add support for broadcast_to

Author: RandySheriffH

tests/test_backend.py

@@ -2955,6 +2955,14 @@ def func(input_holder):
         for input_val in input_vals:
             self._run_test_case(func, [_OUTPUT], {_INPUT: input_val})
 
+    @check_opset_min_version(8)
+    def test_broadcast(self):
+        input_tensor_val = np.random.randint(low=0, high=256, size=[2, 3]).astype(np.float32)
+        new_shape_val = np.array([3,2,3]).astype(np.int64)
+        def func(input_tensor, new_shape):
+            return tf.broadcast_to(input_tensor, new_shape, _TFOUTPUT)
+        self._run_test_case(func, [_OUTPUT], {_INPUT: input_tensor_val, _INPUT1: new_shape_val})
+
 
 if __name__ == '__main__':
     unittest_main()

tf2onnx/onnx_opset/tensor.py

@@ -1806,3 +1806,10 @@ def version_11(cls, ctx, node, **kwargs):
         ctx.remove_node(node.name)
         squeezed_result = ctx.make_node('Squeeze', [gathered_result.output[0]], attr={"axes": [-1]},
                                         name=node.name, outputs=node.output, shapes=shapes, dtypes=dtypes)
+
+@tf_op("BroadcastTo")
+class BroadcastTo:
+    @classmethod
+    def version_8(cls, ctx, node, **kwargs):
+        node.type = "Expand"
+        ctx.insert_new_node_on_input(node, "Cast", node.input[1], to=TensorProto.INT64)