[Lang] Remove deprecated compile option ndarray_use_cached_allocator #7937
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…aichi-dev#7937) Issue: # ### Brief Summary <!-- copilot:summary --> ### <samp>🤖 Generated by Copilot at b10a055</samp> Removed the `use_cached` flag and related parameters from various classes and functions that handle memory allocation for different devices. This flag was unnecessary and redundant, as all devices now use a caching allocator by default. This simplifies the code and reduces the complexity of the memory management logic. ### Walkthrough <!-- copilot:walkthrough --> ### <samp>🤖 Generated by Copilot at b10a055</samp> * Remove `ndarray_use_cached_allocator` flag and simplify memory allocation logic for different devices * Eliminate `ndarray_use_cached_allocator` field from `CompileConfig` struct and class ([link](https://github.com/taichi-dev/taichi/pull/7937/files?diff=unified&w=0#diff-84b498f7923f43bc9e292dffb7b3d9a0cb7da1c16ddd0062af184a1b7b777976L45), [link](https://github.com/taichi-dev/taichi/pull/7937/files?diff=unified&w=0#diff-604e33db5b7c4f4b819098dee1f2634a36c0974822c1538aec0d57d28ca00dd9L40), [link](https://github.com/taichi-dev/taichi/pull/7937/files?diff=unified&w=0#diff-af631a0c71978fe591e17005f01f7c06bc30ae36c65df306bbb3b08ade770167L196-L197)) * Remove `use_cached` parameter and field from `allocate_memory_runtime` function and `DeviceAllocation` struct in `CUDADevice` and `AMDGPUDevice` classes ([link](https://github.com/taichi-dev/taichi/pull/7937/files?diff=unified&w=0#diff-e0843d34a17298595cd26f5b47b1933a0d18c5c795b0c91b73ec8541a2cdd3f9L59-R59), [link](https://github.com/taichi-dev/taichi/pull/7937/files?diff=unified&w=0#diff-e0843d34a17298595cd26f5b47b1933a0d18c5c795b0c91b73ec8541a2cdd3f9L65-R67), [link](https://github.com/taichi-dev/taichi/pull/7937/files?diff=unified&w=0#diff-7919f5d7e33aafc72f27ed93febc58a0ac77c220ae718bf78ef134dad3790654L54-R54), [link](https://github.com/taichi-dev/taichi/pull/7937/files?diff=unified&w=0#diff-7919f5d7e33aafc72f27ed93febc58a0ac77c220ae718bf78ef134dad3790654L61-R63)) * Remove `use_cached` parameter from `allocate_memory` function in `LlvmRuntime` class and `allocate_memory_runtime` function call in `allocate_memory_ndarray` function ([link](https://github.com/taichi-dev/taichi/pull/7937/files?diff=unified&w=0#diff-10c4f36944f322074d4a7f5e6d1878ada018992f7c965f6944c60d4468f7719dL55-R61), [link](https://github.com/taichi-dev/taichi/pull/7937/files?diff=unified&w=0#diff-b9155792159f392bd8bacd44cb1819be5239b022d707499fc364c0f93dd8c5e5L478)) * Remove `use_cached` field from `LlvmDevice` class ([link](https://github.com/taichi-dev/taichi/pull/7937/files?diff=unified&w=0#diff-96f2f848955ca34e50c83bdaa4b970cd7d60ac595e924f626c4568a03a43658eL13)) * Remove `ndarray_use_cached_allocator` parameter from `test` decorator in `test_ndarray_caching_allocator` function in `test_ndarray.py` ([link](https://github.com/taichi-dev/taichi/pull/7937/files?diff=unified&w=0#diff-ca3c8d1edb25b6a7f4affbb79b2e3e74f73b3757e5d465258ce42ea9eb09fbc0L281-R281))
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Issue: #
Brief Summary
🤖 Generated by Copilot at b10a055
Removed the
use_cachedflag and related parameters from various classes and functions that handle memory allocation for different devices. This flag was unnecessary and redundant, as all devices now use a caching allocator by default. This simplifies the code and reduces the complexity of the memory management logic.Walkthrough
🤖 Generated by Copilot at b10a055
ndarray_use_cached_allocatorflag and simplify memory allocation logic for different devicesndarray_use_cached_allocatorfield fromCompileConfigstruct and class (link, link, link)use_cachedparameter and field fromallocate_memory_runtimefunction andDeviceAllocationstruct inCUDADeviceandAMDGPUDeviceclasses (link, link, link, link)use_cachedparameter fromallocate_memoryfunction inLlvmRuntimeclass andallocate_memory_runtimefunction call inallocate_memory_ndarrayfunction (link, link)use_cachedfield fromLlvmDeviceclass (link)ndarray_use_cached_allocatorparameter fromtestdecorator intest_ndarray_caching_allocatorfunction intest_ndarray.py(link)