primordic/IssueDupesLite huggingface dataset:
Repository: aws/serverless-application-model

Issue #248: Support API Gateway Logging Metrics, Usage Plans, EndpointConfiguration, and CORS
Created: 2018-01-08T19:55:21Z
Parent Tracking Issue for Logging, Usage Plans, CORS etc on API resources (Implicit and Explicit). As part of this, we will move to a model where all API features will be supported in both Implicit & Explicit definitions consistently.

 Logging
 Usage Plans queued for v1.21.0
 Custom Authorizers (AWS::ApiGateway::Authorizer and AWS Cognito) (#49) (#512)
 AWS_IAM
 Custom Domains v1.20.0
 ACM
 Base Path Mapping
 Regional Endpoints

For deeper details on the different issues, see the appropriate issue that is referenced below.

Duplicate issue #130: Is there any way to define the API Gateway cache TTL?
Created: 2017-05-09T07:36:11Z
In the resource type AWS::Serverless::Api I'm able to enable the API Gateway caching using
CacheClusterEnabled: true
CacheClusterSize: "0.5"
I can't see any possibility to set the cache TTL anywhere - is there any way to do it? Unfortunately the cache is not working without that value and setting it manually is not an option.
Thanks in advance

Closing comment (2018-01-08T20:23:59Z): We created a parent task to track this. Please see #248 for updates.
Closing as duplicate of #248
Repository: aws/serverless-application-model

Issue #91: Mappings in template do not maintain quotes during package step
Created: 2017-02-14T19:55:07Z
Hello, using aws cloudformation package with the following simple snippet results in the loss of quotes which causes a ChangeSet to remain in CREATE_IN_PROGRESS indefinitely in the proper scenerio.
Mappings:
  '1234567890':
    kmskeys:
      'dev': 'arn:aws:kms:us-east-1:1234567890:key/1234567890-abcdefg-1234-1234'
      'test': 'arn:aws:kms:us-east-1:1234567890:key/1234567890-abcdefg-1234-12345'
after the aws cloudformation package step:
Mappings:
  1234567890:
    kmskeys:
      dev: arn:aws:kms:us-east-1:1234567890:key/1234567890-abcdefg-1234-1234
      test: arn:aws:kms:us-east-1:1234567890:key/1234567890-abcdefg-1234-12345
This is a problem because when using the !Ref "AWS::AccountID" function, a string is returned so it will never match the mapping - if you are mapping per AccountID.
Per the docs, if a Mapping is not used, it is an invalid changeset
So, I'm curious if this is a bug. I feel like I should be able to create a Mapping with Account ID's and then reference the AccountID later in a later block and it is currently not possible with aws cloudformation package. Thoughts?
$ aws --version
aws-cli/1.11.47 Python/2.7.10 Darwin/16.0.0 botocore/1.5.10

Duplicate issue #94: Stack Failure in 'Method response status' with inline swagger definition
Created: 2017-02-18T16:31:24Z
Using the inline swagger definition,
it failed with below message when the swagger definition has 'Method response status' like 200.
An error occurred (ValidationError) when calling the CreateChangeSet operation: Template format error: [/Resources/ApiGatewayApi/Properties/DefinitionBody/paths//XXXX/delete/responses] map keys must be strings; received numeric [200] instead

Closing comment (2017-04-05T20:24:46Z): Could this be related to #91?
Repository: aws/serverless-application-model

Issue #57: VpcConfig invalid when referencing other resources
Created: 2017-01-09T23:21:26Z
The following returns the error message Resource with id [SampleFunction] is invalid. Type of property 'VpcConfig' is invalid. though appears to be valid.
VpcConfig:
  SecurityGroupIds:
    - !Ref FunctionSecurityGroup
  SubnetIds:
    - !ImportValue "aroundme-private-subnet"

When I modify the block to reference the actual values (as follows), template works as expected, thus this seems to be a transform issue.
VpcConfig:
  SecurityGroupIds:
    - "sg-ABC123"
  SubnetIds:
    - "subnet-ABC123"

Duplicate issue #75: VpcConfig Substitution Parameters
Created: 2017-01-26T08:57:34Z
Is it possible to define Comma Delimited List parameter and use that parameter reference when configuring Function’s VpcConfig?
Parameters:
  SubnetIdList:
    Type: CommaDelimitedList
    Description: Subnet Id list

. . .

  VpcConfig:
    SubnetIds: !Ref SubnetIdList

The deployment fails with the following error:
‘Invalid Serverless Application Specification document. Number of errors found: 1. Resource with id [TestFunction] is invalid. Type of property 'VpcConfig' is invalid’
Actually, the list is not the only problem. The following construct does not work as well.
Parameters:
  SubnetId:
    Type: String
    Description: Subnet Id 

. . .

  VpcConfig:
    SubnetIds: 
      - !Ref SubnetId

Any opinion?

