Michalis Spyrou | 16934a5 | 2018-08-21 18:03:58 +0100 | [diff] [blame] | 1 | /* |
| 2 | * Copyright (c) 2018 ARM Limited. |
| 3 | * |
| 4 | * SPDX-License-Identifier: MIT |
| 5 | * |
| 6 | * Permission is hereby granted, free of charge, to any person obtaining a copy |
| 7 | * of this software and associated documentation files (the "Software"), to |
| 8 | * deal in the Software without restriction, including without limitation the |
| 9 | * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| 10 | * sell copies of the Software, and to permit persons to whom the Software is |
| 11 | * furnished to do so, subject to the following conditions: |
| 12 | * |
| 13 | * The above copyright notice and this permission notice shall be included in all |
| 14 | * copies or substantial portions of the Software. |
| 15 | * |
| 16 | * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| 17 | * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| 18 | * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| 19 | * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| 20 | * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| 21 | * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| 22 | * SOFTWARE. |
| 23 | */ |
| 24 | #ifndef ARM_COMPUTE_TEST_SPACE_TO_BATCH_LAYER_FIXTURE |
| 25 | #define ARM_COMPUTE_TEST_SPACE_TO_BATCH_LAYER_FIXTURE |
| 26 | |
| 27 | #include "tests/Globals.h" |
| 28 | #include "tests/framework/Asserts.h" |
| 29 | #include "tests/framework/Fixture.h" |
| 30 | #include "tests/validation/reference/SpaceToBatch.h" |
| 31 | |
| 32 | namespace arm_compute |
| 33 | { |
| 34 | namespace test |
| 35 | { |
| 36 | namespace validation |
| 37 | { |
| 38 | template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| 39 | class SpaceToBatchLayerValidationFixture : public framework::Fixture |
| 40 | { |
| 41 | public: |
| 42 | template <typename...> |
Michalis Spyrou | 13a51e1 | 2018-09-18 13:09:30 +0100 | [diff] [blame] | 43 | void setup(TensorShape input_shape, TensorShape block_shape_shape, TensorShape paddings_shape, TensorShape output_shape, DataType data_type, DataLayout data_layout) |
Michalis Spyrou | 16934a5 | 2018-08-21 18:03:58 +0100 | [diff] [blame] | 44 | { |
Michalis Spyrou | 13a51e1 | 2018-09-18 13:09:30 +0100 | [diff] [blame] | 45 | _target = compute_target(input_shape, block_shape_shape, paddings_shape, output_shape, data_type, data_layout); |
Michalis Spyrou | 16934a5 | 2018-08-21 18:03:58 +0100 | [diff] [blame] | 46 | _reference = compute_reference(input_shape, block_shape_shape, paddings_shape, output_shape, data_type); |
| 47 | } |
| 48 | |
| 49 | protected: |
| 50 | template <typename U> |
| 51 | void fill(U &&tensor, int i) |
| 52 | { |
| 53 | std::uniform_real_distribution<> distribution(-1.0f, 1.0f); |
| 54 | library->fill(tensor, distribution, i); |
| 55 | } |
| 56 | template <typename U> |
| 57 | void fill_pad(U &&tensor, int i) |
| 58 | { |
| 59 | std::uniform_int_distribution<> distribution(0, 0); |
| 60 | library->fill(tensor, distribution, i); |
| 61 | } |
Michalis Spyrou | 13a51e1 | 2018-09-18 13:09:30 +0100 | [diff] [blame] | 62 | TensorType compute_target(TensorShape input_shape, const TensorShape &block_shape_shape, const TensorShape &paddings_shape, TensorShape output_shape, |
| 63 | DataType data_type, DataLayout data_layout) |
Michalis Spyrou | 16934a5 | 2018-08-21 18:03:58 +0100 | [diff] [blame] | 64 | { |
Michalis Spyrou | 13a51e1 | 2018-09-18 13:09:30 +0100 | [diff] [blame] | 65 | if(data_layout == DataLayout::NHWC) |
| 66 | { |
| 67 | permute(input_shape, PermutationVector(2U, 0U, 1U)); |
| 68 | permute(output_shape, PermutationVector(2U, 0U, 1U)); |
| 69 | } |
| 70 | |
Michalis Spyrou | 16934a5 | 2018-08-21 18:03:58 +0100 | [diff] [blame] | 71 | // Create tensors |
