test/global-average-pooling-2d.cc - platform/external/XNNPACK - Git at Google

 // 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);
 }
	// 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);
	}