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-rw-r--r--README.md1
-rw-r--r--nerv/examples/swb_baseline.lua3
-rw-r--r--nerv/io/sgd_buffer.lua48
-rw-r--r--nerv/lib/matrix/cukernel.h2
-rw-r--r--nerv/lib/matrix/cumatrix.c1
-rw-r--r--nerv/lib/matrix/cumatrix.h1
-rw-r--r--nerv/lib/matrix/generic/cukernel.cu20
-rw-r--r--nerv/lib/matrix/generic/cumatrix.c19
-rw-r--r--nerv/lib/matrix/generic/cumatrix.h2
-rw-r--r--nerv/lib/matrix/mmatrix.c37
-rw-r--r--nerv/lib/matrix/mmatrix.h3
-rw-r--r--nerv/matrix/generic/cumatrix.c22
-rw-r--r--nerv/matrix/mmatrix.c46
-rw-r--r--nerv/nn/layer_dag.lua2
14 files changed, 145 insertions, 62 deletions
diff --git a/README.md b/README.md
index be8e5b0..8c21bd9 100644
--- a/README.md
+++ b/README.md
@@ -13,6 +13,7 @@ cd nerv
git clone https://github.com/Nerv-SJTU/nerv-speech.git speech
git submodule init && git submodule update
make
+make speech
```
The `git submodule` command is for the __luajit__ repository inside __Nerv__.
Now, you can try to run some example scripts.
diff --git a/nerv/examples/swb_baseline.lua b/nerv/examples/swb_baseline.lua
index bbc6467..8015884 100644
--- a/nerv/examples/swb_baseline.lua
+++ b/nerv/examples/swb_baseline.lua
@@ -173,7 +173,8 @@ function make_buffer(readers)
{
buffer_size = gconf.buffer_size,
randomize = gconf.randomize,
- readers = readers
+ readers = readers,
+ use_gpu = true
})
end
diff --git a/nerv/io/sgd_buffer.lua b/nerv/io/sgd_buffer.lua
index f9d281c..74c4934 100644
--- a/nerv/io/sgd_buffer.lua
+++ b/nerv/io/sgd_buffer.lua
@@ -5,8 +5,22 @@ function SGDBuffer:__init(global_conf, buffer_conf)
self.buffer_size = math.floor(buffer_conf.buffer_size /
global_conf.batch_size) * global_conf.batch_size
self.randomize = buffer_conf.randomize
- if self.randomize == nil then
- self.randomize = false
+ self.consume = buffer_conf.consume
+ local cumat_type = global_conf.cumat_type
+ if buffer_conf.use_gpu then
+ self.mat_type = cumat_type
+ self.copy_rows_from_by_idx = cumat_type.copy_rows_fromd_by_idx
+ self.copy_from = cumat_type.copy_fromd
+ self.copy_from_reader = cumat_type.copy_fromh
+ self.perm_gen = function (x)
+ return cumat_type.new_from_host(nerv.MMatrixFloat.perm_gen(x))
+ end
+ else
+ self.mat_type = global_conf.mmat_type
+ self.copy_rows_from_by_idx = cumat_type.copy_rows_fromh_by_idx
+ self.copy_from = cumat_type.copy_fromh
+ self.perm_gen = nerv.MMatrixFloat.perm_gen
+ self.copy_from_reader = self.mat_type.copy_from
end
self.head = 0
self.tail = 0
@@ -14,7 +28,7 @@ function SGDBuffer:__init(global_conf, buffer_conf)
for i, reader_spec in ipairs(buffer_conf.readers) do
local buffs = {}
for id, width in pairs(reader_spec.data) do
- buffs[id] = {data = global_conf.mmat_type(self.buffer_size, width),
+ buffs[id] = {data = self.mat_type(self.buffer_size, width),
leftover = nil,
width = width}
end
@@ -41,7 +55,7 @@ function SGDBuffer:saturate()