Michalis Spyrou | 13a51e1 | 2018-09-18 13:09:30 +0100 | [diff] [blame] | 72 | TensorType input = create_tensor<TensorType>(input_shape, data_type, 1, QuantizationInfo(), data_layout); |
Michalis Spyrou | 16934a5 | 2018-08-21 18:03:58 +0100 | [diff] [blame] | 73 | TensorType block_shape = create_tensor<TensorType>(block_shape_shape, DataType::S32); |
| 74 | TensorType paddings = create_tensor<TensorType>(paddings_shape, DataType::S32); |
Michalis Spyrou | 13a51e1 | 2018-09-18 13:09:30 +0100 | [diff] [blame] | 75 | TensorType output = create_tensor<TensorType>(output_shape, data_type, 1, QuantizationInfo(), data_layout); |
Michalis Spyrou | 16934a5 | 2018-08-21 18:03:58 +0100 | [diff] [blame] | 76 | |
| 77 | // Create and configure function |
| 78 | FunctionType space_to_batch; |
| 79 | space_to_batch.configure(&input, &block_shape, &paddings, &output); |
| 80 | |
| 81 | ARM_COMPUTE_EXPECT(input.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 82 | ARM_COMPUTE_EXPECT(block_shape.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 83 | ARM_COMPUTE_EXPECT(paddings.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 84 | ARM_COMPUTE_EXPECT(output.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 85 | |
| 86 | // Allocate tensors |
| 87 | input.allocator()->allocate(); |
| 88 | block_shape.allocator()->allocate(); |
| 89 | paddings.allocator()->allocate(); |
| 90 | output.allocator()->allocate(); |
| 91 | |
| 92 | ARM_COMPUTE_EXPECT(!input.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 93 | ARM_COMPUTE_EXPECT(!block_shape.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 94 | ARM_COMPUTE_EXPECT(!paddings.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 95 | ARM_COMPUTE_EXPECT(!output.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 96 | |
| 97 | // Fill tensors |
| 98 | fill(AccessorType(input), 0); |
| 99 | fill_pad(AccessorType(paddings), 0); |
| 100 | { |
Michalis Spyrou | 13a51e1 | 2018-09-18 13:09:30 +0100 | [diff] [blame] | 101 | auto block_shape_data = AccessorType(block_shape); |
| 102 | const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); |
Michalis Spyrou | 16934a5 | 2018-08-21 18:03:58 +0100 | [diff] [blame] | 103 | for(unsigned int i = 0; i < block_shape_shape.x(); ++i) |
| 104 | { |
Michalis Spyrou | 13a51e1 | 2018-09-18 13:09:30 +0100 | [diff] [blame] | 105 | static_cast<int32_t *>(block_shape_data.data())[i] = input_shape[i + idx_width] / output_shape[i + idx_width]; |
Michalis Spyrou | 16934a5 | 2018-08-21 18:03:58 +0100 | [diff] [blame] | 106 | } |
| 107 | } |
| 108 | // Compute function |
| 109 | space_to_batch.run(); |
| 110 | |
| 111 | return output; |
| 112 | } |
| 113 | |
| 114 | SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &block_shape_shape, const TensorShape &paddings_shape, |
| 115 | const TensorShape &output_shape, DataType data_type) |
| 116 | { |
| 117 | // Create reference |
| 118 | SimpleTensor<T> input{ input_shape, data_type }; |
| 119 | SimpleTensor<int32_t> block_shape{ block_shape_shape, DataType::S32 }; |
| 120 | SimpleTensor<int32_t> paddings{ paddings_shape, DataType::S32 }; |
| 121 | |
| 122 | // Fill reference |
| 123 | fill(input, 0); |
| 124 | fill_pad(paddings, 0); |
| 125 | for(unsigned int i = 0; i < block_shape_shape.x(); ++i) |
| 126 | { |
| 127 | block_shape[i] = input_shape[i] / output_shape[i]; |
| 128 | } |
| 129 | |
| 130 | // Compute reference |
| 131 | return reference::space_to_batch(input, block_shape, paddings, output_shape); |
| 132 | } |
| 133 | |
| 134 | TensorType _target{}; |
| 135 | SimpleTensor<T> _reference{}; |
| 136 | }; |
| 137 | } // namespace validation |
| 138 | } // namespace test |
| 139 | } // namespace arm_compute |
| 140 | #endif /* ARM_COMPUTE_TEST_SPACE_TO_BATCH_LAYER_FIXTURE */ |