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Nicholas Leonard
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Feb 23, 2017
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,15 +1,61 @@ | ||
| SET(CMAKE_MODULE_PATH ${PROJECT_SOURCE_DIR}) | ||
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| CMAKE_MINIMUM_REQUIRED(VERSION 2.6 FATAL_ERROR) | ||
| CMAKE_POLICY(VERSION 2.6) | ||
| IF(LUAROCKS_PREFIX) | ||
| MESSAGE(STATUS "Installing Torch through Luarocks") | ||
| STRING(REGEX REPLACE "(.*)lib/luarocks/rocks.*" "\\1" CMAKE_INSTALL_PREFIX "${LUAROCKS_PREFIX}") | ||
| MESSAGE(STATUS "Prefix inferred from Luarocks: ${CMAKE_INSTALL_PREFIX}") | ||
| ENDIF() | ||
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| FIND_PACKAGE(Torch REQUIRED) | ||
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| SET(src) | ||
| FILE(GLOB luasrc *.lua) | ||
| SET(luasrc ${luasrc}) | ||
| ADD_SUBDIRECTORY(test) | ||
| ADD_TORCH_PACKAGE(rnn "${src}" "${luasrc}" "Recurrent Neural Networks") | ||
| SET(BUILD_STATIC YES) # makes sure static targets are enabled in ADD_TORCH_PACKAGE | ||
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| SET(CMAKE_C_FLAGS "--std=c99 -pedantic -Werror -Wall -Wextra -Wno-unused-function -D_GNU_SOURCE ${CMAKE_C_FLAGS}") | ||
| SET(src | ||
| init.c | ||
| ) | ||
| SET(luasrc | ||
| init.lua | ||
| AbstractRecurrent.lua | ||
| AbstractSequencer.lua | ||
| BiSequencer.lua | ||
| BiSequencerLM.lua | ||
| CopyGrad.lua | ||
| Dropout.lua | ||
| ExpandAs.lua | ||
| FastLSTM.lua | ||
| GRU.lua | ||
| LinearNoBias.lua | ||
| LookupTableMaskZero.lua | ||
| LSTM.lua | ||
| MaskZero.lua | ||
| MaskZeroCriterion.lua | ||
| Module.lua | ||
| Mufuru.lua | ||
| NormStabilizer.lua | ||
| Padding.lua | ||
| Recurrence.lua | ||
| Recurrent.lua | ||
| RecurrentAttention.lua | ||
| recursiveUtils.lua | ||
| Recursor.lua | ||
| Repeater.lua | ||
| RepeaterCriterion.lua | ||
| SAdd.lua | ||
| SeqBRNN.lua | ||
| SeqGRU.lua | ||
| SeqLSTM.lua | ||
| SeqLSTMP.lua | ||
| SeqReverseSequence.lua | ||
| Sequencer.lua | ||
| SequencerCriterion.lua | ||
| TrimZero.lua | ||
| ZeroGrad.lua | ||
| test/bigtest.lua | ||
| test/test.lua | ||
| ) | ||
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| ADD_TORCH_PACKAGE(rnn "${src}" "${luasrc}" "An RNN library for Torch") | ||
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| TARGET_LINK_LIBRARIES(rnn luaT TH) | ||
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| SET_TARGET_PROPERTIES(rnn_static PROPERTIES COMPILE_FLAGS "-fPIC -DSTATIC_TH") | ||
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| INSTALL(FILES ${luasrc} DESTINATION "${Torch_INSTALL_LUA_PATH_SUBDIR}/rnn") |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,79 @@ | ||
| local VariableLength, parent = torch.class("nn.VariableLength", "nn.Decorator") | ||
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| -- make sure your module has been set-up for zero-masking (that is, module:maskZero()) | ||
| function VariableLength:__init(module, lastOnly) | ||
| parent.__init(self, module) | ||
| -- only extract the last element of each sequence | ||
| self.lastOnly = lastOnly -- defaults to false | ||
| end | ||
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| -- recursively masks input (inplace) | ||
| function VariableLength.recursiveMask(input, mask) | ||
| if torch.type(input) == 'table' then | ||
| for k,v in ipairs(input) do | ||
| self.recursiveMask(v, mask) | ||
| end | ||
| else | ||
| assert(torch.isTensor(input)) | ||
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| -- make sure mask has the same dimension as the input tensor | ||
| assert(mask:dim() == 2, "Expecting batchsize x seqlen mask tensor") | ||
| -- expand mask to input (if necessary) | ||
| local zeroMask | ||
| if input:dim() == 2 then | ||
| zeroMask = mask | ||
| elseif input:dim() > 2 then | ||
| local inputSize = input:size():fill(1) | ||
| inputSize[1] = input:size(1) | ||
