Data Science

Background / Objective

Docstrings in Python are string literals that occur as the first statement in a module, function, class, or method definition.

These are some of the characteristics of a docstring:

• Triple quotes are used to encompass the docstring text.
• There is no blank line before or after the docstring.

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

What happened + What you expected to happen

The shim tune.create_scheduler() does not properly parse the keyword parameters passed in a dictionary for the pb2 scheduler. For this call

pb2_parm_dict = {"time_attr": "time_total_s", "metric": "metric_score", "mode": "min",
                 "hyperparam_bounds": {"param1": [0, 1]}}

pb2_scheduler = create_scheduler("pb2", **pb2_pa

Problem

See #3856 . Developer would like the ability to configure whether the developer menu or viewer menu is displayed while they are developing on cloud IDEs like Gitpod or Github Codespaces

Solution

Create a config option

showDeveloperMenu: true | false | auto

where

• true: always shows the developer menu locally and while deployed
• false: always sho

🐛 Bug

Trainer profilers are typehinted with the deprecated BaseProfiler instead of Profiler. This means that you cannot use class_path initialization of profilers with LightningCLI.

Error message:

  - "pytorch_lightning.profiler.PyTorchProfiler" is not a subclass of <class 'pytorch_lightning.profiler.base.BaseProfiler'>
  - Expected a <class 'str'> but got "{'class_path':

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

Bug summary

When the build gets to https://github.com/matplotlib/matplotlib/blob/main/src/_tkagg.cpp#L262-L273 on Cygwin, the build fails with a few goto crosses initialization warnings, which are easy to fix, and two error: ‘PyErr_SetFromWindowsErr’ was not declared in this scope, which are less easy to fix.

Code for reproduction

pip install matplotlib

https://ipython.readthedocs.io/en/stable/api/generated/IPython.lib.demo.html

The example of demo.py uses print statements instead of print function, which does not work in python 3.x

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

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

Describe the issue:
During computing Channel Dependencies reshape_break_channel_dependency does following code to ensure that the number of input channels equals the number of output channels:

in_shape = op_node.auxiliary['in_shape']
out_shape = op_node.auxiliary['out_shape']
in_channel = in_shape[1]
out_channel = out_shape[1]
return in_channel != out_channel

This is correct

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.

• Base README.md
• Quizzes
• Introduction base README
  • Defining Data Science README
  • Defining Data Science assignment
  • Ethics README
  • Ethics assignment
  • Defining Data README
  • Defining Data assignment
  • Stats and Probability README
  • Stats and Probability assignment
• Working with Data base README
  • Rel

We support toml as params file. There are a few issues with our current toml parsing:

1. We use toml library, which is not toml 1.0 standard compatible. Also, the library is not being actively maintained.
2. toml dumping does not preserve existing formatting.
3. iterative/dvc#6402

We can try migrating to tomli (which