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[JIT][WIP] memorization memory planning #63873
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💊 CI failures summary and remediationsAs of commit 20114a8 (more details on the Dr. CI page):
🕵️ 19 new failures recognized by patternsThe following CI failures do not appear to be due to upstream breakages: win-vs2019-cuda11.3-py3 / build (1/19)Step: "Build" (full log | diagnosis details | 🔁 rerun)
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Job | Step | Action |
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Lint / clang-format | Run clang-format | 🔁 rerun |
pytorch_xla_linux_bionic_py3_6_clang9_build | Build | 🔁 rerun |
pytorch_linux_xenial_py3_6_gcc5_4_build | Build | 🔁 rerun |
ci.pytorch.org: 1 failed
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ghstack-source-id: 67d22a0884a989ae76169025879d8c8c50099ad7 Pull Request resolved: #63873
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ghstack-source-id: 14e2f8ef811c0f24a617cf609218a10a3306aec4 Pull Request resolved: #63873
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This PR extends memory planning strategies to support memory allocations and frees collected using the `MemoryTracingAllocator` (which follows the pattern from kineto). These plans can then be deployed using `MemoryPlanningAllocator` in combination with `prim::PreAllocateTensor` ops (inserted into the graph) to appropriately give out slices of the initially allocated region. Differential Revision: [D30769097](https://our.internmc.facebook.com/intern/diff/D30769097) [ghstack-poisoned]
This PR extends memory planning strategies to support memory allocations and frees collected using the `MemoryTracingAllocator` (which follows the pattern from kineto). These plans can then be deployed using `MemoryPlanningAllocator` in combination with `prim::PreAllocateTensor` ops (inserted into the graph) to appropriately give out slices of the initially allocated region. Differential Revision: [D30769097](https://our.internmc.facebook.com/intern/diff/D30769097) [ghstack-poisoned]
ghstack-source-id: 5256d94abbf80ddda00980dade0623674bb05299 Pull Request resolved: #63873 reorder refactor profiling allocator put profiling back reconcile profiling ghstack-source-id: 5256d94abbf80ddda00980dade0623674bb05299 Pull Request resolved: #64351 use make_pair instead of make_tuple incorporate uniqueliverange fix tests whoops rename stuff size_t for memory tracing
This PR extends memory planning strategies to support memory allocations and frees collected using the `MemoryTracingAllocator` (which follows the pattern from kineto). These plans can then be deployed using `MemoryPlanningAllocator` in combination with `prim::PreAllocateTensor` ops (inserted into the graph) to appropriately give out slices of the initially allocated region. Differential Revision: [D30769097](https://our.internmc.facebook.com/intern/diff/D30769097) [ghstack-poisoned]
This PR extends memory planning strategies to support memory allocations and frees collected using the `MemoryTracingAllocator` (which follows the pattern from kineto). These plans can then be deployed using `MemoryPlanningAllocator` in combination with `prim::PreAllocateTensor` ops (inserted into the graph) to appropriately give out slices of the initially allocated region. Differential Revision: [D30769097](https://our.internmc.facebook.com/intern/diff/D30769097) [ghstack-poisoned]
This PR extends memory planning strategies to support memory allocations and frees collected using the `MemoryTracingAllocator` (which follows the pattern from kineto). These plans can then be deployed using `MemoryPlanningAllocator` in combination with `prim::PreAllocateTensor` ops (inserted into the graph) to appropriately give out slices of the initially allocated region. Differential Revision: [D30769097](https://our.internmc.facebook.com/intern/diff/D30769097) [ghstack-poisoned]
This PR extends memory planning strategies to support memory allocations and frees collected using the `MemoryTracingAllocator` (which follows the pattern from kineto). These plans can then be deployed using `MemoryPlanningAllocator` in combination with `prim::PreAllocateTensor` ops (inserted into the graph) to appropriately give out slices of the initially allocated region. Differential Revision: [D30769097](https://our.internmc.facebook.com/intern/diff/D30769097) [ghstack-poisoned]
ghstack-source-id: 132dc0c37f92f5ad0c855da06adc6a41f82f6574 Pull Request resolved: #63873 reorder refactor profiling allocator put profiling back reconcile profiling ghstack-source-id: 132dc0c37f92f5ad0c855da06adc6a41f82f6574 Pull Request resolved: #64351 use make_pair instead of make_tuple incorporate uniqueliverange fix tests whoops rename stuff size_t for memory tracing
This PR extends memory planning strategies to support memory allocations and frees collected using the `MemoryTracingAllocator` (which follows the pattern from kineto). These plans can then be deployed using `MemoryPlanningAllocator` in combination with `prim::PreAllocateTensor` ops (inserted into the graph) to appropriately give out slices of the initially allocated region. Differential Revision: [D30769097](https://our.internmc.facebook.com/intern/diff/D30769097) [ghstack-poisoned]
ghstack-source-id: b038aa015025f59110466e1326512379c97b9427 Pull Request resolved: #63873 reorder refactor profiling allocator put profiling back reconcile profiling ghstack-source-id: b038aa015025f59110466e1326512379c97b9427 Pull Request resolved: #64351 use make_pair instead of make_tuple incorporate uniqueliverange fix tests whoops rename stuff size_t for memory tracing
This PR extends memory planning strategies to support memory allocations and frees collected using the `MemoryTracingAllocator` (which follows the pattern from kineto). These plans can then be deployed using `MemoryPlanningAllocator` in combination with `prim::PreAllocateTensor` ops (inserted into the graph) to appropriately give out slices of the initially allocated region. Differential Revision: [D30769097](https://our.internmc.facebook.com/intern/diff/D30769097) [ghstack-poisoned]
ghstack-source-id: db94a55a0dd8eabf662ea9ae260ffb62f1c8bdb6 Pull Request resolved: #63873 reorder refactor profiling allocator put profiling back reconcile profiling ghstack-source-id: db94a55a0dd8eabf662ea9ae260ffb62f1c8bdb6 Pull Request resolved: #64351 use make_pair instead of make_tuple incorporate uniqueliverange fix tests whoops rename stuff size_t for memory tracing
CI Flow Status⚛️ CI FlowRuleset - Version:
You can add a comment to the PR and tag @pytorchbot with the following commands: # ciflow rerun, "ciflow/default" will always be added automatically
@pytorchbot ciflow rerun
# ciflow rerun with additional labels "-l <ciflow/label_name>", which is equivalent to adding these labels manually and trigger the rerun
@pytorchbot ciflow rerun -l ciflow/scheduled -l ciflow/slow For more information, please take a look at the CI Flow Wiki. |
@makslevental has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
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Looks like this PR hasn't been updated in a while so we're going to go ahead and mark this as |
Stack from ghstack:
This PR extends memory planning strategies to support memory allocations and frees collected using the
MemoryTracingAllocator
(which follows the pattern from kineto). These plans can then be deployed usingMemoryPlanningAllocator
in combination withprim::PreAllocateTensor
ops (inserted into the graph) to appropriately give out slices of the initially allocated region.Differential Revision: D30769097