400 lines
17 KiB
C++
400 lines
17 KiB
C++
|
// Copyright 2022 Google LLC
|
||
|
|
//
|
||
|
|
// This source code is licensed under the BSD-style license found in the
|
||
|
|
// LICENSE file in the root directory of this source tree.
|
||
|
|
|
||
|
|
#include <algorithm>
|
||
|
|
#include <array>
|
||
|
|
#include <functional>
|
||
|
|
#include <limits>
|
||
|
|
#include <memory>
|
||
|
|
#include <numeric>
|
||
|
|
#include <random>
|
||
|
|
#include <vector>
|
||
|
|
|
||
|
|
#include <xnnpack.h>
|
||
|
|
#include <xnnpack/node-type.h>
|
||
|
|
#include <xnnpack/operator.h>
|
||
|
|
#include <xnnpack/requantization.h>
|
||
|
|
#include <xnnpack/subgraph.h>
|
||
|
|
|
||
|
|
#include <gtest/gtest.h>
|
||
|
|
|
||
|
|
template <typename T> class GlobalAveragePooling2DTest : public ::testing::Test {
|
||
|
|
protected:
|
||
|
|
GlobalAveragePooling2DTest()
|
||
|
|
{
|
||
|
|
random_device = std::unique_ptr<std::random_device>(new std::random_device());
|
||
|
|
rng = std::mt19937((*random_device)());
|
||
|
|
shape_dist = std::uniform_int_distribution<size_t>(1, XNN_MAX_TENSOR_DIMS);
|
||
|
|
dim_dist = std::uniform_int_distribution<size_t>(1, 9);
|
||
|
|
f32dist = std::uniform_real_distribution<float>();
|
||
|
|
i8dist =
|
||
|
|
std::uniform_int_distribution<int32_t>(std::numeric_limits<int8_t>::min(), std::numeric_limits<int8_t>::max());
|
||
|
|
u8dist =
|
||
|
|
std::uniform_int_distribution<int32_t>(std::numeric_limits<uint8_t>::min(), std::numeric_limits<uint8_t>::max());
|
||
|
|
scale_dist = std::uniform_real_distribution<float>(0.1f, 5.0f);
|
||
|
|
|
||
|
|
input_dims = RandomShape(4);
|
||
|
|
output_dims = {input_dims[0], 1, 1, input_dims[3]};
|
||
|
|
input = std::vector<T>(XNN_EXTRA_BYTES / sizeof(T) + NumElements(input_dims));
|
||
|
|
operator_output = std::vector<T>(NumElements(output_dims));
|
||
|
|
subgraph_output = std::vector<T>(operator_output.size());
|
||
|
|
batch_size = input_dims[0];
|
||
|
|
input_width = input_dims[1] * input_dims[2];
|
||
|
|
channels = input_dims[3];
|
||
|
|
}
|
||
|
|
|
||
|
|
std::vector<size_t> RandomShape(size_t num_dims)
|
||
|
|
{
|
||
|
|
std::vector<size_t> dims(num_dims);
|
||
|
|
std::generate(dims.begin(), dims.end(), [&] { return dim_dist(rng); });
|
||
|
|
return dims;
|
||
|
|
}
|
||
|
|
|
||
|
|
size_t NumElements(std::vector<size_t>& dims)
|
||
|
|
{
|
||
|
|
return std::accumulate(dims.begin(), dims.end(), size_t(1), std::multiplies<size_t>());
|
||
|
|
}
|
||
|
|
|
||
|
|
std::unique_ptr<std::random_device> random_device;
|
||
|
|
std::mt19937 rng;
|
||
|
|
std::uniform_int_distribution<size_t> shape_dist;
|
||
|
|
std::uniform_int_distribution<size_t> dim_dist;
|
||
|
|
std::uniform_real_distribution<float> f32dist;
|
||
|
|
std::uniform_real_distribution<float> scale_dist;
|
||
|
|
std::uniform_int_distribution<int32_t> i8dist;
|
||
|
|
std::uniform_int_distribution<int32_t> u8dist;
|
||
|
|
|
||
|
|
float output_min = -std::numeric_limits<float>::infinity();
|
||
|
|
float output_max = std::numeric_limits<float>::infinity();
|
||
|
|
size_t batch_size;
|
||
|
|
size_t input_width;
|
||
|
|
size_t channels;
|
||
|
|
|
||
|
|
std::vector<size_t> input_dims;
|
||
|
