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Update deprecated gradient_kwargs usage #1045

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merged 18 commits into from
Jan 24, 2025
Merged

Update deprecated gradient_kwargs usage #1045

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9262ebc
fix: Update test_adjoint_jacobian.py with new gradient_kwargs
andrijapau Jan 22, 2025
573149f
Auto update version from '0.41.0-dev5' to '0.41.0-dev6'
ringo-but-quantum Jan 22, 2025
a5b8522
fix: Update pylint
andrijapau Jan 22, 2025
ed1c419
Merge branch 'fix-gradient-kwargs' of github.com:PennyLaneAI/pennylan…
andrijapau Jan 22, 2025
6ab8865
fix: Update pylint
andrijapau Jan 22, 2025
5ce277d
doc: Update changelog
andrijapau Jan 22, 2025
6c84d3a
doc: Update changelog
andrijapau Jan 22, 2025
cca5f35
doc: Fix changelog
andrijapau Jan 22, 2025
49a2927
doc: Update changelog
andrijapau Jan 22, 2025
34f93e7
Trigger CI
andrijapau Jan 23, 2025
259c831
Trigger CI
andrijapau Jan 23, 2025
6526003
Trigger CI
andrijapau Jan 23, 2025
1cb749f
Merge branch 'master' into fix-gradient-kwargs
andrijapau Jan 24, 2025
e5a8649
Auto update version from '0.41.0-dev6' to '0.41.0-dev7'
ringo-but-quantum Jan 24, 2025
f58700f
fix: Change pytest disable to what it was
andrijapau Jan 24, 2025
41cec71
Merge branch 'fix-gradient-kwargs' of github.com:PennyLaneAI/pennylan…
andrijapau Jan 24, 2025
5e07724
doc: fix pylint
andrijapau Jan 24, 2025
d0ac2d3
doc: Update changelog
andrijapau Jan 24, 2025
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6 changes: 5 additions & 1 deletion .github/CHANGELOG.md
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Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,10 @@

### Improvements

* Update Lightning integration tests following the `gradient_kwargs` deprecation
in Pennylane.
[(#1045)](https://github.com/PennyLaneAI/pennylane-lightning/pull/1045)

* Update `qml.MultiControlledX` tests following the latest updates in PennyLane.
[(#1040)](https://github.com/PennyLaneAI/pennylane-lightning/pull/1040)

Expand All @@ -31,7 +35,7 @@

This release contains contributions from (in alphabetical order):

Yushao Chen, Amintor Dusko, Joseph Lee, Shuli Shu
Yushao Chen, Amintor Dusko, Joseph Lee, Andrija Paurevic, Shuli Shu

---

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16 changes: 10 additions & 6 deletions mpitests/test_adjoint_jacobian.py
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Expand Up @@ -226,7 +226,7 @@
],
)
@pytest.mark.parametrize("batch_obs", [True, False])
def test_r_gradient(

Check notice on line 229 in mpitests/test_adjoint_jacobian.py

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codefactor.io / CodeFactor

mpitests/test_adjoint_jacobian.py#L229 

Too many positional arguments (8/5) (too-many-positional-arguments)
self, tol, param, rotation, meas, expected_func, batch_obs, dev
): # pylint: disable=too-many-arguments
"""Test for the gradient of the rotation gate matches the known formula."""
Expand Down Expand Up @@ -546,7 +546,7 @@
h = self.tol_for_allclose(dev.c_dtype)
tol = self.tol_for_allclose(dev.c_dtype)

qnode2 = QNode(circuit, dev, diff_method="finite-diff", h=h)
qnode2 = QNode(circuit, dev, diff_method="finite-diff", gradient_kwargs={"h": h})
grad_fn = qml.grad(qnode2)
grad_F = grad_fn(*args)

Expand All @@ -556,7 +556,7 @@

@pytest.mark.parametrize("reused_p", thetas**3 / 19)
@pytest.mark.parametrize("other_p", thetas**2 / 1)
def test_fanout_multiple_params(

Check notice on line 559 in mpitests/test_adjoint_jacobian.py

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codefactor.io / CodeFactor

mpitests/test_adjoint_jacobian.py#L559 

Too many positional arguments (6/5) (too-many-positional-arguments)
self, reused_p, other_p, tol, mocker, dev
): # pylint: disable=too-many-arguments
"""Tests that the correct gradient is computed for qnodes which
Expand Down Expand Up @@ -638,7 +638,7 @@
h = self.tol_for_allclose(dev.c_dtype)
tol = self.tol_for_allclose(dev.c_dtype)

cost = QNode(circuit, dev, diff_method="finite-diff", h=h)
cost = QNode(circuit, dev, diff_method="finite-diff", gradient_kwargs={"h": h})

grad_fn = qml.grad(cost)
grad_F = grad_fn(params)
Expand Down Expand Up @@ -678,7 +678,7 @@
tol = self.tol_for_allclose(dev.c_dtype)

qnode1 = QNode(f, dev, interface="tf", diff_method="adjoint")
qnode2 = QNode(f, dev, interface="tf", diff_method="finite-diff", h=h)
qnode2 = QNode(f, dev, interface="tf", diff_method="finite-diff", gradient_kwargs={"h": h})

