diff options
| -rw-r--r-- | Makefile | 6 | ||||
| -rw-r--r-- | common.h | 1 | ||||
| -rw-r--r-- | layer/combiner.lua | 55 | ||||
| -rw-r--r-- | layer/init.lua | 2 | ||||
| -rw-r--r-- | layer/mse.lua | 52 | ||||
| -rw-r--r-- | layer/softmax_ce.lua | 12 | ||||
| -rw-r--r-- | layer/window.lua | 2 | ||||
| -rw-r--r-- | matrix/cukernel.h | 3 | ||||
| -rw-r--r-- | matrix/generic/cukernel.cu | 31 | ||||
| -rw-r--r-- | matrix/generic/cumatrix.c | 24 | ||||
| -rw-r--r-- | matrix/mmatrix.c | 2 |
11 files changed, 173 insertions, 17 deletions
@@ -8,12 +8,12 @@ LIBS := libnerv.so LUA_LIBS := matrix/init.lua io/init.lua nerv.lua \ pl/utils.lua pl/compat.lua \ layer/init.lua layer/affine.lua layer/sigmoid.lua layer/softmax_ce.lua \ - layer/window.lua layer/bias.lua \ + layer/window.lua layer/bias.lua layer/combiner.lua layer/mse.lua \ nn/init.lua nn/layer_repo.lua nn/param_repo.lua nn/layer_dag.lua \ io/sgd_buffer.lua INCLUDE := -I build/luajit-2.0/include/luajit-2.0/ -DLUA_USE_APICHECK -CUDA_BASE := /usr/local/cuda-6.5 -#CUDA_BASE := /usr/local/cuda-5.0 +#CUDA_BASE := /usr/local/cuda-6.5 +CUDA_BASE := /usr/local/cuda-5.0 CUDA_INCLUDE := -I $(CUDA_BASE)/include/ INCLUDE += $(CUDA_INCLUDE) LDFLAGS := -L$(CUDA_BASE)/lib64/ -Wl,-rpath=$(CUDA_BASE)/lib64/ -lcudart -lcublas @@ -26,6 +26,7 @@ typedef struct HashMap { HashMap *hashmap_create(size_t size, HashKey_t hfunc, HashMapCmp_t cmp); void *hashmap_getval(HashMap *h, const char *key); void hashmap_setval(HashMap *h, const char *key, void *val); +void hashmap_clear(HashMap *h); size_t bkdr_hash(const char *key); diff --git a/layer/combiner.lua b/layer/combiner.lua new file mode 100644 index 0000000..2eac83c --- /dev/null +++ b/layer/combiner.lua @@ -0,0 +1,55 @@ +local CombinerLayer = nerv.class('nerv.CombinerLayer', 'nerv.Layer') + +function CombinerLayer:__init(id, global_conf, layer_conf) + self.id = id + self.lambda = layer_conf.lambda + self.dim_in = layer_conf.dim_in + self.dim_out = layer_conf.dim_out + self.gconf = global_conf + self:check_dim_len(#self.lambda, -1) +end + +function CombinerLayer:init() + local dim = self.dim_in[1] + for i = 2, #self.dim_in do + if self.dim_in[i] ~= dim then + nerv.error("mismatching dimensions of inputs") + end + end + for i = 1, #self.dim_out do + if self.dim_out[i] ~= dim then + nerv.error("mismatching dimensions of inputs/outputs") + end + end +end + +function CombinerLayer:update(bp_err, input, output) +end + +function CombinerLayer:propagate(input, output) + output[1]:fill(0) + for i = 1, #self.dim_in do + output[1]:add(output[1], input[i], 1.0, self.lambda[i]) + end + for i = 2, #self.dim_out do + output[i]:copy_fromd(output[1]) + end +end + +function CombinerLayer:back_propagate(next_bp_err, bp_err, input, output) + local sum = bp_err[1]:create() + sum:fill(0) + for i = 1, #self.dim_out do + sum:add(sum, bp_err[i], 1.0, 1.0) + end + for i = 1, #self.dim_in do + local scale = nerv.CuMatrixFloat(sum:nrow(), 1) + scale:fill(self.lambda[i]) + next_bp_err[i]:copy_fromd(sum) + next_bp_err[i]:scale_rows_by_col(scale) + end +end + +function CombinerLayer:get_params() + return {self.lambda} +end diff --git a/layer/init.lua b/layer/init.lua index 844f46b..169427d 100644 --- a/layer/init.lua +++ b/layer/init.lua @@ -71,3 +71,5 @@ require 'layer.sigmoid' require 'layer.softmax_ce' require 'layer.bias' require 'layer.window' +require 'layer.mse' +require 'layer.combiner' diff --git a/layer/mse.lua b/layer/mse.lua new file mode 100644 index 0000000..da5b24d --- /dev/null +++ b/layer/mse.lua @@ -0,0 +1,52 @@ +local MSELayer = nerv.class("nerv.MSELayer", "nerv.Layer") + +function MSELayer:__init(id, global_conf, layer_conf) + self.id = id + self.dim_in = layer_conf.dim_in + self.dim_out = layer_conf.dim_out + self.gconf = global_conf + self:check_dim_len(2, -1) +end + +function MSELayer:init() + if self.dim_in[1] ~= self.dim_in[2] then + nerv.error("mismatching dimensions of previous network output and labels") + end + self.total_mse = 0.0 + self.total_frames = 0 +end + +function MSELayer:update(bp_err, input, output) + -- no params, therefore do nothing +end + +function MSELayer:propagate(input, output) + local mse = input[1]:create() + mse:add(input[1], input[2], 1.0, -1.0) + self.diff = mse:create() + self.diff:copy_fromd(mse) + mse:mul_elem(mse, mse) + mse = mse:rowsum(mse) + local scale = nerv.CuMatrixFloat(mse:nrow(), 1) + scale:fill(1 / input[1]:ncol()) + mse:scale_rows_by_col(scale) + if output[1] ~= nil then + output[1]:copy_fromd(mse) + end + self.total_mse = self.total_mse + mse:colsum()[0] + self.total_frames = self.total_frames + mse:nrow() +end + +-- NOTE: must call propagate before back_propagate +function MSELayer:back_propagate(next_bp_err, bp_err, input, output) + local nbe = next_bp_err[1] + nbe:copy_fromd(self.diff) + self.diff = nil + if bp_err[1] ~= nil then + nbe:scale_rows_by_col(bp_err[1]) + end +end + +function MSELayer:get_params() + return {} +end diff --git a/layer/softmax_ce.lua b/layer/softmax_ce.lua index 2e1f5fb..7888540 100644 --- a/layer/softmax_ce.lua +++ b/layer/softmax_ce.lua @@ -36,8 +36,12 @@ function SoftmaxCELayer:propagate(input, output) label = label:decompress(input[1]:ncol()) end ce:mul_elem(ce, label) + ce = ce:rowsum() + if output[1] ~= nil then + output[1]:copy_fromd(ce) + end -- add total ce - self.total_ce = self.total_ce - ce:rowsum():colsum()[0] + self.total_ce = self.total_ce - ce:colsum()[0] self.total_frames = self.total_frames + soutput:nrow() -- TODO: add colsame for uncompressed label if self.compressed then @@ -51,7 +55,11 @@ function SoftmaxCELayer:back_propagate(next_bp_err, bp_err, input, output) if self.compressed then label = label:decompress(input[1]:ncol()) end - next_bp_err[1]:add(self.soutput, label, 1.0, -1.0) + local nbe = next_bp_err[1] + nbe:add(self.soutput, label, 1.0, -1.0) + if bp_err[1] ~= nil then + nbe:scale_rows_by_col(bp_err[1]) + end end function SoftmaxCELayer:get_params() diff --git a/layer/window.lua b/layer/window.lua index b381c9b..3a093f4 100644 --- a/layer/window.lua +++ b/layer/window.lua @@ -20,7 +20,7 @@ end function WindowLayer:propagate(input, output) output[1]:copy_fromd(input[1]) - output[1]:scale_row(self.window.trans) + output[1]:scale_rows_by_row(self.window.trans) end function WindowLayer:get_params() diff --git a/matrix/cukernel.h b/matrix/cukernel.h index 23398c8..8a1494f 100644 --- a/matrix/cukernel.h +++ b/matrix/cukernel.h @@ -14,6 +14,7 @@ void cudak_(cuda_add_row)(const Matrix *a, Matrix *b, double beta); void cudak_(cuda_fill)(Matrix *a, double val); void cudak_(cuda_expand_frm)(const Matrix *a, Matrix *b, int context); void cudak_(cuda_rearrange_frm)(const Matrix *a, Matrix *b, int step); -void cudak_(cuda_scale_row)(const Matrix *a, Matrix *b); +void cudak_(cuda_scale_rows_by_row)(const Matrix *a, Matrix *b); +void cudak_(cuda_scale_rows_by_col)(const Matrix *a, Matrix *b); void cudak_(cuda_decompress)(const Matrix *a, Matrix *b); #endif diff --git a/matrix/generic/cukernel.cu b/matrix/generic/cukernel.cu index ffae5ed..d6c8adc 100644 --- a/matrix/generic/cukernel.cu +++ b/matrix/generic/cukernel.cu @@ -237,9 +237,18 @@ __global__ void cudak_(rearrange_frm)(const MATRIX_ELEM *a, MATRIX_ELEM *b, b[j + i * stride] = a[j / step + (j % step) * orig_dim + i * stride]; } -__global__ void cudak_(scale_row)(const MATRIX_ELEM *a, MATRIX_ELEM *b, - int nrow, int ncol, - int stride) { +__global__ void cudak_(scale_rows_by_col)(const MATRIX_ELEM *a, MATRIX_ELEM *b, + int nrow, int ncol, + int astride, int bstride) { + int j = blockIdx.x * blockDim.x + threadIdx.x; + int i = blockIdx.y * blockDim.y + threadIdx.y; + if (i >= nrow || j >= ncol) return; + b[j + i * bstride] *= a[i * astride]; +} + +__global__ void cudak_(scale_rows_by_row)(const MATRIX_ELEM *a, MATRIX_ELEM *b, + int nrow, int ncol, + int stride) { int j = blockIdx.x * blockDim.x + threadIdx.x; int i = blockIdx.y * blockDim.y + threadIdx.y; if (i >= nrow || j >= ncol) return; @@ -526,11 +535,23 @@ extern "C" { cudaStreamSynchronize(0); } - void cudak_(cuda_scale_row)(const Matrix *a, Matrix *b) { + void cudak_(cuda_scale_rows_by_col)(const Matrix *a, Matrix *b) { + dim3 threadsPerBlock(CUDA_THREADS_N, CUDA_THREADS_N); + dim3 numBlocks(CEIL_DIV(b->ncol, threadsPerBlock.x), + CEIL_DIV(b->nrow, threadsPerBlock.y)); + cudak_(scale_rows_by_col)<<<numBlocks, threadsPerBlock>>> \ + (MATRIX_ELEM_PTR(a), MATRIX_ELEM_PTR(b), + b->nrow, b->ncol, + a->stride / sizeof(MATRIX_ELEM), + b->stride / sizeof(MATRIX_ELEM)); + cudaStreamSynchronize(0); + } + + void cudak_(cuda_scale_rows_by_row)(const Matrix *a, Matrix *b) { dim3 threadsPerBlock(CUDA_THREADS_N, CUDA_THREADS_N); dim3 