diff --git a/experiments/fmnist.jl b/experiments/fmnist.jl index ccdb1c39fef497e9d17f8c7acda5a1bbe896db3c..d911473b32e77dcadda7e4a908c1fd57151bd516 100644 --- a/experiments/fmnist.jl +++ b/experiments/fmnist.jl @@ -16,7 +16,7 @@ test_data = load_fashion_mnist_test() model_tuning_params = DEFAULT_MODEL_TUNING_LARGE # Tuning parameters: -tuning_params = DEFAULT_GENERATOR_TUNING +tuning_params = DEFAULT_GENERATOR_TUNING[2:end] push!(tuning_params.Λ, [0.1, 0.1, 3.0]) # Additional models: diff --git a/experiments/jobscripts/tuning/generators/fmnist.sh b/experiments/jobscripts/tuning/generators/fmnist.sh index 8b19a5a0744c3091ae384faa6da6a953216aed0b..d8aefd4009829093295769ed999f8b6a82aae9bf 100644 --- a/experiments/jobscripts/tuning/generators/fmnist.sh +++ b/experiments/jobscripts/tuning/generators/fmnist.sh @@ -1,8 +1,8 @@ #!/bin/bash #SBATCH --job-name="Grid-search Fashion MNIST (ECCCo)" -#SBATCH --time=24:00:00 -#SBATCH --ntasks=2400 +#SBATCH --time=32:00:00 +#SBATCH --ntasks=1000 #SBATCH --cpus-per-task=1 #SBATCH --partition=compute #SBATCH --mem-per-cpu=8GB diff --git a/experiments/jobscripts/tuning/generators/mnist.sh b/experiments/jobscripts/tuning/generators/mnist.sh index 4b37cd40861965fbddf3925647082237c4a4ad69..8e1ea4fc3d3e7efa548970cb5c244060d6fd9c09 100644 --- a/experiments/jobscripts/tuning/generators/mnist.sh +++ b/experiments/jobscripts/tuning/generators/mnist.sh @@ -1,8 +1,8 @@ #!/bin/bash #SBATCH --job-name="Grid-search MNIST (ECCCo)" -#SBATCH --time=24:00:00 -#SBATCH --ntasks=2400 +#SBATCH --time=32:00:00 +#SBATCH --ntasks=1000 #SBATCH --cpus-per-task=1 #SBATCH --partition=compute #SBATCH --mem-per-cpu=8GB diff --git a/experiments/mnist.jl b/experiments/mnist.jl index 695fb6206580e159383fb5cfc2f6050223c33f31..388af47d89bb7bce981f6334162eecfcd4c7d890 100644 --- a/experiments/mnist.jl +++ b/experiments/mnist.jl @@ -16,7 +16,7 @@ test_data = load_mnist_test() model_tuning_params = DEFAULT_MODEL_TUNING_LARGE # Tuning parameters: -tuning_params = DEFAULT_GENERATOR_TUNING +tuning_params = DEFAULT_GENERATOR_TUNING[2:end] push!(tuning_params.Λ, [0.1, 0.1, 3.0]) # Additional models: