390 lines
17 KiB
C++
390 lines
17 KiB
C++
// Copyright 2022 Google LLC
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//
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// This source code is licensed under the BSD-style license found in the
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// LICENSE file in the root directory of this source tree.
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#include <algorithm> // For std::generate, std::min.
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#include <array> // For std::array.
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#include <cmath> // For std::lrintf.
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#include <cstddef> // For size_t.
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#include <cstdint> // For uint32_t.
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#include <limits> // For std::numeric_limits.
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#include <memory> // For std::unique_ptr.
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#include <random> // For std::random_device, std::mt19937, std::uniform_real_distribution.
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#include <vector> // For std::vector.
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#include <xnnpack.h>
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#include <xnnpack/operator.h>
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#include <xnnpack/subgraph.h>
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#include <gtest/gtest.h>
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template <class T> class StaticResizeBilinear2DTestBase : public ::testing::Test {
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protected:
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StaticResizeBilinear2DTestBase()
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{
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random_device = std::unique_ptr<std::random_device>(new std::random_device());
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rng = std::mt19937((*random_device)());
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input_size_dist = std::uniform_int_distribution<uint32_t>(10, 15);
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kernel_size_dist = std::uniform_int_distribution<uint32_t>(2, 5);
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stride_dist = std::uniform_int_distribution<uint32_t>(1, 2);
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f32dist = std::uniform_real_distribution<float>();
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scale_dist = std::uniform_real_distribution<float>(1.0f, 5.0f);
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i32dist = std::uniform_int_distribution<int32_t>(-10000, 10000);
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dilation_dist = std::uniform_int_distribution<uint32_t>(1, 2);
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i8dist =
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std::uniform_int_distribution<int32_t>(std::numeric_limits<int8_t>::min(), std::numeric_limits<int8_t>::max());
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u8dist =
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std::uniform_int_distribution<int32_t>(std::numeric_limits<uint8_t>::min(), std::numeric_limits<uint8_t>::max());
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batch_size = input_size_dist(rng);
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input_height = input_size_dist(rng);
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input_width = input_size_dist(rng);
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channels = input_size_dist(rng);
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output_height = input_size_dist(rng);
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output_width = input_size_dist(rng);
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input_dims = {{batch_size, input_height, input_width, channels}};
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output_dims = {{batch_size, output_height, output_width, channels}};
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input = std::vector<T>(XNN_EXTRA_BYTES / sizeof(T) + batch_size * input_height * input_width * channels);
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operator_output = std::vector<T>(batch_size * output_height * output_width * channels);
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subgraph_output = std::vector<T>(batch_size * output_height * output_width * channels);
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}
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std::unique_ptr<std::random_device> random_device;
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std::mt19937 rng;
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std::uniform_int_distribution<uint32_t> input_size_dist;
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std::uniform_int_distribution<uint32_t> kernel_size_dist;
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std::uniform_int_distribution<uint32_t> stride_dist;
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std::uniform_int_distribution<int32_t> i32dist;
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std::uniform_real_distribution<float> f32dist;
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std::uniform_real_distribution<float> scale_dist;
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std::uniform_int_distribution<uint32_t> dilation_dist;
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std::uniform_int_distribution<int32_t> i8dist;
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std::uniform_int_distribution<int32_t> u8dist;
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uint32_t batch_size;
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uint32_t input_height;
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uint32_t input_width;
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uint32_t channels;
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uint32_t output_height;
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uint32_t output_width;
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std::array<size_t, 4> input_dims;
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std::array<size_t, 4> output_dims;
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std::vector<T> input;
