workers | Support cross-domain request Convert HTTP | Key Value Database library
kandi X-RAY | workers Summary
kandi X-RAY | workers Summary
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Lines of Code : 66License : Non-SPDX (Apache License 2.0)
Copydef _initialize_local(self, cluster_resolver, devices=None):
"""Initializes the object for local training."""
self._is_chief = True
self._num_workers = 1
if ops.executing_eagerly_outside_functions():
try:
context.contex def get_workers_list(cluster_resolver):
"""Returns a comma separated list of TPU worker host:port pairs.
Gets cluster_spec from cluster_resolver. Use the worker's task indices to
obtain and return a list of host:port pairs.
Args:
cluste def _multi_worker_concat(v, strategy):
"""Order PerReplica objects for CollectiveAllReduceStrategy and concat."""
replicas = strategy.gather(v, axis=0)
# v might not have the same shape on different replicas
if _is_per_replica_instance(v):
Community Discussions
Trending Discussions on workers
QUESTION
I am writing a program in python to have a user input multiple websites then request and scrape those websites for their titles and output it. However, when the program surpasses 8 websites the program crashes every time. I am not sure if it is a memory problem, but I have been looking all over and can't find any one who has had the same problem. The code is below (I added 9 lists so all you have to do is copy and paste the code to see the issue).
...ANSWER
Answered 2021-Jun-15 at 19:45To avoid the page from crashing, add the user-agent header to the headers= parameter in requests.get(), otherwise, the page thinks that your a bot and will block you.
QUESTION
I have a generator object, that loads quite big amount of data and hogs the I/O of the system. The data is too big to fit into memory all at once, hence the use of generator. And I have a consumer that all of the CPU to process the data yielded by generator. It does not consume much of other resources. Is it possible to interleave these tasks using threads?
For example I'd guess it is possible to run the simplified code below in 11 seconds.
...ANSWER
Answered 2021-Jun-15 at 16:02Send your data to separate processes. I used concurrent.futures because I like the simple interface.
This runs in about 11 seconds on my computer.
QUESTION
As is known, we can't access the dom element from the workers. When I create AudioContext:
...ANSWER
Answered 2021-Jun-15 at 14:36Not yet no. Here is a specs issue discussing this very matter, and it is something a lot of actors would like to see, so there is hope it comes, one day.
Note that there is an AudioWorklet API available, which will create its own Worklet (which also works in a parallel thread), but you still need to instantiate it from the UI thread, and you don't have access to everything that can be done in an AudioContext. Still, it may suit your needs.
Also, note that it might be possible to do the computing you have to do in a Worker already, by transferring ArrayBuffers from your UI thread to the Worker's one, or by using SharedArrayBuffers.
QUESTION
My data set comes from an excel file set up by non-data orientated co-workers. My data is sensitive, so I cannot share the data set, but I will try to make an example so it's easier to see what I'm talking about. I have a unique identifier column. My problem is with the date columns. I have multiple date columns. When imported into R, some of the columns imported as dates, and some of them imported as excel dates. then some of the cells in the columns have a string of dates (in character type). not all the strings are the same size. Some have a list of 2, some a list 7.
I'm trying to Tidy my data. My thoughts were to put all the collection dates in one column. Here is where I'm stuck. I can use pivot_longer() bc not all the columns are the same type. I can't convert the excel dates into R dates w/out getting rid of the list of strings. And I can' get rid of the list of strings, bc I'm running into the Error: Incompatible lengths. I think my logic flow is wrong and any advice to point me in the right direction would be helpful. I can look up coding after i get my flow right.
What I have:
...ANSWER
Answered 2021-Jun-14 at 19:04Since you didn't post real data, we have to make some assumptions on the structure of your dataset.
DataAssuming, your data looks like
QUESTION
Assuming I have a cluster with two worker nodes and from these two workers, I have 10 executors. How much memory will be used up in my cluster if I choose to broadcast a 1gb Map?
Will it be 1gb per worker so 2gb in total? Or will it be 1gb per executor so 10gb in total?
Apologies for the simple question, but for me, a number of articles written about broadcast variables aren’t 100% clear on this issue.
...ANSWER
Answered 2021-Jun-14 at 17:17Executers are the entities that perform the actual work. Each executor is its own JVM process with allotted memory.
