MLCE-347 'REDUCE_MIN, REDUCE_MAX, REDUCE_SUM Support'
* Added TfLiteParser support for REDUCE_MIN and REDUCE_MAX operators
* Added ACL workloads support for REDUCE_MIN, REDUCE_MAX, and REDUCE_SUM operators
* Added TfLite Delegate support for REDUCE_MIN, REDUCE_MAX, and REDUCE_SUM operators
Signed-off-by: Sadik Armagan <sadik.armagan@arm.com>
Change-Id: I8085d59946bfd4ab78a59a61f899031ae53371a8
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index 1b91576..8ce1667 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -631,6 +631,8 @@
m_ParserFunctions[tflite::BuiltinOperator_QUANTIZE] = &TfLiteParserImpl::ParseQuantize;
m_ParserFunctions[tflite::BuiltinOperator_RELU] = &TfLiteParserImpl::ParseRelu;
m_ParserFunctions[tflite::BuiltinOperator_RELU6] = &TfLiteParserImpl::ParseRelu6;
+ m_ParserFunctions[tflite::BuiltinOperator_REDUCE_MAX] = &TfLiteParserImpl::ParseReduceMax;
+ m_ParserFunctions[tflite::BuiltinOperator_REDUCE_MIN] = &TfLiteParserImpl::ParseReduceMin;
m_ParserFunctions[tflite::BuiltinOperator_RESHAPE] = &TfLiteParserImpl::ParseReshape;
m_ParserFunctions[tflite::BuiltinOperator_RESIZE_BILINEAR] = &TfLiteParserImpl::ParseResizeBilinear;
m_ParserFunctions[tflite::BuiltinOperator_RESIZE_NEAREST_NEIGHBOR] = &TfLiteParserImpl::ParseResizeNearestNeighbor;
@@ -3059,6 +3061,21 @@
void TfLiteParserImpl::ParseSum(size_t subgraphIndex, size_t operatorIndex)
{
+ ParseReduce(subgraphIndex, operatorIndex, armnn::ReduceOperation::Sum);
+}
+
+void TfLiteParserImpl::ParseReduceMax(size_t subgraphIndex, size_t operatorIndex)
+{
+ ParseReduce(subgraphIndex, operatorIndex, armnn::ReduceOperation::Max);
+}
+
+void TfLiteParserImpl::ParseReduceMin(size_t subgraphIndex, size_t operatorIndex)
+{
+ ParseReduce(subgraphIndex, operatorIndex, armnn::ReduceOperation::Min);
+}
+
+void TfLiteParserImpl::ParseReduce(size_t subgraphIndex, size_t operatorIndex, ReduceOperation reduceOperation)
+{
CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
const auto &operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
@@ -3070,7 +3087,7 @@
auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
CHECK_VALID_SIZE(outputs.size(), 1);
- auto layerName = fmt::format("Sum:{}:{}", subgraphIndex, operatorIndex);
+ auto layerName = fmt::format("Reduce:{}:{}", subgraphIndex, operatorIndex);
armnn::TensorInfo inputTensorInfo0 = ToTensorInfo(inputs[0]);
armnn::TensorInfo inputTensorInfo1 = ToTensorInfo(inputs[1]);
@@ -3088,11 +3105,18 @@
axisBufferPtr->data.data()[i]));
}
}
+ else
+ {
+ for (uint32_t i = 0; i < inputTensorInfo0.GetNumDimensions(); ++i)
+ {
+ desc.m_vAxis.push_back(i);
+ }
+ }
desc.m_TargetHeight = input0Shape[1];
desc.m_TargetWidth = input0Shape[2];
desc.m_KeepDims = options->keep_dims;
- desc.m_ReduceOperation = armnn::ReduceOperation::Sum;
+ desc.m_ReduceOperation = reduceOperation;
// Register a new layer object, Sum.
IConnectableLayer *layer = m_Network->AddReduceLayer(desc, layerName.c_str());
diff --git a/src/armnnTfLiteParser/TfLiteParser.hpp b/src/armnnTfLiteParser/TfLiteParser.hpp
index 2603d90..b59571e 100644
--- a/src/armnnTfLiteParser/TfLiteParser.hpp
+++ b/src/armnnTfLiteParser/TfLiteParser.hpp
@@ -124,6 +124,9 @@
void ParsePad(size_t subgraphIndex, size_t operatorIndex);
void ParsePool(size_t subgraphIndex, size_t operatorIndex, armnn::PoolingAlgorithm algorithm);
void ParseQuantize(size_t subgraphIndex, size_t operatorIndex);
+ void ParseReduce(size_t subgraphIndex, size_t operatorIndex, armnn::ReduceOperation reduceOperation);
+ void ParseReduceMax(size_t subgraphIndex, size_t operatorIndex);
+ void ParseReduceMin(size_t subgraphIndex, size_t operatorIndex);
void ParseRelu(size_t subgraphIndex, size_t operatorIndex);
void ParseRelu6(size_t subgraphIndex, size_t operatorIndex);
void ParseReshape(size_t subgraphIndex, size_t operatorIndex);
diff --git a/src/armnnTfLiteParser/test/Reduce.cpp b/src/armnnTfLiteParser/test/Reduce.cpp
new file mode 100644
index 0000000..622d54e
--- /dev/null
+++ b/src/armnnTfLiteParser/test/Reduce.cpp
@@ -0,0 +1,193 @@
+//
+// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include <boost/test/unit_test.hpp>
+#include "ParserFlatbuffersFixture.hpp"
+#include "../TfLiteParser.hpp"
+
+#include <string>
+#include <iostream>
+
+BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)
+
+struct ReduceMaxFixture : public ParserFlatbuffersFixture
+{
+ explicit ReduceMaxFixture(const std::string& inputShape,
+ const std::string& outputShape,
+ const std::string& axisShape,
+ const std::string& axisData)
+ {
+ m_JsonString = R"(
+ {
+ "version": 3,
+ "operator_codes": [ { "builtin_code": "REDUCE_MAX" } ],
+ "subgraphs": [ {
+ "tensors": [
+ {
+ "shape": )" + inputShape + R"(,
+ "type": "FLOAT32",
+ "buffer": 0,
+ "name": "inputTensor",
+ "quantization": {
+ "min": [ 0.0 ],
+ "max": [ 255.0 ],
+ "scale": [ 1.0 ],
+ "zero_point": [ 0 ],
+ }
+ },
+ {
+ "shape": )" + outputShape + R"( ,
+ "type": "FLOAT32",
+ "buffer": 1,
+ "name": "outputTensor",
+ "quantization": {
+ "min": [ 0.0 ],
+ "max": [ 255.0 ],
+ "scale": [ 1.0 ],
+ "zero_point": [ 0 ],
+ }
+ },
+ {
+ "shape": )" + axisShape + R"( ,
+ "type": "INT32",
+ "buffer": 2,
+ "name": "axis",
+ "quantization": {
+ "min": [ 0.0 ],
+ "max": [ 255.0 ],
+ "scale": [ 1.0 ],
+ "zero_point": [ 0 ],
+ }
+ }
+ ],
+ "inputs": [ 0 ],
+ "outputs": [ 1 ],
+ "operators": [
+ {
+ "opcode_index": 0,
+ "inputs": [ 0 , 2 ],
+ "outputs": [ 1 ],
+ "builtin_options_type": "ReducerOptions",
+ "builtin_options": {
+ "keep_dims": true,
+ },
+ "custom_options_format": "FLEXBUFFERS"
+ }
+ ],
+ } ],
+ "buffers" : [
+ { },
+ { },
+ { "data": )" + axisData + R"(, },
+ ]
+ }
+ )";
+ SetupSingleInputSingleOutput("inputTensor", "outputTensor");
+ }
+};
+
+struct SimpleReduceMaxFixture : public ReduceMaxFixture
+{
+ SimpleReduceMaxFixture() : ReduceMaxFixture("[ 1, 1, 2, 3 ]", "[ 1, 1, 1, 3 ]", "[ 1 ]", "[ 2 ]") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(ParseReduceMax, SimpleReduceMaxFixture)
+{
+ RunTest<4, armnn::DataType::Float32, armnn::DataType::Float32>
+ (0, {{ "inputTensor", { 1001.0f, 11.0f, 1003.0f,
+ 10.0f, 1002.0f, 12.0f } } },
+ {{ "outputTensor", { 1001.0f, 1002.0f, 1003.0f } } });
+}
+
+struct ReduceMinFixture : public ParserFlatbuffersFixture
+{
+ explicit ReduceMinFixture(const std::string& inputShape,
+ const std::string& outputShape,
+ const std::string& axisShape,
+ const std::string& axisData)
+ {
+ m_JsonString = R"(
+ {
+ "version": 3,
+ "operator_codes": [ { "builtin_code": "REDUCE_MIN" } ],
+ "subgraphs": [ {
+ "tensors": [
+ {
+ "shape": )" + inputShape + R"(,
+ "type": "FLOAT32",
+ "buffer": 0,
+ "name": "inputTensor",
+ "quantization": {
+ "min": [ 0.0 ],
+ "max": [ 255.0 ],
+ "scale": [ 1.0 ],
+ "zero_point": [ 0 ],
+ }
+ },
+ {
+ "shape": )" + outputShape + R"( ,
+ "type": "FLOAT32",
+ "buffer": 1,
+ "name": "outputTensor",
+ "quantization": {
+ "min": [ 0.0 ],
+ "max": [ 255.0 ],
+ "scale": [ 1.0 ],
+ "zero_point": [ 0 ],
+ }
+ },
+ {
+ "shape": )" + axisShape + R"( ,
+ "type": "INT32",
+ "buffer": 2,
+ "name": "axis",
+ "quantization": {
+ "min": [ 0.0 ],
+ "max": [ 255.0 ],
+ "scale": [ 1.0 ],
+ "zero_point": [ 0 ],
+ }
+ }
+ ],
+ "inputs": [ 0 ],
+ "outputs": [ 1 ],
+ "operators": [
+ {
+ "opcode_index": 0,
+ "inputs": [ 0 , 2 ],
+ "outputs": [ 1 ],
+ "builtin_options_type": "ReducerOptions",
+ "builtin_options": {
+ "keep_dims": true,
+ },
+ "custom_options_format": "FLEXBUFFERS"
+ }
+ ],
+ } ],
+ "buffers" : [
+ { },
+ { },
+ { "data": )" + axisData + R"(, },
+ ]
+ }
+ )";
+ SetupSingleInputSingleOutput("inputTensor", "outputTensor");
+ }
+};
+
+struct SimpleReduceMinFixture : public ReduceMinFixture
+{
+ SimpleReduceMinFixture() : ReduceMinFixture("[ 1, 1, 2, 3 ]", "[ 1, 1, 1, 3 ]", "[ 1 ]", "[ 2 ]") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(ParseReduceMin, SimpleReduceMinFixture)
+{
+ RunTest<4, armnn::DataType::Float32, armnn::DataType::Float32>
+ (0, {{ "inputTensor", { 1001.0f, 11.0f, 1003.0f,
+ 10.0f, 1002.0f, 12.0f } } },
+ {{ "outputTensor", { 10.0f, 11.0f, 12.0f } } });
+}
+
+BOOST_AUTO_TEST_SUITE_END()