Closing comment (2017-01-26T18:37:52Z): Duplicate of #57
Repository: awslabs/gluonts

Issue #617: GluonTSFramework Hyper Parameter Optimization Support
Created: 2020-02-11T12:58:16Z
Description
Implement Hyper Parameter Optimisation (HPO) Support in GluonTSFramework.
There are already multiple comments in the code of how to go about it:
# HPO implementation sketch:
#    > Example HPO of model: MODEL_HPM:Trainer:batch_size:64
#    > Now construct nested dict from MODEL_HPM hyperparameters
#    > Load the serialized model as a dict
#    > Update the model dict with the nested dict from the MODEL_HPMs
#      with dict.update(...)
#    > Write this new dict back to a s3 as a .json file like before

This is important to support:

The HyperparameterTuner: https://sagemaker.readthedocs.io/en/stable/tuner.html
and SageMaker Experiments: https://aws.amazon.com/blogs/aws/amazon-sagemaker-experiments-organize-track-and-compare-your-machine-learning-trainings/

References

Where the https://github.com/awslabs/gluon-ts/blob/master/src/gluonts/nursery/sagemaker_sdk/estimator.py

Duplicate issue #637: Bayesian Optimization for parameter tuning
Created: 2020-02-14T07:39:35Z
Hi,
Even though GluonTS models provide competitive forecasts with default parameters, it would be great to have Bayesian Optimization to tune the model parameters. That would enhance the usability  and power of GluonTS even more. Grid Search and Random Search shouldn't be used, as Bayesian Optimization provides a more efficient way of finding an optimal set of parameters. Are there any plans to add Bayesian Optimization any time soon?

Closing comment (2020-02-14T08:56:59Z): @StatMixedML this may be related to #617 I guess?
Repository: awslabs/gluonts

Issue #379: Regression tests
Created: 2019-10-10T11:37:54Z
Description
For the 0.4 release, I propose to add regression test coverage so that we are sure not to deteriorate accuracy on any of the datasets that are listed in publications.  For example, there recently seems to have occurred a regression in the M4 data sets and GluonTS should be protected against this.

Duplicate issue #764: Robustness of certain models tests.
Created: 2020-04-16T17:45:24Z
Description
Some tests are not robust and often fail:

test/model/deepstate/test_model.py
test/model/wavenet/test_model.py

They should be made more robust.
Currently they fail in unrelated PRs which creates unnecessary noise.

Closing comment (2020-04-23T13:02:20Z): As per offline discussion: this story is about making the tests mention in the original post less noisy, i.e. fail less often, but keeping them fast enough that they can run with every build or local pytest run.
Proper model accuracy regression testing is tracked by #379
Repository: awslabs/gluonts

Issue #2133: get_dataset function is broken with python3.9
Created: 2022-07-05T13:12:11Z
Description
A call to get_dataset with any dataset doesn't work with python3.9, but works with python 3.8.
The Error is in DatasetCollection.
It might be the interplay of inheriting from Protocol and dataclass decorator as reported here.
To Reproduce
from gluonts.dataset.repository.datasets import get_dataset
get_dataset("m4_hourly")
Error message or code output
warnings.warn(
Traceback (most recent call last):
  File "/local/home/nirwar/tests/gts39error/p.py", line 2, in <module>
    get_dataset("m4_hourly")
  File "/local/home/nirwar/tests/gts39error/lib/python3.9/site-packages/gluonts/dataset/repository/datasets.py", line 332, in get_dataset
    return load_datasets(
  File "/local/home/nirwar/tests/gts39error/lib/python3.9/site-packages/gluonts/dataset/common.py", line 446, in load_datasets
    train_ds = FileDataset(
  File "/local/home/nirwar/tests/gts39error/lib/python3.9/site-packages/gluonts/dataset/common.py", line 183, in FileDataset
    return DatasetCollection(
TypeError: DatasetCollection() takes no arguments

Environment

Operating system: Amazon Linux and macOS
Python version: 3.9.7 (3.8.13 works)
GluonTS version: 0.10.0
MXNet version: -

Duplicate issue #2140: TypeError: PandasDataset() takes no arguments for PandasDataset.from_long_dataframe
Created: 2022-07-06T15:09:32Z
Following as described in https://ts.gluon.ai/stable/tutorials/data_manipulation/pandasdataframes.html#Use-case-3---Loading-data-with-missing-values I could not get it to work with my own DF nor the example given:
ds = PandasDataset.from_long_dataframe(df, target="target", item_id="item_id")
Traceback (most recent call last):

  File "C:\\AppData\Local\Temp/ipykernel_33648/388385624.py", line 1, in <module>
    ds = PandasDataset.from_long_dataframe(dfx, target="target", item_id="item_id")

  File "C:\\Anaconda3\lib\site-packages\gluonts\dataset\pandas.py", line 182, in from_long_dataframe
    return cls(dataframes=dict(list(dataframe.groupby(item_id))), **kwargs)

TypeError: PandasDataset() takes no arguments

Also wanted to know if there are any plans of adding a methodology to achieve the same result starting from a wide DF, but (unlike the wide df example) incorporating a way to pass a list of feat_dynamic_cat, feat_static_cat, and so on (in same shape as the width of the wide df).

Closing comment (2022-07-06T15:41:48Z): @strakehyr are you running on Python 3.9 or newer? If so, this may be related to #2133

Yes using Python 3.9.
Repository: awslabs/gluonts

Issue #272: Incremental Training
Created: 2019-08-30T06:23:54Z
Description

As we are working on Timeseries, new data keeps flowing in.
So every time, when new data comes we have to train the entire model again which is costly and time consuming.
INCREMENTAL TRAINING would be great to deal with this problem.

References

Some thing similar to transfer learning which we can do with tensorflow and other frame works
list known implementations : Incremental training in Amazon sage maker(as of now it supports object detection and image classification algorithms only)

Duplicate issue #557: Incremental Learning
Created: 2020-01-10T00:42:03Z
I thought I saw somewhere, that some one was able to re-load weights from a previously trained predictor and create a new model starting from the previously learned weights. One the incremental learning, they set the epoch=1.
My question is, can someone remind me how that was done?
Thanks!

