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Merge pull request #1469 from IntelPython/origin-gh-pages
Manually update gh-pages for 0.23.0 release.
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0.23.0/.buildinfo

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# Sphinx build info version 1
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# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
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config: a41f3370922f21b5ece5433b91ecd52a
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config: d1a7806fc9c6a8d9394e1e860f163b50
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tags: 645f666f9bcd5a90fca523b33c5a78b7
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:orphan:
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numba_dpex.core.boxing.ranges
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=============================
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.. py:module:: numba_dpex.core.boxing.ranges
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Overview
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--------
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.. list-table:: Function
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:header-rows: 0
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:widths: auto
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:class: summarytable
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* - :py:obj:`unbox_range <numba_dpex.core.boxing.ranges.unbox_range>`\ (typ, obj, c)
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- Converts a Python Range object to numba-dpex's native struct representation
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* - :py:obj:`unbox_ndrange <numba_dpex.core.boxing.ranges.unbox_ndrange>`\ (typ, obj, c)
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- Converts a Python Range object to numba-dpex's native struct representation
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* - :py:obj:`box_range <numba_dpex.core.boxing.ranges.box_range>`\ (typ, val, c)
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- Convert a native range structure to a Range object.
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* - :py:obj:`box_ndrange <numba_dpex.core.boxing.ranges.box_ndrange>`\ (typ, val, c)
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- Convert a native range structure to a Range object.
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Functions
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---------
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.. py:function:: unbox_range(typ, obj, c)
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Converts a Python Range object to numba-dpex's native struct representation
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for RangeType.
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.. py:function:: unbox_ndrange(typ, obj, c)
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Converts a Python Range object to numba-dpex's native struct representation
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for NdRangeType.
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.. py:function:: box_range(typ, val, c)
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Convert a native range structure to a Range object.
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.. py:function:: box_ndrange(typ, val, c)
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Convert a native range structure to a Range object.
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numba_dpex.core.boxing.usm_ndarray
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==================================
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.. py:module:: numba_dpex.core.boxing.usm_ndarray
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Overview
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--------
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.. list-table:: Function
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:header-rows: 0
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:widths: auto
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:class: summarytable
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* - :py:obj:`unbox_dpnp_nd_array <numba_dpex.core.boxing.usm_ndarray.unbox_dpnp_nd_array>`\ (typ, obj, c)
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- Converts a dpctl.tensor.usm_ndarray/dpnp.ndarray object to a Numba-dpex
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* - :py:obj:`box_array <numba_dpex.core.boxing.usm_ndarray.box_array>`\ (typ, val, c)
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- Boxes a NativeValue representation of USMNdArray/DpnpNdArray type into a
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Functions
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---------
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.. py:function:: unbox_dpnp_nd_array(typ, obj, c)
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Converts a dpctl.tensor.usm_ndarray/dpnp.ndarray object to a Numba-dpex
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internal array structure.
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:param typ: The Numba type of the PyObject
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:param obj: The actual PyObject to be unboxed
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:param c: The unboxing context
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Returns: A NativeValue object representing an unboxed
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dpctl.tensor.usm_ndarray/dpnp.ndarray
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.. py:function:: box_array(typ, val, c)
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Boxes a NativeValue representation of USMNdArray/DpnpNdArray type into a
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dpctl.tensor.usm_ndarray/dpnp.ndarray PyObject
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:param typ: The representation of the USMNdArray/DpnpNdArray type.
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:param val: A native representation of a Numba USMNdArray/DpnpNdArray type
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object.
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:param c: The boxing context.
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Returns: A Pyobject for a dpctl.tensor.usm_ndarray/dpnp.ndarray boxed from
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the Numba-dpex native value.
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numba_dpex.core.config
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======================
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.. py:module:: numba_dpex.core.config
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.. autoapi-nested-parse::
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The config options are meant to provide extra information and tweak optimization
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configurations to help debug code generation issues.
