Adds shots to experimental device interface and integrate with QNode

doc/releases/changelog-dev.md

@@ -87,6 +87,19 @@
 * When given a callable, `qml.ctrl` now does its custom pre-processing on all queued operators from the callable.
   [(#4370)](https://github.com/PennyLaneAI/pennylane/pull/4370)
 
+<<<<<<< HEAD
+* `qml.interfaces.set_shots` accepts `Shots` object as well as `int`'s and tuples of `int`'s.
+=======
+* `qml.interfaces.set_shots` can now accept shots specified as a `qml.measurements.Shots` object.
+  If a `pennylane.devices.experimental.Device` is provided, the `set_shots` will no longer raise an error, but will simply return without doing anything.
+>>>>>>> 2e776ac7ba5a71dcbab599828607563c08794333
+  [(#4388)](https://github.com/PennyLaneAI/pennylane/pull/4388)
+
+* `pennylane.devices.experimental.Device` now accepts a shots keyword argument and has a `shots`
+  property. This property is merely used to set defaults for a workflow, and does not directly
+  influence the number of shots used in executions or derivatives.
+  [(#4388)](https://github.com/PennyLaneAI/pennylane/pull/4388)
+
 * PennyLane no longer directly relies on `Operator.__eq__`.
   [(#4398)](https://github.com/PennyLaneAI/pennylane/pull/4398)
 
@@ -109,7 +122,7 @@
 * The `grouping_type` and `grouping_method` keyword arguments are removed from `qchem.molecular_hamiltonian`.
 
 * `zyz_decomposition` and `xyx_decomposition` are removed. Use `one_qubit_decomposition` instead.
 
 * `LieAlgebraOptimizer` has been removed. Use `RiemannianGradientOptimizer` instead.
 
 * `Operation.base_name` has been removed.

pennylane/devices/experimental/default_qubit_2.py

@@ -44,13 +44,14 @@
 class DefaultQubit2(Device):
     """A PennyLane device written in Python and capable of backpropagation derivatives.
 
-    Keyword Args:
+    Args:
+        shots (int, Sequence[int], Sequence[Union[int, Sequence[int]]]): The default number of shots to use in executions involving
+            this device.
         seed="global" (Union[str, None, int, array_like[int], SeedSequence, BitGenerator, Generator]): A
             seed-like parameter matching that of ``seed`` for ``numpy.random.default_rng`` or
             a request to seed from numpy's global random number generator.
             The default, ``seed="global"`` pulls a seed from NumPy's global generator. ``seed=None``
             will pull a seed from the OS entropy.
-
         max_workers=None (int): A ``ProcessPoolExecutor`` executes tapes asynchronously
             using a pool of at most ``max_workers`` processes. If ``max_workers`` is ``None``,
             only the current process executes tapes. If you experience any
@@ -137,8 +138,8 @@ def name(self):
         """The name of the device."""
         return "default.qubit.2"
 
-    def __init__(self, seed="global", max_workers=None) -> None:
-        super().__init__()
+    def __init__(self, shots=None, seed="global", max_workers=None) -> None:
+        super().__init__(shots=shots)
         self._max_workers = max_workers
         seed = np.random.randint(0, high=10000000) if seed == "global" else seed
         self._rng = np.random.default_rng(seed)

pennylane/devices/experimental/device_api.py

@@ -20,6 +20,7 @@
 from numbers import Number
 from typing import Callable, Union, Sequence, Tuple, Optional
 
+from pennylane.measurements import Shots
 from pennylane.tape import QuantumTape, QuantumScript
 from pennylane.typing import Result, ResultBatch
 from pennylane import Tracker
@@ -152,9 +153,20 @@ def name(self) -> str:
             self.tracker.record()
     """
 
-    def __init__(self) -> None:
+    def __init__(self, shots=None) -> None:
         # each instance should have its own Tracker.
         self.tracker = Tracker()
+        self._shots = Shots(shots)
+
+    @property
+    def shots(self) -> Shots:
+        """Default shots for execution workflows containing this device.
+
+        Note that the device itself should **always** pull shots from the provided :class:`~.QuantumTape` and its
+        :attr:`~.QuantumTape.shots`, not from this property. This property is used to provide a default at the start of a workflow.
+
+        """
+        return self._shots
 
     def preprocess(
         self,

pennylane/interfaces/execution.py

@@ -23,9 +23,7 @@
 # pylint: disable=unused-argument,unnecessary-lambda-assignment,inconsistent-return-statements,
 # pylint: disable=too-many-statements, invalid-unary-operand-type, function-redefined
 
-import inspect
 import warnings
-from contextlib import _GeneratorContextManager
 from functools import wraps, partial
 from typing import Callable, Sequence, Optional, Union, Tuple
 
@@ -244,23 +242,7 @@ def wrapper(tapes: Sequence[QuantumTape], **kwargs):
                 # Tape exists within the cache, store the cached result
                 cached_results[i] = cache[hashes[i]]
 
