Refactor Distributors to make it acutally do its jobs #68
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…ch#68) Summary: In the current Shampoo design, there are three major components: `DistributedShampoo`, which describes the high-level algorithm flow; `Distributor`, which manages the distribution of parameters for different computing paradigms (e.g., DDP, FSDP, HSDP, etc.); and `PreconditionerList`, which contains the detailed algorithm implementation. The `Distributor` manages the distribution of parameters and then sends them to `DistributedShampoo` which invokes the corresponding algorithms implemented by each `PreconditionerList`. Since the `Distributor` handles parameter distribution, ideally, downstream classes (i.e., `DistributedShampoo` and `PreconditionerList`) should not need to use `Distributor.distributor_selector` to compress parameters for their use. However, in the current implementation, such usages appear in both [`DistributedShampoo`](https://www.internalfb.com/code/fbsource/[20bcdb4983a16c2cd7f00995754851159da91ed3]/fbcode/hpc/optimizers/distributed_shampoo/dev/distributed_shampoo.py?lines=614-617) and [`PreconditionerList`](https://www.internalfb.com/code/fbsource/[20bcdb4983a16c2cd7f00995754851159da91ed3]/fbcode/hpc/optimizers/distributed_shampoo/dev/utils/shampoo_preconditioner_list.py?lines=145-146). The main changes are listed as follows: 1. `Distributor` now only provides access to the local version of `params` and `block_info` to align with its responsibilities. 2. `Distributor` no longer needs to store `global_block_info_list`, the global version of `block_info`; instead, it stores `local_block_info_list`. 3. `PreconditionerList` no longer requires `distributor_selector` as an input argument because `Distributor` already performs this task. Differential Revision: D64708506
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…ch#68) Summary: In the current Shampoo design, there are three major components: `DistributedShampoo`, which describes the high-level algorithm flow; `Distributor`, which manages the distribution of parameters for different computing paradigms (e.g., DDP, FSDP, HSDP, etc.); and `PreconditionerList`, which contains the detailed algorithm implementation. The `Distributor` manages the distribution of parameters and then sends them to `DistributedShampoo` which invokes the corresponding algorithms implemented by each `PreconditionerList`. Since the `Distributor` handles parameter distribution, ideally, downstream classes (i.e., `DistributedShampoo` and `PreconditionerList`) should not need to use `Distributor.distributor_selector` to compress parameters for their use. However, in the current implementation, such usages appear in both [`DistributedShampoo`](https://www.internalfb.com/code/fbsource/[20bcdb4983a16c2cd7f00995754851159da91ed3]/fbcode/hpc/optimizers/distributed_shampoo/dev/distributed_shampoo.py?lines=614-617) and [`PreconditionerList`](https://www.internalfb.com/code/fbsource/[20bcdb4983a16c2cd7f00995754851159da91ed3]/fbcode/hpc/optimizers/distributed_shampoo/dev/utils/shampoo_preconditioner_list.py?lines=145-146). The main changes are listed as follows: 1. `Distributor` now only provides access to the local version of `params` and `block_info` to align with its responsibilities. 2. `Distributor` no longer needs to store `global_block_info_list`, the global version of `block_info`; instead, it stores `local_block_info_list`. 3. `PreconditionerList` no longer requires `distributor_selector` as an input argument because `Distributor` already performs this task. Reviewed By: chuanhaozhuge Differential Revision: D64708506
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…ch#68) Summary: In the current Shampoo design, there are three major components: `DistributedShampoo`, which describes the high-level algorithm flow; `Distributor`, which manages the distribution of parameters for different computing paradigms (e.g., DDP, FSDP, HSDP, etc.); and `PreconditionerList`, which contains the detailed algorithm implementation. The `Distributor` manages the distribution of parameters and then sends them to `DistributedShampoo` which invokes the corresponding algorithms implemented by each `PreconditionerList`. Since the `Distributor` handles parameter distribution, ideally, downstream classes (i.e., `DistributedShampoo` and `PreconditionerList`) should not need to use `Distributor.distributor_selector` to compress parameters for their use. However, in the current implementation, such usages appear in both [`DistributedShampoo`](https://www.internalfb.com/code/fbsource/[20bcdb4983a16c2cd7f00995754851159da91ed3]/fbcode/hpc/optimizers/distributed_shampoo/dev/distributed_shampoo.py?lines=614-617) and [`PreconditionerList`](https://www.internalfb.com/code/fbsource/[20bcdb4983a16c2cd7f00995754851159da91ed3]/fbcode/hpc/optimizers/distributed_shampoo/dev/utils/shampoo_preconditioner_list.py?lines=145-146). The main changes are listed as follows: 1. `Distributor` now only provides access to the local version of `params` and `block_info` to align with its responsibilities. 