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beta-vae-normalizing-flows
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Kaan Güney Keklikçi
beta-vae-normalizing-flows
Commits
dd1525fc
Commit
dd1525fc
authored
Aug 08, 2021
by
Kaan Güney Keklikçi
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inverse autoregressive flow MLE, maf execution modified
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d9ce121b
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iaf_execute.ipynb
notebooks/iaf_execute.ipynb
+218
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maf_execute.ipynb
notebooks/maf_execute.ipynb
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notebooks/iaf_execute.ipynb
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dd1525fc
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"import os \n",
"os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' \n",
"import numpy as np\n",
"from sklearn.preprocessing import StandardScaler\n",
"\n",
"import tensorflow as tf\n",
"tf.compat.v1.disable_eager_execution() \n",
"import tensorflow_probability as tfp\n",
"\n",
"import matplotlib.pyplot as plt\n",
"plt.style.use('seaborn')\n",
"\n",
"from data_loader import load_data\n",
"from data_preprocesser import preprocess_data\n",
"from maf import IAF"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Data successfully loaded...\n",
"\n",
"Data successfully preprocessed...\n",
"\n",
"TensorFlow version: 2.5.0\n",
"Number of dimensions: 37\n",
"Learning rate: 0.0001\n",
"\n",
"Successfully created model...\n",
"\n",
"Optimizer and loss successfully defined...\n",
"\n",
"Iteration 0: 60.449180603027344\n",
"Iteration 10000: 32.882728576660156\n",
"Iteration 20000: 26.221080780029297\n",
"Iteration 30000: 23.287174224853516\n",
"Iteration 40000: 22.44567108154297\n",
"Iteration 50000: 17.521474838256836\n",
"Iteration 60000: 22.41493797302246\n",
"Iteration 70000: 24.137344360351562\n",
"Iteration 80000: 14.954710006713867\n",
"Iteration 90000: 21.243478775024414\n",
"Training finished...\n",
"\n",
"Displaying results...\n"
]
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"def train(session, loss, optimizer, steps=int(1e5)):\n",
" \n",
" \"\"\" optimize for all dimensions \"\"\"\n",
" \n",
" recorded_steps = []\n",
" recorded_losses = []\n",
" for i in range(steps):\n",
" _, loss_per_iteration = session.run([optimizer, loss])\n",
" if i % 100 == 0:\n",
" recorded_steps.append(i)\n",
" recorded_losses.append(loss_per_iteration)\n",
" if i % int(1e4) == 0:\n",
" print('Iteration {iteration}: {loss}'.format(iteration=i,loss=loss_per_iteration))\n",
" return recorded_losses\n",
"\n",
"def plot_results(recorded_losses):\n",
" \n",
" \"\"\" plot loss \"\"\"\n",
" print('Displaying results...')\n",
" fig = plt.figure(figsize=(10,5))\n",
" x = np.arange(len(recorded_losses))\n",
" y = recorded_losses\n",
" m, b = np.polyfit(x, y, 1) \n",
" plt.scatter(x, y, s=10, alpha=0.3)\n",
" plt.plot(x, m*x+b, c=\"r\")\n",
" plt.title('Loss per 100 iteration')\n",
" plt.xlabel('Iteration')\n",
" plt.ylabel('Loss')\n",
" plt.tight_layout()\n",
" plt.show()\n",
"\n",
"def main():\n",
" \n",
" \"\"\" load data \"\"\"\n",
"\n",
" filename = 'prostate.xls'\n",
" directory = '/Users/kaanguney.keklikci/Data/'\n",
"\n",
" loader = load_data(filename, directory)\n",
" loader.create_directory(directory)\n",