|
std::vector<size_t> output_dims;
|
||
|
|
|
||
|
|
std::vector<T> input;
|
||
|
|
std::vector<T> operator_output;
|
||
|
|
std::vector<T> subgraph_output;
|
||
|
|
};
|
||
|
|
|
||
|
|
using GlobalAveragePooling2DTestQS8 = GlobalAveragePooling2DTest<int8_t>;
|
||
|
|
using GlobalAveragePooling2DTestQU8 = GlobalAveragePooling2DTest<uint8_t>;
|
||
|
|
using GlobalAveragePooling2DTestF32 = GlobalAveragePooling2DTest<float>;
|
||
|
|
|
||
|
|
TEST_F(GlobalAveragePooling2DTestQS8, define)
|
||
|
|
{
|
||
|
|
ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
|
||
|
|
|
||
|
|
xnn_subgraph_t subgraph = nullptr;
|
||
|
|
ASSERT_EQ(xnn_status_success, xnn_create_subgraph(2, /*flags=*/0, &subgraph));
|
||
|
|
std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph);
|
||
|
|
|
||
|
|
uint32_t input_id = XNN_INVALID_NODE_ID;
|
||
|
|
ASSERT_EQ(
|
||
|
|
xnn_status_success, xnn_define_quantized_tensor_value(
|
||
|
|
subgraph, xnn_datatype_qint8, 0, 1.0f, input_dims.size(), input_dims.data(), nullptr,
|
||
|
|
/*external_id=*/0, /*flags=*/0, &input_id));
|
||
|
|
ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
|
||
|
|
|
||
|
|
uint32_t output_id = XNN_INVALID_NODE_ID;
|
||
|
|
ASSERT_EQ(
|
||
|
|
xnn_status_success, xnn_define_quantized_tensor_value(
|
||
|
|
subgraph, xnn_datatype_qint8, 0, 1.0f, output_dims.size(), output_dims.data(), nullptr,
|
||
|
|
/*external_id=*/1, /*flags=*/0, &output_id));
|
||
|
|
ASSERT_NE(output_id, XNN_INVALID_NODE_ID);
|
||
|
|
|
||
|
|
ASSERT_EQ(
|
||
|
|
xnn_status_success,
|
||
|
|
xnn_define_global_average_pooling_2d(subgraph, output_min, output_max, input_id, output_id, /*flags=*/0));
|
||
|
|
|
||
|
|
ASSERT_EQ(subgraph->num_nodes, 1);
|
||
|
|
const struct xnn_node* node = &subgraph->nodes[0];
|
||
|
|
ASSERT_EQ(node->type, xnn_node_type_global_average_pooling_2d);
|
||
|
|
ASSERT_EQ(node->compute_type, xnn_compute_type_qs8);
|
||
|
|
ASSERT_EQ(node->activation.output_min, output_min);
|
||
|
|
ASSERT_EQ(node->activation.output_max, output_max);
|
||
|
|
ASSERT_EQ(node->num_inputs, 1);
|
||
|
|
ASSERT_EQ(node->inputs[0], input_id);
|
||
|
|
ASSERT_EQ(node->num_outputs, 1);
|
||
|
|
ASSERT_EQ(node->outputs[0], output_id);
|
||
|
|
ASSERT_EQ(node->flags, 0);
|
||
|
|
}
|
||
|
|
|
||
|
|
TEST_F(GlobalAveragePooling2DTestQU8, define)
|
||
|
|
{
|
||
|
|
ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
|
||
|
|
|
||
|
|
xnn_subgraph_t subgraph = nullptr;
|
||
|
|
ASSERT_EQ(xnn_status_success, xnn_create_subgraph(2, /*flags=*/0, &subgraph));
|
||
|
|
std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph);
|
||
|
|
|
||
|
|
uint32_t input_id = XNN_INVALID_NODE_ID;
|
||
|
|
ASSERT_EQ(
|
||
|
|
xnn_status_success, xnn_define_quantized_tensor_value(
|
||
|
|
subgraph, xnn_datatype_quint8, 0, 1.0f, input_dims.size(), input_dims.data(), nullptr,
|
||
|
|
/*external_id=*/0, /*flags=*/0, &input_id));
|
||
|
|
ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
|
||
|
|
|
||
|
|
uint32_t output_id = XNN_INVALID_NODE_ID;
|
||
|
|
ASSERT_EQ(
|
||
|
|
xnn_status_success, xnn_define_quantized_tensor_value(
|
||
|
|
subgraph, xnn_datatype_quint8, 0, 1.0f, output_dims.size(), output_dims.data(), nullptr,