buff.data:copy_from(buff.leftover, 0, lrow)
buff.leftover = nil
end
- nerv.printf("buffer leftover: %d\n", lrow)
+ nerv.info("buffer leftover: %d\n", lrow)
reader.tail = lrow
reader.has_leftover = false
end
@@ -65,21 +79,21 @@ function SGDBuffer:saturate()
if d == nil then
nerv.error("reader does not provide data for %s", id)
end
- buff.leftover = self.gconf.mmat_type(drow - remain,
- buff.width)
- buff.leftover:copy_from(d, remain, drow)
+ buff.leftover = self.mat_type(drow - remain,
+ buff.width)
+ self.copy_from_reader(buff.leftover, d, remain, drow)
end
drow = remain
reader.has_leftover = true
end
for id, buff in pairs(reader.buffs) do
- buff.data:copy_from(data[id], 0, drow, reader.tail)
+ self.copy_from_reader(buff.data, data[id], 0, drow, reader.tail)
end
reader.tail = reader.tail + drow
end
self.tail = math.min(self.tail, reader.tail)
end
- self.rand_map = nerv.MMatrixInt.perm_gen(self.tail) -- generate shuffled index
+ self.rand_map = self.perm_gen(self.tail) -- generate shuffled index
collectgarbage("collect")
return self.tail >= self.gconf.batch_size
end
@@ -88,26 +102,30 @@ function SGDBuffer:get_data()
local batch_size = self.gconf.batch_size
if self.head >= self.tail then -- buffer is empty
local t = os.clock()
- if not self:saturate() then
+ if (not self:saturate()) and (not self.consume) then
return nil -- the remaining data cannot build a batch
end
+ if self.tail == self.head then
+ return nil -- nothing left
+ end
nerv.info("%.3fs to fill the buffer", os.clock() - t)
end
- if self.head + batch_size > self.tail then
+ if self.head + batch_size > self.tail and (not self.consume) then
return nil -- the remaining data cannot build a batch
end
+ actual_batch_size = math.min(batch_size, self.tail - self.head)
local res = {}
for i, reader in ipairs(self.readers) do
for id, buff in pairs(reader.buffs) do
- local batch = self.gconf.cumat_type(batch_size, buff.width)
+ local batch = self.gconf.cumat_type(actual_batch_size, buff.width)
if self.randomize then
- batch:copy_rows_fromh_by_idx(buff.data, self.rand_map, self.head)
+ self.copy_rows_from_by_idx(batch, buff.data, self.rand_map, self.head)
else
- batch:copy_fromh(buff.data, self.head, self.head + batch_size)
+ self.copy_from(batch, buff.data, self.head, self.head + actual_batch_size)
end
res[id] = batch
end
end
- self.head = self.head + batch_size
+ self.head = self.head + actual_batch_size
return res
end
diff --git a/nerv/lib/matrix/cukernel.h b/nerv/lib/matrix/cukernel.h
index 7bb4c2c..2126c6f 100644
--- a/nerv/lib/matrix/cukernel.h
+++ b/nerv/lib/matrix/cukernel.h
@@ -18,4 +18,6 @@ void cudak_(cuda_rearrange_frm)(const Matrix *a, Matrix *b, int step);
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);
+void cudak_(cuda_copy_rows_by_idx)(const Matrix *a, Matrix *b,
+ const Matrix *idx, int b_begin);
#endif
diff --git a/nerv/lib/matrix/cumatrix.c b/nerv/lib/matrix/cumatrix.c
