Пример #1
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 def test_diff_cfg_no_new_allowed(self):
     """check that if new_allowed is False, new keys cause key error"""
     # create base config
     cfg1 = CfgNode()
     cfg1.A = CfgNode()
     cfg1.A.set_new_allowed(False)
     cfg1.A.Y = 2
     # case 2: new allowed not set, new config has new keys
     cfg2 = cfg1.clone()
     cfg2.A.X = 2
     self.assertRaises(KeyError, get_diff_cfg, cfg1, cfg2)
Пример #2
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def _add_rcnn_default_config(_C):
    _C.EXPORT_CAFFE2 = CfgNode()
    _C.EXPORT_CAFFE2.USE_HEATMAP_MAX_KEYPOINT = False

    # Options about how to export the model
    _C.RCNN_EXPORT = CfgNode()
    # whether or not to include the postprocess (GeneralizedRCNN._postprocess) step
    # inside the exported model
    _C.RCNN_EXPORT.INCLUDE_POSTPROCESS = False

    _C.RCNN_PREPARE_FOR_EXPORT = "default_rcnn_prepare_for_export"
    _C.RCNN_PREPARE_FOR_QUANT = "default_rcnn_prepare_for_quant"
    _C.RCNN_PREPARE_FOR_QUANT_CONVERT = "default_rcnn_prepare_for_quant_convert"
Пример #3
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 def test_diff_cfg_with_new_allowed(self):
     """diff config with new keys and new_allowed set to True"""
     # create base config
     cfg1 = CfgNode()
     cfg1.A = CfgNode()
     cfg1.A.set_new_allowed(True)
     cfg1.A.Y = 2
     # case 3: new allowed set, new config has new keys
     cfg2 = cfg1.clone()
     cfg2.A.X = 2
     gt = CfgNode()
     gt.A = CfgNode()
     gt.A.X = 2
     self.assertEqual(gt, get_diff_cfg(cfg1, cfg2))
Пример #4
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 def test_get_diff_cfg(self):
     """check config that is diff from default config, no new keys"""
     # create base config
     cfg1 = CfgNode()
     cfg1.A = CfgNode()
     cfg1.A.Y = 2
     # case 1: new allowed not set, new config has only old keys
     cfg2 = cfg1.clone()
     cfg2.set_new_allowed(False)
     cfg2.A.Y = 3
     gt = CfgNode()
     gt.A = CfgNode()
     gt.A.Y = 3
     self.assertEqual(gt, get_diff_cfg(cfg1, cfg2))
Пример #5
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    def test_modeling_hook_cfg(self):
        """Create model with modeling hook using build_model"""
        cfg = CfgNode()
        cfg.MODEL = CfgNode()
        cfg.MODEL.DEVICE = "cpu"
        cfg.MODEL.META_ARCHITECTURE = "TestArch"
        cfg.MODEL.MODELING_HOOKS = ["PlusOneHook", "TimesTwoHook"]
        model = build_model(cfg)
        self.assertEqual(model(2), 10)

        self.assertTrue(hasattr(model, "_modeling_hooks"))
        self.assertTrue(hasattr(model, "unapply_modeling_hooks"))
        orig_model = model.unapply_modeling_hooks()
        self.assertIsInstance(orig_model, TestArch)
        self.assertEqual(orig_model(2), 4)
Пример #6
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 def cast_from_other_class(cls, other_cfg):
     """Cast an instance of other CfgNode to D2Go's CfgNode (or its subclass)"""
     new_cfg = CfgNode(other_cfg)
     # copy all fields inside __dict__, this will preserve fields like __deprecated_keys__
     for k, v in other_cfg.__dict__.items():
         new_cfg.__dict__[k] = v
     return new_cfg
Пример #7
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def create_cfg_from_cli_args(args, default_cfg):
    """
    Instead of loading from defaults.py, this binary only includes necessary
    configs building from scratch, and overrides them from args. There're two
    levels of config:
        _C: the config system used by this binary, which is a sub-set of training
            config, override by configurable_cfg. It can also be override by
            args.opts for convinience.
        configurable_cfg: common configs that user should explicitly specify
            in the args.
    """

    _C = CfgNode()
    _C.INPUT = default_cfg.INPUT
    _C.DATASETS = default_cfg.DATASETS
    _C.DATALOADER = default_cfg.DATALOADER
    _C.TEST = default_cfg.TEST
    if hasattr(default_cfg, "D2GO_DATA"):
        _C.D2GO_DATA = default_cfg.D2GO_DATA
    if hasattr(default_cfg, "TENSORBOARD"):
        _C.TENSORBOARD = default_cfg.TENSORBOARD

    # NOTE configs below might not be necessary, but must add to make code work
    _C.MODEL = CfgNode()
    _C.MODEL.META_ARCHITECTURE = default_cfg.MODEL.META_ARCHITECTURE
    _C.MODEL.MASK_ON = default_cfg.MODEL.MASK_ON
    _C.MODEL.KEYPOINT_ON = default_cfg.MODEL.KEYPOINT_ON
    _C.MODEL.LOAD_PROPOSALS = default_cfg.MODEL.LOAD_PROPOSALS
    assert _C.MODEL.LOAD_PROPOSALS is False, "caffe2 model doesn't support"

