Python caffe2.python.core.config() Examples

The following are 14 code examples of caffe2.python.core.config(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module caffe2.python.core , or try the search function .
Example #1
Source File: net.py    From seg_every_thing with Apache License 2.0 6 votes vote down vote up 
def configure_bbox_reg_weights(model, saved_cfg):
    """Compatibility for old models trained with bounding box regression
    mean/std normalization (instead of fixed weights).
    """
    if 'MODEL' not in saved_cfg or 'BBOX_REG_WEIGHTS' not in saved_cfg.MODEL:
        logger.warning('Model from weights file was trained before config key '
                       'MODEL.BBOX_REG_WEIGHTS was added. Forcing '
                       'MODEL.BBOX_REG_WEIGHTS = (1., 1., 1., 1.) to ensure '
                       'correct **inference** behavior.')
        # Generally we don't allow modifying the config, but this is a one-off
        # hack to support some very old models
        is_immutable = cfg.is_immutable()
        cfg.immutable(False)
        cfg.MODEL.BBOX_REG_WEIGHTS = (1., 1., 1., 1.)
        cfg.immutable(is_immutable)
        logger.info('New config:')
        logger.info(pprint.pformat(cfg))
        assert not model.train, (
            'This model was trained with an older version of the code that '
            'used bounding box regression mean/std normalization. It can no '
            'longer be used for training. To upgrade it to a trainable model '
            'please use fb/compat/convert_bbox_reg_normalized_model.py.'
        )
Example #2
Source File: test_proposal_target.py    From masktextspotter.caffe2 with Apache License 2.0 6 votes vote down vote up 
def parse_args():
    parser = argparse.ArgumentParser(
        description='Train a network with Detectron'
    )
    parser.add_argument(
        '--cfg',
        dest='cfg_file',
        help='Config file for training (and optionally testing)',
        default=None,
        type=str
    )
    parser.add_argument(
        'opts',
        help='See lib/core/config.py for all options',
        default=None,
        nargs=argparse.REMAINDER
    )
    if len(sys.argv) == 1:
        parser.print_help()
        sys.exit(1)
    return parser.parse_args()
Example #3
Source File: net.py    From masktextspotter.caffe2 with Apache License 2.0 6 votes vote down vote up 
def configure_bbox_reg_weights(model, saved_cfg):
    """Compatibility for old models trained with bounding box regression
    mean/std normalization (instead of fixed weights).
    """
    if 'MODEL' not in saved_cfg or 'BBOX_REG_WEIGHTS' not in saved_cfg.MODEL:
        logger.warning('Model from weights file was trained before config key '
                       'MODEL.BBOX_REG_WEIGHTS was added. Forcing '
                       'MODEL.BBOX_REG_WEIGHTS = (1., 1., 1., 1.) to ensure '
                       'correct **inference** behavior.')
        cfg.MODEL.BBOX_REG_WEIGHTS = (1., 1., 1., 1.)
        logger.info('New config:')
        logger.info(pprint.pformat(cfg))
        assert not model.train, (
            'This model was trained with an older version of the code that '
            'used bounding box regression mean/std normalization. It can no '
            'longer be used for training. To upgrade it to a trainable model '
            'please use fb/compat/convert_bbox_reg_normalized_model.py.'
        )
Example #4
Source File: net.py    From NucleiDetectron with Apache License 2.0 6 votes vote down vote up 
def configure_bbox_reg_weights(model, saved_cfg):
    """Compatibility for old models trained with bounding box regression
    mean/std normalization (instead of fixed weights).
    """
    if 'MODEL' not in saved_cfg or 'BBOX_REG_WEIGHTS' not in saved_cfg.MODEL:
        logger.warning('Model from weights file was trained before config key '
                       'MODEL.BBOX_REG_WEIGHTS was added. Forcing '
                       'MODEL.BBOX_REG_WEIGHTS = (1., 1., 1., 1.) to ensure '
                       'correct **inference** behavior.')
        cfg.MODEL.BBOX_REG_WEIGHTS = (1., 1., 1., 1.)
        logger.info('New config:')
        logger.info(pprint.pformat(cfg))
        assert not model.train, (
            'This model was trained with an older version of the code that '
            'used bounding box regression mean/std normalization. It can no '
            'longer be used for training. To upgrade it to a trainable model '
            'please use fb/compat/convert_bbox_reg_normalized_model.py.'
        )
Example #5
Source File: test_on_single_video.py    From DetectAndTrack with Apache License 2.0 6 votes vote down vote up 
def parse_args():
    parser = argparse.ArgumentParser(description='Run DetectandTrack on a single video and visualize the results')
    parser.add_argument(
        '--cfg', '-c', dest='cfg_file', required=True,
        help='Config file to run')
    parser.add_argument(
        '--video', '-v', dest='video_path',
        help='Path to Video',
        required=True)
    parser.add_argument(
        '--output', '-o', dest='out_path',
        help='Path to Output')
    parser.add_argument(
        'opts', help='See lib/core/config.py for all options', default=None,
        nargs=argparse.REMAINDER)
    if len(sys.argv) == 1:
        parser.print_help()
        sys.exit(1)
    return parser.parse_args()
Example #6
Source File: net.py    From DetectAndTrack with Apache License 2.0 5 votes vote down vote up 
def configure_bbox_reg_weights(model, saved_cfg):
    if 'MODEL' not in saved_cfg or 'BBOX_REG_WEIGHTS' not in saved_cfg.MODEL:
        logger.warning('Model from weights file was trained before config key '
                       'MODEL.BBOX_REG_WEIGHTS was added. Forcing '
                       'MODEL.BBOX_REG_WEIGHTS = (1., 1., 1., 1.) to ensure '
                       'correct **inference** behavior.')
        cfg.MODEL.BBOX_REG_WEIGHTS = (1., 1., 1., 1.)
        logger.info('New config:')
        logger.info(pprint.pformat(cfg))
        assert not model.train, 'This mode should only be used for inference'
Example #7
Source File: data_loader_benchmark.py    From seg_every_thing with Apache License 2.0 4 votes vote down vote up 
def parse_args():
    parser = argparse.ArgumentParser()
    parser.add_argument(
        '--loaders', dest='num_loaders',
        help='Number of data loading threads',
        default=4, type=int)
    parser.add_argument(
        '--dequeuers', dest='num_dequeuers',
        help='Number of dequeuers',
        default=1, type=int)
    parser.add_argument(
        '--minibatch-queue-size', dest='minibatch_queue_size',
        help='Size of minibatch queue',
        default=64, type=int)
    parser.add_argument(
        '--blobs-queue-capacity', dest='blobs_queue_capacity',
        default=8, type=int)
    parser.add_argument(
        '--num-batches', dest='num_batches',
        help='Number of minibatches to run',
        default=200, type=int)
    parser.add_argument(
        '--sleep', dest='sleep_time',
        help='Seconds sleep to emulate a network running',
        default=0.1, type=float)
    parser.add_argument(
        '--cfg', dest='cfg_file', help='optional config file', default=None,
        type=str)
    parser.add_argument(
        '--x-factor', dest='x_factor', help='simulates x-factor more GPUs',
        default=1, type=int)
    parser.add_argument(
        '--profiler', dest='profiler', help='profile minibatch load time',
        action='store_true')
    parser.add_argument(
        'opts', help='See lib/core/config.py for all options', default=None,
        nargs=argparse.REMAINDER)
    if len(sys.argv) == 1:
        parser.print_help()
        sys.exit(1)
    args = parser.parse_args()
    return args
Example #8
Source File: convert_pkl_to_pb.py    From seg_every_thing with Apache License 2.0 4 votes vote down vote up 
def parse_args():
    parser = argparse.ArgumentParser(
        description='Convert a trained network to pb format'
    )
    parser.add_argument(
        '--cfg', dest='cfg_file', help='optional config file', default=None,
        type=str)
    parser.add_argument(
        '--net_name', dest='net_name', help='optional name for the net',
        default="detectron", type=str)
    parser.add_argument(
        '--out_dir', dest='out_dir', help='output dir', default=None,
        type=str)
    parser.add_argument(
        '--test_img', dest='test_img',
        help='optional test image, used to verify the model conversion',
        default=None,
        type=str)
    parser.add_argument(
        '--fuse_af', dest='fuse_af', help='1 to fuse_af',
        default=1,
        type=int)
    parser.add_argument(
        '--device', dest='device',
        help='Device to run the model on',
        choices=['cpu', 'gpu'],
        default='cpu',
        type=str)
    parser.add_argument(
        '--net_execution_type', dest='net_execution_type',
        help='caffe2 net execution type',
        choices=['simple', 'dag'],
        default='simple',
        type=str)
    parser.add_argument(
        '--use_nnpack', dest='use_nnpack',
        help='Use nnpack for conv',
        default=1,
        type=int)
    parser.add_argument(
        'opts', help='See lib/core/config.py for all options', default=None,
        nargs=argparse.REMAINDER)
    if len(sys.argv) == 1:
        parser.print_help()
        sys.exit(1)
    ret = parser.parse_args()
    ret.out_dir = os.path.abspath(ret.out_dir)
    if ret.device == 'gpu' and ret.use_nnpack:
        logger.warn('Should not use mobile engine for gpu model.')
        ret.use_nnpack = 0

    return ret
Example #9
Source File: convert_pkl_to_pb.py    From seg_every_thing with Apache License 2.0 4 votes vote down vote up 
def main():
    workspace.GlobalInit(['caffe2', '--caffe2_log_level=0'])
    args = parse_args()
    logger.info('Called with args:')
    logger.info(args)
    if args.cfg_file is not None:
        merge_cfg_from_file(args.cfg_file)
    if args.opts is not None:
        merge_cfg_from_list(args.opts)
    cfg.NUM_GPUS = 1
    assert_and_infer_cfg()
    logger.info('Conerting model with config:')
    logger.info(pprint.pformat(cfg))

    assert not cfg.MODEL.KEYPOINTS_ON, "Keypoint model not supported."
    assert not cfg.MODEL.MASK_ON, "Mask model not supported."
    assert not cfg.FPN.FPN_ON, "FPN not supported."
    assert not cfg.RETINANET.RETINANET_ON, "RetinaNet model not supported."

    # load model from cfg
    model, blobs = load_model(args)

    net = core.Net('')
    net.Proto().op.extend(copy.deepcopy(model.net.Proto().op))
    net.Proto().external_input.extend(
        copy.deepcopy(model.net.Proto().external_input))
    net.Proto().external_output.extend(
        copy.deepcopy(model.net.Proto().external_output))
    net.Proto().type = args.net_execution_type
    net.Proto().num_workers = 1 if args.net_execution_type == 'simple' else 4

    # Reset the device_option, change to unscope name and replace python operators
    convert_net(args, net.Proto(), blobs)

    # add operators for bbox
    add_bbox_ops(args, net, blobs)

    if args.fuse_af:
        print('Fusing affine channel...')
        net, blobs = mutils.fuse_net_affine(
            net, blobs)

    if args.use_nnpack:
        mutils.update_mobile_engines(net.Proto())

    # generate init net
    empty_blobs = ['data', 'im_info']
    init_net = gen_init_net(net, blobs, empty_blobs)

    if args.device == 'gpu':
        [net, init_net] = convert_model_gpu(args, net, init_net)

    net.Proto().name = args.net_name
    init_net.Proto().name = args.net_name + "_init"

    if args.test_img is not None:
        verify_model(args, [net, init_net], args.test_img)

