Function mindspore::dataset::CLUE

Function Documentation

inline std::shared_ptr<CLUEDataset> mindspore::dataset::CLUE(const std::vector<std::string> &dataset_files, const std::string &task = "AFQMC", const std::string &usage = "train", int64_t num_samples = 0, ShuffleMode shuffle = ShuffleMode::kGlobal, int32_t num_shards = 1, int32_t shard_id = 0, const std::shared_ptr<DatasetCache> &cache = nullptr)

Function to create a CLUEDataset.

Note

The generated dataset has a variable number of columns depending on the task and usage.

Parameters

  • dataset_files – [in] List of files to be read to search for a pattern of files. The list will be sorted in a lexicographical order.

  • task – [in] The kind of task, one of “AFQMC”, “TNEWS”, “IFLYTEK”, “CMNLI”, “WSC” and “CSL” (default=”AFQMC”).

  • usage – [in] Part of dataset of CLUE, can be “train”, “test” or “eval” data (default=”train”).

  • num_samples – [in] The number of samples to be included in the dataset (Default = 0 means all samples).

  • shuffle – [in] The mode for shuffling data every epoch. (Default=ShuffleMode.kGlobal) Can be any of: ShuffleMode::kFalse - No shuffling is performed. ShuffleMode::kFiles - Shuffle files only. ShuffleMode::kGlobal - Shuffle both the files and samples.

  • num_shards – [in] Number of shards that the dataset should be divided into. (Default = 1)

  • shard_id – [in] The shard ID within num_shards. This argument should be specified only when num_shards is also specified (Default = 0).

  • cache – [in] Tensor cache to use (default=nullptr which means no cache is used).

Returns

Shared pointer to the CLUEDataset.

Example
/* Define dataset path and MindData object */
std::string train_file = "/path/to/clue_dataset_file";
std::shared_ptr<Dataset> ds = CLUE({train_file}, "AFQMC", "train", 0, ShuffleMode::kFalse);

/* Create iterator to read dataset */
std::shared_ptr<Iterator> iter = ds->CreateIterator();
std::unordered_map<std::string, mindspore::MSTensor> row;
iter->GetNextRow(&row);

auto text = row["sentence1"];