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v4.3 update. (#2709)

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* v4.3 update.

* Update the cute_dsl_api changelog's doc link

* Update version to 4.3.0

* Update the example link

* Update doc to encourage user to install DSL from requirements.txt

---------

Co-authored-by: Larry Wu <larwu@nvidia.com>
This commit is contained in:
Junkai-Wu
2025-10-22 02:26:30 +08:00
committed by GitHub
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19
media/docs/pythonDSL/cute_dsl_general/framework_integration.rst
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@ -63,7 +63,7 @@ The full signature of from_dlpack is as follows:
.. code-block:: python
def from_dlpack(tensor, assumed_align=None):
def from_dlpack(tensor, assumed_align=None, use_32bit_stride=False):
The ``assumed_align`` integer parameter specifies the alignment of the tensor in unit of bytes.
The tensor's base address must be divisible by ``assumed_align``. When not provided explicitly,
@ -72,6 +72,13 @@ information is part of the pointer type in the generated IR. Therefore, programs
alignments have a different IR and identical IRs are required for hitting the kernel caching
mechanism of |DSL|.
The ``use_32bit_stride`` parameter determines whether to use 32-bit stride for the tensor's dynamic stride values.
By default, it is set to False (64bit) to ensure that address calculations do not risk overflow. For smaller
problem sizes (where ``cosize(layout_of_tensor) <= Int32_MAX``), users may set it to True (32bit) to improve performance
by reducing register usage and the number of address calculation instructions. When ``use_32bit_stride`` is set
to True, a runtime check is performed to ensure that the layout does not overflow. Please note that this parameter
only has an effect when the tensor's layout is marked as dynamic.
Code Example
~~~~~~~~~~~~
@ -242,6 +249,10 @@ The following example demonstrates how to use ``mark_layout_dynamic`` to specify
t7 = from_dlpack(b).mark_layout_dynamic(leading_dim=3)
# Expected strides[leading_dim] == 1, but got 4
c = torch.empty(1000000000, 1000000000)
t8 = from_dlpack(c, use_32bit_stride=True).mark_layout_dynamic()
# Layout in DLTensorWrapper has int32 overflow risk. Please set use_32bit_stride to False.
Mark the Tensor's Layout as Dynamic with ``mark_compact_shape_dynamic``
-----------------------------------------------------------------------
@ -398,6 +409,12 @@ The following example demonstrates how to use ``mark_compact_shape_dynamic`` to
)
# The stride_order is not consistent with the layout
c = torch.empty(1000000000, 1000000000)
t13 = from_dlpack(c, use_32bit_stride=True).mark_compact_shape_dynamic(
mode=0, divisibility=1
)
# Layout in DLTensorWrapper has int32 overflow risk. Please set use_32bit_stride to False.
Bypass the DLPack Protocol
--------------------------