|
||
|
|
/*external_id=*/1, /*flags=*/0, &output_id));
|
||
|
|
ASSERT_NE(output_id, XNN_INVALID_NODE_ID);
|
||
|
|
|
||
|
|
ASSERT_EQ(
|
||
|
|
xnn_status_success,
|
||
|
|
xnn_define_global_average_pooling_2d(subgraph, output_min, output_max, input_id, output_id, /*flags=*/0));
|
||
|
|
|
||
|
|
ASSERT_EQ(subgraph->num_nodes, 1);
|
||
|
|
const struct xnn_node* node = &subgraph->nodes[0];
|
||
|
|
ASSERT_EQ(node->type, xnn_node_type_global_average_pooling_2d);
|
||
|
|
ASSERT_EQ(node->compute_type, xnn_compute_type_qu8);
|
||
|
|
ASSERT_EQ(node->activation.output_min, output_min);
|
||
|
|
ASSERT_EQ(node->activation.output_max, output_max);
|
||
|
|
ASSERT_EQ(node->num_inputs, 1);
|
||
|
|
ASSERT_EQ(node->inputs[0], input_id);
|
||
|
|
ASSERT_EQ(node->num_outputs, 1);
|
||
|
|
ASSERT_EQ(node->outputs[0], output_id);
|
||
|
|
ASSERT_EQ(node->flags, 0);
|
||
|
|
}
|
||
|
|
|
||
|
|
TEST_F(GlobalAveragePooling2DTestF32, define)
|
||
|
|
{
|
||
|
|
ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
|
||
|
|
|
||
|
|
xnn_subgraph_t subgraph = nullptr;
|
||
|
|
ASSERT_EQ(xnn_status_success, xnn_create_subgraph(2, /*flags=*/0, &subgraph));
|
||
|
|
std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph);
|
||
|
|
|
||
|
|
uint32_t input_id = XNN_INVALID_NODE_ID;
|
||
|
|
ASSERT_EQ(
|
||
|
|
xnn_status_success, xnn_define_tensor_value(
|
||
|
|
subgraph, xnn_datatype_fp32, input_dims.size(), input_dims.data(), nullptr,
|
||
|
|
/*external_id=*/0, /*flags=*/0, &input_id));
|
||
|
|
ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
|
||
|
|
|
||
|
|
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, /*flags=*/0, &output_id));
|
||
|
|
ASSERT_NE(output_id, XNN_INVALID_NODE_ID);
|
||
|
|
|
||
|
|
ASSERT_EQ(
|
||
|
|
xnn_status_success,
|
||
|
|
xnn_define_global_average_pooling_2d(subgraph, output_min, output_max, input_id, output_id, /*flags=*/0));
|
||
|
|
|
||
|
|
ASSERT_EQ(subgraph->num_nodes, 1);
|
||
|
|
const struct xnn_node* node = &subgraph->nodes[0];
|
||
|
|
ASSERT_EQ(node->type, xnn_node_type_global_average_pooling_2d);
|
||
|
|
ASSERT_EQ(node->compute_type, xnn_compute_type_fp32);
|
||
|
|
ASSERT_EQ(node->activation.output_min, output_min);
|
||
|
|
ASSERT_EQ(node->activation.output_max, output_max);
|
||
|
|
ASSERT_EQ(node->num_inputs, 1);
|
||
|
|
ASSERT_EQ(node->inputs[0], input_id);
|
||
|
|
ASSERT_EQ(node->num_outputs, 1);
|
||
|
|
ASSERT_EQ(node->outputs[0], output_id);
|
||
|
|
ASSERT_EQ(node->flags, 0);
|
||
|
|
}
|
||
|
|
|
||
|
|
TEST_F(GlobalAveragePooling2DTestQS8, matches_operator_api)
|
||
|
|
{
|
||
|
|
const int32_t input_zero_point = i8dist(rng);
|
||
|
|
const int32_t output_zero_point = i8dist(rng);
|
||
|
|
const float input_scale = scale_dist(rng);
|
||
|
|
const float output_scale = scale_dist(rng);
|
||
|
|
const int8_t quantized_output_min = xnn_qs8_quantize(output_min, output_scale, output_zero_point);
|
||
|
|
const int8_t quantized_output_max = xnn_qs8_quantize(output_max, output_scale, output_zero_point);
|
||
|
|
|
||
|
|
ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
|
||
|
|
|
||
|
|
xnn_operator_t op = nullptr;
|
||
|
|
const xnn_status status = xnn_create_global_average_pooling_nwc_qs8(
