinja2: 3.1.5
markupsafe: 2.1.5
numpy: 1.26.4
orjson: 3.10.15
packaging: 24.2
pandas: 2.2.2
pillow: 11.1.0
pydantic: 2.10.6
pydub: 0.25.1
python-multipart: 0.0.20
pyyaml: 6.0.2
ruff: 0.9.7
safehttpx: 0.1.6
semantic-version: 2.10.0
starlette: 0.45.3
tomlkit: 0.13.2
typer: 0.15.1
typing-extensions: 4.12.2
urllib3: 2.3.0
uvicorn: 0.34.0
authlib; extra == 'oauth' is not installed.
itsdangerous; extra == 'oauth' is not installed.
gradio_client dependencies in your environment:
fsspec: 2024.10.0
httpx: 0.28.1
huggingface-hub: 0.28.1
packaging: 24.2
typing-extensions: 4.12.2
websockets: 14.2
```
### Severity
I can work around it | open | 2025-02-25T17:35:26Z | 2025-02-27T02:53:28Z | https://github.com/gradio-app/gradio/issues/10675 | [
"bug"
] | crcdng | 0 |
jupyterlab/jupyter-ai | jupyter | 613 | Custom slash command build failed | Hello, I'm working on implementing a custom slash command in ChatUI as per the guidelines provided in the documentation at https://jupyter-ai.readthedocs.io/en/latest/developers/index.html#custom-slash-commands-in-the-chat-ui.
I followed the plugin creation instructions outlined in https://github.com/jupyterlab/jupyter-ai/blob/main/packages/jupyter-ai-module-cookiecutter/README.md.
However, I'm encountering an unusual build issue that I find challenging to comprehend. When I attempt to build the plugin solution using https://github.com/jupyterlab/jupyter-ai/blob/main/scripts/install.sh, the build fails due to a new command plugin issue.
error that I retrieve
```
@jupyter-ai/jupyter-ai-chat: Traceback (most recent call last):
@jupyter-ai/jupyter-ai-chat: File "/miniconda3/envs/jupyter-ai/lib/python3.11/site-packages/pip/_internal/cli/base_command.py", line 180, in exc_logging_wrapper
@jupyter-ai/jupyter-ai-chat: status = run_func(*args)
@jupyter-ai/jupyter-ai-chat: ^^^^^^^^^^^^^^^
@jupyter-ai/jupyter-ai-chat: File "/miniconda3/envs/jupyter-ai/lib/python3.11/site-packages/pip/_internal/cli/req_command.py", line 245, in wrapper
@jupyter-ai/jupyter-ai-chat: return func(self, options, args)
@jupyter-ai/jupyter-ai-chat: ^^^^^^^^^^^^^^^^^^^^^^^^^
@jupyter-ai/jupyter-ai-chat: File "/miniconda3/envs/jupyter-ai/lib/python3.11/site-packages/pip/_internal/commands/install.py", line 377, in run
@jupyter-ai/jupyter-ai-chat: requirement_set = resolver.resolve(
@jupyter-ai/jupyter-ai-chat: ^^^^^^^^^^^^^^^^^
@jupyter-ai/jupyter-ai-chat: File "/miniconda3/envs/jupyter-ai/lib/python3.11/site-packages/pip/_internal/resolution/resolvelib/resolver.py", line 95, in resolve
@jupyter-ai/jupyter-ai-chat: result = self._result = resolver.resolve(
@jupyter-ai/jupyter-ai-chat: ^^^^^^^^^^^^^^^^^
@jupyter-ai/jupyter-ai-chat: File "/miniconda3/envs/jupyter-ai/lib/python3.11/site-packages/pip/_vendor/resolvelib/resolvers.py", line 546, in resolve
@jupyter-ai/jupyter-ai-chat: state = resolution.resolve(requirements, max_rounds=max_rounds)
@jupyter-ai/jupyter-ai-chat: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
@jupyter-ai/jupyter-ai-chat: File "/miniconda3/envs/jupyter-ai/lib/python3.11/site-packages/pip/_vendor/resolvelib/resolvers.py", line 427, in resolve
@jupyter-ai/jupyter-ai-chat: failure_causes = self._attempt_to_pin_criterion(name)
@jupyter-ai/jupyter-ai-chat: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
@jupyter-ai/jupyter-ai-chat: File "/miniconda3/envs/jupyter-ai/lib/python3.11/site-packages/pip/_vendor/resolvelib/resolvers.py", line 239, in _attempt_to_pin_criterion
@jupyter-ai/jupyter-ai-chat: criteria = self._get_updated_criteria(candidate)
@jupyter-ai/jupyter-ai-chat: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
@jupyter-ai/jupyter-ai-chat: File "/miniconda3/envs/jupyter-ai/lib/python3.11/site-packages/pip/_vendor/resolvelib/resolvers.py", line 230, in _get_updated_criteria
@jupyter-ai/jupyter-ai-chat: self._add_to_criteria(criteria, requirement, parent=candidate)
@jupyter-ai/jupyter-ai-chat: File "/miniconda3/envs/jupyter-ai/lib/python3.11/site-packages/pip/_vendor/resolvelib/resolvers.py", line 148, in _add_to_criteria
@jupyter-ai/jupyter-ai-chat: matches = self._p.find_matches(
@jupyter-ai/jupyter-ai-chat: ^^^^^^^^^^^^^^^^^^^^^
@jupyter-ai/jupyter-ai-chat: File "/miniconda3/envs/jupyter-ai/lib/python3.11/site-packages/pip/_internal/resolution/resolvelib/provider.py", line 231, in find_matches
@jupyter-ai/jupyter-ai-chat: return self._factory.find_candidates(
@jupyter-ai/jupyter-ai-chat: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
@jupyter-ai/jupyter-ai-chat: File "/miniconda3/envs/jupyter-ai/lib/python3.11/site-packages/pip/_internal/resolution/resolvelib/factory.py", line 446, in find_candidates
@jupyter-ai/jupyter-ai-chat: return self._iter_found_candidates(
@jupyter-ai/jupyter-ai-chat: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
@jupyter-ai/jupyter-ai-chat: File "/miniconda3/envs/jupyter-ai/lib/python3.11/site-packages/pip/_internal/resolution/resolvelib/factory.py", line 338, in _iter_found_candidates
@jupyter-ai/jupyter-ai-chat: _get_installed_candidate(),
@jupyter-ai/jupyter-ai-chat: ^^^^^^^^^^^^^^^^^^^^^^^^^^
@jupyter-ai/jupyter-ai-chat: File "/miniconda3/envs/jupyter-ai/lib/python3.11/site-packages/pip/_internal/resolution/resolvelib/factory.py", line 284, in _get_installed_candidate
@jupyter-ai/jupyter-ai-chat: if not specifier.contains(installed_dist.version, prereleases=True):
@jupyter-ai/jupyter-ai-chat: ^^^^^^^^^^^^^^^^^^^^^^
@jupyter-ai/jupyter-ai-chat: File "/miniconda3/envs/jupyter-ai/lib/python3.11/site-packages/pip/_internal/metadata/importlib/_dists.py", line 177, in version
@jupyter-ai/jupyter-ai-chat: return parse_version(self._dist.version)
@jupyter-ai/jupyter-ai-chat: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
@jupyter-ai/jupyter-ai-chat: File "/Users/fbalicchia/miniconda3/envs/jupyter-ai/lib/python3.11/site-packages/pip/_vendor/packaging/version.py", line 49, in parse
@jupyter-ai/jupyter-ai-chat: return Version(version)
@jupyter-ai/jupyter-ai-chat: ^^^^^^^^^^^^^^^^
@jupyter-ai/jupyter-ai-chat: File "/Users/fbalicchia/miniconda3/envs/jupyter-ai/lib/python3.11/site-packages/pip/_vendor/packaging/version.py", line 264, in __init__
@jupyter-ai/jupyter-ai-chat: match = self._regex.search(version)
@jupyter-ai/jupyter-ai-chat: ^^^^^^^^^^^^^^^^^^^^^^^^^^^
@jupyter-ai/jupyter-ai-chat: TypeError: expected string or bytes-like object, got 'NoneType'
@jupyter-ai/jupyter-ai-chat:
```
a Custom slash command used to reproduce the problem can be found here `git@github.com:fbalicchia/jupyter-ai-chat.git.`
Please note that on the other hand, building it with `jlpm dev-install` in the https://github.com/jupyterlab/jupyter-ai/tree/main/packages/jupyter-ai-chat folder works for me
Could you please advise me on where I might be making a mistake?
Thanks
| closed | 2024-02-01T11:52:27Z | 2024-02-14T13:34:38Z | https://github.com/jupyterlab/jupyter-ai/issues/613 | [
"bug"
] | fbalicchia | 7 |
WZMIAOMIAO/deep-learning-for-image-processing | pytorch | 370 | 关于EfficientNetV2的特征图可视化，及其features（或是blocks） | 作者你好，我打算进行特征图可视化，用到hook方法，但是需要有网络结构得features，请问有什么办法可以获取吗？我看到blocks，但是调用不了 | closed | 2021-10-25T07:40:21Z | 2021-10-28T06:43:10Z | https://github.com/WZMIAOMIAO/deep-learning-for-image-processing/issues/370 | [] | LaoGanGit | 1 |
Anjok07/ultimatevocalremovergui | pytorch | 1,239 | Intel GPU (PVC) support on Linux | Hi @Anjok07, Does UVR support Intel GPUs on Linux and especially do you support Intel PVC yet? | open | 2024-03-11T05:36:02Z | 2024-10-29T16:45:39Z | https://github.com/Anjok07/ultimatevocalremovergui/issues/1239 | [] | kballeda | 2 |
bmoscon/cryptofeed | asyncio | 252 | Can you add additional liquidation feed? | Looking at standards.py, it looks like Bitmex is the only liquidation feed?
```
LIQUIDATIONS: {
BITMEX: 'liquidation'
}
```
There is another project that I've been watching (that is also pretty awesome IMHO), [SignificantTrades](https://github.com/Tucsky/SignificantTrades).. I'm particularly interested in Binance (in this case Binance Futures) at this time, because that is where I have funds. So...I guess that is why I am aware of this.
The project here:
> line 82 of:
> https://github.com/Tucsky/SignificantTrades/blob/master/src/exchanges/binance-futures.js
The stream is 'forceOrder'. Documentation here:
> https://binance-docs.github.io/apidocs/futures/en/#liquidation-order-streams
Looking at the docs, it looks like they also have a feed for all liquidations regardless of the pair. I kind of would be curious to collect and look at this and see what is going on.. Don't know if it would 'fit in' w/how things are setup now though? | closed | 2020-06-20T21:53:49Z | 2020-08-25T23:33:39Z | https://github.com/bmoscon/cryptofeed/issues/252 | [
"good first issue",
"Feature Request"
] | brizzbane | 6 |
quasarstream/python-ffmpeg-video-streaming | dash | 79 | cannot schedule new futures after interpreter shutdown when use cloud (s3) to upload outputs | **app.py
```
import os
import pathlib
import ffmpeg_streaming
from ffmpeg_streaming import Formats, S3, CloudManager
BASE_DIR = str(pathlib.Path(__file__).parent)
INPUT_PATH = os.path.join(BASE_DIR, 'video.mp4')
OUTPUT_PATH = os.path.join(BASE_DIR, 'output')
video = ffmpeg_streaming.input(INPUT_PATH)
hls = video.hls(Formats.h264())
hls.auto_generate_representations()
s3 = S3(
region_name='sgp1',
aws_access_key_id='<hidden_for_security_reason>',
aws_secret_access_key='<hidden_for_security_reason>'
)
save_to_s3 = CloudManager().add(s3, bucket_name="tokbee")
hls.output(clouds=save_to_s3)
```
** Error Log
```
app_1 | Error in atexit._run_exitfuncs:
app_1 | Traceback (most recent call last):
app_1 | File "/usr/local/lib/python3.8/site-packages/ffmpeg_streaming/_clouds.py", line 59, in upload_directory
app_1 | self.s3.upload_file(join(directory, file), bucket_name, join(folder, file).replace("\\", "/"))
app_1 | File "/usr/local/lib/python3.8/site-packages/boto3/s3/inject.py", line 143, in upload_file
app_1 | return transfer.upload_file(
app_1 | File "/usr/local/lib/python3.8/site-packages/boto3/s3/transfer.py", line 284, in upload_file
app_1 | future = self._manager.upload(
app_1 | File "/usr/local/lib/python3.8/site-packages/s3transfer/manager.py", line 330, in upload
app_1 | return self._submit_transfer(
app_1 | File "/usr/local/lib/python3.8/site-packages/s3transfer/manager.py", line 525, in _submit_transfer
app_1 | self._submission_executor.submit(
app_1 | File "/usr/local/lib/python3.8/site-packages/s3transfer/futures.py", line 474, in submit
app_1 | future = ExecutorFuture(self._executor.submit(task))
app_1 | File "/usr/local/lib/python3.8/concurrent/futures/thread.py", line 181, in submit
app_1 | raise RuntimeError('cannot schedule new futures after '
app_1 | RuntimeError: cannot schedule new futures after interpreter shutdown
hls_transcoder_pro_app_1 exited with code 0
``` | closed | 2022-03-17T15:31:15Z | 2023-04-09T11:19:30Z | https://github.com/quasarstream/python-ffmpeg-video-streaming/issues/79 | [
"bug"
] | hir4k | 3 |
mouredev/Hello-Python | fastapi | 440 | 网上平台客服告知流水不足无法提现该怎么办？ | 被黑了不能出款找我们啊超出黑团队多年经验，如果你被黑了请联系我们帮忙把损失降到最低/微x:<>《微信xiaolu460570》前期出不收任何费用，我们团队都是先出款/后收费。不成功不收费、
当网赢了不能提款的问题怎么办呢？
首先我们应该保持冷静，如果提现被拒绝不重复点了，切不能跟平台客服称代理人有任何争执，一旦激怒对方，极有可能造成账号冻结之类的情况，这样问题就很难处理了，此时对方的理由或者我们要表示相信，并尽快处理，在稳定住对方后希望。
第一时间联系专业出黑团队，通过藏分锁卡等手段分批出款，这样问题我们就顺利解决了，如果您目前遇到网赢钱无法提款的，请及时联系专业出黑团队为您处理↓↓↓↓↓
 | closed | 2025-03-03T12:26:13Z | 2025-03-04T08:41:36Z | https://github.com/mouredev/Hello-Python/issues/440 | [] | 376838 | 0 |
plotly/dash | data-science | 2,683 | @cache.memoize() does not work within a callback with background=True [BUG] | within a dash background callback
```
@dash.callback(background=True, manager=background_callback_manager)
def the_callback_method():
x = get_data_from_db_that_needs_caching(bla)
```
If the code within the callback calls another method decorated with cache memoize.
e.g.
```
@cache.memoize()
def get_data_from_db_that_needs_caching(bla):
return lots_of_data
```
Then nothing is cached. The next time the callback runs, the result is not pulled from cache but 'get_data_from_db_that_needs_caching' executes again.
With the following cache configurations:
```disk_cache = diskcache.Cache("./cache")
background_callback_manager = DiskcacheManager(disk_cache)
cache = Cache(config={
'CACHE_TYPE': 'SimpleCache',
'CACHE_DEFAULT_TIMEOUT': 14400, #4 hours
'CACHE_IGNORE_ERRORS': True,
'CACHE_THRESHOLD' : 20
})
app = Dash(__name__, use_pages=True, suppress_callback_exceptions=True, external_stylesheets=[dbc.themes.BOOTSTRAP])
app.enable_dev_tools(dev_tools_hot_reload=False)
cache.init_app(app.server)
```
if background=False / no background callback manager, then caching of 'get_data_from_db_that_needs_caching' works fine.
dash==2.9.3 | closed | 2023-11-01T23:57:31Z | 2023-11-02T03:06:55Z | https://github.com/plotly/dash/issues/2683 | [] | leijer | 2 |
xlwings/xlwings | automation | 1,619 | Not able to close the excel file that is open by xlwings | #### OS
Windows 10
#### Versions of xlwings, Excel and Python
xlwings 0.23.3
Python 3.8.6
Office 365
#### Description
I am new to xlwings,
The code below left an open instance of excel which is not shown and idk how to close it ,now every time I run any excel operation it gives me a [Errno13] permission denied.
I checked all permissions, everything is as need to be.
There is an instance ~file.xlsx open when I see my VS code editor.
Although my code has .close() it doesn't close the open file
How do I close it?
```python
# Your traceback here
Exception: [Errno 13] Permission Denied: 'filepath'
```
#### Include a minimal code sample to reproduce the issue (and attach a sample workbook if required!)
```python
import xlwings as xw
def write_to_excel(sheetname,df1,df2,df3,df4,df5)
wb = xw.Book(r"filepath/file.xlsx")
ws = wb.sheets(sheetname)
ws.cells(row,col).options(index=False, header=False).value = df1
ws.cells(row,col).options(index=False, header=False).value = df2
ws.cells(row,col).options(index=False, header=False).value = df3
ws.cells(row,col).options(index=False, header=False).value = df4
ws.cells(row,col).options(index=False, header=False).value = df5
wb.save()
wb.close()
``` | closed | 2021-06-11T20:41:45Z | 2021-10-18T13:47:56Z | https://github.com/xlwings/xlwings/issues/1619 | [] | Abhishekkini | 15 |
polakowo/vectorbt | data-visualization | 92 | Inserting a custom Subplot | Hi @polakowo,
I am trying to add an external plotly chart into `portfolio.plot()` charts (with same x-axis size).
It is a candlestick chart:
```
fig = go.Figure(data=[go.Candlestick(x=df.index,
open=df['Open'], high=df['High'],
low=df['Low'], close=df['Close'])
])
last = 0
for i in range(len(df.index)):
temp = df.iloc[i]
if temp.b_s == 1:
fig.add_annotation(x=i, y=temp['buy'], text="▲", showarrow=False, font=dict(size=20, color='LightSeaGreen'))
last = temp
elif temp.b_s == -1:
fig.add_annotation(x=i, y=temp['sell'], text="▼", showarrow=False, font=dict(size=20, color='red'))
fig.update_layout(xaxis_rangeslider_visible=False)
```
Is it possible to add this as a subplot ?
I got stuck how should I proceed
```
fig2 = portfolio.plot(subplots=[
'orders',
('candlestick-orders', dict(
title='candlestick-orders',
can_plot_groups=False
))
])
```
| closed | 2021-01-27T22:54:15Z | 2021-01-28T17:15:28Z | https://github.com/polakowo/vectorbt/issues/92 | [] | kaleming | 2 |
globaleaks/globaleaks-whistleblowing-software | sqlalchemy | 3,190 | Configurable Default Configuration for Sites | **Is your feature request related to a problem? Please describe.**
When creating a new site based on the multisite feature, the default configuration settings defined in [1] are applied to this new site. Any changes to these settings must be applied after the site was created, either manually via UI or via REST. Currently, there is no way to configure the default configuration settings, as they are hard coded [1].
**Describe the solution you'd like**
As an administrator, I would like to be able to configure the default configuration settings in order for them to be applied automatically upon site creation.
This could be achieved in multiple ways, not limited to but including:
1) Storing all default configuration settings in an editable configuration file / database table.
2) Overriding individual configuration settings from an editable configuration file or database table.
**Describe alternatives you've considered**
It was considered to create a JS file, upload it to a newly created site and have it execute REST calls to update settings. A clear limitation of this approach would be that e.g. the SMTP password or SSL certificates would have to be stored in plain text in such a JS file.
**Additional context**
[1] https://github.com/globaleaks/GlobaLeaks/blob/main/backend/globaleaks/models/config_desc.py | closed | 2022-03-07T14:51:25Z | 2023-04-19T10:32:54Z | https://github.com/globaleaks/globaleaks-whistleblowing-software/issues/3190 | [] | fdoe | 3 |
hyperspy/hyperspy | data-visualization | 2,959 | Plotting EELS Spectrum in .dm4 file | #### Describe the bug
Hello, I am new to this Forum and in the use hyperspy, probably my bug is a stupid thing.
I have a problem with plotting the EELS spectrum, inside in .dm4 file (Gatan File)
#### To Reproduce
import hyperspy.api as hs
%matplotlib notebook
s = hs.load("data/[...].dm4")
s
<Signal2D, title: ADF Image (SI Survey), dimensions: (|512, 512)>,
<EELSSpectrum, title: EELS Spectrum Image, dimensions: (364, 363|1638)>]
**s.plot()**
AttributeError Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_1736\1823596060.py in <cell line: 1>()
----> 1 s.plot()
AttributeError: 'list' object has no attribute 'plot'
#### Expected behavior
Why I can't plot the spectrum?
What is a 'list file'?
Can I split the data?
Thanks to all
| closed | 2022-06-16T09:43:25Z | 2022-06-16T11:26:50Z | https://github.com/hyperspy/hyperspy/issues/2959 | [] | Psiche91 | 2 |
plotly/dash | plotly | 2,982 | Remove component loader | Remove the old component loader, old libraries which do not generate the python components will be unsupported.
- [x] Deprecate component loader.
- [ ] Remove component loader for dash 3.0 | open | 2024-09-04T15:30:44Z | 2024-09-06T14:44:16Z | https://github.com/plotly/dash/issues/2982 | [
"dash-3.0"
] | T4rk1n | 0 |
tensorly/tensorly | numpy | 365 | Whether the feature loading was the importance of feature in CP or tucker decomposition? | In PCA, the feature loading was taken as the contribution of each feature to the axis.
Could we claim the feature loading of variable was the importance in some conditions? | closed | 2022-01-23T13:38:00Z | 2023-01-24T15:30:12Z | https://github.com/tensorly/tensorly/issues/365 | [] | wanglu2014 | 1 |
Urinx/WeixinBot | api | 93 | 小白求教已安装Microsoft Visual C++ Compiler for Python 2.7，安装lxml时还是失败。单独安装 libxml2 and libxslt时也找不到相应版本。 | (weixin) C:\python>pip install lxml
Collecting lxml
Using cached lxml-3.6.4.tar.gz
Building wheels for collected packages: lxml
Running setup.py bdist_wheel for lxml ... error
Complete output from command c:\python\weixin\scripts\python.exe -u -c "import setuptools, tokenize;**file**='c:\users\lenovo\appdata\local\temp\pip-build-nyz5gp\lxml\setup.py';exec(compile(getattr(tokenize, 'open', open)(**file**).read().replace('\r\n', '\n'), **file**, 'exec'))" bdist_wheel -d c:\users\lenovo\appdata\local\temp\tmpdddbcppip-wheel- --python-tag cp27:
Building lxml version 3.6.4.
Building without Cython.
ERROR: 'xslt-config' 不是内部或外部命令，也不是可运行的程序
或批处理文件。
*\* make sure the development packages of libxml2 and libxslt are installed **
Using build configuration of libxslt
running bdist_wheel
running build
running build_py
creating build
creating build\lib.win32-2.7
creating build\lib.win32-2.7\lxml
copying src\lxml\builder.py -> build\lib.win32-2.7\lxml
copying src\lxml\cssselect.py -> build\lib.win32-2.7\lxml
copying src\lxml\doctestcompare.py -> build\lib.win32-2.7\lxml
copying src\lxml\ElementInclude.py -> build\lib.win32-2.7\lxml
copying src\lxml\pyclasslookup.py -> build\lib.win32-2.7\lxml
copying src\lxml\sax.py -> build\lib.win32-2.7\lxml
copying src\lxml\usedoctest.py -> build\lib.win32-2.7\lxml
copying src\lxml_elementpath.py -> build\lib.win32-2.7\lxml
copying src\lxml__init__.py -> build\lib.win32-2.7\lxml
creating build\lib.win32-2.7\lxml\includes
copying src\lxml\includes__init__.py -> build\lib.win32-2.7\lxml\includes
creating build\lib.win32-2.7\lxml\html
copying src\lxml\html\builder.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html\clean.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html\defs.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html\diff.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html\ElementSoup.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html\formfill.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html\html5parser.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html\soupparser.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html\usedoctest.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html_diffcommand.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html_html5builder.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html_setmixin.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html__init__.py -> build\lib.win32-2.7\lxml\html
creating build\lib.win32-2.7\lxml\isoschematron
copying src\lxml\isoschematron__init__.py -> build\lib.win32-2.7\lxml\isoschematron
copying src\lxml\lxml.etree.h -> build\lib.win32-2.7\lxml
copying src\lxml\lxml.etree_api.h -> build\lib.win32-2.7\lxml
copying src\lxml\includes\c14n.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\config.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\dtdvalid.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\etreepublic.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\htmlparser.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\relaxng.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\schematron.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\tree.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\uri.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\xinclude.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\xmlerror.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\xmlparser.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\xmlschema.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\xpath.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\xslt.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\etree_defs.h -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\lxml-version.h -> build\lib.win32-2.7\lxml\includes
creating build\lib.win32-2.7\lxml\isoschematron\resources
creating build\lib.win32-2.7\lxml\isoschematron\resources\rng
copying src\lxml\isoschematron\resources\rng\iso-schematron.rng -> build\lib.win32-2.7\lxml\isoschematron\resources\rng
creating build\lib.win32-2.7\lxml\isoschematron\resources\xsl
copying src\lxml\isoschematron\resources\xsl\RNG2Schtrn.xsl -> build\lib.win32-2.7\lxml\isoschematron\resources\xsl
copying src\lxml\isoschematron\resources\xsl\XSD2Schtrn.xsl -> build\lib.win32-2.7\lxml\isoschematron\resources\xsl
creating build\lib.win32-2.7\lxml\isoschematron\resources\xsl\iso-schematron-xslt1
copying src\lxml\isoschematron\resources\xsl\iso-schematron-xslt1\iso_abstract_expand.xsl -> build\lib.win32-2.7\lxml\isoschematron\resources\xsl\iso-schematron-xslt1
copying src\lxml\isoschematron\resources\xsl\iso-schematron-xslt1\iso_dsdl_include.xsl -> build\lib.win32-2.7\lxml\isoschematron\resources\xsl\iso-schematron-xslt1
copying src\lxml\isoschematron\resources\xsl\iso-schematron-xslt1\iso_schematron_message.xsl -> build\lib.win32-2.7\lxml\isoschematron\resources\xsl\iso-schematron-xslt1
copying src\lxml\isoschematron\resources\xsl\iso-schematron-xslt1\iso_schematron_skeleton_for_xslt1.xsl -> build\lib.win32-2.7\lxml\isoschematron\resources\xsl\iso-schematron-xslt1
copying src\lxml\isoschematron\resources\xsl\iso-schematron-xslt1\iso_svrl_for_xslt1.xsl -> build\lib.win32-2.7\lxml\isoschematron\resources\xsl\iso-schematron-xslt1
copying src\lxml\isoschematron\resources\xsl\iso-schematron-xslt1\readme.txt -> build\lib.win32-2.7\lxml\isoschematron\resources\xsl\iso-schematron-xslt1
running build_ext
building 'lxml.etree' extension
creating build\temp.win32-2.7
creating build\temp.win32-2.7\Release
creating build\temp.win32-2.7\Release\src
creating build\temp.win32-2.7\Release\src\lxml
C:\Users\lenovo\AppData\Local\Programs\Common\Microsoft\Visual C++ for Python\9.0\VC\Bin\cl.exe /c /nologo /Ox /MD /W3 /GS- /DNDEBUG -Isrc\lxml\includes -Ic:\python27\include -Ic:\python\weixin\PC /Tcsrc\lxml\lxml.etree.c /Fobuild\temp.win32-2.7\Release\src\lxml\lxml.etree.obj -w
cl : Command line warning D9025 : overriding '/W3' with '/w'
lxml.etree.c
src\lxml\includes\etree_defs.h(14) : fatal error C1083: Cannot open include file: 'libxml/xmlversion.h': No such file or directory
Compile failed: command 'C:\Users\lenovo\AppData\Local\Programs\Common\Microsoft\Visual C++ for Python\9.0\VC\Bin\cl.exe' failed with exit status 2
creating users
creating users\lenovo
creating users\lenovo\appdata
creating users\lenovo\appdata\local
creating users\lenovo\appdata\local\temp
C:\Users\lenovo\AppData\Local\Programs\Common\Microsoft\Visual C++ for Python\9.0\VC\Bin\cl.exe /c /nologo /Ox /MD /W3 /GS- /DNDEBUG -I/usr/include/libxml2 /Tcc:\users\lenovo\appdata\local\temp\xmlXPathInitk4hzgn.c /Fousers\lenovo\appdata\local\temp\xmlXPathInitk4hzgn.obj
xmlXPathInitk4hzgn.c
c:\users\lenovo\appdata\local\temp\xmlXPathInitk4hzgn.c(1) : fatal error C1083: Cannot open include file: 'libxml/xpath.h': No such file or directory
---
Could not find function xmlCheckVersion in library libxml2. Is libxml2 installed?
---
error: command 'C:\Users\lenovo\AppData\Local\Programs\Common\Microsoft\Visual C++ for Python\9.0\VC\Bin\cl.exe' failed with exit status 2
---
Failed building wheel for lxml
Running setup.py clean for lxml
Failed to build lxml
Installing collected packages: lxml
Running setup.py install for lxml ... error
Complete output from command c:\python\weixin\scripts\python.exe -u -c "import setuptools, tokenize;**file**='c:\users\lenovo\appdata\local\temp\pip-build-nyz5gp\lxml\setup.py';exec(compile(getattr(tokenize, 'open', open)(**file**).read().replace('\r\n', '\n'), **file**, 'exec'))" install --record c:\users\lenovo\appdata\local\temp\pip-g884nz-record\install-record.txt --single-version-externally-managed --compile --install-headers c:\python\weixin\include\site\python2.7\lxml:
Building lxml version 3.6.4.
Building without Cython.
ERROR: 'xslt-config' 不是内部或外部命令，也不是可运行的程序
或批处理文件。
```
** make sure the development packages of libxml2 and libxslt are installed **
Using build configuration of libxslt
running install
running build
running build_py
creating build
creating build\lib.win32-2.7
creating build\lib.win32-2.7\lxml
copying src\lxml\builder.py -> build\lib.win32-2.7\lxml
copying src\lxml\cssselect.py -> build\lib.win32-2.7\lxml
copying src\lxml\doctestcompare.py -> build\lib.win32-2.7\lxml
copying src\lxml\ElementInclude.py -> build\lib.win32-2.7\lxml
copying src\lxml\pyclasslookup.py -> build\lib.win32-2.7\lxml
copying src\lxml\sax.py -> build\lib.win32-2.7\lxml
copying src\lxml\usedoctest.py -> build\lib.win32-2.7\lxml
copying src\lxml\_elementpath.py -> build\lib.win32-2.7\lxml
copying src\lxml\__init__.py -> build\lib.win32-2.7\lxml
creating build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\__init__.py -> build\lib.win32-2.7\lxml\includes
creating build\lib.win32-2.7\lxml\html
copying src\lxml\html\builder.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html\clean.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html\defs.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html\diff.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html\ElementSoup.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html\formfill.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html\html5parser.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html\soupparser.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html\usedoctest.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html\_diffcommand.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html\_html5builder.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html\_setmixin.py -> build\lib.win32-2.7\lxml\html
copying src\lxml\html\__init__.py -> build\lib.win32-2.7\lxml\html
creating build\lib.win32-2.7\lxml\isoschematron
copying src\lxml\isoschematron\__init__.py -> build\lib.win32-2.7\lxml\isoschematron
copying src\lxml\lxml.etree.h -> build\lib.win32-2.7\lxml
copying src\lxml\lxml.etree_api.h -> build\lib.win32-2.7\lxml
copying src\lxml\includes\c14n.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\config.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\dtdvalid.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\etreepublic.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\htmlparser.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\relaxng.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\schematron.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\tree.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\uri.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\xinclude.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\xmlerror.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\xmlparser.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\xmlschema.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\xpath.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\xslt.pxd -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\etree_defs.h -> build\lib.win32-2.7\lxml\includes
copying src\lxml\includes\lxml-version.h -> build\lib.win32-2.7\lxml\includes
creating build\lib.win32-2.7\lxml\isoschematron\resources
creating build\lib.win32-2.7\lxml\isoschematron\resources\rng
copying src\lxml\isoschematron\resources\rng\iso-schematron.rng -> build\lib.win32-2.7\lxml\isoschematron\resources\rng
creating build\lib.win32-2.7\lxml\isoschematron\resources\xsl
copying src\lxml\isoschematron\resources\xsl\RNG2Schtrn.xsl -> build\lib.win32-2.7\lxml\isoschematron\resources\xsl
copying src\lxml\isoschematron\resources\xsl\XSD2Schtrn.xsl -> build\lib.win32-2.7\lxml\isoschematron\resources\xsl
creating build\lib.win32-2.7\lxml\isoschematron\resources\xsl\iso-schematron-xslt1
copying src\lxml\isoschematron\resources\xsl\iso-schematron-xslt1\iso_abstract_expand.xsl -> build\lib.win32-2.7\lxml\isoschematron\resources\xsl\iso-schematron-xslt1
copying src\lxml\isoschematron\resources\xsl\iso-schematron-xslt1\iso_dsdl_include.xsl -> build\lib.win32-2.7\lxml\isoschematron\resources\xsl\iso-schematron-xslt1
copying src\lxml\isoschematron\resources\xsl\iso-schematron-xslt1\iso_schematron_message.xsl -> build\lib.win32-2.7\lxml\isoschematron\resources\xsl\iso-schematron-xslt1
copying src\lxml\isoschematron\resources\xsl\iso-schematron-xslt1\iso_schematron_skeleton_for_xslt1.xsl -> build\lib.win32-2.7\lxml\isoschematron\resources\xsl\iso-schematron-xslt1
copying src\lxml\isoschematron\resources\xsl\iso-schematron-xslt1\iso_svrl_for_xslt1.xsl -> build\lib.win32-2.7\lxml\isoschematron\resources\xsl\iso-schematron-xslt1
copying src\lxml\isoschematron\resources\xsl\iso-schematron-xslt1\readme.txt -> build\lib.win32-2.7\lxml\isoschematron\resources\xsl\iso-schematron-xslt1
running build_ext
building 'lxml.etree' extension
creating build\temp.win32-2.7
creating build\temp.win32-2.7\Release
creating build\temp.win32-2.7\Release\src
creating build\temp.win32-2.7\Release\src\lxml
C:\Users\lenovo\AppData\Local\Programs\Common\Microsoft\Visual C++ for Python\9.0\VC\Bin\cl.exe /c /nologo /Ox /MD /W3 /GS- /DNDEBUG -Isrc\lxml\includes -Ic:\python27\include -Ic:\python\weixin\PC /Tcsrc\lxml\lxml.etree.c /Fobuild\temp.win32-2.7\Release\src\lxml\lxml.etree.obj -w
cl : Command line warning D9025 : overriding '/W3' with '/w'
lxml.etree.c
src\lxml\includes\etree_defs.h(14) : fatal error C1083: Cannot open include file: 'libxml/xmlversion.h': No such file or directory
Compile failed: command 'C:\\Users\\lenovo\\AppData\\Local\\Programs\\Common\\Microsoft\\Visual C++ for Python\\9.0\\VC\\Bin\\cl.exe' failed with exit status 2
C:\Users\lenovo\AppData\Local\Programs\Common\Microsoft\Visual C++ for Python\9.0\VC\Bin\cl.exe /c /nologo /Ox /MD /W3 /GS- /DNDEBUG -I/usr/include/libxml2 /Tcc:\users\lenovo\appdata\local\temp\xmlXPathInitqngawr.c /Fousers\lenovo\appdata\local\temp\xmlXPathInitqngawr.obj
xmlXPathInitqngawr.c
c:\users\lenovo\appdata\local\temp\xmlXPathInitqngawr.c(1) : fatal error C1083: Cannot open include file: 'libxml/xpath.h': No such file or directory
*********************************************************************************
Could not find function xmlCheckVersion in library libxml2. Is libxml2 installed?
*********************************************************************************
error: command 'C:\\Users\\lenovo\\AppData\\Local\\Programs\\Common\\Microsoft\\Visual C++ for Python\\9.0\\VC\\Bin\\cl.exe' failed with exit status 2
----------------------------------------
```
Command "c:\python\weixin\scripts\python.exe -u -c "import setuptools, tokenize;**file**='c:\users\lenovo\appdata\local\temp\pip-build-nyz5gp\lxml\setup.py';exec(compile(getattr(tokenize, 'open', open)(**file**).read().replace('\r\n', '\n'), **file**, 'exec'))" install --record c:\users\lenovo\appdata\local\temp\pip-g884nz-record\install-record.txt --single-version-externally-managed --compile --install-headers c:\python\weixin\include\site\python2.7\lxml" failed with error code 1 in c:\users\lenovo\appdata\local\temp\pip-build-nyz5gp\lxml\
| closed | 2016-10-09T14:42:53Z | 2016-10-10T01:58:31Z | https://github.com/Urinx/WeixinBot/issues/93 | [] | linglim | 1 |
ShishirPatil/gorilla | api | 930 | [bug] Hosted Gorilla: <Issue> | Exception: Error communicating with OpenAI: HTTPSConnectionPool(host='luigi.millennium.berkeley.edu', port=443): Max retries exceeded with url: /v1/chat/completions/chat/completions (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f1a2ae1d190>: Failed to establish a new connection: [Errno 111] Connection refused'))
Failed model: gorilla-7b-hf-v1, for prompt: I would like to translate 'I feel very good today.' from English to Chinese | open | 2025-03-03T19:30:01Z | 2025-03-03T19:30:01Z | https://github.com/ShishirPatil/gorilla/issues/930 | [
"hosted-gorilla"
] | KateKateKKK | 0 |
piskvorky/gensim | data-science | 2,590 | out of memory issue in PyLDAV visulization | <!--
**IMPORTANT**:
- Use the [Gensim mailing list](https://groups.google.com/forum/#!forum/gensim) to ask general or usage questions. Github issues are only for bug reports.
- Check [Recipes&FAQ](https://github.com/RaRe-Technologies/gensim/wiki/Recipes-&-FAQ) first for common answers.
Github bug reports that do not include relevant information and context will be closed without an answer. Thanks!
-->
#### Problem description
What are you trying to achieve?
Visualization of topic model having 8.5L document and 25L vocab size ang 8gb of memory
What is the expected result?
Create a visualization file.
What are you seeing instead?
We are getting a Memory out of error while programme is preparing a data for pylda vis.
#### Steps/code/corpus to reproduce
Include full tracebacks, logs and datasets if necessary. Please keep the examples minimal ("minimal reproducible example").