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std::vector<T> operator_output;
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std::vector<T> subgraph_output;
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};
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using StaticResizeBilinear2DTestQS8 = StaticResizeBilinear2DTestBase<int8_t>;
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using StaticResizeBilinear2DTestQU8 = StaticResizeBilinear2DTestBase<uint8_t>;
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using StaticResizeBilinear2DTestF32 = StaticResizeBilinear2DTestBase<float>;
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TEST_F(StaticResizeBilinear2DTestQS8, define)
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{
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ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
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xnn_subgraph_t subgraph = nullptr;
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ASSERT_EQ(xnn_status_success, xnn_create_subgraph(2, /*flags=*/0, &subgraph));
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std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph);
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uint32_t input_id = XNN_INVALID_NODE_ID;
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ASSERT_EQ(
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xnn_status_success, xnn_define_quantized_tensor_value(
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subgraph, xnn_datatype_qint8, 0, 1.0f, input_dims.size(), input_dims.data(), nullptr,
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/*external_id=*/0, /*flags=*/0, &input_id));
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ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
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uint32_t output_id = XNN_INVALID_NODE_ID;
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ASSERT_EQ(
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xnn_status_success, xnn_define_quantized_tensor_value(
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subgraph, xnn_datatype_qint8, 0, 1.0f, output_dims.size(), output_dims.data(), nullptr,
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/*external_id=*/1, /*flags=*/0, &output_id));
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ASSERT_NE(output_id, XNN_INVALID_NODE_ID);
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ASSERT_EQ(
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xnn_status_success,
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xnn_define_static_resize_bilinear_2d(subgraph, output_height, output_width, input_id, output_id, /*flags=*/0));
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ASSERT_EQ(subgraph->num_nodes, 1);
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const struct xnn_node* node = &subgraph->nodes[0];
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ASSERT_EQ(node->type, xnn_node_type_static_resize_bilinear_2d);
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ASSERT_EQ(node->compute_type, xnn_compute_type_qs8);
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ASSERT_EQ(node->params.static_resize.new_height, output_height);
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ASSERT_EQ(node->params.static_resize.new_width, output_width);
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ASSERT_EQ(node->num_inputs, 1);
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ASSERT_EQ(node->inputs[0], input_id);
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ASSERT_EQ(node->num_outputs, 1);
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ASSERT_EQ(node->outputs[0], output_id);
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ASSERT_EQ(node->flags, 0);
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}
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TEST_F(StaticResizeBilinear2DTestQU8, define)
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{
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ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
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xnn_subgraph_t subgraph = nullptr;
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ASSERT_EQ(xnn_status_success, xnn_create_subgraph(2, /*flags=*/0, &subgraph));
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std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph);
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uint32_t input_id = XNN_INVALID_NODE_ID;
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ASSERT_EQ(
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xnn_status_success, xnn_define_quantized_tensor_value(
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subgraph, xnn_datatype_quint8, 0, 1.0f, input_dims.size(), input_dims.data(), nullptr,
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/*external_id=*/0, /*flags=*/0, &input_id));
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ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
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uint32_t output_id = XNN_INVALID_NODE_ID;
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ASSERT_EQ(
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xnn_status_success, xnn_define_quantized_tensor_value(
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subgraph, xnn_datatype_quint8, 0, 1.0f, output_dims.size(), output_dims.data(), nullptr,
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/*external_id=*/1, /*flags=*/0, &output_id));
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ASSERT_NE(output_id, XNN_INVALID_NODE_ID);
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ASSERT_EQ(
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xnn_status_success,
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xnn_define_static_resize_bilinear_2d(subgraph, output_height, output_width, input_id, output_id, /*flags=*/0));
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ASSERT_EQ(subgraph->num_nodes, 1);
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const struct xnn_node* node = &subgraph->nodes[0];
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ASSERT_EQ(node->type, xnn_node_type_static_resize_bilinear_2d);
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ASSERT_EQ(node->compute_type, xnn_compute_type_qu8);
