From ac2a7ecc64bc365ca9cf4390dfb5b6a9060e0431 Mon Sep 17 00:00:00 2001
From: Tamino Huxohl <thuxohl@techfak.uni-bielefeld.de>
Date: Fri, 6 Jan 2023 12:15:01 +0100
Subject: [PATCH] fixes to random search
---
mu_map/training/random_search.py | 8 +++++---
1 file changed, 5 insertions(+), 3 deletions(-)
diff --git a/mu_map/training/random_search.py b/mu_map/training/random_search.py
index 0b08c60..aa39d4d 100644
--- a/mu_map/training/random_search.py
+++ b/mu_map/training/random_search.py
@@ -276,14 +276,16 @@ class RandomSearchCGAN(RandomSearch):
return [[32, 64, 128, 256], [64, 128, 256, 512]]
self.param_sampler["discriminator_conv_features"] = DependentChoiceSampler(discriminator_conv_features)
self.param_sampler["generator_features"] = ChoiceSampler([
- [128, 256, 512],
[64, 128, 256, 512],
[32, 64, 128, 256, 512],
])
# training parameters
self.param_sampler["epochs"] = ChoiceSampler([50, 60, 70, 80, 90])
- self.param_sampler["batch_size"] = ChoiceSampler([32, 64])
+ def batch_size(patch_size: int, **kwargs):
+ return [32] if patch_size == 64 else [64]
+ # self.param_sampler["batch_size"] = ChoiceSampler([32, 64])
+ self.param_sampler["batch_size"] = DependentChoiceSampler(batch_size)
self.param_sampler["lr"] = FloatIntervalSampler(0.1, 0.0001)
self.param_sampler["lr_decay"] = ChoiceSampler([False, True])
self.param_sampler["lr_decay_epoch"] = ChoiceSampler([1])
@@ -393,7 +395,7 @@ class RandomSearchCGAN(RandomSearch):
)
self.logger.debug(f"Init discriminator ....")
- input_size = (2, self.n_slices, self.params["patch_size"], self.params["patch_size"])
+ input_size = (self.n_slices, self.params["patch_size"], self.params["patch_size"])
if self.params["discriminator_type"] == "class":
discriminator = Discriminator(
in_channels=2, input_size=input_size, conv_features=self.params["discriminator_conv_features"],
--
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