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Summary: Pull Request resolved: #3174 Previous VBE on CPU was enabled in lookup_{{ optimizer }}.py. To support MTIA ops, VBE should be done after torch.ops.fbgemm.{{ mdesc }}_embedding_codegen_lookup_{{ optimizer }}_function_pt2. This diff follows the same implementation but enables it C++ so that it goes through the same PT2 pipeline (i.e., lookup -> VBE autograd -> cpu wrapper (*do vbe here*) -> cpu kernel). the call is done Reviewed By: q10 Differential Revision: D63410944
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| Original file line number | Diff line number | Diff line change |
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| /* | ||
| * Copyright (c) Meta Platforms, Inc. and affiliates. | ||
| * All rights reserved. | ||
| * | ||
| * This source code is licensed under the BSD-style license found in the | ||
| * LICENSE file in the root directory of this source tree. | ||
| */ | ||
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| #include <ATen/ATen.h> | ||
| #include <ATen/TypeDefault.h> | ||
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| using Tensor = at::Tensor; | ||
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| namespace fbgemm_gpu { | ||
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| //////////////////////////////////////////////////////////////////////////////// | ||
| // Helper Functions | ||
| //////////////////////////////////////////////////////////////////////////////// | ||
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| Tensor reshape_vbe_output( | ||
| const Tensor& grad_output, | ||
| const Tensor& B_offsets, | ||
| const Tensor& B_offsets_rank_per_feature, | ||
| const Tensor& D_offsets) { | ||
| /* FOR CPU VBE to use the same backend */ | ||
| const auto T = D_offsets.numel() - 1; | ||
| int32_t max_B = 0; | ||
| int32_t total_D = 0; | ||
| // find max_B, total_D to create output [max_B, total_D] | ||
| for (int32_t t = 0; t < T; t++) { | ||
| auto b = B_offsets[t + 1].item<int32_t>() - B_offsets[t].item<int32_t>(); | ||
| max_B = std::max(max_B, b); | ||
| total_D += D_offsets[t + 1].item<int32_t>() - D_offsets[t].item<int32_t>(); | ||
| } | ||
| auto grad_output_ = at::empty({max_B, total_D}, grad_output.options()); | ||
| // for each feature | ||
| auto offset = 0; | ||
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| const int32_t R = B_offsets_rank_per_feature.size(1) - 1; | ||
| for (int32_t r = 0; r < R; r++) { | ||
| auto D_offset = 0; | ||
| for (int32_t t = 0; t < T; t++) { | ||
| const int32_t b_begin = B_offsets_rank_per_feature[t][r].item<int32_t>(); | ||
| const int32_t b_end = | ||
| B_offsets_rank_per_feature[t][r + 1].item<int32_t>(); | ||
| const int32_t D = | ||
| D_offsets[t + 1].item<int32_t>() - D_offsets[t].item<int32_t>(); | ||
| const int32_t b = b_end - b_begin; | ||
| const int32_t num_elm = b * D; | ||
| auto values = grad_output.slice(0, offset, offset + num_elm); | ||
| values = values.reshape({b, D}); | ||
| grad_output_.index_put_( | ||
| {at::indexing::Slice(b_begin, b_end), | ||
| at::indexing::Slice(D_offset, D_offset + D)}, | ||
| values); | ||
| D_offset += D; | ||
| offset += num_elm; | ||
| } | ||
| } | ||
| return grad_output_; | ||
| } | ||
| } // namespace fbgemm_gpu |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,31 @@ | ||
| /* | ||
| * Copyright (c) Meta Platforms, Inc. and affiliates. | ||
| * All rights reserved. | ||
| * | ||
| * This source code is licensed under the BSD-style license found in the | ||
| * LICENSE file in the root directory of this source tree. | ||
| */ | ||
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| #include <ATen/ATen.h> | ||
| #include <ATen/TypeDefault.h> | ||
| // #include <ATen/core/op_registration/op_registration.h> | ||
| // #include <torch/script.h> | ||
| // #include "fbgemm_gpu/embedding_common.h" | ||
| // #include "fbgemm_gpu/utils/dispatch_macros.h" | ||
| // #include "fbgemm_gpu/utils/ops_utils.h" | ||
| // #include "fbgemm_gpu/utils/tensor_utils.h" | ||
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| using Tensor = at::Tensor; | ||
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| namespace fbgemm_gpu { | ||
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| //////////////////////////////////////////////////////////////////////////////// | ||
| // Helper Functions | ||
| //////////////////////////////////////////////////////////////////////////////// | ||
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| Tensor reshape_vbe_output( | ||
| const Tensor& grad_output, | ||
| const Tensor& B_offsets, | ||
| const Tensor& B_offsets_rank_per_feature, | ||
| const Tensor& D_offsets); | ||
| } // namespace fbgemm_gpu |
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