- 04 3月, 2025 5 次提交
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由 ricardoV94 提交于
Started failing in 0.4.36: https://github.com/jax-ml/jax/issues/26888 Skip failing JAX test Started failing in 0.4.36 and seems to be fixed in 0.5.1
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由 Ricardo Vieira 提交于
Extends pre-existing rewrite to ravel multiple integer indices, and to place them consecutively. The following cases should now be supported without object mode: * Advanced integer indexing (not mixed with basic or boolean indexing) that do not require broadcasting of indices * Consecutive advanced integer indexing updating (set/inc) (not mixed with basic or boolean indexing) that do not require broadcasting of indices or y.
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由 Ricardo Vieira 提交于
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由 Ricardo Vieira 提交于
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由 dependabot[bot] 提交于
Bumps [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel) from 2.22.0 to 2.23.0. - [Release notes](https://github.com/pypa/cibuildwheel/releases) - [Changelog](https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md) - [Commits](https://github.com/pypa/cibuildwheel/compare/v2.22.0...v2.23.0) --- updated-dependencies: - dependency-name: pypa/cibuildwheel dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by:
dependabot[bot] <support@github.com>
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- 28 2月, 2025 2 次提交
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由 Chris Fonnesbeck 提交于
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由 Aarsh Wankar 提交于
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- 27 2月, 2025 5 次提交
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由 Ricardo Vieira 提交于
JAX needs no special handling because it excludes inplace rewrites.
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由 Ricardo Vieira 提交于
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由 Ricardo Vieira 提交于
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由 Ricardo Vieira 提交于
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由 Ricardo Vieira 提交于
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- 25 2月, 2025 7 次提交
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由 Ricardo Vieira 提交于
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由 Ricardo Vieira 提交于
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由 Ricardo Vieira 提交于
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由 Ricardo Vieira 提交于
Introduced in e593b0ac due to a bug when inputs had zero-strides. The bug can be fixed just by removing a block that assumed some `full`/`broadcasting` behavior by the operation, but this is not happening with DimShuffle.
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由 ricardoV94 提交于
This was caused by 223ee154, which used the generic `PyArray_IntpConverter` to convert the shape numpy vector into a simple C-array for the Reshape operation. There seems to be no need for this change as the strides were correctly used Profiling suggests the previous changes caused a 7.5x slowdown. The benchmark detects only a 2.3x slowdown due to the PyTensor call overhead.
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由 Ricardo Vieira 提交于
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由 Ricardo Vieira 提交于
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- 24 2月, 2025 5 次提交
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由 Aarsh Wankar 提交于
* Added print_shape option to debugprint and simplify __str__ logic in TensorType * Add print_memory_map option to debugprint to enable destroy and view maps
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由 Will Dean 提交于
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由 Ricardo Vieira 提交于
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由 Ben Mares 提交于
For more context, see the discussion in: https://github.com/conda-forge/pytensor-suite-feedstock/pull/133#issuecomment-2673831166
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由 Jesse Grabowski 提交于
* Fix bug in solve_triangular when `overwrite_b = True` * Add regression test
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- 20 2月, 2025 7 次提交
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由 Ricardo Vieira 提交于
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由 Ricardo Vieira 提交于
pytest-sphinx is not compatible with Python 3.13: https://github.com/twmr/pytest-sphinx/issues/67
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由 Ricardo Vieira 提交于
We want to test numpy 1.26.x on `test_math.py` but test_math.py was being excluded in python 3.10, and numpy 1.26.x was being excluded in the non python3.10 job.
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由 Ben Mares 提交于
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由 Ricardo Vieira 提交于
Notably changes the behavior of `__bool__` to always raise. Before there was a hack based on whether a variable had been compared to something before.
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由 Ricardo Vieira 提交于
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- 19 2月, 2025 4 次提交
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由 Ricardo Vieira 提交于
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由 Ricardo Vieira 提交于
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由 Ricardo Vieira 提交于
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由 Ricardo Vieira 提交于
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- 18 2月, 2025 5 次提交
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由 Ricardo Vieira 提交于
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由 Adv 提交于
Co-authored-by:Adv <adhvaithhundi.221ds003@nitk.edu.in>
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由 Brendan Murphy 提交于
Remaining tests now run on latest numpy, except for Numba jobs, which need numpy 2.1.0
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由 Brendan Murphy 提交于
Also added ruff numpy2 transition rule.
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由 Brendan Murphy 提交于
I split this test up to test uint64 separately, since this is the case discussed in Issue #770. I also added a test for the exact example used in that issue. The uint dtypes with lower precision should pass. The uint64 case started passing for me locally on Mac OSX, but still fails on CI. I'm not sure why this is, but at least the test will be more specific now if it fails in the future.
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