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

rf2aa/SE3Transformer/tests/utils.py

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+# 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
+
+import dgl
+import torch
+
+
+def get_random_graph(N, num_edges_factor=18):
+    graph = dgl.transforms.remove_self_loop(dgl.rand_graph(N, N * num_edges_factor))
+    return graph
+
+
+def assign_relative_pos(graph, coords):
+    src, dst = graph.edges()
+    graph.edata['rel_pos'] = coords[src] - coords[dst]
+    return graph
+
+
+def get_max_diff(a, b):
+    return (a - b).abs().max().item()
+
+
+def rot_z(gamma):
+    return torch.tensor([
+        [torch.cos(gamma), -torch.sin(gamma), 0],
+        [torch.sin(gamma), torch.cos(gamma), 0],
+        [0, 0, 1]
+    ], dtype=gamma.dtype)
+
+
+def rot_y(beta):
+    return torch.tensor([
+        [torch.cos(beta), 0, torch.sin(beta)],
+        [0, 1, 0],
+        [-torch.sin(beta), 0, torch.cos(beta)]
+    ], dtype=beta.dtype)
+
+
+def rot(alpha, beta, gamma):
+    return rot_z(alpha) @ rot_y(beta) @ rot_z(gamma)