Merge pull request #2 from QuantumJaeYoo/fix_format

Fix format

Author: QuantumJaeYoo

benchmarks/scripts/benchmark_cuquantum_ops.py

@@ -14,6 +14,7 @@
 SRC = os.path.dirname(os.path.realpath(__file__))
 os.environ['TEST_REPORT_FILE_PREFIX'] = os.path.join(SRC, 'reports/')
 
+
 @dataclass(frozen=True)
 class BenchmarkParams:
     """Frozen dataclass to store the parameters for the benchmark"""
@@ -22,25 +23,31 @@ class BenchmarkParams:
     batch_size: int
     n_iters: int = 100
 
+
 _test_params_1 = BenchmarkParams(n_qubits=20, n_moments=15, batch_size=5)
-_test_params_2 = BenchmarkParams(n_qubits=21, n_moments=25, batch_size=5) # more depth
-_test_params_3 = BenchmarkParams(n_qubits=22, n_moments=15, batch_size=5, n_iters=10)
+_test_params_2 = BenchmarkParams(n_qubits=21, n_moments=25,
+                                 batch_size=5)  # more depth
+_test_params_3 = BenchmarkParams(n_qubits=22,
+                                 n_moments=15,
+                                 batch_size=5,
+                                 n_iters=10)
 
 TEST_PARAMS_EXPECTATION = [
     _test_params_1,
-    _test_params_2, # uncomment for depth params
-    ]
+    _test_params_2,  # uncomment for depth params
+]
 TEST_PARAMS_SAMPLED_EXPECTATION = [
     _test_params_1,
-    _test_params_2, # uncomment for depth params
-    ]
+    _test_params_2,  # uncomment for depth params
+]
 TEST_PARAMS_SAMPLES = [
     _test_params_1,
-    _test_params_2, # uncomment for depth params
-    ]
+    _test_params_2,  # uncomment for depth params
+]
 TEST_PARAMS_STATE = [
     _test_params_3,
-    ]
+]
+
 
 def _measure_median_runtime(
         fn,
@@ -138,7 +145,6 @@ def benchmark_expectation_cpu(self):
 
         return benchmark_values
 
-
     def benchmark_expectation_cuquantum(self):
         """Benchmark expectation simulator on cpu."""
 
@@ -192,7 +198,7 @@ def benchmark_expectation_cuquantum(self):
         self.report_benchmark(**benchmark_values)
 
         return benchmark_values
-    
+
     def benchmark_sampled_expectation_cpu(self, params=None):
         params = params if params else self.params
         n_qubits = params.n_qubits
@@ -248,7 +254,7 @@ def benchmark_sampled_expectation_cpu(self, params=None):
         self.report_benchmark(**benchmark_values)
 
         return benchmark_values
-    
+
     def benchmark_sampled_expectation_cuquantum(self, params=None):
         params = params if params else self.params
         n_qubits = params.n_qubits
@@ -424,7 +430,6 @@ def benchmark_state_cpu(self, params=None):
 
         circuit_batch_tensor = util.convert_to_tensor(circuit_batch)
 
-
         symbol_values_array = np.array(
             [[resolver[symbol]
               for symbol in symbol_names]
@@ -474,7 +479,6 @@ def benchmark_state_cuquantum(self, params=None):
 
         circuit_batch_tensor = util.convert_to_tensor(circuit_batch)
 
-
         symbol_values_array = np.array(
             [[resolver[symbol]
               for symbol in symbol_names]
@@ -512,13 +516,11 @@ def benchmark_state_cuquantum(self, params=None):
         return benchmark_values
 
 
-
-class SimulateExpectationCuquantumTest(tf.test.TestCase, parameterized.TestCase):
+class SimulateExpectationCuquantumTest(tf.test.TestCase,
+                                       parameterized.TestCase):
     """Tests tfq_simulate_expectation."""
 
-    @parameterized.parameters(
-        TEST_PARAMS_EXPECTATION
-    )
+    @parameterized.parameters(TEST_PARAMS_EXPECTATION)
     def test_simulate_expectation_cpu_vs_cuquantum(self, params):
         """Make sure that cuquantum version is faster."""
         bench = RandomCircuitBenchmark(params)
@@ -532,9 +534,7 @@ def test_simulate_expectation_cpu_vs_cuquantum(self, params):
         # cuQuantum op should be faster than CPU op.
         self.assertGreater(cpu_median_time, gpu_median_time)
 
-    @parameterized.parameters(
-        TEST_PARAMS_SAMPLED_EXPECTATION
-    )
+    @parameterized.parameters(TEST_PARAMS_SAMPLED_EXPECTATION)
     def test_simulate_sampled_expectation_cpu_vs_cuquantum(self, params):
         """Make sure that cpu & gpu(cuquantum) ops have the same results."""
         bench = RandomCircuitBenchmark(params)
@@ -548,9 +548,7 @@ def test_simulate_sampled_expectation_cpu_vs_cuquantum(self, params):
         # cuQuantum op should be faster than CPU op.
         self.assertGreater(cpu_median_time, gpu_median_time)
 
-    @parameterized.parameters(
-        TEST_PARAMS_SAMPLES
-    )
+    @parameterized.parameters(TEST_PARAMS_SAMPLES)
     def test_simulate_samples_cpu_vs_cuquantum(self, params):
         """Make sure that cpu & gpu(cuquantum) ops have the same results."""
         bench = RandomCircuitBenchmark(params)
@@ -564,9 +562,7 @@ def test_simulate_samples_cpu_vs_cuquantum(self, params):
         # cuQuantum op should be faster than CPU op.
         self.assertGreater(cpu_median_time, gpu_median_time)
 
-    @parameterized.parameters(
-        TEST_PARAMS_STATE
-    )
+    @parameterized.parameters(TEST_PARAMS_STATE)
     def test_simulate_state_cpu_vs_cuquantum(self, params):
         """Make sure that cpu & gpu(cuquantum) ops have the same results."""
         bench = RandomCircuitBenchmark(params)

release/setup.py

@@ -92,7 +92,6 @@ def has_ext_modules(self):
     project_name = 'tfq-nightly'
     build_version = build_version + '.dev' + str(date.today()).replace('-', '')
 
-
 setup(
     name=project_name,
     version=build_version,

tensorflow_quantum/python/layers/circuit_executors/sampled_expectation_test.py

@@ -404,7 +404,7 @@ def test_sampled_expectation_simple_tf_train(self, use_cuquantum):
             # GPU is not set. Ignores this sub-test.
             self.skipTest("GPU is not set. Ignoring gpu tests...")
         tf.random.set_seed(RANDOM_SEED)
-        initializer = tf.keras.initializers.RandomUniform(0, 2*np.pi)
+        initializer = tf.keras.initializers.RandomUniform(0, 2 * np.pi)
         bit = cirq.GridQubit(0, 0)
         circuit = cirq.Circuit(cirq.rx(sympy.Symbol('theta'))(bit))
         layer = sampled_expectation.SampledExpectation(
@@ -447,7 +447,7 @@ def test_simple_param_value_input(self, backend, use_cuquantum):
             # GPU is not set. Ignores this sub-test.
             self.skipTest("GPU is not set. Ignoring gpu tests...")
         tf.random.set_seed(RANDOM_SEED)
-        initializer = tf.keras.initializers.RandomUniform(0, 2*np.pi)
+        initializer = tf.keras.initializers.RandomUniform(0, 2 * np.pi)
         bit = cirq.GridQubit(0, 0)
         symbols = sympy.symbols('x y z')
         circuit = _gen_single_bit_rotation_problem(
@@ -498,7 +498,7 @@ def test_simple_op_input(self, backend, use_cuquantum):
             # GPU is not set. Ignores this sub-test.
             self.skipTest("GPU is not set. Ignoring gpu tests...")
         tf.random.set_seed(RANDOM_SEED)
-        initializer = tf.keras.initializers.RandomUniform(0, 2*np.pi)
+        initializer = tf.keras.initializers.RandomUniform(0, 2 * np.pi)
         bit = cirq.GridQubit(0, 0)
         symbols = sympy.symbols('x y z')
         ops = util.convert_to_tensor([[cirq.Z(bit)], [cirq.Z(bit)]])
@@ -555,7 +555,7 @@ def test_simple_op_and_param_input(self, backend, use_cuquantum):
             # GPU is not set. Ignores this sub-test.
             self.skipTest("GPU is not set. Ignoring gpu tests...")
         tf.random.set_seed(RANDOM_SEED)
-        initializer = tf.keras.initializers.RandomUniform(0, 2*np.pi)
+        initializer = tf.keras.initializers.RandomUniform(0, 2 * np.pi)
         bit = cirq.GridQubit(0, 0)
         symbols = sympy.symbols('x y z')
         ops = util.convert_to_tensor([[cirq.Z(bit)], [cirq.Z(bit)]])
@@ -616,7 +616,7 @@ def test_dnn_qnn_dnn(self, backend, use_cuquantum):
             # GPU is not set. Ignores this sub-test.
             self.skipTest("GPU is not set. Ignoring gpu tests...")
         tf.random.set_seed(RANDOM_SEED)
-        initializer = tf.keras.initializers.RandomUniform(0, 2*np.pi)
+        initializer = tf.keras.initializers.RandomUniform(0, 2 * np.pi)
         bit = cirq.GridQubit(0, 0)
         symbols = sympy.symbols('x, y, z')
         circuits = util.convert_to_tensor([