2026 black

refraction-ray · refraction-ray · commit 7b170ecab8a9 · 2026-01-20T10:23:33.000+08:00
diff --git a/benchmarks/scripts/benchmark.py b/benchmarks/scripts/benchmark.py
@@ -2,7 +2,6 @@
 import os
 import utils
 
-
 if __name__ == "__main__":
     _uuid = str(uuid.uuid4())
     nwires, nlayer, nitrs, timeLimit, isgpu, minus, path = utils.arg()
diff --git a/benchmarks/scripts/qml_benchmark.py b/benchmarks/scripts/qml_benchmark.py
@@ -2,7 +2,6 @@
 import os
 import utils
 
-
 if __name__ == "__main__":
     _uuid = str(uuid.uuid4())
     nwires, nlayer, nitrs, timeLimit, isgpu, minus, path, nbatch = utils.arg(qml=True)
diff --git a/benchmarks/scripts/utils.py b/benchmarks/scripts/utils.py
@@ -9,7 +9,6 @@
 import optax
 import tensorcircuit as tc
 
-
 qml_data = {}
 
 
diff --git a/docs/source/tutorials/tfim_vqe.ipynb b/docs/source/tutorials/tfim_vqe.ipynb
@@ -450,7 +450,7 @@
     "\n",
     "    def update(i, opt_state):\n",
     "        param = get_params(opt_state)\n",
-    "        (value, gradient) = vqe_tfim_vvag(param, n, nlayers)\n",
+    "        value, gradient = vqe_tfim_vvag(param, n, nlayers)\n",
     "        return value, opt_update(i, gradient, opt_state)\n",
     "\n",
     "    for i in range(maxiter):\n",
diff --git a/docs/source/tutorials/tfim_vqe_cn.ipynb b/docs/source/tutorials/tfim_vqe_cn.ipynb
@@ -447,7 +447,7 @@
     "\n",
     "    def update(i, opt_state):\n",
     "        param = get_params(opt_state)\n",
-    "        (value, gradient) = vqe_tfim_vvag(param, n, nlayers)\n",
+    "        value, gradient = vqe_tfim_vvag(param, n, nlayers)\n",
     "        return value, opt_update(i, gradient, opt_state)\n",
     "\n",
     "    for i in range(maxiter):\n",
diff --git a/examples/circuit_compiler.py b/examples/circuit_compiler.py
@@ -4,7 +4,6 @@
 
 import tensorcircuit as tc
 
-
 c = tc.Circuit(3)
 c.rx(0, theta=0.2)
 c.rz(0, theta=-0.3)
diff --git a/examples/hchainhamiltonian.py b/examples/hchainhamiltonian.py
@@ -18,7 +18,6 @@
 
 import tensorcircuit as tc
 
-
 n = 4
 multiplicity = 1
 geometry = [("H", (0, 0, 0.95 * i)) for i in range(n)]
diff --git a/examples/lennard_jones_optimization.py b/examples/lennard_jones_optimization.py
@@ -16,7 +16,6 @@
 import matplotlib.pyplot as plt
 import tensorcircuit as tc
 
-
 tc.set_dtype("float64")  # Use tc for universal control
 K = tc.set_backend("jax")
 
diff --git a/examples/multi_host/multicontroller_vqe.py b/examples/multi_host/multicontroller_vqe.py
@@ -17,7 +17,6 @@
 import tensorcircuit as tc
 from tensorcircuit.experimental import DistributedContractor, broadcast_py_object
 
-
 # --- Static Configuration ---
 NUM_DEVICES_TOTAL = 4
 os.environ["XLA_FLAGS"] = f"--xla_force_host_platform_device_count={NUM_DEVICES_TOTAL}"
diff --git a/examples/multi_host/multicontroller_vqe_with_path.py b/examples/multi_host/multicontroller_vqe_with_path.py
@@ -17,7 +17,6 @@
 import tensorcircuit as tc
 from tensorcircuit.experimental import DistributedContractor, broadcast_py_object
 
-
 # --- Static Configuration ---
 NUM_DEVICES_TOTAL = 4
 os.environ["XLA_FLAGS"] = f"--xla_force_host_platform_device_count={NUM_DEVICES_TOTAL}"
diff --git a/examples/multi_host/pathfinding.py b/examples/multi_host/pathfinding.py
@@ -12,7 +12,6 @@
 import tensorcircuit as tc
 from tensorcircuit.experimental import DistributedContractor
 