2. `Distributor` no longer needs to store `global_block_info_list`, the global version of `block_info`; instead, it stores `local_block_info_list`. 3. `PreconditionerList` no longer requires `distributor_selector` as an input argument because `Distributor` already performs this task. Reviewed By: chuanhaozhuge Differential Revision: D64708506
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…ch#68) Summary: In the current Shampoo design, there are three major components: `DistributedShampoo`, which describes the high-level algorithm flow; `Distributor`, which manages the distribution of parameters for different computing paradigms (e.g., DDP, FSDP, HSDP, etc.); and `PreconditionerList`, which contains the detailed algorithm implementation. The `Distributor` manages the distribution of parameters and then sends them to `DistributedShampoo` which invokes the corresponding algorithms implemented by each `PreconditionerList`. Since the `Distributor` handles parameter distribution, ideally, downstream classes (i.e., `DistributedShampoo` and `PreconditionerList`) should not need to use `Distributor.distributor_selector` to compress parameters for their use. However, in the current implementation, such usages appear in both [`DistributedShampoo`](https://www.internalfb.com/code/fbsource/[20bcdb4983a16c2cd7f00995754851159da91ed3]/fbcode/hpc/optimizers/distributed_shampoo/dev/distributed_shampoo.py?lines=614-617) and [`PreconditionerList`](https://www.internalfb.com/code/fbsource/[20bcdb4983a16c2cd7f00995754851159da91ed3]/fbcode/hpc/optimizers/distributed_shampoo/dev/utils/shampoo_preconditioner_list.py?lines=145-146). The main changes are listed as follows: 1. `Distributor` now only provides access to the local version of `params` and `block_info` to align with its responsibilities. 2. `Distributor` no longer needs to store `global_block_info_list`, the global version of `block_info`; instead, it stores `local_block_info_list`. 3. `PreconditionerList` no longer requires `distributor_selector` as an input argument because `Distributor` already performs this task. Reviewed By: chuanhaozhuge Differential Revision: D64708506
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…ch#68) Summary: In the current Shampoo design, there are three major components: `DistributedShampoo`, which describes the high-level algorithm flow; `Distributor`, which manages the distribution of parameters for different computing paradigms (e.g., DDP, FSDP, HSDP, etc.); and `PreconditionerList`, which contains the detailed algorithm implementation. The `Distributor` manages the distribution of parameters and then sends them to `DistributedShampoo` which invokes the corresponding algorithms implemented by each `PreconditionerList`. Since the `Distributor` handles parameter distribution, ideally, downstream classes (i.e., `DistributedShampoo` and `PreconditionerList`) should not need to use `Distributor.distributor_selector` to compress parameters for their use. However, in the current implementation, such usages appear in both [`DistributedShampoo`](https://www.internalfb.com/code/fbsource/[20bcdb4983a16c2cd7f00995754851159da91ed3]/fbcode/hpc/optimizers/distributed_shampoo/dev/distributed_shampoo.py?lines=614-617) and [`PreconditionerList`](https://www.internalfb.com/code/fbsource/[20bcdb4983a16c2cd7f00995754851159da91ed3]/fbcode/hpc/optimizers/distributed_shampoo/dev/utils/shampoo_preconditioner_list.py?lines=145-146). The main changes are listed as follows: 1. `Distributor` now only provides access to the local version of `params` and `block_info` to align with its responsibilities. 2. `Distributor` no longer needs to store `global_block_info_list`, the global version of `block_info`; instead, it stores `local_block_info_list`. 3. `PreconditionerList` no longer requires `distributor_selector` as an input argument because `Distributor` already performs this task. Reviewed By: anana10c, chuanhaozhuge Differential Revision: D64708506
