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sglang_v0.5.2/pytorch_2.8.0/third_party/XNNPACK/test/space-to-depth-2d.cc

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// 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 <cmath>
#include <cstddef>
#include <cstdint>
#include <memory>
#include <random>
#include <vector>
#include <gtest/gtest.h>
#include "xnnpack.h"
#include "xnnpack/math.h"
#include "xnnpack/node-type.h"
#include "xnnpack/operator.h"
#include "xnnpack/subgraph.h"
#include "subgraph-unary-tester.h"
using SpaceToDepth2DTestQS8 = UnaryTest<int8_t, int8_t, /*min_dim=*/4, /*max_dim=*/4>;
using SpaceToDepth2DTestQU8 = UnaryTest<uint8_t, uint8_t, /*min_dim=*/4, /*max_dim=*/4>;
using SpaceToDepth2DTestF16 = UnaryTest<xnn_float16, xnn_float16, /*min_dim=*/4, /*max_dim=*/4>;
using SpaceToDepth2DTestF32 = UnaryTest<float, float, /*min_dim=*/4, /*max_dim=*/4>;
TEST_F(SpaceToDepth2DTestQS8, define)
{
const size_t block_size = 2 + (u8dist(rng) % 11);
std::vector<size_t> output_dims = dims;
output_dims[3] *= block_size * block_size;
dims[1] *= block_size;
dims[2] *= block_size;
const int32_t input_zero_point = i8dist(rng);
const float input_scale = scale_dist(rng);
const int32_t output_zero_point = input_zero_point;
const float output_scale = input_scale;
ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
xnn_subgraph_t subgraph = nullptr;
ASSERT_EQ(xnn_status_success, xnn_create_subgraph(/*external_value_ids=*/2, /*flags=*/0, &subgraph));
std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph);
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, dims.size(), dims.data(),
nullptr, 0, /*flags=*/XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id));
ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
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, 1, /*flags=*/XNN_VALUE_FLAG_EXTERNAL_OUTPUT, &output_id));
ASSERT_NE(output_id, XNN_INVALID_NODE_ID);
ASSERT_EQ(
xnn_status_success,
xnn_define_space_to_depth_2d(subgraph, block_size, 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_space_to_depth_2d);
ASSERT_EQ(node->params.space_to_depth_2d.block_size, block_size);
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(SpaceToDepth2DTestQU8, define)
{
const size_t block_size = 2 + (u8dist(rng) % 7);
std::vector<size_t> output_dims = dims;
output_dims[3] *= block_size * block_size;
dims[1] *= block_size;
dims[2] *= block_size;
const int32_t input_zero_point = u8dist(rng);
const float input_scale = scale_dist(rng);
const int32_t output_zero_point = input_zero_point;
const float output_scale = input_scale;
ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
xnn_subgraph_t subgraph = nullptr;
ASSERT_EQ(xnn_status_success, xnn_create_subgraph(/*external_value_ids=*/2, /*flags=*/0, &subgraph));
std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph);
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, dims.size(), dims.data(),
nullptr, 0, /*flags=*/XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id));
ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
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, 1, /*flags=*/XNN_VALUE_FLAG_EXTERNAL_OUTPUT, &output_id));
ASSERT_NE(output_id, XNN_INVALID_NODE_ID);
ASSERT_EQ(
xnn_status_success,
xnn_define_space_to_depth_2d(subgraph, block_size, 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_space_to_depth_2d);
ASSERT_EQ(node->params.space_to_depth_2d.block_size, block_size);
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(SpaceToDepth2DTestF16, define)
{
const size_t block_size = 2 + (u8dist(rng) % 13);
std::vector<size_t> output_dims = dims;
output_dims[3] *= block_size * block_size;
dims[1] *= block_size;
dims[2] *= block_size;
ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
xnn_subgraph_t subgraph = nullptr;
ASSERT_EQ(xnn_status_success, xnn_create_subgraph(/*external_value_ids=*/2, /*flags=*/0, &subgraph));
std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph);
input_id = XNN_INVALID_NODE_ID;
ASSERT_EQ(
xnn_status_success, xnn_define_tensor_value(
subgraph, xnn_datatype_fp16, dims.size(), dims.data(), nullptr, 0,
/*flags=*/XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id));
ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
output_id = XNN_INVALID_NODE_ID;
ASSERT_EQ(
xnn_status_success, xnn_define_tensor_value(
subgraph, xnn_datatype_fp16, output_dims.size(), output_dims.data(), nullptr, 1,
