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update dataset generator for dkitty and ant
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,89 @@ | ||
| import cma | ||
| import numpy as np | ||
| import multiprocessing | ||
| import os | ||
| import argparse | ||
| import itertools | ||
| from design_bench.oracles.exact.ant_morphology_oracle import AntMorphologyOracle | ||
| from design_bench.datasets.continuous.ant_morphology_dataset import AntMorphologyDataset | ||
| from morphing_agents.mujoco.ant.designs import DEFAULT_DESIGN | ||
| from morphing_agents.mujoco.ant.designs import normalize_design_vector | ||
| from morphing_agents.mujoco.ant.designs import denormalize_design_vector | ||
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| def single_evaluate(design): | ||
| placeholder_dataset = AntMorphologyDataset() | ||
| oracle = AntMorphologyOracle(placeholder_dataset) | ||
| return oracle.predict( | ||
| denormalize_design_vector(design)[np.newaxis].astype(np.float32))[0] | ||
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| pool = multiprocessing.Pool() | ||
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| def many_evaluate(designs): | ||
| return pool.map(single_evaluate, designs) | ||
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| if __name__ == "__main__": | ||
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| parser = argparse.ArgumentParser("Process Raw Ant Morphologies") | ||
| parser.add_argument("--shard-folder", type=str, default="./") | ||
| parser.add_argument("--samples", type=int, default=25000) | ||
| args = parser.parse_args() | ||
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| os.makedirs(os.path.join( | ||
| args.shard_folder, f"ant_morphology/"), exist_ok=True) | ||
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| golden_design = normalize_design_vector( | ||
| np.concatenate(DEFAULT_DESIGN, axis=0)) | ||
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| sigma = 0.02 | ||
| max_iterations = 250 | ||
| save_every = 1 | ||
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| designs = [denormalize_design_vector(golden_design)] | ||
| predictions = [single_evaluate(golden_design)] | ||
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| for i in itertools.count(): | ||
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| initial_design = golden_design + \ | ||
| np.random.normal(0, 0.075, golden_design.shape) | ||
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| es = cma.CMAEvolutionStrategy(initial_design, sigma) | ||
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| step = 0 | ||
| while not es.stop() and step < max_iterations: | ||
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| if len(designs) >= args.samples: | ||
| break | ||
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| xs = es.ask() | ||
| ys = many_evaluate(xs) | ||
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| es.tell(xs, [-yi[0] for yi in ys]) | ||
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| step += 1 | ||
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| if step % save_every == 0: | ||
| designs.extend([denormalize_design_vector(xi) for xi in xs]) | ||
| predictions.extend(ys) | ||
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| print(f"CMA-ES ({len(designs)} samples)" | ||
| f" - Restart {i+1}" | ||
| f" - Step {step+1}/{max_iterations}" | ||
| f" - Current Objective Value = {np.mean(ys)}") | ||
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| np.save(os.path.join( | ||
| args.shard_folder, | ||
| f"ant_morphology/ant_morphology-x-0.npy"), | ||
| np.array(designs).astype(np.float32)) | ||
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| np.save(os.path.join( | ||
| args.shard_folder, | ||
| f"ant_morphology/ant_morphology-y-0.npy"), | ||
| np.array(predictions).astype(np.float32).reshape([-1, 1])) | ||
|
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| if len(designs) >= args.samples: | ||
| break | ||
|
|
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,89 @@ | ||
| import cma | ||
| import numpy as np | ||
| import multiprocessing | ||
| import os | ||
| import argparse | ||
| import itertools | ||
| from design_bench.oracles.exact.dkitty_morphology_oracle import DKittyMorphologyOracle | ||
| from design_bench.datasets.continuous.dkitty_morphology_dataset import DKittyMorphologyDataset | ||
| from morphing_agents.mujoco.dkitty.designs import DEFAULT_DESIGN | ||
| from morphing_agents.mujoco.dkitty.designs import normalize_design_vector | ||
| from morphing_agents.mujoco.dkitty.designs import denormalize_design_vector | ||
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||
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| def single_evaluate(design): | ||
| placeholder_dataset = DKittyMorphologyDataset() | ||
| oracle = DKittyMorphologyOracle(placeholder_dataset) | ||
| return oracle.predict( | ||
| denormalize_design_vector(design)[np.newaxis].astype(np.float32))[0] | ||
|
|
||
|
|
||
| pool = multiprocessing.Pool() | ||
|
|
||
|
|
||
| def many_evaluate(designs): | ||
| return pool.map(single_evaluate, designs) | ||
|
|
||
|
|
||
| if __name__ == "__main__": | ||
|
|
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| parser = argparse.ArgumentParser("Process Raw DKitty Morphologies") | ||
| parser.add_argument("--shard-folder", type=str, default="./") | ||
| parser.add_argument("--samples", type=int, default=25000) | ||
| args = parser.parse_args() | ||
|
|
||
| os.makedirs(os.path.join( | ||
| args.shard_folder, f"dkitty_morphology/"), exist_ok=True) | ||
|
|
||
| golden_design = normalize_design_vector( | ||
| np.concatenate(DEFAULT_DESIGN, axis=0)) | ||
|
|
||
| sigma = 0.02 | ||
| max_iterations = 250 | ||
| save_every = 1 | ||
|
|
||
| designs = [denormalize_design_vector(golden_design)] | ||
| predictions = [single_evaluate(golden_design)] | ||
|
|
||
| for i in itertools.count(): | ||
|
|
||
| initial_design = golden_design + \ | ||
| np.random.normal(0, 0.1, golden_design.shape) | ||
|
|
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| es = cma.CMAEvolutionStrategy(initial_design, sigma) | ||
|
|
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| step = 0 | ||
| while not es.stop() and step < max_iterations: | ||
|
|
||
| if len(designs) >= args.samples: | ||
| break | ||
|
|
||
| xs = es.ask() | ||
| ys = many_evaluate(xs) | ||
|
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| es.tell(xs, [-yi[0] for yi in ys]) | ||
|
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| step += 1 | ||
|
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| if step % save_every == 0: | ||
| designs.extend([denormalize_design_vector(xi) for xi in xs]) | ||
| predictions.extend(ys) | ||
|
|
||
| print(f"CMA-ES ({len(designs)} samples)" | ||
| f" - Restart {i+1}" | ||
| f" - Step {step+1}/{max_iterations}" | ||
| f" - Current Objective Value = {np.mean(ys)}") | ||
|
|
||
| np.save(os.path.join( | ||
| args.shard_folder, | ||
| f"dkitty_morphology/dkitty_morphology-x-0.npy"), | ||
| np.array(designs).astype(np.float32)) | ||
|
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||
| np.save(os.path.join( | ||
| args.shard_folder, | ||
| f"dkitty_morphology/dkitty_morphology-y-0.npy"), | ||
| np.array(predictions).astype(np.float32).reshape([-1, 1])) | ||
|
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| if len(designs) >= args.samples: | ||
| break | ||
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|
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