質問編集履歴

写真の追加

2021/05/05 04:39

投稿

taiyo.

スコア2

test CHANGED Viewed

File without changes

test CHANGED Viewed

@@ -195,3 +195,145 @@
 BEST REGARDS.
+![イメージ説明](606b3e862f8144ad2723f6d6bfc5974a.png)
+変更後
+```
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+from torch.utils.data import Dataset, DataLoader
+from sklearn.model_selection import train_test_split
+import pandas as pd
+import matplotlib.pyplot as plt
+%matplotlib inline
+class Model(nn.Module):
+    def __init__(self, in_features=4, h1=8, h2=9,out_features=3):
+        super().__init__()
+        self.fc1 = nn.Linear(in_features, h1)
+        self.fc2 = nn.Linear(h1,h2)
+        self.out = nn.Linear(h2,in_features)
+    def forward(self,x):
+        x = F.relu(self.fc1(x))
+        x = F.relu(self.fc2(x))
+        x = self.out(x)
+        return x
+torch.manual_seed(32)
+model=Model()
+df = pd.read_csv('../Data/iris.csv')
+df.head()
+X = X = df.drop('target',axis=1).values
+y = df['target'].values
+X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.2,random_state=33)
+X_train = torch.FloatTensor(X_train)
+X_test = torch.FloatTensor(X_test)
+# y_train = F.one_hot(torch.LongTensor(y_train))  # not needed with Cross Entropy Loss
+# y_test = F.one_hot(torch.LongTensor(y_test))
+y_train = torch.LongTensor(y_train)
+y_test = torch.LongTensor(y_test)
+criterion = nn.CrossEntropyLoss()
+optimizer = torch.optim.Adam(model.parameters(),lr=0.01)
+model.parameters()
+epochs = 100
+lossses = []
+for i in range(epochs):
+    i+=1
+    y_pred = model.forward(X_train)
+    loss = criterion(y_test, y_pred)
+    losses.append(loss)
+    if i%10 == 1:
+        print(f'epoch: {i:2} loss:{loss.item():10.8f}')
+    optimizer.zero_grad()
+    loss.backward()
+    optimizer.step()
+```