v7.0.0b1
Pre-release
Pre-release
This is the release note of v7.0.0b1. See here for the complete list of solved issues and merged PRs.
Highlights
Host to device copy from NumPy ndarrays is now allowed as an experimental feature with the syntax cupy_array[:] = numpy_array
. Set the environment variable CUPY_EXPERIMENTAL_SLICE_COPY
to try it out.
Notes
- Tensor Core in cuDNN convolution is tentatively disabled for Turing GPUs due to some test failures. The issue is under investigation and hopefully fixed in a future version.
New Features
- Allow copying in the format
cupy_array[:] = numpy_array
(#2079, thanks @pentschev!) - Add
linalg.lstsq
(#2165, thanks @cjekel!) - Add
fallback_mode
(#2229, thanks @Piyush-555!) - Add
CUDNN_POOLING_MAX_DETERMINISTIC
(#2239) - Add API to retrieve installation info (#2245)
Enhancements
- Improve
atomicAdd
in histogram and sample (#1345) - Set current device in
cupy.ndarray.get()
/set()
(#2169, thanks @hyabe!) - Improve out-of-memory error message (#2242)
- Simplify
_prepare_multiple_array_indexing
(#2254) - Fix
_preprocess_args
to avoid callinghasattr
(#2256) - Add
constant
modification tovector_equal
(#2257)
Performance Improvements
- Optimize the initialization of
List[ndarray]
incupy.array
(#2081)
Bug Fixes
- Revert "Fix usage check of Tensor Core" (#2197)
- Fix
power
for large integrals (#2204) - Avoid division by zero in
tensordot
, allowing 0-length arrays (#2209, thanks @pentschev!) - Make
RandomState.permutation
compatible withrandom.permutation
(#2250)
Code Fixes
- Coding style fix (#2211)
Documentation
Installation
Tests
- Ignore invalid axis type test in NumPy 1.12.x or earlier (#2192)
Others
- Fix
array_split
with non-equally dividing sections (#2207)