initial commit

tensorlistdataset.py

+# coding=utf-8
+#
+# Copyright 2020-2022 Heinrich Heine University Duesseldorf
+#
+# 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.
+
+from torch.utils.data import Dataset
+
+
+class TensorListDataset(Dataset):
+    r"""Dataset wrapping tensors, tensor dicts and tensor lists.
+
+    Arguments:
+        *data (Tensor or dict or list of Tensors): tensors that have the same size
+        of the first dimension.
+    """
+
+    def __init__(self, *data):
+        if isinstance(data[0], dict):
+            size = list(data[0].values())[0].size(0)
+        elif isinstance(data[0], list):
+            size = data[0][0].size(0)
+        else:
+            size = data[0].size(0)
+        for element in data:
+            if isinstance(element, dict):
+                assert all(size == tensor.size(0) for name, tensor in element.items()) # dict of tensors
+            elif isinstance(element, list):
+                assert all(size == tensor.size(0) for tensor in element) # list of tensors
+            else:
+                assert size == element.size(0) # tensor
+        self.size = size
+        self.data = data
+
+    def __getitem__(self, index):
+        result = []
+        for element in self.data:
+            if isinstance(element, dict):
+                result.append({k: v[index] for k, v in element.items()})
+            elif isinstance(element, list):
+                result.append(v[index] for v in element)
+            else:
+                result.append(element[index])
+        return tuple(result)
+
+    def __len__(self):
+        return self.size