| 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() |