Ensure Consistent Use of List Type for block_type Shape Argument in semantic.py and interpreter.py #5128
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peterbell10
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simonidaa
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…emantic.py and interpreter.py (triton-lang#5128) ## Description: This pull request addresses a type compatibility issue in the block_type constructor across semantic.py and interpreter.py, specifically where the shape parameter, expected as a List, was being provided as a Tuple in certain cases. This PR is intended to fix issues identified in triton-lang#4860. ### Summary of Changes: 1. semantic.py - Updates in histogram Function and device_assert: - histogram Function: The shape parameter was previously passed as a Tuple when calling the block_type constructor. This has now been updated to a List to align with the constructor's requirements and ensure type consistency. - device_assert Function: The device_assert function’s cond_ty and cond assignments have been updated similarly. The block_type constructor and create_splat call were previously provided a Tuple; this has been updated to a List in both cases. 2. interpreter.py - Adjustment in ReduceOps.sum Method: - In ReduceOps.sum, the to_tensor function was called with a numpy.ndarray whose shape attribute is a Tuple. This shape is now converted to a List before passing it to block_type. ### New Test Addition: Added a new test to cover scenarios where a histogram operation is followed by a broadcasting operation. Co-authored-by: maxim.m66 <[email protected]> Co-authored-by: Maxim <[email protected]> Co-authored-by: peterbell10 <[email protected]>
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Description:
This pull request addresses a type compatibility issue in the block_type constructor across semantic.py and interpreter.py, specifically where the shape parameter, expected as a List, was being provided as a Tuple in certain cases.
This PR is intended to fix issues identified in #4860.
Summary of Changes:
New Test Addition:
Added a new test to cover scenarios where a histogram operation is followed by a broadcasting operation.
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I am not making a trivial change, such as fixing a typo in a comment.
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