(e.g. for links and images), because some of these examples are now being rendered in the docs.

Added by @fchollet in requests for contributions.

Estimator has too many undocumented attributes:

• test_fit_docstring_attributes[OrthogonalMatchingPursuit-OrthogonalMatchingPursuit]
• test_fit_docstring_attributes[Lasso-Lasso]
• test_fit_docstring_attributes[LarsCV-LarsCV]
• test_fit_docstring_attributes[Birch-Birch]

Screenshot

Description

Unnecessary scrollbar

Design input

Please remove them.

cc @yousoph

@richardliaw could we take in the data path as a command line arg for all these examples that defaults to "~/data"? That way the user can specify their own data paths without having to modify the code.

Originally posted by @amogkam in ray-project/ray#15260 (comment)

Steps to reproduce

run %autocall random

Expected result

ERROR:root:Valid modes: (0->Off, 1->Smart, 2->Full

Observed result

ValueError was raised due to parsing the argument "random" as an integer.

System info

Manjaro Linux, Python 3.9.1, IPython 7.22.0.

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

Summary

When import streamlit and supervisely_lib together in a project there occurs a TypeError.

Steps to reproduce

Code snippet:

import streamlit as st
import supervisely_lib as sly

If applicable, please provide the steps we should take to reproduce the bug:

1. run the code with streamlit run ...
2. see error/traceback when you open the streamlit page

🚀 Feature

Motivation

This should work. Add a test to make sure this works reliably in multi-gpu setting.

class MyModel(pl.LightningModule):
    def on_training_epoch_start():
        # calling trainer.predict inside trainer.fit routine.
        # is this okay?
        pred_outputs = self.trainer.pre

Not a high-priority at all, but it'd be more sensible for such a tutorial/testing utility corpus to be implemented elsewhere - maybe under /test/ or some other data- or doc- related module – rather than in gensim.models.word2vec.

Originally posted by @gojomo in RaRe-Technologies/gensim#2939 (comment)

I'm using mxnet to do some work, but there is nothing when I search the mxnet trial and example.