index aa81bfc..ff1168d 100644
--- a/nerv/lib/matrix/cumatrix.c
+++ b/nerv/lib/matrix/cumatrix.c
@@ -49,6 +49,7 @@ void nerv_cumatrix_init() {
#define NERV_CUBLAS_(NAME) cublasS##NAME
#define MATRIX_CUMATRIX_HOST_TNAME nerv_matrix_host_float_tname
#include "generic/cumatrix.c"
+
#undef NERV_CUBLAS_
#undef cudak_
#undef nerv_matrix_
diff --git a/nerv/lib/matrix/cumatrix.h b/nerv/lib/matrix/cumatrix.h
index 9f71507..e6def66 100644
--- a/nerv/lib/matrix/cumatrix.h
+++ b/nerv/lib/matrix/cumatrix.h
@@ -1,5 +1,6 @@
#ifndef NERV_CUMATRIX_H
#define NERV_CUMATRIX_H
+#include "matrix.h"
void nerv_cumatrix_print_profile();
void nerv_cumatrix_clear_profile();
void nerv_cumatrix_init();
diff --git a/nerv/lib/matrix/generic/cukernel.cu b/nerv/lib/matrix/generic/cukernel.cu
index e337798..08feb59 100644
--- a/nerv/lib/matrix/generic/cukernel.cu
+++ b/nerv/lib/matrix/generic/cukernel.cu
@@ -284,6 +284,15 @@ __global__ void cudak_(gen_col_idx)(MATRIX_ELEM *b,
b[j + i * stride] = j;
}
+__global__ void cudak_(copy_rows_by_idx)(const MATRIX_ELEM *a, MATRIX_ELEM *b,
+ const MATRIX_ELEM *idx, int b_begin,
+ 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;
+ b[j + i * stride] = a[j + lrintf(idx[i]) * stride];
+}
+
extern "C" {
#include "../cukernel.h"
void cudak_(cuda_log_elem)(const Matrix *a, Matrix *b) {
@@ -589,5 +598,16 @@ extern "C" {
b->stride / sizeof(MATRIX_ELEM));
cudaStreamSynchronize(0);
}
+
+ void cudak_(cuda_copy_rows_by_idx)(const Matrix *a, Matrix *b,
+ const Matrix *idx, int b_begin) {
+ dim3 threadsPerBlock(CUDA_THREADS_NN, 1);
+ dim3 numBlocks(CEIL_DIV(b->ncol, threadsPerBlock.x), b->nrow);
+ cudak_(copy_rows_by_idx)<<<numBlocks, threadsPerBlock>>> \
+ (MATRIX_ELEM_PTR(a), MATRIX_ELEM_PTR(b),
+ MATRIX_ELEM_PTR(idx) + b_begin,
+ b_begin, b->nrow, b->ncol, b->stride / sizeof(MATRIX_ELEM));
+ cudaStreamSynchronize(0);
+ }
}
#endif
diff --git a/nerv/lib/matrix/generic/cumatrix.c b/nerv/lib/matrix/generic/cumatrix.c
index 2cb3563..770e503 100644
--- a/nerv/lib/matrix/generic/cumatrix.c
+++ b/nerv/lib/matrix/generic/cumatrix.c
@@ -315,7 +315,7 @@ void nerv_matrix_(copy_rows_fromh_by_idx)(Matrix *a, const Matrix *b,
long nrow = a->nrow;
if (!(0 <= b_begin && b_begin + nrow <= idx->ncol))
NERV_EXIT_STATUS(status, MAT_INVALID_COPY_INTERVAL, 0);
- long *idx_ptr = idx->data.i;
+ float *idx_ptr = idx->data.f;
int i;
if (idx->nrow != 1)
NERV_EXIT_STATUS(status, MAT_IDX_VECTOR_EXP, 0);
@@ -325,7 +325,7 @@ void nerv_matrix_(copy_rows_fromh_by_idx)(Matrix *a, const Matrix *b,
cudaStream_t *streams = (cudaStream_t*)malloc(sizeof(cudaStream_t) * nrow);
for (i = 0; i < nrow; i++)
{
- int src_row = idx_ptr[b_begin + i];
+ int src_row = (int)idx_ptr[b_begin + i];
if (!(0 <= src_row && src_row < b->nrow))
NERV_EXIT_STATUS(status, MAT_INVALID_IDX, 0);
CUDA_SAFE_CALL(cudaStreamCreate(streams + i), status);
