598 lines
26 KiB
C++
598 lines
26 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::shuffle.
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#include <array> // For std::array.
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#include <cstddef> // For size_t.
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#include <cstdint>
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#include <memory> // For std::unique_ptr.
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#include <numeric>
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#include <random> // For std::uniform_real_distribution.
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#include <vector> // For std::vector.
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#include <gtest/gtest.h>
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#include "xnnpack.h"
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#include "xnnpack/buffer.h"
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#include "xnnpack/math.h"
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#include "xnnpack/node-type.h"
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#include "xnnpack/operator.h"
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#include "xnnpack/requantization.h"
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#include "xnnpack/subgraph.h"
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#include "subgraph-unary-tester.h"
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using StaticConstantPadTestInt8 = UnaryTest<int8_t>;
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using StaticConstantPadTestUint8 = UnaryTest<uint8_t>;
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using StaticConstantPadTestF16 = UnaryTest<xnn_float16>;
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using StaticConstantPadTestF32 = UnaryTest<float>;
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TEST_F(StaticConstantPadTestInt8, define)
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{
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const int32_t zero_point = i8dist(rng);
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const float scale = scale_dist(rng);
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std::array<size_t, XNN_MAX_TENSOR_DIMS> pre_paddings;
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std::array<size_t, XNN_MAX_TENSOR_DIMS> post_paddings;
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std::fill(pre_paddings.begin(), pre_paddings.begin() + dims.size(), dim_dist(rng));
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std::fill(post_paddings.begin(), post_paddings.begin() + dims.size(), dim_dist(rng));
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float padding_value = f32dist(rng);
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uint32_t quantized_padding_value = xnn_qs8_quantize(padding_value, scale, zero_point);
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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(/*external_value_ids=*/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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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, zero_point, scale, dims.size(), dims.data(), nullptr, 0,
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/*flags=*/XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id));
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ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
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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, zero_point, scale, dims.size(), dims.data(), nullptr, 1,
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/*flags=*/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_constant_pad(
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subgraph, pre_paddings.data(), post_paddings.data(), padding_value, 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_constant_pad);
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for (size_t i = 0; i < dims.size(); i++) {
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ASSERT_EQ(node->params.static_pad.pre_paddings[i], pre_paddings[i]);
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ASSERT_EQ(node->params.static_pad.post_paddings[i], post_paddings[i]);
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}
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ASSERT_EQ(node->params.static_pad.padding_value, quantized_padding_value);
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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(StaticConstantPadTestUint8, define)
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{
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const int32_t zero_point = u8dist(rng);
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const float scale = scale_dist(rng);
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std::array<size_t, XNN_MAX_TENSOR_DIMS> pre_paddings;
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std::array<size_t, XNN_MAX_TENSOR_DIMS> post_paddings;
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std::fill(pre_paddings.begin(), pre_paddings.begin() + dims.size(), dim_dist(rng));
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std::fill(post_paddings.begin(), post_paddings.begin() + dims.size(), dim_dist(rng));
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float padding_value = f32dist(rng);
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uint32_t quantized_padding_value = xnn_qu8_quantize(padding_value, scale, zero_point);
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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(/*external_value_ids=*/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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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, zero_point, scale, dims.size(), dims.data(), nullptr, 0,
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/*flags=*/XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id));
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ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
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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, zero_point, scale, dims.size(), dims.data(), nullptr, 1,
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/*flags=*/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_constant_pad(
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subgraph, pre_paddings.data(), post_paddings.data(), padding_value, 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_constant_pad);
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for (size_t i = 0; i < dims.size(); i++) {
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ASSERT_EQ(node->params.static_pad.pre_paddings[i], pre_paddings[i]);
