8ed9daf4707d86f8fe754045ae819b0961bdd290,studio/helloworld/train_mnist_keras.py,,,#,12

Before Change

from studio import fs_tracker

// this placeholder will contain our input digits, as flat vectors
img = Input((784,))
// fully-connected layer with 128 units and ReLU activation
x = Dense(128, activation="relu")(img)
x = Dense(128, activation="relu")(x)
// output layer with 10 units and a softmax activation
preds = Dense(10, activation="softmax")(x)


model = Model(img, preds)
lr = 0.01
print("learning rate = {}".format(lr))
model.compile(loss="categorical_crossentropy", optimizer=optimizers.SGD(lr=lr))

After Change

//model.add(Conv2D(64, 3, activation="relu"))
//model.add(Flatten())

model.add(Flatten(input_shape=(28,28,1)))
model.add(Dense(128, activation="relu"))
model.add(Dense(128, activation="relu"))

Instances