質問編集履歴
4
タイトル修正
test
CHANGED
|
@@ -1 +1 @@
|
|
|
1
|
-
kerasを使用してtensorboard上にe
|
|
1
|
+
kerasを使用してtensorboard上にembedding visualizationのエラーについて
|
test
CHANGED
|
File without changes
|
3
プログラム編集
test
CHANGED
|
File without changes
|
test
CHANGED
|
@@ -82,7 +82,7 @@
|
|
|
82
82
|
|
|
83
83
|
|
|
84
84
|
|
|
85
|
-
logdir="/Users/
|
|
85
|
+
logdir="/Users/name/Dropbox/python/"
|
|
86
86
|
|
|
87
87
|
|
|
88
88
|
|
2
stackoverflowのコードを試してみました
test
CHANGED
|
File without changes
|
test
CHANGED
|
@@ -61,3 +61,139 @@
|
|
|
61
61
|
何度か試してみてはいるのですが、model.fitの時点でエラーが出てしまいます。
|
|
62
62
|
|
|
63
63
|
間違いなどがあれば教えていただけますと幸いです。よろしくお願いいたします。
|
|
64
|
+
|
|
65
|
+
|
|
66
|
+
|
|
67
|
+
|
|
68
|
+
|
|
69
|
+
#stackoverflowで教えていただいた手法の追記
|
|
70
|
+
|
|
71
|
+
```python
|
|
72
|
+
|
|
73
|
+
import keras
|
|
74
|
+
|
|
75
|
+
from keras.datasets import mnist
|
|
76
|
+
|
|
77
|
+
from keras.models import Sequential
|
|
78
|
+
|
|
79
|
+
from keras.layers import Dense, Dropout
|
|
80
|
+
|
|
81
|
+
from keras import callbacks
|
|
82
|
+
|
|
83
|
+
|
|
84
|
+
|
|
85
|
+
logdir="/Users/kayanoyohei/Dropbox/python/"
|
|
86
|
+
|
|
87
|
+
|
|
88
|
+
|
|
89
|
+
batch_size = 100
|
|
90
|
+
|
|
91
|
+
num_classes = 10
|
|
92
|
+
|
|
93
|
+
epochs = 20
|
|
94
|
+
|
|
95
|
+
|
|
96
|
+
|
|
97
|
+
|
|
98
|
+
|
|
99
|
+
# the data, shuffled and split between train and test sets
|
|
100
|
+
|
|
101
|
+
(x_train, y_train), (x_test, y_test) = mnist.load_data()
|
|
102
|
+
|
|
103
|
+
|
|
104
|
+
|
|
105
|
+
x_train = x_train.reshape(60000, 784)
|
|
106
|
+
|
|
107
|
+
x_test = x_test.reshape(10000, 784)
|
|
108
|
+
|
|
109
|
+
x_train = x_train.astype('float32')
|
|
110
|
+
|
|
111
|
+
x_test = x_test.astype('float32')
|
|
112
|
+
|
|
113
|
+
x_train /= 255
|
|
114
|
+
|
|
115
|
+
x_test /= 255
|
|
116
|
+
|
|
117
|
+
print(x_train.shape[0], 'train samples')
|
|
118
|
+
|
|
119
|
+
print(x_test.shape[0], 'test samples')
|
|
120
|
+
|
|
121
|
+
|
|
122
|
+
|
|
123
|
+
# convert class vectors to binary class matrices
|
|
124
|
+
|
|
125
|
+
y_train = keras.utils.to_categorical(y_train, num_classes)
|
|
126
|
+
|
|
127
|
+
y_test = keras.utils.to_categorical(y_test, num_classes)
|
|
128
|
+
|
|
129
|
+
|
|
130
|
+
|
|
131
|
+
model = Sequential()
|
|
132
|
+
|
|
133
|
+
model.add(Dense(200, activation='relu', input_shape=(784,)))
|
|
134
|
+
|
|
135
|
+
model.add(Dropout(0.2))
|
|
136
|
+
|
|
137
|
+
model.add(Dense(100, activation='relu'))
|
|
138
|
+
|
|
139
|
+
model.add(Dropout(0.2))
|
|
140
|
+
|
|
141
|
+
model.add(Dense(60, activation='relu'))
|
|
142
|
+
|
|
143
|
+
model.add(Dropout(0.2))
|
|
144
|
+
|
|
145
|
+
model.add(Dense(30, activation='relu'))
|
|
146
|
+
|
|
147
|
+
model.add(Dropout(0.2))
|
|
148
|
+
|
|
149
|
+
model.add(Dense(10, activation='softmax'))
|
|
150
|
+
|
|
151
|
+
embedding_layer_names = set(layer.name
|
|
152
|
+
|
|
153
|
+
for layer in model.layers
|
|
154
|
+
|
|
155
|
+
if layer.name.startswith('dense_'))
|
|
156
|
+
|
|
157
|
+
tb = callbacks.TensorBoard(log_dir=log_dir, histogram_freq=10, batch_size=32,write_graph=True, write_grads=True, write_images=True,embeddings_freq=10, embeddings_metadata=None,
|
|
158
|
+
|
|
159
|
+
embeddings_layer_names=embedding_layer_names)
|
|
160
|
+
|
|
161
|
+
|
|
162
|
+
|
|
163
|
+
model.compile(loss='categorical_crossentropy',
|
|
164
|
+
|
|
165
|
+
optimizer='adam',
|
|
166
|
+
|
|
167
|
+
metrics=['accuracy'])
|
|
168
|
+
|
|
169
|
+
history = model.fit(x_train, y_train,
|
|
170
|
+
|
|
171
|
+
callbacks=[tb,early_stop],
|
|
172
|
+
|
|
173
|
+
batch_size=batch_size,
|
|
174
|
+
|
|
175
|
+
epochs=epochs,
|
|
176
|
+
|
|
177
|
+
verbose=1,
|
|
178
|
+
|
|
179
|
+
validation_data=(x_test, y_test))
|
|
180
|
+
|
|
181
|
+
score = model.evaluate(x_test, y_test, verbose=0)
|
|
182
|
+
|
|
183
|
+
print('Test loss:', score[0])
|
|
184
|
+
|
|
185
|
+
print('Test accuracy:', score[1])
|
|
186
|
+
|
|
187
|
+
コード
|
|
188
|
+
|
|
189
|
+
```
|
|
190
|
+
|
|
191
|
+
上記サイトに記載されているコードを試したのですが、
|
|
192
|
+
|
|
193
|
+
To visualize embeddings, embeddings_data must be provided.
|
|
194
|
+
|
|
195
|
+
|
|
196
|
+
|
|
197
|
+
model.fitは進行するのですが、上記のエラーが最後に出力されます。
|
|
198
|
+
|
|
199
|
+
embeddings_data=None,[]などで定義したとしても上記のエラーがでてしまいます。すみませんが、embeddings_dataを与えておくということはどういうことなのでしょうか。
|
1
タイトルを修正しました。
test
CHANGED
|
@@ -1 +1 @@
|
|
|
1
|
-
keras
|
|
1
|
+
kerasを使用してtensorboard上にenbedding visualizationの表示は可能でしょうか?
|
test
CHANGED
|
File without changes
|