migrate to pyproject.toml

Author: FlorianFuerrutter

genQC/__init__.py

@@ -1 +1 @@
-__version__ = "0.2.4"
+__version__ = "0.2.5"

genQC/benchmark/bench_compilation.py

@@ -2,14 +2,14 @@
 
 # AUTOGENERATED! DO NOT EDIT! File to edit: ../../src/benchmark/bench_compilation.ipynb.
 
-# %% auto 0
+# %% auto #0
 __all__ = ['sigma_x', 'sigma_y', 'sigma_z', 'SpecialUnitaries', 'qubit_tensor_product', 'BaseHamiltonian', 'IsingHamiltonian',
            'XXZHamiltonian']
 
-# %% ../../src/benchmark/bench_compilation.ipynb 2
+# %% ../../src/benchmark/bench_compilation.ipynb #a593dee3-594e-4760-a02d-db5559f5f25f
 from ..imports import *
 
-# %% ../../src/benchmark/bench_compilation.ipynb 5
+# %% ../../src/benchmark/bench_compilation.ipynb #e9337291-4d9e-4524-8fe8-9d198a2abb24
 class SpecialUnitaries:
     """Special unitary matrices to benchmark compilation."""
 
@@ -27,7 +27,7 @@ def QFT(num_qubits: int) -> torch.Tensor:
         U *= 1.0/np.sqrt(N)   
         return U
 
-# %% ../../src/benchmark/bench_compilation.ipynb 9
+# %% ../../src/benchmark/bench_compilation.ipynb #86c32afa-32ad-4a52-9aa6-144d8f76f1f2
 sigma_x = torch.tensor([[0, 1],
                         [1, 0]],
                        dtype=torch.complex128)
@@ -40,7 +40,7 @@ def QFT(num_qubits: int) -> torch.Tensor:
                         [0, -1]],
                        dtype=torch.complex128)
 
-# %% ../../src/benchmark/bench_compilation.ipynb 11
+# %% ../../src/benchmark/bench_compilation.ipynb #485317ad-e46c-4652-bd2b-89c0c03afea2
 def qubit_tensor_product(num_qubits: int, *ops: torch.Tensor, pos: int | Sequence[int]) -> torch.Tensor:
     """
     Make tensor product with identities, assumes `ops` placed at `pos` in the tensor product ordering.
@@ -64,7 +64,7 @@ def qubit_tensor_product(num_qubits: int, *ops: torch.Tensor, pos: int | Sequenc
 
     return mat
 
-# %% ../../src/benchmark/bench_compilation.ipynb 19
+# %% ../../src/benchmark/bench_compilation.ipynb #ecb265cc-521a-44fd-bf8d-c97b46938932
 class BaseHamiltonian(abc.ABC):
     """Base implementation of a Hamiltonian."""
 
@@ -94,7 +94,7 @@ def get_evolution(self, t: float | torch.Tensor, split_complex_channel: bool = F
 
         return U
 
-# %% ../../src/benchmark/bench_compilation.ipynb 21
+# %% ../../src/benchmark/bench_compilation.ipynb #8e1da512-6e2f-4eb4-aade-5cb822b6e6f9
 class IsingHamiltonian(BaseHamiltonian):
     """Implementation of the Ising Hamiltonian on a qubit chain."""
 
@@ -140,7 +140,7 @@ def _generate_matrix(self) -> torch.Tensor:
 
         self.data = ham.to(self.device)
 
-# %% ../../src/benchmark/bench_compilation.ipynb 29
+# %% ../../src/benchmark/bench_compilation.ipynb #bcff4597-de9d-436e-908a-ff683e868478
 class XXZHamiltonian(BaseHamiltonian):
     """Implementation of the XXZ Hamiltonian on a qubit chain."""
 

genQC/dataset/balancing.py

@@ -2,14 +2,14 @@
 
 # AUTOGENERATED! DO NOT EDIT! File to edit: ../../src/dataset/balancing.ipynb.
 
-# %% auto 0
+# %% auto #0
 __all__ = ['get_tensor_gate_length', 'add_balance_fn_quantile_qc_length']
 
