Remove NumPy argument support for dpex kernels #866
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- The compiler module only contains the compiler pipeline
to compiler SpirvKernel objects.
- Creates a separate module for the unpack and pack
functions for kernel arguments.
- The new API is intended for use from the Dispatcher class.
- The concept of a kernel was decoupled from the notion of
dispatching of a kernel. The present implementation in
compiler.py intermixes both things, making hard the
separation of compute-follows-data based kernel launch
and legacy `dpctl.device_context` based behavior.
- Deprecates support for numpy arrays as kernel args.
- Deprecates support for the square bracket notation using
`__getitem__` to provide global and local ranges for a
kernel launch.
- Changes the behavior of specializing a kernel using only
a signature. The new way to specialize will require a
device type and a backend.
- Improvements to exception messages using custom exceptions.
- The new API is now inside `numba_dpex.core.kernel_interface`.
Fix docs rst
- Kernel specialization for specific signatures was fixed. - Specialization is only allowed for usm_ndarray. - Dispacther class was renamed as JitKernel. - decorators updated.
- print a better type name with keywords and all attributes.
- store a fully qualified filter string in the type.
- set the default address space to GLOBAL instead of None.
- fix the unify function to test on usm_type, device, address
space.
- Added unit tests for the kernel specialization feature.
- Fix kernel decorator to support list of signatures.
- Disallow JIT compilation of a specialized kernel and raise
an exception.
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Removed test_black_scholes.py. Renamed dppy to dpex in two test files.
- The compute follows data checking is now based on queue
equality.
- USMNdArray no longer requires usm_type and device
during construction. It allows us to specialize an usm_ndarray
only on ndims, layout and dtype.
- No check for compute follows data for eager compilation.
- Change caching to not require backend and device-type.
- Fixes to test cases.
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…Python/numba-dpex into refactor/kernel_interfaces
…Python/numba-dpex into refactor/kernel_interfaces
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Superseded by #1049 |
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We will stop supporting NumPy arrays as arguments to kernel. The following API changes need to be made:
target.TypingContext. Instead if a NumPy array argument is detected raise an exception.