Some gates in rust #5
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This commit adds a native representation of Gates, Instruction, and Operations to rust's circuit module. At a high level this works by either wrapping the Python object in a rust wrapper struct that tracks metadata about the operations (name, num_qubits, etc) and then for other details it calls back to Python to get dynamic details like the definition, matrix, etc. For standard library gates like Swap, CX, H, etc this replaces the on-circuit representation with a new rust enum StandardGate. The enum representation is much more efficient and has a minimal memory footprint (just the enum variant and then any parameters or other mutable state stored in the circuit instruction). All the gate properties such as the matrix, definiton, name, etc are statically defined in rust code based on the enum variant (which represents the gate). The use of an enum to represent standard gates does mean a change in what we store on a CircuitInstruction. To represent a standard gate fully we need to store the mutable properties of the existing Gate class on the circuit instruction as the gate by itself doesn't contain this detail. That means, the parameters, label, unit, duration, and condition are added to the rust side of circuit instrucion. However no Python side access methods are added for these as they're internal only to the Rust code. In Qiskit 2.0 to simplify this storage we'll be able to drop, unit, duration, and condition from the api leaving only label and parameters. But for right now we're tracking all of the fields. To facilitate working with circuits and gates full from rust the setting the `operation` attribute of a `CircuitInstruction` object now transltates the python object to an internal rust representation. For standard gates this translates it to the enum form described earlier, and for other circuit operations 3 new Rust structs: PyGate, PyInstruction, and PyOperation are used to wrap the underlying Python object in a Rust api. These structs cache some commonly accessed static properties of the operation, such as the name, number of qubits, etc. However for dynamic pieces, such as the definition or matrix, callback to python to get a rust representation for those. Similarly whenever the `operation` attribute is accessed from Python it converts it back to the normal Python object representation. For standard gates this involves creating a new instance of a Python object based on it's internal rust representation. For the wrapper structs a reference to the wrapped PyObject is returned. To manage the 4 variants of operation (`StandardGate`, `PyGate`, `PyInstruction`, and `PyOperation`) a new Rust trait `Operation` is created that defines a standard interface for getting the properties of a given circuit operation. This common interface is implemented for the 4 variants as well as the `OperationType` enum which wraps all 4 (and is used as the type for `CircuitInstruction.operation` in the rust code. As everything in the `QuantumCircuit` data model is quite coupled moving the source of truth for the operations to exist in Rust means that more of the underlying `QuantumCircuit`'s responsibility has to move to Rust as well. Primarily this involves the `ParameterTable` which was an internal class for tracking which instructions in the circuit have a `ParameterExpression` parameter so that when we go to bind parameters we can lookup which operations need to be updated with the bind value. Since the representation of those instructions now lives in Rust and Python only recieves a ephemeral copy of the instructions the ParameterTable had to be reimplemented in Rust to track the instructions. This new parameter table maps the Parameter's uuid (as a u128) as a unique identifier for each parameter and maps this to a positional index in the circuit data to the underlying instruction using that parameter. This is a bit different from the Python parameter table which was mapping a parameter object to the id of the operation object using that parmaeter. This also leads to a difference in the binding mechanics as the parameter assignment was done by reference in the old model, but now we need to update the entire instruction more explicitly in rust. Additionally, because the global phase of a circuit can be parameterized the ownership of global phase is moved from Python into Rust in this commit as well. After this commit the only properties of a circuit that are not defined in Rust for the source of truth are the bits (and vars) of the circuit, and when creating circuits from rust this is what causes a Python interaction to still be required. This commit does not translate the full standard library of gates as that would make the pull request huge, instead this adds the basic infrastructure for having a more efficient standard gate representation on circuits. There will be follow up pull requests to add the missing gates and round out support in rust. The goal of this pull request is primarily to add the infrastructure for representing the full circuit model (and dag model in the future) in rust. By itself this is not expected to improve runtime performance (if anything it will probably hurt performance because of extra type conversions) but it is intended to enable writing native circuit manipulations in Rust, including transpiler passes without needing involvement from Python. Longer term this should greatly improve the runtime performance and reduce the memory overhead of Qiskit. But, this is just an early step towards that goal, and is more about unlocking the future capability. The next steps after this commit are to finish migrating the standard gate library and also update the `QuantumCircuit` methods to better leverage the more complete rust representation (which should help offset the performance penalty introduced by this). Fixes: Qiskit#12205
This commit adds a custom implementation of the FromPyObject trait for the Param enum. Previously, the Param trait derived it's impl of the trait, but this logic wasn't perfect. In cases whern a ParameterExpression was effectively a constant (such as `0 * x`) the trait's attempt to coerce to a float first would result in those ParameterExpressions being dropped from the circuit at insertion time. This was a change in behavior from before having gates in Rust as the parameters would disappear from the circuit at insertion time instead of at bind time. This commit fixes this by having a custom impl for FromPyObject that first tries to figure out if the parameter is a ParameterExpression (or a QuantumCircuit) by using a Python isinstance() check, then tries to extract it as a float, and finally stores a non-parameter object; which is a new variant in the Param enum. This new variant also lets us simplify the logic around adding gates to the parameter table as we're able to know ahead of time which gate parameters are `ParameterExpression`s and which are other objects (and don't need to be tracked in the parameter table. Additionally this commit tweaks two tests, the first is test.python.circuit.library.test_nlocal.TestNLocal.test_parameters_setter which was adjusted in the previous commit to workaround the bug fixed by this commit. The second is test.python.circuit.test_parameters which was testing that a bound ParameterExpression with a value of 0 defaults to an int which was a side effect of passing an int input to symengine for the bind value and not part of the api and didn't need to be checked. This assertion was removed from the test because the rust representation is only storing f64 values for the numeric parameters and it is never an int after binding from the Python perspective it isn't any different to have float(0) and int(0) unless you explicit isinstance check like the test previously was.
This commit fixes the handling of standard gates in Qiskit when the user specifies excluding the use of the stdgates.inc file from the exported qasm. Previously the object id of the standard gates were used to maintain a lookup table of the global definitions for all the standard gates explicitly in the file. However, the rust refactor means that every time the exporter accesses `circuit.data[x].operation` a new instance is returned. This means that on subsequent lookups for the definition the gate definitions are never found. To correct this issue this commit adds to the lookup table a fallback of the gate name + parameters to do the lookup for. This should be unique for any standard gate and not interfere with the previous logic that's still in place and functional for other custom gate definitions. While this fixes the logic in the exporter the test is still failing because the test is asserting the object ids are the same in the qasm3 file, which isn't the case anymore. The test will be updated in a subsequent commit to validate the qasm3 file is correct without using a hardcoded object id.
When ALAPScheduleAnalysis and ASAPScheduleAnalysis were setting the duration of a gate they were doing `node.op.duration = duration` this wasn't always working because if `node.op` was a standard gate it returned a new Python object created from the underlying rust representation. This commit fixes the passes so that they modify the duration and then explicit set the operation to update it's rust representation.
While the logic for the qasm3 exporter was fixed in commit a6e69ba to handle the edge case of a user specifying that the qasm exporter does not use the stdgates.inc include file in the output, but also has qiskit's standard gates in their circuit being exported. The one unit test to provide coverage for that scenario was not passing because when an id was used for the gate definitions in the qasm3 file it was being referenced against a temporary created by accessing a standard gate from the circuit and the ids weren't the same so the reference string didn't match what the exporter generated. This commit fixes this by changing the test to not do an exact string comparison, but instead a line by line comparison that either does exact equality check or a regex search for the expected line and the ids are checked as being any 15 character integer.
This commit updates the QuantumCircuit gate methods which add a given gate to the circuit to bypass the python gate object creation and directly insert a rust representation of the gate. This avoids a conversion in the rust side of the code. While in practice this is just the Python side object creation and a getattr for the rust code to determine it's a standard gate that we're skipping. This may add up over time if there are a lot of gates being created by the method. To accomplish this the rust code handling the mapping of rust StandardGate variants to the Python classes that represent those gates needed to be updated as well. By bypassing the python object creation we need a fallback to populate the gate class for when a user access the operation object from Python. Previously this mapping was only being populated at insertion time and if we never insert the python object (for a circuit created only via the methods) then we need a way to find what the gate class is. A static lookup table of import paths and class names are added to `qiskit_circuit::imports` module to faciliate this and helper functions are added to facilitate interacting with the class objects that represent each gate.
This commit adds a new rust crate feature flag for the qiskit-circuits and qiskit-pyext that enables caching the output from CircuitInstruction.operation to python space. Previously, for memory efficiency we were reconstructing the python object on demand for every access. This was to avoid carrying around an extra pointer and keeping the ephemeral python object around longer term if it's only needed once. But right now nothing is directly using the rust representation yet and everything is accessing via the python interface, so recreating gate objects on the fly has a huge performance penalty. To avoid that this adds caching by default as a temporary solution to avoid this until we have more usage of the rust representation of gates. There is an inherent tension between an optimal rust representation and something that is performant for Python access and there isn't a clear cut answer on which one is better to optimize for. A build time feature lets the user pick, if what we settle on for the default doesn't agree with their priorities or use case. Personally I'd like to see us disable the caching longer term (hopefully before releasing this functionality), but that's dependent on a sufficent level of usage from rust superseding the current Python space usage in the core of Qiskit.
This commit adds a native rust implementation to rust for the num_nonlocal_gates method on QuantumCircuit. Now that we have a rust representation of gates it is potentially faster to do the count because the iteration and filtering is done rust side.
This commit fixes some performance issues with the addition of standard gates to a circuit. To workaround potential reference cycles in Python when calling rust we need to check the parameters of the operation. This was causing our fast path for standard gates to access the `operation` attribute to get the parameters. This causes the gate to be eagerly constructed on the getter. However, the reference cycle case can only happen in situations without a standard gate, and the fast path for adding standard gates directly won't need to run this so a skip is added if we're adding a standard gate.
In the previous commit a side effect of the accidental eager operation creation was that the parameter input for gates were being validated by that. By fixing that in the previous commit the validation of input parameters on the circuit methods was broken. This commit fixes that oversight and adds back the validation.
All the things are done to implement R(theta, phi) in Rust to the according to the pattern set in the gates-in-rust PR. The "definition" is left as a todo again following the same pattern. Implementing this is rather clumsy and laborious. Doing the further gates would of course be a bit easier. Some of this is due to interfaces beyond our control. We could probably add a few conveniences that would make a difference. For example implementing some conveniences for complex numbers.
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This is a test PR to see if I can show informative difffs.