-# %% ../../src/dataset/balancing.ipynb 2
+# %% ../../src/dataset/balancing.ipynb #06272f6f-b4e3-4504-a90a-feebbf6ad821
 from ..imports import *
 import genQC.dataset.dataset_helper as dahe
 
-# %% ../../src/dataset/balancing.ipynb 4
+# %% ../../src/dataset/balancing.ipynb #e57ce23e-30fc-434f-9443-3cf97f507b89
 def get_tensor_gate_length(clr_tensor: torch.Tensor, padding_token: int = 0) -> torch.Tensor:
     """
     Returns the gate count of a tokenized circuit.
@@ -21,7 +21,7 @@ def get_tensor_gate_length(clr_tensor: torch.Tensor, padding_token: int = 0) ->
     red_clr_tensor = (clr_tensor != padding_token).any(dim=1) # [b, t]
     return torch.count_nonzero(red_clr_tensor, dim=1)         # [b]
 
-# %% ../../src/dataset/balancing.ipynb 5
+# %% ../../src/dataset/balancing.ipynb #36032308-bd0e-4409-9db0-9d89fc258e5a
 def add_balance_fn_quantile_qc_length(indices: Union[np.ndarray, torch.Tensor], 
                                       x: Union[np.ndarray, torch.Tensor], 
                                       y: Union[np.ndarray, torch.Tensor], 

genQC/dataset/cached_dataset.py

@@ -2,20 +2,20 @@
 
 # AUTOGENERATED! DO NOT EDIT! File to edit: ../../src/dataset/cached_dataset.ipynb.
 
-# %% auto 0
+# %% auto #0
 __all__ = ['CachedOpenCLIPDatasetConfig', 'CachedOpenCLIPDataset']
 
-# %% ../../src/dataset/cached_dataset.ipynb 2
+# %% ../../src/dataset/cached_dataset.ipynb #06272f6f-b4e3-4504-a90a-feebbf6ad821
 from ..imports import *
 from .config_dataset import ConfigDataset, ConfigDatasetConfig
 from ..utils.config_loader import *
 
-# %% ../../src/dataset/cached_dataset.ipynb 3
+# %% ../../src/dataset/cached_dataset.ipynb #ac8e640e-c614-4d52-b772-c173b2682ad9
 @dataclass
 class CachedOpenCLIPDatasetConfig(ConfigDatasetConfig):
     pass
 
-# %% ../../src/dataset/cached_dataset.ipynb 4
+# %% ../../src/dataset/cached_dataset.ipynb #119077c9-999b-44f7-8099-79037503d7e7
 class CachedOpenCLIPDataset(ConfigDataset):
     """
     Adds `.caching` to the `ConfigDataset` class.

genQC/dataset/circuits_dataset.py

@@ -2,11 +2,11 @@
 
 # AUTOGENERATED! DO NOT EDIT! File to edit: ../../src/dataset/circuits_dataset.ipynb.
 
-# %% auto 0
+# %% auto #0
 __all__ = ['CircuitsConfigDatasetConfig', 'CircuitsConfigDataset', 'MixedCircuitsConfigDatasetConfig',
            'MixedCircuitsConfigDataset']
 
-# %% ../../src/dataset/circuits_dataset.ipynb 2
+# %% ../../src/dataset/circuits_dataset.ipynb #06272f6f-b4e3-4504-a90a-feebbf6ad821
 from ..imports import *
 from .cached_dataset import CachedOpenCLIPDataset, CachedOpenCLIPDatasetConfig
 from .mixed_cached_dataset import MixedCachedOpenCLIPDataset, MixedCachedOpenCLIPDatasetConfig
@@ -15,7 +15,7 @@
 from .dataset_helper import shuffle_tensor_dataset
 from ..utils.misc_utils import MemoryCleaner
 
-# %% ../../src/dataset/circuits_dataset.ipynb 4
+# %% ../../src/dataset/circuits_dataset.ipynb #016fc327-f986-4d69-b5f0-1b39466fb528
 @dataclass
 class CircuitsConfigDatasetConfig(CachedOpenCLIPDatasetConfig):
     optimized: bool
@@ -26,7 +26,7 @@ class CircuitsConfigDatasetConfig(CachedOpenCLIPDatasetConfig):
     max_params: int
     gate_pool: list[str]
 
