v1.3.2
版本发布时间: 2024-08-30 23:32:49
NVIDIA/warp最新发布版本:v1.3.3(2024-09-05 04:54:55)
[1.3.2] - 2024-08-30
- Bug fixes
- Fix accuracy of 3x3 SVD
wp.svd3
with fp64 numbers (GH-281). - Fix module hashing when a kernel argument contained a struct array (GH-287).
- Fix a bug in
wp.bvh_query_ray()
where the direction instead of the reciprocal direction was used (GH-288). - Fix errors when launching a CUDA graph after a module is reloaded. Modules that were used during graph capture will no longer be unloaded before the graph is released.
- Fix a bug in
wp.sim.collide.triangle_closest_point_barycentric()
where the returned barycentric coordinates may be incorrect when the closest point lies on an edge. - Fix 32-bit overflow when array shape is specified using
np.int32
. - Fix handling of integer indices in the
input_output_mask
argument toautograd.jacobian
andautograd.jacobian_fd
(GH-289). - Fix
ModelBuilder.collapse_fixed_joints()
to correctly update the body centers of mass and theModelBuilder.articulation_start
array. - Fix precedence of closure constants over global constants.
- Fix quadrature point indexing in
wp.fem.ExplicitQuadrature
(regression from 1.3.0).
- Fix accuracy of 3x3 SVD
- Documentation improvements
- Add missing return types for built-in functions.
- Clarify that atomic operations also return the previous value.
- Clarify that
wp.bvh_query_aabb()
returns parts that overlap the bounding volume.
[1.3.1] - 2024-07-27
- Remove
wp.synchronize()
from PyTorch autograd function example -
Tape.check_kernel_array_access()
andTape.reset_array_read_flags()
are now private methods. - Fix reporting unmatched argument types
[1.3.0] - 2024-07-25
- Warp Core improvements
- Update to CUDA 12.x by default (requires NVIDIA driver 525 or newer), please see README.md for commands to install CUDA 11.x binaries for older drivers
- Add information to the module load print outs to indicate whether a module was
compiled
(compiled)
, loaded from the cache(cached)
, or was unable to be loaded(error)
. -
wp.config.verbose = True
now also prints out a message upon the entry to awp.ScopedTimer
. - Add
wp.clear_kernel_cache()
to the public API. This is equivalent towp.build.clear_kernel_cache()
. - Add code-completion support for
wp.config
variables. - Remove usage of a static task (thread) index for CPU kernels to address multithreading concerns (GH-224)
- Improve error messages for unsupported Python operations such as sequence construction in kernels
- Update
wp.matmul()
CPU fallback to use dtype explicitly innp.matmul()
call - Add support for PEP 563's
from __future__ import annotations
(GH-256). - Allow passing external arrays/tensors to
wp.launch()
directly via__cuda_array_interface__
and__array_interface__
, up to 2.5x faster conversion from PyTorch - Add faster Torch interop path using
return_ctype
argument towp.from_torch()
- Handle incompatible CUDA driver versions gracefully
- Add
wp.abs()
andwp.sign()
for vector types - Expose scalar arithmetic operators to Python's runtime (e.g.:
wp.float16(1.23) * wp.float16(2.34)
) - Add support for creating volumes with anisotropic transforms
- Allow users to pass function arguments by keyword in a kernel using standard Python calling semantics
- Add additional documentation and examples demonstrating
wp.copy()
,wp.clone()
, andarray.assign()
differentiability - Add
__new__()
methods for all class__del__()
methods to handle when a class instance is created but not instantiated before garbage collection - Implement the assignment operator for
wp.quat
- Make the geometry-related built-ins available only from within kernels
- Rename the API-facing query types to remove their
_t
suffix:wp.BVHQuery
,wp.HashGridQuery
,wp.MeshQueryAABB
,wp.MeshQueryPoint
, andwp.MeshQueryRay
- Add
wp.array(ptr=...)
to allow initializing arrays from pointer addresses inside of kernels (GH-206)
1、 warp_lang-1.3.2+cpu-py3-none-macosx_10_13_universal2.whl 41.93MB
2、 warp_lang-1.3.2+cu11-py3-none-manylinux2014_aarch64.whl 58.64MB
3、 warp_lang-1.3.2+cu11-py3-none-manylinux2014_x86_64.whl 60.35MB
4、 warp_lang-1.3.2+cu11-py3-none-win_amd64.whl 51.5MB
5、 warp_lang-1.3.2+cu12-py3-none-manylinux2014_aarch64.whl 62.07MB
6、 warp_lang-1.3.2+cu12-py3-none-manylinux2014_x86_64.whl 62.75MB
7、 warp_lang-1.3.2+cu12-py3-none-win_amd64.whl 52.99MB
8、 warp_lang-1.3.2-py3-none-macosx_10_13_universal2.whl 41.93MB
9、 warp_lang-1.3.2-py3-none-manylinux2014_aarch64.whl 62.07MB
10、 warp_lang-1.3.2-py3-none-win_amd64.whl 52.99MB