@@ -344,6 +344,21 @@ void nerv_matrix_(copy_rows_fromh_by_idx)(Matrix *a, const Matrix *b,
NERV_SET_STATUS(status, NERV_NORMAL, 0);
}
+void nerv_matrix_(copy_rows_fromd_by_idx)(Matrix *a, const Matrix *b,
+ const Matrix *idx, int b_begin, Status *status) {
+ long nrow = a->nrow;
+ if (!(0 <= b_begin && b_begin + nrow <= idx->ncol))
+ NERV_EXIT_STATUS(status, MAT_INVALID_COPY_INTERVAL, 0);
+ if (idx->nrow != 1)
+ NERV_EXIT_STATUS(status, MAT_IDX_VECTOR_EXP, 0);
+ if (a->ncol != b->ncol)
+ NERV_EXIT_STATUS(status, MAT_MISMATCH_DIM, 0);
+ PROFILE_START
+ cudak_(cuda_copy_rows_by_idx)(b, a, idx, b_begin);
+ PROFILE_STOP
+ NERV_SET_STATUS(status, NERV_NORMAL, 0);
+}
+
void nerv_matrix_(expand_frm)(Matrix *a, const Matrix *b,
int context, Status *status) {
if (a->nrow != b->nrow)
diff --git a/nerv/lib/matrix/generic/cumatrix.h b/nerv/lib/matrix/generic/cumatrix.h
index 3f1f8a3..04e8c5a 100644
--- a/nerv/lib/matrix/generic/cumatrix.h
+++ b/nerv/lib/matrix/generic/cumatrix.h
@@ -40,6 +40,8 @@ void nerv_matrix_(log_elem)(Matrix *b, const Matrix *a, Status *status);
Matrix *nerv_matrix_(decompress)(const Matrix *a, int orig_col, Status *status);
void nerv_matrix_(copy_rows_fromh_by_idx)(Matrix *a, const Matrix *b,
const Matrix *idx, int b_begin, Status *status);
+void nerv_matrix_(copy_rows_fromd_by_idx)(Matrix *a, const Matrix *b,
+ const Matrix *idx, int b_begin, Status *status);
void nerv_matrix_(expand_frm)(Matrix *a, const Matrix *b,
int context, Status *status);
diff --git a/nerv/lib/matrix/mmatrix.c b/nerv/lib/matrix/mmatrix.c
index 94f1ea8..b8157eb 100644
--- a/nerv/lib/matrix/mmatrix.c
+++ b/nerv/lib/matrix/mmatrix.c
@@ -7,6 +7,25 @@
#define nerv_matrix_(NAME) nerv_matrix_host_float_##NAME
#include "generic/matrix.h"
#include "generic/mmatrix.c"
+
+Matrix *nerv_matrix_(perm_gen)(int ncol, Status *status) {
+ int i;
+ Matrix *self = nerv_matrix_(create)(1, ncol, status);
+ if (status->err_code != NERV_NORMAL)
+ return NULL;
+ float *prow = self->data.f;
+ for (i = 0; i < ncol; i++)
+ prow[i] = i;
+ for (i = ncol - 1; i >= 0; i--)
+ {
+ size_t j = rand() % (i + 1);
+ float tmp = prow[i];
+ prow[i] = prow[j];
+ prow[j] = tmp;
+ }
+ return self;
+}
+
#undef nerv_matrix_
#undef host_matrix_
#undef MATRIX_USE_FLOAT
@@ -33,21 +52,3 @@
#define host_matrix_(NAME) host_matrix_int_##NAME
#define nerv_matrix_(NAME) nerv_matrix_host_int_##NAME
#include "generic/mmatrix.c"
-
-Matrix *nerv_matrix_(perm_gen)(int ncol, Status *status) {
- int i;
- Matrix *self = nerv_matrix_(create)(1, ncol, status);
- if (status->err_code != NERV_NORMAL)
- return NULL;
- long *prow = self->data.i;
- for (i = 0; i < ncol; i++)
- prow[i] = i;
- for (i = ncol - 1; i >= 0; i--)
- {
- size_t j = rand() % (i + 1);
- long tmp = prow[i];
- prow[i] = prow[j];
- prow[j] = tmp;
- }
- return self;
-}
diff --git a/nerv/lib/matrix/mmatrix.h b/nerv/lib/matrix/mmatrix.h
index df91e4c..31e7984 100644
