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base repository: Pavel-Konarik/detectron2
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head repository: facebookresearch/detectron2
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Commits on Aug 4, 2021
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RandomSubsetTrainingSampler to randomly sample training data subset f…
…or accuracy-data curve Summary: Add a sampler class `RandomSubsetTrainingSampler`, which is similar to TrainingSampler but only sample a random subset (e.g., 50%) of indices. `RandomSubsetTrainingSampler` is useful when you want to estimate the accuracy vs data-volume curves by training the model with different `subset_ratio`. Reviewed By: ppwwyyxx Differential Revision: D29892290 fbshipit-source-id: a342a6f1aa7852feb6566c648bd673028a3e0668
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Added hook that prints detailed pytorch memory stats
Reviewed By: ppwwyyxx Differential Revision: D30076586 fbshipit-source-id: 72017b55bc99d6dab2b11b663cd7da98b814b544
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Commits on Aug 5, 2021
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Summary: Pull Request resolved: facebookresearch#3322 avoid warnings like the following: ``` [W ProcessGroupNCCL.cpp:1569] Rank 0 using best-guess GPU 0 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device. ``` maybe can fix the hang in facebookresearch#3319 Reviewed By: vaibhava0 Differential Revision: D30077957 fbshipit-source-id: b8827e66c5eecc06b650acde2e7ff44106327f69
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Differential Revision: D26773548 fbshipit-source-id: 94bdd659b2bf35235de411795f20d6cd8f045fa4
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remove warnings about cell_anchors
Summary: close facebookresearch#3313 Reviewed By: vaibhava0 Differential Revision: D30062746 fbshipit-source-id: ed548c2b0513933a1071364ac4824f5346675918
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Summary: close T85305354 Reviewed By: vaibhava0 Differential Revision: D30063498 fbshipit-source-id: 251a0700d92071bcb1f9eea1e8bc736119ab552a
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Commits on Aug 10, 2021
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Summary: Add cat methods to Keypoints Reviewed By: ppwwyyxx Differential Revision: D30199199 fbshipit-source-id: 7d2c63810e7e05931c90b7ea5102a734b7ce8af4
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Reviewed By: alexander-kirillov, bowenc0221 Differential Revision: D30215015 fbshipit-source-id: 90c6a791c23f4edacdc7e7a95b41586582e8da93
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Expose stats_mode N for NaiveSyncBN
Summary: * Current code does not enable user to choose stats_mode="N" for naiveSyncBN. This change exposes that. - stats_mode="N" is necessary for supporting zero-length inputs. Without it: `SyncBatchNorm(stats_mode="") does not support zero batch size.` ------------------------ Reviewed By: jonmorton, vaibhava0, ppwwyyxx Differential Revision: D29362934 fbshipit-source-id: f8d5a33cac599f706e6620c31495e8c1577970dc
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Commits on Aug 11, 2021
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Use current device id in dist.barrier
Summary: Pull Request resolved: facebookresearch#3350 `get_local_rank` relies on a global variable set by Detectron2's `launch` utils. Since other frameworks might use Detectron2's distribute utils but don't launch with Detectron2's `launch` utils. Use `torch.cuda.current_device` to get the current device instead. Reviewed By: HarounH, ppwwyyxx Differential Revision: D30233746 fbshipit-source-id: 0b140ed5c1e7cd87ccf05235127f338ffc40a53d
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Summary: rank is 0-based Reviewed By: bowenc0221 Differential Revision: D30258674 fbshipit-source-id: 1e8331e303fdcce8c96c500e520ffadc000f06ba
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Commits on Aug 19, 2021
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avoid list[ndarray] -> tensor conversion in Boxes
Summary: avoid wanings like: ``` detectron2/structures/boxes.py:158: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at torch/csrc/utils/tensor_new.cpp:201.) ``` Reviewed By: wat3rBro Differential Revision: D30172338 fbshipit-source-id: fbe044fead72722b3c6eb9916faa2a7dca3e6eae
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rename matched_boxlist_iou -> matched_pairwise_iou
Summary: The naming "boxlist" comes from maskrcnn-benchmark. This functions is created when pairwise_iou is called `boxlist_iou`. Rename it to follow a consistent naming. Reviewed By: jonmorton Differential Revision: D30428372 fbshipit-source-id: be73f5acb1c6a5a2266c2b7706394b1f84f23479
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Commits on Aug 23, 2021
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let MapDataset support iterable
