import models
import os
import pandas as pd
import numpy as np
from run_model import run
import soundfile as sf
import argparse

parser = argparse.ArgumentParser()
parser.add_argument("run", type=str)
args = parser.parse_args()


folder = '/nfs/NAS6/SABIOD/SITE/CARIMAM/DATA/' #+args.run+'/'

df = pd.read_csv('/nfs/NAS6/SABIOD/SITE/CARIMAM/files.csv')
df.drop(df[df.samplerate.isna()].index, inplace=True)
df = df[df.session==args.run]

fns = list(df.filename)
outdir = '/nfs/NAS6/SABIOD/SITE/CARIMAM/results/stft_depthwise_ovs_128_k7_r1/'

model = models.get['stft_depthwise_ksize'](128, 7)
stdc='models/stft_depthwise_ovs_128_k7_r1.stdc'

outfn = outdir+args.run.replace('/','_')+'_'+stdc.split('/')[-1].rsplit('.',1)[0]+'.preds'
if os.path.isfile(outfn):
    exit()
preds = run(fns, stdc, model, folder, pool=False, batch_size=4, fe=50000, lensample=50)
preds.to_pickle(outfn)