mindspore.dataset.MindDataset
- class mindspore.dataset.MindDataset(dataset_files, columns_list=None, num_parallel_workers=None, shuffle=None, num_shards=None, shard_id=None, sampler=None, padded_sample=None, num_padded=None, num_samples=None, cache=None)[source]
A source dataset that reads and parses MindRecord dataset.
The columns of generated dataset depend on the source MindRecord files.
- Parameters
dataset_files (Union[str, list[str]]) – If dataset_file is a str, it represents for a file name of one component of a mindrecord source, other files with identical source in the same path will be found and loaded automatically. If dataset_file is a list, it represents for a list of dataset files to be read directly.
columns_list (list[str], optional) – List of columns to be read. Default:
None
, read all columns.num_parallel_workers (int, optional) – Number of worker threads to read the data. Default:
None
, will use global default workers(8), it can be set bymindspore.dataset.config.set_num_parallel_workers()
.shuffle (Union[bool, Shuffle], optional) –
Perform reshuffling of the data every epoch. Default:
None
, performs mindspore.dataset.Shuffle.GLOBAL. Bool type and Shuffle enum are both supported to pass in. If shuffle isFalse
, no shuffling will be performed. If shuffle isTrue
, performs global shuffle. There are three levels of shuffling, desired shuffle enum defined bymindspore.dataset.Shuffle
.Shuffle.GLOBAL
: Global shuffle of all rows of data in dataset, same as setting shuffle to True.Shuffle.FILES
: Shuffle the file sequence but keep the order of data within each file. Not supported when the number of samples in the dataset is greater than 100 million.Shuffle.INFILE
: Keep the file sequence the same but shuffle the data within each file. Not supported when the number of samples in the dataset is greater than 100 million.
num_shards (int, optional) – Number of shards that the dataset will be divided into. Default:
None
. When this argument is specified, num_samples reflects the maximum sample number of per shard.shard_id (int, optional) – The shard ID within num_shards . Default:
None
. This argument can only be specified when num_shards is also specified.sampler (Sampler, optional) – Object used to choose samples from the dataset. Default:
None
, sampler is exclusive with shuffle and block_reader. Support list:mindspore.dataset.SubsetRandomSampler
,mindspore.dataset.PKSampler
,mindspore.dataset.RandomSampler
,mindspore.dataset.SequentialSampler
,mindspore.dataset.DistributedSampler
.padded_sample (dict, optional) – Samples will be appended to dataset, where keys are the same as column_list. Default:
None
.num_padded (int, optional) – Number of padding samples. Dataset size plus num_padded should be divisible by num_shards. Default:
None
.num_samples (int, optional) – The number of samples to be included in the dataset. Default:
None
, all samples.cache (DatasetCache, optional) – Use tensor caching service to speed up dataset processing. More details: Single-Node Data Cache . Default:
None
, which means no cache is used.
- Raises
ValueError – If dataset_files are not valid or do not exist.
ValueError – If num_parallel_workers exceeds the max thread numbers.
RuntimeError – If num_shards is specified but shard_id is None.
RuntimeError – If shard_id is specified but num_shards is None.
ValueError – If shard_id is not in range of [0, num_shards ).
Note
This dataset can take in a sampler . sampler and shuffle are mutually exclusive. The table below shows what input arguments are allowed and their expected behavior.
Parameter sampler
Parameter shuffle
Expected Order Behavior
None
None
random order
None
True
random order
None
False
sequential order
Sampler object
None
order defined by sampler
Sampler object
True
not allowed
Sampler object
False
not allowed
Examples
>>> import mindspore.dataset as ds >>> mindrecord_files = ["/path/to/mind_dataset_file"] # contains 1 or multiple MindRecord files >>> dataset = ds.MindDataset(dataset_files=mindrecord_files)
Pre-processing Operation
Apply a function in this dataset. |
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Concatenate the dataset objects in the input list. |
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Filter dataset by prediction. |
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Map func to each row in dataset and flatten the result. |
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Apply each operation in operations to this dataset. |
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The specified columns will be selected from the dataset and passed into the pipeline with the order specified. |
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Rename the columns in input datasets. |
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Repeat this dataset count times. |
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Reset the dataset for next epoch. |
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Save the dynamic data processed by the dataset pipeline in common dataset format. |
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Shuffle the dataset by creating a cache with the size of buffer_size . |
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Skip the first N elements of this dataset. |
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Split the dataset into smaller, non-overlapping datasets. |
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Takes at most given numbers of elements from the dataset. |
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Zip the datasets in the sense of input tuple of datasets. |
Batch
Combine batch_size number of consecutive rows into batch which apply per_batch_map to the samples first. |
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Bucket elements according to their lengths. |
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Combine batch_size number of consecutive rows into batch which apply pad_info to the samples first. |
Iterator
Create an iterator over the dataset. |
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Create an iterator over the dataset. |
Attribute
Return the size of batch. |
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Return the class index. |
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Return the names of the columns in dataset. |
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Return the number of batches in an epoch. |
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Get the replication times in RepeatDataset. |
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Get the column index, which represents the corresponding relationship between the data column order and the network when using the sink mode. |
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Get the number of classes in a dataset. |
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Get the shapes of output data. |
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Get the types of output data. |
Apply Sampler
Add a child sampler for the current dataset. |
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Replace the last child sampler of the current dataset, remaining the parent sampler unchanged. |
Others
Return a transferred Dataset that transfers data through a device. |
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Release a blocking condition and trigger callback with given data. |
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Add a blocking condition to the input Dataset and a synchronize action will be applied. |
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Serialize a pipeline into JSON string and dump into file if filename is provided. |