Add scales attribute parse in upsample for older opset versions

src/onnx/parse_resize.cpp

@@ -265,23 +265,38 @@ struct parse_resize : op_parser<parse_resize>
                                         ": dynamic input scale is not supported!");
 
                     arg_scale.visit([&](const auto& v) { vec_scale.assign(v.begin(), v.end()); });
-                    if(in_lens.size() != vec_scale.size())
-                    {
-                        MIGRAPHX_THROW("PARSE_" + opd.op_name +
-                                       ": ranks of input and scale are different!");
-                    }
-
-                    std::transform(in_lens.begin(),
-                                   in_lens.end(),
-                                   vec_scale.begin(),
-                                   out_lens.begin(),
-                                   [&](auto idx, auto scale) {
-                                       return static_cast<std::size_t>(idx * scale);
-                                   });
                 }
             }
         }
 
+        // scales still missing, must be an attribute
+        if(vec_scale.empty())
+        {
+            if(contains(info.attributes, "scales"))
+            {
+                copy(info.attributes["scales"].floats(), std::back_inserter(vec_scale));
+            }
+            else
+            {
+                MIGRAPHX_THROW("PARSE_" + opd.op_name + ": scale not provided!");
+            }
+        }
+        if(in_lens.size() != vec_scale.size())
+        {
+            MIGRAPHX_THROW("PARSE_" + opd.op_name + ": ranks of input and scale are different!");
+        }
+
+        // if the output was not calculated yet, we update it based on the scales
+        if(all_of(out_lens.cbegin(), out_lens.cend(), [](auto o) { return o == 0; }))
+        {
+            std::transform(
+                in_lens.begin(),
+                in_lens.end(),
+                vec_scale.begin(),
+                out_lens.begin(),
+                [&](auto idx, auto scale) { return static_cast<std::size_t>(idx * scale); });
+        }
+
         shape out_s{in_s.type(), out_lens};
         std::size_t out_elements = out_s.elements();
         auto idx_op              = get_original_idx_op(coord_trans_mode);

test/onnx/gen_onnx.py

@@ -8158,6 +8158,22 @@ def upsample_test():
     return ([node], [X], [Y], [scale_tensor])
 
 
+@onnx_test()
+def upsample_ver7_test():
+    X = helper.make_tensor_value_info('X', TensorProto.FLOAT, [1, 1, 2, 2])
+    Y = helper.make_tensor_value_info('Y', TensorProto.FLOAT, [1, 1, 4, 6])
+
+    node = onnx.helper.make_node(
+        'Upsample',
+        inputs=['X'],
+        outputs=['Y'],
+        mode='nearest',
+        scales=[1.0, 1.0, 2.0, 3.0]
+    )
+
+    return ([node], [X], [Y])
+
+
 @onnx_test()
 def variable_batch_test():
     x = helper.make_tensor_value_info('0', TensorProto.FLOAT,

test/onnx/onnx_test.cpp

@@ -7640,6 +7640,27 @@ TEST_CASE(upsample_test)
     EXPECT(p == prog);
 }
 
+TEST_CASE(upsample_ver7_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+
+    migraphx::shape sx{migraphx::shape::float_type, {1, 1, 2, 2}};
+    auto ix = mm->add_parameter("X", sx);
+
+    migraphx::shape si{migraphx::shape::int32_type, {1, 1, 4, 6}};
+    std::vector<int> ind = {0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3, 2, 2, 2, 3, 3, 3};
+
+    auto li  = mm->add_literal(migraphx::literal(si, ind));
+    auto rsp = mm->add_instruction(migraphx::make_op("reshape", {{"dims", {4}}}), ix);
+    auto r   = mm->add_instruction(migraphx::make_op("gather", {{"axis", 0}}), rsp, li);
+    mm->add_return({r});
+
+    auto prog = migraphx::parse_onnx("upsample_ver7_test.onnx");
+
+    EXPECT(p == prog);
+}
+
 TEST_CASE(unknown_test_throw_print_error)
 {
     migraphx::onnx_options options;