Summary: Most production use cases needs error handling. This is not available in pytorch's `.map()`. This is useful as we move towards using more IterableDataset Differential Revision: D30123656 fbshipit-source-id: 17c4caa3e4ed18c1b073bbfe8309ca3b3681a59b
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scripting support for C4 models
Summary: Pull Request resolved: facebookresearch#3318 Just add some typing. fix facebookresearch#3302 Reviewed By: zhanghang1989, wat3rBro Differential Revision: D30062501 fbshipit-source-id: c1f2a3cb42f8ee11d5e8c582fc5b8f5464c438d0
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Summary: see context in T88568338 Reviewed By: wat3rBro Differential Revision: D30063970 fbshipit-source-id: 1ad0ac0dfb72a6c7aba6e4263724550e4042c664
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Add linear box2box transform and pairwise distance
Summary: both used in FCOS Reviewed By: zhanghang1989 Differential Revision: D30470063 fbshipit-source-id: 495494a669acd9f706c3845551252ced4acc9888
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fix support for empty annotations
Summary: fix facebookresearch#3401 Reviewed By: wat3rBro Differential Revision: D30491149 fbshipit-source-id: 0af0d850afcb4aa451da2975aa46c4c854138523
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check for errors in SemSegFPNHead
Summary: close facebookresearch#3316 Reviewed By: wat3rBro Differential Revision: D30062593 fbshipit-source-id: e8b614c21f62012e081f425dd9df850179f1f2a7
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raise clear error message for mismatched keypoint metadata
Summary: The error message in facebookresearch#3341 is not informative Reviewed By: wat3rBro Differential Revision: D30185963 fbshipit-source-id: 11fda5e6e22851942b5da9df09b6ec4e315eddef
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Commits on Aug 24, 2021
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use OmegaConf.select in omegaconf2.1
Reviewed By: wat3rBro Differential Revision: D29738743 fbshipit-source-id: 08b49cabe5c1c43478418600e3f0076e443d2e22
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allow torchscript tests to run on CPUs
Summary: close T88689498 Reviewed By: vaibhava0 Differential Revision: D30063379 fbshipit-source-id: 23cddad66c17857f96bd60f59cf9f67291aedfff
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Summary: Implemented hook for saving best model, as discussed in facebookresearch#2114 Pull Request resolved: facebookresearch#3222 Reviewed By: zhanghang1989 Differential Revision: D29764303 Pulled By: ppwwyyxx fbshipit-source-id: b5cb42b34a15ea151cce8fe992a9f35a964a6afe
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suppress errors in
fbcode/vision
- batch 1Differential Revision: D30514760 fbshipit-source-id: f80b301ae5ea779588a9d634c1baa35f8f2d3e99
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Commits on Aug 25, 2021
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support IterableDataset in build_detection_train_loader
Differential Revision: D24677397 fbshipit-source-id: 1e4a991c521da1e139ccc7fe40b715dc921d3294
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Commits on Aug 26, 2021
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Summary: it has been deprecated for 1 year. moving to internal Reviewed By: jonmorton Differential Revision: D25876263 fbshipit-source-id: 2ee8cab3b25b66664792578bb40194d813208f2e
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Commits on Aug 27, 2021
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fix MapDataset creation in python 3.9
Summary: fix facebookresearch#3405 The old code works for python 3.6 & 3.7; fails for python 3.9 Reviewed By: zhanghang1989 Differential Revision: D30599139 fbshipit-source-id: ab9e5d68387b68e1095112e9c2531a971567accc
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Summary: run ./dev/linter.sh Reviewed By: zhanghang1989 Differential Revision: D30599861 fbshipit-source-id: 8957443bb1ca9e143ca11a2e2675b8513ed63d16
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Always detach tensor in visualization
Summary: Thanks for your contribution!. Fixed the following runtime Error : numpy() fails when visualizing an output element of a input batch during inference Pull Request resolved: facebookresearch#3400 Reviewed By: jonmorton Differential Revision: D30560943 Pulled By: ppwwyyxx fbshipit-source-id: abe94a12b67a5c8bad2a60fff989072f99b70d16
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Summary: Pull Request resolved: facebookresearch#3410 avoid bugs like the last diff Reviewed By: zhanghang1989 Differential Revision: D30599205 fbshipit-source-id: 3b2abd2885d384bd3f2a29b454d3da5e023e01a3
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Commits on Aug 30, 2021
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add __len__ for ToIterableDataset
Reviewed By: zhanghang1989 Differential Revision: D30635073 fbshipit-source-id: 664ba17b768a69fed97ca94b944e43d186336966
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Commits on Sep 1, 2021