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ASSERT_EQ(node->params.static_resize.new_height, output_height);
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ASSERT_EQ(node->params.static_resize.new_width, output_width);
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ASSERT_EQ(node->num_inputs, 1);
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ASSERT_EQ(node->inputs[0], input_id);
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ASSERT_EQ(node->num_outputs, 1);
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ASSERT_EQ(node->outputs[0], output_id);
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ASSERT_EQ(node->flags, 0);
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}
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TEST_F(StaticResizeBilinear2DTestF32, define)
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{
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ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
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xnn_subgraph_t subgraph = nullptr;
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ASSERT_EQ(xnn_status_success, xnn_create_subgraph(2, /*flags=*/0, &subgraph));
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std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph);
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uint32_t input_id = XNN_INVALID_NODE_ID;
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ASSERT_EQ(
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xnn_status_success, xnn_define_tensor_value(
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subgraph, xnn_datatype_fp32, input_dims.size(), input_dims.data(), nullptr,
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/*external_id=*/0, /*flags=*/0, &input_id));
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ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
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uint32_t output_id = XNN_INVALID_NODE_ID;
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ASSERT_EQ(
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xnn_status_success, xnn_define_tensor_value(
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subgraph, xnn_datatype_fp32, output_dims.size(), output_dims.data(), nullptr,
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/*external_id=*/1, /*flags=*/0, &output_id));
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ASSERT_NE(output_id, XNN_INVALID_NODE_ID);
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ASSERT_EQ(
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xnn_status_success,
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xnn_define_static_resize_bilinear_2d(subgraph, output_height, output_width, input_id, output_id, /*flags=*/0));
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ASSERT_EQ(subgraph->num_nodes, 1);
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const struct xnn_node* node = &subgraph->nodes[0];
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ASSERT_EQ(node->type, xnn_node_type_static_resize_bilinear_2d);
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ASSERT_EQ(node->compute_type, xnn_compute_type_fp32);
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ASSERT_EQ(node->params.static_resize.new_height, output_height);
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ASSERT_EQ(node->params.static_resize.new_width, output_width);
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ASSERT_EQ(node->num_inputs, 1);
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ASSERT_EQ(node->inputs[0], input_id);
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ASSERT_EQ(node->num_outputs, 1);
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ASSERT_EQ(node->outputs[0], output_id);
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ASSERT_EQ(node->flags, 0);
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}
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TEST_F(StaticResizeBilinear2DTestQS8, matches_operator_api)
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{
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ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
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std::generate(input.begin(), input.end(), [&]() { return i8dist(rng); });
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std::fill(operator_output.begin(), operator_output.end(), INT8_C(0xA5));
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std::fill(subgraph_output.begin(), subgraph_output.end(), INT8_C(0xA5));
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const int8_t input_zero_point = i8dist(rng);
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const float input_scale = scale_dist(rng);
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const float output_zero_point = input_zero_point;
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const float output_scale = input_scale;
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// Call operator API.
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xnn_operator_t op = nullptr;
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const xnn_status status = xnn_create_resize_bilinear2d_nhwc_s8(channels, channels, channels, /*flags=*/0, &op);
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std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_op(op, xnn_delete_operator);
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if (status == xnn_status_unsupported_hardware) {
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GTEST_SKIP();
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}
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ASSERT_EQ(xnn_status_success, status);
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ASSERT_NE(nullptr, op);
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ASSERT_EQ(
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xnn_status_success,
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xnn_setup_resize_bilinear2d_nhwc_s8(
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op, batch_size, input_height, input_width, output_height, output_width, input.data(), operator_output.data(),
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/*threadpool=*/nullptr));
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ASSERT_EQ(xnn_status_success, xnn_run_operator(op, /*threadpool=*/nullptr));
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// Call subgraph API.
