import os
from operator import itemgetter

import joblib
import numpy as np
from keras.models import load_model as load_keras_model
from sklearn.utils import class_weight


def exists_or_make_path(p):
    if not os.path.exists(p):
        os.makedirs(p)


def get_custom_class_weights(client, server):
    return {
        "client": class_weight.compute_class_weight('balanced', np.unique(client), client),
        "server": class_weight.compute_class_weight('balanced', np.unique(server), server)
    }


def get_custom_sample_weights(client, server):
    return {
        "client": class_weight.compute_sample_weight("balanced", client),
        "server": class_weight.compute_sample_weight("balanced", server)
    }


def load_ordered_hyperband_results(path):
    results = joblib.load(path)
    return sorted(results, itemgetter("loss"))


def load_model(path, custom_objects=None):
    clf = load_keras_model(path, custom_objects)
    try:
        embd = clf.get_layer("domain_cnn").layer
    except Exception:
        # in some version i forgot to specify domain_cnn
        # this bug fix is for certain compatibility
        try:
            embd = clf.layers[1].layer
        except Exception:
            embd = clf.get_layer("domain_cnn")
    
    return embd, clf