(As described here: http://spark.apache.org/docs/latest/cluster-overview.html)
The broadcast is materialized at the executer level so in the above example- 10GB.
QUESTION
I'm currently working on a seminar paper on nlp, summarization of sourcecode function documentation. I've therefore created my own dataset with ca. 64000 samples (37453 is the size of the training dataset) and I want to fine tune the BART model. I use for this the package simpletransformers which is based on the huggingface package. My dataset is a pandas dataframe. An example of my dataset:
My code:
...ANSWER
Answered 2021-Jun-08 at 08:27While I do not know how to deal with this problem directly, I had a somewhat similar issue(and solved). The difference is:
- I use fairseq
- I can run my code on google colab with 1 GPU
- Got
RuntimeError: unable to mmap 280 bytes from file : Cannot allocate memory (12)immediately when I tried to run it on multiple GPUs.
From the other people's code, I found that he uses python -m torch.distributed.launch -- ... to run fairseq-train, and I added it to my bash script and the RuntimeError is gone and training is going.
So I guess if you can run with 21000 samples, you may use torch.distributed to make whole data into small batches and distribute them to several workers.
QUESTION
I run my model in CPLEX using Constraint Programming, my model managed to run with 8 workers. But after 3 hours, it still has no solution so I have to stop the model.
Is there something wrong with my model? I tried to run the model with only a few sample in the Excel file but it still failed to give me a solution after hours of run time. Thank you so much in advance!
My mod. file:
...ANSWER
Answered 2021-Jun-14 at 07:15If you turn scale into
QUESTION
I originally posted this question as an issue on the GitHub project for the AWS Load Balancer Controller here: https://github.com/kubernetes-sigs/aws-load-balancer-controller/issues/2069.
I'm seeing some odd behavior that I can't trace or explain when trying to get the loadBalacnerDnsName from an ALB created by the controller. I'm using v2.2.0 of the AWS Load Balancer Controller in a CDK project. The ingress that I deploy triggers the provisioning of an ALB, and that ALB can connect to my K8s workloads running in EKS.
Here's my problem: I'm trying to automate the creation of a Route53 A Record that points to the loadBalancerDnsName of the load balancer, but the loadBalancerDnsName that I get in my CDK script is not the same as the loadBalancerDnsName that shows up in the AWS console once my stack has finished deploying. The value in the console is correct and I can get a response from that URL. My CDK script outputs the value of the DnsName as a CfnOutput value, but that URL does not point to anything.
In CDK, I have tried to use KubernetesObjectValue to get the DNS name from the load balancer. This isn't working (see this related issue: https://github.com/aws/aws-cdk/issues/14933), so I'm trying to lookup the Load Balancer with CDK's .fromLookup and using a tag that I added through my ingress annotation:
ANSWER
Answered 2021-Jun-13 at 20:23I think that the answer is to use external-dns.
ExternalDNS allows you to control DNS records dynamically via Kubernetes resources in a DNS provider-agnostic way.
QUESTION
I want to share a list to append output from parallel threads, started by process_map from tqdm. (The reason why I want to use process_map is the nice progress indicator and the max_workers= option.)
I have tried to use from multiprocessing import Manager to create the shared list, but I am doing something wrong here: My code prints an empty shared_list, but it should print a list with 20 numbers, correct order is not important.
Any help would be greatly appreciated, thank you in advance!
...ANSWER
Answered 2021-Jun-13 at 19:47You didn't specify what platform you are running under (you are supposed to tag your question with your platform whenever you tag a question with multiprocessing), but it appears you are running under a platform that uses spawn to create new processes (such as Windows). This means that when a new process is launched, an empty address space is created, a new Python interpreter is launched and the source is re-executed from the top.
So although you have in the block that begins if __name__ == '__main__': assigned to shared_list a managed list, each process in the pool that is created will be executing shared_list = [] clobbering your initial assignment.
You can pass shared_list as the first argument to your worker function:
QUESTION
I got an error for Build Project, Debug & Run
...ANSWER
Answered 2021-Jun-13 at 06:06Latest Version of OpenCV need to install.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install workers
Edit index.js and wrangler.toml (configuration key)
wrangler config configure mailbox and key
wrangler build build
wrangler publish release
Detailed documentation: https://developers.cloudflare.com/workers/quickstart
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