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from __future__ import division
from __future__ import print_function
import os
import sys
import numpy as np
MAX_INPUT_SIZE = int(1e6)
MAX_FLOAT32 = np.finfo(np.float32).max
def IsValidSize(n):
if n == 0:
return False
# PFFFT only supports transforms for inputs of length N of the form
# N = (2^a)*(3^b)*(5^c) where a >= 5, b >=0, c >= 0.
FACTORS = [2, 3, 5]
factorization = [0, 0, 0]
for i, factor in enumerate(FACTORS):
while n % factor == 0:
n = n // factor
factorization[i] += 1
return factorization[0] >= 5 and n == 1
def main():
if len(sys.argv) < 2:
print('Usage: %s <path to output directory>' % sys.argv[0])
sys.exit(1)
output_path = sys.argv[1]
if not os.path.exists(output_path):
print('The output path does not exists.')
sys.exit(2)
# List of valid input sizes.
N = [n for n in range(MAX_INPUT_SIZE) if IsValidSize(n)]
# Set the seed to always generate the same random data.
np.random.seed(0)
# Generate different types of input arrays for each target length.
for n in N:
# Zeros.
z = np.zeros(n, np.float32)
z.tofile(os.path.join(output_path, 'zeros_%d' % n))
# Max float 32.
m = np.ones(n, np.float32) * MAX_FLOAT32
m.tofile(os.path.join(output_path, 'max_%d' % n))
# Random values in the s16 range.
rnd_s16 = 32768.0 * 2.0 * (np.random.rand(n) - 1.0)
rnd_s16 = rnd_s16.astype(np.float32)
rnd_s16.tofile(os.path.join(output_path, 'rnd_s16_%d' % n))
sys.exit(0)
if __name__ == '__main__':
main()
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