Closing comment (2020-05-12T04:58:26Z): related to #272?
Repository: awslabs/gluonts

Issue #998: DeepAR on Solar Energy dataset gives NRMSE > 1 
Created: 2020-08-21T13:29:09Z
after training for 40 epochs, DeepAR model still gives me NRMSE of about 1.03 although ND is reasonable (about 0.51). Why is NRMSE > 1? Possible bug?
Compared the results with https://github.com/awslabs/gluon-ts/blob/master/evaluations/solar-energy/DeepAREstimator.json and it matches, but NRMSE isn't provided.
This only happens on solar energy dataset specifically.

Duplicate issue #999: DeepAR on Solar Energy dataset gives NRMSE > 1 
Created: 2020-08-21T13:29:10Z
after training for 40 epochs, DeepAR model still gives me NRMSE of about 1.03 although ND is reasonable (about 0.51). Why is NRMSE > 1? Possible bug?
Compared the results with https://github.com/awslabs/gluon-ts/blob/master/evaluations/solar-energy/DeepAREstimator.json and it matches, but NRMSE isn't provided.
This only happens on solar energy dataset specifically.

Closing comment (2020-08-24T12:12:59Z): duplicate of #998
Repository: awslabs/gluonts

Issue #272: Incremental Training
Created: 2019-08-30T06:23:54Z
Description

As we are working on Timeseries, new data keeps flowing in.
So every time, when new data comes we have to train the entire model again which is costly and time consuming.
INCREMENTAL TRAINING would be great to deal with this problem.

References

Some thing similar to transfer learning which we can do with tensorflow and other frame works
list known implementations : Incremental training in Amazon sage maker(as of now it supports object detection and image classification algorithms only)

Duplicate issue #979: How to finetune a trained network using gluonts
Created: 2020-08-07T08:31:19Z
I have already trained a network on some period of data. As time goes by, new data comes in. I don't want to re-train the whole thing but finetune the network on the newest data. How could I achieve that?

Closing comment (2020-08-10T08:48:19Z): This is generally called "incremental learning" and unfortunately, this is currently not possible in gluon-ts.
This is a duplicate of #272.
Repository: ayn2op/discordo

Issue #465: Login attempts failing and lead to logout from every authorized device
Created: 2024-11-18T18:59:49Z
here's what discordo says on startup: 2024/11/19 00:38:51 INFO failed to get token from keyring err="secret not found in keyring"

Duplicate issue #470: 2FA makes things weird
Created: 2024-11-27T02:16:57Z
When trying to login with a 2fa code on Zorin OS, discordo does nothing but all of my other clients on all other devices get logged out.

Closing comment (2024-12-14T18:11:24Z): Duplicate: #465
Repository: ayn2op/discordo

Issue #339: App crashes immediately when attempting to login with username and password
Created: 2024-01-29T15:53:37Z
As reported by @Cooliosity, when I run discordo and attempt to put in my UN/PW the app immediately crashes.  The log file in ~/.cache/discordo is empty, and no errors are visible on the screen.
Originally posted by @Cooliosity in #332 (comment)

Duplicate issue #342: Will not start for the last 1-2 weeks
Created: 2024-02-07T19:42:09Z
I like to come back sometimes to test and see if finally is stable, but now is worse than ever, I start it, add my credentials and crashes! Do not even have time to use it. Do you guys actually test this on GNU/Linux? I am using Arch and something broke in the last 2 weeks that I test it. I did remove ~/.cache/discordo and reinstalled no luck, also deleted the config.

Closing comment (2024-02-19T19:38:24Z): Probably duplicate of #339
Repository: ayn2op/discordo

Issue #195: Feature request: Find channel/guild/DMs
Created: 2022-08-28T09:53:47Z
Opens a prompt and gets input, use fuzzy finding to list matching guilds/channels/DMs, potentially integrate with fzf

Duplicate issue #492: Feature request: Ability to filter channels/users in guild tree
Created: 2025-02-06T13:36:46Z
Would be useful to quickly find a channel or a user you want to chat with.

Closing comment (2025-02-06T17:45:47Z): Duplicate: #195
Repository: ayn2op/discordo

Issue #496: Unable to sign in via 2FA: Invalid two-factor code
Created: 2025-02-10T23:49:06Z
When I enter my email, password, and 2FA code (in the form of 123456), I get this error:

Duplicate issue #516: Invalid two-factor code
Created: 2025-03-22T07:24:59Z
Hello, I want to connect to my account but a "Discord 400 error" appears with the message "Invalid two-factor code".
I'm on version 1.0

Closing comment (2025-03-22T18:08:41Z): Duplicate: #496
Repository: ayn2op/discordo

Issue #129: Feature request: List and tag users in a channel
Created: 2022-02-25T13:39:28Z
Would be great to have the functionality of listing users in a channel and tagging @ them in chat.

Duplicate issue #422: Add @mentions in typing box
Created: 2024-09-15T03:44:07Z
I'm not sure how to implement this as I haven't implemented it in my Discord client either.

Closing comment (2024-09-15T07:53:57Z): Duplicate: #129
Repository: ayn2op/discordo

Issue #129: Feature request: List and tag users in a channel
Created: 2022-02-25T13:39:28Z
Would be great to have the functionality of listing users in a channel and tagging @ them in chat.

