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8d1a0c2
Anonym
msikyna Feb 10, 2026
d1ba7d6
Anonym
msikyna Feb 10, 2026
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30 changes: 15 additions & 15 deletions Implementation/Metacentrum/Laion/1000_5000/Metacentrum.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,7 @@
import threading
from concurrent.futures import ThreadPoolExecutor, as_completed

log_file_path = "/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/results/1000_5000/output_log.txt"
log_file_path = "/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/results/1000_5000/output_log.txt"
log_file = open(log_file_path, "w", buffering=1)
sys.stdout = log_file
sys.stderr = log_file
Expand Down Expand Up @@ -258,7 +258,7 @@ def peek_laion(
print(f" {s}")
print()

peek_laion("/storage/plzen1/home/xsikyna/PhD/laion/laionDir", shards=2, rows=5)
peek_laion("/storage/plzen1/home/anonymous/PhD/laion/laionDir", shards=2, rows=5)

def euclidean_distances(target_vector, feature_vectors_keys, feature_vectors_values):
# Compute differences all at once
Expand Down Expand Up @@ -300,15 +300,15 @@ def calculate_scaling_factor(A):
# indices = ["AutofaissL2", "AutofaissIP", "FlatL2", "FlatIP"]
indices = ["FlatL2", "FlatIP"]
methods = [
("Balance", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Balance.npy", 'rb'))),
("Balance+ALT", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Balance+ALT.npy", 'rb'))),
("Balance+Corr", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Balance+Corr.npy", 'rb'))),
("Min", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Min.npy", 'rb'))),
("Min+ALT", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Min+ALT.npy", 'rb'))),
("Min+Corr", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Min+Corr.npy", 'rb'))),
("Max", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Max.npy", 'rb'))),
("Max+ALT", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Max+ALT.npy", 'rb'))),
("Max+Corr", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Max+Corr.npy", 'rb')))
("Balance", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Balance.npy", 'rb'))),
("Balance+ALT", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Balance+ALT.npy", 'rb'))),
("Balance+Corr", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Balance+Corr.npy", 'rb'))),
("Min", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Min.npy", 'rb'))),
("Min+ALT", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Min+ALT.npy", 'rb'))),
("Min+Corr", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Min+Corr.npy", 'rb'))),
("Max", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Max.npy", 'rb'))),
("Max+ALT", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Max+ALT.npy", 'rb'))),
("Max+Corr", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Max+Corr.npy", 'rb')))
]

IVFPQ_PARAM_GRID = {
Expand All @@ -327,7 +327,7 @@ def calculate_scaling_factor(A):

dataset_name = "LAION2B-en" # will appear in CSV and index filenames
# Point this to the folder that contains both file types
LAION_DIR = "/storage/plzen1/home/xsikyna/PhD/laion/laionDir"
LAION_DIR = "/storage/plzen1/home/anonymous/PhD/laion/laionDir"

feature_vectors_keys, feature_vectors_values, selected_indices = load_laion_for_pipeline(
dirpath=LAION_DIR,
Expand Down Expand Up @@ -371,7 +371,7 @@ def params_tag(params: dict) -> str:

def make_or_load_index(dataset_name: str, index_name: str, size: int, params: dict):
"""Build and persist the FAISS index if missing; return loaded index and the final filename used."""
base_dir = "/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/results/1000_5000"
base_dir = "/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/results/1000_5000"
os.makedirs(base_dir, exist_ok=True)

# Include params in filename for IVFPQ and Autofaiss* (Flat stays without params)
Expand All @@ -390,7 +390,7 @@ def make_or_load_index(dataset_name: str, index_name: str, size: int, params: di
ids = feature_vectors_keys.astype(str)
emb = data

emb_path = f"/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/results/1000_5000/autofaiss_data/{dataset_name}/"
emb_path = f"/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/results/1000_5000/autofaiss_data/{dataset_name}/"
os.makedirs(emb_path, exist_ok=True)

emb_file = os.path.join(emb_path, f"{size}_embeddings.npy")
Expand Down Expand Up @@ -468,7 +468,7 @@ def describe_array(data, which):
which + '_IQR': pct[3] - pct[1],
}