-                # Introspect the set_shots decorator of the input function:
-                #   warn the user in case of finite shots with cached results
-                finite_shots = False
-
-                closure = inspect.getclosurevars(fn).nonlocals
-                if "original_fn" in closure:  # deal with expand_fn wrapper above
-                    closure = inspect.getclosurevars(closure["original_fn"]).nonlocals
-
-                # retrieve the captured context manager instance (for set_shots)
-                if "self" in closure and isinstance(closure["self"], _GeneratorContextManager):
-                    # retrieve the shots from the arguments or device instance
-                    if closure["self"].func.__name__ == "set_shots":
-                        dev, shots = closure["self"].args
-                        shots = dev.shots if shots is False else shots
-                        finite_shots = isinstance(shots, int)
-
-                if finite_shots and getattr(cache, "_persistent_cache", True):
+                if tape.shots and getattr(cache, "_persistent_cache", True):
                     warnings.warn(
                         "Cached execution with finite shots detected!\n"
                         "Note that samples as well as all noisy quantities computed via sampling "

pennylane/interfaces/set_shots.py

@@ -18,6 +18,9 @@
 # pylint: disable=protected-access
 import contextlib
 
+import pennylane as qml
+from pennylane.measurements import Shots
+
 
 @contextlib.contextmanager
 def set_shots(device, shots):
@@ -40,6 +43,14 @@ def set_shots(device, shots):
     >>> set_shots(dev, shots=100)(lambda: dev.shots)()
     100
     """
+    if isinstance(device, qml.devices.experimental.Device):
+        raise ValueError(
+            "The new device interface is not compatible with `set_shots`. "
+
+            "Set shots when calling the qnode or put the shots on the QuantumTape."
+        )
+    if isinstance(shots, Shots):
+        shots = shots.shot_vector if shots.has_partitioned_shots else shots.total_shots
     if shots == device.shots:
         yield
         return

pennylane/measurements/shots.py

@@ -190,7 +190,11 @@ def __repr__(self):
 
     def __eq__(self, other):
         """Equality between Shot instances."""
-        return self.total_shots == other.total_shots and self.shot_vector == other.shot_vector
+        return (
+            isinstance(other, Shots)
+            and self.total_shots == other.total_shots
+            and self.shot_vector == other.shot_vector
+        )
 
     def __hash__(self):
         """Hash for a given Shot instance."""

pennylane/qnode.py

@@ -27,7 +27,7 @@
 import pennylane as qml
 from pennylane import Device
 from pennylane.interfaces import INTERFACE_MAP, SUPPORTED_INTERFACES, set_shots
-from pennylane.measurements import ClassicalShadowMP, CountsMP, MidMeasureMP
+from pennylane.measurements import ClassicalShadowMP, CountsMP, MidMeasureMP, Shots
 from pennylane.tape import QuantumTape, make_qscript
 
 
@@ -49,6 +49,15 @@ def _convert_to_interface(res, interface):
     return qml.math.asarray(res, like=interface if interface != "tf" else "tensorflow")
 
 
+# pylint: disable=protected-access
+def _get_device_shots(device) -> Shots:
+    if isinstance(device, Device):
+        if device._shot_vector:
+            return Shots(device._raw_shot_sequence)
+        return Shots(device.shots)
+    return device.shots
+
+
 class QNode:
     """Represents a quantum node in the hybrid computational graph.
 
@@ -693,7 +702,8 @@ def best_method_str(device, interface):
 
     @staticmethod
     def _validate_backprop_method(device, interface, shots=None):
-        if shots is not None or getattr(device, "shots", None) is not None:
+        if shots is not None or _get_device_shots(device):
+            print(shots, _get_device_shots(device))
             raise qml.QuantumFunctionError("Backpropagation is only supported when shots=None.")
 
         if isinstance(device, qml.devices.experimental.Device):
@@ -830,14 +840,10 @@ def construct(self, args, kwargs):  # pylint: disable=too-many-branches
         """Call the quantum function with a tape context, ensuring the operations get queued."""
         old_interface = self.interface
 
-        if not self._qfunc_uses_shots_arg:
-            shots = kwargs.pop("shots", None)
+        if self._qfunc_uses_shots_arg:
+            shots = _get_device_shots(self._original_device)
         else:
-            shots = (
-                self._original_device._raw_shot_sequence
-                if self._original_device._shot_vector
-                else self._original_device.shots
-            )
+            shots = kwargs.pop("shots", _get_device_shots(self._original_device))
 
         if old_interface == "auto":
             self.interface = qml.math.get_interface(*args, *list(kwargs.values()))
@@ -935,20 +941,14 @@ def __call__(self, *args, **kwargs) -> qml.typing.Result:
 
