add any axis type (#373)

Signed-off-by: Oleksii Kuchaiev <[email protected]>
NVIDIA · Feb 14, 2020 · 142bed9 · 142bed9
1 parent 6b3be90
commit 142bed9
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Showing 3 changed files with 17 additions and 2 deletions.
diff --git a/nemo/core/neural_types/axes.py b/nemo/core/neural_types/axes.py
@@ -34,7 +34,7 @@ class AxisKind(AxisKindAbstract):
     """This Enum represents what does varying axis dimension mean.
     For example, does this dimension correspond to width, batch, time, etc.
     The "Dimension" and "Channel" kinds are the same and used to represent
-    a general axis.
+    a general axis. "Any" axis will accept any axis kind fed to it.
     """
 
     Batch = 0
@@ -43,6 +43,7 @@ class AxisKind(AxisKindAbstract):
     Channel = 2
     Width = 3
     Height = 4
+    Any = 5
 
     def __str__(self):
         return str(self.name).lower()
@@ -61,6 +62,8 @@ def from_str(label):
             return AxisKind.Width
         elif _label == "h" or _label == "height":
             return AxisKind.Height
+        elif _label == "any":
+            return AxisKind.Any
         else:
             raise ValueError(f"Can't create AxisKind from {label}")
 

diff --git a/nemo/core/neural_types/neural_type.py b/nemo/core/neural_types/neural_type.py
@@ -165,7 +165,9 @@ def __compare_axes(axes_a, axes_b) -> int:
         for axis_a, axis_b in zip(axes_a, axes_b):
             kinds_a[axis_a.kind] = axis_a.size
             kinds_b[axis_b.kind] = axis_b.size
-            if (
+            if axis_a.kind == AxisKind.Any:
+                same = True
+            elif (
                 axis_a.kind != axis_b.kind
                 or axis_a.is_list != axis_b.is_list
                 or (axis_a.size != axis_b.size and axis_a.size is not None)

diff --git a/tests/core/test_neural_types.py b/tests/core/test_neural_types.py
@@ -176,3 +176,13 @@ def test_unspecified_dimensions(self):
         t1 = NeuralType(('B', 'T', 'C'), SpectrogramType())
         self.assertEqual(t1.compare(t0), NeuralTypeComparisonResult.SAME)
         self.assertEqual(t0.compare(t1), NeuralTypeComparisonResult.DIM_INCOMPATIBLE)
+
+    def test_any_axis(self):
+        t0 = NeuralType(('B', 'Any', 'Any'), VoidType())
+        t1 = NeuralType(('B', 'Any', 'Any'), SpectrogramType())
+        t2 = NeuralType(('B', 'T', 'C'), SpectrogramType())
+        self.assertEqual(t0.compare(t1), NeuralTypeComparisonResult.SAME)
+        self.assertEqual(t0.compare(t2), NeuralTypeComparisonResult.SAME)
+        self.assertEqual(t1.compare(t2), NeuralTypeComparisonResult.SAME)
+        self.assertEqual(t2.compare(t1), NeuralTypeComparisonResult.INCOMPATIBLE)
+        self.assertEqual(t1.compare(t0), NeuralTypeComparisonResult.INCOMPATIBLE)