Scripts to execute in the GPU cluster advances #26

Makefile

@@ -20,7 +20,7 @@ ifndef CONDA
 endif
 	@echo "Creating the Conda environment if it doesn't exist..."
 	@conda env list | grep -q '^$(ENV_NAME) ' || \
-	conda create --yes --name $(ENV_NAME) python=$(PYTHON_VERSION)
+	conda create --yes --prefix $(ENV_NAME) python=$(PYTHON_VERSION)
 
 # Install packages from an environment file or manually specified
 .PHONY: install

scripts/create_configs.sh

@@ -0,0 +1,40 @@
+#!/bin/bash
+
+# Define the ranges for each parameter
+learning_rates=(0.0001 0.001 0.01)
+batch_sizes=(16 32 64)
+num_epochs=(2 5 10)
+optimizers=(Adam RMSProp SGD)
+loss_functions=(CrossEntropyLoss MeanSquaredError)
+
+# Define the config file and output directory
+config_file="config.yaml"
+output_dir="experiments"
+
+# Create the output directory if it doesn't exist
+mkdir -p "$output_dir"
+
+# Loop through each combination of parameters
+for lr in "${learning_rates[@]}"; do
+  for bs in "${batch_sizes[@]}"; do
+    for ne in "${num_epochs[@]}"; do
+      for opt in "${optimizers[@]}"; do
+        for lf in "${loss_functions[@]}"; do
+          # Create a new config file with the modified parameters
+          new_config_file="$output_dir/config_lr_${lr}_bs_${bs}_ne_${ne}_opt_${opt}_lf_${lf}.yaml"
+          cp "$config_file" "$new_config_file"
+
+          # Modify the parameters in the new config file
+          sed -i "s/learning_rate:.*/learning_rate: $lr/" "$new_config_file"
+          sed -i "s/batch_size:.*/batch_size: $bs/" "$new_config_file"
+          sed -i "s/num_epochs:.*/num_epochs: $ne/" "$new_config_file"
+          sed -i "s/optimizer:.*/optimizer:\n  type: \"$opt\"/" "$new_config_file"
+          sed -i "s/loss_function:.*/loss_function:\n  type: \"$lf\"/" "$new_config_file"
+
+          # Run the training process with the new config file
+          python train.py --config "$new_config_file"
+        done
+      done
+    done
+  done
+done

scripts/find_learning_rates.sh

@@ -0,0 +1,23 @@
+#!/bin/bash
+
+#SBATCH --job-name LR_EfficientNetB0    # Nombre del proceso
+
+#SBATCH --partition dios                # Cola para ejecutar
+
+#SBATCH --gres=gpu:1                    # Numero de gpus a usar
+
+
+
+export PATH="/opt/anaconda/anaconda3/bin:$PATH"
+
+export PATH="/opt/anaconda/bin:$PATH"
+
+eval "$(conda shell.bash hook)"
+
+conda activate /mnt/homeGPU/polivares/tda-nn-separability
+
+export TFHUB_CACHE_DIR=.
+
+python find_learning_rates.py          
+
+mail -s "Proceso finalizado" [email protected] <<< "El proceso ha finalizado"