--- a/nerv/lib/matrix/mmatrix.h
+++ b/nerv/lib/matrix/mmatrix.h
@@ -1,4 +1,5 @@
#ifndef NERV_MMATRIX_H
#define NERV_MMATRIX_H
-Matrix *nerv_matrix_(perm_gen)(int ncol, Status *status);
+#include "matrix.h"
+Matrix *nerv_matrix_host_float_perm_gen(int ncol, Status *status);
#endif
diff --git a/nerv/matrix/generic/cumatrix.c b/nerv/matrix/generic/cumatrix.c
index ab7f7c4..08cb4c2 100644
--- a/nerv/matrix/generic/cumatrix.c
+++ b/nerv/matrix/generic/cumatrix.c
@@ -228,12 +228,12 @@ static int nerv_matrix_(lua_decompress)(lua_State *L) {
return 1;
}
-extern const char *nerv_matrix_host_int_tname;
+extern const char *nerv_matrix_host_float_tname;
static int nerv_matrix_(lua_copy_rows_fromh_by_idx)(lua_State *L) {
Status status;
Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
const Matrix *b = luaT_checkudata(L, 2, MATRIX_CUMATRIX_HOST_TNAME);
- const Matrix *idx = luaT_checkudata(L, 3, nerv_matrix_host_int_tname);
+ const Matrix *idx = luaT_checkudata(L, 3, nerv_matrix_host_float_tname);
long nrow = a->nrow;
int b_begin = lua_gettop(L) > 3 ? luaL_checkinteger(L, 4) : 0;
nerv_matrix_(copy_rows_fromh_by_idx)(a, b, idx, b_begin, &status);
@@ -241,6 +241,18 @@ static int nerv_matrix_(lua_copy_rows_fromh_by_idx)(lua_State *L) {
return 0;
}
+static int nerv_matrix_(lua_copy_rows_fromd_by_idx)(lua_State *L) {
+ Status status;
+ Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
+ const Matrix *b = luaT_checkudata(L, 2, nerv_matrix_(tname));
+ const Matrix *idx = luaT_checkudata(L, 3, nerv_matrix_(tname));
+ long nrow = a->nrow;
+ int b_begin = lua_gettop(L) > 3 ? luaL_checkinteger(L, 4) : 0;
+ nerv_matrix_(copy_rows_fromd_by_idx)(a, b, idx, b_begin, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
+ return 0;
+}
+
static int nerv_matrix_(lua_expand_frm)(lua_State *L) {
Status status;
Matrix *a = luaT_checkudata(L, 1, nerv_matrix_(tname));
@@ -290,6 +302,8 @@ static const luaL_Reg nerv_matrix_(extra_methods)[] = {
/* in-place calc */
{"copy_fromh", nerv_matrix_(lua_copy_fromh)},
{"copy_fromd", nerv_matrix_(lua_copy_fromd)},
+ /* alias for copy_fromd */
+ {"copy_from", nerv_matrix_(lua_copy_fromd)},
{"copy_toh", nerv_matrix_(lua_copy_toh)},
{"add", nerv_matrix_(lua_add)},
{"mul", nerv_matrix_(lua_mul)},
@@ -302,6 +316,7 @@ static const luaL_Reg nerv_matrix_(extra_methods)[] = {
{"mul_elem", nerv_matrix_(lua_mul_elem)},
{"log_elem", nerv_matrix_(lua_log_elem)},
{"copy_rows_fromh_by_idx", nerv_matrix_(lua_copy_rows_fromh_by_idx)},
+ {"copy_rows_fromd_by_idx", nerv_matrix_(lua_copy_rows_fromd_by_idx)},
{"expand_frm", nerv_matrix_(lua_expand_frm)},
{"rearrange_frm", nerv_matrix_(lua_rearrange_frm)},
{"scale_rows_by_row", nerv_matrix_(lua_scale_rows_by_row)},
@@ -311,6 +326,9 @@ static const luaL_Reg nerv_matrix_(extra_methods)[] = {
static void cuda_matrix_(init)(lua_State *L) {
luaN_append_methods(L, nerv_matrix_(extra_methods));
