forked from cad-audio/executorch
-
Notifications
You must be signed in to change notification settings - Fork 1
Adding cat, full, permute_copy and relu ops #34
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Merged
Merged
Changes from all commits
Commits
Show all changes
3 commits
Select commit
Hold shift + click to select a range
File filter
Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
There are no files selected for viewing
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,158 @@ | ||
| /* | ||
| * 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. | ||
| */ | ||
|
|
||
| #include <executorch/kernels/portable/cpu/util/copy_ops_util.h> | ||
| #include <executorch/runtime/kernel/kernel_includes.h> | ||
| #include <cstring> | ||
|
|
||
| #include <executorch/backends/cadence/hifi/kernels/kernels.h> | ||
|
|
||
| using exec_aten::ScalarType; | ||
| using exec_aten::Tensor; | ||
| using executorch::aten::RuntimeContext; | ||
| using executorch::runtime::getLeadingDims; | ||
| using executorch::runtime::getTrailingDims; | ||
| using executorch::runtime::resize_tensor; | ||
| using executorch::runtime::tensors_have_same_dim_order; | ||
| using torch::executor::check_cat_args; | ||
| using torch::executor::Error; | ||
| using torch::executor::get_cat_out_target_size; | ||
|
|
||
| namespace cadence { | ||
| namespace impl { | ||
| namespace HiFi { | ||
| namespace native { | ||
|
|
||
| Tensor& cat_out( | ||
| RuntimeContext& ctx, | ||
| exec_aten::ArrayRef<Tensor> tensors, | ||
| int64_t dim, | ||
| Tensor& out) { | ||
| constexpr auto name = "cat.out"; | ||
| constexpr int kNnlibMaxDim = 16; | ||
|
|
||
| bool optimized = true; | ||
|
|
||
| if (out.scalar_type() != ScalarType::Float) | ||
| optimized = false; | ||
|
|
||
| if (optimized) { | ||
| WORD32 num_inp = tensors.size(); | ||
| WORD32 num_inp_dims = out.dim(); | ||
| WORD32 num_out_dims = num_inp_dims; | ||
| WORD32 axis = dim; | ||
|
|
||
| WORD32 inp_shape[kNnlibMaxDim][kNnlibMaxDim]; | ||
| WORD32 p_out_shape[kNnlibMaxDim]; | ||
|
|
||
| WORD32* ptr_shape[kNnlibMaxDim]; | ||
| const WORD32* ptr[kNnlibMaxDim]; | ||
|
|
||
| int k = 0; | ||
| for (int i = 0; i < num_inp; i++) { | ||
| if (tensors[i].numel() == 0) | ||
| continue; | ||
| ptr[k] = (const WORD32*)tensors[i].const_data_ptr<float>(); | ||
| for (int j = 0; j < num_inp_dims; j++) { | ||
| inp_shape[k][j] = tensors[i].size(j); | ||
| } | ||
| ptr_shape[k] = inp_shape[k]; | ||
| k++; | ||
| } | ||
|
|
||
| num_inp = k; | ||
|
|
||
| for (int i = 0; i < num_out_dims; i++) { | ||
| p_out_shape[i] = out.size(i); | ||
| } | ||
|
|
||
| const WORD32** pp_inps = &ptr[0]; | ||
|
|
||
| WORD32* p_out = (WORD32*)out.mutable_data_ptr<float>(); | ||
|
|
||
| const WORD32* const* pp_inps_shape = (const WORD32* const*)&ptr_shape[0]; | ||
|
|
||
| WORD32 ret_val = xa_nn_concat_32_32( | ||
| p_out, | ||
| p_out_shape, | ||
| pp_inps, | ||
| pp_inps_shape, | ||
| num_out_dims, | ||
| num_inp, | ||
| num_inp_dims, | ||
| axis); | ||
|
|
||
| ET_KERNEL_CHECK(ctx, ret_val == 0, Internal, out); | ||
|
|
||
| return out; | ||
| } | ||
|
|
||
| if (dim < 0) { | ||
| dim += out.dim(); | ||
| } | ||
|
|
||
| ET_KERNEL_CHECK(ctx, check_cat_args(tensors, dim, out), Internal, out); | ||
|
|
||
| Tensor::SizesType | ||
| expected_out_size[executorch::runtime::kTensorDimensionLimit]; | ||
| size_t expected_out_dim = 0; | ||
| get_cat_out_target_size(tensors, dim, expected_out_size, &expected_out_dim); | ||
|
|
||
| ET_KERNEL_CHECK( | ||
| ctx, | ||
| resize_tensor(out, {expected_out_size, expected_out_dim}) == Error::Ok, | ||
| InvalidArgument, | ||
| out); | ||
|
|
||
| // Special handling when all inputs are 1D-empty tensors for aten consistency | ||
| // In that case, just return an 1D-empty tensor without checking dim | ||
| bool all_1d_empty = true; | ||
| for (size_t i = 0; i < tensors.size(); ++i) { | ||
| if (tensors[i].numel() != 0 || tensors[i].dim() != 1) { | ||
| all_1d_empty = false; | ||
| break; | ||
| } | ||
| } | ||
| if (all_1d_empty) { | ||
| return out; | ||
| } | ||
|
|
||
| const size_t outer = getLeadingDims(out, dim); | ||
| const size_t dim_stride = getTrailingDims(out, dim); | ||
| const size_t ninputs = tensors.size(); | ||
|
|
||
| const auto out_type = out.scalar_type(); | ||
| ET_SWITCH_REALHB_TYPES(out_type, ctx, name, CTYPE_OUT, [&] { | ||
| CTYPE_OUT* out_ptr = out.mutable_data_ptr<CTYPE_OUT>(); | ||
| for (size_t i = 0; i < outer; ++i) { | ||
| for (size_t j = 0; j < ninputs; ++j) { | ||
| const auto in_type = tensors[j].scalar_type(); | ||
| ET_SWITCH_REALHB_TYPES(in_type, ctx, name, CTYPE_IN, [&] { | ||
| if (tensors[j].numel() == 0) { | ||
| return; | ||
| } | ||
| size_t inner = tensors[j].size(dim) * dim_stride; | ||
| const CTYPE_IN* const in_ptr = | ||
| tensors[j].const_data_ptr<CTYPE_IN>() + i * inner; | ||
|
|
||
| for (size_t k = 0; k < inner; ++k) { | ||
| out_ptr[k] = static_cast<CTYPE_OUT>(in_ptr[k]); | ||
| } | ||
| out_ptr += inner; | ||
| }); | ||
| } | ||
| } | ||
| }); | ||
|
|
||
| return out; | ||
| } | ||
|
|
||
| } // namespace native | ||
| } // namespace HiFi | ||
| } // namespace impl | ||
| } // namespace cadence |
Oops, something went wrong.
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Uh oh!
There was an error while loading. Please reload this page.