EDIT: Apologies, figured it out - wasn’t sure how to delete
How come these two pieces of code do not give approximately equivalent outputs? Is there something about calculating BCE loss I’m not understanding?
import numpy as np
import torch
import torch.nn.functional as F
from torch.autograd import Variable as V
import torch.nn as nn

epsilon = 10e-8
def BCE_loss(x, y):
    x = np.reshape(x, (x.shape[0], -1))
    y = np.reshape(y, (y.shape[0], -1))
    
    loss = np.sum(-y * np.log(x + epsilon) - (1 - y) * np.log(1 - x + epsilon))
    
    #loss = -np.sum(y * np.log(x + epsilon))
    
    return loss

x = np.array([[.5,.6, .7],[.9, .8, .9]])
y = np.array([[.9, .8, .7],[.4, .5, .6]])

print(BCE_loss(x, y))

xt = V(torch.from_numpy(x).unsqueeze(1))
yt = V(torch.from_numpy(y).unsqueeze(1))
loss_func = nn.BCELoss(size_average=False)

print(loss_func(xt, yt))