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There are two ways of setting these config options:
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- Config options can be directly set programmatically, *e.g.*,
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.. code-block:: python
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from numba_dpex.core.config import DUMP_KERNEL_LLVM
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DUMP_KERNEL_LLVM = 1
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- The options can also be set globally using environment flags. The name of the
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environment variable for every config option is annotated next to its
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definition.
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.. code-block:: bash
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export NUMBA_DPEX_DUMP_KERNEL_LLVM = 1
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Attributes
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----------
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.. py:data:: SAVE_IR_FILES
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:type: Annotated[int, Save the IR files (LLVM and SPIRV-V) generated for each kernel to current directory, default = 0, ENVIRONMENT FLAG: NUMBA_DPEX_SAVE_IR_FILES]
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.. py:data:: OFFLOAD_DIAGNOSTICS
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:type: Annotated[int, Print diagnostic information for automatic offloading of parfor nodes to kernels, default = 0, ENVIRONMENT FLAG: NUMBA_DPEX_OFFLOAD_DIAGNOSTICS]
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.. py:data:: DEBUG
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:type: Annotated[int, Generates extra debug prints when set to a non-zero value, default = 0, ENVIRONMENT FLAG: NUMBA_DPEX_DEBUG]
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.. py:data:: DEBUGINFO_DEFAULT
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:type: Annotated[int, Compiles in the debug mode generating debug symbols in the compiler IR. It is a global way of setting the "debug" keyword for all numba_dpex.kernel and numba_dpex.device_func decorators used in a program., default = 0, ENVIRONMENT FLAG: NUMBA_DPEX_DEBUGINFO]
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.. py:data:: DUMP_KERNEL_LLVM
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:type: Annotated[int, Writes the optimized LLVM IR generated for a numba_dpex.kernel decorated function to current directory, default = 0, ENVIRONMENT FLAG: NUMBA_DPEX_DUMP_KERNEL_LLVM]
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.. py:data:: DUMP_KERNEL_LAUNCHER
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:type: Annotated[int, Writes the optimized LLVM IR generated for every numba_dpex.call_kernel function to current directory, default = 0, ENVIRONMENT FLAG: NUMBA_DPEX_DUMP_KERNEL_LAUNCHER]
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.. py:data:: DEBUG_KERNEL_LAUNCHER
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:type: Annotated[int, Enables debug printf messages inside the compiled module generated for a numba_dpex.call_kernel function.default = 0, ENVIRONMENT FLAG: NUMBA_DPEX_DEBUG_KERNEL_LAUNCHER]
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.. py:data:: BUILD_KERNEL_OPTIONS
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:type: Annotated[str, Can use used to pass extra flags to the device driver compiler during kernel compilation. For available OpenCL options refer https://intel.github.io/llvm-docs/clang/ClangCommandLineReference.html#opencl-options, default = "", ENVIRONMENT FLAG: NUMBA_DPEX_BUILD_KERNEL_OPTIONS]
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.. py:data:: TESTING_SKIP_NO_DEBUGGING
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.. py:data:: TESTING_LOG_DEBUGGING
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:type: Annotated[int, Generates extra logs when using gdb to debug a kernel, defaults = 0, ENVIRONMENT_FLAG: NUMBA_DPEX_TESTING_LOG_DEBUGGING]
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.. py:data:: DPEX_OPT
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:type: Annotated[int, Sets the optimization level globally for every function compiled by numba-dpex, default = 2, ENVIRONMENT_FLAG: NUMBA_DPEX_OPT]
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.. py:data:: INLINE_THRESHOLD
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:type: Annotated[int, Sets the inlining-threshold level globally for every function compiled by numba-dpex. A higher value enables more aggressive inlining settings for the compiler. Note: Even if NUMBA_DPEX_INLINE_THRESHOLD is set to 0, many internal functions that are attributed "alwaysinline" will still get inlined., default = 2, ENVIRONMENT_FLAG: NUMBA_DPEX_INLINE_THRESHOLD]
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