Add support for relational ops

Signed-off-by: Kainan Cha <kainan.zha@verisilicon.com>

include/tim/vx/ops/relational_operations.h

@@ -0,0 +1,51 @@
+/****************************************************************************
+*
+*    Copyright (c) 2021 Vivante Corporation
+*
+*    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.
+*
+*****************************************************************************/
+#ifndef TIM_VX_OPS_RELATIONAL_H_
+#define TIM_VX_OPS_RELATIONAL_H_
+#include "tim/vx/operation.h"
+
+namespace tim {
+namespace vx {
+namespace ops {
+
+#define DECLARE_RELATIONAL_OP(NAME)  \
+  class NAME : public Operation {    \
+   public:                           \
+    NAME(Graph* graph);              \
+  };
+
+DECLARE_RELATIONAL_OP(Greater)
+DECLARE_RELATIONAL_OP(GreaterOrEqual)
+DECLARE_RELATIONAL_OP(Less)
+DECLARE_RELATIONAL_OP(LessOrEqual)
+DECLARE_RELATIONAL_OP(NotEqual)
+DECLARE_RELATIONAL_OP(Equal)
+
+#undef DECLARE_RELATIONAL_OP
+
+}  // namespace ops
+}  // namespace vx
+}  // namespace tim
+
+#endif /* TIM_VX_OPS_RELATIONAL_H_ */

include/tim/vx/types.h

@@ -36,7 +36,8 @@ enum class DataType {
   INT32,
   UINT32,
   FLOAT16,
-  FLOAT32
+  FLOAT32,
+  BOOL8
 };
 
 enum class QuantType { NONE, ASYMMETRIC, SYMMETRIC_PER_CHANNEL };

src/tim/CMakeLists.txt

@@ -16,6 +16,7 @@ list(REMOVE_ITEM SRC ./vx/context_test.cc)
 list(REMOVE_ITEM SRC ./vx/graph_test.cc)
 list(REMOVE_ITEM SRC ./vx/ops/reorg_test.cc)
 list(REMOVE_ITEM SRC ./vx/ops/simple_operations_test.cc)
+list(REMOVE_ITEM SRC ./vx/ops/relational_operations_test.cc)
 
 include_directories(${PROJECT_SOURCE_DIR}/include)
 include_directories(${PROJECT_SOURCE_DIR}/include/tim/vx)

src/tim/vx/ops/README.md

@@ -59,7 +59,11 @@ Pad|PAD|Mapped
 ||MATRIXMUL|Unmapped
 ||LSTMUNIT|Unmapped
 ||LAYER_NORM|Unmapped
-Min/Max/Any/prod/Mean|REDUCE|Mapped
+ReduceMin|REDUCE_MIN|Mapped
+ReduceMax|REDUCE_MAX|Mapped
+ReduceAny|REDUCE_ANY|Mapped
+ReduceProd|REDUCE_PROD|Mapped
+ReduceMean|REDUCE_MEAN|Mapped
 ||INSTANCE_NORM|Unmapped
 ||TENSORSTACKCONCAT|Unmapped
 StridedSlice|STRIDED_SLICE|Mapped
@@ -71,7 +75,12 @@ Abs|ABS|Mapped
 NBG|NBG|Mapped
 ||CONCATSHIFT|Unmapped
 LocalResponseNormalization|LRN2|Mapped
-||RELATIONAL_OPS|Unmapped
+Greater|RELATIONAL_OPS_GREATER|Mapped
+GreaterOrEqual|RELATIONAL_OPS_GREATER_EQUAL|Mapped
+Less|RELATIONAL_OPS_LESS|Mapped
+LessOrEqual|RELATIONAL_OPS_LESS_EQUAL|Mapped
+Equal|RELATIONAL_OPS_EQUAL|Mapped
+NotEqual|RELATIONAL_OPS_NOT_EQUAL|Mapped
 ||SYNC_HOST|Unmapped
 Pow|POW|Mapped
 ||FLOORDIV|Unmapped

