Skip to content

v0.14.0
Compare
Choose a tag to compare
@antonwolfy antonwolfy released this 09 Apr 11:50
· 469 commits to master since this release
0.14.0
aa7d883
This commit was created on GitHub.com and signed with GitHub’s verified signature.
GPG key ID: B5690EEEBB952194
Learn about vigilant mode.

This release will require DPC++ 2024.1.0, which no longer supports Intel Gen9 integrated GPUs found in Intel CPUs of 10th generation and older.

Added

  • Added implementation of dpnp.tensordot function #1699
  • Added implementation of dpnp.nanmean and dpnp.nanstd functions #1654
  • Added implementation of dpnp.angle function #1650
  • Added implementation of dpnp.logsumexp and dpnp.reduce_hypot functions #1648
  • Added implementation of dpnp.column_stack, dpnp.dstack and dpnp.row_stack functions #1647
  • Added implementation of dpnp.nanargmax, dpnp.nanargmin, dpnp.nanmax and dpnp.nanmin functions #1646
  • Added implementation of dpnp.clip function, available as well as a method of dpnp array #1645
  • Added implementation of dpnp.copysign and dpnp.rsqrt functions #1624
  • Added implementation of dpnp.linalg.slogdet function #1607
  • Added implementation of dpnp.can_cast function #1600
  • Added implementation of dpnp.linalg.solve function #1598
  • Added implementation of dpnp.broadcast_arrays function #1594
  • Added implementation of dpnp.tile function #1586
  • Added implementation of dpnp.iinfo and dpnp.finfo functions #1582
  • Added implementation of dpnp.logaddexp function #1561
  • Added implementation of dpnp.positive function #1559

Changed

  • Changed exception type from ValueError to NotImplementedError for unsupporting keyword arguments in array creation functions #1695
  • Enabled compatibility support against numpy 1.26.4 #1690
  • Implemented dpnp.true_divide as an alias on dpnp.divide function #1641
  • Added support of more number of data types and dimensions for input array in dpnp.vdot function #1692
  • Added support of more number of data types and dimensions for input array in dpnp.linalg.qr function #1673
  • Added support of more number of data types and dimensions for input array in dpnp.dot function #1669
  • Added support of more number of data types and dimensions for input array in dpnp.linalg.inv function #1665
  • Added support of more number of data types for input array in dpnp.sort and dpnp.argsort functions, as well as implementing support of axis keyword #1660
  • Added support of more number of data types and dimensions for input array in dpnp.linalg.cholesky function, as well as implementing support of upper keyword #1638
  • Added support of more number of data types and dimensions for input array in dpnp.diff, as well as implementing support of prepend and append keywords #1637
  • Added support of more number of data types and dimensions for input array in dpnp.matmul function #1616
  • Added support of more number of data types and dimensions for input array in dpnp.linalg.det function #1607
  • Added support of more number of data types and dimensions for input array in dpnp.linalg.svd function, as well as implementing support of full_matrices, compute_uv and hermitian keywords #1604
  • Accepted different data types and dimensions of input arrays in dpnp.put_along_axis and dpnp.take_along_axis functions, as well as available values of axis keyword #1636
  • Added keepdims, initial and where keywords to dpnp.amax and dpnp.amin functions #1639
  • Extended dpnp.meshgrid function to support sparse and copy keyword arguments #1675
  • Extended dpnp.average function to support axis, weights, returned and keepdims keywords and dpnp.nansum function with axis, dtype, keepdims and out keyword arguments #1654
  • Extended dpnp.std, dpnp.var and nanvar functions to support axis, dtype, out and keepdims keyword arguments #1635
  • Extended dpnp.ogrid and dpnp.mgrid functions with support of device-aware keywords of compute follows data paradigm #1622
  • Extended dpnp.indices function to support dtype and sparse keyword arguments, as well as device-aware keywords of compute follows data paradigm #1622
  • Extended dpnp.count_nonzero function to support axis and keepdims keyword arguments #1615
  • Extended dpnp.put_along_axis and dpnp.take_along_axis functions to support out, dtype and casting keyword arguments #1608
  • Extended dpnp.stack and dpnp.concatenate functions to support out, dtype and casting keyword arguments #1608
  • Extended dpnp.vstack function to support dtype and casting keyword arguments #1595
  • Extended dpnp.diag, dpnp.diagflat, dpnp.ptp and dpnp.vander functions with support of extra keywords to align with compute follows data paradigm #1579
  • Extended dpnp.tri and dpnp.identity functions with support of device-aware keywords of compute follows data paradigm #1577
  • Added dedicated in-place kernels to dpnp.divide and dpnp.floor_divide functions #1587
  • Redesigned dpnp.cbrt and dpnp.exp2 functions through pybind11 extension of OneMKL call where possible or leveraging on dpctl.tensor implementation #1624
  • Redesigned dpnp.exp, dpnp.expm1, dpnp.log10, dpnp.log1p and dpnp.log2 functions through pybind11 extension of OneMKL call where possible or leveraging on dpctl.tensor implementation #1576
  • Redesigned dpnp.abs function through pybind11 extension of OneMKL call where possible or leveraging on dpctl.tensor implementation #1575
  • Redesigned dpnp.hypot function through pybind11 extension of OneMKL call where possible or leveraging on dpctl.tensor implementation #1560
  • Leveraged dpctl.tensor implementation for dpnp.reciprocal function #1650
  • Leveraged dpctl.tensor implementation for dpnp.mean function #1632
  • Leveraged dpctl.tensor implementation for dpnp.repeat function #1614
  • Leveraged dpctl.tensor implementation for dpnp.argmax and dpnp.argmin functions #1610
  • Leveraged dpctl.tensor implementation for dpnp.geomspace and dpnp.logspace functions #1603
  • Leveraged dpctl.tensor implementation for dpnp.max and dpnp.min functions #1602
  • Leveraged dpctl.tensor implementation for dpnp.astype function #1597
  • Leveraged dpctl.tensor implementation for dpnp.maximum and dpnp.minimum functions #1558

Fixed

  • Resolved potential raising of execution placement error from dpnp.take_along_axis and dpnp.put_along_axis functions #1702
  • Improved performance of dpnp.matmul and dpnp.dot function when out keyword is passed #1694
  • Completed documentation for each array creation functions #1674
  • Aligned dpnp.clip where both min and max keywords have None value with NumPy implementation #1670
  • Fixed a bug related to out keyword in elementwise functions #1656
  • Resolved compilation warnings due to -Wvla-extension option enabled by default #1651
  • Replaced deprecated IntelDPCPPConfig.cmake script with vendored IntelSYCLConfig.cmake #1611
  • Improved coverage report to include code of pybind11 extensions #1609
  • Improved performance of dpnp.atleast_2d and dpnp.atleast_3d functions and fixed to return a correct shape of resulting array #1560
Assets 4
Loading