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ASSERT_EQ(node->params.static_pad.post_paddings[i], post_paddings[i]);
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}
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ASSERT_EQ(node->params.static_pad.padding_value, quantized_padding_value);
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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(StaticConstantPadTestF16, define)
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{
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std::array<size_t, XNN_MAX_TENSOR_DIMS> pre_paddings;
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std::array<size_t, XNN_MAX_TENSOR_DIMS> post_paddings;
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std::fill(pre_paddings.begin(), pre_paddings.begin() + dims.size(), dim_dist(rng));
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std::fill(post_paddings.begin(), post_paddings.begin() + dims.size(), dim_dist(rng));
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union {
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xnn_float16 padding_value;
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uint16_t padding_value_as_bits;
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};
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padding_value = static_cast<xnn_float16>(f32dist(rng));
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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(/*external_value_ids=*/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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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_fp16, dims.size(), dims.data(), nullptr, 0,
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/*flags=*/XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id));
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ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
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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_fp16, dims.size(), dims.data(), nullptr, 1,
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/*flags=*/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_constant_pad(
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subgraph, pre_paddings.data(), post_paddings.data(), padding_value, 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_constant_pad);
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for (size_t i = 0; i < dims.size(); i++) {
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ASSERT_EQ(node->params.static_pad.pre_paddings[i], pre_paddings[i]);
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ASSERT_EQ(node->params.static_pad.post_paddings[i], post_paddings[i]);
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}
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ASSERT_EQ(node->params.static_pad.padding_value, padding_value_as_bits);
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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(StaticConstantPadTestF32, define)
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{
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std::array<size_t, XNN_MAX_TENSOR_DIMS> pre_paddings;
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std::array<size_t, XNN_MAX_TENSOR_DIMS> post_paddings;
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std::fill(pre_paddings.begin(), pre_paddings.begin() + dims.size(), dim_dist(rng));
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std::fill(post_paddings.begin(), post_paddings.begin() + dims.size(), dim_dist(rng));
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float padding_value = f32dist(rng);
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uint32_t padding_value_as_bits = float_as_uint32(padding_value);
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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(/*external_value_ids=*/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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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, dims.size(), dims.data(), nullptr, 0,
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/*flags=*/XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id));
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ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
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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, dims.size(), dims.data(), nullptr, 1,
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/*flags=*/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_constant_pad(
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subgraph, pre_paddings.data(), post_paddings.data(), padding_value, 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_constant_pad);
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for (size_t i = 0; i < dims.size(); i++) {
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ASSERT_EQ(node->params.static_pad.pre_paddings[i], pre_paddings[i]);
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ASSERT_EQ(node->params.static_pad.post_paddings[i], post_paddings[i]);
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}
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ASSERT_EQ(node->params.static_pad.padding_value, padding_value_as_bits);
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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(StaticConstantPadTestInt8, matches_operator_api)
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{
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const int32_t zero_point = i8dist(rng);
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const float scale = scale_dist(rng);
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std::array<size_t, XNN_MAX_TENSOR_DIMS> pre_paddings;
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std::array<size_t, XNN_MAX_TENSOR_DIMS> post_paddings;
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std::fill(pre_paddings.begin(), pre_paddings.begin() + dims.size(), dim_dist(rng));
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std::fill(post_paddings.begin(), post_paddings.begin() + dims.size(), dim_dist(rng));
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float padding_value = f32dist(rng);
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uint32_t quantized_padding_value = xnn_qs8_quantize(padding_value, scale, zero_point);
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std::vector<size_t> output_dims = dims;
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for (size_t i = 0; i < dims.size(); i++) {
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output_dims[i] = pre_paddings[i] + output_dims[i] + post_paddings[i];
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}
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// Output sizes