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Update mmdetection to latest github master
Summary: Wanted to use some of the latest additions to mmdetection; in particular, the UniformAssignment from YOLOF (Free box AP win, even in two stage models!). I just cloned latest mmdetection and copied into `deeplearning/projects/third_party/mmdetection`. Reviewed By: ppwwyyxx Differential Revision: D30598178 fbshipit-source-id: 05fc559534a2fde41b36fc8c088c4e5c1729e7a2
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Commits on Sep 2, 2021
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Make vis module importable, remove required torch and torchvision
Summary: In PR facebookresearch#3311 we made densepose a pip-installable Python package. However, we forgot to include an `__init__.py` so that the `vis` module is importable. This PR adds that `__init__.py`. It was also mentioned in that PR that there is a preference not to require torch and torchvision requirements versions: facebookresearch#3311 (comment) This PR also removes those requirements from the `setup.py` and lists them instead in the prerequisites in the documentation. Pull Request resolved: facebookresearch#3382 Reviewed By: patricklabatut Differential Revision: D30462761 Pulled By: vkhalidov fbshipit-source-id: e58985ff24cc75ff1d7905a863fa040e3be99bc3
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Increase limit on number of detections per image in {COCO,LVIS}Evaluator
Summary: ## Context - The current limit on the number of detections per image (`K`) in LVIS is 300. - Implementing AP_pool/AP_fixed requires removing this default limit on `K` - [Literature](https://arxiv.org/pdf/2102.01066.pdf) has shown that increasing `K` correlates with AP gains ## This Diff - Changed limit on number of detections per image (`K`) to be customizable for LVIS and COCO through `TEST.DETECTIONS_PER_IMAGE` in the config - For COCO: - Maintain the default `max_dets_per_image` to be [1, 10, 100] as from [COCOEval](https://www.internalfb.com/code/fbsource/[88bb57c3054a]/fbcode/deeplearning/projects/cocoApi/PythonAPI/pycocotools/cocoeval.py?lines=28-29) - Allow users to input a custom integer for `TEST.DETECTIONS_PER_IMAGE` in the config, and use [1, 10, `TEST.DETECTIONS_PER_IMAGE`] for COCOEval - For LVIS: - Maintain the default `max_dets_per_image` to be 300 as from [LVISEval](https://www.internalfb.com/code/fbsource/[f6b86d023721]/fbcode/deeplearning/projects/lvisApi/lvis/eval.py?lines=528-529) - Allow users to input a custom integer for `TEST.DETECTIONS_PER_IMAGE` in the config, and use this in LVISEval - Added `COCOevalMaxDets` for evaluating AP with the custom limit on number of detections per image (since default `COCOeval` uses 100 as limit on detections per image for evaluating AP) ## Inference Runs using this Diff - Performed inference using `K = {300, 1000, 10000, 100000}` - Launched fblearner flows for object detector baseline models with N1055536 (LVIS) and N1055756 (COCO) - Recorded [results of running inference](https://docs.google.com/spreadsheets/d/1rgdjN2KvxcYfKCkGUC4tMw0XQJ5oZL0dwjOIh84YRg8/edit?usp=sharing) Reviewed By: ppwwyyxx Differential Revision: D30077359 fbshipit-source-id: 372eb5e0d7c228fb77fe23bf80d53597ec66287b
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Commits on Sep 8, 2021
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add a scriptable ResizeShortestEdge.get_output_shape
Summary: this function alone is useful in deployment Reviewed By: zhanghang1989 Differential Revision: D30801733 fbshipit-source-id: 792f8ca016f2c6782fc25c9bbaa302588597d087
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Summary: Correct typo to to swap -> to swap Regarding issue facebookresearch#3458 Thanks for your contribution! If you're sending a large PR (e.g., >100 lines), please open an issue first about the feature / bug, and indicate how you want to contribute. We do not always accept features. See https://detectron2.readthedocs.io/notes/contributing.html#pull-requests about how we handle PRs. Before submitting a PR, please run `dev/linter.sh` to lint the code. Pull Request resolved: facebookresearch#3459 Reviewed By: zhanghang1989 Differential Revision: D30802143 Pulled By: ppwwyyxx fbshipit-source-id: a820fa521d9e54c32d4af614ea48df3207dc6515
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Commits on Sep 10, 2021
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support creating bitmasks from empty polygons
Reviewed By: HannaMao Differential Revision: D30795434 fbshipit-source-id: 7a841e0f980f6c8ff40411acff9c732a53ac2c3b
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Commits on Sep 13, 2021
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Summary: Pre-computing trimap weights avoids unnecessary CPU <--> GPU copy during loss calculation and leads to 45% training speed up. In addition to that, this also brings accuracy improvements. For xirp17e res 160 Portal model pre-computing trimap weights got +0.7 IOU, +1.2 B-IOU and +0.2 BT-IOU. Note that the Portal model still uses the trimap computation and not boundary loss. In fact, for xirp17e boundary loss did not show additional gains compared to trimap. Reviewed By: wenliangzhao2018 Differential Revision: D30200036 fbshipit-source-id: 4e6c5f022b341757c93678e81d73d2e8c259b43a
