hrayrhar

Պարետոյի բազմությունը մոտարկելու երկրորդ ալգորիթմ։

import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from scipy.optimize import linprog

hrayrhar

Պարետոյի բազմությունը մոտարկելու առաջին ալգորիթմ։

import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import shapely.geometry as geom
from scipy.optimize import linprog

hrayrhar

class Adam:
    
    """Adam optimizer.
    Default parameters follow those provided in the original paper.
    # Arguments
        lr: float >= 0. Learning rate.
        beta_1: float, 0 < beta < 1. Generally close to 1.
        beta_2: float, 0 < beta < 1. Generally close to 1.
        epsilon: float >= 0. Fuzz factor.
        decay: float >= 0. Learning rate decay over each update.

hrayrhar

# lambda=0.1
echo lambda=0.1, dim=256
python -u main.py --network lstm --prefix los_decomp_ --dropout 0.3 --dim 256 --batch_size 8 --log_every 30 --batch_norm --ihm_C 0.0 --decomp_C 0.1 --ph_C 0.0 --los_C 1.0 --epochs 100 &> los_decomp_lstm.n256.bn.d0.3.bs16.0.00.1.00.0.00.0.10.ts1.0.previous;
echo lambda=0.1, dim=512
python -u main.py --network lstm --prefix los_decomp_ --dropout 0.3 --dim 512 --batch_size 8 --log_every 30 --batch_norm --ihm_C 0.0 --decomp_C 0.1 --ph_C 0.0 --los_C 1.0 --epochs 100 &> los_decomp_lstm.n512.bn.d0.3.bs16.0.00.1.00.0.00.0.10.ts1.0.previous;
echo lambda=0.1, dim=1024
python -u main.py --network lstm --prefix los_decomp_ --dropout 0.3 --dim 1024 --batch_size 8 --log_every 30 --batch_norm --ihm_C 0.0 --decomp_C 0.1 --ph_C 0.0 --los_C 1.0 --epochs 100 &> los_decomp_lstm.n1024.bn.d0.3.bs16.0.00.1.00.0.00.0.10.ts1.0.previous;


# lambda=0.3

hrayrhar

0cwr2rsylmd,0
0cxzmce10wr,89
0d0rfpzewzc,70
0d0t0iea1sy,147
0d0zyuor1ih,99
0d11h44yzbq,70
0d1brgfi0xd,104
0d1dcbrf451,123
0d1ly3fjwnw,64
0d1nqvenpln,3