$ docker run arraiy/torchgeometry /bin/bash -c "source path.bash.inc && pytest test/"
============================= test session starts ==============================
platform linux -- Python 3.7.1, pytest-4.1.1, py-1.7.0, pluggy-0.8.1
rootdir: /torchgeometry, inifile:
collected 158 items
test/smoke_test.py ...                                                   [  1%]
test/test_conversions.py .............................................   [ 30%]
test/test_depth_warper.py .                                              [ 31%]
test/test_homography_warper.py ...................                       [ 43%]
test/test_image.py .........................................             [ 68%]
test/test_imgwarp.py ..............                                      [ 77%]
test/test_jit_tracing.py ..                                              [ 79%]
test/test_losses.py ............                                         [ 86%]
test/test_pinhole.py .................                                   [ 97%]
test/test_utils.py ....                                                  [100%]
=============================== warnings summary ===============================
test/test_jit_tracing.py::test_jit_tracing[True-cpu]
  /torchgeometry/torchgeometry/imgwarp.py:21: TracerWarning: torch.Tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
    [0.0, 0.0, 1.0]])  # 1x3x3
  /torchgeometry/torchgeometry/conversions.py:147: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
    if not dst_pose_src.shape[0] == points_src.shape[0]:
  /torchgeometry/torchgeometry/conversions.py:149: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
    if not dst_pose_src.shape[-1] == (points_src.shape[-1] + 1):
test/test_jit_tracing.py::test_jit_tracing[False-cpu]
  /torchgeometry/torchgeometry/imgwarp.py:21: TracerWarning: torch.Tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
    [0.0, 0.0, 1.0]])  # 1x3x3
  /torchgeometry/torchgeometry/conversions.py:147: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
    if not dst_pose_src.shape[0] == points_src.shape[0]:
  /torchgeometry/torchgeometry/conversions.py:149: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
    if not dst_pose_src.shape[-1] == (points_src.shape[-1] + 1):
-- Docs: https://docs.pytest.org/en/latest/warnings.html
=================== 158 passed, 6 warnings in 54.66 seconds ====================
The command "docker run arraiy/torchgeometry /bin/bash -c "source path.bash.inc && pytest test/"" exited with 0.