제발 도와주세요ㅜㅠ
미해결
import numpy as np from keras.models import Sequential from keras.layers import Dense, Dropout, Flatten, LSTM from keras.layers import BatchNormalization from keras.initializers import he_normal !pip install np_utils import np_utils from tensorflow.keras.utils import to_categorical from google.colab import drive drive.mount('/content/drive') [train_x, train_y, test_x, test_y] = np.load('/content/drive/MyDrive/LSTM_disaster_prediction_data.npy', allow_pickle = True) X_train = train_x.astype('float32') X_test = test_x.astype('float32') X_train = np.transpose(X_train,(0,2,1)) X_test = np.transpose(X_test,(0,2,1)) y_train = to_categorical(train_y, num_classes=num_classes) y_test = to_categorical(test_y, num_classes=num_classes) num_classes = y_train.shape[1] model = Sequential() model.add(LSTM(units = 4, return_sequences = True, input_shape = (168, 12))) model.add(LSTM(units = 1, return_sequences= True)) model.add(BatchNormalization()) model.add(Dense(64,activation = 'relu', kernel_initializer = 'he_normal')) model.add(Dropout(0.25)) model.add(Dense(num_classes, activation = 'softmax')) model.summary() model.compile(loss = 'categorical_crossentropy', optimizer = 'adam', metrics = ['accuracy']) model.fit(X_train, y_train, epochs = 5, batch_size = 16, verbose = 1, validation_data=(X_test, y_test)) test_loss, test_accuracy = model.evaluate(X_test, y_test) print('검증결과') print('test loss = ', test_loss) print('test accuracy = ', test_accuracy) ValueError: Shapes (None, 3) and (None, 168, 3) are incompatible 이렇게 뜨는데 어떻게 고쳐야할지 모르겠어요 ㅠㅠㅠㅠㅠㅠㅠㅠㅠㅠ
- phython
- 인공지능
- 딥러닝
- 파이썬