|
||
|
|
channels, channels, channels, input_zero_point, input_scale, output_zero_point, output_scale, quantized_output_min,
|
||
|
|
quantized_output_max,
|
||
|
|
/*flags=*/0, &op);
|
||
|
|
std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_op(op, xnn_delete_operator);
|
||
|
|
|
||
|
|
if (status == xnn_status_unsupported_hardware) {
|
||
|
|
GTEST_SKIP();
|
||
|
|
}
|
||
|
|
|
||
|
|
ASSERT_EQ(xnn_status_success, status);
|
||
|
|
ASSERT_NE(nullptr, op);
|
||
|
|
ASSERT_EQ(
|
||
|
|
xnn_status_success, xnn_setup_global_average_pooling_nwc_qs8(
|
||
|
|
op, batch_size, input_width, input.data(), operator_output.data(),
|
||
|
|
/*threadpool=*/nullptr));
|
||
|
|
|
||
|
|
ASSERT_EQ(xnn_status_success, xnn_run_operator(op, /*threadpool=*/nullptr));
|
||
|
|
|
||
|
|
xnn_subgraph_t subgraph = nullptr;
|
||
|
|
ASSERT_EQ(xnn_status_success, xnn_create_subgraph(2, /*flags=*/0, &subgraph));
|
||
|
|
std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph);
|
||
|
|
|
||
|
|
uint32_t input_id = XNN_INVALID_NODE_ID;
|
||
|
|
ASSERT_EQ(
|
||
|
|
xnn_status_success,
|
||
|
|
xnn_define_quantized_tensor_value(
|
||
|
|
subgraph, xnn_datatype_qint8, input_zero_point, input_scale, input_dims.size(), input_dims.data(), nullptr,
|
||
|
|
/*external_id=*/0, XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id));
|
||
|
|
ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
|
||
|
|
|
||
|
|
uint32_t output_id = XNN_INVALID_NODE_ID;
|
||
|
|
ASSERT_EQ(
|
||
|
|
xnn_status_success,
|
||
|
|
xnn_define_quantized_tensor_value(
|
||
|
|
subgraph, xnn_datatype_qint8, output_zero_point, output_scale, 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_global_average_pooling_2d(subgraph, output_min, output_max, 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);
|
||
|
|
}
|
||
|
|
|
||
|
|
TEST_F(GlobalAveragePooling2DTestQU8, matches_operator_api)
|
||
|
|
{
|
||
|
|
const int32_t input_zero_point = u8dist(rng);
|
||
|
|
const int32_t output_zero_point = u8dist(rng);
|
||
|
|
const float input_scale = scale_dist(rng);
|
||
|
|
const float output_scale = scale_dist(rng);
|
||
|
|
const uint8_t quantized_output_min = xnn_qu8_quantize(output_min, output_scale, output_zero_point);
|
||
|
|
const uint8_t quantized_output_max = xnn_qu8_quantize(output_max, output_scale, output_zero_point);
|
||
|
|
|
||
|
|
ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
|
||
|
|
|
||
|
|
xnn_operator_t op = nullptr;
|
||
|
|
const xnn_status status = xnn_create_global_average_pooling_nwc_qu8(
|
||
|
|
channels, channels, channels, input_zero_point, input_scale, output_zero_point, output_scale, quantized_output_min,
|
||
|
|
quantized_output_max,
|
||
|
|
/*flags=*/0, &op);
|
||
|
|
std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_op(op, xnn_delete_operator);
|
||
|
|
|
||
|
|
if (status == xnn_status_unsupported_hardware) {
|
||
|
|
GTEST_SKIP();
|
||
|
|
}
|
||
|
|
|
||
|
|
ASSERT_EQ(xnn_status_success, status);
|
||
|
|
ASSERT_NE(nullptr, op);
|
||
|
|
ASSERT_EQ(
|
||
|
|
xnn_status_success, xnn_setup_global_average_pooling_nwc_qu8(
|
||
|
|
op, batch_size, input_width, input.data(), operator_output.data(),
|
||
|
|
/*threadpool=*/nullptr));