" data = loader.read_data(directory, filename)\n",
" print('Data successfully loaded...\\n')\n",
" \n",
" \"\"\" preprocess data \"\"\"\n",
"\n",
" fillna_vals = ['sz', 'sg', 'wt']\n",
" dropna_vals = ['ekg', 'age']\n",
" drop_vals = ['patno', 'sdate']\n",
"\n",
" preprocesser = preprocess_data(StandardScaler(), fillna_vals, dropna_vals, drop_vals)\n",
" data = preprocesser.dropna_features(data)\n",
" data = preprocesser.impute(data)\n",
" data = preprocesser.drop_features(data)\n",
" data = preprocesser.encode_categorical(data)\n",
" data = preprocesser.scale(data)\n",
" print('Data successfully preprocessed...\\n')\n",
" \n",
" \"\"\" set MAF parameters \"\"\"\n",
"\n",
" batch_size = 32\n",
" dtype = np.float32\n",
" tf_version = tf.__version__\n",
" params = 2\n",
" hidden_units = [5,5]\n",
" base_dist = tfp.distributions.Normal(loc=0., scale=1.)\n",
" dims = data.shape[1]\n",
" learning_rate = 1e-4\n",
" activation = 'relu'\n",
" hidden_degrees = 'random'\n",
" conditional=True\n",
" conditional_event_shape = (dims,)\n",
" event_shape = conditional_event_shape\n",
" conditional_input_layers = 'first_layer'\n",
" \n",
" \"\"\" initialize samples \"\"\"\n",
"\n",
" iaf = IAF(dtype, tf_version, batch_size, \n",
" params, hidden_units, base_dist, dims,\n",
" activation,\n",
" conditional, hidden_degrees, \n",
" conditional_event_shape,\n",
" conditional_input_layers,\n",
" event_shape\n",
" )\n",
"\n",
" dims = iaf.get_dims(data)\n",
" samples = iaf.create_tensor(data)\n",
" print(f'TensorFlow version: {iaf.tf_version}')\n",
" print(f'Number of dimensions: {iaf.dims}')\n",
" print(f'Learning rate: {learning_rate}\\n')\n",
" \n",
" \"\"\" initialize iaf \"\"\"\n",
"\n",
" iaf = iaf.make_maf(data)\n",
" print('Successfully created model...\\n')\n",
" \n",
" \"\"\" initialize loss and optimizer \"\"\"\n",
"\n",
" loss = -tf.reduce_mean(iaf.log_prob(samples, bijector_kwargs={'conditional_input': samples}))\n",
" optimizer = tf.compat.v1.train.AdamOptimizer(learning_rate).minimize(loss)\n",
"\n",
" session = tf.compat.v1.Session()\n",
" tf.compat.v1.set_random_seed(42)\n",
" session.run(tf.compat.v1.global_variables_initializer())\n",
" print('Optimizer and loss successfully defined...\\n')\n",
" \n",
" \"\"\" start training \"\"\"\n",
" recorded_losses = train(session, loss, optimizer)\n",
" print('Training finished...\\n')\n",
" \n",
" \"\"\" display results \"\"\"\n",
" plot_results(recorded_losses)\n",
" \n",
" \n",
"if __name__ == \"__main__\":\n",
" main()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.10"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
notebooks/maf_execute.ipynb
View file @
dd1525fc
...
@@ -2,7 +2,7 @@
...
@@ -2,7 +2,7 @@
"cells": [
"cells": [
{
{
"cell_type": "code",
"cell_type": "code",
"execution_count":
3
,
"execution_count":
1
,
"metadata": {
"metadata": {
"scrolled": true
"scrolled": true
},
},
...
@@ -18,6 +18,7 @@
...
@@ -18,6 +18,7 @@
"import tensorflow_probability as tfp\n",
"import tensorflow_probability as tfp\n",
"\n",
"\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib.pyplot as plt\n",
"plt.style.use('seaborn')\n",
"\n",
"\n",
"from data_loader import load_data\n",
"from data_loader import load_data\n",
"from data_preprocesser import preprocess_data\n",
"from data_preprocesser import preprocess_data\n",
...
@@ -47,16 +48,16 @@
...
