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Quantum gate models for IR integration (#16)
* Add IR * Move tests * Run black * Rename ir/ directories to xir/ * Apply formatter and update import paths * Clarify that top-level makefile is for C++ code * Rename Python bindings package to 'bindings' * Move Python bindings tests to subdirectory * Update import path to Python bindings module * Rename 'requirements_test.txt' to 'requirements.txt' * Add Python wheel dependencies * Add Python distribution directory to .gitignore * Create top-level Jet Python package * Create setup.py to build quantum-jet Python wheels * Move setup.py to python/ directory * Make cleaned directory prefixes consistent * Add 'build' help documentation and clean build/ and dist/ * Change source directory to parent directory * Import all bindings directly into the 'jet' package * Exclude tests from package * Fix wheel build error for lark * Remove deprecated Python bindings build steps * Update changelog * Adjust PR number * Flatten jet.bindings package and apply formatter * Change 'lark' requirement to 'lark-parser' * add circuit class * add first gate * Add gates (WIP) * add gates * Add jet/ to formatted directories * Refactor Gate class * Apply formatter to jet/ directory * Factor parameter validation to Gate class * Remove positional arguments after keyword arguments * Move dtype factories to separate module to avoid circular dependency * Add unit tests for the Gate class * Delegate package exports to modules * Update name of validation parameter * Add unit tests for H, CNOT, and Pauli gates * Add unit tests for remaining gates * Add unit test IDs * Add unit tests for CV Fock gates * Defer circuit.py to future PR * Update changelog * Add thewalrus to package requirements and specify numpy versions * Create type aliases for union of template class specializations * Convert Gate into an ABC, expose num_wires, and distribute validation * Use MockGate instead of CPhaseShift in Gate tests * Elaborate docstring comments * Replace conjugate transpose with matrix inverse * Replace MockGate data with invertible matrix * Move parameter validation to gate constructors * Rename 'gates.py' to 'gate.py' * Reword @indices.getter docstring * Remove leftover *params from Displacement constructor * Import symbols from math and cmath modules explicitly * Rename 'CNOT' gate to 'CX' gate * Add aliases for NOT and CNOT gates * Add code span formatting to None Co-authored-by: antalszava <[email protected]> * Add colon after Exception class in docstring Co-authored-by: antalszava <[email protected]> * Apply hanging indent to Exception description Co-authored-by: antalszava <[email protected]> * Update wording of num_wires attribute Co-authored-by: antalszava <[email protected]> * Remove full stop from docstring argument descriptions * Restore full stop and capitalize argument descriptions * Fix grammar error in transmissivity argument description * Remove tensor ID (and **kwargs) from Gate (sub)class(es) * Test multi-character string indices * Add descriptions to *args and **kwargs * Remove extra space from list * Mention Antal and Josh in changelog Co-authored-by: Mikhail Andrenkov <[email protected]> Co-authored-by: Mikhail Andrenkov <[email protected]> Co-authored-by: antalszava <[email protected]>
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,83 +1,9 @@ | ||
| from typing import Union | ||
|
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| import numpy as np | ||
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| # The existence of a Python binding is proof of its intention to be exposed. | ||
| from .bindings import * | ||
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| def TaskBasedCpuContractor( | ||
| *args, **kwargs | ||
| ) -> Union[TaskBasedCpuContractorC64, TaskBasedCpuContractorC128]: | ||
| """Constructs a task-based CPU contractor with the specified data type. If a | ||
| `dtype` keyword argument is not provided, a TaskBasedCpuContractorC128 | ||
| instance will be returned. | ||
| """ | ||
| dtype = kwargs.pop("dtype", "complex128") | ||
| if np.dtype(dtype) == np.complex64: | ||
| return TaskBasedCpuContractorC64(*args, **kwargs) | ||
| elif np.dtype(dtype) == np.complex128: | ||
| return TaskBasedCpuContractorC128(*args, **kwargs) | ||
| else: | ||
| raise TypeError(f"Data type '{dtype}' is not supported.") | ||
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| def Tensor(*args, **kwargs) -> Union[TensorC64, TensorC128]: | ||