-# %% ../../src/dataset/circuits_dataset.ipynb 5
+# %% ../../src/dataset/circuits_dataset.ipynb #36032308-bd0e-4409-9db0-9d89fc258e5a
 class CircuitsConfigDataset(CachedOpenCLIPDataset):
     """Dataset for quantum circuits, access `gate_pool` directly and all other paras with `.params_config`"""
 
@@ -56,12 +56,12 @@ def params_config(self):
             params_config = CircuitsConfigDatasetConfig(**params_config)
         return params_config   
 
-# %% ../../src/dataset/circuits_dataset.ipynb 8
+# %% ../../src/dataset/circuits_dataset.ipynb #75c9a200-f9eb-42f9-b3c3-e074e377737a
 @dataclass
 class MixedCircuitsConfigDatasetConfig(CircuitsConfigDatasetConfig, MixedCachedOpenCLIPDatasetConfig):
     pass
 
-# %% ../../src/dataset/circuits_dataset.ipynb 9
+# %% ../../src/dataset/circuits_dataset.ipynb #e804a8d7-dcf3-40e4-83a5-cd98207c8dea
 class MixedCircuitsConfigDataset(CircuitsConfigDataset, MixedCachedOpenCLIPDataset):
     """
     Dataset that uses multiple cached dataset and combines them with padding, either i) Bucket or ii) Max.

genQC/dataset/config_dataset.py

@@ -2,24 +2,24 @@
 
 # AUTOGENERATED! DO NOT EDIT! File to edit: ../../src/dataset/config_dataset.ipynb.
 
-# %% auto 0
+# %% auto #0
 __all__ = ['ConfigDatasetConfig', 'ConfigDataset']
 
-# %% ../../src/dataset/config_dataset.ipynb 2
+# %% ../../src/dataset/config_dataset.ipynb #06272f6f-b4e3-4504-a90a-feebbf6ad821
 from ..imports import *
 from ..utils.config_loader import *
 from .dataset_helper import *
 
 from huggingface_hub import snapshot_download
 
-# %% ../../src/dataset/config_dataset.ipynb 3
+# %% ../../src/dataset/config_dataset.ipynb #a2688c32-b901-4ac1-9ed6-de0dbd12108b
 @dataclass
 class ConfigDatasetConfig:
     """Config `dataclass` used for storage."""
     store_dict: dict 
     dataset_to_gpu: bool
 
-# %% ../../src/dataset/config_dataset.ipynb 4
+# %% ../../src/dataset/config_dataset.ipynb #36032308-bd0e-4409-9db0-9d89fc258e5a
 class ConfigDataset():  
     """Base class for datasets, manages loading and saving."""
 

genQC/dataset/dataset_helper.py

@@ -2,16 +2,16 @@
 
 # AUTOGENERATED! DO NOT EDIT! File to edit: ../../src/dataset/dataset_helper.ipynb.
 
-# %% auto 0
+# %% auto #0
 __all__ = ['check_duplicate_in_dataset', 'check_duplicates_in_dataset', 'shuffle_tensor_dataset', 'get_unique_elements_indices',
            'uniquify_tensor_dataset', 'balance_tensor_dataset']
 
-# %% ../../src/dataset/dataset_helper.ipynb 2
+# %% ../../src/dataset/dataset_helper.ipynb #06272f6f-b4e3-4504-a90a-feebbf6ad821
 from ..imports import *
 from ..utils.config_loader import *
 from ..utils.async_fn import run_parallel_jobs
 
-# %% ../../src/dataset/dataset_helper.ipynb 4
+# %% ../../src/dataset/dataset_helper.ipynb #36032308-bd0e-4409-9db0-9d89fc258e5a
 def check_duplicate_in_dataset(x, dataset):
     """Check if 'x' is in 'dataset'"""
     # x        ...  [   *]
@@ -22,7 +22,7 @@ def check_duplicate_in_dataset(x, dataset):
     comp = torch.all(comp, dim=1)
     return comp.any().item()         
 
