質問編集履歴
6
コードが見難かったので修正しました。
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@@ -57,6 +57,7 @@
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```
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＜追記＞
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```python
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class MyChain(chainer.Chain):
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def init(self):
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super(MyChain, self).init()
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with self.init_scope():
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self.l1 = L.Linear(None, 3)
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self.l2 = L.Linear(None, 2)
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```
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おそらくこの下の箇所が問題かと思っているのですが、
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```python
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def call(self, x):
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h = F.relu(self.l1(x))
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h = self.l2(h)
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return h
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```
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・書き方１
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```python
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def call(self, x):
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h1 = F.relu(self.l1(x))
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y = self.l2(h1)
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return y
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```
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・書き方２
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```python
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def call(self, x):
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h1 = F.relu(self.l1(x))
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h2 = self.l2(h1)
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return h2
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```
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・書き方３
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```python
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def call(self, x):
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h = F.relu(self.l1(x))
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return self.l2(h)
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```
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などの書き方をしても解消されない状態です。。
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5
コード検証例追加
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@@ -54,4 +54,38 @@
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trainer.run()
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chainer.serializers.save_npz("result/out.model",model)
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```
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```
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＜追記＞
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class MyChain(chainer.Chain):
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def init(self):
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super(MyChain, self).init()
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with self.init_scope():
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self.l1 = L.Linear(None, 3)
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self.l2 = L.Linear(None, 2)
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おそらくこの下の箇所が問題かと思っているのですが、
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def call(self, x):
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h = F.relu(self.l1(x))
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h = self.l2(h)
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return h
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・書き方１
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def call(self, x):
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h1 = F.relu(self.l1(x))
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y = self.l2(h1)
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return y
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・書き方２
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def call(self, x):
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h1 = F.relu(self.l1(x))
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h2 = self.l2(h1)
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return h2
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・書き方３
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def call(self, x):
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h = F.relu(self.l1(x))
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return self.l2(h)
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などの書き方をしても解消されない状態です。。
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4
微修正
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@@ -5,6 +5,7 @@
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〜コード〜
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```python
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import numpy as np
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import chainer
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import chainer.functions as F
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trainer.run()
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chainer.serializers.save_npz("result/out.model",model)
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chainer.serializers.save_npz("result/out.model",model)
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```
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微修正
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@@ -20,6 +20,7 @@
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with self.init_scope():
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self.l1 = L.Linear(None, 3)
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self.l2 = L.Linear(None, 2)
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def __call__(self, x):
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h = F.relu(self.l1(x))
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h = self.l2(h)
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微修正
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@@ -5,7 +5,6 @@
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〜コード〜
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```python
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import numpy as np
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import chainer
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import chainer.functions as F
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from chainer import training
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from chainer.training import extensions
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#NNの設定
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class MyChain(chainer.Chain):
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def __init__(self):
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super(MyChain, self).__init__()
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h = self.l2(h)
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return h
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#データの設定
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trainx = np.array(([0,0],[0,1],[1,0],[1,1]),dtype=np.float32)
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trainy = np.array([0,1,1,0],dtype=np.int32)
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train = chainer.datasets.TupleDataset(trainx,trainy)
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test = chainer.datasets.TupleDataset(trainx,trainy)
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#chainerの設定
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#ニューラルネットの登録
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model = L.Classifier(MyChain(),lossfun=F.softmax_cross_entropy)
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optimizer = chainer.optimizers.Adam()
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optimizer.setup(model)
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#イテレータの定義
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batchsize = 4
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train_iter = chainer.iterators.SerialIterator(train,batchsize) #学習用
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test_iter = chainer.iterators.SerialIterator(test,batchsize,repeat=False,shuffle=False) #評価用
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#アップデータの登録
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updater = training.StandardUpdater(train_iter,optimizer)
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#トレーナーの登録
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epoch = 500
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trainer = training.Trainer(updater,(epoch,'epoch'))
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#学習状況の表示や保存
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trainer.extend(extensions.LogReport()) #ログ
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trainer.extend(extensions.Evaluator(test_iter,model)) #エポック数の表示
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trainer.extend(extensions.PrintReport(['epoch','main/loss','validation/main/loss','main/accuracy','validation/main/accuracy','elapsed_time'])) #計算状態の表示
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trainer.extend(extensions.PlotReport(['main/loss','validation/main/loss'],'epoch',file_name='loss.png')) #誤差グラフ
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trainer.extend(extensions.PlotReport(['main/accuracy','validation/main/accuracy'],'epoch',file_name='accuracy.png')) #精度グラフ
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#学習開始
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trainer.run()
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#モデルの保存
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chainer.serializers.save_npz("result/out.model",model)
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chainer.serializers.save_npz("result/out.model",model)```
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```
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1
コードが見難かったので修正しました。
title
CHANGED
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File without changes
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body
CHANGED
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@@ -4,7 +4,8 @@
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4
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5
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6
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〜コード〜
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7
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-
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```python
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8
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import numpy as np
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import chainer
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import chainer.functions as F
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@@ -61,4 +62,6 @@
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trainer.run()
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#モデルの保存
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chainer.serializers.save_npz("result/out.model",model)
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chainer.serializers.save_npz("result/out.model",model)
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+
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+
```
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