numBlocks(CEIL_DIV(b->ncol, threadsPerBlock.x), CEIL_DIV(b->nrow, threadsPerBlock.y)); - cudak_(scale_row)<<<numBlocks, threadsPerBlock>>> \ + cudak_(scale_rows_by_row)<<<numBlocks, threadsPerBlock>>> \ (MATRIX_ELEM_PTR(a), MATRIX_ELEM_PTR(b), b->nrow, b->ncol, b->stride / sizeof(MATRIX_ELEM)); cudaStreamSynchronize(0); diff --git a/matrix/generic/cumatrix.c b/matrix/generic/cumatrix.c index a8e18e0..b5d1a35 100644 --- a/matrix/generic/cumatrix.c +++ b/matrix/generic/cumatrix.c @@ -37,8 +37,8 @@ static int nerv_matrix_(add)(lua_State *L) { Matrix *c = luaT_checkudata(L, 1, nerv_matrix_(tname)); Matrix *a = luaT_checkudata(L, 2, nerv_matrix_(tname)); Matrix *b = luaT_checkudata(L, 3, nerv_matrix_(tname)); - MATRIX_ELEM alpha = luaL_checknumber(L, 4); /* alpha */ - MATRIX_ELEM beta = luaL_checknumber(L, 5); /* alpha */ + MATRIX_ELEM alpha = luaL_checknumber(L, 4); + MATRIX_ELEM beta = luaL_checknumber(L, 5); CHECK_SAME_DIMENSION(a, b); CHECK_SAME_DIMENSION(a, c); nerv_matrix_(add_)(L, a, b, c, alpha, beta); @@ -396,7 +396,20 @@ static int nerv_matrix_(rearrange_frm)(lua_State *L) { return 0; } -static int nerv_matrix_(scale_row)(lua_State *L) { +static int nerv_matrix_(scale_rows_by_col)(lua_State *L) { + Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); + Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname)); + if (a->nrow != b->nrow) + nerv_error(L, "the number of rows is not the same"); + if (b->ncol != 1) + nerv_error(L, "a column vector is expected"); + PROFILE_START + cudak_(cuda_scale_rows_by_col)(b, a); + PROFILE_STOP + return 0; +} + +static int nerv_matrix_(scale_rows_by_row)(lua_State *L) { Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname)); Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname)); if (a->ncol != b->ncol) @@ -404,7 +417,7 @@ static int nerv_matrix_(scale_row)(lua_State *L) { if (b->nrow != 1) nerv_error(L, "a row vector is expected"); PROFILE_START - cudak_(cuda_scale_row)(b, a); + cudak_(cuda_scale_rows_by_row)(b, a); PROFILE_STOP return 0; } @@ -434,7 +447,8 @@ static const luaL_Reg nerv_matrix_(extra_methods)[] = { {"copy_rows_fromh_by_idx", nerv_matrix_(copy_rows_fromh_by_idx)}, {"expand_frm", nerv_matrix_(expand_frm)}, {"rearrange_frm", nerv_matrix_(rearrange_frm)}, - {"scale_row", nerv_matrix_(scale_row)}, + {"scale_rows_by_row", nerv_matrix_(scale_rows_by_row)}, + {"scale_rows_by_col", nerv_matrix_(scale_rows_by_col)}, {NULL, NULL} }; diff --git a/matrix/mmatrix.c b/matrix/mmatrix.c index ffc058d..d1d68b9 100644 --- a/matrix/mmatrix.c +++ b/matrix/mmatrix.c @@ -1,10 +1,12 @@ #define NERV_GENERIC_MMATRIX +#include <stdlib.h> #include "../common.h" void nerv_matrix_host_float_init(lua_State *L); void nerv_matrix_host_double_init(lua_State *L); void nerv_matrix_host_int_init(lua_State *L); void nerv_mmatrix_init(lua_State *L) { + srand(1); nerv_matrix_host_float_init(L); nerv_matrix_host_double_init(L); nerv_matrix_host_int_init(L); |