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…ch#68) Summary: In the current Shampoo design, there are three major components: `DistributedShampoo`, which describes the high-level algorithm flow; `Distributor`, which manages the distribution of parameters for different computing paradigms (e.g., DDP, FSDP, HSDP, etc.); and `PreconditionerList`, which contains the detailed algorithm implementation. The `Distributor` manages the distribution of parameters and then sends them to `DistributedShampoo` which invokes the corresponding algorithms implemented by each `PreconditionerList`. Since the `Distributor` handles parameter distribution, ideally, downstream classes (i.e., `DistributedShampoo` and `PreconditionerList`) should not need to use `Distributor.distributor_selector` to compress parameters for their use. However, in the current implementation, such usages appear in both [`DistributedShampoo`](https://www.internalfb.com/code/fbsource/[20bcdb4983a16c2cd7f00995754851159da91ed3]/fbcode/hpc/optimizers/distributed_shampoo/dev/distributed_shampoo.py?lines=614-617) and [`PreconditionerList`](https://www.internalfb.com/code/fbsource/[20bcdb4983a16c2cd7f00995754851159da91ed3]/fbcode/hpc/optimizers/distributed_shampoo/dev/utils/shampoo_preconditioner_list.py?lines=145-146). The main changes are listed as follows: 1. `Distributor` now only provides access to the local version of `params` and `block_info` to align with its responsibilities. 2. `Distributor` no longer needs to store `global_block_info_list`, the global version of `block_info`; instead, it stores `local_block_info_list`. 3. `PreconditionerList` no longer requires `distributor_selector` as an input argument because `Distributor` already performs this task. Reviewed By: anana10c, chuanhaozhuge Differential Revision: D64708506
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…ch#68) Summary: In the current Shampoo design, there are three major components: `DistributedShampoo`, which describes the high-level algorithm flow; `Distributor`, which manages the distribution of parameters for different computing paradigms (e.g., DDP, FSDP, HSDP, etc.); and `PreconditionerList`, which contains the detailed algorithm implementation. The `Distributor` manages the distribution of parameters and then sends them to `DistributedShampoo` which invokes the corresponding algorithms implemented by each `PreconditionerList`. Since the `Distributor` handles parameter distribution, ideally, downstream classes (i.e., `DistributedShampoo` and `PreconditionerList`) should not need to use `Distributor.distributor_selector` to compress parameters for their use. However, in the current implementation, such usages appear in both [`DistributedShampoo`](https://www.internalfb.com/code/fbsource/[20bcdb4983a16c2cd7f00995754851159da91ed3]/fbcode/hpc/optimizers/distributed_shampoo/dev/distributed_shampoo.py?lines=614-617) and [`PreconditionerList`](https://www.internalfb.com/code/fbsource/[20bcdb4983a16c2cd7f00995754851159da91ed3]/fbcode/hpc/optimizers/distributed_shampoo/dev/utils/shampoo_preconditioner_list.py?lines=145-146). The main changes are listed as follows: 1. `Distributor` now only provides access to the local version of `params` and `block_info` to align with its responsibilities. 2. `Distributor` no longer needs to store `global_block_info_list`, the global version of `block_info`; instead, it stores `local_block_info_list`. 3. `PreconditionerList` no longer requires `distributor_selector` as an input argument because `Distributor` already performs this task. Reviewed By: anana10c, chuanhaozhuge Differential Revision: D64708506
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Summary:
In the current Shampoo design, there are three major components:
DistributedShampoo, which describes the high-level algorithm flow;Distributor, which manages the distribution of parameters for different computing paradigms (e.g., DDP, FSDP, HSDP, etc.); andPreconditionerList, which contains the detailed algorithm implementation.The
Distributormanages the distribution of parameters and then sends them toDistributedShampoowhich invokes the corresponding algorithms implemented by eachPreconditionerList.Since the
Distributorhandles parameter distribution, ideally, downstream classes (i.e.,DistributedShampooandPreconditionerList) should not need to useDistributor.distributor_selectorto compress parameters for their use. However, in the current implementation, such usages appear in bothDistributedShampooandPreconditionerList.The main changes are listed as follows:
Distributornow only provides access to the local version ofparamsandblock_infoto align with its responsibilities.Distributorno longer needs to storeglobal_block_info_list, the global version ofblock_info; instead, it storeslocal_block_info_list.PreconditionerListno longer requiresdistributor_selectoras an input argument becauseDistributoralready performs this task.Differential Revision: D64708506