change num_samples definition

mindspore/ccsrc/minddata/dataset/engine/datasetops/source/csv_op.cc

@@ -27,7 +27,7 @@
 namespace mindspore {
 namespace dataset {
 CsvOp::Builder::Builder()
-    : builder_device_id_(0), builder_num_devices_(1), builder_num_samples_(0), builder_shuffle_files_(false) {
+    : builder_device_id_(0), builder_num_devices_(1), builder_num_samples_(-1), builder_shuffle_files_(false) {
   std::shared_ptr<ConfigManager> config_manager = GlobalContext::config_manager();
   builder_num_workers_ = config_manager->num_parallel_workers();
   builder_op_connector_size_ = config_manager->op_connector_size();
@@ -451,7 +451,7 @@ Status CsvOp::operator()() {
       RETURN_IF_NOT_OK(jagged_buffer_connector_->Pop(0, &buffer));
       if (buffer->eoe()) {
         workers_done++;
-      } else if (num_samples_ == 0 || rows_read < num_samples_) {
+      } else if (num_samples_ == -1 || rows_read < num_samples_) {
         if ((num_samples_ > 0) && (rows_read + buffer->NumRows() > num_samples_)) {
           int64_t rowsToRemove = buffer->NumRows() - (num_samples_ - rows_read);
           RETURN_IF_NOT_OK(buffer->SliceOff(rowsToRemove));

mindspore/dataset/engine/datasets.py

@@ -4935,7 +4935,7 @@ class CSVDataset(SourceDataset):
             columns as string type.
         column_names (list[str], optional): List of column names of the dataset (default=None). If this
             is not provided, infers the column_names from the first row of CSV file.
-        num_samples (int, optional): number of samples(rows) to read (default=None, reads the full dataset).
+        num_samples (int, optional): number of samples(rows) to read (default=-1, reads the full dataset).
         num_parallel_workers (int, optional): number of workers to read the data
             (default=None, number set in the config).
         shuffle (Union[bool, Shuffle level], optional): perform reshuffling of the data every epoch
@@ -4959,7 +4959,7 @@ class CSVDataset(SourceDataset):
     """
 
     @check_csvdataset
-    def __init__(self, dataset_files, field_delim=',', column_defaults=None, column_names=None, num_samples=None,
+    def __init__(self, dataset_files, field_delim=',', column_defaults=None, column_names=None, num_samples=-1,
                  num_parallel_workers=None, shuffle=Shuffle.GLOBAL, num_shards=None, shard_id=None):
         super().__init__(num_parallel_workers)
         self.dataset_files = self._find_files(dataset_files)
@@ -5010,7 +5010,7 @@ class CSVDataset(SourceDataset):
         if self._dataset_size is None:
             num_rows = CsvOp.get_num_rows(self.dataset_files, self.column_names is None)
             num_rows = get_num_rows(num_rows, self.num_shards)
-            if self.num_samples is None:
+            if self.num_samples == -1:
                 return num_rows
             return min(self.num_samples, num_rows)
         return self._dataset_size

mindspore/dataset/engine/validators.py

@@ -813,12 +813,16 @@ def check_csvdataset(method):
     def new_method(self, *args, **kwargs):
         _, param_dict = parse_user_args(method, *args, **kwargs)
 
-        nreq_param_int = ['num_samples', 'num_parallel_workers', 'num_shards', 'shard_id']
+        nreq_param_int = ['num_parallel_workers', 'num_shards', 'shard_id']
 
         # check dataset_files; required argument
         dataset_files = param_dict.get('dataset_files')
         type_check(dataset_files, (str, list), "dataset files")
 
+        # check num_samples
+        num_samples = param_dict.get('num_samples')
+        check_value(num_samples, [-1, INT32_MAX], "num_samples")
+
         # check field_delim
         field_delim = param_dict.get('field_delim')
         type_check(field_delim, (str,), 'field delim')