| """Constructs a tensor with the specified data type. If a `dtype` keyword | ||
| argument is not provided, a TensorC128 instance will be returned. | ||
| """ | ||
| dtype = kwargs.pop("dtype", "complex128") | ||
| if np.dtype(dtype) == np.complex64: | ||
| return TensorC64(*args, **kwargs) | ||
| elif np.dtype(dtype) == np.complex128: | ||
| return TensorC128(*args, **kwargs) | ||
| else: | ||
| raise TypeError(f"Data type '{dtype}' is not supported.") | ||
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| def TensorNetwork(*args, **kwargs) -> Union[TensorNetworkC64, TensorNetworkC128]: | ||
| """Constructs a tensor network with the specified data type. If a `dtype` | ||
| keyword argument is not provided, a TensorNetworkC128 instance will be | ||
| returned. | ||
| """ | ||
| dtype = kwargs.pop("dtype", "complex128") | ||
| if np.dtype(dtype) == np.complex64: | ||
| return TensorNetworkC64(*args, **kwargs) | ||
| elif np.dtype(dtype) == np.complex128: | ||
| return TensorNetworkC128(*args, **kwargs) | ||
| else: | ||
| raise TypeError(f"Data type '{dtype}' is not supported.") | ||
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| def TensorNetworkFile(*args, **kwargs) -> Union[TensorNetworkFileC64, TensorNetworkFileC128]: | ||
| """Constructs a tensor network file with the specified data type. If a | ||
| `dtype` keyword argument is not provided, a TensorNetworkFileC128 instance | ||
| will be returned. | ||
| """ | ||
| dtype = kwargs.pop("dtype", "complex128") | ||
| if np.dtype(dtype) == np.complex64: | ||
| return TensorNetworkFileC64(*args, **kwargs) | ||
| elif np.dtype(dtype) == np.complex128: | ||
| return TensorNetworkFileC128(*args, **kwargs) | ||
| else: | ||
| raise TypeError(f"Data type '{dtype}' is not supported.") | ||
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| def TensorNetworkSerializer( | ||
| *args, **kwargs | ||
| ) -> Union[TensorNetworkSerializerC64, TensorNetworkSerializerC128]: | ||
| """Constructs a tensor network serializer with the specified data type. If a | ||
| `dtype` keyword argument is not provided, a TensorNetworkSerializerC128 | ||
| instance will be returned. | ||
| """ | ||
| dtype = kwargs.pop("dtype", "complex128") | ||
| if np.dtype(dtype) == np.complex64: | ||
| return TensorNetworkSerializerC64(*args, **kwargs) | ||
| elif np.dtype(dtype) == np.complex128: | ||
| return TensorNetworkSerializerC128(*args, **kwargs) | ||
| else: | ||
| raise TypeError(f"Data type '{dtype}' is not supported.") | ||
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| # The rest of the modules control their exports using `__all__`. | ||
| from .factory import * | ||
| from .gate import * | ||
|
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| # Grab the current Jet version from the C++ headers. | ||
| __version__ = version() |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,140 @@ | ||
| from typing import Union | ||
|
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| import numpy as np | ||
|
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| from .bindings import ( | ||
| TaskBasedCpuContractorC64, | ||
| TaskBasedCpuContractorC128, | ||
| TensorC64, | ||
| TensorC128, | ||
| TensorNetworkC64, | ||
| TensorNetworkC128, | ||
| TensorNetworkFileC64, | ||
| TensorNetworkFileC128, | ||
| TensorNetworkSerializerC64, | ||
| TensorNetworkSerializerC128, | ||
| ) | ||
|
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| __all__ = [ | ||
| "TaskBasedCpuContractorType", | ||
| "TensorType", | ||
| "TensorNetworkType", | ||
| "TensorNetworkFileType", | ||
| "TensorNetworkSerializerType", | ||
| "TaskBasedCpuContractor", | ||
| "Tensor", | ||
| "TensorNetwork", | ||
| "TensorNetworkFile", | ||
| "TensorNetworkSerializer", | ||
| ] | ||
|
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| # Type aliases to avoid enumerating class specializations. | ||
| TaskBasedCpuContractorType = Union[TaskBasedCpuContractorC64, TaskBasedCpuContractorC128] | ||
| TensorType = Union[TensorC64, TensorC128] | ||
| TensorNetworkType = Union[TensorNetworkC64, TensorNetworkC128] | ||
| TensorNetworkFileType = Union[TensorNetworkFileC64, TensorNetworkFileC128] | ||
| TensorNetworkSerializerType = Union[TensorNetworkSerializerC64, TensorNetworkSerializerC128] | ||
|
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| def TaskBasedCpuContractor(*args, **kwargs) -> TaskBasedCpuContractorType: | ||
