tensorflow / tensorflow/datasets

cannot download coco 2014

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Description

Short description
I try to download coco2014 with the following code.

trainset = tfds.load(name = "coco/2014", split = tfds.Split.TRAIN, download = True);

tfds complains that

2020-09-07 10:38:48.913458: E tensorflow/core/platform/cloud/curl_http_request.cc:611] The transmission of request 0x58a3e90 (URI: https://www.googleapis.com/storage/v1/b/tfds-data/o/dataset_info%2Fcoco%2F2014%2F1.1.0?fields=size%2Cgeneration%2Cupdated) has been stuck at 0 of 0 bytes for 61 seconds and will be aborted. CURL timing information: lookup time: 0.00351 (No error), connect time: 60.0547 (No error), pre-transfer time: 0 (No error), start-transfer time: 0 (No error)

I try to open the link given in the error message and get the json response

{
  "error": {
    "code": 404,
    "message": "No such object: tfds-data/dataset_info/coco/2014/1.1.0",
    "errors": [
      {
        "message": "No such object: tfds-data/dataset_info/coco/2014/1.1.0",
        "domain": "global",
        "reason": "notFound"
      }
    ]
  }
}

by the way, how can I use the downloaded 1.0.0 version coco2014 tfds dataset?

Environment information

  • Operating System: ubuntu 18.04
  • Python version: 3.6.9
  • tfds-nightly version: 3.2.1.dev202009060105
  • tensorflow version: 2.3.0

Reproduction instructions

trainset = tfds.load(name = "coco/2014", split = tfds.Split.TRAIN, download = True);

Link to logs
If applicable, <link to gist with logs, stack trace>

Expected behavior
the coco 2014 should be download without problem.

Additional context
Add any other context about the problem here.

Contributor guide

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First steps

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Research direction

Start by reproducing the reported tfds.load(name="coco/2014", split=tfds.Split.TRAIN, download=True) failure in the stated TensorFlow Datasets environment. Investigate why the loader requests the missing 1.1.0 metadata object when a 1.0.0 dataset is available; the issue is done when the supported COCO 2014 dataset downloads successfully or the version-selection behavior is clearly resolved.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, tensorflow
Domain
data, machine-learning
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
35/100

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