Duplicate issue #232: Feature Request: @mention support
Created: 2022-10-06T09:53:32Z
If this is made as a component it would help with further features

Closing comment (2022-10-06T10:03:15Z): duplicate: #129
Repository: ayn2op/discordo

Issue #162: Feature request: Support for sending attachments
Created: 2022-07-02T20:40:26Z
Hello! I would like to request a feature for supporting images, I have seen the issue about feature request for images. I have some ideas about the image feature :

For sending, type send *.png/*.jpg.
For seeing the image, just press Ctrl-O on the selected message. The message should be like this "Image : *.png | OPEN"

Duplicate issue #263: Feature request: Uploading files
Created: 2022-12-24T17:07:58Z
Maybe I just can't find it, but it seems like it's impossible to send an attached image or file. This is a quite useful feature and I'd like to see it implemented in Discordo.

Closing comment (2023-01-23T17:50:17Z): Duplicate: #162
Repository: ayn2op/discordo

Issue #403: Guild Tree duplicated when reconnecting
Created: 2024-07-04T15:50:03Z
Every time the client reconnects, a new copy of the Guild Tree is added. All copies of the Guild Tree seem to respond correctly to user input.
Guild Tree should be replaced instead of duplicated.

Duplicate issue #461: Guilds list got duplicated
Created: 2024-11-12T12:23:20Z
For some reason Guilds list got duplicated. Maybe because this client was idle for like 4 hours or something, because when I tried to open different chat client did froze for like 10 seconds (which makes me think it was reconnecting to my account)

Closing comment (2024-11-12T18:37:02Z): Duplicate: #403
Repository: ayn2op/discordo

Issue #230: Feature Request: Re-sort DM channels by recent order on message create
Created: 2022-10-06T09:06:56Z
The DM channels aren't sorted in the same way that the discord client sorts them, and it is quite hard to navigate through DMs

Duplicate issue #280: Proper ordering of channels
Created: 2023-02-04T14:59:22Z
Expectation: Dms newest to oldest, vcs at the bottom
Reality: My dms are ordered from oldest to newest, and voice channels at the top

Closing comment (2023-02-04T15:35:17Z): Duplicate: #230
Repository: ayn2op/discordo

Issue #342: Will not start for the last 1-2 weeks
Created: 2024-02-07T19:42:09Z
I like to come back sometimes to test and see if finally is stable, but now is worse than ever, I start it, add my credentials and crashes! Do not even have time to use it. Do you guys actually test this on GNU/Linux? I am using Arch and something broke in the last 2 weeks that I test it. I did remove ~/.cache/discordo and reinstalled no luck, also deleted the config.

Duplicate issue #346: Gateway Error?
Created: 2024-02-24T14:58:18Z
Here are my logs:
2024/02/24 09:48:52 ws.go:16: Gateway error: websocket: close sent
2024/02/24 09:48:52 main.go:22: websocket closed, reason: 4004 Authentication failed.
I tried building this from source, thinking that I might be able to get some progress, but no luck. Am I missing something? A dependency?
Would anyone please explain to me what the log is telling me??

Closing comment (2024-02-24T15:52:26Z): Have you tried searching up any available issues? This is a duplicate of #342. You may need an authentication code.
Repository: azavea/raster-vision

Issue #502: Distribute quickstart prediction package and update docs
Created: 2018-10-16T15:28:03Z
This will help people quickly get started making predictions even if they can't train on a model on a GPU.

Duplicate issue #513: Add sample prediction package to "Getting started"/Quickstart docs
Created: 2018-10-18T16:49:39Z
This is so people can see "good predictions" after training a crummy model.

Closing comment (2018-10-18T17:13:33Z): Duplicate of #502
Repository: azavea/raster-vision

Issue #1075: Add support for Dependabot
Created: 2021-01-20T18:55:40Z
Comb repository for dependencies that we would want to manage via Dependabot and add support through dependabot.yml. Support for GitHub Security dependency updates have already been enabled for this repository.
See:

Simple: https://github.com/azavea/operations/blob/main/.github/dependabot.yml

version: 2
updates:
  - package-ecosystem: "npm"
    directory: "/"
    schedule:
      interval: "weekly"

  - package-ecosystem: "pip"
    directory: "/src/gh_2fa_stats"
    schedule:
      interval: "weekly"

  - package-ecosystem: "github-actions"
    directory: "/"
    schedule:
      interval: "weekly"

Smarter: https://github.com/raster-foundry/groundwork/blob/develop/.github/dependabot.yml

version: 2
updates:
  # Enable version updates for npm
  - package-ecosystem: "npm"
    # Look for `package.json` and `lock` files in the `root` directory
    directory: "."
    # Check the npm registry for updates every day (weekdays)
    schedule:
      interval: "daily"
    ignore:
      - dependency-name: "polygon-clipping"
      - dependency-name: "deck.gl"
      - dependency-name: "@nebula.gl/layers"
      - dependency-name: "@nebula.gl/overlays"
      - dependency-name: "@types/mapbox-gl"
      - dependency-name: "mapbox-gl"
      - dependency-name: "@turf/bbox"
      - dependency-name: "@turf/bbox-polygon"
      - dependency-name: "@turf/boolean-contains"
      - dependency-name: "@turf/boolean-point-in-polygon"
      - dependency-name: "@turf/buffer"
      - dependency-name: "@turf/center"
      - dependency-name: "@turf/difference"
      - dependency-name: "@turf/helpers"
      - dependency-name: "@turf/intersect"
      - dependency-name: "@turf/simplify"

https://github.com/raster-foundry/groundwork/blob/develop/.github/workflows/merge-dependabot.yml

name: merge-dependabot

on:
  check_suite:
    types:
      - completed
  pull_request:
    types:
      - edited
      - labeled
      - opened
      - ready_for_review
      - reopened
      - synchronize
      - unlabeled
      - unlocked

jobs:
  merge-dependabot:
    runs-on: ubuntu-latest
    steps:
      - uses: ridedott/merge-me-action@v1.8.79
        with:
          GITHUB_LOGIN: "dependabot[bot]"
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
          PRESET: DEPENDABOT_MINOR

Duplicate issue #1074: Consider using Dependabot for keeping dependencies up to date
Created: 2021-01-20T18:54:57Z
This was suggested by @jisantuc

Closing comment (2021-01-20T18:57:37Z): Duplicate of #1075
Repository: azavea/raster-vision

Issue #991: Local runner should write makefile to temporary dir
Created: 2020-09-08T21:04:09Z
Instead, it writes it to the root_uri which might be an S3 URI, and make, which is used by the local runner cannot handle that.

