Changes to QBC and RB apps

README.md

@@ -165,6 +165,29 @@ Create a `config.json` file with the following structure:
   ]
 }
 ```
+### Additional arguments
+
+Additional arguments can be passed to quantum applications in the "jobs" array though `app_args' objects:
+
+```
+{ "type": "RB",
+  "app_args": {
+    "benchmarks": list of lists, each containing the qubit numbers on which one- or two-qubit RBs will be run, # [[0],[1,2]]
+    "depths":     list of integers representing the different number of Clifford gates employed in the RB, # [2,4,8,16]
+    "reps":       integer representing the number of times circuits of a particular depth are generated, # 10
+  }
+}
+
+{ "type": "QBC",
+  "app_args": {
+    "pqc_number" :    integer in [2,5,15] representing the parametrized quantum circuit with the same number
+                      in figure 2 of Adv. Quantum Technol. 2, 1900070 (2019)
+    "training_size" : integer representing the number of feature vectors in the training dataset # 20
+    "max_iters" :     integer representing the maximum number of iterations in the model's training
+  }
+}
+```
+
 
 For detailed configuration options, refer to the [JSON schema](qstone/utils/config_schema.py).
 

qstone/apps/QBC.py

@@ -1,6 +1,9 @@
 """QBC computations steps."""
 
+import base64
 import os
+import pickle
+import sys
 
 import numpy
 from pandera import Check, Column, DataFrameSchema
@@ -12,10 +15,15 @@
 from qstone.utils.utils import ComputationStep, trace
 
 
+def _to_ob(string):
+    return pickle.loads(base64.b64decode(string.encode("utf-8")))
+
+
 @trace(
     computation_type="QBC",
     computation_step=ComputationStep.RUN,
     label="QASM_GENERATION",
+    logging_level=4,
 )
 def generate_vqc_qasm(pqc_number, num_qubits, datum, parameters):
     """
@@ -80,6 +88,7 @@ def generate_vqc_qasm(pqc_number, num_qubits, datum, parameters):
     computation_type="QBC",
     computation_step=ComputationStep.RUN,
     label="MPI_COMMUNICATION",
+    logging_level=4,
 )
 def mpi_communication(data, comm, bcast=True):
     """MPI communication wrapper"""
@@ -90,6 +99,7 @@ def mpi_communication(data, comm, bcast=True):
     computation_type="QBC",
     computation_step=ComputationStep.RUN,
     label="LOSS_COMPUTATION",
+    logging_level=3,
 )
 def loss(
     parameters,
@@ -124,16 +134,15 @@ def loss(
             counts = response["counts"]
         else:
             print("ERROR: counts not found in qpu response.")
-            quit()
-            counts = response
+            sys.exit()
         probs = {key: counts[key] / shots for key in counts.keys()}
-        loss -= probs[str(labels[i])] / training_size
+        if str(labels[i]) in probs.keys():
+            loss -= probs[str(labels[i])] / training_size
     print(f"partial loss for rank {comm.Get_rank()}: {loss}", flush=True)
-    temp = mpi_communication(loss, comm, bcast=False)
-    loss = temp
-    print(f"total loss: {loss}", flush=True)
+    total_loss = mpi_communication(loss, comm, bcast=False)
+    print(f"total loss: {total_loss}", flush=True)
 
-    return loss
+    return total_loss
 
 
 class QBC(Computation):  # pylint:disable=invalid-name
@@ -179,6 +188,25 @@ def __init__(self, cfg: dict):
         self.size = self.comm.Get_size()
         self.rank = self.comm.Get_rank()
 
+        self.num_required_qubits = int(
+            os.environ.get("NUM_QUBITS", cfg.get("num_required_qubits", 4))
+        )
+        self.shots = int(os.environ.get("NUM_SHOTS", str(cfg.get("shots", 64))))
+        app_args: dict = {}
+        env_app_args = os.environ.get("APP_ARGS", "")
+        if env_app_args != "":
+            loaded = _to_ob(env_app_args)
+            if isinstance(loaded, dict):
+                app_args = loaded
+        else:
+            pass
+        if "pqc_number" in app_args.keys():
+            self.pqc_number = int(app_args["pqc_number"])
+        if "training_size" in app_args.keys():
+            self.benchmarks = int(app_args["training_size"])
+        if "max_iters" in app_args.keys():
+            self.depths = int(app_args["max_iters"])
+
     @trace(
         computation_type=COMPUTATION_NAME,
         computation_step=ComputationStep.PRE,
@@ -225,21 +253,20 @@ def run(self, datapath: str, connection: connector.Connector):
         starts = list(sum(jobsizes[:i]) for i in range(len(jobsizes)))
         idxs = numpy.arange(starts[self.rank], starts[self.rank] + jobsizes[self.rank])
 
-        totqasms: list = []
-        totresults: list = []
-        totlosses: list = []
         if self.pqc_number in [2, 15]:
             totparameters = (
                 2 * numpy.pi * numpy.random.rand(2 * self.num_required_qubits)
             )
-        if self.pqc_number == 5:
+        elif self.pqc_number == 5:
             totparameters = (
                 2
                 * numpy.pi
                 * numpy.random.rand(
                     pow(self.num_required_qubits, 2) + 3 * self.num_required_qubits
                 )
             )
+        else:
+            raise ValueError(f"Unknown pqc_number: {self.pqc_number}")
 
         mpi_communication(totparameters, self.comm)