Merge pull request #518 from tensorflow/noisy_samples

Adds tfq.noise.samples op.

Author: jaeyoo

release/BUILD

@@ -40,6 +40,7 @@ sh_binary(
         "//tensorflow_quantum/core/ops:tfq_utility_ops_py",
         "//tensorflow_quantum/core/ops:tfq_simulate_ops_py",
         "//tensorflow_quantum/core/ops/math_ops:inner_product_op_py",
+        "//tensorflow_quantum/core/ops/noise:noisy_samples_op_py",
         "//tensorflow_quantum/core/ops/noise:noisy_expectation_op_py",
         "//tensorflow_quantum/core/serialize:serializer",
         "//tensorflow_quantum/datasets:cluster_state",

scripts/import_test.py

@@ -39,6 +39,7 @@ def test_imports():
 
     # Noisy simulation ops.
     _ = tfq.noise.expectation
+    _ = tfq.noise.samples
 
     # Util functions.
     _ = tfq.convert_to_tensor

tensorflow_quantum/core/ops/noise/BUILD

@@ -16,6 +16,7 @@ cc_binary(
     name = "_tfq_noise_ops.so",
     srcs = [
         "tfq_noisy_expectation.cc",
+        "tfq_noisy_samples.cc"
     ],
     copts = select({
         ":windows": [
@@ -89,3 +90,25 @@ py_test(
         "//tensorflow_quantum/python:util",
     ],
 )
+
+py_library(
+    name = "noisy_samples_op_py",
+    srcs = ["noisy_samples_op.py"],
+    data = [":_tfq_noise_ops.so"],
+    deps = [
+        "//tensorflow_quantum/core/ops:load_module",
+        "//tensorflow_quantum/core/ops:tfq_utility_ops_py",
+    ],
+)
+
+py_test(
+    name = "noisy_samples_op_test",
+    srcs = ["noisy_samples_op_test.py"],
+    python_version = "PY3",
+    deps = [
+        ":noisy_samples_op_py",
+        "//tensorflow_quantum/core/ops:batch_util",
+        "//tensorflow_quantum/python:util",
+    ],
+)
+

tensorflow_quantum/core/ops/noise/__init__.py

@@ -15,3 +15,4 @@
 """Module for tfq.core.ops.noise.*"""
 
 from tensorflow_quantum.core.ops.noise.noisy_expectation_op import expectation
+from tensorflow_quantum.core.ops.noise.noisy_samples_op import samples

tensorflow_quantum/core/ops/noise/noisy_samples_op.py

@@ -0,0 +1,71 @@
+# Copyright 2020 The TensorFlow Quantum Authors. 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.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License 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.
+# ==============================================================================
+"""Module for high performance noisy circuit sampling ops"""
+import os
+import tensorflow as tf
+from tensorflow_quantum.core.ops import tfq_utility_ops
+from tensorflow_quantum.core.ops.load_module import load_module
+
+NOISY_OP_MODULE = load_module(os.path.join("noise", "_tfq_noise_ops.so"))
+
+
+def samples(programs, symbol_names, symbol_values, num_samples):
+    """Generate samples using the C++ noisy trajectory simulator.
+
+    Simulate the final state of `programs` given `symbol_values` are placed
+    inside of the symbols with the name in `symbol_names` in each circuit.
+    Channels in this simulation will be "tossed" to a certain realization
+    during simulation. After each simulation is a run a single bitstring
+    will be drawn. These simulations are repeated `num_samples` times.
+
+
+    >>> # Sample a noisy circuit with C++.
+    >>> qubit = cirq.GridQubit(0, 0)
+    >>> my_symbol = sympy.Symbol('alpha')
+    >>> my_circuit_tensor = tfq.convert_to_tensor([
+    ...     cirq.Circuit(
+    ...         cirq.X(qubit) ** my_symbol,
+    ...         cirq.depolarize(0.01)(qubit)
+    ...     )
+    ... ])
+    >>> my_values = np.array([[0.123]])
+    >>> my_num_samples = np.array([100])
+    >>> # This op can now be run with:
+    >>> output = tfq.noise.samples(
+    ...     my_circuit_tensor, ['alpha'], my_values, my_num_samples)
+    >>> output
+    <tf.RaggedTensor [[[0], [0], [1], [0], [0], [0], [0], [1], [0], [0]]]>
+
+
+    Args:
+        programs: `tf.Tensor` of strings with shape [batch_size] containing
+            the string representations of the circuits to be executed.
+        symbol_names: `tf.Tensor` of strings with shape [n_params], which
+            is used to specify the order in which the values in
+            `symbol_values` should be placed inside of the circuits in
+            `programs`.
+        symbol_values: `tf.Tensor` of real numbers with shape
+            [batch_size, n_params] specifying parameter values to resolve
+            into the circuits specified by programs, following the ordering
+            dictated by `symbol_names`.
+        num_samples: `tf.Tensor` with one element indicating the number of
+            samples to draw for all circuits in the batch.
+    Returns:
+        A `tf.Tensor` containing the samples taken from each circuit in
+        `programs`.
+    """
+    padded_samples = NOISY_OP_MODULE.tfq_noisy_samples(
+        programs, symbol_names, tf.cast(symbol_values, tf.float32), num_samples)
+    return tfq_utility_ops.padded_to_ragged(padded_samples)