CSV_PATH = '/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/results/1000_5000/results.csv'
CSV_PATH = '/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/results/1000_5000/results.csv'
FIELDNAMES = [
'dataset','method','k','growth', 'dataset_size', 'scaling_factor', 'index', 'index_params',
'count_superset',
Expand Down
10 changes: 5 additions & 5 deletions Implementation/Metacentrum/Laion/1000_5000/run_experiment.sh
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -3,12 +3,12 @@
#PBS -l walltime=24:0:0
#PBS -l select=1:ncpus=16:mem=400gb:scratch_local=400mb:spec=11.0

cd /storage/brno2/home/xsikyna/PhD/metric_learning_exp
cd /storage/brno2/home/anonymous/PhD/metric_learning_exp
module add mambaforge
mamba init
source /storage/brno2/home/xsikyna/.bashrc
mamba activate /storage/brno2/home/xsikyna/PhD/metric_learning_exp/faiss312
source /storage/brno2/home/anonymous/.bashrc
mamba activate /storage/brno2/home/anonymous/PhD/metric_learning_exp/faiss312

cd /storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/implementation/Metacentrum/1000_5000/
cd /storage/brno2/home/anonymous/PhD/metric_learning_exp_3/implementation/Metacentrum/1000_5000/
export PYTHONPATH=$PYTHONPATH:../..
python /storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/implementation/Metacentrum/1000_5000/Metacentrum.py
python /storage/brno2/home/anonymous/PhD/metric_learning_exp_3/implementation/Metacentrum/1000_5000/Metacentrum.py
30 changes: 15 additions & 15 deletions Implementation/Metacentrum/Laion/100_500/Metacentrum.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,7 @@
import threading
from concurrent.futures import ThreadPoolExecutor, as_completed

log_file_path = "/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/results/100_500/output_log.txt"
log_file_path = "/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/results/100_500/output_log.txt"
log_file = open(log_file_path, "w", buffering=1)
sys.stdout = log_file
sys.stderr = log_file
Expand Down Expand Up @@ -258,7 +258,7 @@ def peek_laion(
print(f" {s}")
print()

peek_laion("/storage/plzen1/home/xsikyna/PhD/laion/laionDir", shards=2, rows=5)
peek_laion("/storage/plzen1/home/anonymous/PhD/laion/laionDir", shards=2, rows=5)

def euclidean_distances(target_vector, feature_vectors_keys, feature_vectors_values):
# Compute differences all at once
Expand Down Expand Up @@ -300,15 +300,15 @@ def calculate_scaling_factor(A):
# indices = ["AutofaissL2", "AutofaissIP", "FlatL2", "FlatIP"]
indices = ["FlatL2", "FlatIP"]
methods = [
("Balance", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Balance.npy", 'rb'))),
("Balance+ALT", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Balance+ALT.npy", 'rb'))),
("Balance+Corr", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Balance+Corr.npy", 'rb'))),
("Min", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Min.npy", 'rb'))),
("Min+ALT", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Min+ALT.npy", 'rb'))),
("Min+Corr", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Min+Corr.npy", 'rb'))),
("Max", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Max.npy", 'rb'))),
("Max+ALT", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Max+ALT.npy", 'rb'))),
("Max+Corr", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Max+Corr.npy", 'rb')))
("Balance", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Balance.npy", 'rb'))),
("Balance+ALT", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Balance+ALT.npy", 'rb'))),
("Balance+Corr", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Balance+Corr.npy", 'rb'))),
("Min", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Min.npy", 'rb'))),
("Min+ALT", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Min+ALT.npy", 'rb'))),
("Min+Corr", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Min+Corr.npy", 'rb'))),
("Max", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Max.npy", 'rb'))),
("Max+ALT", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Max+ALT.npy", 'rb'))),
("Max+Corr", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Max+Corr.npy", 'rb')))
]