Duplicate issue #1452: Makefile error when `root_uri` is an S3 path
Created: 2022-08-09T13:13:29Z
🐛 Bug
When running training command and having root_uri set to an S3 folder, this error shows up:
make: s3://<random_bucket_name>/predictions/Makefile: No such file or directory
make: *** No rule to make target 's3://<random_bucket_name>/predictions/Makefile'.  Stop.

This error disappears when root_uri is a local path. AWS config is right as it is able to read and write the files.
To Reproduce
Steps to reproduce the behavior:

I ran the following command inside the container:
python -m rastervision.pipeline.cli run local code/local_exp.py -a raw_uri s3://<random_bucket_name>/datafortesting/data/ -a root_uri s3://<random_bucket_name>/predictions -a test False


Expected behavior
It should run normally like it is running when root_uri is a local path.
Environment
Running with docker.  Image: quay.io/azavea/raster-vision:pytorch-v0.13.1
Additional context
This might be a relevant issue: #991

Closing comment (2022-08-10T11:06:37Z): Yes, this is the same as #991.
Two possible workarounds:

Use inprocess instead of local: python -m rastervision.pipeline.cli run inprocess ...
Change this line so that makefile_path is a local path (e.g. in a temporary directory): 
  
    
      raster-vision/rastervision_pipeline/rastervision/pipeline/runner/local_runner.py
    
    
         Line 69
      in
      b735cff
    
  
  
    

        
          
           makefile_path = join(dirname(cfg_json_uri), 'Makefile')
Repository: azavea/raster-vision

Issue #598: when i use pip to install rastervision and it has an error
Created: 2018-12-04T10:35:53Z
Complete output from command python setup.py egg_info:
INFO:root:Building on Windows requires extra options to setup.py to locate needed GDAL files. More information is available in the README.
ERROR: A GDAL API version must be specified. Provide a path to gdal-config using a GDAL_CONFIG environment variable or use a GDAL_VERSION environment variable.

Duplicate issue #597: when i use pip to install rastervision and it has an error
Created: 2018-12-04T10:35:15Z

Closing comment (2018-12-04T15:08:53Z): Duplicate of #598
Repository: azavea/raster-vision

Issue #1221: HTTP error 403: rate limit exceeded when using external model in isprs_potsdam.py
Created: 2021-07-25T07:40:11Z
Hi! sir I want to test your code--'isprs_potsdam.py ' and load the data about it need,but the bug is taking place.
what is happending????

Duplicate issue #1271: External Model Definition Functionality Potentially Broken in PyTorch 1.9
Created: 2021-09-11T01:38:40Z
🐛 Bug
It seems to currently not be possible to load external model definitions from inside of training pipelines.  When running in local and inprocess mode locally, I get a HTTP Error 403: rate limit exceeded error when trying to use external model definition functionality (in particular a resnet18-fpn from 'AdeelH/pytorch-fpn:0.1') in a training pipeline.
This is apparently an known issue, and can be read-about here:
pytorch/vision#4156 (comment)
To Reproduce
Steps to reproduce the behavior:

Attempt to use an external model definition in a training pipeline.  I can confirm this locally, I do not know if it exists on batch.

(I can provide the exact context and command in a different context.)
Expected behavior
I was not expecting this to happen.
Environment
Running in a docker container with the most recent

How you installed and are running Raster Vision (pip install on local vs. inside Docker image): docker
Raster Vision version or commit: current master of 09/10/2021
OS (e.g., Linux): Linux
Python version: From docker image
CUDA/cuDNN version if running on GPU: 11.2
Any other relevant information:

Additional context

Closing comment (2021-09-11T13:29:50Z): This was also reported in #1221.
Looks like a problem with PyTorch 1.9 that won't be fixed until the next release. Maybe we should revert the dependency to 1.8?
As a workaround, you can throw a zip of the repo on S3 and link to that in the external module config.

Ah, I see, I missed that earlier issue.  I was able to work around the issue by patching PyTorch within the image: pytorch/vision#4156 (comment) .
Repository: azavea/raster-vision

Issue #1410: GPU Usage for predict command for Object Detection
Created: 2022-05-26T06:56:01Z
i'm running rv 0.12 for object detection and i have input image with 60006000 dimension and chip size is 300300. so can you give understanding of how many of this parameters can be store in gpu?
how gpu is used in predict command?
can you explain gpu usage ?
if my parameters change how to find estimated gpu memoty usage?

Duplicate issue #1408: GPU memory 
Created: 2022-05-24T04:31:06Z
i'm running rv 0.12. in object detection my batch size is 1 and chip size is 300 when i run predict command it will occupied 1.7 gb in gpu but when i change chip size to 500 or 1000 it will occupied same 1.7 gb in gpu so how chip will store in gpu? can you help me regarding this?
How this chip will occupied memory in gpu?
is it possible that i change some settings and my gpu itilization will be high and can reduce prediction time ?

