训练好的权重文件上传

深度学习笔记/前馈神经网络/feedforward_neural_network.py

@@ -166,7 +166,7 @@ class FFNNModel():
                 param_w[l] = param_w[l] - learning_rate * dw[l]
                 param_b[l] = param_b[l] - learning_rate * db[l]
 
-            if i % 5000 == 4999:
+            if i % 500 == 499:
                 print("第{}批数据的损失率: {}".format(i + 1, cost))
                 rcost = cost
 
@@ -180,22 +180,22 @@ class FFNNModel():
 
 (train_data, train_labels), (test_data, test_labels) = imdb.load_data(path="imdb/imdb.npz",num_words=10000)
 
-x_train = train_data[:2000]
-x_test = test_data[:10]
+x_train = train_data[:25000]
+x_test = test_data[:20]
 
-y_train = train_labels[:2000]
-y_test = test_labels[:10]
+y_train = train_labels[:25000]
+y_test = test_labels[:20]
 
 model = FFNNModel(x_train, y_train, 16, 100)
-model.load()
+### model.load()
 model.train()
 
 y_pre = model.predict(x_test)
 print(y_test)
 print(y_pre)
 
-y_pre2 = model.predict(x_train[:10])
-print(y_train[:10])
+y_pre2 = model.predict(x_train[:20])
+print(y_train[:20])
 print(y_pre2)
 
 sys.exit()