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ZJUGuoShuaicliffburdick
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Refine some file I/O functions' doxygen comments
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include/matx/core/file_io.h

Lines changed: 34 additions & 13 deletions
Original file line numberDiff line numberDiff line change
@@ -118,16 +118,27 @@ using namespace pybind11::literals;
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/**
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* Read a CSV file into a tensor view
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* @brief Read a CSV file into a tensor view
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*
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* CSVs are currently read in using the Python interpreter through pybind11.
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*This has a startup performance hit, but CSV reading is intended to be a
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*slow-path function, so this is not a critical component to speed up. Currently
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*1D and 2D tensors are supported only.
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* This has a startup performance hit, but CSV reading is intended to be a
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* slow-path function, so this is not a critical component to speed up. Currently
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* 1D and 2D tensors are supported only.
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*
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* @tparam TensorType
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* Data type of tensor
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* @param t
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* Tensor to read data into
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* @param fname
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* File path of .csv file
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* @param delimiter
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* Delimiter to use for CSV file
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* @param skip_header
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* Skip the header row of the CSV file, default as `true`.
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**/
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template <typename TensorType>
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void read_csv(TensorType &t, const std::string fname,
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const std::string delimiter, bool header = true)
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const std::string delimiter, bool skip_header = true)
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{
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MATX_NVTX_START("", matx::MATX_NVTX_LOG_API)
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@@ -146,18 +157,27 @@ void read_csv(TensorType &t, const std::string fname,
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auto np = pybind11::module_::import("numpy");
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auto obj = np.attr("genfromtxt")("fname"_a = fname.c_str(), "delimiter"_a = delimiter,
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"skip_header"_a = header ? 1 : 0,
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"skip_header"_a = skip_header,
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"dtype"_a = detail::MatXPybind::GetNumpyDtype<typename TensorType::scalar_type>());
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pb->NumpyToTensorView(t, obj);
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}
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/**
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* Read a CSV file into a tensor view
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* Write a CSV file from a tensor view
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*
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* CSVs are currently read in using the Python interpreter through pybind11.
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*This has a startup performance hit, but CSV reading is intended to be a
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*slow-path function, so this is not a critical component to speed up. Currently
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*1D and 2D tensors are supported only.
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* CSVs are currently written using the Python interpreter through pybind11.
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* This has a startup performance hit, but CSV writing is intended to be a
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* slow-path function, so this is not a critical component to speed up. Currently
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* 1D and 2D tensors are supported only.
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*
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* @tparam TensorType
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* Data type of tensor
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* @param t
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* Tensor to write data from
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* @param fname
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* File path of .csv file
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* @param delimiter
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* Delimiter to use for CSV file
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**/
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template <typename TensorType>
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void write_csv(const TensorType &t, const std::string fname,
@@ -220,7 +240,7 @@ void read_mat(TensorType &t, const std::string fname,
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}
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/**
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* @brief Read a MAT file into a tensor view
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* @brief Read a MAT file and return a tensor view
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*
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* MAT files use SciPy's loadmat() function to read various MATLAB file
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* types in. MAT files are supersets of HDF5 files, and are allowed to
@@ -232,7 +252,8 @@ void read_mat(TensorType &t, const std::string fname,
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* File name of .mat file
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* @param var
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* Variable name inside of .mat to read
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*
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* @return
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* Tensor view of data read from file
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**/
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template <typename TensorType>
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auto read_mat(const std::string fname,

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