src/tim/vx/ops/relational_operations.cc

@@ -0,0 +1,49 @@
+/****************************************************************************
+*
+*    Copyright (c) 2021 Vivante Corporation
+*
+*    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 "tim/vx/ops/relational_operations.h"
+
+#include "operation_private.h"
+#include "vsi_nn_pub.h"
+
+namespace tim {
+namespace vx {
+namespace ops {
+
+#define DEFINE_RELATIONAL_OP(NAME, VSI_OP_CODE) \
+  NAME::NAME(Graph* graph) : Operation(graph, VSI_NN_OP_RELATIONAL_OPS, 2, 1) { \
+    this->impl()->node()->nn_param.relational_ops.op = VSI_OP_CODE;    \
+  }
+
+DEFINE_RELATIONAL_OP(Greater, VSI_NN_RELATIONAL_OPS_GREAT)
+DEFINE_RELATIONAL_OP(GreaterOrEqual, VSI_NN_RELATIONAL_OPS_GREAT_EQUAL)
+DEFINE_RELATIONAL_OP(Less, VSI_NN_RELATIONAL_OPS_LESS)
+DEFINE_RELATIONAL_OP(LessOrEqual, VSI_NN_RELATIONAL_OPS_LESS_EQUAL)
+DEFINE_RELATIONAL_OP(NotEqual, VSI_NN_RELATIONAL_OPS_NOT_EQUAL)
+DEFINE_RELATIONAL_OP(Equal, VSI_NN_RELATIONAL_OPS_EQUAL)
+
+#undef DEFINE_RELATIONAL_OP
+
+}  // namespace ops
+}  // namespace vx
+}  // namespace tim

