From c55cddaabb251bebf34605d49cfc4c1cfd8091ff Mon Sep 17 00:00:00 2001 From: flowerthrower Date: Thu, 27 Aug 2026 12:32:00 +0200 Subject: [PATCH] =?UTF-8?q?=F0=9F=90=9B=20Honor=20Gymnasium=20seeds=20for?= =?UTF-8?q?=20circuit=20sampling?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Signed-off-by: flowerthrower Assisted-by: GPT 5.6 via Codex --- src/mqt/predictor/rl/helper.py | 4 ++-- src/mqt/predictor/rl/predictorenv.py | 7 +++++-- 2 files changed, 7 insertions(+), 4 deletions(-) diff --git a/src/mqt/predictor/rl/helper.py b/src/mqt/predictor/rl/helper.py index 25812b453..66cd7737b 100644 --- a/src/mqt/predictor/rl/helper.py +++ b/src/mqt/predictor/rl/helper.py @@ -47,14 +47,14 @@ def get_state_sample(max_qubits: int, path_training_circuits: Path, rng: Generat Raises: RuntimeError: If no quantum circuit could be read from the training circuits folder. """ - file_list = list(path_training_circuits.glob("*.qasm")) + file_list = sorted(path_training_circuits.glob("*.qasm")) path_zip = path_training_circuits / "training_data_compilation.zip" if len(file_list) == 0 and path_zip.exists(): with zipfile.ZipFile(str(path_zip), "r") as zip_ref: zip_ref.extractall(path_training_circuits) - file_list = list(path_training_circuits.glob("*.qasm")) + file_list = sorted(path_training_circuits.glob("*.qasm")) assert len(file_list) > 0 found_suitable_qc = False diff --git a/src/mqt/predictor/rl/predictorenv.py b/src/mqt/predictor/rl/predictorenv.py index c667f8c0d..7306f0ac3 100644 --- a/src/mqt/predictor/rl/predictorenv.py +++ b/src/mqt/predictor/rl/predictorenv.py @@ -177,7 +177,6 @@ def __init__( self.layout: TranspileLayout | None = None self.has_parameterized_gates = False - self.rng = np.random.default_rng(10) operation_spaces = { operation: Box(low=0, high=1, shape=(1,), dtype=np.float32) for operation in OBSERVATION_OPERATIONS @@ -419,7 +418,11 @@ def reset( self.filename = str(qc) current_circuit_name = Path(str(qc)).stem else: - self.state, self.filename = get_state_sample(self.device.num_qubits, self.path_training_circuits, self.rng) + self.state, self.filename = get_state_sample( + self.device.num_qubits, + self.path_training_circuits, + self.np_random, + ) current_circuit_name = Path(self.filename).stem self.action_space = Discrete(len(self.action_set.keys()))