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kandi X-RAY | distributions Summary
kandi X-RAY | distributions Summary
Snaps are containerized software packages designed to work across cloud, desktop, and IoT devices. They work natively on most popular Linux distributions and feature automatic transactional updates. The NodeSource-managed Node.js snap contains the Node.js runtime, along with the two most widely-used package managers, npm and Yarn. They are delivered from the snapcraft store and are automatically built and pushed for each supported Node.js release line. Generally you will have a new version of Node.js automatically running on your computer the same day it is released on nodejs.org. The Node.js snap can currently be installed on Arch Linux, Debian, Fedora, Linux Mint, Manjaro, OpenEmbedded/Yocto, OpernWrt, Solus, Ubuntu and many other distributions built on top these. NodeSource has not tested the Node.js snap on all of these distributions and feedback is welcome in this repository if you run into problems.
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Lines of Code : 17
License : No License
Copyimport numpy as np
from imgaug import augmenters as iaa
from imgaug import parameters as iap
images = np.random.randint(0, 255, (16, 128, 128, 3), dtype=np.uint8)
# Blur by a value sigma which is sampled from a uniform distribution
# of range 10.1 def _kl_dirichlet_dirichlet(d1, d2, name=None):
"""Batchwise KL divergence KL(d1 || d2) with d1 and d2 Dirichlet.
Args:
d1: instance of a Dirichlet distribution object.
d2: instance of a Dirichlet distribution object.
name: (optional def kl_divergence(distribution_a, distribution_b,
allow_nan_stats=True, name=None):
"""Get the KL-divergence KL(distribution_a || distribution_b).
If there is no KL method registered specifically for `type(distribution_a)`
an def should_execute_combination(self, kwargs):
distributions = [
v for v in kwargs.values() if isinstance(v, NamedDistribution)
]
required_gpus = kwargs.get("required_gpus", 0)
required_physical_gpus = kwargs.get("required_phys Community Discussions
Trending Discussions on distributions
QUESTION
I want to create a vector of random integers with values between 1 and 10, with a gradual increase in the likelihood of higher numbers appearing as I progress through the vector. But, I still want the values to be mixed together, i.e., I'm trying to avoid 1,1,1,1,2,2,2,3... etc
I have so far managed the following, which works, but surely there is a more elegant way of achieving this?
...ANSWER
Answered 2022-Apr-05 at 13:04You don't say anything about the distribution you actually want, but if a binomial distribution is acceptable:
QUESTION
I have a project which was running well yesterday, but today I find this problem:
Could not resolve all files for configuration ':app:debugRuntimeClasspath'. Could not resolve com.google.android.gms:play-services-location:16.+. Required by: project :app > project :location > Failed to list versions for com.google.android.gms:play-services-location. > Unable to load Maven meta-data from https://google.bintray.com/exoplayer/com/google/android/gms/play-services-location/maven-metadata.xml. > Could not get resource 'https://google.bintray.com/exoplayer/com/google/android/gms/play-services-location/maven-metadata.xml'. > Could not GET 'https://google.bintray.com/exoplayer/com/google/android/gms/play-services-location/maven-metadata.xml'. Received status code 502 from server: Bad Gateway
acutely I'm using classpath 'com.android.tools.build:gradle:4.1.0'with distributionUrl=https://services.gradle.org/distributions/gradle-6.5-bin.zip
I have followed this question
and I upgraded 'com.android.tools.build:gradle:4.1.0' to classpath 'com.android.tools.build:gradle:4.2.0' then I changed distributionUrl=https://services.gradle.org/distributions/gradle-6.5-bin.zip to distributionUrl=https\://services.gradle.org/distributions/gradle-6.7.1-all.zip but I still got the error.
my android/build.gradle:
...ANSWER
Answered 2021-Dec-01 at 09:09It looks like a temporary issue, the server with these libraries is down. I have the same problem now with Room:
QUESTION
I'm learning about policy gradients and I'm having hard time understanding how does the gradient passes through a random operation. From here: It is not possible to directly backpropagate through random samples. However, there are two main methods for creating surrogate functions that can be backpropagated through.
They have an example of the score function:
ANSWER
Answered 2021-Nov-30 at 05:48It is indeed true that sampling is not a differentiable operation per se. However, there exist two (broad) ways to mitigate this - [1] The REINFORCE way and [2] The reparameterization way. Since your example is related to [1], I will stick my answer to REINFORCE.
What REINFORCE does is it entirely gets rid of sampling operation in the computation graph. However, the sampling operation remains outside the graph. So, your statement
.. how does the gradient passes through a random operation ..
isn't correct. It does not pass through any random operation. Let's see your example
QUESTION
I'm trying to build a project in my M1,
but I got this error when I run npx react-native run-android
ANSWER
Answered 2021-Sep-02 at 23:03The error is being caused because one of your dependencies is internally using WorkManager 2.7.0-beta01 that was released today (which needs API 31). In my case it was CheckAarMetadata.kt.
