Merge remote-tracking branch 'origin/onnx-slice-const-data-input' into mlir-test-perf

src/onnx/parse_slice.cpp

@@ -44,6 +44,8 @@ struct parse_slice : op_parser<parse_slice>
         std::vector<int64_t> steps;
         std::vector<int64_t> raxes;
 
+        void always_insert(instruction_ref arg) { op_args.insert(op_args.begin(), arg); }
+
         std::vector<int64_t> insert(instruction_ref arg)
         {
             std::vector<int64_t> result;
@@ -132,7 +134,7 @@ struct parse_slice : op_parser<parse_slice>
         }
 
         // data input argument
-        sd.insert(args.at(0));
+        sd.always_insert(args.at(0));
 
         // If axes arg is not given, the default is all of them.
         if(sd.op.axes.empty() and sd.op_args.size() < 3)

test/onnx/gen_onnx.py

@@ -6414,6 +6414,30 @@ def slice_test():
     return ([node], [x], [y])
 
 
+@onnx_test()
+def slice_constant_test():
+    y = helper.make_tensor_value_info('1', TensorProto.FLOAT, [1, 2])
+
+    x_tensor = helper.make_tensor(name='x_tensor',
+                                  data_type=TensorProto.FLOAT,
+                                  dims=[3, 2],
+                                  vals=[0, 1, 2, 3, 4, 5])
+
+    x = onnx.helper.make_node('Constant',
+                              inputs=[],
+                              outputs=['x'],
+                              value=x_tensor)
+
+    node = onnx.helper.make_node('Slice',
+                                 inputs=['x'],
+                                 axes=[0, 1],
+                                 starts=[1, 0],
+                                 ends=[2, 2],
+                                 outputs=['1'])
+
+    return ([x, node], [], [y])
+
+
 @onnx_test()
 def slice_dyn_test():
     x = helper.make_tensor_value_info('0', TensorProto.FLOAT, [None, None, 2])

test/onnx/onnx_test.cpp

@@ -6294,6 +6294,19 @@ TEST_CASE(slice_test)
     EXPECT(p == prog);
 }
 
+TEST_CASE(slice_constant_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    auto l0  = mm->add_literal(migraphx::literal{
+        migraphx::shape{migraphx::shape::float_type, {3, 2}}, {0, 1, 2, 3, 4, 5}});
+    mm->add_instruction(
+        migraphx::make_op("slice", {{"axes", {0, 1}}, {"starts", {1, 0}}, {"ends", {2, 2}}}), l0);
+    auto prog = optimize_onnx("slice_constant_test.onnx");
+
+    EXPECT(p == prog);
+}
+
 TEST_CASE(slice_dyn_test)
 {
     migraphx::program p;