From 46f04e7467567a08836e89e955a33c91ff26db5a Mon Sep 17 00:00:00 2001
From: Ignacio <ignacio.fernandez-grana@pasqal.com>
Date: Fri, 19 Apr 2024 17:22:57 +0200
Subject: [PATCH] lint and format

---
 qadence_libs/qinfo_tools/qng.py | 11 ++++++++---
 tests/conftest.py               |  7 ++++---
 tests/qinfo_tools/test_qfi.py   |  3 ++-
 tests/qinfo_tools/test_qng.py   |  8 ++++----
 tests/qinfo_tools/test_spsa.py  |  5 +----
 5 files changed, 19 insertions(+), 15 deletions(-)

diff --git a/qadence_libs/qinfo_tools/qng.py b/qadence_libs/qinfo_tools/qng.py
index b507715..6b83189 100644
--- a/qadence_libs/qinfo_tools/qng.py
+++ b/qadence_libs/qinfo_tools/qng.py
@@ -28,11 +28,13 @@ def __init__(
     ):
         """
         Args:
+
             params (tuple | torch.Tensor): Variational parameters to be updated
             circuit (QuantumCircuit): Quantum circuit. Needed to compute the QFI matrix
             lr (float): Learning rate.
             beta (float):
-                Shift applied to the QFI matrix before inversion to ensure numerical stability. Defaults to 10e-3.
+                Shift applied to the QFI matrix before inversion to ensure numerical stability.
+                Defaults to 10e-3.
         """
 
         if not 0.0 <= lr:
@@ -105,13 +107,16 @@ def __init__(
     ):
         """
         Args:
+
             params (tuple | torch.Tensor): Variational parameters to be updated
             circuit (QuantumCircuit): Quantum circuit. Required to compute the QFI matrix.
             lr (float): Learning rate.
             iteration (int): Current iteration. Required to compute the SPSA estimator of the QFI.
             beta (float):
-                Shift applied to the QFI matrix before inversion to ensure numerical stability. Defaults to 10e-3.
-            epsilon (float): Finite shift applied when computing the SPSA derivatives.
+                Shift applied to the QFI matrix before inversion to ensure numerical stability.
+                Defaults to 10e-3.
+            epsilon (float):
+                Finite shift applied when computing the SPSA derivatives. Defaults to 10e-2.
         """
 
         if not 0.0 <= lr:
diff --git a/tests/conftest.py b/tests/conftest.py
index 05658ac..e3e4aff 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -1,9 +1,10 @@
 # use this file for configuring test fixtures and
 # functions common to every test
-from pytest import fixture
+from __future__ import annotations
 
-from qadence import BasisSet, QuantumCircuit, QNN
-from qadence.constructors import feature_map, hea, hamiltonian_factory
+from pytest import fixture
+from qadence import QNN, BasisSet, QuantumCircuit
+from qadence.constructors import feature_map, hamiltonian_factory, hea
 from qadence.operations import RX, RY, Z
 
 N_QUBITS_OPTIM = 2
diff --git a/tests/qinfo_tools/test_qfi.py b/tests/qinfo_tools/test_qfi.py
index f2fe3e4..123db54 100644
--- a/tests/qinfo_tools/test_qfi.py
+++ b/tests/qinfo_tools/test_qfi.py
@@ -1,11 +1,12 @@
 from __future__ import annotations
 
 import random
+
 import numpy as np
 import torch
+from qadence import QuantumCircuit
 from torch import Size, allclose
 
-from qadence import QuantumCircuit
 from qadence_libs.qinfo_tools import get_quantum_fisher, get_quantum_fisher_spsa
 
 SEED = 42
diff --git a/tests/qinfo_tools/test_qng.py b/tests/qinfo_tools/test_qng.py
index 2630bff..2f31851 100644
--- a/tests/qinfo_tools/test_qng.py
+++ b/tests/qinfo_tools/test_qng.py
@@ -5,9 +5,7 @@
 import numpy as np
 import pytest
 import torch
-from qadence import QNN, BasisSet, QuantumCircuit, hamiltonian_factory
-from qadence.constructors import feature_map, hea
-from qadence.operations import RX, RY, Z
+from qadence import QuantumCircuit
 from torch import Tensor
 
 from qadence_libs.qinfo_tools import QNG, QNG_SPSA
@@ -39,7 +37,9 @@ def sin_dataset(samples: int) -> tuple[Tensor, Tensor]:
 
 @pytest.mark.parametrize("dataset", DATASETS)
 @pytest.mark.parametrize("optim_config", OPTIMIZERS_CONFIG)
-def test_optims(dataset: tuple[Tensor, Tensor], optim_config: dict, basic_optim_model) -> None:
+def test_optims(
+    dataset: tuple[Tensor, Tensor], optim_config: dict, basic_optim_model: QuantumCircuit
+) -> None:
     circuit, model = basic_optim_model
     model.reset_vparams(torch.rand((len(model.vparams))))
 
diff --git a/tests/qinfo_tools/test_spsa.py b/tests/qinfo_tools/test_spsa.py
index a514ae4..9d50147 100644
--- a/tests/qinfo_tools/test_spsa.py
+++ b/tests/qinfo_tools/test_spsa.py
@@ -5,12 +5,9 @@
 import numpy as np
 import pytest
 import torch
-from qadence import BasisSet, Overlap, QuantumCircuit
-from qadence.constructors import feature_map, hea
-from qadence.operations import RX, RY
+from qadence import Overlap, QuantumCircuit
 from torch import Size
 
-from qadence import QuantumCircuit
 from qadence_libs.qinfo_tools.spsa import _shifted_overlap, spsa_2gradient_step
 
 SEED = 42