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Fix docstring (#913)

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* Fix docstring

* fix
This commit is contained in:
Zaida Zhou 2023-02-13 16:10:53 +08:00 committed by GitHub
parent c712070c90
commit ad0b296fd4
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20 changed files with 92 additions and 89 deletions
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22
mmengine/fileio/file_client.py
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@ -43,9 +43,9 @@ class FileClient:
Args:
backend (str, optional): The storage backend type. Options are "disk",
"memcached", "lmdb", "http" and "petrel". Default: None.
"memcached", "lmdb", "http" and "petrel". Defaults to None.
prefix (str, optional): The prefix of the registered storage backend.
Options are "s3", "http", "https". Default: None.
Options are "s3", "http", "https". Defaults to None.
Examples:
>>> # only set backend
@ -163,9 +163,9 @@ class FileClient:
Args:
file_client_args (dict, optional): Arguments to instantiate a
FileClient. Default: None.
FileClient. Defaults to None.
uri (str | Path, optional): Uri to be parsed that contains the file
prefix. Default: None.
prefix. Defaults to None.
Examples:
>>> uri = 's3://path/of/your/file'
@ -263,7 +263,7 @@ class FileClient:
force (bool, optional): Whether to override the backend if the name
has already been registered. Defaults to False.
prefixes (str or list[str] or tuple[str], optional): The prefixes
of the registered storage backend. Default: None.
of the registered storage backend. Defaults to None.
`New in version 1.3.15.`
"""
if backend is not None:
@ -302,7 +302,7 @@ class FileClient:
Args:
filepath (str or Path): Path to read data.
encoding (str): The encoding format used to open the ``filepath``.
Default: 'utf-8'.
Defaults to 'utf-8'.
Returns:
str: Expected text reading from ``filepath``.
@ -333,7 +333,7 @@ class FileClient:
obj (str): Data to be written.
filepath (str or Path): Path to write data.
encoding (str, optional): The encoding format used to open the
`filepath`. Default: 'utf-8'.
`filepath`. Defaults to 'utf-8'.
"""
self.client.put_text(obj, filepath)
@ -442,12 +442,12 @@ class FileClient:
Args:
dir_path (str | Path): Path of the directory.
list_dir (bool): List the directories. Default: True.
list_file (bool): List the path of files. Default: True.
list_dir (bool): List the directories. Defaults to True.
list_file (bool): List the path of files. Defaults to True.
suffix (str or tuple[str], optional): File suffix
that we are interested in. Default: None.
that we are interested in. Defaults to None.
recursive (bool): If set to True, recursively scan the
directory. Default: False.
directory. Defaults to False.
Yields:
Iterable[str]: A relative path to ``dir_path``.

4
mmengine/fileio/io.py
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@ -776,8 +776,8 @@ def generate_presigned_url(
Args:
url (str): Url of video stream.
client_method (str): Method of client, 'get_object' or
'put_object'. Default: 'get_object'.
expires_in (int): expires, in seconds. Default: 3600.
'put_object'. Defaults to 'get_object'.
expires_in (int): expires, in seconds. Defaults to 3600.
backend_args (dict, optional): Arguments to instantiate the
corresponding backend. Defaults to None.

2
mmengine/hooks/logger_hook.py
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@ -62,7 +62,7 @@ class LoggerHook(Hook):
by epoch. It can be true when running in epoch based runner.
If set to True, `after_val_epoch` will set `step` to self.epoch in
`runner.visualizer.add_scalars`. Otherwise `step` will be
self.iter. Default to True.
self.iter. Defaults to True.
backend_args (dict, optional): Arguments to instantiate the
preifx of uri corresponding backend. Defaults to None.
New in v0.2.0.

