Unverified Commit e65e4726 authored by moto-meta's avatar moto-meta Committed by GitHub
Browse files

Move libtorchaudio to dedicated directory

Differential Revision: D50086556

Pull Request resolved: https://github.com/pytorch/audio/pull/3648
parent 03d12709
......@@ -165,10 +165,10 @@ else()
message(STATUS "Could not find ccache. Consider installing ccache to speed up compilation.")
endif()
add_subdirectory(src/torchaudio/csrc)
add_subdirectory(src/libtorchaudio)
if (BUILD_SOX)
add_subdirectory(third_party/sox)
add_subdirectory(src/torchaudio/csrc/sox)
add_subdirectory(src/libtorchaudio/sox)
endif()
if (USE_FFMPEG)
if (DEFINED ENV{FFMPEG_ROOT})
......@@ -183,7 +183,7 @@ if (BUILD_CUDA_CTC_DECODER)
if (NOT USE_CUDA)
message(FATAL "BUILD_CUDA_CTC_DECODER=1 but USE_CUDA=0.")
endif()
add_subdirectory(src/torchaudio/csrc/cuctc)
add_subdirectory(src/libtorchaudio/cuctc)
endif()
if (BUILD_CPP_TEST)
add_subdirectory(test/cpp)
......
......@@ -167,8 +167,9 @@ class bitonic {
* You can think of this function in two ways:
*
* 1) Sort any bitonic sequence.
* 2) Merge two halfs of the input data assuming they're already sorted, and
* their order is opposite (i.e. either ascending, descending or vice-versa).
* 2) Merge two halves of the input data assuming they're already sorted,
* and their order is opposite (i.e. either ascending, descending or
* vice-versa).
*
* The input pointers are unique per-thread.
* See the class description for the description of the data layout.
......
......@@ -122,7 +122,7 @@ class warp_sort {
public:
/**
* The `empty` value for the choosen binary operation,
* The `empty` value for the chosen binary operation,
* i.e. `Ascending ? upper_bound<T>() : lower_bound<T>()`.
*/
static constexpr T kDummy = Ascending ? upper_bound<T>() : lower_bound<T>();
......
#include <libtorchaudio/forced_align/compute.h>
#include <torch/script.h>
#include <torchaudio/csrc/forced_align/compute.h>
std::tuple<torch::Tensor, torch::Tensor> forced_align(
const torch::Tensor& logProbs,
......
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