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Commits on Sep 15, 2021
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Fix the coco_evaluation for keypoints
Summary: Fix the keypoint evaluation pipeline. Reviewed By: ppwwyyxx Differential Revision: D30904414 fbshipit-source-id: ef8bff166fccf2ef059013ae97ff119f8a9b4df0
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Commits on Sep 16, 2021
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fix ColorMode.IMAGE_BW of visualizer
Summary: fix facebookresearch#3486 Reviewed By: zhanghang1989 Differential Revision: D30974958 fbshipit-source-id: 68c7d041f3b5b64eb0c32b4fcc99ad6d13e3542f
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Commits on Sep 17, 2021
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Visualizer: make keypoint threshold configurable
Summary: Make the keypoint threshold a class member, so it can be changed. Reviewed By: ppwwyyxx Differential Revision: D30690598 fbshipit-source-id: 29499eaf12257e5bb4871ea318dc4ab5523d304e
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Commits on Sep 20, 2021
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Fix reduction of cross_entropy
Summary: Reduction of cross_entropy is always set to "mean". Fixed to receive the reduction. Pull Request resolved: facebookresearch#3454 Reviewed By: zhanghang1989 Differential Revision: D31052191 Pulled By: ppwwyyxx fbshipit-source-id: 0bd992cac13c67a772fac8539ab5cc4f7c8e5c3c
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Summary: Thanks for your contribution! If you're sending a large PR (e.g., >100 lines), please open an issue first about the feature / bug, and indicate how you want to contribute. We do not always accept features. See https://detectron2.readthedocs.io/notes/contributing.html#pull-requests about how we handle PRs. Before submitting a PR, please run `dev/linter.sh` to lint the code. Pull Request resolved: facebookresearch#3476 Reviewed By: zhanghang1989 Differential Revision: D31052262 Pulled By: ppwwyyxx fbshipit-source-id: d1f7ab357ce48e4d7735e024d6441a96b863bd71
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set default pre-trained model to empty
Summary: Empty is a better default Reviewed By: zhanghang1989 Differential Revision: D30980361 fbshipit-source-id: 9ad2bde6b9d9462ccf7cf953c33894a0c0279ad1
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Summary: Correct typo standarized -> standardized Regarding issue facebookresearch#3467 Thanks for your contribution! If you're sending a large PR (e.g., >100 lines), please open an issue first about the feature / bug, and indicate how you want to contribute. We do not always accept features. See https://detectron2.readthedocs.io/notes/contributing.html#pull-requests about how we handle PRs. Before submitting a PR, please run `dev/linter.sh` to lint the code. Pull Request resolved: facebookresearch#3468 Reviewed By: zhanghang1989 Differential Revision: D31052099 Pulled By: ppwwyyxx fbshipit-source-id: 4128566943cfa54fcebd357d6c1a1f9dda70a7da
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config: warning when the dumped yaml is invalid
Summary: if dumped yaml is unloadable, print warning and save a pkl Reviewed By: zhanghang1989 Differential Revision: D30975516 fbshipit-source-id: c2eb839c9ffcdee7951d78b01e5c10939debec77
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let LazyCall support dataclasses
Summary: it was unsupported due to omegaconf Reviewed By: zhanghang1989 Differential Revision: D30753898 fbshipit-source-id: d47b014bdc806023ebc95364359d8695865cd3c7
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Commits on Sep 25, 2021
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remove caffe2-export of panopticfpn
Summary: Caffe2 export should be deprecated. Start from the least used model. Reviewed By: wat3rBro Differential Revision: D31038278 fbshipit-source-id: 18fd26942dd35f3a542f2da1e593b6c629a22ba1
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support using bitmask with LSJ
Summary: `polygons_to_bitmask` fails with empty polygon which could happen with LSJ. Pull Request resolved: fairinternal/detectron2#564 Reviewed By: HannaMao Differential Revision: D31181422 Pulled By: ppwwyyxx fbshipit-source-id: 5f955e04518bae153401df0760840f5daf0da66a
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Commits on Sep 28, 2021
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support iterable dataset in build_detection_test_loader
Summary: Like D24677397 (facebookresearch@05bc843), but for test loader Differential Revision: D31161853 fbshipit-source-id: 6c101843a2be681fc23b2ff241070876a77be80f
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