src/tim/vx/ops/relational_operations_test.cc

@@ -0,0 +1,252 @@
+/****************************************************************************
+*
+*    Copyright (c) 2021 Vivante Corporation
+*
+*    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 "tim/vx/context.h"
+#include "tim/vx/graph.h"
+#include "tim/vx/ops/relational_operations.h"
+
+#include "gtest/gtest.h"
+
+TEST(OP, equal_shape_1_uint8) {
+    auto ctx = tim::vx::Context::Create();
+    auto graph = ctx->CreateGraph();
+
+    tim::vx::ShapeType io_shape({1});
+    tim::vx::Quantization quant(tim::vx::QuantType::ASYMMETRIC, 1, 0);
+    tim::vx::TensorSpec input_spec(tim::vx::DataType::UINT8,
+                            io_shape, tim::vx::TensorAttribute::INPUT, quant);
+    tim::vx::TensorSpec output_spec(tim::vx::DataType::BOOL8,
+                            io_shape, tim::vx::TensorAttribute::OUTPUT);
+
+    auto input_tensor1 = graph->CreateTensor(input_spec);
+    auto input_tensor2 = graph->CreateTensor(input_spec);
+    auto output_tensor = graph->CreateTensor(output_spec);
+
+    std::vector<uint8_t> in_data1 = { 255 };
+    std::vector<uint8_t> in_data2 = { 0 };
+
+    std::vector<uint8_t> golden = {0};
+
+    EXPECT_TRUE(input_tensor1->CopyDataToTensor(in_data1.data(), in_data1.size()));
+    EXPECT_TRUE(input_tensor2->CopyDataToTensor(in_data2.data(), in_data2.size()));
+
+    auto add = graph->CreateOperation<tim::vx::ops::Equal>();
+    (*add).BindInputs({input_tensor1, input_tensor2}).BindOutputs({output_tensor});
+
+    EXPECT_TRUE(graph->Compile());
+    EXPECT_TRUE(graph->Run());
+
+    //Not using vector<bool> because it uses a bitfield representation internally
+    //and it's cumbersome to copy tensor data to it.
+    std::vector<uint8_t> output(1, 0);
+    EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
+    EXPECT_EQ(golden, output);
+}
+
+TEST(OP, notequal_shape_5_fp32) {
+    auto ctx = tim::vx::Context::Create();
+    auto graph = ctx->CreateGraph();
+
+    tim::vx::ShapeType io_shape({5});
+    tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
+                            io_shape, tim::vx::TensorAttribute::INPUT);
+    tim::vx::TensorSpec output_spec(tim::vx::DataType::BOOL8,
+                            io_shape, tim::vx::TensorAttribute::OUTPUT);
+
+    auto input_tensor1 = graph->CreateTensor(input_spec);
+    auto input_tensor2 = graph->CreateTensor(input_spec);
+    auto output_tensor = graph->CreateTensor(output_spec);
+
+    std::vector<float> in_data1 = { -2.5, -0.1, 0, 0.55, std::numeric_limits<float>::infinity() };
+    std::vector<float> in_data2 = { -2, -1, 0.2, 0.55, std::numeric_limits<float>::infinity() };
+
+    std::vector<uint8_t> golden = {1, 1, 1, 0, 0};
+
+    EXPECT_TRUE(input_tensor1->CopyDataToTensor(in_data1.data(), in_data1.size()));
+    EXPECT_TRUE(input_tensor2->CopyDataToTensor(in_data2.data(), in_data2.size()));
+
+    auto add = graph->CreateOperation<tim::vx::ops::NotEqual>();
+    (*add).BindInputs({input_tensor1, input_tensor2}).BindOutputs({output_tensor});
+
+    EXPECT_TRUE(graph->Compile());
+    EXPECT_TRUE(graph->Run());
+
+    //Not using vector<bool> because it uses a bitfield representation internally
+    //and it's cumbersome to copy tensor data to it.
+    std::vector<uint8_t> output(5, 0);
+    EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
+    EXPECT_EQ(golden, output);
+}
+
+TEST(OP, less_shape_5_1_fp32) {
+    auto ctx = tim::vx::Context::Create();
+    auto graph = ctx->CreateGraph();
+
+    tim::vx::ShapeType io_shape({1,5});
+    tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
+                            io_shape, tim::vx::TensorAttribute::INPUT);
+    tim::vx::TensorSpec output_spec(tim::vx::DataType::BOOL8,
+                            io_shape, tim::vx::TensorAttribute::OUTPUT);
+
+    auto input_tensor1 = graph->CreateTensor(input_spec);
+    auto input_tensor2 = graph->CreateTensor(input_spec);
+    auto output_tensor = graph->CreateTensor(output_spec);
+
+    std::vector<float> in_data1 = { 0.1, 0.1, 0, 0.55, std::numeric_limits<float>::infinity() };
+    std::vector<float> in_data2 = { -1, -1, 0.2, 0.55, std::numeric_limits<float>::infinity() };
+
+    std::vector<uint8_t> golden = {0, 0, 1, 0, 0};
+
+    EXPECT_TRUE(input_tensor1->CopyDataToTensor(in_data1.data(), in_data1.size()));
+    EXPECT_TRUE(input_tensor2->CopyDataToTensor(in_data2.data(), in_data2.size()));
+
+    auto add = graph->CreateOperation<tim::vx::ops::Less>();
+    (*add).BindInputs({input_tensor1, input_tensor2}).BindOutputs({output_tensor});
+
+    EXPECT_TRUE(graph->Compile());
+    EXPECT_TRUE(graph->Run());
+
+    //Not using vector<bool> because it uses a bitfield representation internally
+    //and it's cumbersome to copy tensor data to it.
+    std::vector<uint8_t> output(5, 0);
+    EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
+    EXPECT_EQ(golden, output);
+}
+
+TEST(OP, greaterorequal_shape_5_2_1_fp32) {
+    auto ctx = tim::vx::Context::Create();
+    auto graph = ctx->CreateGraph();
+
+    tim::vx::ShapeType io_shape({5,2,1});
+    tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
+                            io_shape, tim::vx::TensorAttribute::INPUT);
+    tim::vx::TensorSpec output_spec(tim::vx::DataType::BOOL8,
+                            io_shape, tim::vx::TensorAttribute::OUTPUT);
+
+    auto input_tensor1 = graph->CreateTensor(input_spec);
+    auto input_tensor2 = graph->CreateTensor(input_spec);
+    auto output_tensor = graph->CreateTensor(output_spec);
+
+    std::vector<float> in_data1 = {
+        -2.5, -0.1, 0, 0.55, std::numeric_limits<float>::infinity(),
+        -2.5, -0.1, 0, 0.55, std::numeric_limits<float>::infinity() };
+    std::vector<float> in_data2 = {
+        -2, -1, 0.2, 0.55, std::numeric_limits<float>::infinity(),
+        -2, -1, 0.2, 0.55, std::numeric_limits<float>::infinity() };
+
+    std::vector<uint8_t> golden = {0, 1, 0, 1, 1, 0, 1, 0, 1, 1};
+
+    EXPECT_TRUE(input_tensor1->CopyDataToTensor(in_data1.data(), in_data1.size()));
+    EXPECT_TRUE(input_tensor2->CopyDataToTensor(in_data2.data(), in_data2.size()));
+
+    auto add = graph->CreateOperation<tim::vx::ops::GreaterOrEqual>();
+    (*add).BindInputs({input_tensor1, input_tensor2}).BindOutputs({output_tensor});
+
+    EXPECT_TRUE(graph->Compile());
+    EXPECT_TRUE(graph->Run());
+
+    //Not using vector<bool> because it uses a bitfield representation internally
+    //and it's cumbersome to copy tensor data to it.
+    std::vector<uint8_t> output(10, 0);
+    EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
+    EXPECT_EQ(golden, output);
+}
+
+TEST(OP, greater_shape_5_2_1_1_fp32) {
+    auto ctx = tim::vx::Context::Create();
+    auto graph = ctx->CreateGraph();
+
+    tim::vx::ShapeType io_shape({5,2,1,1});
+    tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
+                            io_shape, tim::vx::TensorAttribute::INPUT);
+    tim::vx::TensorSpec output_spec(tim::vx::DataType::BOOL8,
+                            io_shape, tim::vx::TensorAttribute::OUTPUT);
+
+    auto input_tensor1 = graph->CreateTensor(input_spec);
+    auto input_tensor2 = graph->CreateTensor(input_spec);
+    auto output_tensor = graph->CreateTensor(output_spec);
+
+    std::vector<float> in_data1 = {
+        -2.5, -0.1, 0, 0.55, std::numeric_limits<float>::infinity(),
+        -2.5, -0.1, 0, 0.55, std::numeric_limits<float>::infinity() };
+    std::vector<float> in_data2 = {
+        -2, -1, 0.2, 0.55, std::numeric_limits<float>::infinity(),
+        -2, -1, 0.2, 0.55, std::numeric_limits<float>::infinity() };
+
+    std::vector<uint8_t> golden = {0, 1, 0, 0, 0, 0, 1, 0, 0, 0};
+
+    EXPECT_TRUE(input_tensor1->CopyDataToTensor(in_data1.data(), in_data1.size()));
+    EXPECT_TRUE(input_tensor2->CopyDataToTensor(in_data2.data(), in_data2.size()));
+
+    auto add = graph->CreateOperation<tim::vx::ops::Greater>();
+    (*add).BindInputs({input_tensor1, input_tensor2}).BindOutputs({output_tensor});
+
+    EXPECT_TRUE(graph->Compile());
+    EXPECT_TRUE(graph->Run());
+
+    //Not using vector<bool> because it uses a bitfield representation internally
+    //and it's cumbersome to copy tensor data to it.
+    std::vector<uint8_t> output(10, 0);
+    EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
+    EXPECT_EQ(golden, output);
+}
+
+TEST(OP, lessorequal_shape_1_5_2_1_1_fp32) {
+    auto ctx = tim::vx::Context::Create();
+    auto graph = ctx->CreateGraph();
+
+    tim::vx::ShapeType io_shape({1,5,2,1,1});
+    tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
+                            io_shape, tim::vx::TensorAttribute::INPUT);
+    tim::vx::TensorSpec output_spec(tim::vx::DataType::BOOL8,
+                            io_shape, tim::vx::TensorAttribute::OUTPUT);
+
+    auto input_tensor1 = graph->CreateTensor(input_spec);
+    auto input_tensor2 = graph->CreateTensor(input_spec);
+    auto output_tensor = graph->CreateTensor(output_spec);
+
+    std::vector<float> in_data1 = {
+        -2.5, -0.1, 0, 0.55, std::numeric_limits<float>::infinity(),
+        -2.5, -0.1, 0, 0.55, std::numeric_limits<float>::infinity() };
+    std::vector<float> in_data2 = {
+        -2, -1, 0.2, 0.55, std::numeric_limits<float>::infinity(),
+        -2, -1, 0.2, 0.55, std::numeric_limits<float>::infinity() };
+
+    std::vector<uint8_t> golden = {1, 0, 1, 1, 1, 1, 0, 1, 1, 1};
+
+    EXPECT_TRUE(input_tensor1->CopyDataToTensor(in_data1.data(), in_data1.size()));
+    EXPECT_TRUE(input_tensor2->CopyDataToTensor(in_data2.data(), in_data2.size()));
+
+    auto add = graph->CreateOperation<tim::vx::ops::LessOrEqual>();
+    (*add).BindInputs({input_tensor1, input_tensor2}).BindOutputs({output_tensor});
+
+    EXPECT_TRUE(graph->Compile());
+    EXPECT_TRUE(graph->Run());
+
+    //Not using vector<bool> because it uses a bitfield representation internally
+    //and it's cumbersome to copy tensor data to it.
+    std::vector<uint8_t> output(10, 0);
+    EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
+    EXPECT_EQ(golden, output);
+}
+

src/tim/vx/type_utils.cc

@@ -43,6 +43,8 @@ vsi_nn_type_e TranslateDataType(DataType dtype) {
       return VSI_NN_TYPE_FLOAT16;
     case DataType::FLOAT32:
       return VSI_NN_TYPE_FLOAT32;
+    case DataType::BOOL8:
+      return VSI_NN_TYPE_BOOL8;
     default:
       break;
   }