...

Merge remote-tracking branch 'upstream/master'

2 files changed, 74 insertions, 8 deletions

diff --git a/examples/chunk_file_example.lua b/examples/chunk_file_example.lua
new file mode 100644
index 0000000..5961c98
--- /dev/null
+++ b/examples/chunk_file_example.lua
@@ -0,0 +1,53 @@
+-- To define a readable and writable chunk, one must define a class with the
+-- following methods: __init(id, global_conf), read(handle), write(handle),
+-- get_info(), set_info(info) and an id attribute. This file demonstrates a
+-- basic chunk implementation which manages the I/O of a matrix
+
+local MatrixChunk = nerv.class("nerv.MatrixChunk")
+
+function MatrixChunk:__init(id, global_conf)
+    self.id = id
+    self.info = {}
+    self.gconf = global_conf
+end
+
+function MatrixChunk:read(handle)
+    -- pass the read handle to the matrix method
+    self.data = nerv.MMatrixFloat.load(handle)
+end
+
+function MatrixChunk:write(handle)
+    -- pass the write handle to the matrix method
+    self.data:save(handle)
+end
+
+function MatrixChunk:get_info()
+    return self.info
+end
+
+function MatrixChunk:set_info(info)
+    self.info = info
+end
+
+function MatrixChunk.create_from_matrix(id, mat)
+    local ins = nerv.MatrixChunk(id)
+    ins.data = mat
+    return ins
+end
+
+mat = nerv.MMatrixFloat(3, 4)
+for i = 0, 2 do
+    for j = 0, 3 do
+        mat[i][j] = i + j
+    end
+end
+
+cd = nerv.MatrixChunk.create_from_matrix("matrix1", mat)
+
+cf = nerv.ChunkFile("test.nerv", "w")
+cf:write_chunk(cd)
+cf:close()
+
+cf2 = nerv.ChunkFile("test.nerv", "r")
+cd2 = cf2:read_chunk("matrix1")
+print(cd2.data)
diff --git a/examples/test_nn_lib.lua b/examples/test_nn_lib.lua
index 04fd7d6..6fdbd67 100644
--- a/examples/test_nn_lib.lua
+++ b/examples/test_nn_lib.lua
@@ -117,7 +117,7 @@ tnet_reader = nerv.TNetReader(gconf,
 buffer = nerv.SGDBuffer(gconf,
     {
         buffer_size = 81920,
-        -- randomize = true,
+        randomize = true,
         readers = {
             { reader = tnet_reader,
               data = {main_scp = 429, ref = 1}}
@@ -128,9 +128,12 @@ sm = sublayer_repo:get_layer("softmax_ce0")
 main = layer_repo:get_layer("main")
 main:init(gconf.batch_size)
 gconf.cnt = 0
+-- data = buffer:get_data()
+-- input = {data.main_scp, data.ref}
+-- while true do
 for data in buffer.get_data, buffer do
-    if gconf.cnt == 1000 then break end
-    gconf.cnt = gconf.cnt + 1
+--    if gconf.cnt == 100 then break end
+--    gconf.cnt = gconf.cnt + 1
 
     input = {data.main_scp, data.ref}
     output = {}
@@ -141,11 +144,21 @@ for data in buffer.get_data, buffer do
     main:back_propagate(err_output, err_input, input, output)
     main:update(err_input, input, output)
 
-    nerv.utils.printf("cross entropy: %.8f\n", sm.total_ce)
-    nerv.utils.printf("correct: %d\n", sm.total_correct)
-    nerv.utils.printf("frames: %d\n", sm.total_frames)
-    nerv.utils.printf("err/frm: %.8f\n", sm.total_ce / sm.total_frames)
-    nerv.utils.printf("accuracy: %.8f\n", sm.total_correct / sm.total_frames)
+--    nerv.utils.printf("cross entropy: %.8f\n", sm.total_ce)
+--    nerv.utils.printf("correct: %d\n", sm.total_correct)
+--    nerv.utils.printf("frames: %d\n", sm.total_frames)
+--    nerv.utils.printf("err/frm: %.8f\n", sm.total_ce / sm.total_frames)
+--    nerv.utils.printf("accuracy: %.8f\n", sm.total_correct / sm.total_frames)
     collectgarbage("collect")
 end
+nerv.utils.printf("cross entropy: %.8f\n", sm.total_ce)
+nerv.utils.printf("correct: %d\n", sm.total_correct)
+nerv.utils.printf("accuracy: %.3f%%\n", sm.total_correct / sm.total_frames * 100)
+nerv.utils.printf("writing back...\n")
+cf = nerv.ChunkFile("output.nerv", "w")
+for i, p in ipairs(main:get_params()) do
+    print(p)
+    cf:write_chunk(p)
+end
+cf:close()
 nerv.Matrix.print_profile()