From c1b69e4862f4e7241bbcd6b71dc56b9f0c1e48c7 Mon Sep 17 00:00:00 2001
From: lucas_miranda <lucasmiranda42@gmail.com>
Date: Mon, 7 Dec 2020 23:47:39 +0100
Subject: [PATCH] Added CustomStopper class to train_utils.py, to start early
stopping only after annealing is over
---
deepof/train_model.py | 33 ++++++++++++++++-----------------
deepof_experiments.smk | 4 ++--
2 files changed, 18 insertions(+), 19 deletions(-)
diff --git a/deepof/train_model.py b/deepof/train_model.py
index 4975c33e..c1ff5aca 100644
--- a/deepof/train_model.py
+++ b/deepof/train_model.py
@@ -490,7 +490,7 @@ if not tune:
history = gmvaep.fit(
x=Xs,
y=ys,
- epochs=35,
+ epochs=1,
batch_size=batch_size,
verbose=1,
validation_data=(
@@ -510,25 +510,24 @@ if not tune:
)
)
- if logparam is not None:
- # Logparams to tensorboard
- def run(run_dir, hpms):
- with tf.summary.create_file_writer(run_dir).as_default():
- hp.hparams(hpms) # record the values used in this trial
- val_mae = tf.reduce_mean(
- tf.keras.metrics.mean_absolute_error(
- X_val, gmvaep.predict(X_val)
- )
+ # Logparams to tensorboard
+ def run(run_dir, hpms):
+ with tf.summary.create_file_writer(run_dir).as_default():
+ hp.hparams(hpms) # record the values used in this trial
+ val_mae = tf.reduce_mean(
+ tf.keras.metrics.mean_absolute_error(
+ X_val, gmvaep.predict(X_val)
)
- val_mse = tf.reduce_mean(
- tf.keras.metrics.mean_squared_error(
- X_val, gmvaep.predict(X_val)
- )
+ )
+ val_mse = tf.reduce_mean(
+ tf.keras.metrics.mean_squared_error(
+ X_val, gmvaep.predict(X_val)
)
- tf.summary.scalar("val_mae", val_mae, step=1)
- tf.summary.scalar("val_mse", val_mse, step=1)
+ )
+ tf.summary.scalar("val_mae", val_mae, step=1)
+ tf.summary.scalar("val_mse", val_mse, step=1)
- run(os.path.join(output_path, "hparams", run_ID), logparam)
+ run(os.path.join(output_path, "hparams", run_ID), logparam)
# To avoid stability issues
tf.keras.backend.clear_session()
diff --git a/deepof_experiments.smk b/deepof_experiments.smk
index 80c5a744..a6aca153 100644
--- a/deepof_experiments.smk
+++ b/deepof_experiments.smk
@@ -73,8 +73,8 @@ rule explore_encoding_dimension_and_loss_function:
"--predictor 0 "
"--variational True "
"--loss {wildcards.loss} "
- "--kl-warmup 2 "
- "--mmd-warmup 2 "
+ "--kl-warmup 20 "
+ "--mmd-warmup 20 "
"--montecarlo-kl 10 "
"--encoding-size {wildcards.encs} "
"--batch-size 256 "
--
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