IVFPQ_PARAM_GRID = {
Expand All @@ -327,7 +327,7 @@ def calculate_scaling_factor(A):

dataset_name = "LAION2B-en" # will appear in CSV and index filenames
# Point this to the folder that contains both file types
LAION_DIR = "/storage/plzen1/home/xsikyna/PhD/laion/laionDir"
LAION_DIR = "/storage/plzen1/home/anonymous/PhD/laion/laionDir"

feature_vectors_keys, feature_vectors_values, selected_indices = load_laion_for_pipeline(
dirpath=LAION_DIR,
Expand Down Expand Up @@ -371,7 +371,7 @@ def params_tag(params: dict) -> str:

def make_or_load_index(dataset_name: str, index_name: str, size: int, params: dict):
"""Build and persist the FAISS index if missing; return loaded index and the final filename used."""
base_dir = "/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/results/100_500"
base_dir = "/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/results/100_500"
os.makedirs(base_dir, exist_ok=True)

# Include params in filename for IVFPQ and Autofaiss* (Flat stays without params)
Expand All @@ -390,7 +390,7 @@ def make_or_load_index(dataset_name: str, index_name: str, size: int, params: di
ids = feature_vectors_keys.astype(str)
emb = data

emb_path = f"/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/results/100_500/autofaiss_data/{dataset_name}/"
emb_path = f"/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/results/100_500/autofaiss_data/{dataset_name}/"
os.makedirs(emb_path, exist_ok=True)

emb_file = os.path.join(emb_path, f"{size}_embeddings.npy")
Expand Down Expand Up @@ -468,7 +468,7 @@ def describe_array(data, which):
which + '_IQR': pct[3] - pct[1],
}

CSV_PATH = '/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/results/100_500/results.csv'
CSV_PATH = '/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/results/100_500/results.csv'
FIELDNAMES = [
'dataset','method','k','growth', 'dataset_size', 'scaling_factor', 'index', 'index_params',
'count_superset',
Expand Down
10 changes: 5 additions & 5 deletions Implementation/Metacentrum/Laion/100_500/run_experiment.sh
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -3,12 +3,12 @@
#PBS -l walltime=24:0:0
#PBS -l select=1:ncpus=16:mem=400gb:scratch_local=400mb:spec=11.0

cd /storage/brno2/home/xsikyna/PhD/metric_learning_exp
cd /storage/brno2/home/anonymous/PhD/metric_learning_exp
module add mambaforge
mamba init
source /storage/brno2/home/xsikyna/.bashrc
mamba activate /storage/brno2/home/xsikyna/PhD/metric_learning_exp/faiss312
source /storage/brno2/home/anonymous/.bashrc
mamba activate /storage/brno2/home/anonymous/PhD/metric_learning_exp/faiss312

cd /storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/implementation/Metacentrum/100_500/
cd /storage/brno2/home/anonymous/PhD/metric_learning_exp_3/implementation/Metacentrum/100_500/
export PYTHONPATH=$PYTHONPATH:../..
python /storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/implementation/Metacentrum/100_500/Metacentrum.py
python /storage/brno2/home/anonymous/PhD/metric_learning_exp_3/implementation/Metacentrum/100_500/Metacentrum.py
30 changes: 15 additions & 15 deletions Implementation/Metacentrum/Laion/10_50/Metacentrum.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,7 @@
import threading
from concurrent.futures import ThreadPoolExecutor, as_completed

log_file_path = "/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/results/10_50/output_log.txt"
log_file_path = "/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/results/10_50/output_log.txt"
log_file = open(log_file_path, "w", buffering=1)
sys.stdout = log_file
sys.stderr = log_file
Expand Down Expand Up @@ -258,7 +258,7 @@ def peek_laion(
print(f" {s}")
print()

peek_laion("/storage/plzen1/home/xsikyna/PhD/laion/laionDir", shards=2, rows=5)
peek_laion("/storage/plzen1/home/anonymous/PhD/laion/laionDir", shards=2, rows=5)