@@ -47,16 +48,16 @@
"\n",
"\n",
"Optimizer and loss successfully defined...\n",
"Optimizer and loss successfully defined...\n",
"\n",
"\n",
"Iteration 0: 5
2.72296142578125
\n",
"Iteration 0: 5
1.908042907714844
\n",
"Iteration 10000: -
12.12372779846191
4\n",
"Iteration 10000: -
66.4150009155273
4\n",
"Iteration 20000: -
31.257366180419922
\n",
"Iteration 20000: -
85.92218017578125
\n",
"Iteration 30000: -
19.52370834350586
\n",
"Iteration 30000: -
86.00814819335938
\n",
"Iteration 40000: -
34.72262954711914
\n",
"Iteration 40000: -
95.52314758300781
\n",
"Iteration 50000: -
37.22956085205078
\n",
"Iteration 50000: -
100.09404754638672
\n",
"Iteration 60000: -
31.837202072143555
\n",
"Iteration 60000: -
101.45828247070312
\n",
"Iteration 70000: -
36.162353515625
\n",
"Iteration 70000: -
109.66394805908203
\n",
"Iteration 80000: -
40.44646453857422
\n",
"Iteration 80000: -
117.25852966308594
\n",
"Iteration 90000: -
39.50082015991211
\n",
"Iteration 90000: -
108.93268585205078
\n",
"Training finished...\n",
"Training finished...\n",
"\n",
"\n",
"Displaying results...\n"
"Displaying results...\n"
...
@@ -64,7 +65,7 @@
...
@@ -64,7 +65,7 @@
},
},
{
{
"data": {
"data": {
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
\n",
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
\n",
"text/plain": [
"text/plain": [
"<Figure size 720x360 with 1 Axes>"
"<Figure size 720x360 with 1 Axes>"
]
]
...
@@ -89,7 +90,6 @@
...
@@ -89,7 +90,6 @@
" print('Iteration {iteration}: {loss}'.format(iteration=i,loss=loss_per_iteration))\n",
" print('Iteration {iteration}: {loss}'.format(iteration=i,loss=loss_per_iteration))\n",
" return recorded_losses\n",
" return recorded_losses\n",
"\n",
"\n",
"\n",
"def plot_results(recorded_losses):\n",
"def plot_results(recorded_losses):\n",
" \n",
" \n",
" \"\"\" plot loss \"\"\"\n",
" \"\"\" plot loss \"\"\"\n",
...
@@ -142,10 +142,23 @@
...
@@ -142,10 +142,23 @@
" base_dist = tfp.distributions.Normal(loc=0., scale=1.)\n",
" base_dist = tfp.distributions.Normal(loc=0., scale=1.)\n",
" dims = data.shape[1]\n",
" dims = data.shape[1]\n",
" learning_rate = 1e-4\n",
" learning_rate = 1e-4\n",
" activation = 'relu'\n",
" hidden_degrees = 'random'\n",
" conditional=True\n",
" conditional_event_shape = (dims,)\n",
" event_shape = conditional_event_shape\n",
" conditional_input_layers = 'first_layer'\n",
" \n",
" \n",
" \"\"\" initialize samples \"\"\"\n",
" \"\"\" initialize samples \"\"\"\n",
"\n",
"\n",
" maf = MAF(dtype, tf_version, batch_size, params, hidden_units, base_dist, dims)\n",
" maf = MAF(dtype, tf_version, batch_size, \n",
" params, hidden_units, base_dist, dims,\n",
" activation,\n",
" conditional, hidden_degrees, \n",
" conditional_event_shape,\n",
" conditional_input_layers,\n",
" event_shape\n",
" )\n",
"\n",
"\n",
" dims = maf.get_dims(data)\n",
" dims = maf.get_dims(data)\n",
" samples = maf.create_tensor(data)\n",
" samples = maf.create_tensor(data)\n",
...
@@ -160,7 +173,7 @@
...
@@ -160,7 +173,7 @@
" \n",
" \n",
" \"\"\" initialize loss and optimizer \"\"\"\n",
" \"\"\" initialize loss and optimizer \"\"\"\n",
"\n",
"\n",
" loss = -tf.reduce_mean(maf.log_prob(samples))\n",
" loss = -tf.reduce_mean(maf.log_prob(samples
, bijector_kwargs={'conditional_input': samples}
))\n",
" optimizer = tf.compat.v1.train.AdamOptimizer(learning_rate).minimize(loss)\n",
" optimizer = tf.compat.v1.train.AdamOptimizer(learning_rate).minimize(loss)\n",
"\n",
"\n",
" session = tf.compat.v1.Session()\n",
" session = tf.compat.v1.Session()\n",
...
@@ -179,6 +192,13 @@
...
@@ -179,6 +192,13 @@
"if __name__ == \"__main__\":\n",
"if __name__ == \"__main__\":\n",
" main()"
" main()"
]
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
}
],
],
"metadata": {
"metadata": {
...
...
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