Fix for converting Tile Slice (#495)

* Fix for converting `Tile` `Slice`
- Tile: pass `reps` as a int list instead of numpy array to `add_tile
- Slice: If shape is not known but rank is known, proceed with end_mask
false

* adding pytorch model test

Author: bhushan23

onnx_coreml/_operators_nd.py

@@ -1890,8 +1890,15 @@ def _convert_slice_ir4v9(builder, node, graph, err):
     '''
     convert to CoreML Slice Static Layer:
     https://github.com/apple/coremltools/blob/655b3be5cc0d42c3c4fa49f0f0e4a93a26b3e492/mlmodel/format/NeuralNetwork.proto#L5082
-    ''' 
-    data_shape = graph.shape_dict[node.inputs[0]]
+    '''
+    if node.inputs[0] in graph.shape_dict:
+        data_shape = graph.shape_dict[node.inputs[0]]
+    else:
+        rank = builder._get_rank(node.inputs[0])
+        if rank == -1:
+            return err.unsupported_op_configuration(builder, node, graph, "Input shape not available")
+        data_shape = [INT_MAX] * rank
+
     len_of_data = len(data_shape)
     begin_masks = [True] * len_of_data
     end_masks = [True] * len_of_data
@@ -2160,7 +2167,7 @@ def _convert_tile(builder, node, graph, err):
         name=node.name,
         input_name=node.inputs[0],
         output_name=node.outputs[0],
-        reps=node.input_tensors[node.inputs[1]]
+        reps=node.input_tensors[node.inputs[1]].astype(np.int32).tolist()
     )
 
 def _convert_topk(builder, node, graph, err):

tests/pytorch_model_test.py

@@ -572,6 +572,20 @@ def forward(self, x):
         torch_model.train(False)
         _test_torch_model_single_io(torch_model, (18, 4, 5), (18, 4, 5), target_ios=target_ios)  # type: ignore
 
+class OperatorTests(unittest.TestCase):
+    '''
+    Operator test for Operator
+    '''
+    @unittest.skipIf(macos_version() < MIN_MACOS_VERSION_10_15,
+                     'macOS 10.15+ required. Skipping test.')
+    def test_repeat(self, target_ios='13'):
+        class Net(nn.Module):
+            def forward(self, x):
+                return x.repeat([2, 3, 1])
+        torch_model = Net()
+        torch_model.train(False)
+        _test_torch_model_single_io(torch_model, (18, 4, 5), (18, 4, 5), target_ios=target_ios)  # type: ignore
+
 class BinaryOperationTests(unittest.TestCase):
     '''
     Binary Operation Test cases
@@ -600,7 +614,7 @@ def forward(self, x):
         y1 = torch.rand((4, 5))
         y2 = torch.rand((18, 4, 5))
         y3 = 7.234
-        
+
         torch_model = Net()  # type: ignore
         torch_model.train(False)
         _test_torch_model_single_io(torch_model, (18, 4, 5), (18, 4, 5), target_ios=target_ios)  # type: ignore
@@ -653,7 +667,7 @@ def forward(self, x):
         y1 = torch.rand((4, 5))
         y2 = torch.rand((18, 4, 5))
         y3 = 7.234
-        
+
         torch_model = Net()  # type: ignore
         torch_model.train(False)
         _test_torch_model_single_io(torch_model, (18, 4, 5), (18, 4, 5), target_ios=target_ios)  # type: ignore
@@ -696,7 +710,7 @@ def forward(self, x):
         e = torch.rand((5))
         f = 8.234
         g = 5
-         
+
         torch_model = Net()  # type: ignore
         torch_model.train(False)
         _test_torch_model_single_io(torch_model, (18, 4, 5), (18, 4, 5), target_ios=target_ios)  # type: ignore
@@ -742,6 +756,7 @@ def test_cast_removal_transformation(self, target_ios='13'):
         torch_model.train(False)
         _test_torch_model_single_io(torch_model, (1, 18, 4, 5), (1, 18, 8, 10), target_ios=target_ios)
 
+
 if __name__ == '__main__':
     unittest.main()
     #suite = unittest.TestSuite()