qml.layer support for tensorflow Variable

.github/CHANGELOG.md

@@ -394,6 +394,9 @@ and requirements-ci.txt (unpinned). This latter would be used by the CI.
 
 <h3>Bug fixes</h3>
 
+* The `qml.layer` template now works with tensorflow variables.
+[(#1615)](https://github.com/PennyLaneAI/pennylane/pull/1615)
+
 * Remove `QFT` from possible operations in `default.qubit` and `default.mixed`.
   [(#1600)](https://github.com/PennyLaneAI/pennylane/pull/1600)
 

pennylane/templates/layer.py

@@ -16,6 +16,7 @@
 """
 # pylint: disable-msg=too-many-branches,too-many-arguments,protected-access
 from pennylane.templates.decorator import template as temp
+from pennylane.math import shape
 
 
 def _preprocess(args, depth):
@@ -30,7 +31,7 @@ def _preprocess(args, depth):
 
     for arg in args:
 
-        if len(arg) != depth:
+        if shape(arg)[0] != depth:
             raise ValueError(
                 "Each positional argument must have length matching 'depth'; expected {} got {}".format(
                     depth, len(arg)

tests/templates/test_layer.py

@@ -155,3 +155,21 @@ def test_layer(self, unitary, depth, arguments, keywords, gates):
             target = [gates[i].name, gates[i].parameters, gates[i].wires]
 
         assert prep == target
+
+    def test_layer_tf(self):
+
+        tf = pytest.importorskip("tensorflow")
+
+        def unitary(param):
+            qml.RX(param, wires=0)
+
+        x = tf.Variable([0.1, 0.2, 0.3])
+
+        with qml.tape.OperationRecorder() as rec:
+            layer(unitary, 3, x)
+
+        assert len(rec.operations) == 3
+
+        for ii, op in enumerate(rec.operations):
+            assert qml.math.allclose(op.parameters[0], x[ii])
+            assert isinstance(op, qml.RX)