Shard grouped conv bwd data instances

[bartekxk]

Proposed changes

Shard grouped conv bwd data instances to improve compilation time

Checklist

Please put an x into the boxes that apply. You can also fill these out after creating the PR. If you're not sure, please don't hesitate to ask.

• I have added tests relevant to the introduced functionality, and the unit tests are passing locally
• I have added the test to REGRESSION_TESTS list defined at the top of CMakeLists.txt in tests/CMakeLists.txt, IF the test takes more than 30 seconds to run.
• I have added inline documentation which enables the maintainers with understanding the motivation
• I have removed the stale documentation which is no longer relevant after this pull request
• (If this change is user-facing) I have added release notes which provide the end users with a brief summary of the improvement from this pull request
• I have run clang-format on all changed files
• Any dependent changes have been merged

Discussion

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[Copilot]

Pull Request Overview

This pull request implements sharding for grouped convolution backward data instances to improve compilation time. The changes transform monolithic instance files into sharded templates using a modulo-based filtering approach.

• Transforms function-based instance generation to template-based sharded instantiation
• Introduces sharding with different numbers of shards for various data types and configurations
• Refactors CMakeLists.txt to use the new sharding infrastructure

Reviewed Changes

Copilot reviewed 72 out of 72 changed files in this pull request and generated no comments.

File	Description
CMakeLists.txt files	Replace hardcoded file lists with sharded instance generation
Instance template files (.in)	Convert functions to templated sharded functions with modulo filtering
Header files (.inc/.hpp)	Update function declarations to match renamed functions
Source files (.cpp)	Fix function name consistency in scale and bilinear variants

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