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xnn_subgraph_t subgraph = nullptr;
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ASSERT_EQ(xnn_status_success, xnn_create_subgraph(2, /*flags=*/0, &subgraph));
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std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph);
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uint32_t input_id = XNN_INVALID_NODE_ID;
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ASSERT_EQ(
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xnn_status_success, xnn_define_quantized_tensor_value(
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subgraph, xnn_datatype_qint8, input_zero_point, input_scale, input_dims.size(),
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input_dims.data(), nullptr, /*external_id=*/0, XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id));
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ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
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uint32_t output_id = XNN_INVALID_NODE_ID;
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ASSERT_EQ(
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xnn_status_success, xnn_define_quantized_tensor_value(
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subgraph, xnn_datatype_qint8, output_zero_point, output_scale, output_dims.size(),
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output_dims.data(), nullptr, /*external_id=*/1, XNN_VALUE_FLAG_EXTERNAL_OUTPUT, &output_id));
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ASSERT_NE(output_id, XNN_INVALID_NODE_ID);
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ASSERT_EQ(
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xnn_status_success,
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xnn_define_static_resize_bilinear_2d(subgraph, output_height, output_width, input_id, output_id, /*flags=*/0));
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xnn_runtime_t runtime = nullptr;
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ASSERT_EQ(xnn_status_success, xnn_create_runtime_v3(subgraph, nullptr, nullptr, /*flags=*/0, &runtime));
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ASSERT_NE(nullptr, runtime);
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std::unique_ptr<xnn_runtime, decltype(&xnn_delete_runtime)> auto_runtime(runtime, xnn_delete_runtime);
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std::array<xnn_external_value, 2> external = {
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xnn_external_value{input_id, input.data()}, xnn_external_value{output_id, subgraph_output.data()}};
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ASSERT_EQ(xnn_status_success, xnn_setup_runtime(runtime, external.size(), external.data()));
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ASSERT_EQ(xnn_status_success, xnn_invoke_runtime(runtime));
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ASSERT_EQ(subgraph_output, operator_output);
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}
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TEST_F(StaticResizeBilinear2DTestQU8, matches_operator_api)
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{
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ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
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std::generate(input.begin(), input.end(), [&]() { return i8dist(rng); });
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std::fill(operator_output.begin(), operator_output.end(), UINT8_C(0xA5));
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std::fill(subgraph_output.begin(), subgraph_output.end(), UINT8_C(0xA5));
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const uint8_t input_zero_point = u8dist(rng);
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const float input_scale = scale_dist(rng);
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const uint8_t output_zero_point = input_zero_point;
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const float output_scale = input_scale;
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// Call operator API.
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xnn_operator_t op = nullptr;
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const xnn_status status = xnn_create_resize_bilinear2d_nhwc_u8(channels, channels, channels, /*flags=*/0, &op);
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std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_op(op, xnn_delete_operator);
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if (status == xnn_status_unsupported_hardware) {
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GTEST_SKIP();
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}
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ASSERT_EQ(xnn_status_success, status);
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ASSERT_NE(nullptr, op);
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ASSERT_EQ(
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xnn_status_success,
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xnn_setup_resize_bilinear2d_nhwc_u8(
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op, batch_size, input_height, input_width, output_height, output_width, input.data(), operator_output.data(),
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/*threadpool=*/nullptr));
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ASSERT_EQ(xnn_status_success, xnn_run_operator(op, /*threadpool=*/nullptr));
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// Call subgraph API.
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xnn_subgraph_t subgraph = nullptr;
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ASSERT_EQ(xnn_status_success, xnn_create_subgraph(2, /*flags=*/0, &subgraph));
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std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph);
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uint32_t input_id = XNN_INVALID_NODE_ID;
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ASSERT_EQ(
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xnn_status_success, xnn_define_quantized_tensor_value(
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subgraph, xnn_datatype_quint8, input_zero_point, input_scale, input_dims.size(),
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input_dims.data(), nullptr, /*external_id=*/0, XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id));
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ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
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uint32_t output_id = XNN_INVALID_NODE_ID;
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ASSERT_EQ(
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xnn_status_success, xnn_define_quantized_tensor_value(
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subgraph, xnn_datatype_quint8, output_zero_point, output_scale, output_dims.size(),
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output_dims.data(), nullptr, /*external_id=*/1, XNN_VALUE_FLAG_EXTERNAL_OUTPUT, &output_id));
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ASSERT_NE(output_id, XNN_INVALID_NODE_ID);
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ASSERT_EQ(
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xnn_status_success,
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xnn_define_static_resize_bilinear_2d(subgraph, output_height, output_width, input_id, output_id, /*flags=*/0));
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xnn_runtime_t runtime = nullptr;
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ASSERT_EQ(xnn_status_success, xnn_create_runtime_v3(subgraph, nullptr, nullptr, /*flags=*/0, &runtime));
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ASSERT_NE(nullptr, runtime);
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std::unique_ptr<xnn_runtime, decltype(&xnn_delete_runtime)> auto_runtime(runtime, xnn_delete_runtime);
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std::array<xnn_external_value, 2> external = {
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xnn_external_value{input_id, input.data()}, xnn_external_value{output_id, subgraph_output.data()}};
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ASSERT_EQ(xnn_status_success, xnn_setup_runtime(runtime, external.size(), external.data()));
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ASSERT_EQ(xnn_status_success, xnn_invoke_runtime(runtime));
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ASSERT_EQ(subgraph_output, operator_output);
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}
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TEST_F(StaticResizeBilinear2DTestF32, matches_operator_api)
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{
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ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
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std::generate(input.begin(), input.end(), [&]() { return f32dist(rng); });
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std::fill(operator_output.begin(), operator_output.end(), std::nanf(""));
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std::fill(subgraph_output.begin(), subgraph_output.end(), std::nanf(""));
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// Call operator API.
