Add contrib groupnorm

src/onnx/parse_groupnorm.cpp

@@ -32,36 +32,72 @@
 
 struct parse_groupnorm : op_parser<parse_groupnorm>
 {
-    std::vector<op_desc> operators() const { return {{"GroupNormalization"}}; }
+    std::vector<op_desc> operators() const 
+    { 
+        return {{"GroupNormalization", "GroupNormalization"}, {"GroupNorm", "Contrib_GroupNorm"}};
+    }
 
-    instruction_ref parse(const op_desc& /*opd*/,
+    instruction_ref parse(const op_desc& opd,
                           const onnx_parser& parser,
                           const onnx_parser::node_info& info,
                           std::vector<instruction_ref> args) const
     {
+        bool is_contrib = (!opd.op_name.compare("Contrib_GroupNorm"));
+
         float epsilon = 1e-5f;
         if(contains(info.attributes, "epsilon"))
         {
             epsilon = parser.parse_value(info.attributes.at("epsilon")).at<float>();
         }
         size_t num_groups;
-        if(contains(info.attributes, "num_groups"))
+        if(contains(info.attributes, "num_groups") or contains(info.attributes, "groups"))
         {
-            num_groups = parser.parse_value(info.attributes.at("num_groups")).at<size_t>();
+            if (is_contrib)
+            {
+                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>();
         }
         else
         {
             MIGRAPHX_THROW("PARSE_GROUPNORM: num_groups must be available");
         }
 
+        bool is_nhwc = false; 
+        if(is_contrib)
+        {   // default state for GroupNorm Contrib op
+            is_nhwc = true;
+            if(contains(info.attributes, "channels_last") and is_contrib)
+            {
+                is_nhwc = parser.parse_value(info.attributes.at("channels_last")).at<size_t>();
+            }
+        }
+
+        bool silu_activation = false;
+        if(contains(info.attributes, "activation") and is_contrib)
+        {
+            silu_activation = (1 == parser.parse_value(info.attributes.at("activation")).at<size_t>());
+        }
+        else if(is_contrib)
+        {
+            MIGRAPHX_THROW("PARSE_GROUPNORM: activation must be available");
+        }
+
         if(args.size() != 3)
         {
             MIGRAPHX_THROW("PARSE_GROUPNORM: invalid input count");
         }
 
-        auto x     = args.at(0);
-        auto scale = args.at(1);
-        auto bias  = args.at(2);
+        // Adjust chanels from NHWC-> NCHW if last channel is set for contrib op
+        auto x = args.at(0);
+        if(is_nhwc and is_contrib)
+        {
+            x = info.add_instruction(make_op("transpose", {{"permutation", {0, 2, 1}}}), x);
+        }
+
+        auto scale = args.at(1); //gamma in the GroupNorm contrib case
+        auto bias  = args.at(2); //beta in the GroupNorm contrib case
 
         auto x_shape = x->get_shape();
         auto x_dtype = x_shape.type();
@@ -120,7 +156,20 @@
             info.add_instruction(make_op("broadcast", {{"axis", 1}, {"out_lens", dims}}), bias);
         auto scaled = info.add_instruction(make_op("mul"), result, scale_bcast);
         auto y      = info.add_instruction(make_op("add"), scaled, bias_bcast);
-        return info.add_instruction(make_op("reshape", {{"dims", x_dims}}), y);
+        auto output = info.add_instruction(make_op("reshape", {{"dims", x_dims}}), y);
+
+        if(silu_activation)
+        {
+            // SiLU activation is just  out = x * sigmoid(x)
+            auto sigmoid = info.add_instruction(make_op("sigmoid"), output);
+            output = info.add_instruction(make_op("mul"), output, sigmoid);
+        }
+        // Convert to NCHW -> NHWC for contrib GroupNorm
+        if(is_nhwc and is_contrib)
+        {
+            output = info.add_instruction(make_op("transpose", {{"permutation", {0, 2, 1}}}), output);
+        }
+        return output;
     }
 };
 

test/onnx/gen_onnx.py

@@ -4742,6 +4742,78 @@ def group_norm_invalid_bias_shape_test():
     return group_norm_test([1, 4, 3, 3], [2], [3], [1, 4, 3, 3], 2)
 
