DRAFT experiment with LayerNorm to InstanceNorm

on-going draft to experiment with LayerNorm to InstanceNorm.

Signed-off-by: SaeHie Park <[email protected]>

compiler/luci/lang/include/luci/IR/CircleNodes.h

@@ -146,6 +146,7 @@
 // Virtual nodes
 #include "Nodes/CircleConst.h"
 #include "Nodes/CircleInput.h"
+#include "Nodes/CircleLayerNorm.h"
 #include "Nodes/CircleOutput.h"
 #include "Nodes/CircleVariable.h"
 // Multi-output virtual nodes

compiler/luci/lang/include/luci/IR/CircleNodes.lst

@@ -144,6 +144,7 @@ CIRCLE_NODE(ROPE, CircleRoPE)
 // Virtual node(s)
 CIRCLE_VNODE(CIRCLECONST, CircleConst)
 CIRCLE_VNODE(CIRCLEINPUT, CircleInput)
+CIRCLE_VNODE(CIRCLELAYERNORM, CircleLayerNorm)
 CIRCLE_VNODE(CIRCLEOUTPUT, CircleOutput)
 CIRCLE_VNODE(CIRCLEOUTPUTDUMMY, CircleOutputDummy)
 CIRCLE_VNODE(CIRCLEOUTPUTEXCLUDE, CircleOutputExclude)

compiler/luci/lang/include/luci/IR/Nodes/CircleLayerNorm.h

@@ -0,0 +1,55 @@
+/*
+ * Copyright (c) 2024 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef __LUCI_IR_CIRCLE_LAYER_NORM_H__
+#define __LUCI_IR_CIRCLE_LAYER_NORM_H__
+
+#include "luci/IR/CircleNodeDecl.h"
+#include "luci/IR/CircleOpcode.h"
+
+#include "luci/IR/AttrFusedActFunc.h"
+#include "luci/IR/CircleNodeMixins.h"
+
+namespace luci
+{
+
+/**
+ * @brief Virtual LayerNorm
+ */
+class CircleLayerNorm final
+  : public FixedArityNode<3, CircleNodeImpl<CircleOpcode::CIRCLELAYERNORM>>
+{
+public:
+  loco::Node *input(void) const { return at(0)->node(); }
+  void input(loco::Node *node) { at(0)->node(node); }
+
+  loco::Node *gamma(void) const { return at(1)->node(); }
+  void gamma(loco::Node *node) { at(1)->node(node); }
+
+  loco::Node *beta(void) const { return at(2)->node(); }
+  void beta(loco::Node *node) { at(2)->node(node); }
+
+public:
+  float epsilon() const { return _epsilon; }
+  void epsilon(float epsilon) { _epsilon = epsilon; }
+
+private:
+  float _epsilon{1e-05};
+};
+
+} // namespace luci
+
+#endif // __LUCI_IR_CIRCLE_LAYER_NORM_H__

res/TensorFlowLiteRecipes/Net_LayerNorm_000/test.recipe

@@ -0,0 +1,157 @@
+#
+# Generated with tflchef-reverse
+# refer https://github.com/Samsung/ONE/issues/14467
+#
+operand {
+  name: "serving_default_input:0"
+  type: FLOAT32
+  shape {
+    dim: 1
+    dim: 16
+    dim: 4
+  }
+}
+operand {
+  name: "onnx_tf_prefix_/ln/Constant_1"
+  type: FLOAT32
+  shape {
+  }
+  filler {
+    tag: "explicit"
+    arg: "1e-05"
+  }
+}
+operand {
+  name: "onnx_tf_prefix_/ln/ReduceMean/reduction_indices"
+  type: INT32
+  shape {
+  }
+  filler {
+    tag: "explicit"
+    arg: "-1"
+  }
+}
+operand {
+  name: "onnx_tf_prefix_/ln/ReduceMean"
+  type: FLOAT32
+  shape {
+    dim: 1
+    dim: 16
+    dim: 1
+  }
+}
+operand {
+  name: "onnx_tf_prefix_/ln/Sub"
+  type: FLOAT32
+  shape {
+    dim: 1
+    dim: 16
+    dim: 4
+  }
+}
+operand {
+  name: "onnx_tf_prefix_/ln/Pow;onnx_tf_prefix_/ln/Constant"
+  type: FLOAT32
+  shape {
+    dim: 1
+    dim: 16
+    dim: 4
+  }
+}
+operand {
+  name: "onnx_tf_prefix_/ln/ReduceMean_1"
+  type: FLOAT32
+  shape {
+    dim: 1
+    dim: 16
+    dim: 1
+  }
+}
+operand {
+  name: "onnx_tf_prefix_/ln/Add"
+  type: FLOAT32
+  shape {
+    dim: 1
+    dim: 16
+    dim: 1
+  }
+}
+operand {
+  name: "onnx_tf_prefix_/ln/Div;onnx_tf_prefix_/ln/Sqrt"
+  type: FLOAT32
+  shape {
+    dim: 1
+    dim: 16
+    dim: 1
+  }
+}
+operand {
+  name: "PartitionedCall:0"
+  type: FLOAT32
+  shape {
+    dim: 1
+    dim: 16
+    dim: 4
+  }
+}
+operation {
+  type: "Mean"
+  input: "serving_default_input:0"
+  input: "onnx_tf_prefix_/ln/ReduceMean/reduction_indices"
+  output: "onnx_tf_prefix_/ln/ReduceMean"
+  mean_options {
+    keep_dims: true
+  }
+}
+operation {
+  type: "Sub"
+  input: "serving_default_input:0"
+  input: "onnx_tf_prefix_/ln/ReduceMean"
+  output: "onnx_tf_prefix_/ln/Sub"
+  sub_options {
+    activation: NONE
+  }
+}
+operation {
+  type: "Mul"
+  input: "onnx_tf_prefix_/ln/Sub"
+  input: "onnx_tf_prefix_/ln/Sub"
+  output: "onnx_tf_prefix_/ln/Pow;onnx_tf_prefix_/ln/Constant"
+  mul_options {
+    activation: NONE
+  }
+}
+operation {
+  type: "Mean"
+  input: "onnx_tf_prefix_/ln/Pow;onnx_tf_prefix_/ln/Constant"
+  input: "onnx_tf_prefix_/ln/ReduceMean/reduction_indices"
+  output: "onnx_tf_prefix_/ln/ReduceMean_1"
+  mean_options {
+    keep_dims: true
+  }
+}
+operation {
+  type: "Add"
+  input: "onnx_tf_prefix_/ln/ReduceMean_1"
+  input: "onnx_tf_prefix_/ln/Constant_1"
+  output: "onnx_tf_prefix_/ln/Add"
+  add_options {
+    activation: NONE
+  }
+}
+operation {
+  type: "Rsqrt"
+  input: "onnx_tf_prefix_/ln/Add"
+  output: "onnx_tf_prefix_/ln/Div;onnx_tf_prefix_/ln/Sqrt"
+}
+operation {
+  type: "Mul"
+  input: "onnx_tf_prefix_/ln/Sub"
+  input: "onnx_tf_prefix_/ln/Div;onnx_tf_prefix_/ln/Sqrt"
+  output: "PartitionedCall:0"
+  mul_options {
+    activation: NONE
+  }
+}
+input: "serving_default_input:0"
+output: "PartitionedCall:0"