4
mmengine/hooks/naive_visualization_hook.py
View File

@ -20,9 +20,9 @@ class NaiveVisualizationHook(Hook):
Args:
interval (int): Visualization interval. Defaults to 1.
draw_gt (bool): Whether to draw the ground truth. Default to True.
draw_gt (bool): Whether to draw the ground truth. Defaults to True.
draw_pred (bool): Whether to draw the predicted result.
Default to True.
Defaults to True.
"""
priority = 'NORMAL'

2
mmengine/optim/optimizer/default_constructor.py
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@ -51,7 +51,7 @@ class DefaultOptimWrapperConstructor:
rate for parameters of offset layer in the deformable convs
of a model.
- ``bypass_duplicate`` (bool): If true, the duplicate parameters
would not be added into optimizer. Default: False.
would not be added into optimizer. Defaults to False.
Note:

2
mmengine/optim/optimizer/optimizer_wrapper.py
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@ -43,7 +43,7 @@ class OptimWrapper:
``'inf'`` for infinity norm.
- error_if_nonfinite (bool): If True, an error is thrown if
the total norm of the gradients from :attr:`parameters` is
``nan``, ``inf``, or ``-inf``. Default: False (will switch
``nan``, ``inf``, or ``-inf``. Defaults to False (will switch
to True in the future)
If the key ``type`` is set to "value", the accepted keys are as

12
mmengine/optim/scheduler/lr_scheduler.py
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@ -260,20 +260,20 @@ class OneCycleLR(LRSchedulerMixin, OneCycleParamScheduler):
total_steps (int): The total number of steps in the cycle. Note that
if a value is not provided here, then it must be inferred by
providing a value for epochs and steps_per_epoch.
Default to None.
Defaults to None.
pct_start (float): The percentage of the cycle (in number of steps)
spent increasing the learning rate.
Default to 0.3
Defaults to 0.3
anneal_strategy (str): {'cos', 'linear'}
Specifies the annealing strategy: "cos" for cosine annealing,
"linear" for linear annealing.
Default to 'cos'
Defaults to 'cos'
div_factor (float): Determines the initial learning rate via
initial_param = eta_max/div_factor
Default to 25
Defaults to 25
final_div_factor (float): Determines the minimum learning rate via
eta_min = initial_param/final_div_factor
Default to 1e4
Defaults to 1e4
three_phase (bool): If ``True``, use a third phase of the schedule to
annihilate the learning rate according to 'final_div_factor'
instead of modifying the second phase (the first two phases will be
@ -308,7 +308,7 @@ class CosineRestartLR(LRSchedulerMixin, CosineRestartParamScheduler):
Defaults to None.
eta_min_ratio (float, optional): The ratio of minimum parameter value
to the base parameter value. Either `min_lr` or `min_lr_ratio`
should be specified. Default: None.
should be specified. Defaults to None.
begin (int): Step at which to start updating the parameters.
Defaults to 0.
end (int): Step at which to stop updating the parameters.

2
mmengine/optim/scheduler/momentum_scheduler.py
View File

@ -274,7 +274,7 @@ class CosineRestartMomentum(MomentumSchedulerMixin,
Defaults to None.
eta_min_ratio (float, optional): The ratio of minimum parameter value
to the base parameter value. Either `min_lr` or `min_lr_ratio`
should be specified. Default: None.
should be specified. Defaults to None.
begin (int): Step at which to start updating the parameters.
Defaults to 0.
end (int): Step at which to stop updating the parameters.

10
mmengine/optim/scheduler/param_scheduler.py
View File

@ -924,20 +924,20 @@ class OneCycleParamScheduler(_ParamScheduler):
for each parameter group.
total_steps (int): The total number of steps in the cycle. Note that
if a value is not provided here, then it will be equal to
``end - begin``. Default to None
``end - begin``. Defaults to None
pct_start (float): The percentage of the cycle (in number of steps)
spent increasing the learning rate.
Default to 0.3
Defaults to 0.3
anneal_strategy (str): {'cos', 'linear'}
Specifies the annealing strategy: "cos" for cosine annealing,
"linear" for linear annealing.
Default to 'cos'
Defaults to 'cos'
div_factor (float): Determines the initial learning rate via
initial_param = eta_max/div_factor
Default to 25
Defaults to 25
final_div_factor (float): Determines the minimum learning rate via
eta_min = initial_param/final_div_factor
Default to 1e4
Defaults to 1e4
three_phase (bool): If ``True``, use a third phase of the schedule to
annihilate the learning rate according to 'final_div_factor'
instead of modifying the second phase (the first two phases will be

2
mmengine/registry/registry.py
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@ -594,7 +594,7 @@ class Registry:
name (str or list of str, optional): The module name to be
registered. If not specified, the class name will be used.
force (bool): Whether to override an existing class with the same
name. Default to False.
name. Defaults to False.
module (type, optional): Module class or function to be registered.
Defaults to None.