-# %% ../../src/dataset/dataset_helper.ipynb 5
+# %% ../../src/dataset/dataset_helper.ipynb #2a8886b0-2b43-4c06-9992-b859d11e698e
 def check_duplicates_in_dataset(xs, dataset, return_ind=False, invert=False):
     '''
     Checks if `xs` is are `dataset`. Boolean `invert` changes if we count duplicates (False) or ones that are not in dataset (True). 
@@ -53,7 +53,7 @@ def get_comp(x, dataset):
     if return_ind: return num, comp.squeeze()  #comp is [i_xs, i_dataset] pairs
     return num
 
-# %% ../../src/dataset/dataset_helper.ipynb 9
+# %% ../../src/dataset/dataset_helper.ipynb #9ea47154-d7c2-435b-8d08-0999c744af1a
 def shuffle_tensor_dataset(x, y=None, *z, cpu_copy=True):
     '''Assumes numpy or tensor objects with same length.'''
     rand_indx = torch.randperm(x.shape[0])
@@ -86,7 +86,7 @@ def _cpu_array_index(var):
 
     return x[rand_indx]
 
-# %% ../../src/dataset/dataset_helper.ipynb 10
+# %% ../../src/dataset/dataset_helper.ipynb #c8005564-1f96-41da-94f5-16d2f9f48b2a
 def get_unique_elements_indices(tensor):
     '''Returns indices of unique_elements in `tensor`.'''
     tensor_unique, ptrs, cnt = torch.unique(tensor, dim=0, return_inverse=True, return_counts=True)
@@ -99,7 +99,7 @@ def get_unique_elements_indices(tensor):
 
     return tensor[idx], idx
 
-# %% ../../src/dataset/dataset_helper.ipynb 11
+# %% ../../src/dataset/dataset_helper.ipynb #a9295de7-54e1-435b-aeea-26746019dd95
 def uniquify_tensor_dataset(x, y=None, *z):
     '''`x` has to be tensor, assumes numpy or tensor obj for `y` and `z`'''
     x, x_idx = get_unique_elements_indices(x)
@@ -112,7 +112,7 @@ def uniquify_tensor_dataset(x, y=None, *z):
 
     return x
 
-# %% ../../src/dataset/dataset_helper.ipynb 12
+# %% ../../src/dataset/dataset_helper.ipynb #e63e9933-a2ce-47b3-a957-58705e060fc7
 def balance_tensor_dataset(x, y, *z, samples: int=None, make_unique: bool=True, y_uniques=None, shuffle_lables: bool=True, add_balance_fn: callable=None, njobs=1):
     '''Assumes `x` is tensor and `y` is tensor or numpy.'''
 

genQC/dataset/mixed_cached_dataset.py

@@ -2,25 +2,25 @@
 
 # AUTOGENERATED! DO NOT EDIT! File to edit: ../../src/dataset/mixed_cached_dataset.ipynb.
 
-# %% auto 0
+# %% auto #0
 __all__ = ['MixedCachedOpenCLIPDatasetConfig', 'MixedCachedOpenCLIPDataset']
 
-# %% ../../src/dataset/mixed_cached_dataset.ipynb 3
+# %% ../../src/dataset/mixed_cached_dataset.ipynb #06272f6f-b4e3-4504-a90a-feebbf6ad821
 from ..imports import *
 from .cached_dataset import CachedOpenCLIPDataset, CachedOpenCLIPDatasetConfig, ConfigDataset
 from .dataset_helper import *
 from ..utils.misc_utils import DataLoaders, MemoryCleaner
 from tensordict import TensorDict
 
-# %% ../../src/dataset/mixed_cached_dataset.ipynb 4
+# %% ../../src/dataset/mixed_cached_dataset.ipynb #119077c9-999b-44f7-8099-79037503d7e7
 @dataclass
 class MixedCachedOpenCLIPDatasetConfig(CachedOpenCLIPDatasetConfig):
     pad_constant: int
     collate_fn: str
     bucket_batch_size: int
     model_scale_factor: int
 