-
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 
diff --git a/examples/multi_host/slurm_vqe_with_path.py b/examples/multi_host/slurm_vqe_with_path.py
@@ -17,7 +17,6 @@
 import tensorcircuit as tc
 from tensorcircuit.experimental import DistributedContractor, broadcast_py_object
 
-
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 
diff --git a/examples/xyzmodel_tebd_obc_imag.py b/examples/xyzmodel_tebd_obc_imag.py
@@ -8,7 +8,6 @@
 import scipy
 import tensorcircuit as tc
 
-
 K = tc.set_backend("jax")
 tc.set_dtype("complex128")
 
diff --git a/tensorcircuit/applications/dqas.py b/tensorcircuit/applications/dqas.py
@@ -24,7 +24,6 @@
 import scipy as sp
 import tensorflow as tf
 
-
 Array = Any  # np.array
 Opt = Any  # tf.keras.optimizer
 Model = Any  # tf.keras.Model
diff --git a/tensorcircuit/applications/vags.py b/tensorcircuit/applications/vags.py
@@ -317,15 +317,15 @@ def qaoa_block_vag(
     with tf.GradientTape() as t:
         t.watch(pnnp.values)  # type: ignore
         loss = exp_forward(pnnp, preset, gdata, f)
-    gr = t.gradient(loss, pnnp.values)  # type:ignore
+    gr = t.gradient(loss, pnnp.values)  # type: ignore
     if gr is None:
         # if all gates in preset are not trainable, then gr returns None instead of 0s
         gr = tf.zeros_like(pnnp)
     else:
         gr = cons.backend.real(gr)
         gr = tf.where(tf.math.is_nan(gr), 0.0, gr)
         # if all gates in preset are not trainable, then gr returns None instead of 0s
-        gr = pnnp.with_values(gr)  # type:ignore
+        gr = pnnp.with_values(gr)  # type: ignore
 
     gr = cons.backend.real(gr)
 
diff --git a/tensorcircuit/applications/vqes.py b/tensorcircuit/applications/vqes.py
@@ -22,7 +22,6 @@
 from ..quantum import generate_local_hamiltonian
 from .. import gates as G
 
-
 Tensor = Any
 Array = Any
 Model = Any
diff --git a/tensorcircuit/backends/cupy_backend.py b/tensorcircuit/backends/cupy_backend.py
@@ -85,7 +85,7 @@ def norm(self, tensor: Tensor) -> Tensor:
         return cp.linalg.norm(tensor)
 
     def shape_tuple(self, tensor: Tensor) -> Tuple[int]:
-        return tensor.shape  # type:ignore
+        return tensor.shape  # type: ignore
 
     def tensordot(
         self, a: Tensor, b: Tensor, axes: Union[int, Sequence[Sequence[int]]]
diff --git a/tensorcircuit/basecircuit.py b/tensorcircuit/basecircuit.py
@@ -33,7 +33,6 @@
 from .simplify import _split_two_qubit_gate
 from .utils import arg_alias
 
-
 Gate = gates.Gate
 Tensor = Any
 
diff --git a/tensorcircuit/channels.py b/tensorcircuit/channels.py
@@ -14,7 +14,6 @@
 from . import gates
 from .gates import array_to_tensor
 
-
 thismodule = sys.modules[__name__]
 
 Gate = gates.Gate
diff --git a/tensorcircuit/cloud/wrapper.py b/tensorcircuit/cloud/wrapper.py
@@ -19,7 +19,6 @@
 from .apis import submit_task, get_device
 from .abstraction import Device
 
-
 logger = logging.getLogger(__name__)
 Tensor = Any
 
@@ -88,10 +87,8 @@ def sample_expectation_ps(
     """
     Deprecated, please use :py:meth:`tensorcircuit.cloud.wrapper.batch_expectation_ps`.
     """
-    logger.warning(
-        "This method is deprecated and not maintained, \
-        please use `tensorcircuit.cloud.wrapper.batch_expectation_ps` instead"
-    )
+    logger.warning("This method is deprecated and not maintained, \
+        please use `tensorcircuit.cloud.wrapper.batch_expectation_ps` instead")
     c1 = Circuit.from_qir(c.to_qir())
     if x is None:
         x = []
diff --git a/tensorcircuit/experimental.py b/tensorcircuit/experimental.py
@@ -18,7 +18,6 @@
 from .gates import Gate
 from .timeevol import hamiltonian_evol, evol_global, evol_local
 
