From 511187ba16bb3ea32e60d6d90503e13c2d901217 Mon Sep 17 00:00:00 2001 From: Malte Grosse Date: Thu, 30 Nov 2023 10:04:15 +0900 Subject: [PATCH] gpu --- .woodpecker.yml | 4 ++-- run.py | 26 ++++++++++++-------------- 2 files changed, 14 insertions(+), 16 deletions(-) diff --git a/.woodpecker.yml b/.woodpecker.yml index bdaecb0..578fcc7 100644 --- a/.woodpecker.yml +++ b/.woodpecker.yml @@ -1,8 +1,8 @@ steps: - "caffe": + "train": image: nvcr.io/nvidia/tensorflow:23.10-tf2-py3 commands: - - echo "ci working................b. " + - echo "starting python script" - python run.py diff --git a/run.py b/run.py index 611bce4..cff39c4 100644 --- a/run.py +++ b/run.py @@ -46,18 +46,6 @@ y_test_categorical = keras.utils.to_categorical( print("model build") -model = keras.Sequential([ - keras.layers.Flatten(input_shape=(32,32,3)), - keras.layers.Dense(300, activation='relu'), - keras.layers.Dense(100, activation='relu'), - keras.layers.Dense(10, activation='sigmoid') - ]) - -model.compile(optimizer='SGD', - loss='categorical_crossentropy', - metrics=['accuracy']) - -model.fit(X_train_scaled, y_train_categorical, epochs=1) def get_model(): model = keras.Sequential([ @@ -73,7 +61,17 @@ def get_model(): return model with tf.device('/GPU:0'): - cpu_model = get_model() - cpu_model.fit(X_train_scaled, y_train_categorical, epochs=10) + model = keras.Sequential([ + keras.layers.Flatten(input_shape=(32,32,3)), + keras.layers.Dense(3000, activation='relu'), + keras.layers.Dense(1000, activation='relu'), + keras.layers.Dense(10, activation='sigmoid') + ]) + + model.compile(optimizer='SGD', + loss='categorical_crossentropy', + metrics=['accuracy']) + model.fit(X_train_scaled, y_train_categorical, epochs=10) + model.save('mymodel.keras') print("done") \ No newline at end of file