 
+def group_norm_contrib_test(x_dims,
+                            gamma_dims,
+                            beta_dims,
+                            y_dims,
+                            num_groups,
+                            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)
+    beta = helper.make_tensor_value_info('beta', dtype, beta_dims)
+    y = helper.make_tensor_value_info('y', dtype, y_dims)
+
+    node = onnx.helper.make_node('GroupNorm',
+                                 inputs=['x', 'gamma', 'beta'],
+                                 outputs=['y'],
+                                 activation=activation,
+                                 channels_last=channels_last,
+                                 num_groups=num_groups,
+                                 epsilon=eps_value)
+
+    return ([node], [x, gamma, beta], [y])
+
+
+@onnx_test()
+def group_norm_contrib_3d_test():
+    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])
+    gamma = helper.make_tensor_value_info('gamma', TensorProto.FLOAT, [2])
+    beta = helper.make_tensor_value_info('beta', TensorProto.FLOAT, [2])
+    y = helper.make_tensor_value_info('y', TensorProto.FLOAT, [1, 4, 2])
+
+    node = onnx.helper.make_node('GroupNorm',
+                                 inputs=['x', 'gamma', 'Beta'],
+                                 outputs=['y'],
+                                 channels_last=0,
+                                 num_groups=2)
+
+    return ([node], [x, gamma, beta], [y])
+
+
+@onnx_test()
+def group_norm_contrib_no_num_groups_attr_test():
+    x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [1, 4, 2])
+    gamma = helper.make_tensor_value_info('gamma', TensorProto.FLOAT, [2])
+    beta = helper.make_tensor_value_info('beta', TensorProto.FLOAT, [2])
+    y = helper.make_tensor_value_info('y', TensorProto.FLOAT, [1, 4, 2])
+
+    node = onnx.helper.make_node('GroupNorm',
+                                 inputs=['x', 'gamma', 'Beta'],
+                                 outputs=['y'],
+                                 activation=0,
+                                 channels_last=0)
+
+    return ([node], [x, gamma, beta], [y])
+
+
 @onnx_test()
 def group_query_attention_test():
     qkv = helper.make_tensor_value_info('qkv', TensorProto.FLOAT16,

test/onnx/include/onnx_test_utils.hpp

@@ -120,14 +120,16 @@
                 const std::vector<int64_t>& reshape_dims,
                 const std::vector<int64_t>& reduce_axes,
                 const float eps_value               = 1e-5f,
-                const migraphx::shape::type_t dtype = migraphx::shape::float_type)
+                const migraphx::shape::type_t dtype = migraphx::shape::float_type,
+                const std::string param1_name = "scale",
+                const std::string param2_name = "bias")
 {
     migraphx::program p;
     auto* mm = p.get_main_module();
 
     auto x     = mm->add_parameter("x", {dtype, input_dims});
-    auto scale = mm->add_parameter("scale", {dtype, scale_dims});
-    auto bias  = mm->add_parameter("bias", {dtype, bias_dims});
+    auto scale = mm->add_parameter(param1_name, {dtype, scale_dims});
+    auto bias  = mm->add_parameter(param2_name, {dtype, bias_dims});
 
     auto eps = mm->add_literal(migraphx::literal{dtype, {eps_value}});
 

test/onnx/parse/group_norm_contrib_3d_no_activation_err_test.cpp

@@ -0,0 +1,31 @@
+/*
+ * 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_no_activation_err_test)
+{
+    EXPECT(test::throws([&] { read_onnx("group_norm_contrib_no_activation_attr_test.onnx"); }));
+}

test/onnx/parse/group_norm_contrib_3d_no_num_groups_err_test.cpp

@@ -0,0 +1,31 @@
+/*
+ * 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_no_num_groups_err_test)
+{
+    EXPECT(test::throws([&] { read_onnx("group_norm_contrib_no_num_groups_attr_test.onnx"); }));
+}

test/onnx/parse/group_norm_contrib_3d_test.cpp

@@ -0,0 +1,34 @@
+/*
+ * 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_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_3d_test.onnx");
+    EXPECT(p == prog);
+}

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);
+}

test/onnx/parse/group_norm_contrib_silu_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_silu_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_silu_3d_test.onnx");
+    EXPECT(p == prog);
+}