Add finite difference tests to all `operations` about metatensor HOT 3 OPEN

import torch
import metatensor
from metatensor import Labels, TensorMap, TensorBlock

g = torch.Generator()
g.manual_seed(0)
input_values1 = torch.rand(3, 5, generator=g, requires_grad=True)
values1 = input_values1**2 # some operation that makes ϑf(values)/ϑvalues not equal one
values1_grad = torch.autograd.grad(inputs=input_values1, outputs=values1,
        grad_outputs=torch.ones_like(values1), retain_graph=True)[0]

block1 = metatensor.block_from_array(values1.detach())
block1.add_gradient(
    parameter="g",
    gradient=TensorBlock(
        values=values1_grad.detach(),
        samples=Labels.range("sample", len(values1)),
        components=[],
        properties=block1.properties,
    ),
)
tensor1 = TensorMap(Labels.range("_", 1), [block1])

output_tensor = metatensor.add(tensor1, tensor1)
output_values = values1 + values1
grad_autograd = torch.autograd.grad(
        inputs=input_values1,
        outputs=output_values,
        grad_outputs=torch.ones_like(output_values),
        retain_graph=False)[0]
grad_metatensor = output_tensor[0].gradient("g").values
print(torch.allclose(grad_autograd, grad_metatensor))