-
 # for backward compatibility
 
 Tensor = Any
@@ -582,7 +581,7 @@ def broadcast_py_object_jax(obj: Any) -> Any:
     send_arr_uint8 = np.frombuffer(data, dtype=np.uint8)
     padded_length = (length + 3) // 4 * 4
     if send_arr_uint8.size < padded_length:
-        send_arr_uint8 = np.pad(  #  type: ignore
+        send_arr_uint8 = np.pad(  # type: ignore
             send_arr_uint8, (0, padded_length - send_arr_uint8.size), mode="constant"
         )
     send_arr_int32 = send_arr_uint8.astype(np.int32)
diff --git a/tensorcircuit/fgs.py b/tensorcircuit/fgs.py
@@ -1234,7 +1234,7 @@ def charge_moment(
         self, alpha: Tensor, n: int, subsystems_to_trace_out: List[int]
     ) -> Tensor:
         rho = quantum.reduced_density_matrix(self.state, subsystems_to_trace_out)
-        l = rho.shape[-1]  # type:ignore
+        l = rho.shape[-1]  # type: ignore
         r = np.eye(l)
         L = int(np.log(l) / np.log(2) + 0.001)
         qa = np.diagonal(
diff --git a/tensorcircuit/interfaces/torch.py b/tensorcircuit/interfaces/torch.py
@@ -9,7 +9,6 @@
 from ..utils import is_sequence
 from .tensortrans import general_args_to_backend
 
-
 Tensor = Any
 
 # TODO(@refraction-ray): new paradigm compatible with torch functional transformation
diff --git a/tensorcircuit/noisemodel.py b/tensorcircuit/noisemodel.py
@@ -62,7 +62,7 @@ def add_noise(
         """
         if gate_name == "readout":
             assert qubit is None
-            self.readout_error = kraus  # type:ignore
+            self.readout_error = kraus  # type: ignore
             return
 
         gate_name = AbstractCircuit.standardize_gate(gate_name)
@@ -85,7 +85,7 @@ def condition(d: Dict[str, Any]) -> bool:
                 description = (gate_name, idx)
 
                 # https://stackoverflow.com/questions/1107210/python-create-function-in-a-loop-capturing-the-loop-variable
-                def condition(  # type:ignore
+                def condition(  # type: ignore
                     d: Dict[str, Any], _idx: Sequence[Any]
                 ) -> bool:
                     # avoid bad black style because the long is too long
@@ -176,13 +176,13 @@ def apply_qir_with_noise(
                         c.unitary_kraus(
                             krauslist,
                             *d["index"],
-                            status=status[quantum_index],  #  type: ignore
+                            status=status[quantum_index],  # type: ignore
                         )
                     else:
                         c.general_kraus(
                             krauslist,
                             *d["index"],
-                            status=status[quantum_index],  #  type: ignore
+                            status=status[quantum_index],  # type: ignore
                         )
                     quantum_index += 1
 
@@ -269,7 +269,7 @@ def sample_expectation_ps_noisfy(
         else:
 
             def mcsim(statusc: Optional[Tensor], status: Optional[Tensor]) -> Tensor:
-                cnoise = circuit_with_noise(c, noise_conf, statusc)  #  type: ignore
+                cnoise = circuit_with_noise(c, noise_conf, statusc)  # type: ignore
                 return cnoise.sample_expectation_ps(
                     x=x,
                     y=y,
@@ -340,7 +340,7 @@ def expectation_noisfy(
         else:
 
             def mcsim(status: Optional[Tensor]) -> Tensor:
-                cnoise = circuit_with_noise(c, noise_conf, status)  #  type: ignore
+                cnoise = circuit_with_noise(c, noise_conf, status)  # type: ignore
                 return cnoise.expectation(*ops, **kws)
 
             mcsim_vmap = backend.vmap(mcsim, vectorized_argnums=0)
diff --git a/tensorcircuit/quditcircuit.py b/tensorcircuit/quditcircuit.py
@@ -23,7 +23,6 @@
 from .quantum import QuOperator, QuVector
 from .quditgates import SINGLE_BUILDERS, TWO_BUILDERS
 