/*flags=*/XNN_VALUE_FLAG_EXTERNAL_OUTPUT, &output_id));
ASSERT_NE(output_id, XNN_INVALID_NODE_ID);
ASSERT_EQ(
xnn_status_success,
xnn_define_space_to_depth_2d(subgraph, block_size, 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_space_to_depth_2d);
ASSERT_EQ(node->params.space_to_depth_2d.block_size, block_size);
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(SpaceToDepth2DTestF32, define)
{
const size_t block_size = 2 + (u8dist(rng) % 13);
std::vector<size_t> output_dims = dims;
output_dims[3] *= block_size * block_size;
dims[1] *= block_size;
dims[2] *= block_size;
ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
xnn_subgraph_t subgraph = nullptr;
ASSERT_EQ(xnn_status_success, xnn_create_subgraph(/*external_value_ids=*/2, /*flags=*/0, &subgraph));
std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph);
input_id = XNN_INVALID_NODE_ID;
ASSERT_EQ(
xnn_status_success, xnn_define_tensor_value(
subgraph, xnn_datatype_fp32, dims.size(), dims.data(), nullptr, 0,
/*flags=*/XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id));
ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
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, 1,
/*flags=*/XNN_VALUE_FLAG_EXTERNAL_OUTPUT, &output_id));
ASSERT_NE(output_id, XNN_INVALID_NODE_ID);
ASSERT_EQ(
xnn_status_success,
xnn_define_space_to_depth_2d(subgraph, block_size, 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_space_to_depth_2d);
ASSERT_EQ(node->params.space_to_depth_2d.block_size, block_size);
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(SpaceToDepth2DTestQS8, matches_operator_api)
{
std::vector<size_t> output_dims = dims;
const size_t block_size = 2 + (u8dist(rng) % 11);
output_dims[3] *= block_size * block_size;
dims[1] *= block_size;
dims[2] *= block_size;
AllocateInputsAndOutputs();
const int32_t input_zero_point = u8dist(rng);
const float input_scale = scale_dist(rng);
const int32_t output_zero_point = input_zero_point;
const float output_scale = input_scale;
size_t input_channels = dims[3];
size_t input_height = dims[1];
size_t input_width = dims[2];
size_t batch_size = dims[0];
std::generate(input.begin(), input.end(), [&]() { return u8dist(rng); });
// Call operator API.
ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
xnn_operator_t op = nullptr;
const xnn_status status = xnn_create_space_to_depth_nhwc_x8(block_size, /*flags=*/0, &op);
if (status == xnn_status_unsupported_hardware) {
GTEST_SKIP();
}
ASSERT_EQ(xnn_status_success, status);
ASSERT_NE(nullptr, op);
std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_op(op, xnn_delete_operator);
ASSERT_EQ(
xnn_status_success, xnn_reshape_space_to_depth_nhwc_x8(
op, batch_size, input_height, input_width, input_channels,
/*output_height_out=*/nullptr, /*output_width_out=*/nullptr, /*output_channels_out=*/nullptr,
/*threadpool=*/nullptr));
ASSERT_EQ(xnn_status_success, xnn_setup_space_to_depth_nhwc_x8(op, input.data(), operator_output.data()));
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(/*external_value_ids=*/2, /*flags=*/0, &subgraph));
std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph);
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, dims.size(), dims.data(),
nullptr, /*external_id=*/0, /*flags=*/XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id));
ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
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, dims.size(),
output_dims.data(), nullptr, /*external_id=*/1, /*flags=*/XNN_VALUE_FLAG_EXTERNAL_OUTPUT,
&output_id));
ASSERT_NE(output_id, XNN_INVALID_NODE_ID);
ASSERT_EQ(
xnn_status_success,
xnn_define_space_to_depth_2d(subgraph, block_size, 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));
EXPECT_EQ(subgraph_output, operator_output);
}
TEST_F(SpaceToDepth2DTestQU8, matches_operator_api)
{
std::vector<size_t> output_dims = dims;
const size_t block_size = 2 + (u8dist(rng) % 11);
output_dims[3] *= block_size * block_size;
dims[1] *= block_size;
dims[2] *= block_size;
AllocateInputsAndOutputs();
const int32_t input_zero_point = u8dist(rng);
const float input_scale = scale_dist(rng);
const int32_t output_zero_point = input_zero_point;
const float output_scale = input_scale;
size_t input_channels = dims[3];
size_t input_height = dims[1];
size_t input_width = dims[2];
size_t batch_size = dims[0];
std::generate(input.begin(), input.end(), [&]() { return u8dist(rng); });
// Call operator API.
ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
xnn_operator_t op = nullptr;
const xnn_status status = xnn_create_space_to_depth_nhwc_x8(block_size, /*flags=*/0, &op);
if (status == xnn_status_unsupported_hardware) {
GTEST_SKIP();
}
ASSERT_EQ(xnn_status_success, status);
ASSERT_NE(nullptr, op);
std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_op(op, xnn_delete_operator);
ASSERT_EQ(
xnn_status_success, xnn_reshape_space_to_depth_nhwc_x8(
op, batch_size, input_height, input_width, input_channels,
/*output_height_out=*/nullptr, /*output_width_out=*/nullptr, /*output_channels_out=*/nullptr,
/*threadpool=*/nullptr));
ASSERT_EQ(xnn_status_success, xnn_setup_space_to_depth_nhwc_x8(op, input.data(), operator_output.data()));
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(/*external_value_ids=*/2, /*flags=*/0, &subgraph));
std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph);
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, dims.size(), dims.data(),
nullptr, /*external_id=*/0, /*flags=*/XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id));
ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
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, dims.size(),
output_dims.data(), nullptr, /*external_id=*/1, /*flags=*/XNN_VALUE_FLAG_EXTERNAL_OUTPUT,
&output_id));
ASSERT_NE(output_id, XNN_INVALID_NODE_ID);
ASSERT_EQ(
xnn_status_success,
xnn_define_space_to_depth_2d(subgraph, block_size, 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));
EXPECT_EQ(subgraph_output, operator_output);
}
TEST_F(SpaceToDepth2DTestF16, matches_operator_api)
{
std::vector<size_t> output_dims = dims;
const size_t block_size = 2 + (u8dist(rng) % 11);
output_dims[3] *= block_size * block_size;
dims[1] *= block_size;
dims[2] *= block_size;
AllocateInputsAndOutputs();
size_t input_channels = dims[3];
size_t input_height = dims[1];
size_t input_width = dims[2];
size_t batch_size = dims[0];
std::generate(input.begin(), input.end(), [&]() { return f32dist(rng); });
// Call operator API.
ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
xnn_operator_t op = nullptr;
const xnn_status status = xnn_create_space_to_depth_nhwc_x16(block_size, /*flags=*/0, &op);
if (status == xnn_status_unsupported_hardware) {
GTEST_SKIP();
}
ASSERT_EQ(xnn_status_success, status);
ASSERT_NE(nullptr, op);
std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_op(op, xnn_delete_operator);
ASSERT_EQ(
xnn_status_success, xnn_reshape_space_to_depth_nhwc_x16(
op, batch_size, input_height, input_width, input_channels,
/*output_height_out=*/nullptr, /*output_width_out=*/nullptr, /*output_channels_out=*/nullptr,
/*threadpool=*/nullptr));
ASSERT_EQ(xnn_status_success, xnn_setup_space_to_depth_nhwc_x16(op, input.data(), operator_output.data()));
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(/*external_value_ids=*/2, /*flags=*/0, &subgraph));
std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph);
input_id = XNN_INVALID_NODE_ID;
ASSERT_EQ(
xnn_status_success, xnn_define_tensor_value(
subgraph, xnn_datatype_fp16, dims.size(), dims.data(),
nullptr, /*external_id=*/0, /*flags=*/XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id));
ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
output_id = XNN_INVALID_NODE_ID;
ASSERT_EQ(
xnn_status_success, xnn_define_tensor_value(
subgraph, xnn_datatype_fp16, dims.size(), output_dims.data(),
nullptr, /*external_id=*/1, /*flags=*/XNN_VALUE_FLAG_EXTERNAL_OUTPUT, &output_id));
ASSERT_NE(output_id, XNN_INVALID_NODE_ID);
ASSERT_EQ(
xnn_status_success,
xnn_define_space_to_depth_2d(subgraph, block_size, 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));
EXPECT_EQ(subgraph_output, operator_output);
}
TEST_F(SpaceToDepth2DTestF32, matches_operator_api)
{
std::vector<size_t> output_dims = dims;
const size_t block_size = 2 + (u8dist(rng) % 11);
output_dims[3] *= block_size * block_size;
dims[1] *= block_size;
dims[2] *= block_size;
AllocateInputsAndOutputs();
size_t input_channels = dims[3];
size_t input_height = dims[1];
size_t input_width = dims[2];
size_t batch_size = dims[0];
std::generate(input.begin(), input.end(), [&]() { return f32dist(rng); });
// Call operator API.
ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
xnn_operator_t op = nullptr;
const xnn_status status = xnn_create_space_to_depth_nhwc_x32(block_size, /*flags=*/0, &op);
if (status == xnn_status_unsupported_hardware) {
GTEST_SKIP();
}
ASSERT_EQ(xnn_status_success, status);
ASSERT_NE(nullptr, op);
std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_op(op, xnn_delete_operator);
ASSERT_EQ(
xnn_status_success, xnn_reshape_space_to_depth_nhwc_x32(
op, batch_size, input_height, input_width, input_channels,
/*output_height_out=*/nullptr, /*output_width_out=*/nullptr, /*output_channels_out=*/nullptr,
/*threadpool=*/nullptr));
ASSERT_EQ(xnn_status_success, xnn_setup_space_to_depth_nhwc_x32(op, input.data(), operator_output.data()));
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(/*external_value_ids=*/2, /*flags=*/0, &subgraph));
std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph);
input_id = XNN_INVALID_NODE_ID;
ASSERT_EQ(
xnn_status_success, xnn_define_tensor_value(
subgraph, xnn_datatype_fp32, dims.size(), dims.data(),
nullptr, /*external_id=*/0, /*flags=*/XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id));
ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
output_id = XNN_INVALID_NODE_ID;
ASSERT_EQ(
xnn_status_success, xnn_define_tensor_value(
subgraph, xnn_datatype_fp32, dims.size(), output_dims.data(),
nullptr, /*external_id=*/1, /*flags=*/XNN_VALUE_FLAG_EXTERNAL_OUTPUT, &output_id));
ASSERT_NE(output_id, XNN_INVALID_NODE_ID);
ASSERT_EQ(
xnn_status_success,
xnn_define_space_to_depth_2d(subgraph, block_size, 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));
EXPECT_EQ(subgraph_output, operator_output);
}
TEST_F(SpaceToDepth2DTestF32, reshape_output)
{
std::vector<size_t> output_dims = dims;
const size_t block_size = 2 + (u8dist(rng) % 11);
output_dims[3] *= block_size * block_size;
dims[1] *= block_size;
dims[2] *= block_size;
AllocateInputsAndOutputs();
// Call subgraph API.
xnn_subgraph_t subgraph = nullptr;
ASSERT_EQ(xnn_status_success, xnn_create_subgraph(/*external_value_ids=*/2, /*flags=*/0, &subgraph));
std::unique_ptr<xnn_subgraph, decltype(&xnn_delete_subgraph)> auto_subgraph(subgraph, xnn_delete_subgraph);
input_id = XNN_INVALID_NODE_ID;
ASSERT_EQ(
xnn_status_success, xnn_define_tensor_value(
subgraph, xnn_datatype_fp32, dims.size(), dims.data(),
nullptr, /*external_id=*/0, /*flags=*/XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id));
ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
output_id = XNN_INVALID_NODE_ID;
ASSERT_EQ(
xnn_status_success, xnn_define_tensor_value(
subgraph, xnn_datatype_fp32, dims.size(), output_dims.data(),
nullptr, /*external_id=*/1, /*flags=*/XNN_VALUE_FLAG_EXTERNAL_OUTPUT, &output_id));
ASSERT_NE(output_id, XNN_INVALID_NODE_ID);
ASSERT_EQ(
xnn_status_success,
xnn_define_space_to_depth_2d(subgraph, block_size, 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));
dims[0] += 2;
dims[1] += block_size;
dims[2] += block_size;
ASSERT_EQ(xnn_status_success, xnn_reshape_external_value(runtime, input_id, dims.size(), dims.data()));
const struct xnn_node* node = &subgraph->nodes[0];
ASSERT_EQ(node->reshape(&runtime->opdata[0], runtime->values, runtime->num_values, /*threadpool=*/nullptr), xnn_status_reallocation_required);
const xnn_shape* output_shape = &runtime->values[node->outputs[0]].shape;
ASSERT_EQ(output_shape->dim[0], dims[0]);
ASSERT_EQ(output_shape->dim[1], dims[1] / block_size);
ASSERT_EQ(output_shape->dim[2], dims[2] / block_size);
ASSERT_EQ(output_shape->dim[3], dims[3] * block_size * block_size);
dims[0] -= 1;
ASSERT_EQ(xnn_status_success, xnn_reshape_external_value(runtime, input_id, dims.size(), dims.data()));
ASSERT_EQ(node->reshape(&runtime->opdata[0], runtime->values, runtime->num_values, /*threadpool=*/nullptr), xnn_status_success);
ASSERT_EQ(output_shape->dim[0], dims[0]);
ASSERT_EQ(output_shape->dim[1], dims[1] / block_size);
ASSERT_EQ(output_shape->dim[2], dims[2] / block_size);
ASSERT_EQ(output_shape->dim[3], dims[3] * block_size * block_size);
}
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