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Question

我已经创建了一个OpenResty / Lusty项目，并且一直在尝试使用它来围绕我正在使用的分类器包装REST API。不幸的是，我没有太多运气，我的根本原因是当我尝试

时

require 'nn'
require 'image'

Lua无法解释该文件。不幸的是，Lusty没有在日志中给我一个堆栈跟踪，只是返回404错误。但是，经过大量的代码评论和试用/错误之后，我确定了根本原因是当我尝试要求这些软件包时会抛出错误。

我在使用Torch7和其他工具预先构建的Docker容器上使用Luarocks安装了OpenResty / Lusty。当我尝试单独运行分类器时，我可以使用th classify.lua轻松完成。但是，当我尝试将其包含在其自己的函数中的Lusty请求时，上面的导入失败并且Lusty返回404错误，我认为这实际上是500错误，因为如果我注释掉火炬代码，它将返回200。

重要的是要注意我已经使用了预构建容器附带的luarocks命令。此外，当我检查本地安装文件夹时，我发现以下软件包，包括nn和image：

以下是我在实现时使用的代码，知道为什么我无法导入这些包？

classify.lua中

package.path

.\/app\/?.lua;\/opt\/openresty\/lualib\/?.lua;\/opt\/openresty\/lualib\/?\/init.lua;\/root\/.luarocks\/share\/lua\/5.1\/?.lua;\/root\/.luarocks\/share\/lua\/5.1\/?\/init.lua;\/root\/torch\/install\/share\/lua\/5.1\/?.lua;\/root\/torch\/install\/share\/lua\/5.1\/?\/init.lua;.\/?.lua;\/root\/torch\/install\/share\/luajit-2.1.0-beta1\/?.lua;\/usr\/local\/share\/lua\/5.1\/?.lua;\/usr\/local\/share\/lua\/5.1\/?\/init.lua;

lusty_project /应用/请求/ classify.lua

-- these require statements throw an error
require 'nn'
require 'image'


function classifyImage()
  local ParamBank = require 'ParamBank'
  local label     = require 'classifier_label'
  torch.setdefaulttensortype('torch.FloatTensor')
  torch.setnumthreads(opt.threads)


  -- set modules to be in use
  if opt.backend == 'nn' or opt.backend == 'cunn' then
     require(opt.backend)
     SpatialConvolution = nn.SpatialConvolutionMM
     SpatialMaxPooling = nn.SpatialMaxPooling
     ReLU = nn.ReLU
     SpatialSoftMax = nn.SpatialSoftMax
  else
     assert(false, 'Unknown backend type')
  end


  local net = nn.Sequential()
     net:add(SpatialConvolution(3, 96, 7, 7, 2, 2))
     net:add(ReLU(opt.inplace))
     net:add(SpatialMaxPooling(3, 3, 3, 3))
     net:add(SpatialConvolution(96, 256, 7, 7, 1, 1))
     net:add(ReLU(opt.inplace))
     net:add(SpatialMaxPooling(2, 2, 2, 2))
     net:add(SpatialConvolution(256, 512, 3, 3, 1, 1, 1, 1))
     net:add(ReLU(opt.inplace))
     net:add(SpatialConvolution(512, 512, 3, 3, 1, 1, 1, 1))
     net:add(ReLU(opt.inplace))
     net:add(SpatialConvolution(512, 1024, 3, 3, 1, 1, 1, 1))
     net:add(ReLU(opt.inplace))
     net:add(SpatialConvolution(1024, 1024, 3, 3, 1, 1, 1, 1))
     net:add(ReLU(opt.inplace))
     net:add(SpatialMaxPooling(3, 3, 3, 3))
     net:add(SpatialConvolution(1024, 4096, 5, 5, 1, 1))
     net:add(ReLU(opt.inplace))
     net:add(SpatialConvolution(4096, 4096, 1, 1, 1, 1))
     net:add(ReLU(opt.inplace))
     net:add(SpatialConvolution(4096, 1000, 1, 1, 1, 1))
     if not opt.spatial then net:add(nn.View(1000)) end
     net:add(SpatialSoftMax())
     print(net)

