Initial commit: RoseTTAFold-All-Atom configured for Wes with Harbor images and s3:// paths

rf2aa/SE3Transformer/se3_transformer/runtime/metrics.py

@@ -0,0 +1,83 @@
+# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# Permission is hereby granted, free of charge, to any person obtaining a
+# copy of this software and associated documentation files (the "Software"),
+# to deal in the Software without restriction, including without limitation
+# the rights to use, copy, modify, merge, publish, distribute, sublicense,
+# and/or sell copies of the Software, and to permit persons to whom the
+# Software is furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
+# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
+# DEALINGS IN THE SOFTWARE.
+#
+# SPDX-FileCopyrightText: Copyright (c) 2021 NVIDIA CORPORATION & AFFILIATES
+# SPDX-License-Identifier: MIT
+
+from abc import ABC, abstractmethod
+
+import torch
+import torch.distributed as dist
+from torch import Tensor
+
+
+class Metric(ABC):
+    """ Metric class with synchronization capabilities similar to TorchMetrics """
+
+    def __init__(self):
+        self.states = {}
+
+    def add_state(self, name: str, default: Tensor):
+        assert name not in self.states
+        self.states[name] = default.clone()
+        setattr(self, name, default)
+
+    def synchronize(self):
+        if dist.is_initialized():
+            for state in self.states:
+                dist.all_reduce(getattr(self, state), op=dist.ReduceOp.SUM, group=dist.group.WORLD)
+
+    def __call__(self, *args, **kwargs):
+        self.update(*args, **kwargs)
+
+    def reset(self):
+        for name, default in self.states.items():
+            setattr(self, name, default.clone())
+
+    def compute(self):
+        self.synchronize()
+        value = self._compute().item()
+        self.reset()
+        return value
+
+    @abstractmethod
+    def _compute(self):
+        pass
+
+    @abstractmethod
+    def update(self, preds: Tensor, targets: Tensor):
+        pass
+
+
+class MeanAbsoluteError(Metric):
+    def __init__(self):
+        super().__init__()
+        self.add_state('error', torch.tensor(0, dtype=torch.float32, device='cuda'))
+        self.add_state('total', torch.tensor(0, dtype=torch.int32, device='cuda'))
+
+    def update(self, preds: Tensor, targets: Tensor):
+        preds = preds.detach()
+        n = preds.shape[0]
+        error = torch.abs(preds.view(n, -1) - targets.view(n, -1)).sum()
+        self.total += n
+        self.error += error
+
+    def _compute(self):
+        return self.error / self.total