[torch/lua] Split ArrayTableHandler and MatrixTableHandler.

binding/lua/ArrayTableHandler.lua

@@ -0,0 +1,37 @@
+local ffi = require 'ffi'
+local util = require('multiverso.util')
+
+local tbh = torch.class('ArrayTableHanlder')
+
+ffi.cdef[[
+    void MV_NewArrayTable(int size, TableHandler* out);
+    void MV_GetArrayTable(TableHandler handler, float* data, int size);
+    void MV_AddArrayTable(TableHandler handler, float* data, int size);
+]]
+
+function tbh:new(size)
+    tbh = {}
+    size = size or 0
+    setmetatable(tbh, self)
+    self.__index = self
+    tbh._handler = ffi.new("TableHandler[1]")
+    tbh._size = ffi.new("int", size)
+    libmv.MV_NewArrayTable(
+        tbh._size,
+        tbh._handler
+    )
+    return tbh
+end
+
+function tbh:get()
+    cdata = ffi.new("float[?]", self._size)
+    libmv.MV_GetArrayTable(self._handler[0], cdata, self._size)
+    return util.cdata2tensor(cdata, tonumber(self._size))
+end
+
+function tbh:add(data)
+    cdata = util.tensor2cdata(data)
+    libmv.MV_AddArrayTable(self._handler[0], cdata, self._size)
+end
+
+return tbh

binding/lua/MatrixTableHandler.lua

@@ -0,0 +1,63 @@
+local ffi = require 'ffi'
+local util = require('multiverso.util')
+
+local tbh = torch.class('MatrixTableHandler')
+
+ffi.cdef[[
+    void MV_NewMatrixTable(int num_row, int num_col, TableHandler* out);
+    void MV_GetMatrixTableAll(TableHandler handler, float* data, int size);
+    void MV_AddMatrixTableAll(TableHandler handler, float* data, int size);
+    void MV_GetMatrixTableByRows(TableHandler handler, float* data, int size, int row_ids[], int row_ids_n);
+    void MV_AddMatrixTableByRows(TableHandler handler, float* data, int size, int row_ids[], int row_ids_n);
+]]
+
+function tbh:new(num_row, num_col)
+    tbh = {}
+    num_row = num_row or 0
+    num_col = num_col or 0
+    setmetatable(tbh, self)
+    self.__index = self
+    tbh._handler = ffi.new("TableHandler[1]")
+    tbh._num_row = ffi.new("int", num_row)
+    tbh._num_col = ffi.new("int", num_col)
+    tbh._size = ffi.new("int", num_row * num_col)
+    libmv.MV_NewMatrixTable(
+        tbh._num_row,
+        tbh._num_col,
+        tbh._handler
+    )
+    return tbh
+end
+
+function tbh:get(row_ids)
+    if row_ids == nil then
+        cdata = ffi.new("float[?]", self._size)
+        libmv.MV_GetMatrixTableAll(self._handler[0], cdata, self._size)
+        data = util.cdata2tensor(cdata, tonumber(self._size))
+        return torch.reshape(data, tonumber(self._num_row), tonumber(self._num_col))
+    else
+        cdata = ffi.new("float[?]", #row_ids * self._num_col)
+        crow_ids = util.tensor2cdata(row_ids, 'int')
+        crow_ids_n = ffi.new("int", #row_ids)
+        libmv.MV_GetMatrixTableByRows(self._handler[0], cdata,
+                                      crow_ids_n * self._num_col,
+                                      crow_ids, crow_ids_n)
+        data = util.cdata2tensor(cdata, tonumber(#row_ids * self._num_col))
+        return torch.reshape(data, #row_ids, tonumber(self._num_col))
+    end
+end
+
+function tbh:add(data, row_ids)
+    cdata = util.tensor2cdata(data)
+    if row_ids == nil then
+        libmv.MV_AddMatrixTableAll(self._handler[0], cdata, self._size)
+    else
+        crow_ids = util.tensor2cdata(row_ids, 'int')
+        crow_ids_n = ffi.new("int", #row_ids)
+        libmv.MV_AddMatrixTableByRows(self._handler[0], cdata,
+                                      crow_ids_n * self._num_col,
+                                      crow_ids, crow_ids_n)
+    end
+end
+
+return tbh