    _save_models(net, init_net, args)
Example #10
Source File: data_loader_benchmark.py    From masktextspotter.caffe2 with Apache License 2.0 4 votes vote down vote up 
def parse_args():
    parser = argparse.ArgumentParser()
    parser.add_argument(
        '--loaders', dest='num_loaders',
        help='Number of data loading threads',
        default=4, type=int)
    parser.add_argument(
        '--dequeuers', dest='num_dequeuers',
        help='Number of dequeuers',
        default=1, type=int)
    parser.add_argument(
        '--minibatch-queue-size', dest='minibatch_queue_size',
        help='Size of minibatch queue',
        default=64, type=int)
    parser.add_argument(
        '--blobs-queue-capacity', dest='blobs_queue_capacity',
        default=8, type=int)
    parser.add_argument(
        '--num-batches', dest='num_batches',
        help='Number of minibatches to run',
        default=500, type=int)
    parser.add_argument(
        '--sleep', dest='sleep_time',
        help='Seconds sleep to emulate a network running',
        default=0.1, type=float)
    parser.add_argument(
        '--cfg', dest='cfg_file', help='optional config file', default=None,
        type=str)
    parser.add_argument(
        '--x-factor', dest='x_factor', help='simulates x-factor more GPUs',
        default=1, type=int)
    parser.add_argument(
        '--profiler', dest='profiler', help='profile minibatch load time',
        action='store_true')
    parser.add_argument(
        'opts', help='See lib/core/config.py for all options', default=None,
        nargs=argparse.REMAINDER)
    if len(sys.argv) == 1:
        parser.print_help()
        sys.exit(1)
    args = parser.parse_args()
    return args
Example #11
Source File: data_loader_benchmark.py    From NucleiDetectron with Apache License 2.0 4 votes vote down vote up 
def parse_args():
    parser = argparse.ArgumentParser()
    parser.add_argument(
        '--loaders', dest='num_loaders',
        help='Number of data loading threads',
        default=4, type=int)
    parser.add_argument(
        '--dequeuers', dest='num_dequeuers',
        help='Number of dequeuers',
        default=1, type=int)
    parser.add_argument(
        '--minibatch-queue-size', dest='minibatch_queue_size',
        help='Size of minibatch queue',
        default=64, type=int)
    parser.add_argument(
        '--blobs-queue-capacity', dest='blobs_queue_capacity',
        default=8, type=int)
    parser.add_argument(
        '--num-batches', dest='num_batches',
        help='Number of minibatches to run',
        default=500, type=int)
    parser.add_argument(
        '--sleep', dest='sleep_time',
        help='Seconds sleep to emulate a network running',
        default=0.1, type=float)
    parser.add_argument(
        '--cfg', dest='cfg_file', help='optional config file', default=None,
        type=str)
    parser.add_argument(
        '--x-factor', dest='x_factor', help='simulates x-factor more GPUs',
        default=1, type=int)
    parser.add_argument(
        '--profiler', dest='profiler', help='profile minibatch load time',
        action='store_true')
    parser.add_argument(
        'opts', help='See lib/core/config.py for all options', default=None,
        nargs=argparse.REMAINDER)
    if len(sys.argv) == 1:
        parser.print_help()
        sys.exit(1)
    args = parser.parse_args()
    return args
Example #12
Source File: convert_pkl_to_pb.py    From NucleiDetectron with Apache License 2.0 4 votes vote down vote up 
def parse_args():
    parser = argparse.ArgumentParser(
        description='Convert a trained network to pb format'
    )
    parser.add_argument(
        '--cfg', dest='cfg_file', help='optional config file', default=None,
        type=str)
    parser.add_argument(
        '--net_name', dest='net_name', help='optional name for the net',
        default="detectron", type=str)
    parser.add_argument(
        '--out_dir', dest='out_dir', help='output dir', default=None,
        type=str)
    parser.add_argument(
        '--test_img', dest='test_img',
        help='optional test image, used to verify the model conversion',
        default=None,
        type=str)
    parser.add_argument(
        '--fuse_af', dest='fuse_af', help='1 to fuse_af',
        default=1,
        type=int)
    parser.add_argument(
        '--device', dest='device',
        help='Device to run the model on',
        choices=['cpu', 'gpu'],
        default='cpu',
        type=str)
    parser.add_argument(
        '--net_execution_type', dest='net_execution_type',
        help='caffe2 net execution type',
        choices=['simple', 'dag'],
        default='simple',
        type=str)
    parser.add_argument(
        '--use_nnpack', dest='use_nnpack',
        help='Use nnpack for conv',
        default=1,
        type=int)
    parser.add_argument(
        'opts', help='See lib/core/config.py for all options', default=None,
        nargs=argparse.REMAINDER)
    if len(sys.argv) == 1:
        parser.print_help()
        sys.exit(1)
    ret = parser.parse_args()
    ret.out_dir = os.path.abspath(ret.out_dir)
    if ret.device == 'gpu' and ret.use_nnpack:
        logger.warn('Should not use mobile engine for gpu model.')
        ret.use_nnpack = 0

