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3fb2dca
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Parent(s):
7acfb32
Format code with black
Browse filesThis commit fixes the style issues introduced in 7acfb32 according to the output
from black.
Details: https://deepsource.io/gh/MilesCranmer/PySR/transform/42920b26-add2-4718-9b08-113f6a24afb0/
- benchmarks/hyperparamopt.py +1 -0
- benchmarks/print_best_model.py +27 -28
benchmarks/hyperparamopt.py
CHANGED
@@ -267,6 +267,7 @@ def merge_trials(trials1, trials2_slice):
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import glob
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path = TRIALS_FOLDER + "/*.pkl"
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n_prior_trials = len(list(glob.glob(path)))
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import glob
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+
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path = TRIALS_FOLDER + "/*.pkl"
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n_prior_trials = len(list(glob.glob(path)))
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benchmarks/print_best_model.py
CHANGED
@@ -6,12 +6,13 @@ import hyperopt
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from hyperopt import hp, fmin, tpe, Trials
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-
#Change the following code to your file
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################################################################################
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# TODO: Declare a folder to hold all trials objects
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TRIALS_FOLDER =
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################################################################################
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def merge_trials(trials1, trials2_slice):
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"""Merge two hyperopt trials objects
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@@ -23,43 +24,43 @@ def merge_trials(trials1, trials2_slice):
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"""
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max_tid = 0
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if len(trials1.trials) > 0:
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-
max_tid = max([trial[
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for trial in trials2_slice:
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tid = trial[
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hyperopt_trial = Trials().new_trial_docs(
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-
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-
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results=[None],
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miscs=[None])
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hyperopt_trial[0] = trial
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hyperopt_trial[0][
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hyperopt_trial[0][
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for key in hyperopt_trial[0][
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hyperopt_trial[0][
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trials1.insert_trial_docs(hyperopt_trial)
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trials1.refresh()
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return trials1
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np.random.seed()
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# Load up all runs:
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import glob
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-
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files = 0
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for fname in glob.glob(path):
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trials_obj = pkl.load(open(fname,
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n_trials = trials_obj[
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trials_obj = trials_obj[
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if files == 0:
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trials = trials_obj
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else:
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trials = merge_trials(trials, trials_obj.trials[-n_trials:])
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files += 1
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print(files,
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best_loss = np.inf
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@@ -70,22 +71,20 @@ except NameError:
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raise NameError("No trials loaded. Be sure to set the right folder")
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# for trial in trials:
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-
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-
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-
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-
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# print(best_loss, best_trial['misc']['vals'])
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-
#trials = sorted(trials, key=lambda x: (x['result']['loss'] if trials['result']['status'] == 'ok' else float('inf')))
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clean_trials = []
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for trial in trials:
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-
clean_trials.append((trial[
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clean_trials = sorted(clean_trials, key=lambda x: x[0])
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for trial in clean_trials:
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print(trial)
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-
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-
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from hyperopt import hp, fmin, tpe, Trials
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+
# Change the following code to your file
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################################################################################
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# TODO: Declare a folder to hold all trials objects
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TRIALS_FOLDER = "trials2"
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################################################################################
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+
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def merge_trials(trials1, trials2_slice):
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"""Merge two hyperopt trials objects
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"""
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max_tid = 0
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if len(trials1.trials) > 0:
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max_tid = max([trial["tid"] for trial in trials1.trials])
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for trial in trials2_slice:
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tid = trial["tid"] + max_tid + 1
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hyperopt_trial = Trials().new_trial_docs(
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tids=[None], specs=[None], results=[None], miscs=[None]
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)
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hyperopt_trial[0] = trial
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hyperopt_trial[0]["tid"] = tid
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hyperopt_trial[0]["misc"]["tid"] = tid
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for key in hyperopt_trial[0]["misc"]["idxs"].keys():
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hyperopt_trial[0]["misc"]["idxs"][key] = [tid]
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trials1.insert_trial_docs(hyperopt_trial)
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trials1.refresh()
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return trials1
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+
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np.random.seed()
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# Load up all runs:
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import glob
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path = TRIALS_FOLDER + "/*.pkl"
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files = 0
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for fname in glob.glob(path):
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trials_obj = pkl.load(open(fname, "rb"))
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n_trials = trials_obj["n"]
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trials_obj = trials_obj["trials"]
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if files == 0:
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trials = trials_obj
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else:
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trials = merge_trials(trials, trials_obj.trials[-n_trials:])
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files += 1
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print(files, "trials merged")
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best_loss = np.inf
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raise NameError("No trials loaded. Be sure to set the right folder")
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# for trial in trials:
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# if trial['result']['status'] == 'ok':
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# loss = trial['result']['loss']
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# if loss < best_loss:
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# best_loss = loss
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# best_trial = trial
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# print(best_loss, best_trial['misc']['vals'])
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# trials = sorted(trials, key=lambda x: (x['result']['loss'] if trials['result']['status'] == 'ok' else float('inf')))
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clean_trials = []
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for trial in trials:
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clean_trials.append((trial["result"]["loss"], trial["misc"]["vals"]))
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clean_trials = sorted(clean_trials, key=lambda x: x[0])
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for trial in clean_trials:
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print(trial)
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