| inputSize[2] = input:size(2) | ||
| mask:resize(inputSize) | ||
| zeroMask = mask:expandAs(input) | ||
| else | ||
| error"Expecting batchsize x seqlen [ x ...] input tensor" | ||
| end | ||
| -- zero-mask input in between sequences | ||
| input:maskedFill(zeroMask, 0) | ||
| end | ||
| end | ||
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| function VariableLength:updateOutput(input) | ||
| -- input is a table of batchSize tensors | ||
| assert(torch.type(input) == 'table') | ||
| assert(torch.isTensor(input[1])) | ||
| local batchSize = #input | ||
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| self._input = self._input or input[1].new() | ||
| -- mask is a binary tensor with 1 where self._input is zero (between sequence zero-mask) | ||
| self._mask = self._mask or torch.ByteTensor() | ||
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| -- now we process input into _input. | ||
| -- indexes and mappedLengths are meta-information tables, explained below. | ||
| self.indexes, self.mappedLengths = self._input.nn.VariableLength_FromSamples(input, self._input, self._mask) | ||
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| -- zero-mask the _input where mask is 1 | ||
| self.recursiveMask(self._input, self._mask) | ||
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| -- feedforward the zero-mask format through the decorated module | ||
| local output = self.modules[1]:updateOutput(self._input) | ||
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| if self.lastOnly then | ||
| -- Extract the last time step of each sample. | ||
| -- self.output tensor has shape: batchSize [x outputSize] | ||
| self.output = torch.isTensor(self.output) and self.output or output.new() | ||
| self.output.nn.VariableLength_ToFinal(selfindexes, self.mappedLengths, output, self.output) | ||
| else | ||
| -- This is the revese operation of everything before updateOutput | ||
| self.output = input.nn.VariableLength_ToSamples(self.indexes, self.mappedLengths, output) | ||
| end | ||
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| return self.output | ||
| end | ||
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| function VariableLength:updateGradInput(input, gradInput) | ||
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| return self.gradInput | ||
| end | ||
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| function VariableLength:accGradParameters(input, gradInput, scale) | ||
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| end |
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,24 @@ | ||
| #ifndef _ERROR_H_ | ||
| #define _ERROR_H_ | ||
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| #include "luaT.h" | ||
| #include <string.h> | ||
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| static inline int _lua_error(lua_State *L, int ret, const char* file, int line) { | ||
| int pos_ret = ret >= 0 ? ret : -ret; | ||
| return luaL_error(L, "ERROR: (%s, %d): (%d, %s)\n", file, line, pos_ret, strerror(pos_ret)); | ||
| } | ||
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| static inline int _lua_error_str(lua_State *L, const char *str, const char* file, int line) { | ||
| return luaL_error(L, "ERROR: (%s, %d): (%s)\n", file, line, str); | ||
| } | ||
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| static inline int _lua_error_str_str(lua_State *L, const char *str, const char* file, int line, const char *extra) { | ||
| return luaL_error(L, "ERROR: (%s, %d): (%s: %s)\n", file, line, str, extra); | ||
| } | ||
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| #define LUA_HANDLE_ERROR(L, ret) _lua_error(L, ret, __FILE__, __LINE__) | ||
| #define LUA_HANDLE_ERROR_STR(L, str) _lua_error_str(L, str, __FILE__, __LINE__) | ||
| #define LUA_HANDLE_ERROR_STR_STR(L, str, extra) _lua_error_str_str(L, str, __FILE__, __LINE__, extra) | ||
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| #endif |
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