    return ret
Example #13
Source File: convert_pkl_to_pb.py    From NucleiDetectron with Apache License 2.0 4 votes vote down vote up 
def main():
    workspace.GlobalInit(['caffe2', '--caffe2_log_level=0'])
    args = parse_args()
    logger.info('Called with args:')
    logger.info(args)
    if args.cfg_file is not None:
        merge_cfg_from_file(args.cfg_file)
    if args.opts is not None:
        merge_cfg_from_list(args.opts)
    cfg.NUM_GPUS = 1
    assert_and_infer_cfg()
    logger.info('Conerting model with config:')
    logger.info(pprint.pformat(cfg))

    assert not cfg.MODEL.KEYPOINTS_ON, "Keypoint model not supported."
    assert not cfg.MODEL.MASK_ON, "Mask model not supported."
    assert not cfg.FPN.FPN_ON, "FPN not supported."
    assert not cfg.RETINANET.RETINANET_ON, "RetinaNet model not supported."

    # load model from cfg
    model, blobs = load_model(args)

    net = core.Net('')
    net.Proto().op.extend(copy.deepcopy(model.net.Proto().op))
    net.Proto().external_input.extend(
        copy.deepcopy(model.net.Proto().external_input))
    net.Proto().external_output.extend(
        copy.deepcopy(model.net.Proto().external_output))
    net.Proto().type = args.net_execution_type
    net.Proto().num_workers = 1 if args.net_execution_type == 'simple' else 4

    # Reset the device_option, change to unscope name and replace python operators
    convert_net(args, net.Proto(), blobs)

    # add operators for bbox
    add_bbox_ops(args, net, blobs)

    if args.fuse_af:
        print('Fusing affine channel...')
        net, blobs = mutils.fuse_net_affine(
            net, blobs)

    if args.use_nnpack:
        mutils.update_mobile_engines(net.Proto())

    # generate init net
    empty_blobs = ['data', 'im_info']
    init_net = gen_init_net(net, blobs, empty_blobs)

    if args.device == 'gpu':
        [net, init_net] = convert_model_gpu(args, net, init_net)

    net.Proto().name = args.net_name
    init_net.Proto().name = args.net_name + "_init"

    if args.test_img is not None:
        verify_model(args, [net, init_net], args.test_img)

    _save_models(net, init_net, args)
Example #14
Source File: data_loader_benchmark.py    From DetectAndTrack with Apache License 2.0 4 votes vote down vote up 
def parse_args():
    parser = argparse.ArgumentParser()
    parser.add_argument(
        '--loaders', dest='num_loaders',
        help='Number of data loading threads',
        default=4, type=int)
    parser.add_argument(
        '--dequeuers', dest='num_dequeuers',
        help='Number of dequeuers',
        default=1, type=int)
    parser.add_argument(
        '--minibatch-queue-size', dest='minibatch_queue_size',
        help='Size of minibatch queue',
        default=64, type=int)
    parser.add_argument(
        '--blobs-queue-capacity', dest='blobs_queue_capacity',
        default=8, type=int)
    parser.add_argument(
        '--num-batches', dest='num_batches',
        help='Number of minibatches to run',
        default=200, type=int)
    parser.add_argument(
        '--sleep', dest='sleep_time',
        help='Seconds sleep to emulate a network running',
        default=0.1, type=float)
    parser.add_argument(
        '--cfg', dest='cfg_file', help='optional config file', default=None,
        type=str)
    parser.add_argument(
        '--x-factor', dest='x_factor', help='simulates x-factor more GPUs',
        default=1, type=int)
    parser.add_argument(
        '--profiler', dest='profiler', help='profile minibatch load time',
        action='store_true')
    parser.add_argument(
        'opts', help='See lib/core/config.py for all options', default=None,
        nargs=argparse.REMAINDER)
    if len(sys.argv) == 1:
        parser.print_help()
        sys.exit(1)
    args = parser.parse_args()
    return args