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- -- ref: https://github.com/torch/nn/issues/112#issuecomment-64427049
- local function zeroDataSize(data)
- if type(data) == 'table' then
- for i = 1, #data do
- data[i] = zeroDataSize(data[i])
- end
- elseif type(data) == 'userdata' then
- data = torch.Tensor():typeAs(data)
- end
- return data
- end
- -- Resize the output, gradInput, etc temporary tensors to zero (so that the
- -- on disk size is smaller)
- local function cleanupModel(node)
- if node.output ~= nil then
- node.output = zeroDataSize(node.output)
- end
- if node.gradInput ~= nil then
- node.gradInput = zeroDataSize(node.gradInput)
- end
- if node.finput ~= nil then
- node.finput = zeroDataSize(node.finput)
- end
- if tostring(node) == "nn.LeakyReLU" or tostring(node) == "w2nn.LeakyReLU" then
- if node.negative ~= nil then
- node.negative = zeroDataSize(node.negative)
- end
- end
- if tostring(node) == "nn.Dropout" then
- if node.noise ~= nil then
- node.noise = zeroDataSize(node.noise)
- end
- end
- -- Recurse on nodes with 'modules'
- if (node.modules ~= nil) then
- if (type(node.modules) == 'table') then
- for i = 1, #node.modules do
- local child = node.modules[i]
- cleanupModel(child)
- end
- end
- end
- end
- function w2nn.cleanup_model(model)
- cleanupModel(model)
- return model
- end
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