update example code, test=docs_preview

PaddlePaddle · Aug 1, 2023 · fbce310 · fbce310
1 parent e8a6b31
commit fbce310
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diff --git a/python/paddle/io/dataloader/batch_sampler.py b/python/paddle/io/dataloader/batch_sampler.py
@@ -58,8 +58,10 @@ class BatchSampler(Sampler):
 
         .. code-block:: python
 
+            >>> import numpy as np
             >>> from paddle.io import RandomSampler, BatchSampler, Dataset
 
+            >>> np.random.seed(2023)
             >>> # init with dataset
             >>> class RandomDataset(Dataset):
             ...     def __init__(self, num_samples):
@@ -80,7 +82,9 @@ class BatchSampler(Sampler):
             ...
             >>> for batch_indices in bs:
             ...     print(batch_indices)
+            [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]
             ...
+            [96, 97, 98, 99]
             >>> # init with sampler
             >>> sampler = RandomSampler(RandomDataset(100))
             >>> bs = BatchSampler(sampler=sampler,
@@ -89,6 +93,9 @@ class BatchSampler(Sampler):
             ...
             >>> for batch_indices in bs:
             ...     print(batch_indices)
+            [56, 12, 68, 0, 82, 66, 91, 44]
+            ...
+            [53, 17, 22, 86, 52, 3, 92, 33]
     """
 
     def __init__(

diff --git a/python/paddle/io/dataloader/dataset.py b/python/paddle/io/dataloader/dataset.py
@@ -55,7 +55,8 @@ class Dataset:
             ...
             >>> dataset = RandomDataset(10)
             >>> for i in range(len(dataset)):
-            ...     print(dataset[i])
+            ...     image, label = dataset[i]
+            ...     # do something
     """
 
     def __init__(self):
@@ -109,8 +110,9 @@ class IterableDataset(Dataset):
             ...             yield image, label
             ...
             >>> dataset = RandomDataset(10)
-            >>> for img, lbl in dataset:
-            ...     print(img, lbl)
+            >>> for img, label in dataset:
+            ...     # do something
+            ...     ...
 
     When :attr:`num_workers > 0`, each worker has a different copy of the dataset object and
     will yield whole dataset samples, which means samples in dataset will be repeated in
@@ -158,7 +160,7 @@ class IterableDataset(Dataset):
             ...     drop_last=True)
             ...
             >>> for data in dataloader:
-            ...     print(data)
+            ...     print(data) # doctest: +SKIP
             Tensor(shape=[1, 1], dtype=int64, place=Place(cpu), stop_gradient=True,
                 [[2]])
             Tensor(shape=[1, 1], dtype=int64, place=Place(cpu), stop_gradient=True,
@@ -216,7 +218,7 @@ class IterableDataset(Dataset):
             ...     worker_init_fn=worker_init_fn)
             ...
             >>> for data in dataloader:
-            ...     print(data)
+            ...     print(data) # doctest: +SKIP
             Tensor(shape=[1, 1], dtype=int64, place=Place(cpu), stop_gradient=True,
                 [[2]])
             Tensor(shape=[1, 1], dtype=int64, place=Place(cpu), stop_gradient=True,
@@ -288,7 +290,7 @@ class TensorDataset(Dataset):
 
             >>> for i in range(len(dataset)):
             ...     input, label = dataset[i]
-            ...     print(input, label)
+            ...     # do something
     """
 
     def __init__(self, tensors):
@@ -354,10 +356,7 @@ class ComposeDataset(Dataset):
             >>> dataset = ComposeDataset([RandomDataset(10), RandomDataset(10)])
             >>> for i in range(len(dataset)):
             ...     image1, label1, image2, label2 = dataset[i]
-            ...     print(image1)
-            ...     print(label1)
-            ...     print(image2)
-            ...     print(label2)
+            ...     # do something
     """
 
     def __init__(self, datasets):
@@ -420,7 +419,9 @@ class ChainDataset(IterableDataset):
             ...
             >>> dataset = ChainDataset([RandomDataset(10), RandomDataset(10)])
             >>> for image, label in iter(dataset):
-            ...     print(image, label)
+            ...     # do something
+            ...     ...
+
     """
 
     def __init__(self, datasets):
@@ -497,31 +498,28 @@ def random_split(dataset, lengths, generator=None):
             >>> import paddle
             >>> from paddle.io import random_split
 
+            >>> paddle.seed(2023)
             >>> a_list = paddle.io.random_split(range(10), [3, 7])
             >>> print(len(a_list))
             2
 
             >>> # output of the first subset
             >>> for idx, v in enumerate(a_list[0]):
             ...     print(idx, v)
-            >>> # doctest: +SKIP
-            0 1
-            1 3
-            2 9
-            >>> # doctest: -SKIP
+            0 8
+            1 2
+            2 5
 
             >>> # output of the second subset
             >>> for idx, v in enumerate(a_list[1]):
             ...     print(idx, v)
-            >>> # doctest: +SKIP
-            0 5
-            1 7
-            2 8
-            3 6
-            4 0
-            5 2
-            6 4
-            >>> # doctest: -SKIP
+            0 9
+            1 6
+            2 3
+            3 4
+            4 1
+            5 0
+            6 7
     """
     # Cannot verify that dataset is Sized
     if sum(lengths) != len(dataset):  # type: ignore

diff --git a/python/paddle/io/dataloader/sampler.py b/python/paddle/io/dataloader/sampler.py
@@ -170,8 +170,10 @@ class RandomSampler(Sampler):
 
         .. code-block:: python
 
+            >>> import numpy as np
             >>> from paddle.io import Dataset, RandomSampler
 
+            >>> np.random.seed(2023)
             >>> class RandomDataset(Dataset):
             ...     def __init__(self, num_samples):
             ...         self.num_samples = num_samples
@@ -188,6 +190,11 @@ class RandomSampler(Sampler):
 
             >>> for index in sampler:
             ...     print(index)
+            56
+            12
+            68
+            ...
+            87
     """
 
     def __init__(
@@ -297,14 +304,22 @@ class WeightedRandomSampler(Sampler):
 
         .. code-block:: python
 
+            >>> import numpy as np
             >>> from paddle.io import WeightedRandomSampler
 
-            >>> sampler = WeightedRandomSampler(weights=[0.1, 0.3, 0.5, 0.7, 0.2],
-            ...                                 num_samples=5,
-            ...                                 replacement=True)
-            ...
+            >>> np.random.seed(2023)
+            >>> sampler = WeightedRandomSampler(
+            ...     weights=[0.1, 0.3, 0.5, 0.7, 0.2],
+            ...     num_samples=5,
+            ...     replacement=True
+            ... )
             >>> for index in sampler:
             ...     print(index)
+            2
+            4
+            3
+            1
+            1
     """
 
     def __init__(self, weights, num_samples, replacement=True):