Data Science

Describe the issue linked to the documentation

Documentation should be changed to reflect that one-vs-rest is possible.

x = np.array([0,1,2,3,4,5,3,3,5,5,5,7,7,2])
x = x.reshape(-1,1)#this has 1 feature, therefore reshaping properly

y = [0,0,0,1,0,2,1,1,2,2,2,3,3,0] #note: y has multiple classes.


model = SVC(gamma = "auto", decision_function_shape="ovr")
model.fit(x,y)
p

The Mixed Time-Series chart type allows for configuring the title of the primary and the secondary y-axis.
However, while only the title of the primary axis is shown next to the axis, the title of the secondary one is placed at the upper end of the axis where it gets hidden by bar values and zoom controls.

How to reproduce the bug

1. Create a mixed time-series chart
2. Configure axi

Search before asking

• I had searched in the issues and found no similar feature requirement.

Description

the ci/travis folder is confusing. The ci/README.md also mentions Travis, could be interpreted in all sorts of ways. maybe time to change that to something more agnostic? After all, we're not using Travis anymore.

Use case

Summary

Aesthetically trivial, yet I've spotted a discrepancy with font sizes in our tooltip (front-end + back-end screenshots below).
I believe sections #1 and #2 should have the same font size?

![image](https://user-images.githubusercontent.com/27242399/139825179-4d62e3

Proposal

We should have a dedicated page to track deprecations, breaking changes and optional alternatives in our documentation.
Similar to this.

Motivation

Describe your context
Please provide us your environment, so we can easily reproduce the issue.

• replace the result of pip list | grep dash below

dash                      2.0.0
dash-bootstrap-components 1.0.0

• if frontend related, tell us your Browser, Version and OS

  • OS: [e.g. iOS] Windows
  • Browser [e.g. chrome, safari]: Chrome 96.0x, Edge 96.0x, Firefox

Python 3.10 added suggestions for AttributeError and NameError in the error messages. It seems the suggestions are not stored in the exception object but calculated when Error is displayed. There is a note that that this won't work with IPython but it will be good to see if it's feasible. Opening an issue for discussion.

https://bugs.python.org/issue38530
https://docs.python.org/3/whatsnew/3.

Summary

We have clf/clear and cla/clear as pairs of related but not quite the same methods an the Figure and Axes classes. The clf/clear pair has mostly been consolidated (and is fully in #22735 ), but the cla case is more work because we bunch of Axes subclasses in the code base. Long term I think every Axes subclass:

• clear and cla should be identical
• every subclass shoul

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

Although the results look nice and ideal in all TensorFlow plots and are consistent across all frameworks, there is a small difference (more of a consistency issue). The result training loss/accuracy plots look like they are sampling on a lesser number of points. It looks more straight and smooth and less wiggly as compared to PyTorch or MXNet.

It can be clearly seen in chapter 6([CNN Lenet](ht

https://github.com/microsoft/nni/blob/8d5f643c64580bb26a7b10a3c4c9accf617f65b1/nni/compression/pytorch/speedup/jit_translate.py#L382

While trying to speedup my single shot detector, the following error comes up. Any way to fix this,

/usr/local/lib/python3.8/dist-packages/nni/compression/pytorch/speedup/jit_translate.py in forward(self, *args)
    363 
    364         def forward(self, *

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.