Dynamic Conv bias fix (#1502)

Fixes ONNX parsing of convolution to handle dynamic broadcasting of bias input

src/onnx/onnx_parser.cpp

@@ -110,9 +110,19 @@ instruction_ref onnx_parser::node_info::add_bias(const std::vector<instruction_r
 {
     if(args.size() == 3)
     {
-        auto bias_bcast = mod->add_instruction(
+        instruction_ref bias_bcast;
+        // if curr_ins has a dynamic output shape use 2 input broadcast
+        if(curr_ins->get_shape().dynamic())
+        {
+            bias_bcast =
+                mod->add_instruction(make_op("broadcast", {{"axis", axis}}), args[2], curr_ins);
+        }
+        else
+        {
+            bias_bcast = mod->add_instruction(
                 make_op("broadcast", {{"axis", axis}, {"out_lens", curr_ins->get_shape().lens()}}),
                 args[2]);
+        }
         return mod->add_instruction(make_op("add"), curr_ins, bias_bcast);
     }
     return curr_ins;

test/onnx/gen_onnx.py

@@ -1121,6 +1121,24 @@ def conv_dynamic_batch_test():
     return ([node], [x, y], [out])
 
 
+@onnx_test()
+def conv_dynamic_bias_test():
+    x = helper.make_tensor_value_info('0', TensorProto.FLOAT,
+                                      [None, 3, 32, 32])
+    y = helper.make_tensor_value_info('1', TensorProto.FLOAT, [1, 3, 5, 5])
+    z = helper.make_tensor_value_info('2', TensorProto.FLOAT, [1])
+    out = helper.make_tensor_value_info('3', TensorProto.FLOAT,
+                                        [None, 2, 28, 28])
+
+    node = onnx.helper.make_node('Conv',
+                                 inputs=['0', '1', '2'],
+                                 outputs=['3'],
+                                 dilations=[1, 1],
+                                 strides=[1, 1])
+
+    return ([node], [x, y, z], [out])
+
+
 @onnx_test()
 def conv_dynamic_img_test():
     x = helper.make_tensor_value_info('0', TensorProto.FLOAT,

test/onnx/onnx_test.cpp

@@ -1118,6 +1118,25 @@ TEST_CASE(conv_dynamic_batch_test)
     EXPECT(p == prog);
 }
 
+TEST_CASE(conv_dynamic_bias_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    auto x0  = mm->add_parameter(
+        "0", {migraphx::shape::float_type, {{1, 6, 0}, {3, 3, 0}, {32, 32, 0}, {32, 32, 0}}});
+    auto x1 = mm->add_parameter("1", {migraphx::shape::float_type, {1, 3, 5, 5}});
+    auto x2 = mm->add_parameter("2", {migraphx::shape::float_type, {1}});
+    auto x3 = mm->add_instruction(migraphx::make_op("convolution"), x0, x1);
+    auto x4 = mm->add_instruction(migraphx::make_op("broadcast", {{"axis", 1}}), x2, x3);
+    auto x5 = mm->add_instruction(migraphx::make_op("add"), x3, x4);
+    mm->add_return({x5});
+
+    migraphx::onnx_options options;
+    options.default_dyn_dim_value = {1, 6, 0};
+    auto prog                     = migraphx::parse_onnx("conv_dynamic_bias_test.onnx", options);
+    EXPECT(p == prog);
+}
+
 TEST_CASE(conv_dynamic_img_test)
 {
     migraphx::program p;