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-17
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13 files changed

+17
-17
lines changed

src/hdbo_benchmark/experiments/training_vae_on_zinc250k/train_vae.py

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import click
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import numpy as np
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import torch
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import wandb
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import hdbo_benchmark
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import wandb
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from hdbo_benchmark.generative_models.vae_selfies import VAESelfies
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from hdbo_benchmark.utils.constants import DEVICE, WANDB_ENTITY
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from hdbo_benchmark.utils.data.zinc_250k import load_zinc_250k_dataloaders

src/hdbo_benchmark/experiments/training_vae_on_zinc250k/train_vae_rnn.py

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import click
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import numpy as np
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import torch
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import wandb
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import hdbo_benchmark
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import wandb
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from hdbo_benchmark.generative_models.vae_rnn_selfies import VAERNNSelfies
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from hdbo_benchmark.utils.constants import DEVICE, WANDB_ENTITY
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from hdbo_benchmark.utils.data.zinc_250k import load_zinc_250k_dataloaders

src/hdbo_benchmark/results/benchmark_on_pmo/create_table.py

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"""
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import pandas as pd
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import wandb
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from hdbo_benchmark.utils.constants import ROOT_DIR
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from hdbo_benchmark.utils.results.download_from_wandb import get_all_runs_for_experiment
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src/hdbo_benchmark/results/benchmark_on_pmo/visualize_function_vs_solver_heatmap.py

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"""
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"""
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""" """
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import matplotlib
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import matplotlib.pyplot as plt

src/hdbo_benchmark/results/download_tables.py

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"""
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import pandas as pd
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import wandb
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from hdbo_benchmark.utils.constants import ROOT_DIR
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from hdbo_benchmark.utils.results.download_from_wandb import (
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get_all_runs_for_function_names,

src/hdbo_benchmark/utils/ax/ax_solver.py

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)
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def evaluate(
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parametrization: dict[str, float]
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parametrization: dict[str, float],
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) -> dict[str, tuple[float, float]]:
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x = np.array([[parametrization[f"x{i}"] for i in range(x0.shape[1])]])
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y = black_box(x)

src/hdbo_benchmark/utils/data/experiments/loading_results.py

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from typing import Any, Dict, List
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import pandas as pd
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import wandb
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from hdbo_benchmark.utils.constants import WANDB_ENTITY
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ROOT_DIR = Path(__file__).parent.parent.parent.parent.parent.parent.resolve()

src/hdbo_benchmark/utils/experiments/load_generative_models.py

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@@ -15,9 +15,9 @@ def load_generative_model_and_bounds(
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problem: Problem,
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) -> tuple[VAE | LitAutoEncoder, tuple[float, float]]:
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match function_name:
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case function_name if function_name in PMOBenchmark(
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string_representation="SELFIES"
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).problem_names:
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case function_name if (
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function_name in PMOBenchmark(string_representation="SELFIES").problem_names
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):
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experiment_name = "benchmark_on_pmo"
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latent_space_bounds = (-10.0, 10.0)
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vae = VAEFactory().create(

src/hdbo_benchmark/utils/experiments/load_problems.py

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def _load_problem(function_name: str) -> Problem:
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match function_name:
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case function_name if function_name in PMOBenchmark(
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string_representation="SELFIES"
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).problem_names:
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case function_name if (
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function_name in PMOBenchmark(string_representation="SELFIES").problem_names
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):
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return _load_pmo_problem(function_name)
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case "rfp_rasp":
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return _load_rasp()

src/hdbo_benchmark/utils/logging/back_up.py

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from time import time
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import pandas as pd
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import wandb
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from hdbo_benchmark.utils.constants import ROOT_DIR, WANDB_ENTITY, WANDB_PROJECT
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from hdbo_benchmark.utils.data.experiments.loading_results import _load_run_as_row
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src/hdbo_benchmark/utils/logging/idempotence_of_experiments.py

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import wandb
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from hdbo_benchmark.utils.constants import WANDB_ENTITY
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src/hdbo_benchmark/utils/logging/wandb_observer.py

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import numpy as np
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import poli
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import poli_baselines
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import wandb
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from poli.core.black_box_information import BlackBoxInformation
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from poli.core.problem import Problem
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from poli.core.util.abstract_observer import AbstractObserver
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import hdbo_benchmark
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import wandb
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from hdbo_benchmark.utils.constants import WANDB_ENTITY, WANDB_PROJECT
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from hdbo_benchmark.utils.logging.library_hashes import get_git_hash_of_library
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from hdbo_benchmark.utils.logging.uncommited_changes import has_uncommitted_changes

src/hdbo_benchmark/utils/results/download_from_wandb.py

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import wandb
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from hdbo_benchmark.utils.constants import WANDB_ENTITY
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