1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
|
/*
* Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "arm_compute/core/TensorShape.h"
#include "arm_compute/core/Types.h"
#include "tests/AssetsLibrary.h"
#include "tests/Globals.h"
#include "tests/IAccessor.h"
#include "tests/framework/Asserts.h"
#include "tests/framework/Fixture.h"
#include "tests/validation/Helpers.h"
#include "tests/validation/reference/DeconvolutionLayer.h"
#include <random>
namespace arm_compute
{
namespace test
{
namespace validation
{
template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
class DeconvolutionLayerFixtureBase : public framework::Fixture
{
public:
template <typename...>
void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info,
const std::pair<unsigned int, unsigned int> &inner_border, DataType data_type)
{
_data_type = data_type;
_target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, inner_border, data_type);
_reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, inner_border, data_type);
}
protected:
template <typename U>
void fill(U &&tensor, int i)
{
if(is_data_type_float(tensor.data_type()))
{
std::uniform_real_distribution<> distribution(-1.0f, 1.0f);
library->fill(tensor, distribution, i);
}
else
{
library->fill_tensor_uniform(tensor, i);
}
}
TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape,
const PadStrideInfo &info, const std::pair<unsigned int, unsigned int> &inner_border, DataType data_type)
{
// Create tensors
TensorType src = create_tensor<TensorType>(input_shape, data_type, 1);
TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1);
TensorType bias = create_tensor<TensorType>(bias_shape, data_type, 1);
TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1);
// Create and configure function
FunctionType conv;
conv.configure(&src, &weights, &bias, &dst, info, inner_border.first, inner_border.second);
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
// Allocate tensors
src.allocator()->allocate();
weights.allocator()->allocate();
bias.allocator()->allocate();
dst.allocator()->allocate();
ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(!weights.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(!bias.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
// Fill tensors
fill(AccessorType(src), 0);
fill(AccessorType(weights), 1);
fill(AccessorType(bias), 2);
// Compute NEConvolutionLayer function
conv.run();
return dst;
}
SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape,
const PadStrideInfo &info, const std::pair<unsigned int, unsigned int> inner_border, DataType data_type)
{
// Create reference
SimpleTensor<T> src{ input_shape, data_type, 1 };
SimpleTensor<T> weights{ weights_shape, data_type, 1 };
SimpleTensor<T> bias{ bias_shape, data_type, 1 };
// Fill reference
fill(src, 0);
fill(weights, 1);
fill(bias, 2);
return reference::deconvolution_layer<T>(src, weights, bias, output_shape, info, inner_border);
}
TensorType _target{};
SimpleTensor<T> _reference{};
DataType _data_type{};
};
template <typename TensorType, typename AccessorType, typename FunctionType, typename T, unsigned int kernel_size_x, unsigned int kernel_size_y>
class DeconvolutionValidationFixture : public DeconvolutionLayerFixtureBase<TensorType, AccessorType, FunctionType, T>
{
public:
template <typename...>
void setup(TensorShape input_shape, unsigned int sx, unsigned int sy, unsigned int padx, unsigned int pady,
unsigned int inner_border_right, unsigned int inner_border_top, unsigned int num_kernels, DataType data_type)
{
ARM_COMPUTE_ERROR_ON_MSG(kernel_size_x != kernel_size_y, "Only square kernels supported");
const TensorShape weights_shape(kernel_size_x, kernel_size_y, input_shape.z(), num_kernels);
const TensorShape bias_shape(num_kernels);
const PadStrideInfo info(sx, sy, padx, pady, DimensionRoundingType::CEIL);
const std::pair<unsigned int, unsigned int> inner_border(inner_border_right, inner_border_top);
auto out_dim = deconvolution_output_dimensions(input_shape.x(), input_shape.y(), kernel_size_x, kernel_size_y, padx, pady, inner_border.first, inner_border.second, sx, sy);
TensorShape output_shape = deconvolution_output_shape(out_dim, input_shape, weights_shape);
DeconvolutionLayerFixtureBase<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, inner_border, data_type);
}
};
} // namespace validation
} // namespace test
} // namespace arm_compute
|
