Repository: Project-MONAI/MONAI

Issue:
shufflebuffer is not compatible with the dataloader
**Describe the bug**
```py
import monai

buffer = monai.data.ShuffleBuffer([1,2,3,4])
for x in monai.data.DataLoader(buffer, batch_size=2):
    print(x)
```

```
    for x in monai.data.DataLoader(buffer, batch_size=2):
  File "/Users/Documents/MONAI/monai/data/dataloader.py", line 78, in __init__
    set_rnd(dataset, int(_seed))
  File "/Users/Documents/MONAI/monai/data/utils.py", line 624, in set_rnd
    obj.set_random_state(seed=seed % MAX_SEED)
  File "/Users/Documents/MONAI/monai/data/iterable_dataset.py", line 119, in set_random_state
    raise NotImplementedError(f"`set_random_state` is not available in {self.__class__.__name__}.")
NotImplementedError: `set_random_state` is not available in ShuffleBuffer.
```


Discussion:

Resolving patch:
diff --git a/monai/data/grid_dataset.py b/monai/data/grid_dataset.py
--- a/monai/data/grid_dataset.py
+++ b/monai/data/grid_dataset.py
@@ -187,23 +187,19 @@ def __init__(
     ) -> None:
         super().__init__(data=data, transform=None)
         self.patch_iter = patch_iter
-        self.transform = transform
+        self.patch_transform = transform
         self.with_coordinates = with_coordinates
 
     def __iter__(self):
         for image in super().__iter__():
-            if not self.with_coordinates:
-                for patch, *_ in self.patch_iter(image):  # patch_iter to yield at least 1 item: patch
-                    out_patch = (
-                        patch if self.transform is None else apply_transform(self.transform, patch, map_items=False)
-                    )
+            for patch, *others in self.patch_iter(image):
+                out_patch = patch
+                if self.patch_transform is not None:
+                    out_patch = apply_transform(self.patch_transform, patch, map_items=False)
+                if self.with_coordinates and len(others) > 0:  # patch_iter to yield at least 2 items: patch, coords
+                    yield out_patch, others[0]
+                else:
                     yield out_patch
-            else:
-                for patch, slices, *_ in self.patch_iter(image):  # patch_iter to yield at least 2 items: patch, coords
-                    out_patch = (
-                        patch if self.transform is None else apply_transform(self.transform, patch, map_items=False)
-                    )
-                    yield out_patch, slices
 
 
 class PatchDataset(Dataset):
diff --git a/monai/data/iterable_dataset.py b/monai/data/iterable_dataset.py
--- a/monai/data/iterable_dataset.py
+++ b/monai/data/iterable_dataset.py
@@ -11,7 +11,6 @@
 
 from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Union
 
-import numpy as np
 from torch.utils.data import IterableDataset as _TorchIterableDataset
 from torch.utils.data import get_worker_info
 
@@ -115,9 +114,6 @@ def _get_item():
     def randomize(self, size: int) -> None:
         self._idx = self.R.randint(size)
 
-    def set_random_state(self, seed: Optional[int] = None, state: Optional[np.random.RandomState] = None):
-        raise NotImplementedError(f"`set_random_state` is not available in {self.__class__.__name__}.")
-
 
 class CSVIterableDataset(IterableDataset):
     """


Test patch:
diff --git a/tests/test_grid_dataset.py b/tests/test_grid_dataset.py
--- a/tests/test_grid_dataset.py
+++ b/tests/test_grid_dataset.py
@@ -60,7 +60,7 @@ def test_loading_array(self):
             np.testing.assert_equal(tuple(item[0].shape), (2, 1, 2, 2))
         np.testing.assert_allclose(
             item[0],
-            np.array([[[[7.4965, 8.4965], [11.4965, 12.4965]]], [[[11.3584, 12.3584], [15.3584, 16.3584]]]]),
+            np.array([[[[8.0577, 9.0577], [12.0577, 13.0577]]], [[[10.5540, 11.5540], [14.5540, 15.5540]]]]),
             rtol=1e-4,
         )
         np.testing.assert_allclose(item[1], np.array([[[0, 1], [2, 4], [0, 2]], [[0, 1], [2, 4], [2, 4]]]), rtol=1e-5)
@@ -69,7 +69,7 @@ def test_loading_array(self):
                 np.testing.assert_equal(tuple(item[0].shape), (2, 1, 2, 2))
             np.testing.assert_allclose(
                 item[0],
-                np.array([[[[7.2548, 8.2548], [11.2548, 12.2548]]], [[[9.1106, 10.1106], [13.1106, 14.1106]]]]),
+                np.array([[[[7.6533, 8.6533], [11.6533, 12.6533]]], [[[9.8524, 10.8524], [13.8524, 14.8524]]]]),
                 rtol=1e-3,
             )
             np.testing.assert_allclose(
@@ -102,7 +102,7 @@ def test_loading_dict(self):
             self.assertListEqual(item[0]["metadata"], ["test string", "test string"])
         np.testing.assert_allclose(
             item[0]["image"],
-            np.array([[[[7.4965, 8.4965], [11.4965, 12.4965]]], [[[11.3584, 12.3584], [15.3584, 16.3584]]]]),
+            np.array([[[[8.0577, 9.0577], [12.0577, 13.0577]]], [[[10.5540, 11.5540], [14.5540, 15.5540]]]]),
             rtol=1e-4,
         )
         np.testing.assert_allclose(item[1], np.array([[[0, 1], [2, 4], [0, 2]], [[0, 1], [2, 4], [2, 4]]]), rtol=1e-5)
@@ -111,7 +111,7 @@ def test_loading_dict(self):
                 np.testing.assert_equal(item[0]["image"].shape, (2, 1, 2, 2))
             np.testing.assert_allclose(
                 item[0]["image"],
-                np.array([[[[7.2548, 8.2548], [11.2548, 12.2548]]], [[[9.1106, 10.1106], [13.1106, 14.1106]]]]),
+                np.array([[[[7.6533, 8.6533], [11.6533, 12.6533]]], [[[9.8524, 10.8524], [13.8524, 14.8524]]]]),
                 rtol=1e-3,
             )
             np.testing.assert_allclose(
diff --git a/tests/test_shuffle_buffer.py b/tests/test_shuffle_buffer.py
new file mode 100644
--- /dev/null
+++ b/tests/test_shuffle_buffer.py
@@ -0,0 +1,34 @@
+# Copyright (c) MONAI Consortium
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#     http://www.apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import sys
+import unittest
+
+import numpy as np
+
+from monai.data import DataLoader, ShuffleBuffer
+from monai.utils import convert_data_type
+
+
+class TestShuffleBuffer(unittest.TestCase):
+    def test_shape(self):
+        buffer = ShuffleBuffer([1, 2, 3, 4], seed=0)
+        num_workers = 2 if sys.platform == "linux" else 0
+        dataloader = DataLoader(dataset=buffer, batch_size=2, num_workers=num_workers)
+        output = [convert_data_type(x, np.ndarray)[0] for x in dataloader]
+        if num_workers == 0:
+            np.testing.assert_allclose(output, [[2, 1], [3, 4]])
+        else:  # multiprocess shuffle
+            np.testing.assert_allclose(output, [[2, 3], [1, 4]])
+
+
+if __name__ == "__main__":
+    unittest.main()