Function Differences with tf.data.TextLineDataset
tf.data.TextLineDataset
class tf.data.TextLineDataset(
filenames,
compression_type=None,
buffer_size=None,
num_parallel_reads=None
)
For more information, see tf.data.TextLineDataset.
mindspore.dataset.TextFileDataset
class mindspore.dataset.TextFileDataset(
dataset_files,
num_samples=None,
num_parallel_workers=None,
shuffle=Shuffle.GLOBAL,
num_shards=None,
shard_id=None,
cache=None
)
For more information, see mindspore.dataset.TextFileDataset.
Differences
TensorFlow: Create Dataset from a list of text files. It supports decompression operations and can set the cache size.
MindSpore: Create Dataset from a list of text files. It supports setting the number of samples.
Code Example
# The following implements TextFileDataset with MindSpore.
import mindspore.dataset as ds
dataset_files = ['/tmp/example0.txt',
'/tmp/example1.txt']
dataset = ds.TextFileDataset(dataset_files)
# The following implements TextLineDataset with TensorFlow.
import tensorflow as tf
filenames = ['/tmp/example0.txt',
'/tmp/example1.txt']
dataset = tf.data.TextLineDataset(filenames)