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xnn_operator_t op = nullptr;
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const xnn_status status = xnn_create_resize_bilinear2d_nhwc_f32(channels, channels, channels, /*flags=*/0, &op);
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std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_op(op, xnn_delete_operator);
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if (status == xnn_status_unsupported_hardware) {
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GTEST_SKIP();
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}
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ASSERT_EQ(xnn_status_success, status);
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ASSERT_NE(nullptr, op);
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ASSERT_EQ(
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xnn_status_success,
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xnn_setup_resize_bilinear2d_nhwc_f32(
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op, batch_size, input_height, input_width, output_height, output_width, input.data(), operator_output.data(),
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/*threadpool=*/nullptr));
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ASSERT_EQ(xnn_status_success, xnn_run_operator(op, /*threadpool=*/nullptr));
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// Call subgraph API.
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xnn_subgraph_t subgraph = nullptr;
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ASSERT_EQ(xnn_status_success, xnn_create_subgraph(2, /*flags=*/0, &subgraph));
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std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph);
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uint32_t input_id = XNN_INVALID_NODE_ID;
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ASSERT_EQ(
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xnn_status_success, xnn_define_tensor_value(
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subgraph, xnn_datatype_fp32, input_dims.size(), input_dims.data(), nullptr, /*external_id=*/0,
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XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id));
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ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
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uint32_t output_id = XNN_INVALID_NODE_ID;
|
|
ASSERT_EQ(
|
|
xnn_status_success, xnn_define_tensor_value(
|
|
subgraph, xnn_datatype_fp32, output_dims.size(), output_dims.data(), nullptr,
|
|
/*external_id=*/1, XNN_VALUE_FLAG_EXTERNAL_OUTPUT, &output_id));
|
|
ASSERT_NE(output_id, XNN_INVALID_NODE_ID);
|
|
ASSERT_EQ(
|
|
xnn_status_success,
|
|
xnn_define_static_resize_bilinear_2d(subgraph, output_height, output_width, input_id, output_id, /*flags=*/0));
|
|
|
|
xnn_runtime_t runtime = nullptr;
|
|
ASSERT_EQ(xnn_status_success, xnn_create_runtime_v3(subgraph, nullptr, nullptr, /*flags=*/0, &runtime));
|
|
ASSERT_NE(nullptr, runtime);
|
|
std::unique_ptr<xnn_runtime, decltype(&xnn_delete_runtime)> auto_runtime(runtime, xnn_delete_runtime);
|
|
std::array<xnn_external_value, 2> external = {
|
|
xnn_external_value{input_id, input.data()}, xnn_external_value{output_id, subgraph_output.data()}};
|
|
ASSERT_EQ(xnn_status_success, xnn_setup_runtime(runtime, external.size(), external.data()));
|
|
ASSERT_EQ(xnn_status_success, xnn_invoke_runtime(runtime));
|
|
|
|
ASSERT_EQ(subgraph_output, operator_output);
|
|
}
|