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covariance_spmd.py
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# ==============================================================================
# Copyright 2014 Intel Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
# daal4py covariance example for distributed memory systems; SPMD mode
# run like this:
# mpirun -n 4 python ./covariance_spmd.py
from pathlib import Path
from readcsv import pd_read_csv
from spmd_chunks_read import get_chunk_params
import daal4py as d4p
def main(readcsv=pd_read_csv):
data_path = Path(__file__).parent / "data" / "batch"
infile = data_path / "covcormoments_dense.csv"
# We know the number of lines in the file
# and use this to separate data between processes
skiprows, nrows = get_chunk_params(
lines_count=200, chunks_count=d4p.num_procs(), chunk_number=d4p.my_procid()
)
# Each process reads its chunk of the file
data = readcsv(infile, skip_header=skiprows, max_rows=nrows)
# Create algorithm with distributed mode
alg = d4p.covariance(distributed=True)
# Perform computation
res = alg.compute(data)
# covariance result objects provide correlation, covariance and mean
assert res.covariance.shape == (data.shape[1], data.shape[1])
assert res.mean.shape == (1, data.shape[1])
assert res.correlation.shape == (data.shape[1], data.shape[1])
return res
if __name__ == "__main__":
# Initialize SPMD mode
d4p.daalinit()
res = main()
# result is available on all processes - but we print only on root
if d4p.my_procid() == 0:
print(res)
d4p.daalfini()