add tests for default_unciollate

tests/data/test_batch.py

@@ -0,0 +1,57 @@
+# Copyright The PyTorch Lightning team.
+#
+# 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 torch
+from torch.tensor import Tensor
+from torch.testing import assert_allclose
+
+from flash.data.batch import default_uncollate
+
+
+class TestDefaultUncollate:
+
+    def test_smoke(self):
+        batch = torch.rand(2, 1)
+        assert default_uncollate(batch) is not None
+
+    def test_tensor_zero(self):
+        batch = torch.tensor(1)
+        output = default_uncollate(batch)
+        assert_allclose(batch, output)
+
+    def test_tensor_batch(self):
+        batch = torch.rand(2, 1)
+        output = default_uncollate(batch)
+        assert isinstance(output, list)
+        assert all([isinstance(x, torch.Tensor) for x in output])
+
+    def test_sequence(self):
+        B = 3  # batch_size
+
+        batch = {}
+        batch['a'] = torch.rand(B, 4)
+        batch['b'] = torch.rand(B, 2)
+        batch['c'] = torch.rand(B)
+
+        output = default_uncollate(batch)
+        assert isinstance(output, list)
+        assert len(batch) == B
+
+        for sample in output:
+            assert list(sample.keys()) == ['a', 'b', 'c']
+            assert isinstance(sample['a'], list)
+            assert len(sample['a']) == 4
+            assert isinstance(sample['b'], list)
+            assert len(sample['b']) == 2
+            assert isinstance(sample['c'], torch.Tensor)
+            assert len(sample['c'].shape) == 0