def euclidean_distances(target_vector, feature_vectors_keys, feature_vectors_values):
# Compute differences all at once
Expand Down Expand Up @@ -300,15 +300,15 @@ def calculate_scaling_factor(A):
# indices = ["AutofaissL2", "AutofaissIP", "FlatL2", "FlatIP"]
indices = ["FlatL2", "FlatIP"]
methods = [
("Balance", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Balance.npy", 'rb'))),
("Balance+ALT", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Balance+ALT.npy", 'rb'))),
("Balance+Corr", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Balance+Corr.npy", 'rb'))),
("Min", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Min.npy", 'rb'))),
("Min+ALT", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Min+ALT.npy", 'rb'))),
("Min+Corr", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Min+Corr.npy", 'rb'))),
("Max", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Max.npy", 'rb'))),
("Max+ALT", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Max+ALT.npy", 'rb'))),
("Max+Corr", np.load(open("/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/inputs/Max+Corr.npy", 'rb')))
("Balance", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Balance.npy", 'rb'))),
("Balance+ALT", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Balance+ALT.npy", 'rb'))),
("Balance+Corr", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Balance+Corr.npy", 'rb'))),
("Min", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Min.npy", 'rb'))),
("Min+ALT", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Min+ALT.npy", 'rb'))),
("Min+Corr", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Min+Corr.npy", 'rb'))),
("Max", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Max.npy", 'rb'))),
("Max+ALT", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Max+ALT.npy", 'rb'))),
("Max+Corr", np.load(open("/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/inputs/Max+Corr.npy", 'rb')))
]

IVFPQ_PARAM_GRID = {
Expand All @@ -327,7 +327,7 @@ def calculate_scaling_factor(A):

dataset_name = "LAION2B-en" # will appear in CSV and index filenames
# Point this to the folder that contains both file types
LAION_DIR = "/storage/plzen1/home/xsikyna/PhD/laion/laionDir"
LAION_DIR = "/storage/plzen1/home/anonymous/PhD/laion/laionDir"

feature_vectors_keys, feature_vectors_values, selected_indices = load_laion_for_pipeline(
dirpath=LAION_DIR,
Expand Down Expand Up @@ -371,7 +371,7 @@ def params_tag(params: dict) -> str:

def make_or_load_index(dataset_name: str, index_name: str, size: int, params: dict):
"""Build and persist the FAISS index if missing; return loaded index and the final filename used."""
base_dir = "/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/results/10_50"
base_dir = "/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/results/10_50"
os.makedirs(base_dir, exist_ok=True)

# Include params in filename for IVFPQ and Autofaiss* (Flat stays without params)
Expand All @@ -390,7 +390,7 @@ def make_or_load_index(dataset_name: str, index_name: str, size: int, params: di
ids = feature_vectors_keys.astype(str)
emb = data

emb_path = f"/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/results/10_50/autofaiss_data/{dataset_name}/"
emb_path = f"/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/results/10_50/autofaiss_data/{dataset_name}/"
os.makedirs(emb_path, exist_ok=True)

emb_file = os.path.join(emb_path, f"{size}_embeddings.npy")
Expand Down Expand Up @@ -468,7 +468,7 @@ def describe_array(data, which):
which + '_IQR': pct[3] - pct[1],
}

CSV_PATH = '/storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/results/10_50/results.csv'
CSV_PATH = '/storage/brno2/home/anonymous/PhD/metric_learning_exp_3/results/10_50/results.csv'
FIELDNAMES = [
'dataset','method','k','growth', 'dataset_size', 'scaling_factor', 'index', 'index_params',
'count_superset',
Expand Down
10 changes: 5 additions & 5 deletions Implementation/Metacentrum/Laion/10_50/run_experiment.sh
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -3,12 +3,12 @@
#PBS -l walltime=24:0:0
#PBS -l select=1:ncpus=16:mem=400gb:scratch_local=400mb:spec=11.0

cd /storage/brno2/home/xsikyna/PhD/metric_learning_exp
cd /storage/brno2/home/anonymous/PhD/metric_learning_exp
module add mambaforge
mamba init
source /storage/brno2/home/xsikyna/.bashrc
mamba activate /storage/brno2/home/xsikyna/PhD/metric_learning_exp/faiss312
source /storage/brno2/home/anonymous/.bashrc
mamba activate /storage/brno2/home/anonymous/PhD/metric_learning_exp/faiss312

cd /storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/implementation/Metacentrum/10_50/
cd /storage/brno2/home/anonymous/PhD/metric_learning_exp_3/implementation/Metacentrum/10_50/
export PYTHONPATH=$PYTHONPATH:../..
python /storage/brno2/home/xsikyna/PhD/metric_learning_exp_3/implementation/Metacentrum/10_50/Metacentrum.py
python /storage/brno2/home/anonymous/PhD/metric_learning_exp_3/implementation/Metacentrum/10_50/Metacentrum.py
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