"Mxnet"의 두 판 사이의 차이

ph
이동: 둘러보기, 검색
잔글 (→‎etc)
잔글 (→‎etc)
9번째 줄: 9번째 줄:
 
==etc==
 
==etc==
 
* batch normalization example
 
* batch normalization example
<pre>def ConvFactory(data, num_filter, kernel, stride=(1,1), pad=(0, 0),name=None, suffix=''):
+
<pre>def ConvFactory(data, num_filter, kernel,  
     conv = mx.sym.Convolution(data=data, num_filter=num_filter, kernel=kernel,
+
                stride=(1,1), pad=(0, 0),name=None, suffix=''):
                   stride=stride, pad=pad, name='conv_%s%s' %(name, suffix))
+
     conv = mx.sym.Convolution(data=data,
 +
                  num_filter=num_filter,
 +
                  kernel=kernel,
 +
                   stride=stride,
 +
                  pad=pad,
 +
                  name='conv_%s%s' %(name, suffix))
 
     bn = mx.sym.BatchNorm(data=conv, name='bn_%s%s' %(name, suffix))
 
     bn = mx.sym.BatchNorm(data=conv, name='bn_%s%s' %(name, suffix))
 
     act = mx.sym.Activation(data=bn, act_type='relu', name='relu_%s%s'
 
     act = mx.sym.Activation(data=bn, act_type='relu', name='relu_%s%s'

2017년 7월 4일 (화) 19:05 판

http://mxnet.io

뭘 이렇게들 만들어 대는지. tf가 맘에 안들기는 하지만.

Mxnet/Basics

Mxnet/Training and Inference

etc

  • batch normalization example
def ConvFactory(data, num_filter, kernel, 
                stride=(1,1), pad=(0, 0),name=None, suffix=''):
    conv = mx.sym.Convolution(data=data,
                  num_filter=num_filter,
                  kernel=kernel,
                  stride=stride,
                  pad=pad,
                  name='conv_%s%s' %(name, suffix))
    bn = mx.sym.BatchNorm(data=conv, name='bn_%s%s' %(name, suffix))
    act = mx.sym.Activation(data=bn, act_type='relu', name='relu_%s%s'
                  %(name, suffix))
    return act

How do I fine-tune pre-trained models to a new dataset?