|
||
|
|
|
||
|
|
ASSERT_EQ(xnn_status_success, xnn_run_operator(op, /*threadpool=*/nullptr));
|
||
|
|
|
||
|
|
xnn_subgraph_t subgraph = nullptr;
|
||
|
|
ASSERT_EQ(xnn_status_success, xnn_create_subgraph(2, /*flags=*/0, &subgraph));
|
||
|
|
std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph);
|
||
|
|
|
||
|
|
uint32_t input_id = XNN_INVALID_NODE_ID;
|
||
|
|
ASSERT_EQ(
|
||
|
|
xnn_status_success,
|
||
|
|
xnn_define_quantized_tensor_value(
|
||
|
|
subgraph, xnn_datatype_quint8, input_zero_point, input_scale, input_dims.size(), input_dims.data(), nullptr,
|
||
|
|
/*external_id=*/0, XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id));
|
||
|
|
ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
|
||
|
|
|
||
|
|
uint32_t output_id = XNN_INVALID_NODE_ID;
|
||
|
|
ASSERT_EQ(
|
||
|
|
xnn_status_success,
|
||
|
|
xnn_define_quantized_tensor_value(
|
||
|
|
subgraph, xnn_datatype_quint8, output_zero_point, output_scale, 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_global_average_pooling_2d(subgraph, output_min, output_max, 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);
|
||
|
|
}
|
||
|
|
|
||
|
|
TEST_F(GlobalAveragePooling2DTestF32, matches_operator_api)
|
||
|
|
{
|
||
|
|
ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
|
||
|
|
|
||
|
|
xnn_operator_t op = nullptr;
|
||
|
|
|
||
|
|
std::generate(input.begin(), input.end(), [&]() { return f32dist(rng); });
|
||
|
|
std::fill(operator_output.begin(), operator_output.end(), nanf(""));
|
||
|
|
std::fill(subgraph_output.begin(), subgraph_output.end(), nanf(""));
|
||
|
|
|
||
|
|
// Call operator API.
|
||
|
|
const xnn_status status = xnn_create_global_average_pooling_nwc_f32(
|
||
|
|
channels, channels, channels, output_min, output_max,
|
||
|
|
/*flags=*/0, &op);
|
||
|
|
std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_op(op, xnn_delete_operator);
|
||
|
|
|
||
|
|
if (status == xnn_status_unsupported_hardware) {
|
||
|
|
GTEST_SKIP();
|
||
|
|
}
|
||
|
|
|
||
|
|
ASSERT_EQ(xnn_status_success, status);
|
||
|
|
ASSERT_NE(nullptr, op);
|
||
|
|
ASSERT_EQ(
|
||
|
|
xnn_status_success, xnn_setup_global_average_pooling_nwc_f32(
|
||
|
|
op, batch_size, input_width, input.data(), operator_output.data(),
|
||
|
|
/*threadpool=*/nullptr));
|
||
|
|
|
||
|
|
ASSERT_EQ(xnn_status_success, xnn_run_operator(op, /*threadpool=*/nullptr));
|
||
|
|
|
||
|
|
// Call subgraph API.
|
||
|
|
xnn_subgraph_t subgraph = nullptr;
|
||
|
|
ASSERT_EQ(xnn_status_success, xnn_create_subgraph(2, /*flags=*/0, &subgraph));
|
||
|
|
std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph);
|
||
|
|
|
||
|
|
uint32_t input_id = XNN_INVALID_NODE_ID;
|
||
|
|
ASSERT_EQ(
|
||
|
|
xnn_status_success, xnn_define_tensor_value(
|
||
|
|
subgraph, xnn_datatype_fp32, input_dims.size(), input_dims.data(), nullptr,
|
||
|
|
/*external_id=*/0, XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id));
|
||
|
|
ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
|
||
|
|
|
||
|
|
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_global_average_pooling_2d(subgraph, output_min, output_max, 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);
|
||
|
|
}
|