Minor enhancements (#2026)

Author: TobyRoseman

coremltools/converters/mil/input_types.py

@@ -152,8 +152,8 @@ def __repr__(self):
         return self.__str__()
 
     def __str__(self):
-        str_repr = 'ImageType[name={}, shape={}, scale={}, bias={}, ' +\
-                'color_layout={}, channel_first={}]'
+        str_repr = 'ImageType(name={}, shape={}, scale={}, bias={}, ' +\
+                'color_layout={}, channel_first={})'
         return str_repr.format(self.name, self.shape, self.scale, self.bias,
                                self.color_layout, self.channel_first)
 
@@ -268,7 +268,7 @@ def __repr__(self):
         return self.__str__()
 
     def __str__(self):
-        return 'TensorType[name={}, shape={}, dtype={}]'.format(self.name,
+        return 'TensorType(name={}, shape={}, dtype={})'.format(self.name,
                                                                 self.shape,
                                                                 self.dtype)
 
@@ -408,6 +408,11 @@ def __init__(self, shape, default=None):
     def __str__(self):
         return str(self.shape)
 
+
+    def __repr__(self):
+        return self.__str__()
+
+
     @property
     def has_symbolic(self):
         return any(is_symbolic(s) for s in self.symbolic_shape)
@@ -436,7 +441,27 @@ def __init__(self, shapes, default=None):
             the metadata of the model file.
 
             If None, then the first element in ``shapes`` is used.
+
+        Examples
+        --------
+        .. sourcecode:: python
+
+        sample_shape = ct.EnumeratedShapes(
+            shapes=[
+                (2, 4, 64, 64),
+                (2, 4, 48, 48),
+                (2, 4, 32, 32)
+            ],
+            default=(2, 4, 64, 64)
+        )
+
+        my_core_ml_model = ct.convert(
+            my_model,
+            inputs=[ct.TensorType(name="sample", shape=sample_shape)],
+        )
         """
+
+        # lazy import to avoid circular import
         from coremltools.converters.mil.mil import get_new_symbol
 
         if not isinstance(shapes, (list, tuple)):
@@ -490,6 +515,14 @@ def __init__(self, shapes, default=None):
         self.default = default
 
 
+    def __repr__(self):
+        return self.__str__()
+
+
+    def __str__(self):
+        return "EnumeratedShapes(" + str(self.shapes) + ", default=" + str(self.default) + ")"
+
+
 def _get_shaping_class(shape):
     """
         Returns a Shape class or EnumeratedShapes class for `shape`

coremltools/converters/mil/mil/ops/defs/iOS15/linear.py

@@ -291,7 +291,8 @@ def type_inference(self):
         x_shape = x.shape
         y_shape = y.shape
         assert len(x_shape) == len(y_shape), "inputs not of the same rank"
-        assert x_shape[-1] == y_shape[-3], "input shapes incompatible"
+        if not (is_symbolic(x_shape[-1]) or is_symbolic(y_shape[-3])):
+            assert x_shape[-1] == y_shape[-3], f"input shapes incompatible: {x_shape[-1]} and {y_shape[-3]}"
         if x_shape[-2] != 1 and y_shape[-2] != 1:
             assert x_shape[-2] == y_shape[-2], "input shapes incompatible"
         if len(x_shape) == 4: