We should be using pkg_resources (or importlib.resources if our min Python version is 3.7) instead of uses of __file__.

$ get grep '__file__' sklearn/
sklearn/__check_build/__init__.py:    local_dir = os.path.split(__file__)[0]
sklearn/datasets/_base.py:    module_path = dirname(__file__)
sklearn/datasets/_base.py:    module_path = dirname(__file__)
sklearn/datasets/_base.py:    

Screenshot

Description

chart 3 dot menu is behind the chart title panel in chart maximize mode

Trying out a simple example using TuneSearchCV with LGBMClassifier and it fails on start.

Environment:

Python 3.8.3
tune-sklearn 0.3.0
ray 1.3.0
macos mojave 10.14.6

Code:

from ray.tune.sklearn import TuneSearchCV

from lightgbm import LGBMClassifier

lgmb_param_dists = dict(

                boosting_type=['gbdt','dart','rf'],
                num_leaves=(10,500),
 

Summary

The grayish background oval indicating a selected st.radio label has too much padding on the right hand side by a few pixels. Here's an example:

(Notice how the background rounded rectangle extends further to the right past "Notion" than it does to the left of the sel

The docs for IPython.core.interactiveshell.InteractiveShell.set_custom_exc have horribly mangled a warning message into a list of arguments. I can't work out at a glance why this is happening; it might be a sphinx.ext.napoleon bug, or a sphi

In recent versions (can't say from exactly when), there seems to be an off-by-one error in dcc.DatePickerRange. I set max_date_allowed = datetime.today().date(), but in the calendar, yesterday is the maximum date allowed. I see it in my apps, and it is also present in the first example on the DatePickerRange documentation page.

E

🐛 Bug

If the Trainer's profiler parameter is set to "pytorch" and the Trainer's logger is an instance of LoggerCollection, the profiler fails to write to a local file (with a warning).

The path for said file is derived from [this property](https://github.com/PyTorchLightning/pytorch-lightning/blob/28afc7a10d9f9c1160935fb5c81a1a8c0492b392/pytorch_lightning/trainer/properties.py#L22

Problem

I would like to be able to modify the alpha of both the line and marker in a legend as an extension of this example: https://matplotlib.org/stable/gallery/event_handling/legend_picking.html

However, currently the only way to access the marker in in the legend in order to set it's alpha value is via the private legline._legmarker attribute.
https://github.com/matplotlib/matplotli

In gensim/models/fasttext.py:

    model = FastText(
        vector_size=m.dim,
        vector_size=m.dim,
        window=m.ws,
        window=m.ws,
        epochs=m.epoch,
        epochs=m.epoch,
        negative=m.neg,
        negative=m.neg,
        # FIXME: these next 2 lines read in unsupported FB FT modes (loss=3 softmax or loss=4 onevsall,
        # or model=3 supervi

Is your feature request related to a problem? Please describe.
I typically used compressed datasets (e.g. gzipped) to save disk space. This works fine with AllenNLP during training because I can write my dataset reader to load the compressed data. However, the predict command opens the file and reads lines for the Predictor. This fails when it tries to load data from my compressed files.