| """Constructs a task-based CPU contractor (TBCC) with the specified data | ||
| type. If a ``dtype`` keyword argument is not provided, a | ||
| ``TaskBasedCpuContractorC128`` instance will be returned. | ||
| Args: | ||
| *args: Positional arguments to pass to the TBCC constructor. | ||
| **kwargs: Keyword arguments to pass to the TBCC constructor. | ||
| Returns: | ||
| Task-based CPU contractor instance. | ||
| """ | ||
| dtype = kwargs.pop("dtype", np.complex128) | ||
| if np.dtype(dtype) == np.complex64: | ||
| return TaskBasedCpuContractorC64(*args, **kwargs) | ||
| elif np.dtype(dtype) == np.complex128: | ||
| return TaskBasedCpuContractorC128(*args, **kwargs) | ||
| else: | ||
| raise TypeError(f"Data type '{dtype}' is not supported.") | ||
|
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||
|
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| def Tensor(*args, **kwargs) -> TensorType: | ||
| """Constructs a tensor with the specified data type. If a ``dtype`` keyword | ||
| argument is not provided, a ``TensorC128`` instance will be returned. | ||
| Args: | ||
| *args: Positional arguments to pass to the tensor constructor. | ||
| **kwargs: Keyword arguments to pass to the tensor constructor. | ||
| Returns: | ||
| Tensor instance. | ||
| """ | ||
| dtype = kwargs.pop("dtype", np.complex128) | ||
| if np.dtype(dtype) == np.complex64: | ||
| return TensorC64(*args, **kwargs) | ||
| elif np.dtype(dtype) == np.complex128: | ||
| return TensorC128(*args, **kwargs) | ||
| else: | ||
| raise TypeError(f"Data type '{dtype}' is not supported.") | ||
|
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||
|
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| def TensorNetwork(*args, **kwargs) -> TensorNetworkType: | ||
| """Constructs a tensor network with the specified data type. If a ``dtype`` | ||
| keyword argument is not provided, a ``TensorNetworkC128`` instance will be | ||
| returned. | ||
| Args: | ||
| *args: Positional arguments to pass to the tensor network constructor. | ||
| **kwargs: Keyword arguments to pass to the tensor network constructor. | ||
| Returns: | ||
| Tensor network instance. | ||
| """ | ||
| dtype = kwargs.pop("dtype", np.complex128) | ||
| if np.dtype(dtype) == np.complex64: | ||
| return TensorNetworkC64(*args, **kwargs) | ||
| elif np.dtype(dtype) == np.complex128: | ||
| return TensorNetworkC128(*args, **kwargs) | ||
| else: | ||
| raise TypeError(f"Data type '{dtype}' is not supported.") | ||
|
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||
|
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| def TensorNetworkFile(*args, **kwargs) -> TensorNetworkFileType: | ||
| """Constructs a tensor network file with the specified data type. If a | ||
| ``dtype`` keyword argument is not provided, a ``TensorNetworkFileC128`` | ||
| instance will be returned. | ||
| Args: | ||
| *args: Positional arguments to pass to the tensor network file constructor. | ||
| **kwargs: Keyword arguments to pass to the tensor network file constructor. | ||
| Returns: | ||
| Tensor network file instance. | ||
| """ | ||
| dtype = kwargs.pop("dtype", np.complex128) | ||
| if np.dtype(dtype) == np.complex64: | ||
| return TensorNetworkFileC64(*args, **kwargs) | ||
| elif np.dtype(dtype) == np.complex128: | ||
| return TensorNetworkFileC128(*args, **kwargs) | ||
| else: | ||
| raise TypeError(f"Data type '{dtype}' is not supported.") | ||
|
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||
|
|
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| def TensorNetworkSerializer(*args, **kwargs) -> TensorNetworkSerializerType: | ||
| """Constructs a tensor network serializer with the specified data type. If a | ||
| ``dtype`` keyword argument is not provided, a ``TensorNetworkSerializerC128`` | ||
| instance will be returned. | ||
| Args: | ||
| *args: Positional arguments to pass to the tensor network serializer constructor. | ||
| **kwargs: Keyword arguments to pass to the tensor network serializer constructor. | ||
| Returns: | ||
| Tensor network serializer instance. | ||
| """ | ||
| dtype = kwargs.pop("dtype", np.complex128) | ||
| if np.dtype(dtype) == np.complex64: | ||
| return TensorNetworkSerializerC64(*args, **kwargs) | ||
| elif np.dtype(dtype) == np.complex128: | ||
| return TensorNetworkSerializerC128(*args, **kwargs) | ||
| else: | ||
| raise TypeError(f"Data type '{dtype}' is not supported.") |
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