Python ndarray.load方法代码示例

本文整理汇总了Python中mxnet.ndarray.load方法的典型用法代码示例。如果您正苦于以下问题：Python ndarray.load方法的具体用法？Python ndarray.load怎么用？Python ndarray.load使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类mxnet.ndarray的用法示例。

在下文中一共展示了ndarray.load方法的13个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: load_params

# 需要导入模块: from mxnet import ndarray [as 别名]
# 或者: from mxnet.ndarray import load [as 别名]
def load_params(dir_path="", epoch=None, name=""):
    prefix = os.path.join(dir_path, name)
    _, param_loading_path, _ = get_saving_path(prefix, epoch)
    while not os.path.isfile(param_loading_path):
        logging.info("in load_param, %s Not Found!" % param_loading_path)
        time.sleep(60)
    save_dict = nd.load(param_loading_path)
    arg_params = {}
    aux_params = {}
    for k, v in save_dict.items():
        tp, name = k.split(':', 1)
        if tp == 'arg':
            arg_params[name] = v
        if tp == 'aux':
            aux_params[name] = v
    return arg_params, aux_params, param_loading_path

开发者ID:awslabs，项目名称:dynamic-training-with-apache-mxnet-on-aws，代码行数:18，代码来源:utils.py

示例2: load_misc

# 需要导入模块: from mxnet import ndarray [as 别名]
# 或者: from mxnet.ndarray import load [as 别名]
def load_misc(dir_path="", epoch=None, name=""):
    prefix = os.path.join(dir_path, name)
    _, _, misc_saving_path = get_saving_path(prefix, epoch)
    with open(misc_saving_path, 'r') as fp:
        misc = json.load(fp)
    return misc

开发者ID:awslabs，项目名称:dynamic-training-with-apache-mxnet-on-aws，代码行数:8，代码来源:utils.py

示例3: load_npz

# 需要导入模块: from mxnet import ndarray [as 别名]
# 或者: from mxnet.ndarray import load [as 别名]
def load_npz(path):
    with numpy.load(path) as data:
        ret = {k: data[k] for k in data.keys()}
        return ret

开发者ID:awslabs，项目名称:dynamic-training-with-apache-mxnet-on-aws，代码行数:6，代码来源:utils.py

示例4: _try_load_parameters

# 需要导入模块: from mxnet import ndarray [as 别名]
# 或者: from mxnet.ndarray import load [as 别名]
def _try_load_parameters(self, filename=None, model=None, ctx=None, allow_missing=False,
                         ignore_extra=False):
    def getblock(parent, name):
        if len(name) == 1:
            if name[0].isnumeric():
                return parent[int(name[0])]
            else:
                return getattr(parent, name[0])
        else:
            if name[0].isnumeric():
                return getblock(parent[int(name[0])], name[1:])
            else:
                return getblock(getattr(parent, name[0]), name[1:])
    if filename is not None:
        loaded = ndarray.load(filename)
    else:
        loaded = {k: v.data() for k, v in model._collect_params_with_prefix().items()}
    params = self._collect_params_with_prefix()
    if not loaded and not params:
        return

    if not any('.' in i for i in loaded.keys()):
        # legacy loading
        del loaded
        self.collect_params().load(
            filename, ctx, allow_missing, ignore_extra, self.prefix)
        return

    for name in loaded:
        if name in params:
            if params[name].shape != loaded[name].shape:
                continue
            params[name]._load_init(loaded[name], ctx)

开发者ID:dmlc，项目名称:gluon-cv，代码行数:35，代码来源:utils.py

示例5: _load_from_pytorch

# 需要导入模块: from mxnet import ndarray [as 别名]
# 或者: from mxnet.ndarray import load [as 别名]
def _load_from_pytorch(self, filename, ctx=None):
    import torch
    from mxnet import nd
    loaded = torch.load(filename)
    params = self._collect_params_with_prefix()

    new_params = {}

    for name in loaded:
        if 'bn' in name or 'batchnorm' in name or '.downsample.1.' in name:
            if 'weight' in name:
                mxnet_name = name.replace('weight', 'gamma')
            elif 'bias' in name:
                mxnet_name = name.replace('bias', 'beta')
            else:
                mxnet_name = name
            new_params[mxnet_name] = nd.array(loaded[name].cpu().data.numpy())
        else:
            new_params[name] = nd.array(loaded[name].cpu().data.numpy())

    for name in new_params:
        if name not in params:
            print('==={}==='.format(name))
            raise Exception
        if name in params:
            params[name]._load_init(new_params[name], ctx=ctx)

开发者ID:dmlc，项目名称:gluon-cv，代码行数:28，代码来源:utils.py

示例6: resnet18_v1b_89

# 需要导入模块: from mxnet import ndarray [as 别名]
# 或者: from mxnet.ndarray import load [as 别名]
def resnet18_v1b_89(pretrained=False, root='~/.mxnet/models', ctx=cpu(0), **kwargs):
    """Constructs a ResNetV1b-18_2.6x model. Uses resnet18_v1b construction from resnetv1b.py

    Parameters
    ----------
    pretrained : bool or str
        Boolean value controls whether to load the default pretrained weights for model.
        String value represents the hashtag for a certain version of pretrained weights.
    root : str, default '~/.mxnet/models'
        Location for keeping the model parameters.
    ctx : Context, default CPU
        The context in which to load the pretrained weights.
    """
    model = ResNetV1b(BasicBlockV1b, [2, 2, 2, 2], name_prefix='resnetv1b_', **kwargs)
    dirname = os.path.dirname(__file__)
    json_filename = os.path.join(dirname, 'resnet%d_v%db_%.1fx' % (18, 1, 2.6) + ".json")
    with open(json_filename, "r") as jsonFile:
        params_shapes = json.load(jsonFile)
    if pretrained:
        from ..model_store import get_model_file
        params_file = get_model_file('resnet%d_v%db_%.1fx' % (18, 1, 2.6), tag=pretrained,
                                     root=root)
        prune_gluon_block(model, model.name, params_shapes, params=ndarray.load(params_file),
                          pretrained=True, ctx=ctx)
    else:
        prune_gluon_block(model, model.name, params_shapes, params=None, pretrained=False, ctx=ctx)
    if pretrained:
        from ...data import ImageNet1kAttr
        attrib = ImageNet1kAttr()
        model.synset = attrib.synset
        model.classes = attrib.classes
        model.classes_long = attrib.classes_long
    return model

开发者ID:dmlc，项目名称:gluon-cv，代码行数:35，代码来源:resnetv1b_pruned.py