+#ifdef CUMATRIX_INIT
+ CUMATRIX_INIT(L);
+#endif
}
int nerv_matrix_(lua_get_elem)(lua_State *L) {
diff --git a/nerv/matrix/mmatrix.c b/nerv/matrix/mmatrix.c
index 5561572..961059c 100644
--- a/nerv/matrix/mmatrix.c
+++ b/nerv/matrix/mmatrix.c
@@ -16,7 +16,30 @@ void nerv_lua_mmatrix_init(lua_State *L) {
#define host_matrix_(NAME) host_matrix_float_##NAME
#define nerv_matrix_(NAME) nerv_matrix_host_float_##NAME
const char *nerv_matrix_(tname) = "nerv.MMatrixFloat";
+#define MMATRIX_INIT(L) host_matrix_(init_extra)(L)
+
+static const luaL_Reg nerv_matrix_(extra_methods_int)[];
+static void host_matrix_(init_extra)(lua_State *L) {
+ luaN_append_methods(L, nerv_matrix_(extra_methods_int));
+}
+
#include "generic/mmatrix.c"
+#include "../lib/matrix/mmatrix.h"
+
+static int nerv_matrix_(lua_perm_gen)(lua_State *L) {
+ Status status;
+ int i, ncol = luaL_checkinteger(L, 1);
+ Matrix *self = nerv_matrix_(perm_gen)(ncol, &status);
+ NERV_LUA_CHECK_STATUS(L, status);
+ luaT_pushudata(L, self, nerv_matrix_(tname));
+ return 1;
+}
+
+static const luaL_Reg nerv_matrix_(extra_methods_int)[] = {
+ {"perm_gen", nerv_matrix_(lua_perm_gen)},
+ {NULL, NULL}
+};
+
#undef nerv_matrix_
#undef host_matrix_
#undef MATRIX_USE_FLOAT
@@ -24,6 +47,7 @@ const char *nerv_matrix_(tname) = "nerv.MMatrixFloat";
#undef MATRIX_ELEM_PTR
#undef MATRIX_ELEM_FMT
#undef MATRIX_ELEM_WRITE_FMT
+#undef MMATRIX_INIT
#define NERV_GENERIC_MMATRIX
#define MATRIX_USE_DOUBLE
@@ -44,26 +68,4 @@ const char *nerv_matrix_(tname) = "nerv.MMatrixDouble";
#define host_matrix_(NAME) host_matrix_int_##NAME
#define nerv_matrix_(NAME) nerv_matrix_host_int_##NAME
const char *nerv_matrix_(tname) = "nerv.MMatrixInt";
-#define MMATRIX_INIT(L) host_matrix_(init_extra)(L)
-
-static const luaL_Reg nerv_matrix_(extra_methods_int)[];
-static void host_matrix_(init_extra)(lua_State *L) {
- luaN_append_methods(L, nerv_matrix_(extra_methods_int));
-}
-
#include "generic/mmatrix.c"
-#include "../lib/matrix/mmatrix.h"
-
-static int nerv_matrix_(lua_perm_gen)(lua_State *L) {
- Status status;
- int i, ncol = luaL_checkinteger(L, 1);
- Matrix *self = nerv_matrix_(perm_gen)(ncol, &status);
- NERV_LUA_CHECK_STATUS(L, status);
- luaT_pushudata(L, self, nerv_matrix_(tname));
- return 1;
-}
-
-static const luaL_Reg nerv_matrix_(extra_methods_int)[] = {
- {"perm_gen", nerv_matrix_(lua_perm_gen)},
- {NULL, NULL}
-};
diff --git a/nerv/nn/layer_dag.lua b/nerv/nn/layer_dag.lua
index 25297c2..f69d31c 100644
--- a/nerv/nn/layer_dag.lua
+++ b/nerv/nn/layer_dag.lua
@@ -266,7 +266,7 @@ function DAGLayer:get_intermediate(id, port_type)
if id == "<input>" or id == "<output>" then
nerv.error("an actual real layer id is expected")
end
- local layer = layers[id]
+ local layer = self.layers[id]
if layer == nil then
nerv.error("layer id %s not found", id)
end
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