From 99ae1569e31cafd8d155dffd44ff38e8e8b49347 Mon Sep 17 00:00:00 2001 From: Israel Figueroa Date: Sun, 16 Mar 2025 22:36:53 -0300 Subject: [PATCH] again --- TrainerClass.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/TrainerClass.py b/TrainerClass.py index 7f349f1..de8a750 100644 --- a/TrainerClass.py +++ b/TrainerClass.py @@ -191,9 +191,9 @@ class eNoseTrainer: # maxpool 2 o 3 => 2 | 2/15 def build_model_conv1D(config, input_shape, output_dim): model = keras.Sequential([ - layers.Conv1D(filters=config['filters'], kernel_size=config['kernel_l1'], stride=config['kernel_l1']//2, activation='relu', padding='causal', input_shape=input_shape), + layers.Conv1D(filters=config['filters'], kernel_size=config['kernel_l1'], strides=config['kernel_l1']//2, activation='relu', padding='causal', input_shape=input_shape), layers.MaxPooling1D(pool_size=config['pool_size']), - layers.Conv1D(filters=config['filters'] * 2, kernel_size=config['kernel_l2'], stride=config['kernel_l2']//2, activation='relu', padding='causal'), + layers.Conv1D(filters=config['filters'] * 2, kernel_size=config['kernel_l2'], strides=config['kernel_l2']//2, activation='relu', padding='causal'), layers.MaxPooling1D(pool_size=config['pool_size']), layers.Flatten(), layers.Dense(config['dense_units'], activation='relu'),