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operator_output = xnnpack::Buffer<int8_t>(NumElements(output_dims));
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subgraph_output = xnnpack::Buffer<int8_t>(operator_output.size());
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std::iota(input.begin(), input.end(), 0);
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ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
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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_constant_pad_nd_x8(&quantized_padding_value, /*flags=*/0, &op);
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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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std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_op(op, xnn_delete_operator);
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ASSERT_EQ(
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xnn_status_success,
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xnn_reshape_constant_pad_nd_x8(
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op, dims.size(), dims.data(), pre_paddings.data(), post_paddings.data(), /*threadpool=*/nullptr));
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ASSERT_EQ(xnn_status_success, xnn_setup_constant_pad_nd_x8(op, input.data(), operator_output.data()));
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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(/*external_value_ids=*/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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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, zero_point, scale, dims.size(), dims.data(), nullptr, 0,
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/*flags=*/XNN_VALUE_FLAG_EXTERNAL_INPUT, &input_id));
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ASSERT_NE(input_id, XNN_INVALID_NODE_ID);
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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_quantized_tensor_value(
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subgraph, xnn_datatype_qint8, zero_point, scale, output_dims.size(), output_dims.data(), nullptr, 1,
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/*flags=*/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_constant_pad(
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subgraph, pre_paddings.data(), post_paddings.data(), padding_value, 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(StaticConstantPadTestUint8, matches_operator_api)
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{
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const int32_t zero_point = u8dist(rng);
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const float scale = scale_dist(rng);
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std::array<size_t, XNN_MAX_TENSOR_DIMS> pre_paddings;
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std::array<size_t, XNN_MAX_TENSOR_DIMS> post_paddings;
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std::fill(pre_paddings.begin(), pre_paddings.begin() + dims.size(), dim_dist(rng));
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std::fill(post_paddings.begin(), post_paddings.begin() + dims.size(), dim_dist(rng));
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float padding_value = f32dist(rng);
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uint32_t quantized_padding_value = xnn_qu8_quantize(padding_value, scale, zero_point);
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std::vector<size_t> output_dims = dims;
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for (size_t i = 0; i < dims.size(); i++) {
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output_dims[i] = pre_paddings[i] + output_dims[i] + post_paddings[i];
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}
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// Output sizes
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operator_output = xnnpack::Buffer<uint8_t>(NumElements(output_dims));
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subgraph_output = xnnpack::Buffer<uint8_t>(operator_output.size());
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std::iota(input.begin(), input.end(), 0);
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ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
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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_constant_pad_nd_x8(&quantized_padding_value, /*flags=*/0, &op);
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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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std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_op(op, xnn_delete_operator);
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ASSERT_EQ(
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xnn_status_success,
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xnn_reshape_constant_pad_nd_x8(
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op, dims.size(), dims.data(), pre_paddings.data(), post_paddings.data(), /*threadpool=*/nullptr));
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ASSERT_EQ(xnn_status_success, xnn_setup_constant_pad_nd_x8(op, input.data(), operator_output.data()));
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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(/*external_value_ids=*/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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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, zero_point, scale, dims.size(), dims.data(), nullptr, 0,
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/*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, zero_point, 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_static_constant_pad(
|
|
subgraph, pre_paddings.data(), post_paddings.data(), padding_value, 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(StaticConstantPadTestF16, matches_operator_api)
|
|
{
|
|
std::array<size_t, XNN_MAX_TENSOR_DIMS> pre_paddings;
|
|
std::array<size_t, XNN_MAX_TENSOR_DIMS> post_paddings;
|
|
std::fill(pre_paddings.begin(), pre_paddings.begin() + dims.size(), dim_dist(rng));
|
|
std::fill(post_paddings.begin(), post_paddings.begin() + dims.size(), dim_dist(rng));
|
|
float padding_value = f32dist(rng);
|
|
xnn_float16 padding_value_half = static_cast<xnn_float16>(padding_value);
|
|
std::vector<size_t> output_dims = dims;
|
|
for (size_t i = 0; i < dims.size(); i++) {
|
|
output_dims[i] = pre_paddings[i] + output_dims[i] + post_paddings[i];
|
|
}
|
|
// Output sizes
|
|
operator_output = xnnpack::Buffer<xnn_float16>(NumElements(output_dims));
|
|
subgraph_output = xnnpack::Buffer<xnn_float16>(operator_output.size());
|
|
|
|
std::iota(input.begin(), input.end(), 0);
|
|
|
|
ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
|
|
|
|
// Call operator API.