-# %% ../../src/dataset/mixed_cached_dataset.ipynb 5
+# %% ../../src/dataset/mixed_cached_dataset.ipynb #0037efb5-d3a9-46e4-94d1-3dd80297e934
 class MixedCachedOpenCLIPDataset(CachedOpenCLIPDataset):  
     """Dataset that uses multiple cached dataset and combines them with padding, either i) Bucket or ii) Max."""
 

genQC/inference/eval_metrics.py

@@ -2,14 +2,14 @@
 
 # AUTOGENERATED! DO NOT EDIT! File to edit: ../../src/inference/eval_metrics.ipynb.
 
-# %% auto 0
+# %% auto #0
 __all__ = ['BaseNorm', 'UnitaryFrobeniusNorm', 'UnitaryInfidelityNorm']
 
-# %% ../../src/inference/eval_metrics.ipynb 2
+# %% ../../src/inference/eval_metrics.ipynb #06272f6f-b4e3-4504-a90a-feebbf6ad821
 from ..imports import *
 from scipy.stats import unitary_group
 
-# %% ../../src/inference/eval_metrics.ipynb 4
+# %% ../../src/inference/eval_metrics.ipynb #ccbc4adc-098b-415a-98c8-8b80a0697d34
 class BaseNorm(abc.ABC): 
     """Base class for norms."""
 
@@ -21,7 +21,7 @@ def distance(approx_U: torch.Tensor, target_U: torch.Tensor) -> torch.Tensor: ra
     @abc.abstractmethod
     def name() -> str: raise NotImplementedError()
 
-# %% ../../src/inference/eval_metrics.ipynb 6
+# %% ../../src/inference/eval_metrics.ipynb #1b178cbc-d116-49c9-862d-16f646daa39b
 class UnitaryFrobeniusNorm(BaseNorm):
     """
     The Frobenius-Norm for unitaries: defined in https://arxiv.org/pdf/2106.05649.pdf.
@@ -38,7 +38,7 @@ def distance(approx_U: torch.Tensor, target_U: torch.Tensor) -> torch.Tensor:
     @staticmethod
     def name() -> str: return "Frobenius-Norm"
 
-# %% ../../src/inference/eval_metrics.ipynb 7
+# %% ../../src/inference/eval_metrics.ipynb #90080d81-c872-4da3-9f81-31c8908c1056
 class UnitaryInfidelityNorm(BaseNorm):
     """
     The Infidelity-Norm for unitaries: defined in https://link.aps.org/accepted/10.1103/PhysRevA.95.042318, TABLE I: 1.

genQC/inference/evaluation_helper.py

@@ -2,23 +2,23 @@
 
 # AUTOGENERATED! DO NOT EDIT! File to edit: ../../src/inference/evaluation_helper.ipynb.
 
-# %% auto 0
+# %% auto #0
 __all__ = ['get_srvs', 'get_unitaries']
 
-# %% ../../src/inference/evaluation_helper.ipynb 2
+# %% ../../src/inference/evaluation_helper.ipynb #68f0714b-e45a-46d8-aa05-d6735d4d0e33
 from ..imports import *
 from ..utils.async_fn import run_parallel_jobs
 from ..platform.simulation import Simulator 
 
-# %% ../../src/inference/evaluation_helper.ipynb 4
+# %% ../../src/inference/evaluation_helper.ipynb #f265206e-7f08-4d74-955b-25eb644adc22
 def get_srvs(simulator: Simulator, backend_obj_list: Sequence, n_jobs: int = 1, **kwargs): 
     """Returns SRVs of a given list of backen objects `backend_obj_list`."""
     def _f(backend_obj):
         return simulator.backend.schmidt_rank_vector(backend_obj, **kwargs)
 
     return run_parallel_jobs(_f, backend_obj_list, n_jobs)
 
-# %% ../../src/inference/evaluation_helper.ipynb 6
+# %% ../../src/inference/evaluation_helper.ipynb #4cf36492-a8c9-437c-850d-09148fe39eeb
 def get_unitaries(simulator: Simulator, backend_obj_list: Sequence, n_jobs: int = 1, **kwargs):
     """Returns unitaries of a given list of backen objects `backend_obj_list`."""
     def _f(backend_obj):