2
mmengine/registry/utils.py
View File

@ -17,7 +17,7 @@ def traverse_registry_tree(registry: Registry, verbose: bool = True) -> list:
Args:
registry (Registry): a registry node in the registry tree.
verbose (bool): Whether to print log. Default: True
verbose (bool): Whether to print log. Defaults to True
Returns:
list: Statistic results of all modules in each node of the registry

21
mmengine/runner/checkpoint.py
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@ -56,7 +56,7 @@ def load_state_dict(module, state_dict, strict=False, logger=None):
state_dict (OrderedDict): Weights.
strict (bool): whether to strictly enforce that the keys
in :attr:`state_dict` match the keys returned by this module's
:meth:`~torch.nn.Module.state_dict` function. Default: ``False``.
:meth:`~torch.nn.Module.state_dict` function. Defaults to False.
logger (:obj:`logging.Logger`, optional): Logger to log the error
message. If not specified, print function will be used.
"""
@ -285,7 +285,7 @@ class CheckpointLoader:
Args:
filename (str): checkpoint file name with given prefix
map_location (str, optional): Same as :func:`torch.load`.
Default: None
Defaults to None
logger (str): The logger for message. Defaults to 'current'.
Returns:
@ -332,7 +332,7 @@ def load_from_http(filename,
torchvision prefix
map_location (str, optional): Same as :func:`torch.load`.
model_dir (string, optional): directory in which to save the object,
Default: None
Defaults to None
Returns:
dict or OrderedDict: The loaded checkpoint.
@ -364,7 +364,7 @@ def load_from_pavi(filename, map_location=None):
Args:
filename (str): checkpoint file path with pavi prefix
map_location (str, optional): Same as :func:`torch.load`.
Default: None
Defaults to None
Returns:
dict or OrderedDict: The loaded checkpoint.
@ -443,7 +443,7 @@ def load_from_openmmlab(filename, map_location=None):
filename (str): checkpoint file path with open-mmlab or
openmmlab prefix
map_location (str, optional): Same as :func:`torch.load`.
Default: None
Defaults to None
Returns:
dict or OrderedDict: The loaded checkpoint.
@ -504,9 +504,9 @@ def _load_checkpoint(filename, map_location=None, logger=None):
``open-mmlab://xxx``. Please refer to ``docs/model_zoo.md`` for
details.
map_location (str, optional): Same as :func:`torch.load`.
Default: None.
Defaults to None.
logger (:mod:`logging.Logger`, optional): The logger for error message.
Default: None
Defaults to None
Returns:
dict or OrderedDict: The loaded checkpoint. It can be either an
@ -524,7 +524,8 @@ def _load_checkpoint_with_prefix(prefix, filename, map_location=None):
filename (str): Accept local filepath, URL, ``torchvision://xxx``,
``open-mmlab://xxx``. Please refer to ``docs/model_zoo.md`` for
details.
map_location (str | None): Same as :func:`torch.load`. Default: None.
map_location (str | None): Same as :func:`torch.load`.
Defaults to None.
Returns:
dict or OrderedDict: The loaded checkpoint.
@ -594,7 +595,7 @@ def load_checkpoint(model,
logger (:mod:`logging.Logger` or None): The logger for error message.
revise_keys (list): A list of customized keywords to modify the
state_dict in checkpoint. Each item is a (pattern, replacement)
pair of the regular expression operations. Default: strip
pair of the regular expression operations. Defaults to strip
the prefix 'module.' by [(r'^module\\.', '')].
Returns:
@ -668,7 +669,7 @@ def get_state_dict(module, destination=None, prefix='', keep_vars=False):
module.
prefix (str): Prefix of the key.
keep_vars (bool): Whether to keep the variable property of the
parameters. Default: False.
parameters. Defaults to False.
Returns:
dict: A dictionary containing a whole state of the module.

