Steboss

#!/bin/bash
#SBATCH -A your_account
#SBATCH -p your_partition
#SBATCH -N 4 # example with 4 nodes
#SBATCH -t 04:00:00 # max run time
#SBATCH -J "something_in_line_with_your_system"


export CONFIG="fuji-70B-v2-flash" # here you can insert, for example,  fuji-7B-v2-flash 
export CONTAINER="ghcr.io/nvidia/jax:axlearn" # this is our public jax-axlearn container

Steboss

#!/bin/bash 
#SBATCH -A something 
#SBATCH -p some partition 
#SBATCH -N 2 # number of nodes to use 
#SBATCH -t 
#SBATCH -J 

export CONFIG="fuji-70B-v2-flash"
export CONTAINER="my-container"

Steboss

Steboss

Steboss

Steboss

34 10
34 0.48683107 0.14057207 0.3592165 -0.13256235 -0.49405771 -0.18247333 0.9730174 0.90780646 -0.54426414 0.19603086
1 -0.8219996 -0.07360967 -0.37923583 0.1678768 0.5701133 -0.022573324 0.5270768 0.1042953 -1.1950656 0.038347103
33 0.85932285 0.4355257 0.4255835 0.3498892 -0.2654177 -0.13620856 0.95363593 0.76315534 -0.75525486 -0.031420168
3 -0.6389102 0.13940942 0.121233 -0.47521314 -0.19695918 0.27296686 0.80421066 0.37764257 -0.53217506 0.50822085
2 -0.6869131 0.25971353 -0.97738224 -0.17773396 0.12573187 0.17894426 0.46030718 0.5900712 -1.0935975 0.6173614

Steboss

34 10
34 0.48683107 0.14057207 0.3592165 -0.13256235 -0.49405771 -0.18247333 0.9730174 0.90780646 -0.54426414 0.19603086
1 -0.8219996 -0.07360967 -0.37923583 0.1678768 0.5701133 -0.022573324 0.5270768 0.1042953 -1.1950656 0.038347103
33 0.85932285 0.4355257 0.4255835 0.3498892 -0.2654177 -0.13620856 0.95363593 0.76315534 -0.75525486 -0.031420168
3 -0.6389102 0.13940942 0.121233 -0.47521314 -0.19695918 0.27296686 0.80421066 0.37764257 -0.53217506 0.50822085
2 -0.6869131 0.25971353 -0.97738224 -0.17773396 0.12573187 0.17894426 0.46030718 0.5900712 -1.0935975 0.6173614

Steboss

for random_walk in random_walks:
    N = len(random_walk)
    #print(random_walk)
    for i in range(N):
        idxs_left = np.arange(max(0, i-window_size), i).tolist()
        idxs_right = np.arange(i+1, min(N, i+window_size+1)).tolist()

        for j in idxs_left:
            X.append(random_walk[i])
            y.append(random_walk[j])

Steboss

walks = build_deepwalk_corpus(G,
                              num_paths = number_walks,
                              path_length = walk_length,
                              rand = random.Random(42)
                              )

Steboss

scales, fluct_to_array, coeff_to_array= dfa.play(X,5,9,0.25)
print("Fluctuations")
print(fluct_to_array)
print("Coefficients, swapped")
print(coeff_to_array)
#we need to swap the order here, due to the way coeff are computed!
coeff_tmp = coeff_to_array[1]
coeff_to_array[1] = coeff_to_array[0]
coeff_to_array[0] = coeff_tmp
fluctfit = 2**np.polyval(coeff_to_array,np.log2(scales))