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saved current state to various formats

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paul-loedige
2023-02-01 01:30:11 +09:00
parent f11e895caf
commit 776eff1077
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Final_Project_Loedige.ipynb
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@@ -603,6 +603,927 @@
"source": [
"tkinter.messagebox.showinfo(\"DONE\", \"DONE\")"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Save data for future use"
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},
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"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [
{
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{
"name": "stdout",
"output_type": "stream",
"text": [
"INFO:tensorflow:Assets written to: saved_models/regular Neural Network (5 hidden layers)/assets\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"INFO:tensorflow:Assets written to: saved_models/regular Neural Network (5 hidden layers)/assets\n",
"WARNING:absl:Found untraced functions such as _update_step_xla while saving (showing 1 of 1). These functions will not be directly callable after loading.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"INFO:tensorflow:Assets written to: saved_models/regular Neural Network (10 hidden layers)/assets\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"INFO:tensorflow:Assets written to: saved_models/regular Neural Network (10 hidden layers)/assets\n",
"WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _update_step_xla while saving (showing 2 of 2). These functions will not be directly callable after loading.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"INFO:tensorflow:Assets written to: saved_models/convolutional neural network (1 convolution)/assets\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"INFO:tensorflow:Assets written to: saved_models/convolutional neural network (1 convolution)/assets\n",
"WARNING:absl:Found untraced functions such as _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _update_step_xla while saving (showing 4 of 4). These functions will not be directly callable after loading.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"INFO:tensorflow:Assets written to: saved_models/convolutional neural network (3 convolutions)/assets\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"INFO:tensorflow:Assets written to: saved_models/convolutional neural network (3 convolutions)/assets\n",
"WARNING:absl:Found untraced functions such as _update_step_xla, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 14). These functions will not be directly callable after loading.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"INFO:tensorflow:Assets written to: saved_models/frozen VGG16 base model/assets\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"INFO:tensorflow:Assets written to: saved_models/frozen VGG16 base model/assets\n",
"WARNING:absl:Found untraced functions such as _update_step_xla, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 14). These functions will not be directly callable after loading.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"INFO:tensorflow:Assets written to: saved_models/fully trainable VGG16 base model/assets\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"INFO:tensorflow:Assets written to: saved_models/fully trainable VGG16 base model/assets\n",
"WARNING:absl:Found untraced functions such as _update_step_xla, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op, _jit_compiled_convolution_op while saving (showing 5 of 14). These functions will not be directly callable after loading.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"INFO:tensorflow:Assets written to: saved_models/partly trainable VGG16 base model/assets\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"INFO:tensorflow:Assets written to: saved_models/partly trainable VGG16 base model/assets\n"
]
}
],
"source": [
"# store histories with pickle\n",
"import pickle\n",
"histories = {}\n",
"for config_name, config in configs.items():\n",
" histories[config_name] = config['history']\n",
"with open('savepoint.pkl', 'wb') as out:\n",
" pickle.dump(histories, out)\n",
"\n",
"# store models with tensorflow\n",
"for config_name, config in configs.items():\n",
" config['model'].save(f'saved_models/{config_name}')\n",
"\n",
"# store models in HDF5 format\n",
"for config_name, config in configs.items():\n",
" config['model'].save(f'hdf5_models/{config_name}.h5')\n"
]
}
],
"metadata": {

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import tensorflow as tf
import tensorflow_datasets as tfds
new_model = tf.keras.models.load_model('hdf5_models/fully trainable VGG16 base model.h5')
new_model.summary()
ds_train, ds_test = tfds.load(
'svhn_cropped',
split=['train', 'test'],
shuffle_files=True,
as_supervised=True
)
loss, acc = new_model.evaluate(ds_test, verbose=2)
print('Restored model, accuracy: {:5.2f}%'.format(100 * acc))