2
mmengine/runner/runner.py
View File

@ -2027,7 +2027,7 @@ class Runner:
the model and checkpoint.
revise_keys (list): A list of customized keywords to modify the
state_dict in checkpoint. Each item is a (pattern, replacement)
pair of the regular expression operations. Default: strip
pair of the regular expression operations. Defaults to strip
the prefix 'module.' by [(r'^module\\.', '')].
"""
checkpoint = _load_checkpoint(filename, map_location=map_location)

4
mmengine/runner/utils.py
View File

@ -53,9 +53,9 @@ def set_random_seed(seed: Optional[int] = None,
deterministic (bool): Whether to set the deterministic option for
CUDNN backend, i.e., set `torch.backends.cudnn.deterministic`
to True and `torch.backends.cudnn.benchmark` to False.
Default: False.
Defaults to False.
diff_rank_seed (bool): Whether to add rank number to the random seed to
have different random seed in different threads. Default: False.
have different random seed in different threads. Defaults to False.
"""
if seed is None:
seed = sync_random_seed()

6
mmengine/utils/dl_utils/hub.py
View File

@ -68,15 +68,15 @@ if TORCH_VERSION != 'parrots' and digit_version(TORCH_VERSION) < digit_version(
map_location (optional): a function or a dict specifying how to
remap storage locations (see torch.load)
progress (bool, optional): whether or not to display a progress bar
to stderr. Default: True
to stderr. Defaults to True
check_hash(bool, optional): If True, the filename part of the URL
should follow the naming convention ``filename-<sha256>.ext``
where ``<sha256>`` is the first eight or more digits of the
SHA256 hash of the contents of the file. The hash is used to
ensure unique names and to verify the contents of the file.
Default: False
Defaults to False
file_name (str, optional): name for the downloaded file. Filename
from ``url`` will be used if not set. Default: None.
from ``url`` will be used if not set. Defaults to None.
Example:
>>> url = ('https://s3.amazonaws.com/pytorch/models/resnet18-5c106'
... 'cde.pth')

2
mmengine/utils/misc.py
View File

@ -46,7 +46,7 @@ def import_modules_from_strings(imports, allow_failed_imports=False):
Args:
imports (list | str | None): The given module names to be imported.
allow_failed_imports (bool): If True, the failed imports will return
None. Otherwise, an ImportError is raise. Default: False.
None. Otherwise, an ImportError is raise. Defaults to False.
Returns:
list[module] | module | None: The imported modules.

6
mmengine/utils/path.py
View File

@ -42,11 +42,11 @@ def scandir(dir_path, suffix=None, recursive=False, case_sensitive=True):
Args:
dir_path (str | :obj:`Path`): Path of the directory.
suffix (str | tuple(str), optional): File suffix that we are
interested in. Default: None.
interested in. Defaults to None.
recursive (bool, optional): If set to True, recursively scan the
directory. Default: False.
directory. Defaults to False.
case_sensitive (bool, optional) : If set to False, ignore the case of
suffix. Default: True.
suffix. Defaults to True.
Returns:
A generator for all the interested files with relative paths.

2
mmengine/utils/version_utils.py
View File

@ -14,7 +14,7 @@ def digit_version(version_str: str, length: int = 4):
Args:
version_str (str): The version string.
length (int): The maximum number of version levels. Default: 4.
length (int): The maximum number of version levels. Defaults to 4.
Returns:
tuple[int]: The version info in digits (integers).

