From ac0ec7211b88444719dbeb2e2487d093946d0cce Mon Sep 17 00:00:00 2001 From: Smiril Date: Sun, 10 Jul 2022 22:41:13 +0200 Subject: [PATCH] Update m1_tf_test.py --- m1_tf_test.py | 15 +++++++++++---- 1 file changed, 11 insertions(+), 4 deletions(-) diff --git a/m1_tf_test.py b/m1_tf_test.py index 56e739e..b536111 100644 --- a/m1_tf_test.py +++ b/m1_tf_test.py @@ -10,24 +10,31 @@ import tensorflow as tf tf.__version__ tf.config.list_physical_devices() logits = [[4.0, 2.0, 1.0], [0.0, 5.0, 1.0]] +inputs = tf.keras.Input(shape=(784,), name="digits") model = tf.keras.models.load_model('model') mnist = tf.keras.datasets.mnist (x_train, y_train), (x_test, y_test) = mnist.load_data() x_train, x_test = x_train / 255.0, x_test / 255.0 model = tf.keras.models.Sequential([ tf.keras.layers.Flatten(input_shape=(28, 28)), - tf.keras.layers.Dense(128,activation='selu'), + tf.keras.layers.Dense(128,activation='selu',name='layer1'), tf.keras.layers.Dropout(0.2), - tf.keras.layers.Dense(10,activation='tanh'), + tf.keras.layers.Dense(64,activation='relu',name='layer2'), tf.keras.layers.Dropout(0.2), - tf.keras.layers.Dense(2,activation='sigmoid'), + tf.keras.layers.Dense(32,activation='elu',name='layer3'), + tf.keras.layers.Dropout(0.2), + tf.keras.layers.Dense(16,activation='tanh',name='layer4'), + tf.keras.layers.Dropout(0.2), + tf.keras.layers.Dense(8,activation='sigmoid',name='layer5'), tf.keras.layers.Dropout(0.2) ]) loss_fn = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True) model.compile(optimizer='adam', loss=loss_fn, metrics=['accuracy']) -model.fit(x_train, y_train, epochs=10) +model.fit(x_test, y_test, epochs=10) +outputs = tf.keras.layers.Dense(4, activation="softmax", name="predictions")(x_test) +model = tf.keras.Model(inputs=inputs, outputs=outputs) model.build() model.save('model') model.summary()