|
|
xnn_operator_t op = nullptr;
|
|
const xnn_status status = xnn_create_constant_pad_nd_x16(&padding_value_half, /*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_constant_pad_nd_x16(
|
|
op, dims.size(), dims.data(), pre_paddings.data(), post_paddings.data(), /*threadpool=*/nullptr));
|
|
ASSERT_EQ(xnn_status_success, xnn_setup_constant_pad_nd_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, 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_static_constant_pad(
|
|
subgraph, pre_paddings.data(), post_paddings.data(), padding_value, 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(StaticConstantPadTestF32, matches_operator_api)
|
|
{
|
|
std::array<size_t, XNN_MAX_TENSOR_DIMS> pre_paddings;
|
|
std::array<size_t, XNN_MAX_TENSOR_DIMS> post_paddings;
|
|
std::fill(pre_paddings.begin(), pre_paddings.begin() + dims.size(), dim_dist(rng));
|
|
std::fill(post_paddings.begin(), post_paddings.begin() + dims.size(), dim_dist(rng));
|
|
float padding_value = f32dist(rng);
|
|
uint32_t padding_value_as_u32 = float_as_uint32(padding_value);
|
|
std::vector<size_t> output_dims = dims;
|
|
for (size_t i = 0; i < dims.size(); i++) {
|
|
output_dims[i] = pre_paddings[i] + output_dims[i] + post_paddings[i];
|
|
}
|
|
// Output sizes
|
|
operator_output = xnnpack::Buffer<float>(NumElements(output_dims));
|
|
subgraph_output = xnnpack::Buffer<float>(operator_output.size());
|
|
|
|
std::iota(input.begin(), input.end(), 0);
|
|
|
|
ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
|
|
|
|
// Call operator API.
|
|
xnn_operator_t op = nullptr;
|
|
const xnn_status status = xnn_create_constant_pad_nd_x32(&padding_value_as_u32, /*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_constant_pad_nd_x32(
|
|
op, dims.size(), dims.data(), pre_paddings.data(), post_paddings.data(), /*threadpool=*/nullptr));
|
|
ASSERT_EQ(xnn_status_success, xnn_setup_constant_pad_nd_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, 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_static_constant_pad(
|
|
subgraph, pre_paddings.data(), post_paddings.data(), padding_value, 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(StaticConstantPadTestF32, reshape_output)
|
|
{
|
|
std::array<size_t, XNN_MAX_TENSOR_DIMS> pre_paddings;
|
|
std::array<size_t, XNN_MAX_TENSOR_DIMS> post_paddings;
|
|
std::fill(pre_paddings.begin(), pre_paddings.begin() + dims.size(), dim_dist(rng));
|
|
std::fill(post_paddings.begin(), post_paddings.begin() + dims.size(), dim_dist(rng));
|
|
float padding_value = f32dist(rng);
|
|
std::vector<size_t> output_dims = dims;
|
|
for (size_t i = 0; i < dims.size(); i++) {
|
|
output_dims[i] = pre_paddings[i] + output_dims[i] + post_paddings[i];
|
|
}
|
|
subgraph_output = xnnpack::Buffer<float>(NumElements(output_dims));
|
|
|
|
std::iota(input.begin(), input.end(), 0);
|
|
|
|
ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/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, 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_static_constant_pad(
|
|
subgraph, pre_paddings.data(), post_paddings.data(), padding_value, 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));
|
|
|
|
if (!dims.empty()) {
|
|
dims[0] += 2;
|
|
ASSERT_EQ(xnn_status_success, xnn_reshape_external_value(runtime, input_id, dims.size(), dims.data()));
|
|
ASSERT_EQ(xnn_status_success, xnn_reshape_runtime(runtime));
|
|
const struct xnn_node* node = &subgraph->nodes[0];
|
|
const xnn_shape* output_shape = &runtime->values[node->outputs[0]].shape;
|
|
for (size_t i = 0; i < output_shape->num_dims; ++i) {
|
|
ASSERT_EQ(output_shape->dim[i], dims[i] + pre_paddings[i] + post_paddings[i]);
|
|
}
|
|
|
|
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);
|
|
for (size_t i = 0; i < output_shape->num_dims; ++i) {
|
|
ASSERT_EQ(output_shape->dim[i], dims[i] + pre_paddings[i] + post_paddings[i]);
|
|
}
|
|
}
|
|
}
|