56
mmengine/visualization/vis_backend.py
View File

@ -117,8 +117,8 @@ class BaseVisBackend(metaclass=ABCMeta):
Args:
name (str): The image identifier.
image (np.ndarray): The image to be saved. The format
should be RGB. Default to None.
step (int): Global step value to record. Default to 0.
should be RGB. Defaults to None.
step (int): Global step value to record. Defaults to 0.
"""
pass
@ -132,7 +132,7 @@ class BaseVisBackend(metaclass=ABCMeta):
Args:
name (str): The scalar identifier.
value (int, float): Value to save.
step (int): Global step value to record. Default to 0.
step (int): Global step value to record. Defaults to 0.
"""
pass
@ -146,11 +146,11 @@ class BaseVisBackend(metaclass=ABCMeta):
Args:
scalar_dict (dict): Key-value pair storing the tag and
corresponding values.
step (int): Global step value to record. Default to 0.
step (int): Global step value to record. Defaults to 0.
file_path (str, optional): The scalar's data will be
saved to the `file_path` file at the same time
if the `file_path` parameter is specified.
Default to None.
Defaults to None.
"""
pass
@ -183,11 +183,11 @@ class LocalVisBackend(BaseVisBackend):
produced by the visualizer. If it is none, it means no data
is stored.
img_save_dir (str): The directory to save images.
Default to 'vis_image'.
Defaults to 'vis_image'.
config_save_file (str): The file name to save config.
Default to 'config.py'.
Defaults to 'config.py'.
scalar_save_file (str): The file name to save scalar values.
Default to 'scalars.json'.
Defaults to 'scalars.json'.
"""
def __init__(self,
@ -244,8 +244,8 @@ class LocalVisBackend(BaseVisBackend):
Args:
name (str): The image identifier.
image (np.ndarray): The image to be saved. The format
should be RGB. Default to None.
step (int): Global step value to record. Default to 0.
should be RGB. Defaults to None.
step (int): Global step value to record. Defaults to 0.
"""
assert image.dtype == np.uint8
drawn_image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
@ -264,7 +264,7 @@ class LocalVisBackend(BaseVisBackend):
Args:
name (str): The scalar identifier.
value (int, float, torch.Tensor, np.ndarray): Value to save.
step (int): Global step value to record. Default to 0.
step (int): Global step value to record. Defaults to 0.
"""
if isinstance(value, torch.Tensor):
value = value.item()
@ -285,11 +285,11 @@ class LocalVisBackend(BaseVisBackend):
scalar_dict (dict): Key-value pair storing the tag and
corresponding values. The value must be dumped
into json format.
step (int): Global step value to record. Default to 0.
step (int): Global step value to record. Defaults to 0.
file_path (str, optional): The scalar's data will be
saved to the ``file_path`` file at the same time
if the ``file_path`` parameter is specified.
Default to None.
Defaults to None.
"""
assert isinstance(scalar_dict, dict)
scalar_dict = copy.deepcopy(scalar_dict)
@ -339,7 +339,9 @@ class WandbVisBackend(BaseVisBackend):
save_dir (str, optional): The root directory to save the files
produced by the visualizer.
init_kwargs (dict, optional): wandb initialization
input parameters. Default to None.
input parameters.
See `wandb.init <https://docs.wandb.ai/ref/python/init>`_ for
details. Defaults to None.
define_metric_cfg (dict, optional):
A dict of metrics and summary for wandb.define_metric.
The key is metric and the value is summary.
@ -349,10 +351,10 @@ class WandbVisBackend(BaseVisBackend):
run#define_metric>`_ for details.
Default: None
commit: (bool, optional) Save the metrics dict to the wandb server
and increment the step. If false `wandb.log` just
updates the current metrics dict with the row argument
and metrics won't be saved until `wandb.log` is called
with `commit=True`. Default to True.
and increment the step. If false `wandb.log` just updates the
current metrics dict with the row argument and metrics won't be
saved until `wandb.log` is called with `commit=True`.
Defaults to True.
log_code_name: (str, optional) The name of code artifact.
By default, the artifact will be named
source-$PROJECT_ID-$ENTRYPOINT_RELPATH. See
@ -442,7 +444,7 @@ class WandbVisBackend(BaseVisBackend):
image (np.ndarray): The image to be saved. The format
should be RGB.
step (int): Useless parameter. Wandb does not
need this parameter. Default to 0.
need this parameter. Defaults to 0.
"""
image = self._wandb.Image(image)
self._wandb.log({name: image}, commit=self._commit)
@ -459,7 +461,7 @@ class WandbVisBackend(BaseVisBackend):
name (str): The scalar identifier.
value (int, float, torch.Tensor, np.ndarray): Value to save.
step (int): Useless parameter. Wandb does not
need this parameter. Default to 0.
need this parameter. Defaults to 0.
"""
self._wandb.log({name: value}, commit=self._commit)
@ -475,9 +477,9 @@ class WandbVisBackend(BaseVisBackend):
scalar_dict (dict): Key-value pair storing the tag and
corresponding values.
step (int): Useless parameter. Wandb does not
need this parameter. Default to 0.
need this parameter. Defaults to 0.
file_path (str, optional): Useless parameter. Just for
interface unification. Default to None.
interface unification. Defaults to None.
"""
self._wandb.log(scalar_dict, commit=self._commit)
@ -560,7 +562,7 @@ class TensorboardVisBackend(BaseVisBackend):
name (str): The image identifier.
image (np.ndarray): The image to be saved. The format
should be RGB.
step (int): Global step value to record. Default to 0.
step (int): Global step value to record. Defaults to 0.
"""
self._tensorboard.add_image(name, image, step, dataformats='HWC')
@ -575,14 +577,14 @@ class TensorboardVisBackend(BaseVisBackend):
Args:
name (str): The scalar identifier.
value (int, float, torch.Tensor, np.ndarray): Value to save.
step (int): Global step value to record. Default to 0.
step (int): Global step value to record. Defaults to 0.
"""
if isinstance(value,
(int, float, torch.Tensor, np.ndarray, np.number)):
self._tensorboard.add_scalar(name, value, step)
else:
warnings.warn(f'Got {type(value)}, but numpy array, torch tensor, '
f'int or float are expected. skip it！')
f'int or float are expected. skip it!')
@force_init_env
def add_scalars(self,
@ -595,9 +597,9 @@ class TensorboardVisBackend(BaseVisBackend):
Args:
scalar_dict (dict): Key-value pair storing the tag and
corresponding values.
step (int): Global step value to record. Default to 0.
step (int): Global step value to record. Defaults to 0.
file_path (str, optional): Useless parameter. Just for
interface unification. Default to None.
interface unification. Defaults to None.
"""
assert isinstance(scalar_dict, dict)
assert 'step' not in scalar_dict, 'Please set it directly ' \

18
mmengine/visualization/visualizer.py
View File

@ -71,7 +71,7 @@ class Visualizer(ManagerMixin):
image (np.ndarray, optional): the origin image to draw. The format
should be RGB. Defaults to None.
vis_backends (list, optional): Visual backend config list.
Default to None.
Defaults to None.
save_dir (str, optional): Save file dir for all storage backends.
If it is None, the backend storage will not save any data.
fig_save_cfg (dict): Keyword parameters of figure for saving.
@ -636,7 +636,7 @@ class Visualizer(ManagerMixin):
If ``line_widths`` is single value, all the lines will
have the same linewidth. Defaults to 2.
face_colors (Union[str, tuple, List[str], List[tuple]]):
The face colors. Default to None.
The face colors. Defaults to None.
alpha (Union[int, float]): The transparency of circles.
Defaults to 0.8.
"""
@ -927,7 +927,7 @@ class Visualizer(ManagerMixin):
featmap (torch.Tensor): The featmap to draw which format is
(C, H, W).
overlaid_image (np.ndarray, optional): The overlaid image.
Default to None.
Defaults to None.
channel_reduction (str, optional): Reduce multiple channels to a
single channel. The optional value is 'squeeze_mean'
or 'select_max'. Defaults to 'squeeze_mean'.
@ -938,7 +938,7 @@ class Visualizer(ManagerMixin):
arrangement (Tuple[int, int]): The arrangement of featmap when
channel_reduction is not None and topk > 0. Defaults to (4, 5).
resize_shape (tuple, optional): The shape to scale the feature map.
Default to None.
Defaults to None.
alpha (Union[int, List[int]]): The transparency of featmap.
Defaults to 0.5.
@ -1064,8 +1064,8 @@ class Visualizer(ManagerMixin):
Args:
name (str): The image identifier.
image (np.ndarray, optional): The image to be saved. The format
should be RGB. Default to None.
step (int): Global step value to record. Default to 0.
should be RGB. Defaults to None.
step (int): Global step value to record. Defaults to 0.
"""
for vis_backend in self._vis_backends.values():
vis_backend.add_image(name, image, step) # type: ignore
@ -1081,7 +1081,7 @@ class Visualizer(ManagerMixin):
Args:
name (str): The scalar identifier.
value (float, int): Value to save.
step (int): Global step value to record. Default to 0.
step (int): Global step value to record. Defaults to 0.
"""
for vis_backend in self._vis_backends.values():
vis_backend.add_scalar(name, value, step, **kwargs) # type: ignore
@ -1097,11 +1097,11 @@ class Visualizer(ManagerMixin):
Args:
scalar_dict (dict): Key-value pair storing the tag and
corresponding values.
step (int): Global step value to record. Default to 0.
step (int): Global step value to record. Defaults to 0.
file_path (str, optional): The scalar's data will be
saved to the `file_path` file at the same time
if the `file_path` parameter is specified.
Default to None.
Defaults to None.
"""
for vis_backend in self._vis_backends.values():
vis_backend.add_scalars(scalar_dict, step, file_path, **kwargs)