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authorcloudygoose <[email protected]>2015-06-12 12:27:36 +0800
committercloudygoose <[email protected]>2015-06-12 12:27:36 +0800
commit83dbefa3435b72911ee643f9f99205247d140279 (patch)
tree819edfc2f32080eb398bbb736a61e27db093b317 /doc/nerv_layer.md
parentc3db7ffba45b7e4d0a1d76281e187b3f88129db9 (diff)
doc change
Diffstat (limited to 'doc/nerv_layer.md')
-rw-r--r--doc/nerv_layer.md10
1 files changed, 5 insertions, 5 deletions
diff --git a/doc/nerv_layer.md b/doc/nerv_layer.md
index 0425d5f..ac6480c 100644
--- a/doc/nerv_layer.md
+++ b/doc/nerv_layer.md
@@ -141,7 +141,8 @@ print('network input&output&error space allocation...')
affineI = {dataM} --input to the network is data
affineO = {nerv.CuMatrixFloat(data_num, 2)}
softmaxI = {affineO[1], labelM}
-softmaxO = {nerv.CuMatrixFloat(data_num, 2)}
+softmaxO = {}
+output = nerv.CuMatrixFloat(data_num, 2)
affineE = {nerv.CuMatrixFloat(data_num, 2)}
--[[space allocation end]]--
@@ -152,9 +153,9 @@ ce_last = 0
for l = 0, 10, 1 do
affineL:propagate(affineI, affineO)
softmaxL:propagate(softmaxI, softmaxO)
- softmaxO[1]:softmax(softmaxI[1])
+ output:softmax(softmaxI[1])
- softmaxL:back_propagate(affineE, nil, softmaxI, softmaxO)
+ softmaxL:back_propagate(affineE, {}, softmaxI, softmaxO)
affineL:update(affineE, affineI, affineO)
@@ -162,10 +163,9 @@ for l = 0, 10, 1 do
nerv.utils.printf("training iteration %d finished\n", l)
nerv.utils.printf("cross entropy: %.8f\n", softmaxL.total_ce - ce_last)
ce_last = softmaxL.total_ce
- nerv.utils.printf("accurate labels: %d\n", calculate_accurate(softmaxO[1], labelM))
+ nerv.utils.printf("accurate labels: %d\n", calculate_accurate(output, labelM))
nerv.utils.printf("total frames processed: %.8f\n", softmaxL.total_frames)
end
end
--[[end training]]--
-
``` \ No newline at end of file