                 # pylint: disable=not-callable
                 # update the gradient function
-                if isinstance(self._original_device, Device):
-                    set_shots(self._original_device, override_shots)(self._update_gradient_fn)()
+                if isinstance(self._original_device, qml.Device):
+                    set_shots(self._original_device, override_shots)(self._update_gradient_fn)(
+                        shots=override_shots
+                    )
                 else:
                     self._update_gradient_fn(shots=override_shots)
-
             else:
-                if isinstance(self._original_device, Device):
-                    kwargs["shots"] = (
-                        self._original_device._raw_shot_sequence
-                        if self._original_device._shot_vector
-                        else self._original_device.shots
-                    )
-                else:
-                    kwargs["shots"] = None
+                kwargs["shots"] = _get_device_shots(self._original_device)
 
         # construct the tape
         self.construct(args, kwargs)

tests/devices/experimental/test_default_qubit_2.py

@@ -29,6 +29,28 @@ def test_name():
     assert DefaultQubit2().name == "default.qubit.2"
 
 
+def test_shots():
+    """Test the shots property of DefaultQubit2."""
+    assert DefaultQubit2().shots == qml.measurements.Shots(None)
+    assert DefaultQubit2(shots=100).shots == qml.measurements.Shots(100)
+
+    with pytest.raises(AttributeError):
+        DefaultQubit2().shots = 10
+
+
+
+
+def test_no_device_derivatives():
+    """Test that DefaultQubit2 currently doesn't support device derivatives."""
+    dev = DefaultQubit2()
+
+    with pytest.raises(NotImplementedError):
+        dev.compute_derivatives(qml.tape.QuantumScript())
+
+    with pytest.raises(NotImplementedError):
+        dev.execute_and_compute_derivatives(qml.tape.QuantumScript())
+
+
 def test_debugger_attribute():
     """Test that DefaultQubit2 has a debugger attribute and that it is `None`"""
     # pylint: disable=protected-access

tests/devices/experimental/test_device_api.py

@@ -49,6 +49,17 @@ def test_device_name(self):
         """Test the default name is the name of the class"""
         assert self.dev.name == "MinimalDevice"
 
+    def test_shots(self):
+        """Test default behavior for shots."""
+
+        assert self.dev.shots == qml.measurements.Shots(None)
+
+        shots_dev = self.MinimalDevice(shots=100)
+        assert shots_dev.shots == qml.measurements.Shots(100)
+
+        with pytest.raises(AttributeError):
+            self.dev.shots = 100  # pylint: disable=attribute-defined-outside-init
+
     def test_tracker_set_on_initialization(self):
         """Test that a new tracker instance is initialized with the class."""
         assert isinstance(self.dev.tracker, qml.Tracker)

tests/interfaces/test_set_shots.py

@@ -0,0 +1,58 @@
+# Copyright 2018-2023 Xanadu Quantum Technologies Inc.
+
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+
+#     http://www.apache.org/licenses/LICENSE-2.0
+
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+Tests for interfaces.set_shots
+"""
+
+import pytest
+
+import pennylane as qml
+from pennylane.interfaces import set_shots
+from pennylane.measurements import Shots
+
+
+def test_shots_new_device_interface():
+    """Test that calling set_shots on a device implementing the new interface leaves it
+    untouched.
+    """
+    dev = qml.devices.experimental.DefaultQubit2()
+    with pytest.raises(ValueError):
+        with set_shots(dev, 10):
+            pass
+
+
+def test_set_with_shots_class():
+    """Test that shots can be set on the old device interface with a Shots class."""
+
+    dev = qml.devices.DefaultQubit(wires=1)
+    with set_shots(dev, Shots(10)):
+        assert dev.shots == 10
+
+    assert dev.shots is None
+
+    shot_tuples = Shots((10, 10))
+    with set_shots(dev, shot_tuples):
+        assert dev.shots == 20
+        assert dev.shot_vector == list(shot_tuples.shot_vector)
+
+    assert dev.shots is None
+
+
+def test_shots_not_altered_if_False():
+    """Test a value of False can be passed to shots, indicating to not override
+    shots on the device."""
+
+    dev = qml.devices.DefaultQubit(wires=1)
+    with set_shots(dev, False):
+        assert dev.shots is None

tests/test_qnode.py

@@ -1426,7 +1426,7 @@ def test_warning_finite_shots_tape(self):
             qml.RZ(0.3, wires=0)
             qml.expval(qml.PauliZ(0))
 
-        tape = QuantumScript.from_queue(q)
+        tape = QuantumScript.from_queue(q, shots=5)
         # no warning on the first execution
         cache = {}
         qml.execute([tape], dev, None, cache=cache)
@@ -1696,16 +1696,6 @@ def supports_derivatives(self, execution_config=None, circuit=None) -> bool:
         assert not kwargs
         assert new_dev is dev
 
-    def test_shots_not_set_on_device(self):
-        """Test that shots are not set on the device when override shots are passed on a call."""
-
-        def f():
-            return qml.expval(qml.PauliZ(0))
-
-        qn = QNode(f, self.dev)
-        qn(shots=10)
-        assert getattr(self.dev, "shots", "not here") == "not here"
-
     def test_shots_integration(self):
         """Test that shots provided at call time are passed through the workflow."""