binding/lua/multiverso.lua

@@ -13,23 +13,12 @@ ffi.cdef[[
     int MV_NumWorkers();
     int MV_WorkerId();
     int MV_ServerId();
-
-    // Array Table
-    void MV_NewArrayTable(int size, TableHandler* out);
-    void MV_GetArrayTable(TableHandler handler, float* data, int size);
-    void MV_AddArrayTable(TableHandler handler, float* data, int size);
-
-    // Matrix Table
-    void MV_NewMatrixTable(int num_row, int num_col, TableHandler* out);
-    void MV_GetMatrixTableAll(TableHandler handler, float* data, int size);
-    void MV_AddMatrixTableAll(TableHandler handler, float* data, int size);
-    void MV_GetMatrixTableByRows(TableHandler handler, float* data, int size, int row_ids[], int row_ids_n);
-    void MV_AddMatrixTableByRows(TableHandler handler, float* data, int size, int row_ids[], int row_ids_n);
 ]]
 
-package.cpath = "../../build/src/?.so;" .. package.cpath
+libmv = ffi.load('libmultiverso', 'true')
-libmv_path = package.searchpath('libmultiverso', package.cpath, '')
+
-libmv = ffi.load(libmv_path)
+mv.ArrayTableHandler = require('multiverso.ArrayTableHandler')
+mv.MatrixTableHandler = require('multiverso.MatrixTableHandler')
 
 function mv.init(args)
     args = args or {}
@@ -62,82 +51,4 @@ function mv.server_id()
     return libmv.MV_ServerId()
 end
 
-mv.ArrayTableHandler = {}
-
-function mv.ArrayTableHandler:new(size)
-    tbh = {}
-    size = size or 0
-    setmetatable(tbh, self)
-    self.__index = self
-    tbh._handler = ffi.new("TableHandler[1]")
-    tbh._size = ffi.new("int", size)
-    libmv.MV_NewArrayTable(
-        tbh._size,
-        tbh._handler
-    )
-    return tbh
-end
-
-function mv.ArrayTableHandler:get()
-    cdata = ffi.new("float[?]", self._size)
-    libmv.MV_GetArrayTable(self._handler[0], cdata, self._size)
-    return util.cdata2tensor(cdata, tonumber(self._size))
-end
-
-function mv.ArrayTableHandler:add(data)
-    cdata = util.tensor2cdata(data)
-    libmv.MV_AddArrayTable(self._handler[0], cdata, self._size)
-end
-
-mv.MatrixTableHandler = {}
-
-function mv.MatrixTableHandler:new(num_row, num_col)
-    tbh = {}
-    num_row = num_row or 0
-    num_col = num_col or 0
-    setmetatable(tbh, self)
-    self.__index = self
-    tbh._handler = ffi.new("TableHandler[1]")
-    tbh._num_row = ffi.new("int", num_row)
-    tbh._num_col = ffi.new("int", num_col)
-    tbh._size = ffi.new("int", num_row * num_col)
-    libmv.MV_NewMatrixTable(
-        tbh._num_row,
-        tbh._num_col,
-        tbh._handler
-    )
-    return tbh
-end
-
-function mv.MatrixTableHandler:get(row_ids)
-    if row_ids == nil then
-        cdata = ffi.new("float[?]", self._size)
-        libmv.MV_GetMatrixTableAll(self._handler[0], cdata, self._size)
-        data = util.cdata2tensor(cdata, tonumber(self._size))
-        return torch.reshape(data, tonumber(self._num_row), tonumber(self._num_col))
-    else
-        cdata = ffi.new("float[?]", #row_ids * self._num_col)
-        crow_ids = util.tensor2cdata(row_ids, 'int')
-        crow_ids_n = ffi.new("int", #row_ids)
-        libmv.MV_GetMatrixTableByRows(self._handler[0], cdata,
-                                      crow_ids_n * self._num_col,
-                                      crow_ids, crow_ids_n)
-        data = util.cdata2tensor(cdata, tonumber(#row_ids * self._num_col))
-        return torch.reshape(data, #row_ids, tonumber(self._num_col))
-    end
-end
-
-function mv.MatrixTableHandler:add(data, row_ids)
-    cdata = util.tensor2cdata(data)
-    if row_ids == nil then
-        libmv.MV_AddMatrixTableAll(self._handler[0], cdata, self._size)
-    else
-        crow_ids = util.tensor2cdata(row_ids, 'int')
-        crow_ids_n = ffi.new("int", #row_ids)
-        libmv.MV_AddMatrixTableByRows(self._handler[0], cdata,
-                                      crow_ids_n * self._num_col,
-                                      crow_ids, crow_ids_n)
-    end
-end
-
 return mv