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Merge pull request #9 from calico/run-composer
add gcs capability
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import h5py | ||
import numpy as np | ||
import argparse | ||
import subprocess | ||
import tempfile | ||
import os | ||
from baskerville.helpers.gcs_utils import download_from_gcs, upload_file_gcs | ||
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def collect_h5_borzoi(out_dir, num_procs, sad_stat) -> None: | ||
h5_file = "scores_f0c0.h5" | ||
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# count sequences | ||
num_seqs = 0 | ||
for pi in range(num_procs): | ||
# open job | ||
job_h5_file = "%s/job%d/%s" % (out_dir, pi, h5_file) | ||
job_h5_open = h5py.File(job_h5_file, "r") | ||
num_seqs += job_h5_open[sad_stat].shape[0] | ||
seq_len = job_h5_open[sad_stat].shape[1] | ||
num_targets = job_h5_open[sad_stat].shape[-1] | ||
job_h5_open.close() | ||
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# initialize final h5 | ||
final_h5_file = "%s/%s" % (out_dir, h5_file) | ||
final_h5_open = h5py.File(final_h5_file, "w") | ||
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# keep dict for string values | ||
final_strings = {} | ||
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job0_h5_file = "%s/job0/%s" % (out_dir, h5_file) | ||
job0_h5_open = h5py.File(job0_h5_file, "r") | ||
for key in job0_h5_open.keys(): | ||
key_shape = list(job0_h5_open[key].shape) | ||
key_shape[0] = num_seqs | ||
key_shape = tuple(key_shape) | ||
if job0_h5_open[key].dtype.char == "S": | ||
final_strings[key] = [] | ||
else: | ||
final_h5_open.create_dataset( | ||
key, shape=key_shape, dtype=job0_h5_open[key].dtype | ||
) | ||
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# set values | ||
si = 0 | ||
for pi in range(num_procs): | ||
# open job | ||
job_h5_file = "%s/job%d/%s" % (out_dir, pi, h5_file) | ||
job_h5_open = h5py.File(job_h5_file, "r") | ||
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# append to final | ||
for key in job_h5_open.keys(): | ||
job_seqs = job_h5_open[key].shape[0] | ||
if job_h5_open[key].dtype.char == "S": | ||
final_strings[key] += list(job_h5_open[key]) | ||
else: | ||
final_h5_open[key][si : si + job_seqs] = job_h5_open[key] | ||
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job_h5_open.close() | ||
si += job_seqs | ||
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# create final string datasets | ||
for key in final_strings: | ||
final_h5_open.create_dataset(key, data=np.array(final_strings[key], dtype="S")) | ||
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final_h5_open.close() | ||
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def download_h5_gcs(output_gcs_dir, num_processes) -> str: | ||
temp_dir = tempfile.mkdtemp() # create a temp dir for output | ||
print(f"temp_dir is {temp_dir}") | ||
out_dir = temp_dir + "/" + output_gcs_dir.split("/")[-1] | ||
if not os.path.isdir(out_dir): | ||
os.mkdir(out_dir) | ||
# download output from tempfile | ||
for pi in range(num_processes): | ||
if not os.path.isdir(f"{out_dir}/job{pi}"): | ||
os.mkdir(f"{out_dir}/job{pi}") | ||
download_from_gcs( | ||
f"{output_gcs_dir}/job{pi}/scores_f0c0.h5", | ||
f"{out_dir}/job{pi}/scores_f0c0.h5", | ||
) | ||
print(f"Done downloading {pi} partition") | ||
# download all of the files in the folder | ||
# Use gsutil to copy the contents recursively | ||
# subprocess.check_call(["gsutil", "-m", "cp", "-r", output_gcs_dir, temp_dir]) | ||
print(f"outdir is {out_dir}") | ||
print(f"gcs_out_dir is {output_gcs_dir}") | ||
print(f"Done dowloading") | ||
return out_dir | ||
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def main(): | ||
parser = argparse.ArgumentParser(description="Process and collect h5 files.") | ||
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parser.add_argument( | ||
"out_dir", type=str, help="Output directory for processed data." | ||
) | ||
parser.add_argument("num_procs", type=int, help="Number of processes to use.") | ||
parser.add_argument("sad_stat", type=str, help="Stats to concatenate. E.g. grads") | ||
parser.add_argument( | ||
"--gcs", | ||
action="store_true", | ||
help="Flag indicating if the file is on Google Cloud Storage.", | ||
) | ||
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args = parser.parse_args() | ||
if args.gcs: | ||
# download files to tempdir | ||
local_out_dir = download_h5_gcs(args.out_dir, args.num_procs) | ||
collect_h5_borzoi(local_out_dir, args.num_procs, args.sad_stat) | ||
# upload to gcs | ||
print(f"is there such a file? {local_out_dir}/scores_f0c0.h5") | ||
print(os.path.isfile(f"{local_out_dir}/scores_f0c0.h5")) | ||
upload_file_gcs(f"{local_out_dir}/scores_f0c0.h5", args.out_dir) | ||
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if __name__ == "__main__": | ||
main() |
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