URL(s) with the issue:

https://github.com/tensorflow/examples/tree/master/lite/examples/object_detection/raspberry_pi

Description of issue (what needs changing):

Near the bottom of the instruction on speeding up inference it reads
python3 classify_picamera.py \

Based on the files in that example folder should that instead read
python3 detect_picamera.py \

Clear d

The following do not yet have any pytests:

• boolean_algebra
• digital_image_processing
• divide_and_conquer
• hashes
• linear_algebra #1124
• networking_flow #1126
• traversals
• file_transfer_protocol # This might be difficult
• machine_learning
• neural_network

For ease of review, please only modify one directory per pull request.

It says in the documentation (the last section - "Working with Virtual Environments"):

For Python 3 add the following lines to the top of your .wsgi file:

activate_this = '/path/to/env/bin/activate_this.py'
with open(activate_this) as file_:
    exec(file_.read(), dict(__file__=activate_this))

However `activate_this.p

Brew is listed as the recommended way of installing httpie on macOS. However, it doesn't work with auth plugins.

For example, if you pip3 install requests-hawk and then run http --help hawk will not show as an auth type. If you pip3 install httpie-oauth it will install httpie via pip as a dependency and overwrite the brew installed link in /usr/local/bin/http and now all the plugins wil

tldr; in multi-process environment (Celery) sessions might lead to request/responses being mixed up.

It is unsafe to use Session in a multi-process environment - if the fork happens after Session initialisation the underlying connection pool will be shared across both processes, leading to potentially dangerous and hard to debug issues.

I'm not sure what should happen - whather a code change

SUMMARY

I was working on an example of what not to do—namely, using the yum module instead of package for something meant to be platform agnostic... but then I realized my example (using the yum module on Debian) actually worked.

When I ran the yum task with -vvvv I found:

Running apt as the backend for the yum action plugin
Using module file /usr/local/lib/pytho

We recently merged https://github.com/NicolasHug/scikit-learn/blob/master/examples/release_highlights/plot_release_highlights_0_22_0.py to summarise the highlights of 0.22, to be released in early November.

More release highlights, briefly demonstrating the new thing in action, belong in that example doc:

• Permutation based feature importance
• HistGradientBoostingClassifier with m

I want to save images on a remote server via (FTP?). Is this possible with scrapy?
(I know about S3 or Google but i mean in a custom FTP server).

Context

We would like to add the following two APIs to the C++ frontend:

• torch::nn::TripletMarginLoss , which is the equivalent of Python API torch.nn.TripletMarginLoss.
• torch::nn::functional::triplet_margin_loss, which is the equivalent of Python API torch.nn.functional.triplet_margin_loss.

Steps

• Add torch::nn::TripletMarginLossOptions to `torch/csrc/api/i

One case of this is described at https://community.letsencrypt.org/t/noinstallationerror-cannot-find-apache-executable-apache2ctl/97980. I think the error message here and for other common Apache CLI flags could do a better job of telling the user how to work around the problem.

The code block at this location:

https://dev.pandas.io/docs/user_guide/reshaping.html#pivoting-with-single-aggregations

is not rendered correctly, as we accidentally try to render it as a note. The .. note:: should be replaced with .. code-block::

给定一个原区间[x, y] (y>=x) 和 N个无序的目标区间[x1, y1],[x2, y2],[x3, y3] ... [xn, yn] 判断原区间是否在目标区间内（即\bigcup_{i=1}^{n}[x_i, y_i]是否成立）

例如给定原区间[1,6]和无序的目标区间[2, 3] , [1, 2], [3, 9]. 即可认为区间[1, 6]在[2, 3] , [1, 2], [3, 9]内， 如图所示：