Closing comment (2022-05-30T10:48:13Z): Duplicate of #1410
Repository: azavea/raster-vision

Issue #251: Runtime benchmarks
Created: 2018-05-24T00:43:57Z
We should run experiments to test how much time it takes to make predictions per megapixel of imagery on several types of models and machine instance types. This will help us come up with estimates of AWS budgets for different use cases.

Duplicate issue #600: Test Deeplab on different instance types
Created: 2018-12-04T20:53:17Z
We'd like to know if there's actually a 4x speedup when using P3 instances (as opposed to P2s). We'd also like to test the newly added multi-gpu support (this could be done on a p2.8xlarge -- no need to waste money on a p3.8xlarge). To do this, we need to add the ability to utilize these instances on Batch. To do this, it probably makes sense just to setup temporary compute environments and job queues via the console -- I don't think it's worth it to mess with the raster-vision-aws setup. Then run the same training commands but on different instances and time them. We should do this a few times at the same time of day to minimize variance.

Closing comment (2018-12-04T20:59:02Z): This issue is related to #251 but has a much smaller scope and should be done before that one.
Repository: azavea/raster-vision

Issue #606: Document simple option for running on GPUs
Created: 2018-12-06T19:38:16Z
Using AWS Batch can be complex, and we should document a simple alternative for running on AWS GPUs. This could involve just spinning an instance through the console, SSH'ing into it, cloning RV, building, running console using --gpu. Or something like that.

Duplicate issue #561: Improve docs
Created: 2018-11-12T22:23:40Z
This is a black box issue for estimation purposes. Smaller issues should be created that address specific things to improve.

Closing comment (2018-12-12T15:43:03Z): Importing notes from documentation feedback sessions here. We can solve the quick ones and make issues for ones that seem more tricky as needed. This covers #516.
I'll check off items once they are added to #620, or if they were already addressed.
Intro

 Add images to top of documentation introduction that shows satellite, aerial, and oblique imagery. Can use predictions for object detection, semantic segmentation and chip classification as another visual queue. (#646)

Quickstart

 Make the Quickstart easier to find - should be towards the top of intro page and/or in sidebar.
 Put in visualizations of the data that is used by the tiny_spacenet example
 Document the use of a pre-trained model in the quickstart (#645)
 Explain that the model trained in the quickstart will perform very poorly and why
 Add QGIS visualization to quickstart - bad model output vs pretrained model output (#644)
 Include information about making predictions in the quickstart and link to the predictions page
 Add embedded map to quickstart
 Moving the prompt for docker run below the creating an ExperimentSet section - specific instructions for creating /opt/src/code directory and source code file before running anything. Note: The instructions indicate to make the code directory; the source directory is not needed for the mount, so the current docs are correct.

QGIS Plugin

 Show image of QGIS environment setting (#644)
 QGIS link in the quick links of the docs page should be to the docs page, not the repo. The repository link can be up near the top of the QGIS docs in case that's what people want to navigate to. (#644)
 Mention that for QGIS plugin predict, path to predict package should be S3, HTTP, or local host file system, even if using docker (#644)

README

 README could include instructions on how to run (pip and quay) (#643)

General

 Ensure proper instructions for running Raster Vision on a local GPU machine. Related to #606

Broken Links

 https://docs.rastervision.io/en/0.8/setup.html#install-raster-vision -  docker/console link gives 404
Repository: badaix/snapcast

Issue #22: Add some documentation to the repository
Created: 2016-01-12T15:10:16Z
This is certainly a cool project, with a lot of potential.
But I would also love to see clients on Windows 10 (phone, desktop etc.) and am willing to have a go at some of the basics of a .NET application.
The problem I am facing is a lack of documentation, I know that an answer would be "the code is the documentation", but some basic information might help... like "how" (format) are the packages transferred over the wire, how is the synchronization with the audio-clock made etc.
I found a nice document (master's thesis) on "Synchronization of streamed audio between multiple
playback devices over an unmanaged IP network" here: http://www.eit.lth.se/sprapport.php?uid=894
(don't know what license it covers, there is no real copyright on it). This should cover the basics for most people, but maybe it can help to make some parts more understandable or even have snapcast implement some standards...
Anyway, like I said, documentation would be nice. But even without, keep up the good work!

Duplicate issue #157: JSON API Documentation and API Feature Requests
Created: 2017-01-07T01:48:27Z
Is there any official documentation for the JSON RPC API, or is one expected to look at the code and work it out accordingly? Just wondering if I am missing something. If there is no documentation, please consider this a feature request, as it would be nice to integrate snapcast with 3rd party apps. Likewise, a couple of features that would be great to have in the API would be:

Create/delete new pipe/stream whilst server is started
Client Grouping (I know this is on the to-do) - Muting/Switch Stream/etc.
Disconnecting Clients

Closing comment (2017-03-15T19:59:04Z): There is a list of all available Entities, Requests and Notifications here.
It's still not good enough to call it a specification, but it might be a starting point.
Regarding the roadmap: there is only the checklist :). In the end Snapcast is still a spare time project.
I will close this issue, as it is not solved, but kind of a duplicate of #22
Repository: badaix/snapcast

Issue #402: [Feature Request] Auto stream select
Created: 2018-06-25T21:21:09Z
Can we make snap server more intelligent, what i mean is that snap server could automatically manage incoming streams. For example i have Mopidy and Airplay. Mopidy is always playing and if i want to airplay something from my macbook i need to set this on my mac (Audio -> to Airplay) and in snapcast i need to change the stream.
It would be ideal if i can give a order number to the streams, and let snap cast decide which stream must be used. When both or multiple stream have audio input.
An other example:
Music is playing on my Raspberrypi and i'm sitting in front of my mac. Now I wanna AirPlay something to the same player. Now I need to go to snapcast to set it to AirPlay.(other stream). It would be Nice if snapcast recognize the other stream is playing so it sets it to that stream. If that stream is done Its going back to Mopidy.