-
 Tensor = Any
 SAMPLE_FORMAT = Literal["sample_bin", "count_dict_bin"]
 
diff --git a/tensorcircuit/results/qem/qem_methods.py b/tensorcircuit/results/qem/qem_methods.py
@@ -234,14 +234,14 @@ def dd_rule(slack_length: int, spacing: int = -1) -> Any:
 
     if iscount is True:
         sumcount = dict(
-            functools.reduce(operator.add, map(collections.Counter, exp))  # type:ignore
-        )  # type:ignore
+            functools.reduce(operator.add, map(collections.Counter, exp))  # type: ignore
+        )  # type: ignore
         result = {k: sumcount[k] / num_trials for k in sumcount.keys()}
     else:
-        result = np.mean(exp)  # type:ignore
+        result = np.mean(exp)  # type: ignore
 
     if full_output is True:
-        result = [result, c3]  # type:ignore
+        result = [result, c3]  # type: ignore
 
     # def executortc(c):
     #     c = Circuit.from_qiskit(c, c.num_qubits)
@@ -257,7 +257,7 @@ def dd_rule(slack_length: int, spacing: int = -1) -> Any:
     #     full_output=full_output,
     # )
 
-    return result  # type:ignore
+    return result  # type: ignore
 
 
 def rc_candidates(gate: Gate) -> List[Any]:
@@ -371,13 +371,13 @@ def apply_rc(
 
     if iscount is True:
         sumcount = dict(
-            functools.reduce(operator.add, map(collections.Counter, exp))  # type:ignore
-        )  # type:ignore
+            functools.reduce(operator.add, map(collections.Counter, exp))  # type: ignore
+        )  # type: ignore
         result = {k: sumcount[k] / num_to_average for k in sumcount.keys()}
     else:
-        result = np.mean(exp)  # type:ignore
+        result = np.mean(exp)  # type: ignore
 
-    return result, circuit_list  # type:ignore
+    return result, circuit_list  # type: ignore
 
 
 # TODO(yuqinchen) add executor with batch ability
diff --git a/tensorcircuit/results/readout_mitigation.py b/tensorcircuit/results/readout_mitigation.py
@@ -31,7 +31,6 @@
 from ..circuit import Circuit
 from ..utils import is_sequence
 
-
 Tensor = Any
 
 
diff --git a/tensorcircuit/templates/lattice.py b/tensorcircuit/templates/lattice.py
@@ -2,6 +2,7 @@
 """
 The lattice module for defining and manipulating lattice geometries.
 """
+
 import logging
 import abc
 from typing import (
@@ -25,7 +26,6 @@
 
 from .. import backend
 
-
 # This block resolves a name resolution issue for the static type checker (mypy).
 # GOAL:
 #   Keep `matplotlib` as an optional dependency, so it is only imported
@@ -478,7 +478,7 @@ def show(
                     else:
                         for i, j in bonds:
                             p1, p2 = self._coordinates[i], self._coordinates[j]
-                            if self.dimensionality == 1:  #  type: ignore
+                            if self.dimensionality == 1:  # type: ignore
 
                                 ax.plot([p1[0], p2[0]], [0, 0], **plot_bond_kwargs)  # type: ignore
                             else:
diff --git a/tests/test_calibrating.py b/tests/test_calibrating.py
@@ -5,7 +5,6 @@
 from pytest_lazyfixture import lazy_fixture as lf
 from scipy.optimize import curve_fit
 
-
 thisfile = os.path.abspath(__file__)
 modulepath = os.path.dirname(os.path.dirname(thisfile))
 
diff --git a/tests/test_channels.py b/tests/test_channels.py
@@ -5,7 +5,6 @@
 from pytest_lazyfixture import lazy_fixture as lf
 from scipy.optimize import minimize
 
-
 thisfile = os.path.abspath(__file__)
 modulepath = os.path.dirname(os.path.dirname(thisfile))
 
diff --git a/tests/test_keras.py b/tests/test_keras.py
@@ -11,7 +11,6 @@
 import tensorflow as tf
 import tensorcircuit as tc
 
-
 dtype = np.complex128
 tfdtype = tf.complex128
 
diff --git a/tests/test_mpscircuit.py b/tests/test_mpscircuit.py
@@ -16,7 +16,6 @@
 sys.path.insert(0, modulepath)
 import tensorcircuit as tc
 
-
 N = 8
 D = 6
 split = tc.cons.split_rules(max_singular_values=D)
