fix: add test

src/braket/experimental/algorithms/qc_qrl/__init__.py

@@ -0,0 +1,12 @@
+# Copyright Amazon.com Inc. or its affiliates. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License"). You
+# may not use this file except in compliance with the License. A copy of
+# the License is located at
+#
+#     http://aws.amazon.com/apache2.0/
+#
+# or in the "license" file accompanying this file. This file is
+# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
+# ANY KIND, either express or implied. See the License for the specific
+# language governing permissions and limitations under the License.

test/unit_tests/braket/experimental/algorithms/qc_qrl/test_qc_qrl.py

@@ -0,0 +1,94 @@
+from unittest.mock import patch
+
+import pytest
+
+from braket.experimental.algorithms.qc_qrl.utility.RetroRLAgent import RetroRLAgent
+from braket.experimental.algorithms.qc_qrl.utility.RetroGateModel import RetroGateModel
+
+np.set_printoptions(precision=4, edgeitems=10, linewidth=150, suppress=True)
+
+@pytest.fixture
+def common_agent_param():
+    agent_param = {}
+    # initial the RetroRLModel object
+    init_param = {}
+    method = ['retro-rl', 'retro-qrl']
+
+    for mt in method:
+        if mt == 'retro-rl':
+            init_param[mt] = {}
+            init_param[mt]['param'] = ['inputsize', 'middlesize', 'outputsize']
+        elif mt == 'retro-qrl':
+            init_param[mt] = {}
+            init_param[mt]['param'] = ['n_qubits', 'device', 'framework', 'shots', 'layers']
+
+    agent_param['init_param'] = init_param
+    # train_mode can be: "local-instance", "local-job", "hybrid-job"
+    train_mode = "hybrid-job"
+
+    data_path = 'data'
+    s3_data_path = None
+
+    agent_param["data_path"] = data_path
+    agent_param["s3_data_path"]=s3_data_path
+    agent_param["train_mode"] = train_mode
+    agent_param["episodes"] = 2
+
+    return agent_param
+
+def test_quantum_circuit_parameters(common_agent_param):
+    agent_param = common_agent_param
+
+    model_param={}
+    method = 'retro-qrl'
+    model_param[method] = {}
+    model_param[method]['n_qubits'] = [8]
+    model_param[method]['device'] = ['local']
+    model_param[method]['framework'] = ['pennylane']
+    model_param[method]['shots'] = [100]
+    model_param[method]['layers'] = [1]
+
+    agent_param['model_param'] = model_param
+
+    n_qubits = model_param[method]['n_qubits'][0]
+    device = model_param[method]['device'][0]
+    framework = model_param[method]['framework'][0]
+    shots = model_param[method]['shots'][0]
+    layers = model_param[method]['layers'][0]
+
+    model_name = "{}_{}_{}_{}_{}".format(n_qubits, device, framework, shots, layers)
+    agent_param["model_name"] = model_name
+
+    agent_param["train_mode"]="local-instance"
+
+    retro_qrl_agent = RetroRLAgent(build_model=True, method=method, **agent_param)
+
+    quantum_param_sum = 0
+    for param in retro_qrl_agent.NN.parameters():
+        quantum_param_sum = quantum_param_sum + param.numel()
+
+    assert quantum_param_sum == model_param[method]["n_qubits"][0]
+
+def test_classical_circuit_parameters(common_agent_param):
+    agent_param = common_agent_param
+
+    model_param={}
+    method = 'retro-rl'
+    model_param[method] = {}
+    model_param[method]['inputsize'] = [256]
+    model_param[method]['middlesize'] = [256]
+    model_param[method]['outputsize'] = [1]
+
+    agent_param['model_param'] = model_param
+    model_name = f"{model_param[method]['inputsize'][0]}_{model_param[method]['middlesize'][0]}_{model_param[method]['outputsize'][0]}"
+    agent_param["model_name"] = model_name
+
+    agent_param["train_mode"]="local-instance"
+
+    retro_crl_agent = RetroRLAgent(build_model=True, method=method, **agent_param)
+
+    classical_param_sum = 0
+    for param in retro_crl_agent.NN.parameters():
+        classical_param_sum = classical_param_sum + param.numel()
+
+    assert classical_param_sum == model_param[method]['inputsize'][0]*model_param[method]['middlesize'][0]*model_param[method]['outputsize'][0]