```
`C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\past\translation\__init__.py:35: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp
C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\past\translation\__init__.py:35: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp
C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\past\translation\__init__.py:35: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp
C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\past\translation\__init__.py:35: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp
C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\past\translation\__init__.py:35: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp
C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\past\translation\__init__.py:35: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp
C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\past\translation\__init__.py:35: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp
C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\past\translation\__init__.py:35: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp
joblib.externals.loky.process_executor._RemoteTraceback:
"""
Traceback (most recent call last):
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\joblib\externals\loky\process_executor.py", line 418, in _process_worker
r = call_item()
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\joblib\externals\loky\process_executor.py", line 272, in __call__
return self.fn(*self.args, **self.kwargs)
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\joblib\_parallel_backends.py", line 567, in __call__
return self.func(*args, **kwargs)
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\joblib\parallel.py", line 225, in __call__
for func, args, kwargs in self.items]
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\joblib\parallel.py", line 225, in <listcomp>
for func, args, kwargs in self.items]
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pyLDAvis\_prepare.py", line 213, in _find_relevance_chunks
return pd.concat([_find_relevance(log_ttd, log_lift, R, l) for l in lambda_seq])
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pyLDAvis\_prepare.py", line 213, in <listcomp>
return pd.concat([_find_relevance(log_ttd, log_lift, R, l) for l in lambda_seq])
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pyLDAvis\_prepare.py", line 208, in _find_relevance
relevance = lambda_ * log_ttd + (1 - lambda_) * log_lift
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pandas\core\ops\__init__.py", line 1506, in f
return self._combine_const(other, op)
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pandas\core\frame.py", line 5396, in _combine_const
return ops.dispatch_to_series(self, other, func)
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pandas\core\ops\__init__.py", line 596, in dispatch_to_series
new_data = expressions.evaluate(column_op, str_rep, left, right)
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pandas\core\computation\expressions.py", line 220, in evaluate
return _evaluate(op, op_str, a, b, **eval_kwargs)
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pandas\core\computation\expressions.py", line 126, in _evaluate_numexpr
result = _evaluate_standard(op, op_str, a, b)
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pandas\core\computation\expressions.py", line 70, in _evaluate_standard
return op(a, b)
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pandas\core\ops\__init__.py", line 570, in column_op
return {i: func(a.iloc[:, i], b) for i in range(len(a.columns))}
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pandas\core\ops\__init__.py", line 570, in <dictcomp>
return {i: func(a.iloc[:, i], b) for i in range(len(a.columns))}
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pandas\core\ops\roperator.py", line 17, in rmul
return right * left
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pandas\core\series.py", line 810, in __array_ufunc__
self, ufunc, method, *inputs, **kwargs
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pandas\core\ops\__init__.py", line 1743, in maybe_dispatch_ufunc_to_dunder_op
return getattr(self, name, not_implemented)(inputs[0])
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pandas\core\ops\__init__.py", line 1048, in wrapper
result = na_op(lvalues, rvalues)
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pandas\core\ops\__init__.py", line 968, in na_op
result = expressions.evaluate(op, str_rep, x, y, **eval_kwargs)
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pandas\core\computation\expressions.py", line 220, in evaluate
return _evaluate(op, op_str, a, b, **eval_kwargs)
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pandas\core\computation\expressions.py", line 126, in _evaluate_numexpr
result = _evaluate_standard(op, op_str, a, b)
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pandas\core\computation\expressions.py", line 70, in _evaluate_standard
return op(a, b)
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pandas\core\ops\roperator.py", line 17, in rmul
return right * left
numpy.core._exceptions.MemoryError: Unable to allocate array with shape (100,) and data type float32
"""
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "D:/Projects/docs_handler/lsi_experiment.py", line 47, in <module>
visulize_topic_model(model,corpus,dictionary)
File "D:/Projects/docs_handler/lsi_experiment.py", line 29, in visulize_topic_model
viz = pyLDAvis.gensim.prepare(topic_model=model,corpus=corpus,dictionary=dictionary)
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pyLDAvis\gensim.py", line 119, in prepare
return vis_prepare(**opts)
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pyLDAvis\_prepare.py", line 398, in prepare
topic_info = _topic_info(topic_term_dists, topic_proportion, term_frequency, term_topic_freq, vocab, lambda_step, R, n_jobs)
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pyLDAvis\_prepare.py", line 255, in _topic_info
for ls in _job_chunks(lambda_seq, n_jobs)))
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\joblib\parallel.py", line 934, in __call__
self.retrieve()
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\joblib\parallel.py", line 833, in retrieve
self._output.extend(job.get(timeout=self.timeout))
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\joblib\_parallel_backends.py", line 521, in wrap_future_result
return future.result(timeout=timeout)
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pattern\text\en\..\..\..\..\concurrent\futures\_base.py", line 432, in result
return self.__get_result()
File "C:\Users\koradg\AppData\Local\Programs\Python\Python36\lib\site-packages\pattern\text\en\..\..\..\..\concurrent\futures\_base.py", line 384, in __get_result
raise self._exception
numpy.core._exceptions.MemoryError: Unable to allocate array with shape (100,) and data type float32
Process finished with exit code 1
`
```
#### Versions
Please provide the output of:
```python
import platform; print(platform.platform())
import sys; print("Python", sys.version)
import numpy; print("NumPy", numpy.__version__)
import scipy; print("SciPy", scipy.__version__)
import gensim; print("gensim", gensim.__version__)
from gensim.models import word2vec;print("FAST_VERSION", word2vec.FAST_VERSION)
```
Windows-10-10.0.17763-SP0
Python 3.6.5 (v3.6.5:f59c0932b4, Mar 28 2018, 17:00:18) [MSC v.1900 64 bit (AMD64)]
NumPy 1.17.0
SciPy 1.3.0
gensim 3.8.0
FAST_VERSION 0
| closed | 2019-09-03T04:37:56Z | 2019-10-08T08:14:52Z | https://github.com/piskvorky/gensim/issues/2590 | [
"need info",
"stale"
] | gauravkoradiya | 4 |
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