You can fix it by forcing Gradle to use an older version of Work Manager for the transitive dependency that works with API 30. In your build.gradle file add:
QUESTION
It was working fine before I have done nothing, no packages update, no gradle update no nothing just created new build and this error occurs. but for some team members the error occur after gradle sync.
The issue is that build is generating successfully without any error but when opens the app it suddenly gets crash (in both debug and release mode)
Error
...ANSWER
Answered 2022-Feb-25 at 23:22We have fixed the issue by replacing
QUESTION
ANSWER
Answered 2022-Feb-10 at 22:51I was able to resolve the problem. The root of the problem was the missing library libopenblas64. This could be due to a faulty Julia installation. Here is what I have done.
First, open the Julia command line and execute the following two commands.
QUESTION
The figure below is a conceptual diagram used by Michael Clark, https://m-clark.github.io/docs/lord/index.html to explain Lord's Paradox and related phenomena in regression.
My question is framed in this context and using ggplot2 but it is broader in terms of geometry & graphing.
I would like to reproduce figures like this, but using actual data. I need to know:
- how to draw a new axis at the origin, with a -45 degree angle, corresponding to values of
y-x - how to draw little normal distributions or density diagrams, or other representations of the values
y-xprojected onto this axis.
My minimal base example uses ggplot2,
ANSWER
Answered 2022-Feb-06 at 17:04Fun question! I haven't encountered it yet, but there might be a package to help do this automatically. Here's a manual approach using two hacks:
- the
clip = "off"parameter of thecoord_*functions, to allow us to add annotations outside the plot area. - building a density plot, extracting its coordinates, and then rotating and translating those.
First, we can make a density plot of the change from initial to final, seeing a left skewed distribution:
QUESTION
I have a bunch of Cloudfront distributions scattered across a number of AWS accounts. I'd like to get the Usage Reports for all Cloudfront distros across all AWS accounts.
Now, I have the change-account bit already automated, but I'm not sure how to get the CSV report via the AWS CLI.
I know I can do some ClickOps and download the report via the Cloudfront Console, like here:
but I can't find the command to get the report with the AWS CLI.
I know I can get the Cloudfront metrics via the Cloudwatch API but the documentation doesn't mention the API endpoint I should be querying.
Also, there's aws cloudwatch get-metric-statistics, but I'm not sure how to use that to download the Cloudfront Usage CSV Report.
Question: How can I get the Cloudfront Usage Report for all distributions in an AWS account using the AWS CLI?
...ANSWER
Answered 2022-Jan-31 at 10:07You'll need to use Cost-Explorer API for that.
QUESTION
I am currently having issue with the implementation of the Metropolis-Hastings algorithm.
I am trying to use the algorithm to calculate integrals of the form
In using this algorithm, we can obtain a long chain of configurations ( in this case, each configuration is just a single numbers) such that in the tail-end of the chain the probability of having a particular configuration follows (or rather tends to) a gaussian distribution.
My code seems to be messing up with obtaining the said gaussian distributions. There is a strange dependence on the transition probablity (the probablity of picking a new candidate configuration depending on the previous configuration in the chain). However, if this transition probability is symmetric, there should be no dependence on this function at all (it only affects speed at which phase space [space of potential configurations] is explored and how quickly the chain converges to the desired distribution)!
In my case I am using a normal distribution transition function (which satisfies the need to be symmetric), with width d. For each d I use I do indeed get a gaussian distribution however the standard deviation, sigma, depends on my choice of d. The resulting gaussian should have a sigma of roughly 0.701 but I find that the value I actually get depends on the parameter d, when it shouldn't.
I am not sure where the error in this code is, any help would be greatly appreciated!
...ANSWER
Answered 2022-Feb-02 at 20:28You need to save x even when it doesn't change. Otherwise the center values are under-counted, and more so as d increases, which increases the variance.
QUESTION
Is there any way to declare in Puppet's language that packages in an array should installed in the order they are given in the array?
I want to automate the installation of CUDA, which requires nvidia-driver-latest-dkms, cuda and cuda-drivers (on RHEL7 as an example) to be installed in that order. I do not want to hard-code the array of packages, because I need to support different distributions, which require different packages. Therefore, an array holding the packages provided via Hiera seemed to be a good idea.
My first solution was ensure_packages($packages_parameter_filled_via_hiera), which stopped working recently (probably due to changes in NVIDIA's packages). The problem seems to be that this code installs the packages in a random order, and you cannot install nvidia-driver-latest-dkms (any more) if any of the other packages is already installed.
My next approach,
...ANSWER
Answered 2022-Feb-01 at 16:01Yes, this is actually possible with a "wrapper" defined resource type:
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