[torch/lua] Split ArrayTableHandler and MatrixTableHandler.
This commit is contained in:
huxuan
Родитель
41f905bf35
Коммит
4934722136
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@ -0,0 +1,37 @@
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local ffi = require 'ffi'
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local util = require('multiverso.util')
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local tbh = torch.class('ArrayTableHanlder')
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ffi.cdef[[
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void MV_NewArrayTable(int size, TableHandler* out);
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void MV_GetArrayTable(TableHandler handler, float* data, int size);
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void MV_AddArrayTable(TableHandler handler, float* data, int size);
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]]
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function tbh:new(size)
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tbh = {}
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size = size or 0
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setmetatable(tbh, self)
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self.__index = self
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tbh._handler = ffi.new("TableHandler[1]")
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tbh._size = ffi.new("int", size)
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libmv.MV_NewArrayTable(
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tbh._size,
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tbh._handler
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)
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return tbh
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end
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function tbh:get()
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cdata = ffi.new("float[?]", self._size)
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libmv.MV_GetArrayTable(self._handler[0], cdata, self._size)
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return util.cdata2tensor(cdata, tonumber(self._size))
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end
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function tbh:add(data)
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cdata = util.tensor2cdata(data)
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libmv.MV_AddArrayTable(self._handler[0], cdata, self._size)
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end
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return tbh
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@ -0,0 +1,63 @@
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local ffi = require 'ffi'
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local util = require('multiverso.util')
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local tbh = torch.class('MatrixTableHandler')
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ffi.cdef[[
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void MV_NewMatrixTable(int num_row, int num_col, TableHandler* out);
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void MV_GetMatrixTableAll(TableHandler handler, float* data, int size);
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void MV_AddMatrixTableAll(TableHandler handler, float* data, int size);
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void MV_GetMatrixTableByRows(TableHandler handler, float* data, int size, int row_ids[], int row_ids_n);
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void MV_AddMatrixTableByRows(TableHandler handler, float* data, int size, int row_ids[], int row_ids_n);
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]]
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function tbh:new(num_row, num_col)
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tbh = {}
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num_row = num_row or 0
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num_col = num_col or 0
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setmetatable(tbh, self)
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self.__index = self
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tbh._handler = ffi.new("TableHandler[1]")
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tbh._num_row = ffi.new("int", num_row)
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tbh._num_col = ffi.new("int", num_col)
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tbh._size = ffi.new("int", num_row * num_col)
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libmv.MV_NewMatrixTable(
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tbh._num_row,
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tbh._num_col,
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tbh._handler
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)
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return tbh
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end
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function tbh:get(row_ids)
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if row_ids == nil then
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cdata = ffi.new("float[?]", self._size)
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libmv.MV_GetMatrixTableAll(self._handler[0], cdata, self._size)
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data = util.cdata2tensor(cdata, tonumber(self._size))
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return torch.reshape(data, tonumber(self._num_row), tonumber(self._num_col))
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else
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cdata = ffi.new("float[?]", #row_ids * self._num_col)
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crow_ids = util.tensor2cdata(row_ids, 'int')
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crow_ids_n = ffi.new("int", #row_ids)
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libmv.MV_GetMatrixTableByRows(self._handler[0], cdata,
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crow_ids_n * self._num_col,
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crow_ids, crow_ids_n)
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data = util.cdata2tensor(cdata, tonumber(#row_ids * self._num_col))
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return torch.reshape(data, #row_ids, tonumber(self._num_col))
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end
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end
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function tbh:add(data, row_ids)
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cdata = util.tensor2cdata(data)
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if row_ids == nil then
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libmv.MV_AddMatrixTableAll(self._handler[0], cdata, self._size)
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else
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crow_ids = util.tensor2cdata(row_ids, 'int')
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crow_ids_n = ffi.new("int", #row_ids)
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libmv.MV_AddMatrixTableByRows(self._handler[0], cdata,
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crow_ids_n * self._num_col,
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crow_ids, crow_ids_n)
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end
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end
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return tbh
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@ -13,23 +13,12 @@ ffi.cdef[[
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int MV_NumWorkers();
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int MV_WorkerId();
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int MV_ServerId();
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// Array Table
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void MV_NewArrayTable(int size, TableHandler* out);
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void MV_GetArrayTable(TableHandler handler, float* data, int size);
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void MV_AddArrayTable(TableHandler handler, float* data, int size);
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// Matrix Table
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void MV_NewMatrixTable(int num_row, int num_col, TableHandler* out);
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void MV_GetMatrixTableAll(TableHandler handler, float* data, int size);
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void MV_AddMatrixTableAll(TableHandler handler, float* data, int size);
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void MV_GetMatrixTableByRows(TableHandler handler, float* data, int size, int row_ids[], int row_ids_n);
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void MV_AddMatrixTableByRows(TableHandler handler, float* data, int size, int row_ids[], int row_ids_n);
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]]
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package.cpath = "../../build/src/?.so;" .. package.cpath
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libmv_path = package.searchpath('libmultiverso', package.cpath, '')
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libmv = ffi.load(libmv_path)
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libmv = ffi.load('libmultiverso', 'true')
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mv.ArrayTableHandler = require('multiverso.ArrayTableHandler')
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mv.MatrixTableHandler = require('multiverso.MatrixTableHandler')
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function mv.init(args)
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args = args or {}
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@ -62,82 +51,4 @@ function mv.server_id()
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return libmv.MV_ServerId()
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end
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mv.ArrayTableHandler = {}
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function mv.ArrayTableHandler:new(size)
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tbh = {}
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size = size or 0
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setmetatable(tbh, self)
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self.__index = self
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tbh._handler = ffi.new("TableHandler[1]")
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tbh._size = ffi.new("int", size)
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libmv.MV_NewArrayTable(
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tbh._size,
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tbh._handler
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)
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return tbh
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end
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function mv.ArrayTableHandler:get()
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cdata = ffi.new("float[?]", self._size)
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libmv.MV_GetArrayTable(self._handler[0], cdata, self._size)
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return util.cdata2tensor(cdata, tonumber(self._size))
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end
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function mv.ArrayTableHandler:add(data)
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cdata = util.tensor2cdata(data)
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libmv.MV_AddArrayTable(self._handler[0], cdata, self._size)
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end
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mv.MatrixTableHandler = {}
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function mv.MatrixTableHandler:new(num_row, num_col)
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tbh = {}
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num_row = num_row or 0
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num_col = num_col or 0
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setmetatable(tbh, self)
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self.__index = self
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tbh._handler = ffi.new("TableHandler[1]")
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tbh._num_row = ffi.new("int", num_row)
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tbh._num_col = ffi.new("int", num_col)
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tbh._size = ffi.new("int", num_row * num_col)
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libmv.MV_NewMatrixTable(
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tbh._num_row,
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tbh._num_col,
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tbh._handler
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)
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return tbh
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end
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function mv.MatrixTableHandler:get(row_ids)
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if row_ids == nil then
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cdata = ffi.new("float[?]", self._size)
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libmv.MV_GetMatrixTableAll(self._handler[0], cdata, self._size)
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data = util.cdata2tensor(cdata, tonumber(self._size))
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return torch.reshape(data, tonumber(self._num_row), tonumber(self._num_col))
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else
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cdata = ffi.new("float[?]", #row_ids * self._num_col)
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crow_ids = util.tensor2cdata(row_ids, 'int')
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crow_ids_n = ffi.new("int", #row_ids)
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libmv.MV_GetMatrixTableByRows(self._handler[0], cdata,
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crow_ids_n * self._num_col,
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crow_ids, crow_ids_n)
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data = util.cdata2tensor(cdata, tonumber(#row_ids * self._num_col))
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return torch.reshape(data, #row_ids, tonumber(self._num_col))
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end
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end
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function mv.MatrixTableHandler:add(data, row_ids)
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cdata = util.tensor2cdata(data)
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if row_ids == nil then
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libmv.MV_AddMatrixTableAll(self._handler[0], cdata, self._size)
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else
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crow_ids = util.tensor2cdata(row_ids, 'int')
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crow_ids_n = ffi.new("int", #row_ids)
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libmv.MV_AddMatrixTableByRows(self._handler[0], cdata,
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crow_ids_n * self._num_col,
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crow_ids, crow_ids_n)
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end
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end
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return mv
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