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# Copyright 2024 ByteDance and/or its affiliates.
#
# 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 time
import unittest
import torch
from protenix.model.modules.frames import (
expressCoordinatesInFrame,
gather_frame_atom_by_indices,
)
class TestFrame(unittest.TestCase):
def setUp(self):
self._start_time = time.time()
def test_express_coordinates_in_frame(self):
N_atom = 10
N_frame = 5
bs_dims = (2, 3)
coordinates = torch.rand(size=(*bs_dims, N_atom, 3))
frames = torch.rand(size=(*bs_dims, N_frame, 3, 3))
x_transformed = expressCoordinatesInFrame(coordinate=coordinates, frames=frames)
# shape check
self.assertEqual(
x_transformed.shape, torch.Size((*bs_dims, N_frame, N_atom, 3))
)
# invarient to batch order
x_transformed12 = expressCoordinatesInFrame(
coordinate=coordinates[1][2], frames=frames[1][2]
)
self.assertTrue(torch.allclose(x_transformed12, x_transformed[1][2]))
# value check
frames = torch.tensor([[[1, 0, 0], [0, 0, 0], [0, 1, 0]]]).float()
coordinates = torch.tensor([[1, 0, 0]]).float()
x_transformed = expressCoordinatesInFrame(coordinate=coordinates, frames=frames)
self.assertTrue(
torch.allclose(
x_transformed,
torch.tensor([[0.7071, -0.7071, 0.0000]]),
atol=1e-3,
rtol=1e-3,
)
) # math.sqrt(2)/2
def test_gather_frame_atom_by_indices(self):
N_atom = 10
N_frame = 5
bs_dims = (2, 3)
coordinates = torch.rand(size=(*bs_dims, N_atom, 3))
indexes = torch.randint(size=(*bs_dims, N_frame, 3), low=0, high=10)
out = gather_frame_atom_by_indices(
coordinate=coordinates, frame_atom_index=indexes
)
# shape check
self.assertEqual(out.shape, torch.Size((*bs_dims, N_frame, 3, 3)))
coordinates = torch.rand(size=(*bs_dims, N_atom, 3))
indexes = torch.randint(size=(N_frame, 3), low=0, high=10)
out = gather_frame_atom_by_indices(
coordinate=coordinates, frame_atom_index=indexes
)
# shape check [naive mode]
self.assertEqual(out.shape, torch.Size((*bs_dims, N_frame, 3, 3)))
def tearDown(self):
elapsed_time = time.time() - self._start_time
print(f"Test {self.id()} took {elapsed_time:.6f}s")
if __name__ == "__main__":
unittest.main()
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