[ET-VK] Clean up api::vTensor class #3149
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Differential Revision: [D55811279](https://our.internmc.facebook.com/intern/diff/D55811279/) [ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/3149
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This pull request was exported from Phabricator. Differential Revision: D55811279 |
This was referenced Apr 19, 2024
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## Context Now that we have forked the `api/` directory from PyTorch Vulkan, we can clean up the `vTensor` class and remove functionality that is not necessary for the ExecuTorch Vulkan delegate. The following changes are made: * Remove unused member variables and member functions from `vTensor` and `vTensorStorage` * Remove all quantization related member variables, member functions, and the `vTensor` constructor for quantized tensors. The Quantization API will be reworked from the ground up. * Rename `view_` (which is an instance of `vTensorStorage`) to `storage_` Finally, the critical change that is introduced is that we now store `storage_` as a direct `vTensorStorage` member variable in `vTensor` instead of storing it as a `std::shared_ptr<vTensorStorage>`. For context, the reason `storage_` was stored as a shared pointer is to be compliant with ATen Tensors, which needs to enable copy construction to enable the following: ``` at::Tensor b = at::rand(...); // Oftentimes this will create a "view" of the tensor. a and b will point the the same underlying storage, but with different metadata. at::Tensor a = b; ``` However, in the ExecuTorch delegate this is no longer necessary. Each Tensor is associated with it's own independent storage and is responsible for managing it's own memory. **By getting rid of `std::shared_ptr`, we can avoid a heap allocation and avoid chasing pointers whenever we need to access the resources of a `vTensor`.** Differential Revision: [D55811279](https://our.internmc.facebook.com/intern/diff/D55811279/) [ghstack-poisoned]
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This pull request has been merged in bf5093a. |
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Stack from ghstack (oldest at bottom):
ParamsBindListto prevent needing to passshared_ptrto bind parameter UBOs #3150Value#3148Context
Now that we have forked the
api/directory from PyTorch Vulkan, we can clean up thevTensorclass and remove functionality that is not necessary for the ExecuTorch Vulkan delegate.The following changes are made:
vTensorandvTensorStoragevTensorconstructor for quantized tensors. The Quantization API will be reworked from the ground up.view_(which is an instance ofvTensorStorage) tostorage_Finally, the critical change that is introduced is that we now store
storage_as a directvTensorStoragemember variable invTensorinstead of storing it as astd::shared_ptr<vTensorStorage>.For context, the reason
storage_was stored as a shared pointer is to be compliant with ATen Tensors, which needs to enable copy construction to enable the following:However, in the ExecuTorch delegate this is no longer necessary. Each Tensor is associated with it's own independent storage and is responsible for managing it's own memory. By getting rid of
std::shared_ptr, we can avoid a heap allocation and avoid chasing pointers whenever we need to access the resources of avTensor.Differential Revision: D55811279