Fix naming for contrib op check, add test for channels last and chang…

…e inputs for generated onnx to handle input activation.

TODO Need to finish parser tests

src/onnx/parse_groupnorm.cpp

@@ -34,15 +34,16 @@ struct parse_groupnorm : op_parser<parse_groupnorm>
 {
     std::vector<op_desc> operators() const 
     { 
-        return {{"GroupNormalization"}, {"GroupNorm"}};
+        return {{"GroupNormalization", "GroupNormalization"}, {"GroupNorm", "Contrib_GroupNorm"}};
     }
 
     instruction_ref parse(const op_desc& opd,
                           const onnx_parser& parser,
                           const onnx_parser::node_info& info,
                           std::vector<instruction_ref> args) const
     {
-        auto is_contrib = opd.op_name == "GroupNorm";
+        bool is_contrib = (!opd.op_name.compare("Contrib_GroupNorm"));
+
         float epsilon = 1e-5f;
         if(contains(info.attributes, "epsilon"))
         {
@@ -52,7 +53,9 @@ struct parse_groupnorm : op_parser<parse_groupnorm>
         if(contains(info.attributes, "num_groups") or contains(info.attributes, "groups"))
         {
             if (is_contrib)
-                num_groups = parser.parse_value(info.attributes.at("groups")).at<size_t>();
+            {
+                num_groups = parser.parse_value(info.attributes.at("num_groups")).at<size_t>();
+            }
             else
                 num_groups = parser.parse_value(info.attributes.at("num_groups")).at<size_t>();
         }
@@ -90,7 +93,7 @@ struct parse_groupnorm : op_parser<parse_groupnorm>
         auto x = args.at(0);
         if(is_nhwc and is_contrib)
         {
-            x = info.add_instruction(make_op("transpose", {{"permutation", {0, 3, 2, 1}}}), x);
+            x = info.add_instruction(make_op("transpose", {{"permutation", {0, 2, 1}}}), x);
         }
 
         auto scale = args.at(1); //gamma in the GroupNorm contrib case
@@ -164,7 +167,7 @@ struct parse_groupnorm : op_parser<parse_groupnorm>
         // Convert to NCHW -> NHWC for contrib GroupNorm
         if(is_nhwc and is_contrib)
         {
-            output = info.add_instruction(make_op("transpose", {{"permutation", {0, 2, 3, 1}}}), output);
+            output = info.add_instruction(make_op("transpose", {{"permutation", {0, 2, 1}}}), output);
         }
         return output;
     }

test/onnx/gen_onnx.py

@@ -4747,9 +4747,9 @@ def group_norm_contrib_test(x_dims,
                             beta_dims,
                             y_dims,
                             num_groups,
-                            eps_value=1e-5,
                             activation=0,
                             channels_last=0,
+                            eps_value=1e-5,
                             dtype=TensorProto.FLOAT):
     x = helper.make_tensor_value_info('x', dtype, x_dims)
     gamma = helper.make_tensor_value_info('gamma', dtype, gamma_dims)
@@ -4759,7 +4759,7 @@ def group_norm_contrib_test(x_dims,
     node = onnx.helper.make_node('GroupNorm',
                                  inputs=['x', 'gamma', 'beta'],
                                  outputs=['y'],
-                                 activaction=activation,
+                                 activation=activation,
                                  channels_last=channels_last,
                                  num_groups=num_groups,
                                  epsilon=eps_value)
@@ -4769,14 +4769,19 @@ def group_norm_contrib_test(x_dims,
 
 @onnx_test()
 def group_norm_contrib_3d_test():
-    return group_norm_contrib_test([1, 4, 2], [2], [2], [1, 4, 2], 1, 0, 0)
+    return group_norm_contrib_test([1, 4, 2], [2], [2], [1, 4, 2], 2, 0, 0)
 
 
 @onnx_test()
 def group_norm_contrib_silu_3d_test():
     return group_norm_contrib_test([1, 4, 2], [2], [2], [1, 4, 2], 2, 1, 0)
 
 
+@onnx_test()
+def group_norm_contrib_channels_last_3d_test():
+    return group_norm_contrib_test([1, 4, 2], [2], [2], [1, 4, 2], 2, 0, 1)
+
+
 @onnx_test()
 def group_norm_contrib_no_activation_attr_test():
     x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [1, 4, 2])

test/onnx/parse/group_norm_contrib_channels_last_3d_test.cpp

@@ -0,0 +1,35 @@
+/*
+ * The MIT License (MIT)
+ *
+ * Copyright (c) 2015-2023 Advanced Micro Devices, Inc. All rights reserved.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in
+ * all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+ * THE SOFTWARE.
+ */
+
+#include <onnx_test.hpp>
+#include <onnx_test_utils.hpp>
+
+TEST_CASE(group_norm_contrib_channels_last_3d_test)
+{
+    migraphx::program p = make_group_norm(
+        {1, 4, 2}, {2}, {2}, {1, 2, 2, 2}, {2, 3}, 1e-5f, migraphx::shape::float_type, "gamma", "beta");
+
+    auto prog = optimize_onnx("group_norm_contrib_channels_last_3d_test.onnx");
+    EXPECT(p == prog);
+}