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‎diploma_thesis/configuration/experiments/jsp/GRAPH-NN/experiments/2/machine.yml

+5-5
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@@ -3,7 +3,7 @@ kind: 'rl'
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parameters:
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model:
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kind: 'deep_multi_rule'
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kind: 'deep_rule'
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parameters:
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policy:
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kind: 'ppo'
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parameters:
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device: 'cpu'
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sample_count: 256
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sample_count: 512
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policy_step_ratio: 0.2
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entropy_regularization: 0.001
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entropy_decay: 0.999
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rollback_ratio: 0.0001
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rollback_ratio: 0.00
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critic_weight: 0.5
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epochs: 30
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epochs: 10
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loss:
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kind: 'cross_entropy'
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parameters:
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lr: 0.001
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betas: [0.99, 0.99]
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weight_decay: 0.0000001
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# weight_decay: 0.0000001
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memory:
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kind: 'replay'

‎diploma_thesis/configuration/experiments/jsp/GRAPH-NN/experiments/4/0/experiment.yml

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@@ -0,0 +1,173 @@
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# Evaluate the effectivenes of basic DQNs on the JSP environment
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template: &template 'baseline'
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base_model: &base_model 'configuration/experiments/jsp/GRAPH-NN/experiments/2/machine.yml'
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graph: &graph
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transition_model:
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kind: 'base'
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parameters:
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forward:
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kind: 'complete'
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schedule:
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kind: 'complete'
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memory: 0
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is_machine_set_in_work_center_connected: False
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is_work_center_set_in_shop_floor_connected: False
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###############################################################################################
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ppo_1: &ppo_1
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base_path: *base_model
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template: '0/local'
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mod_dirs:
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- ['configuration/mods/machine/mods']
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mods:
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__factory__:
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- [ 'util/optimizer/grad_norm.yml' ]
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- [
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'__none__',
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]
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- [
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'util/infrastructure/cuda.yml'
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]
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- [ 'util/train_schedule/on_stored_data_exclusively_3.yml']
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ppo_2: &ppo_2
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base_path: *base_model
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template: '0/global'
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mod_dirs:
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- ['configuration/mods/machine/mods']
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mods:
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__factory__:
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- [ 'util/optimizer/grad_norm.yml' ]
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- [
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'__none__',
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# 'agent/ppo/p3or.yml'
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]
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- [
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'util/infrastructure/cuda.yml'
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]
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- [ 'util/train_schedule/on_stored_data_exclusively_3.yml']
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###############################################################################################
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reward: &reward
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- kind: 'global_decomposed_tardiness'
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parameters:
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span: 128
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##############################################################################################
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# 8 runs
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long_single_source_run: &long_single_source_run
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parameters:
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mods:
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__inout_factory__:
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- [ ['utilization/80.yml'] ]
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nested:
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parameters:
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dispatch:
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seed:
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- '__range__': [1000, 1300]
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###############################################################################################
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task:
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kind: 'multi_task'
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n_workers: 3
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n_threads: 10
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debug: False
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store_run_statistics: False
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output_dir: 'results/jsp/experiments/1 (Graph)/Local'
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tasks:
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- kind: 'multi_value'
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parameters:
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base:
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name: 'model'
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output_dir: '1'
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log_stdout: False
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machine_agent:
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kind: 'mod'
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parameters:
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base_path: 'configuration/mods/machine_agent/model.yml'
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mods: [ ]
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work_center_agent:
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kind: 'static'
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parameters:
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model:
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kind: 'static'
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parameters:
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rule: 'et'
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encoder:
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kind: 'plain'
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tape:
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machine_reward:
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kind: 'surrogate_tardiness'
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work_center_reward:
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kind: 'no'
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simulator:
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kind: 'episodic'
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graph:
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*graph
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run:
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kind: 'mod'
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parameters:
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base_path: 'configuration/experiments/jsp/GRAPH-NN/experiments/2/run.yml'
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mod_dirs:
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- 'configuration/mods/run/mods'
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mods: []
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nested:
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parameters:
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simulations:
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- name: ''
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kind: 'multi_value'
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parameters:
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base:
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kind: 'mod'
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parameters:
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base_path: 'configuration/experiments/jsp/GRAPH-NN/experiments/2/simulation.yml'
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mod_dirs:
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- 'configuration/mods/simulation/mods'
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mods: [ ]
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values:
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values:
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__concat__:
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- output_dir: 'Local'
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machine_agent:
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parameters:
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*ppo_1
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- output_dir: 'Global'
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machine_agent:
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parameters:
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*ppo_2
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tape:
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machine_reward:
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*reward
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run:
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parameters:
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nested:
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parameters:
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simulations:
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__0__:
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parameters:
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values:
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__concat__:
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- *long_single_source_run

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