with tf.GradientTape() as tape:
res1 = qnode1(params1, params2)
Expand Down Expand Up @@ -710,7 +710,9 @@
h = self.tol_for_allclose(dev.c_dtype)

qnode1 = QNode(f, dev, interface="torch", diff_method="adjoint")
qnode2 = QNode(f, dev, interface="torch", diff_method="finite-diff", h=h)
qnode2 = QNode(
f, dev, interface="torch", diff_method="finite-diff", gradient_kwargs={"h": h}
)

res1 = qnode1(params1, params2)
res1.backward()
Expand Down Expand Up @@ -749,7 +751,9 @@
tol = self.tol_for_allclose(dev.c_dtype)

qnode_adjoint = QNode(f, dev, interface="jax", diff_method="adjoint")
qnode_fd = QNode(f, dev, interface="jax", diff_method="finite-diff", h=h)
qnode_fd = QNode(
f, dev, interface="jax", diff_method="finite-diff", gradient_kwargs={"h": h}
)

grad_adjoint = jax.grad(qnode_adjoint)(params1, params2)
grad_fd = jax.grad(qnode_fd)(params1, params2)
Expand Down Expand Up @@ -1327,7 +1331,7 @@

circ = qml.QNode(circuit, dev, diff_method="adjoint")
circ_def = qml.QNode(circuit, dev_def, diff_method="adjoint")
circ_fd = qml.QNode(circuit, dev, diff_method="finite-diff", h=h)
circ_fd = qml.QNode(circuit, dev, diff_method="finite-diff", gradient_kwargs={"h": h})
circ_ps = qml.QNode(circuit, dev, diff_method="parameter-shift")
jacs = qml.jacobian(circ)(par, U)
jacs_def = qml.jacobian(circ_def)(par, U)
Expand Down
2 changes: 1 addition & 1 deletion pennylane_lightning/core/_version.py
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Expand Up @@ -16,4 +16,4 @@
Version number (major.minor.patch[-label])
"""

__version__ = "0.41.0-dev6"
__version__ = "0.41.0-dev7"
16 changes: 10 additions & 6 deletions tests/test_adjoint_jacobian.py
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Original file line number Diff line number Diff line change
Expand Up @@ -741,7 +741,7 @@ def circuit(x, y, z):

spy.assert_called()

qnode2 = QNode(circuit, dev, diff_method="finite-diff", h=h)
qnode2 = QNode(circuit, dev, diff_method="finite-diff", gradient_kwargs={"h": h})
grad_fn = qml.grad(qnode2)
grad_F = grad_fn(*args)

Expand Down Expand Up @@ -1026,7 +1026,7 @@ def circuit(params):
)
tol, h = get_tolerance_and_stepsize(dev, step_size=True)

cost = QNode(circuit, dev, diff_method="finite-diff", h=h)
cost = QNode(circuit, dev, diff_method="finite-diff", gradient_kwargs={"h": h})

grad_fn = qml.grad(cost)
grad_F = grad_fn(params)
Expand Down Expand Up @@ -1061,7 +1061,7 @@ def f(params1, params2):
params2 = tf.Variable(0.4, dtype=tf_r_dtype)

qnode1 = QNode(f, dev, interface="tf", diff_method="adjoint")
qnode2 = QNode(f, dev, interface="tf", diff_method="finite-diff", h=h)
qnode2 = QNode(f, dev, interface="tf", diff_method="finite-diff", gradient_kwargs={"h": h})

with tf.GradientTape() as tape:
res1 = qnode1(params1, params2)
Expand Down Expand Up @@ -1093,7 +1093,9 @@ def f(params1, params2):
tol, h = get_tolerance_and_stepsize(dev, step_size=True)

qnode1 = QNode(f, dev, interface="torch", diff_method="adjoint")
qnode2 = QNode(f, dev, interface="torch", diff_method="finite-diff", h=h)
qnode2 = QNode(
f, dev, interface="torch", diff_method="finite-diff", gradient_kwargs={"h": h}
)

res1 = qnode1(params1, params2)
res1.backward()
Expand Down Expand Up @@ -1130,7 +1132,9 @@ def f(params1, params2):
tol, h = get_tolerance_and_stepsize(dev, step_size=True)

qnode_adjoint = QNode(f, dev, interface="jax", diff_method="adjoint")
qnode_fd = QNode(f, dev, interface="jax", diff_method="finite-diff", h=h)
qnode_fd = QNode(
f, dev, interface="jax", diff_method="finite-diff", gradient_kwargs={"h": h}
)

grad_adjoint = jax.grad(qnode_adjoint)(params1, params2)
grad_fd = jax.grad(qnode_fd)(params1, params2)
Expand Down Expand Up @@ -1668,7 +1672,7 @@ def circuit(x, u_mat):

circ = qml.QNode(circuit, dev, diff_method="adjoint")
circ_def = qml.QNode(circuit, dev_def, diff_method="adjoint")
circ_fd = qml.QNode(circuit, dev, diff_method="finite-diff", h=h)
circ_fd = qml.QNode(circuit, dev, diff_method="finite-diff", gradient_kwargs={"h": h})
circ_ps = qml.QNode(circuit, dev, diff_method="parameter-shift")
jacs = qml.jacobian(circ)(par, U)
jacs_def = qml.jacobian(circ_def)(par, U)
Expand Down
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