Duplicate issue #149: [Feature Proposal] Play Sound directly to client
Created: 2016-12-12T16:45:21Z
Hope its ok to put a few ideas in here. Some of them might be far off for now but maybe its interesting for someone.
I would like to have a feature in the server to play sound (out of a .wav file for example) specifically to one client, independent of the current stream subsctiption of that client.
Use Case: I am building a multiroom home audio solution where some clients dont have a user interface, but are instead controlled with an X10 remote control. Some buttons of that remote will trigger snapcast to change volume, mute, change the stream etc. Since there is no display whatsoever, I want to give audio feedback to the client. I am writing my own control application for snapcast already (1st version is available here as module for FHEM: Github - and this module would trigger the sounds to be played.
Currently I have a solution that I built from scratch using pulseaudio tunnel sinks but snapcast is much more modern and much easier to handle than pulseaudio.

Closing comment (2020-03-11T20:30:44Z): duplicate of #402 (actually the other way round :))
Repository: badaix/snapcast

Issue #308: Groups vs. Zones
Created: 2017-11-14T14:13:16Z
Hi, nice work!
I just moved my home audio from a pulseaudio/airplay based distribution to snapcast. Doing this I come upon a few snags; metadata and zones.
I've been trying to create static zones for areas in my house but it seems the groups are dynamic and there is no json api to name them? I can edit the config file but the edits are forgotten once the group is empty (ie no clients left in group).
What I want to achieve is define static zones in my house which can be controlled independently (mute/volume), each with a dynamic (json api) set of speakers (snapclient). Each zone can then be assigned to play any of the defined input streams in the server.
It seems to me I need a json api to change a group name and mark it static for a setup like this to work?
Keep up the good work 👍
Frafall

Duplicate issue #263: Controlling snapcast streams assigned to clients
Created: 2017-08-05T17:09:35Z
Apart from homeassistant/FHEM what are the best options to control which snapcast client gets which stream/volume etc? I have tried homeassistant but with the latest verison of homeassistant there are issues loading the snapcast component.
I also looked at the JSON-RPC client but it appears that I cannot assign streams to clients? Is that correct?
Without some way to control which stream plays where, I am struggling with snapcast a bit and one of the main features goes away..

Closing comment (2020-09-03T19:10:52Z): duplicate of #308
Repository: badaix/snapcast

Issue #308: Groups vs. Zones
Created: 2017-11-14T14:13:16Z
Hi, nice work!
I just moved my home audio from a pulseaudio/airplay based distribution to snapcast. Doing this I come upon a few snags; metadata and zones.
I've been trying to create static zones for areas in my house but it seems the groups are dynamic and there is no json api to name them? I can edit the config file but the edits are forgotten once the group is empty (ie no clients left in group).
What I want to achieve is define static zones in my house which can be controlled independently (mute/volume), each with a dynamic (json api) set of speakers (snapclient). Each zone can then be assigned to play any of the defined input streams in the server.
It seems to me I need a json api to change a group name and mark it static for a setup like this to work?
Keep up the good work 👍
Frafall

Duplicate issue #759: snapclient: allow setting the client name and group to join from the command line
Created: 2021-01-03T09:44:59Z
it would be great to have some more control over the naming from both snapserver command line ("default group for new clients") and snapclient ("client name" and optional "group to join"). the stretch goal would be to use the hostname (if you want to guarantee uniqueness, with a random extension (e.g. "music-pi-FC4D"). i think this would be nicer than having clients show up with entirely cryptic names.
on the other hand, at least the client name might be a purely UI kind of issue - with the snapcast integration in iris, i can actually see the hostnames as well.

Closing comment (2021-02-19T17:35:50Z): Duplicate of #308 and #515
Repository: badaix/snapcast

Issue #505: systemd fails to start snapserver
Created: 2019-11-21T04:26:44Z
new arm package - snapcast service fails to start

Duplicate issue #534: Default snapserver user does not have permissions to .json file
Created: 2020-01-28T00:15:13Z
On a Raspberry Pi with a Buster image, v 15 of SnapServer works fine as a service.  When I upgrade to v 18 SnapServer fails to start.  The debug log lists:
[Error] (main) Exception: failed to open file "/var/lib/snapserver/server.json", permission denied (error 13)
It appears that user and group _snapserver from v15 have permissions to the file but user and group snapserver from v18 do not.
I apologize if I am not clear with this.  Thank you for your time.
KO

Closing comment (2020-01-28T07:15:21Z): I think the user _snapserver was introduced in v0.16, not 0.15, and changed back to snapserver in v0.17.
This seems to be a duplicate of #505
Repository: badaix/snapcast

Issue #121: snapclient crashes when soundcard is in use
Created: 2016-10-28T23:43:52Z
There are several things with the client and a blocked soundcard. (bocked = in use by other program)

When starting the client and the soundcard is blocked, it waits for it to become available (good)
When started with an available soundcard and starting playback when the card got blocked in the meantime, it crashes (bad)

It would be nice, if the client would access the card only when needed (when playback starts) and releases it afterwards. If the card is blocked, it should wait for it, but not crash. This way the client could share the soundcard with other applications.

