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In TF 2.2.0-rc1, validation_data expects tuples, not lists, fixes #131

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Aurélien Geron
2020-03-31 23:09:52 +13:00
parent 7b3d280a86
commit 6adb7253b5
2 changed files with 18 additions and 18 deletions
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4
14_deep_computer_vision_with_cnns.ipynb
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@@ -592,7 +592,7 @@
"outputs": [],
"source": [
"model.compile(loss=\"sparse_categorical_crossentropy\", optimizer=\"nadam\", metrics=[\"accuracy\"])\n",
"history = model.fit(X_train, y_train, epochs=10, validation_data=[X_valid, y_valid])\n",
"history = model.fit(X_train, y_train, epochs=10, validation_data=(X_valid, y_valid))\n",
"score = model.evaluate(X_test, y_test)\n",
"X_new = X_test[:10] # pretend we have new images\n",
"y_pred = model.predict(X_new)"
@@ -1306,7 +1306,7 @@
"model.compile(loss=\"sparse_categorical_crossentropy\", optimizer=\"nadam\",\n",
" metrics=[\"accuracy\"])\n",
"\n",
"model.fit(X_train, y_train, epochs=10, validation_data=[X_valid, y_valid])\n",
"model.fit(X_train, y_train, epochs=10, validation_data=(X_valid, y_valid))\n",
"model.evaluate(X_test, y_test)"
]
},