added symbol values test

FermiQ · Apr 2, 2021 · 750ce65 · 750ce65
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Showing 2 changed files with 42 additions and 23 deletions.
diff --git a/tensorflow_quantum/python/differentiators/parameter_shift.py b/tensorflow_quantum/python/differentiators/parameter_shift.py
@@ -79,28 +79,23 @@ def get_gradient_circuits(self, programs, symbol_names, symbol_values):
         # then reshape to the correct batch size
         batch_programs = tf.reshape(
             tf.transpose(new_programs, [1, 0, 2, 3]), [n_programs, m_tile])
-
-        weights = tf.transpose(weights, [0, 2, 3, 1])
-        shifts = tf.transpose(shifts, [0, 2, 3, 1])
-
-
-        # # tile up and then reshape to order ops correctly
-        # flat_perturbations = tf.concat([
-        #     tf.reshape(
-        #         tf.tile(tf.expand_dims(symbol_values, 0),
-        #                 tf.stack([n_tile, 1, 1])), [total_programs, n_symbols]),
-        #     tf.expand_dims(flat_shifts, axis=1)
-        # ],
-        #                                axis=1)
+        weights = tf.reshape(
+            tf.transpose(weights, [1, 0, 2, 3]), [n_programs, m_tile])
+        shifts = tf.reshape(
+            tf.transpose(shifts, [1, 0, 2, 3]), [n_programs, m_tile])
 
         # Append impurity symbol into symbol name
-        new_symbol_names = tf.concat([
+        expected_new_symbol_names = tf.concat([
             symbol_names,
-            tf.expand_dims(tf.constant(
-                parameter_shift_util._PARAMETER_IMPURITY_NAME),
-                           axis=0)
-        ],
-                                     axis=0)
+            tf.constant([parameter_shift_util._PARAMETER_IMPURITY_NAME])], 0)
+
+        # Symbol values are the input symbol values, tiled according to
+        # `batch_programs`, with the shift values appended.
+        tiled_symbol_names = tf.tile(
+            tf.expand_dims(symbol_values, 1), [1, m_tile, 1])
+        tiled_shifts =  tf.expand_dims(shifts, 1)
+        batch_symbol_values = tf.concat(
+            [tiled_symbol_names, tiled_symbol_values], 2)
 
         return (batch_programs, new_symbol_names, None, None)
 

diff --git a/tensorflow_quantum/python/differentiators/parameter_shift_test.py b/tensorflow_quantum/python/differentiators/parameter_shift_test.py
@@ -148,16 +148,40 @@ def test_get_gradient_circuits(self):
         expected_new_symbol_names = tf.concat([
             input_symbol_names, tf.constant([impurity_symbol_name])], 0)
 
+        # The batch symbol values are the input symbol values, tiled and with
+        # shifts appended.  Locations that have empty programs should also have
+        # zero for the shift.
+        # The shift values are the shifted symbol value, plus 1/2 divided by the
+        # `exponent_scalar` of the gates.
+        expected_batch_symbol_values = tf.constant(
+            [[[1.5, -2.7, 1.5 + 0.5],
+              [1.5, -2.7, 1.5 - 0.5],
+              [1.5, -2.7, 1.5 + 0.5],
+              [1.5, -2.7, 1.5 - 0.5],
+              [1.5, -2.7, -2.7 + 1/(2*np.pi)],
+              [1.5, -2.7, -2.7 - 1/(2*np.pi)],
+              [1.5, -2.7, 0.0],
+              [1.5, -2.7, 0.0]],
+             [[-0.3, 0.9, 0.0],
+              [-0.3, 0.9, 0.0],
+              [-0.3, 0.9, 0.0],
+              [-0.3, 0.9, 0.0],
+              [-0.3, 0.9, 0.9 + 0.5],
+              [-0.3, 0.9, 0.9 - 0.5],
+              [-0.3, 0.9, 0.0],
+              [-0.3, 0.9, 0.0]]])
+
+        #
         (test_batch_programs, test_new_symbol_names, test_batch_symbol_values,
          test_batch_mapper) = diff.get_gradient_circuits(
              input_programs, input_symbol_names, input_symbol_values)
-        for i in range(2):
+        for i in range(tf.shape(input_programs)[0]):
           self.assertAllEqual(util.from_tensor(expected_batch_programs[i]),
                               util.from_tensor(test_batch_programs[i]))
         self.assertAllEqual(expected_new_symbol_names, test_new_symbol_names)
-#        self.assertAllClose(expected_batch_symbol_values,
-#                            test_batch_symbol_values,
-#                            atol=1e-6)
+        self.assertAllClose(expected_batch_symbol_values,
+                            test_batch_symbol_values,
+                            atol=1e-6)
 #        self.assertAllClose(expected_batch_mapper, test_batch_mapper, atol=1e-6)
 
     # @parameterized.parameters(