Add map for Resize1d (#69)

Signed-off-by: zhao.xia <zhao.xia@verisilicon.com>

include/tim/vx/ops/resize1d.h

@@ -0,0 +1,65 @@
+/****************************************************************************
+*
+*    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_RESIZE1D_H_
+#define TIM_VX_OPS_RESIZE1D_H_
+#include "tim/vx/operation.h"
+
+namespace tim {
+namespace vx {
+namespace ops {
+
+/**
+ * ## Resize1d
+ *
+ * Resize1ds 1D tensors to given size.
+ *
+ * - type : NEAREST_NEIGHBOR, BILINEAR or AREA.
+ * - factor : scale the input size. DO NOT use it with target_height / target_width together.
+ * - align_corners : If True, the centers of the 4 corner pixels of the input and output
+ * tensors are aligned, preserving the values at the corner pixels.
+ * - half_pixel_centers : If True, the pixel centers are assumed to be at (0.5, 0.5).
+ * This is the default behavior of image.resize in TF 2.0. If this parameter is True,
+ * then align_corners parameter must be False.
+ * - target_height / target_width : output height / width. DO NOT use it with factor together.
+ */
+
+class Resize1d : public Operation {
+ public:
+  Resize1d(Graph* graph, ResizeType type, float factor, bool align_corners,
+         bool half_pixel_centers, int target_size,
+         DataLayout layout = DataLayout::WHCN);
+
+ protected:
+  const ResizeType type_;
+  const float factor_;
+  const bool align_corners_;
+  const bool half_pixel_centers_;
+  const int target_size_;
+};
+
+}  // namespace ops
+}  // namespace vx
+}  // namespace tim
+
+#endif /* TIM_VX_OPS_RESIZE1D_H_ */

src/tim/vx/ops/README.md

@@ -150,7 +150,7 @@ Mish|MISH|Mapped|[tfa.activations.mish](https://tensorflow.google.cn/addons/api_
 ||SCATTER_ND|Unmapped|[tf.scatter_nd](https://tensorflow.google.cn/api_docs/python/tf/scatter_nd)
 |DeConv1d|DECONVOLUTION1D|Mapped|[tf.nn.conv1d_transpose](https://tensorflow.google.cn/api_docs/python/tf/nn/conv1d_transpose)
 ||INTERP|Unmapped
-||RESIZE_1D|Unmapped
+Resize1d|RESIZE_1D|Mapped|[Onnx.resize 1D image](https://github.com/onnx/onnx/blob/master/docs/Operators.md#resize)
 ||CONV_RELU|Deprecated
 ||CONV_RELU_POOL|Deprecated
 ||FCL|Deprecated

src/tim/vx/ops/resize1d.cc

@@ -0,0 +1,52 @@
+/****************************************************************************
+*
+*    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/resize1d.h"
+
+#include "operation_private.h"
+#include "type_utils.h"
+#include "vsi_nn_pub.h"
+
+namespace tim {
+namespace vx {
+namespace ops {
+
+Resize1d::Resize1d(Graph* graph, ResizeType type, float factor, bool align_corners,
+               bool half_pixel_centers, int target_size, DataLayout layout)
+    : Operation(graph, VSI_NN_OP_RESIZE_1D, 0, 0, layout),
+      type_(type),
+      factor_(factor),
+      align_corners_(align_corners),
+      half_pixel_centers_(half_pixel_centers),
+      target_size_(target_size) {
+  impl()->node()->nn_param.resize_1d.type = TranslateResizeType(type);
+  impl()->node()->nn_param.resize_1d.factor = factor;
+  impl()->node()->nn_param.resize_1d.align_corners = ToVxBool(align_corners);
+  impl()->node()->nn_param.resize_1d.half_pixel_centers =
+      ToVxBool(half_pixel_centers);
+  impl()->node()->nn_param.resize_1d.size[0] = target_size;
+}
+
+}  // namespace ops
+}  // namespace vx
+}  // namespace tim

src/tim/vx/ops/resize1d_test.cc

@@ -0,0 +1,114 @@
+/****************************************************************************
+*
+*    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/resize1d.h"
+
+#include "gtest/gtest.h"
+
+namespace {
+template<typename T>
+::testing::AssertionResult ArraysMatch(const std::vector<T>& expected,
+                                       const std::vector<T>& actual,
+                                       T abs_error){
+    for (size_t i = 0; i < expected.size(); ++i){
+        EXPECT_NEAR(expected[i], actual[i], abs_error) << "at index:" << i;
+    }
+
+    return ::testing::AssertionSuccess();
+}
+}
+
+TEST(Resize1d, shape_4_2_1_float_nearest_whcn) {
+    auto ctx = tim::vx::Context::Create();
+    auto graph = ctx->CreateGraph();
+
+    tim::vx::ShapeType input_shape({4, 2, 1});
+    tim::vx::ShapeType output_shape({2, 2, 1});
+    tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
+                            input_shape, tim::vx::TensorAttribute::INPUT);
+    tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
+                            output_shape, tim::vx::TensorAttribute::OUTPUT);
+
+    auto input_tensor = graph->CreateTensor(input_spec);
+    auto output_tensor = graph->CreateTensor(output_spec);
+
+    std::vector<float> in_data = {
+        1.f, 2.f, 3.f, 4.f,
+        5.f, 6.f, 7.f, 8.f,
+        };
+    std::vector<float> golden = {
+        1.f, 3.f,
+        5.f, 7.f,
+    };
+
+    EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size() * sizeof(float)));
+
+    auto op = graph->CreateOperation<tim::vx::ops::Resize1d>(
+        tim::vx::ResizeType::NEAREST_NEIGHBOR, 0.6, false, false, 0);
+    (*op).BindInputs({input_tensor}).BindOutputs({output_tensor});
+
+    EXPECT_TRUE(graph->Compile());
+    EXPECT_TRUE(graph->Run());
+
+    std::vector<float> output(golden.size() * sizeof(float));
+    EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
+    EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
+}
+
+TEST(Resize1d, shape_5_1_1_uint8_bilinear_align_corners_whcn) {
+    auto ctx = tim::vx::Context::Create();
+    auto graph = ctx->CreateGraph();
+
+    tim::vx::ShapeType input_shape({5, 1, 1});
+    tim::vx::ShapeType output_shape({7, 1, 1});
+    tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
+                            input_shape, tim::vx::TensorAttribute::INPUT);
+    tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
+                            output_shape, tim::vx::TensorAttribute::OUTPUT);
+
+    auto input_tensor = graph->CreateTensor(input_spec);
+    auto output_tensor = graph->CreateTensor(output_spec);
+
+    std::vector<float> in_data = {
+        1.f, 2.f, 3.f, 4.f, 5.f,
+        };
+    std::vector<float> golden = {
+        1.f, 1.66666f, 2.33333f, 3.f,
+        3.66666, 4.33333f, 5.f
+    };
+
+    EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size() * sizeof(float)));
+
+    auto op = graph->CreateOperation<tim::vx::ops::Resize1d>(
+        tim::vx::ResizeType::BILINEAR, 0, true, false, 7);
+    (*op).BindInputs({input_tensor}).BindOutputs({output_tensor});
+
+    EXPECT_TRUE(graph->Compile());
+    EXPECT_TRUE(graph->Run());
+
+    std::vector<float> output(golden.size() * sizeof(float));
+    EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
+    EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
+}