From 1cb29aa8471f4bf78f53d5cbf0b9dee7fa6b0615 Mon Sep 17 00:00:00 2001
From: Ellen Norris-Thompson <ellen.norris-thompson@arm.com>
Date: Thu, 11 Jul 2019 17:27:37 +0100
Subject: IVGCVSW-3305 Support Minimum in HAL1.2 Driver

 * Adds conversion method to HAL1.2 Policy

Signed-off-by: Ellen Norris-Thompson <ellen.norris-thompson@arm.com>
Change-Id: Ib282f32b2f5e899f1fb085bf615df5f984b6fd34
---
 1.2/HalPolicy.cpp    | 52 ++++++++++++++++++++++++++++++++++++++++++++++++++++
 1.2/HalPolicy.hpp    |  2 ++
 NnapiSupport.txt     |  2 +-
 OutputShapeUtils.cpp |  6 ++++++
 OutputShapeUtils.hpp |  3 +++
 5 files changed, 64 insertions(+), 1 deletion(-)

diff --git a/1.2/HalPolicy.cpp b/1.2/HalPolicy.cpp
index 5b501dbc..7a52fcc4 100644
--- a/1.2/HalPolicy.cpp
+++ b/1.2/HalPolicy.cpp
@@ -144,6 +144,8 @@ bool HalPolicy::ConvertOperation(const Operation& operation, const Model& model,
             return ConvertDepthwiseConv2d(operation, model, data);
         case V1_2::OperationType::MAXIMUM:
             return ConvertMaximum(operation, model, data);
+        case V1_2::OperationType::MINIMUM:
+            return ConvertMinimum(operation, model, data);
         case V1_2::OperationType::PAD_V2:
             return ConvertPadV2(operation, model, data);
         case V1_2::OperationType::PRELU:
@@ -551,6 +553,56 @@ bool HalPolicy::ConvertMaximum(const Operation& operation, const Model& model, C
                                                             armnn::Optional<armnn::TensorInfo>(outInfo));
 }
 
+bool HalPolicy::ConvertMinimum(const Operation& operation, const Model& model, ConversionData& data)
+{
+    LayerInputHandle input0 = ConvertToLayerInputHandle<hal_1_2::HalPolicy>(operation, 0, model, data);
+    LayerInputHandle input1 = ConvertToLayerInputHandle<hal_1_2::HalPolicy>(operation, 1, model, data);
+
+    if (!input0.IsValid() || !input1.IsValid())
+    {
+        return Fail("%s: Operation has invalid inputs", __func__);
+    }
+
+    const Operand* output = GetOutputOperand<hal_1_2::HalPolicy>(operation, 0, model);
+    if (!output)
+    {
+        return Fail("%s: Could not read output 0", __func__);
+    }
+
+    armnn::TensorInfo outputInfo = GetTensorInfoForOperand(*output);
+    if (IsDynamicOutput(outputInfo))
+    {
+        ALOGD("Output shape not set, will infer from inputs");
+        outputInfo.SetShape(InferMinimumOutputShape(input0.GetTensorInfo().GetShape(),
+                                                    input1.GetTensorInfo().GetShape()));
+    }
+
+    bool isSupported = false;
+    FORWARD_LAYER_SUPPORT_FUNC(__func__,
+                               IsMinimumSupported,
+                               data.m_Backends,
+                               isSupported,
+                               input0.GetTensorInfo(),
+                               input1.GetTensorInfo(),
+                               outputInfo);
+
+    if (!isSupported)
+    {
+        return false;
+    }
+
+    armnn::IConnectableLayer* const layer = data.m_Network->AddMinimumLayer();
+    assert(layer != nullptr);
+    BroadcastTensor(input0, input1, layer, *data.m_Network);
+
+    return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation,
+                                                            0,
+                                                            *layer,
+                                                            model,
+                                                            data,
+                                                            armnn::Optional<armnn::TensorInfo>(outputInfo));
+}
+
 bool HalPolicy::ConvertPadV2(const Operation& operation, const Model& model, ConversionData& data)
 {
     LayerInputHandle input = ConvertToLayerInputHandle<hal_1_2::HalPolicy>(operation, 0, model, data);
diff --git a/1.2/HalPolicy.hpp b/1.2/HalPolicy.hpp
index d0d988f3..18cf0359 100644
--- a/1.2/HalPolicy.hpp
+++ b/1.2/HalPolicy.hpp
@@ -37,6 +37,8 @@ private:
 
     static bool ConvertMaximum(const Operation& operation, const Model& model, ConversionData& data);
 
+    static bool ConvertMinimum(const Operation& operation, const Model& model, ConversionData& data);
+
     static bool ConvertPadV2(const Operation& operation, const Model& model, ConversionData& data);
 
     static bool ConvertPrelu(const Operation& operation, const Model& model, ConversionData& data);
diff --git a/NnapiSupport.txt b/NnapiSupport.txt
index eabc534f..8c7a814c 100644
--- a/NnapiSupport.txt
+++ b/NnapiSupport.txt
@@ -51,6 +51,7 @@ The following AndroidNN HAL 1.2 operations are currently supported:
 CONV_2D                      (FLOAT32,QUANT8_ASYMM)
 DEPTHWISE_CONV_2D            (FLOAT32,QUANT8_ASYMM)
 MAXIMUM                      (FLOAT32,QUANT8_ASYMM)
+MINIMUM                      (FLOAT32,QUANT8_ASYMM)
 PRELU                        (FLOAT32,QUANT8_ASYMM)
 RESIZE_NEAREST_NEIGHBOR      (FLOAT32,QUANT8_ASYMM)
 
@@ -69,7 +70,6 @@ The following AndroidNN HAL 1.2 operations are currently not supported:
 
 CONCATENATION
 LSTM
-MINIMUM
 PAD_V2
 QUANTIZE
 QUANTIZED_16BIT_LSTM
diff --git a/OutputShapeUtils.cpp b/OutputShapeUtils.cpp
index 6c936ee7..e3812a36 100644
--- a/OutputShapeUtils.cpp
+++ b/OutputShapeUtils.cpp
@@ -121,6 +121,12 @@ TensorShape InferMaximumOutputShape(const armnn::TensorShape& input0Shape,
     return CalculateMaxShape(input0Shape, input1Shape);
 }
 
+TensorShape InferMinimumOutputShape(const armnn::TensorShape& input0Shape,
+                                    const armnn::TensorShape& input1Shape)
+{
+    return CalculateMaxShape(input0Shape, input1Shape);
+}
+
 TensorShape InferPadOutputShape(const TensorShape& inputShape,
                                 const std::vector<std::pair<unsigned int, unsigned int>>& padList)
 {
diff --git a/OutputShapeUtils.hpp b/OutputShapeUtils.hpp
index 2a832618..7452ced9 100644
--- a/OutputShapeUtils.hpp
+++ b/OutputShapeUtils.hpp
@@ -23,6 +23,9 @@ armnn::TensorShape InferDepthwiseConvolution2dOutputShape(const armnn::TensorSha
 armnn::TensorShape InferMaximumOutputShape(const armnn::TensorShape& input0Shape,
                                            const armnn::TensorShape& input1Shape);
 
+armnn::TensorShape InferMinimumOutputShape(const armnn::TensorShape& input0Shape,
+                                           const armnn::TensorShape& input1Shape);
+
 armnn::TensorShape InferPadOutputShape(const armnn::TensorShape& inputShape,
                                        const std::vector<std::pair<unsigned int, unsigned int>>& padList);
 
-- 
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