Duplicate issue #124: how can i switch to non exclusionary alsa mode?
Created: 2016-11-04T10:44:34Z
hi,
i have some respi in my kitchen for playing music using snapcast. Now i want to introduce another snapserver to the network that should be played parallel with the other one. Problem is:
2016-11-04 10-39-10 [err] Controller::onException: Can't open plughw:CARD=Device,DEV=0 PCM device: Device or resource busy

so how can i get snapclient to dont use alsa using the exclusive mode but that mode that can be used by more then one software simultaneously? I know an option with other softwares using alsa.
Thanks in advance

Closing comment (2016-11-10T09:28:00Z): Is it a normal Raspbian Jessie? I can start several snapclients on my pi's (also on my x64 Linux Mint). How can I reproduce this?
Is this related to #121?
Repository: baldurk/renderdoc

Issue #2726: Add support for glEGLImageTargetTexture2DOES
Created: 2022-09-20T16:30:06Z
Description
I want to use RenderDoc to debug Wolvic browser and the web apps running on it. This is a VR-enabled browser and in my case I'm running on a Huawei Mate 40E phone with Huawei VR Glass Kit (6dof).
I installed RenderDoc v1.21 and followed Android setup guide.
When I launch Wolvic from RenderDoc, I see an overlay image that reads:
Capturing OpenGLES.
Captures disabled.
Unsupported function used:
 - glEGLImageTargetTexture2DOES

and no frames are captured.

The function in question was introduced in OES_EGL_image_external extension, a fairly old one. I'm not sure whether this API is popular or not, or if there are specific technical reasons why it hasn't been supported in RenderDoc.
RenderDoc is an invaluable tool for us to debug gfx issues and improving performance in general.  Please consider adding support for this API.
Environment


RenderDoc version: 1.21 (built from 98a9340)
Operating System: HarmonyOS 2.0.0
Graphics API: OpenGL-ES 3.0

Duplicate issue #2962: android feature request and a suggestion
Created: 2023-06-20T06:41:07Z
Description

AFAIK the glEGLImageTargetTexture2DOES is used in common for mobile device. Whenever I try to use the RenderDoc to capture frames for debugging with some apps, it shows,
Captures Disabled. 
Unsupported function used: 
- glEGLImageTargetTexture2DOES

I hope the RenderDoc can support the extension if possible. it could be best for user. But if there is a reason why some of extensions cannot be supported, RenderDoc could still capture frames for other gl data except around the texture though.
(Actually user may not interested in capturing the data for unsupported extensions like me)
Or, is there any possible work-around way to capture frames for app debugging with unsupported extensions?

Environment


RenderDoc version: v1.27
Operating System: Windows
Graphics API: GLES

Closing comment (2023-06-20T10:39:59Z): This is a duplicate of #2726, please see that issue for more information. Your application should be checking for what extensions are available before calling their functions, as otherwise it is behaving illegally.
Repository: baldurk/renderdoc

Issue #1863: Mapped render target memory can crash replaying detected GPU writes
Created: 2020-05-02T03:19:22Z
Description
When loading a specific capture file, RenderDoc, at first it seems normal. I can switch between tabs, and I see the progress bar at the bottom constantly showing movement. But when I click on one of the events on the left, everything hangs.
Steps to reproduce

Load  wgpu-player-capture-bug.zip
Click on the "Color Pass #1"

The diagnostic log complains about nonCoherentAtomSize not being respected, but I'm not seeing in the app code where it would be the case. Not sure if it's related.
Environment


RenderDoc version: 1.7 rev a56af58
Operating System: Linux
Graphics API: Vulkan

The log lists 2 GPUs, not sure which one RenderDoc is using:

Core     PID 188431: [23:07:24]  vk_device_funcs.cpp(1356) - Log     - physical device 0: Intel(R) UHD Graphics 630 (Coffeelake 3x8 GT2) (ver 19.3 patch 0x4) - 8086:3e9b
Core     PID 188431: [23:07:24]  vk_device_funcs.cpp(1356) - Log     - physical device 1: GeForce GTX 1050 Ti with Max-Q Design (ver 440.64 patch 0x0) - 10de:1c8c

Duplicate issue #2083: UI freeze on Linux/vulkan replay
Created: 2020-10-28T13:33:22Z
Description
Capturing and replaying a relatively simple workload freezes the UI and makes it unusable.
Steps to reproduce

download and unpack wgpu-trace.zip
download and unpack wgpu.zip
cd wgpu/player
cargo build --features renderdoc - this may take a bit of time, requires Cargo + Rust. The artifact we are interested in is ../target/debug/play, and that's what we'll be running from renderdoc, passing the wgpu-trace path as a parameter.
launch the app from Renderdoc using the following settings:


You'd need to change the paths to wgpu and wgpu-trace. It will finish quickly and produce a capture automatically.
Navigating to the draw call (EID 43, for example, and then to EID 9) would show the progress bar at the bottom, which never stops and freezes the UI:

The application stops responding and can only be killed after that.
Environment

RenderDoc version: 1.10
Operating System: Solus linux
Graphics API: Vulkan

Closing comment (2020-10-28T14:20:53Z): This seems like it may be the same as #1863 . I can replay the capture fine with latest mesa on my hardware, but looking at it I can see that your application still maps memory behind GPU render targets and there was a bug that meant renderdoc was still replaying mapped memory updates into that.
Please try again with that commit, if it still doesn't work let me know and I can investigate again. If it does still happen I'd particularly be interested to know if it still happens on your nvidia card, or on intel if you don't map memory with render targets bound.