    _C.OUTPUT_DIR = args.output_dir

    configurable_cfg = [
        "DATASETS.TEST",
        args.datasets,
        "INPUT.MIN_SIZE_TEST",
        args.min_size,
        "INPUT.MAX_SIZE_TEST",
        args.max_size,
    ]

    cfg = _C.clone()
    cfg.merge_from_list(configurable_cfg)
    cfg.merge_from_list(args.opts)

    return cfg
Пример #8
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    def test_modeling_hook_copy(self):
        """Create model with modeling hook, the model could be copied"""
        cfg = CfgNode()
        cfg.MODEL = CfgNode()
        cfg.MODEL.DEVICE = "cpu"
        cfg.MODEL.META_ARCHITECTURE = "TestArch"
        cfg.MODEL.MODELING_HOOKS = ["PlusOneHook", "TimesTwoHook"]
        model = build_model(cfg)
        self.assertEqual(model(2), 10)

        model_copy = copy.deepcopy(model)

        orig_model = model.unapply_modeling_hooks()
        self.assertIsInstance(orig_model, TestArch)
        self.assertEqual(orig_model(2), 4)

        orig_model_copy = model_copy.unapply_modeling_hooks()
        self.assertEqual(orig_model_copy(2), 4)
Пример #9
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    def get_default_cfg():
        _C = super(GeneralizedRCNNRunner, GeneralizedRCNNRunner).get_default_cfg()
        _C.EXPORT_CAFFE2 = CfgNode()
        _C.EXPORT_CAFFE2.USE_HEATMAP_MAX_KEYPOINT = False

        _C.RCNN_PREPARE_FOR_EXPORT = "default_rcnn_prepare_for_export"
        _C.RCNN_PREPARE_FOR_QUANT = "default_rcnn_prepare_for_quant"
        _C.RCNN_PREPARE_FOR_QUANT_CONVERT = "default_rcnn_prepare_for_quant_convert"

        return _C
Пример #10
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    def test_merge_from_list_with_new_allowed(self):
        """
        YACS's merge_from_list doesn't take new_allowed into account, D2Go override its behavior, and this test covers it.
        """
        # new_allowed is not set
        cfg = CfgNode()
        cfg.A = CfgNode()
        cfg.A.X = 1
        self.assertRaises(Exception, cfg.merge_from_list, ["A.Y", "2"])

        # new_allowed is set for sub key
        cfg = CfgNode()
        cfg.A = CfgNode(new_allowed=True)
        cfg.A.X = 1
        cfg.merge_from_list(["A.Y", "2"])
        self.assertEqual(cfg.A.Y,
                         2)  # note that the string will be converted to number
        # however new_allowed is not set for root key
        self.assertRaises(Exception, cfg.merge_from_list, ["B", "3"])
Пример #11
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def run_with_cmdline_args(args):
    cfg, output_dir, runner = prepare_for_launch(args)
    inference_config = None
    if args.inference_config_file:
        inference_config = CfgNode(
            CfgNode.load_yaml_with_base(args.inference_config_file))

    return main(
        cfg,
        output_dir,
        runner,
        # binary specific optional arguments
        predictor_types=args.predictor_types,
        compare_accuracy=args.compare_accuracy,
        skip_if_fail=args.skip_if_fail,
        inference_config=inference_config,
    )
Пример #12
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 def _get_default_config():
     cfg = CfgNode()
     cfg.INPUT = CfgNode()
     cfg.INPUT.CROP = CfgNode()
     cfg.INPUT.CROP.ENABLED = False
     cfg.INPUT.CROP.SIZE = (0.9, 0.9)
     cfg.INPUT.CROP.TYPE = "relative_range"
     cfg.MODEL = CfgNode()
     cfg.MODEL.MIN_DIM_SIZE = 360
     cfg.INFERENCE_SDK = CfgNode()
     cfg.INFERENCE_SDK.MODEL = CfgNode()
     cfg.INFERENCE_SDK.MODEL.SCORE_THRESHOLD = 0.8
     cfg.INFERENCE_SDK.IOU_TRACKER = CfgNode()
     cfg.INFERENCE_SDK.IOU_TRACKER.IOU_THRESHOLD = 0.15
     cfg.INFERENCE_SDK.ENABLE_ID_TRACKING = True
     return cfg
Пример #13
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def get_default_config():
    cfg = CfgNode()
    cfg.D2GO_DATA = CfgNode()
    cfg.D2GO_DATA.AUG_OPS = CfgNode()
    return cfg
Пример #14
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 def _test2(cfg):
     cfg.TEST2 = CfgNode()
     cfg.TEST2.Y = 2
     return cfg
Пример #15
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 def _test1(cfg):
     cfg.TEST1 = CfgNode()
     cfg.TEST1.X = 1
     return cfg