Python main Examples

Example #1

File: 2_epses_gpu=0.py Project: yishiliuhuasheng/dctn

main.main(
    (
        "--ds-type",
        "cifar10_28x28_grayscale",
        "--ds-path",
        "/mnt/hdd_1tb/datasets/cifar10",
        "--batch-size",
        "128",
        "--optimizer",
        "adam",
        "--experiments-dir",
        "/mnt/important/experiments/cifar10/28x28_grayscale/2_epses",
        "--epses-specs",
        "(4,4),(3,6)",
        "--lr",
        "1.5e-4",
        "--reg-type",
        "epses_composition",
        "--reg-coeff",
        "0.",
        "--phi-multiplier",
        "1.19",
        "--init-eps-zero-centered-normal-std",
        "0",
        "3.9069653e-3",
        "--init-eps-zero-centered-normal-std",
        "1",
        "1.9525534e-3",
        "--init-linear-weight-zero-centered-uniform",
        "0.01774992567234187",
        "--init-linear-bias-zero-centered-uniform",
        "0.01774992567234187",
    ),
    standalone_mode=False,
)

Example #2

main.main(
    (
        # seed is specific to this file only
        "--seed",
        "1",
        # settings which are basically the same for all experiments
        "--ds-type",
        "fashionmnist",
        "--ds-path",
        "/mnt/hdd_1tb/datasets/fashionmnist",
        "--batch-size",
        "128",
        "--optimizer",
        "adam",
        # settings introduced earlier which are unique to this experiment
        "--experiments-dir",
        "/mnt/important/experiments/eps_plus_linear_fashionmnist/replicate_90.19_vacc",
        "--epses-specs",
        "(4,4)",
        "--lr",
        "3e-3",
        "--reg-type",
        "epses_composition",
        "--reg-coeff",
        "0.",
        # super duper new settings which might bug out
        "--phi-multiplier",
        "0.5",
        "--init-epses-zero-centered-normal",
        "0.25",
        "--init-linear-weight-zero-centered-uniform",
        "0.02",
        "--init-linear-bias-zero-centered-uniform",
        "0.02",
    ),
    standalone_mode=False,
)

Example #3

main.main(
    (
        "--ds-type",
        "fashionmnist",
        "--ds-path",
        "/mnt/hdd_1tb/datasets/fashionmnist",
        "--batch-size",
        "128",
        "--optimizer",
        "adam",
        "--experiments-dir",
        "/mnt/important/experiments/2_epses_plus_linear_fashionmnist/2020-05-18_fashionmnist_check_if_scaling_down_phi_helps_v2.0",
        "--epses-specs",
        "(4,4),(3,6)",
        "--lr",
        "1.5e-4",
        "--reg-type",
        "epses_composition",
        "--reg-coeff",
        "1e-2",
        "--phi-multiplier",
        "1.3",  # 1.3 is too small, it just doesn't train
        "--init-eps-zero-centered-normal-std",
        "0",
        "5.885948427021503448486328125000e-03",
        "--init-eps-zero-centered-normal-std",
        "1",
        "2.112586298608221113681793212891e-05",
        "--init-linear-weight-zero-centered-normal-std",
        "4.437481418085467352319106737468e-03",
        "--init-linear-bias-zero-centered-uniform",
        "1.77499256723418694092764269498729845508933067321777343750e-02",
    ),
    standalone_mode=False,
)

Example #4

File: two_epses_plus_linear_composition_reg_higher_coeff.py Project: yishiliuhuasheng/dctn

from new_runner import main

# copies /mnt/important/experiments/2_epses_plus_linear_fashionmnist/2020-04-15T19:42:03/
# but with epswise l2 regularization
main.main(
    (
        "--experiments-dir",
        "/mnt/important/experiments/2_epses_plus_linear_fashionmnist/adam_and_comp_reg",
        "--ds-type",
        "fashionmnist",
        "--ds-path",
        "/mnt/hdd_1tb/datasets/fashionmnist",
        "--epses-specs",
        "(4,4),(3,6)",
        "--batch-size",
        "128",
        "--optimizer",
        "adam",
        "--lr",
        "1.11e-4",
        "--reg-type",
        "epses_composition",
        "--reg-coeff",
        "1e-3",
        "--no-es-train-acc",
        "--no-es-train-mean-ce",
    ),
    standalone_mode=False,
)