     -- init file pointer
     print('==> overwrite network parameters with pre-trained weigts')
     ParamBank:init("net_weight_1")
     ParamBank:read(        0, {96,3,7,7},      net:get(1).weight)
     ParamBank:read(    14112, {96},            net:get(1).bias)
     ParamBank:read(    14208, {256,96,7,7},    net:get(4).weight)
     ParamBank:read(  1218432, {256},           net:get(4).bias)
     ParamBank:read(  1218688, {512,256,3,3},   net:get(7).weight)
     ParamBank:read(  2398336, {512},           net:get(7).bias)
     ParamBank:read(  2398848, {512,512,3,3},   net:get(9).weight)
     ParamBank:read(  4758144, {512},           net:get(9).bias)
     ParamBank:read(  4758656, {1024,512,3,3},  net:get(11).weight)
     ParamBank:read(  9477248, {1024},          net:get(11).bias)
     ParamBank:read(  9478272, {1024,1024,3,3}, net:get(13).weight)
     ParamBank:read( 18915456, {1024},          net:get(13).bias)
     ParamBank:read( 18916480, {4096,1024,5,5}, net:get(16).weight)
     ParamBank:read(123774080, {4096},          net:get(16).bias)
     ParamBank:read(123778176, {4096,4096,1,1}, net:get(18).weight)
     ParamBank:read(140555392, {4096},          net:get(18).bias)
     ParamBank:read(140559488, {1000,4096,1,1}, net:get(20).weight)
     ParamBank:read(144655488, {1000},          net:get(20).bias)
  -- close file pointer
  ParamBank:close()


  -- load and preprocess image
  print('==> prepare an input image')
  local img = image.load(opt.img):mul(255)

  -- use image larger than the eye size in spatial mode
  if not opt.spatial then
     local dim = (opt.network == 'small') and 231 or 221
     local img_scale = image.scale(img, '^'..dim)
     local h = math.ceil((img_scale:size(2) - dim)/2)
     local w = math.ceil((img_scale:size(3) - dim)/2)
     img = image.crop(img_scale, w, h, w + dim, h + dim):floor()
  end


  -- memcpy from system RAM to GPU RAM if cuda enabled
  if opt.backend == 'cunn' or opt.backend == 'cudnn' then
     net:cuda()
     img = img:cuda()
  end


  -- save bare network (before its buffer filled with temp results)
  print('==> save model to:', opt.save)
  torch.save(opt.save, net)


  -- feedforward network
  print('==> feed the input image')
  timer = torch.Timer()
  img:add(-118.380948):div(61.896913)
  local out = net:forward(img)


  -- find output class name in non-spatial mode
  local results = {}
  local topN = 10
  local probs, idxs = torch.topk(out, topN, 1, true)

  for i=1,topN do
     print(label[idxs[i]], probs[i])
     local r = {}
     r.label = label[idxs[i]]
     r.prob = probs[i]
     results[i] = r
  end

  return results
end

function errorHandler(error)
  return {message: "error"}
end

context.template = {
  type = "mustache",
  name = "app/templates/layout",

  partials = {
    content = "app/templates/classify",
  }
}


context.output = {
  message = xpcall(classifyImage, errorHandler)
}

context.response.status = 200

感谢任何能提供帮助的人。我是Lua n00b，尚未习惯其包装功能。

更新

在我意识到我可以使用xpcall的第二个返回变量（local resultCode, error = xpcall(func, errHandler)）捕获错误后，我已经想出如何最终返回结果中的错误。

错误是这样的：

{"message":false,"errorMessage":"[string \".\/app\/requests\/classify.lua\"]:3: module 'nn' not found:\n\tno field package.preload['nn']\n\tno file '.\/app\/nn.lua'\n\tno file '\/opt\/openresty\/lualib\/nn.lua'\n\tno file '\/opt\/openresty\/lualib\/nn\/init.lua'\n\tno file '\/root\/.luarocks\/share\/lua\/5.1\/nn.lua'\n\tno file '\/root\/.luarocks\/share\/lua\/5.1\/nn\/init.lua'\n\tno file '\/root\/torch\/install\/share\/lua\/5.1\/nn.lua'\n\tno file '\/root\/torch\/install\/share\/lua\/5.1\/nn\/init.lua'\n\tno file '.\/nn.lua'\n\tno file '\/root\/torch\/install\/share\/luajit-2.1.0-beta1\/nn.lua'\n\tno file '\/usr\/local\/share\/lua\/5.1\/nn.lua'\n\tno file '\/usr\/local\/share\/lua\/5.1\/nn\/init.lua'\n\tno file '\/opt\/openresty\/lualib\/nn.so'\n\tno file '\/root\/torch\/install\/lib\/nn.so'\n\tno file '\/root\/.luarocks\/lib\/lua\/5.1\/nn.so'\n\tno file '\/root\/torch\/install\/lib\/lua\/5.1\/nn.so'\n\tno file '.\/nn.so'\n\tno file '\/usr\/local\/lib\/lua\/5.1\/nn.so'\n\tno file '\/usr\/local\/lib\/lua\/5.1\/loadall.so'"}

[string "./app/requests/classify.lua"]:5: module 'nn' not found:
    no field package.preload['nn']
    no file './app/nn.lua'
    no file '/opt/openresty/lualib/nn.lua'
    no file '/opt/openresty/lualib/nn/init.lua'
    no file '/root/.luarocks/share/lua/5.1/nn.lua'
    no file '/root/.luarocks/share/lua/5.1/nn/init.lua'
    no file '/root/torch/install/share/lua/5.1/nn.lua'
    no file '/root/torch/install/share/lua/5.1/nn/init.lua'
    no file './nn.lua'
    no file '/root/torch/install/share/luajit-2.1.0-beta1/nn.lua'
    no file '/usr/local/share/lua/5.1/nn.lua'
    no file '/usr/local/share/lua/5.1/nn/init.lua'
    no file '/root/torch/extra/nn/nn.lua'
    no file '/opt/openresty/lualib/nn.lua'
    no file '/opt/openresty/lualib/nn/init.lua'
    no file '/root/.luarocks/share/lua/5.1/nn.lua'
    no file '/root/.luarocks/share/lua/5.1/nn/init.lua'
    no file '/root/torch/install/share/lua/5.1/nn.lua'
    no file '/root/torch/install/share/lua/5.1/nn/init.lua'
    no file './nn.lua'
    no file '/root/torch/install/share/luajit-2.1.0-beta1/nn.lua'
    no file '/usr/local/share/lua/5.1/nn.lua'
    no file '/usr/local/share/lua/5.1/nn/init.lua'
    no file '/root/torch/extra/image/nn.lua'
    no file '/root/torch/extra/nn/nn.lua'
    no file '/opt/openresty/lualib/nn.so'
    no file '/root/torch/install/lib/nn.so'
    no file '/root/.luarocks/lib/lua/5.1/nn.so'
    no file '/root/torch/install/lib/lua/5.1/nn.so'
    no file './nn.so'
    no file '/usr/local/lib/lua/5.1/nn.so'
    no file '/usr/local/lib/lua/5.1/loadall.so'

当我通过nn搜索find -name nn时，我得到了：

./root/torch/install/share/lua/5.1/nn
./root/torch/install/share/lua/5.1/nngraph
./root/torch/install/share/lua/5.1/nnx
./root/torch/install/lib/luarocks/rocks/nn
./root/torch/install/lib/luarocks/rocks/nn/scm-1/nn-scm-1.rockspec
./root/torch/install/lib/luarocks/rocks/nngraph
./root/torch/install/lib/luarocks/rocks/nngraph/scm-1/nngraph-scm-1.rockspec
./root/torch/install/lib/luarocks/rocks/nnx
./root/torch/install/lib/luarocks/rocks/nnx/0.1-1/nnx-0.1-1.rockspec
./root/torch/extra/nngraph
./root/torch/extra/nngraph/nngraph-scm-1.rockspec
./root/torch/extra/nnx
./root/torch/extra/nnx/build/CMakeFiles/nnx.dir
./root/torch/extra/nnx/nnx-0.1-1.rockspec
./root/torch/extra/nn
./root/torch/extra/nn/rocks/nn-scm-1.rockspec
./root/torch/.git/modules/extra/nngraph
./root/torch/.git/modules/extra/nnx
./root/torch/.git/modules/extra/nn
./usr/local/include/opencv2/flann/nn_index.h
./usr/share/locale/nn
./usr/share/i18n/locales/nn_NO
./usr/share/perl/5.18.2/Unicode/Collate/Locale/nn.pl
./usr/lib/python3.4/nntplib.py
./usr/lib/python2.7/nntplib.pyc
./usr/lib/python2.7/nntplib.py

Answer 1

终于能够解决这个问题了。这是一个相当复杂的权限问题，因为nginx默认是以用户nobody运行其工作进程。由于OpenResty与此特定工作进程相关联，因此所有子Lua进程也绑定到同一用户。

最简单的解决方案是将所有相关文件的权限更改为同一用户。所以你可以这样做：

chown -R nobody:nogroup openresty_project/
chmod -R 755 openresty_project/

一旦这样做，您将重新获得之前已安装的Luarocks的访问权限。

请注意，您必须找到所有相关的lua目录并更改默认用户。

你还可以在nginx配置中更改用户的另一个选项，可以在nginx.conf中这样做：

user myuser mygroup;

请注意，以root身份运行极其危险，不推荐使用。

Lua：为什么我不能要求本地安装的软件包？

更新

1 个答案: