import torch

from utils import print_cpp_vector

batch_norm = torch.nn.BatchNorm2d(2, track_running_stats=False)

weights = torch.Tensor([0.63508, 0.64903])
biases= torch.Tensor([0.25079, 0.66841])

batch_norm.weight = torch.nn.Parameter(weights)
batch_norm.bias = torch.nn.Parameter(biases)

input = torch.Tensor([
    # Channel 0
    0.38899, 0.80478, 0.48836, 0.97381,
    0.57508, 0.60835, 0.65467, 0.00168,
    0.65869, 0.74235, 0.17928, 0.70349,
    0.15524, 0.38664, 0.23411, 0.7137,
    # Channel 1
    0.32473, 0.15698, 0.314, 0.60888,
    0.80268, 0.99766, 0.93694, 0.89237,
    0.13449, 0.27367, 0.53036, 0.18962,
    0.57672, 0.48364, 0.10863, 0.0571
]).reshape(1, 2, 4, 4)

output = batch_norm(input)
print_cpp_vector(output.flatten())

print(batch_norm.running_mean)
print(batch_norm.running_var)