From bfd1521e502cc58e5bd8833f02dc04583e081ccd Mon Sep 17 00:00:00 2001
From: lucas_miranda <lucasmiranda42@gmail.com>
Date: Fri, 5 Jun 2020 15:10:15 +0200
Subject: [PATCH] Implemented KL and MMD warmup on SEQ2SEQ_VAEP in models.py
---
main.ipynb | 34 +++++++++++++++++-----------------
1 file changed, 17 insertions(+), 17 deletions(-)
diff --git a/main.ipynb b/main.ipynb
index ce4168b9..ae8d2a25 100644
--- a/main.ipynb
+++ b/main.ipynb
@@ -295,7 +295,7 @@
"metadata": {},
"outputs": [],
"source": [
- "NAME = 'Baseline_VAE_short_512_10=warmup_begin'\n",
+ "NAME = 'Baseline_VAEP_short_512_10=warmup_begin'\n",
"log_dir = os.path.abspath(\n",
" \"logs/fit/{}_{}\".format(NAME, datetime.now().strftime(\"%Y%m%d-%H%M%S\"))\n",
")\n",
@@ -326,10 +326,10 @@
"metadata": {},
"outputs": [],
"source": [
- "encoder, generator, vae, kl_warmup_callback, mmd_warmup_callback = SEQ_2_SEQ_VAE(pttest.shape,\n",
- " loss='ELBO+MMD',\n",
- " kl_warmup_epochs=10,\n",
- " mmd_warmup_epochs=10).build()"
+ "# encoder, generator, vae, kl_warmup_callback, mmd_warmup_callback = SEQ_2_SEQ_VAE(pttest.shape,\n",
+ "# loss='ELBO+MMD',\n",
+ "# kl_warmup_epochs=10,\n",
+ "# mmd_warmup_epochs=10).build()"
]
},
{
@@ -338,10 +338,10 @@
"metadata": {},
"outputs": [],
"source": [
- "# encoder, generator, vaep, kl_warmup_callback, mmd_warmup_callback = SEQ_2_SEQ_VAEP(pttest.shape,\n",
- "# loss='ELBO+MMD',\n",
- "# kl_warmup_epochs=10,\n",
- "# mmd_warmup_epochs=10).build()"
+ "encoder, generator, vaep, kl_warmup_callback, mmd_warmup_callback = SEQ_2_SEQ_VAEP(pttest.shape,\n",
+ " loss='ELBO+MMD',\n",
+ " kl_warmup_epochs=10,\n",
+ " mmd_warmup_epochs=10).build()"
]
},
{
@@ -405,10 +405,10 @@
"metadata": {},
"outputs": [],
"source": [
- "tf.config.experimental_run_functions_eagerly(False)\n",
- "history = vae.fit(x=pttrain[:-1], y=pttrain[:-1], epochs=500, batch_size=512, verbose=1,\n",
- " validation_data=(pttest[:-1], pttest[:-1]),\n",
- " callbacks=[tensorboard_callback, kl_warmup_callback, mmd_warmup_callback])"
+ "# tf.config.experimental_run_functions_eagerly(False)\n",
+ "# history = vae.fit(x=pttrain[:-1], y=pttrain[:-1], epochs=500, batch_size=512, verbose=1,\n",
+ "# validation_data=(pttest[:-1], pttest[:-1]),\n",
+ "# callbacks=[tensorboard_callback, kl_warmup_callback, mmd_warmup_callback])"
]
},
{
@@ -419,10 +419,10 @@
},
"outputs": [],
"source": [
- "# tf.config.experimental_run_functions_eagerly(False)\n",
- "# history = vaep.fit(x=pttrain[:-1], y=[pttrain[:-1],pttrain[1:]], epochs=500, batch_size=512, verbose=1,\n",
- "# validation_data=(pttest[:-1], [pttest[:-1],pttest[1:]]),\n",
- "# callbacks=[tensorboard_callback])"
+ "tf.config.experimental_run_functions_eagerly(False)\n",
+ "history = vaep.fit(x=pttrain[:-1], y=[pttrain[:-1],pttrain[1:]], epochs=500, batch_size=512, verbose=1,\n",
+ " validation_data=(pttest[:-1], [pttest[:-1],pttest[1:]]),\n",
+ " callbacks=[tensorboard_callback])"
]
}
],
--
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