test: fourier reuploading dummy test

.github/workflows/codecov.yml

@@ -0,0 +1,8 @@
+coverage:
+  status:
+    project:
+      default:
+        threshold: 0.5%
+
+github_checks:
+  annotations: false

pyproject.toml

@@ -6,7 +6,7 @@ build-backend = "poetry.core.masonry.api"
 name = "qiboml"
 version = "0.0.1"
 description = "Quantum Machine Learning using Qibo"
-authors = ["Matteo Robbiati <[email protected]>"]
+authors = ["The Qibo team"]
 readme = "README.md"
 packages = [{ include = "qiboml", from = "src" }]
 
@@ -32,6 +32,7 @@ pylint = "^2.17"
 pytest-cov = "^3.0.0"
 pytest-env = "^0.8.1"
 pytest-benchmark = { version = "^4.0.0", extras = ["histogram"] }
+qibojit = "^0.1.3"
 
 [tool.poe.tasks]
 bench = "pytest benchmarks/"

src/qiboml/operations/expectation.py

@@ -57,7 +57,7 @@ def expectation(
         nshots=nshots,
         backend=backend,
         differentiation_rule=differentiation_rule,
-        exec_backend=exec_backend,
+        backend=exec_backend,
     )
 
     if differentiation_rule is not None:

tests/test_models_reuploading.py

@@ -1,14 +1,24 @@
 from qiboml.models.reuploading.fourier import FourierReuploading
 from qiboml.models.reuploading.u3 import ReuploadingU3
 
-NQUBITS = 3
+NQUBITS = 2
 NLAYERS = 2
-DATADIM = (3,)
+DATADIM = (2,)
 
 
 def test_reuloading_u3():
     model = ReuploadingU3(nqubits=NQUBITS, nlayers=NLAYERS, data_dimensionality=DATADIM)
     init_angles = model.circuit.get_parameters()
-    model.inject_data((0.4, 0.5, 0.6))
+    model.inject_data((0.4, 0.5))
+    new_angles = model.circuit.get_parameters()
+    assert init_angles != new_angles
+
+
+def test_reuloading_fourier():
+    model = FourierReuploading(
+        nqubits=NQUBITS, nlayers=NLAYERS, data_dimensionality=DATADIM
+    )
+    init_angles = model.circuit.get_parameters()
+    model.inject_data((0.4, 0.5))
     new_angles = model.circuit.get_parameters()
     assert init_angles != new_angles

tests/test_operations_differentiation.py

@@ -0,0 +1,61 @@
+import numpy as np
+import pytest
+from qibo import Circuit, gates, hamiltonians
+
+from qiboml.operations.differentiation import parameter_shift
+
+NQUBITS = 1
+GRADS_SCALEF_1 = [-0.41614683654714213, -0.29426025009181417]
+GRADS_SCALEF_05 = [-0.20807341827357106, -0.14713012504590708]
+
+
+def build_circuit(nqubits: int = 1):
+    """Helper function to build parametric circuit."""
+    circuit = Circuit(nqubits)
+    for q in range(nqubits):
+        circuit.add(gates.H(q))
+        circuit.add(gates.RY(q, theta=0.0))
+        circuit.add(gates.T(q))
+        circuit.add(gates.RY(q, theta=0.0))
+    circuit.add(gates.M(*range(nqubits)))
+    return circuit
+
+
+@pytest.mark.parametrize("nshots, atol", [(None, 1e-8), (100000, 1e-2)])
+@pytest.mark.parametrize(
+    "scale_factor, grads",
+    [(1, GRADS_SCALEF_1), (0.5, GRADS_SCALEF_05)],
+)
+def test_parameter_shift(nshots, atol, scale_factor, grads):
+    """Testing parameter shift rule algorithm."""
+
+    h = hamiltonians.Z(NQUBITS)
+
+    c = build_circuit(1)
+    nparams = len(c.get_parameters())
+
+    # testing parameter out of bounds
+    with pytest.raises(ValueError):
+        _ = parameter_shift(circuit=c, hamiltonian=h, parameter_index=5)
+
+    # testing hamiltonian type
+    with pytest.raises(TypeError):
+        _ = parameter_shift(circuit=c, hamiltonian=c, parameter_index=0, nshots=nshots)
+
+    params = np.linspace(0, 2, nparams, dtype=np.float64)
+    c.set_parameters(params)
+
+    psr_grads = []
+
+    for p in range(len(params)):
+        psr_grads.append(
+            parameter_shift(
+                hamiltonian=h,
+                circuit=c,
+                parameter_index=p,
+                scale_factor=scale_factor,
+                nshots=nshots,
+            )
+        )
+
+    np.testing.assert_allclose(grads, psr_grads, atol=atol)