Example #5

File: blah_new_runner.py Project: yishiliuhuasheng/dctn

from new_runner import main

main.main(
    (
        "--experiments-dir",
        "/tmp/new_runner_test/",
        "--ds-type",
        "fashionmnist",
        "--ds-path",
        "/mnt/hdd_1tb/datasets/fashionmnist",
        "--kernel-size",
        "4",
        "--out-size",
        "6",
        "--batch-size",
        "128",
        "--optimizer",
        "adam",
        "--lr",
        "1e-3",
    ),
    standalone_mode=False,
)

Example #6

File: old_scaling_experiment_with_new_runner.py Project: yishiliuhuasheng/dctn

from os import environ

environ["CUDA_VISIBLE_DEVICES"] = "1"

from new_runner import main

main.main(
    (
        "--experiments-dir",
        "/mnt/important/experiments/eps_plus_linear_fashionmnist",
        "--ds-type",
        "fashionmnist",
        "--ds-path",
        "/mnt/hdd_1tb/datasets/fashionmnist",
        "--kernel-size",
        "4",
        "--out-size",
        "4",
        "--batch-size",
        "128",
        "--optimizer",
        "adam",
        "--lr",
        "0.003",
        "--old-scaling",
    ),
    standalone_mode=False,
)

Example #7

File: 01_determine_epses_stds_from_theoretical_init.py Project: yishiliuhuasheng/dctn

from os import environ

environ["CUDA_VISIBLE_DEVICES"] = "0"

from new_runner import main

main.main(
    (
        "--ds-type",
        "cifar10_32x32_grayscale",
        "--ds-path",
        "/mnt/hdd_1tb/datasets/cifar10",
        "--batch-size",
        "128",
        "--optimizer",
        "adam",
        "--experiments-dir",
        "/mnt/important/experiments/cifar10/32x32_grayscale/2_epses",
        "--epses-specs",
        "(4,4),(3,6)",
        "--lr",
        "1.5e-4",
        "--reg-type",
        "epses_composition",
        "--reg-coeff",
        "0.",
        "--init-epses-composition-unit-theoretical-output-std",
    ),
    standalone_mode=False,
)

Example #8

from new_runner import main

# copies /mnt/important/experiments/2_epses_plus_linear_fashionmnist/2020-04-15T19:42:03/
# but with epswise l2 regularization
main.main(
    (
        "--experiments-dir",
        "/mnt/important/experiments/2_epses_plus_linear_fashionmnist/adam_and_epswise_l2",
        "--ds-type",
        "fashionmnist",
        "--ds-path",
        "/mnt/hdd_1tb/datasets/fashionmnist",
        "--epses-specs",
        "(4,4),(3,6)",
        "--batch-size",
        "128",
        "--optimizer",
        "adam",
        "--lr",
        "1.11e-4",
        "--reg-coeff",
        "1e-2",
    ),
    standalone_mode=False,
)

Example #9

from os import environ

environ["CUDA_VISIBLE_DEVICES"] = "0"

from new_runner import main

main.main(
    (
        "--ds-type",
        "fashionmnist",
        "--ds-path",
        "/mnt/hdd_1tb/datasets/fashionmnist",
        "--batch-size",
        "128",
        "--optimizer",
        "adam",
        "--experiments-dir",
        "/mnt/important/experiments/2_epses_plus_linear_fashionmnist/2020-05-18_fashionmnist_check_if_scaling_down_phi_helps_v2.0",
        "--epses-specs",
        "(4,4),(3,6)",
        "--lr",
        "1.5e-4",
        "--reg-type",
        "epses_composition",
        "--reg-coeff",
        "1e-2",
        "--init-epses-composition-unit-empirical-output-std",
    ),
    standalone_mode=False,
)

Example #10

File: init_epses_composition_unit_empirical_output_std.py Project: yishiliuhuasheng/dctn

from os import environ

environ["CUDA_VISIBLE_DEVICES"] = "1"

from new_runner import main

main.main(
    (
        "--ds-type",
        "cifar10_28x28_grayscale",
        "--ds-path",
        "/mnt/hdd_1tb/datasets/cifar10",
        "--batch-size",
        "128",
        "--optimizer",
        "adam",
        "--experiments-dir",
        "/mnt/important/experiments/cifar10/28x28_grayscale/1_eps_k=4_q=4_init_epses_composition_unit_empirical_output_std",
        "--epses-specs",
        "(4,4)",
        "--lr",
        "3e-3",
        "--reg-type",
        "epses_composition",
        "--reg-coeff",
        "0.",
        "--init-epses-composition-unit-empirical-output-std",
    ),
    standalone_mode=False,
)