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fix dataset doc problem

This commit is contained in:
xiefangqi 2021-12-15 11:11:11 +08:00
parent 3a1418288d
commit bde69a7854
1 changed files with 15 additions and 15 deletions
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30
mindspore/dataset/engine/datasets.py
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@ -464,7 +464,7 @@ class Dataset:
Serialize a pipeline into JSON string and dump into file if filename is provided.
Args:
filename (str): filename of JSON file to be saved as.
filename (str): filename of JSON file to be saved as (default="").
Returns:
str, JSON string of the pipeline.
@ -491,7 +491,7 @@ class Dataset:
of the buckets. Must be strictly increasing. If there are n boundaries,
n+1 buckets are created: One bucket for [0, bucket_boundaries[0]), one
bucket for [bucket_boundaries[i], bucket_boundaries[i+1]) for each
0<i<n-1, and last bucket for [bucket_boundaries[n-1], inf).
0<i<n-1, and the last bucket for [bucket_boundaries[n-1], inf).
bucket_batch_sizes (list[int]): A list consisting of the batch sizes for
each bucket. Must contain len(bucket_boundaries)+1 elements.
element_length_function (Callable, optional): A function that takes in
@ -566,12 +566,12 @@ class Dataset:
be dropped and not propagated to the child node.
num_parallel_workers (int, optional): Number of workers(threads) to process the dataset in parallel
(default=None).
per_batch_map (callable, optional): Per batch map callable. A callable which takes
per_batch_map (callable, optional): Per batch map callable (default=None). A callable which takes
(list[Tensor], list[Tensor], ..., BatchInfo) as input parameters. Each list[Tensor] represents a batch
of Tensors on a given column. The number of lists should match with number of entries in input_columns.
The last parameter of the callable should always be a BatchInfo object. Per_batch_map should return
(list[Tensor], list[Tensor], ...). The length of each list in output should be same as the input.
output_columns is required if the number of output lists is different from input.
of Tensors on a given column. The number of lists should match with the number of entries in
input_columns. The last parameter of the callable should always be a BatchInfo object. Per_batch_map
should return (list[Tensor], list[Tensor], ...). The length of each list in output should be the same as
the input. output_columns is required if the number of output lists is different from input.
input_columns (Union[str, list[str]], optional): List of names of the input columns. The size of the list
should match with signature of per_batch_map callable (default=None).
output_columns (Union[str, list[str]], optional): List of names assigned to the columns
@ -580,8 +580,8 @@ class Dataset:
columns of the last operation. (default=None, output columns will have the same
name as the input columns, i.e., the columns will be replaced).
column_order (Union[str, list[str]], optional): Specifies the list of all the columns you need in the whole
dataset. The parameter is required when len(input_column) != len(output_column). Caution: the list here
is not just the columns specified in parameter input_columns and output_columns.
dataset (default=None). The parameter is required when len(input_column) != len(output_column).
Caution: the list here is not just the columns specified in parameter input_columns and output_columns.
pad_info (dict, optional): Whether to perform padding on selected columns. pad_info={"col1":([224,224],0)}
would pad column with name "col1" to a tensor of size [224,224] and fill the missing with 0
(default=None).
@ -620,8 +620,8 @@ class Dataset:
Args:
condition_name (str): The condition name that is used to toggle sending next row.
num_batch (int): the number of batches without blocking at the start of each epoch.
callback (function): The callback function that will be invoked when sync_update is called.
num_batch (int): the number of batches without blocking at the start of each epoch (default=1).
callback (function): The callback function that will be invoked when sync_update is called (default=None).
Returns:
SyncWaitDataset, dataset added a blocking condition.
@ -777,8 +777,8 @@ class Dataset:
columns of the last operation. (default=None, output columns will have the same
name as the input columns, i.e., the columns will be replaced).
column_order (list[str], optional): Specifies the list of all the columns you need in the whole
dataset. The parameter is required when len(input_column) != len(output_column). Caution: the list here
is not just the columns specified in parameter input_columns and output_columns.
dataset (default=None). The parameter is required when len(input_column) != len(output_column).
Caution: the list here is not just the columns specified in parameter input_columns and output_columns.
num_parallel_workers (int, optional): Number of threads used to process the dataset in
parallel (default=None, the value from the configuration will be used).
python_multiprocessing (bool, optional): Parallelize Python operations with multiple worker processes. This
@ -993,7 +993,7 @@ class Dataset:
1. If count is greater than the number of elements in the dataset or equal to -1,
all the elements in dataset will be taken.
2. The order of using take and batch matters. If take is before batch operation,
then take given number of rows; otherwise take given number of batches.
then take the given number of rows; otherwise take the given number of batches.
Args:
count (int, optional): Number of elements to be taken from the dataset (default=-1).
@ -2107,7 +2107,7 @@ class MappableDataset(SourceDataset):
def add_sampler(self, new_sampler):
"""
Add a sampler for current dataset,.
Add a sampler for current dataset.
Args:
new_sampler (Sampler): The sampler to be added as the parent sampler for current dataset.