1 /* Copyright 2015 The TensorFlow Authors. All Rights Reserved. 2 3 Licensed under the Apache License, Version 2.0 (the "License"); 4 you may not use this file except in compliance with the License. 5 You may obtain a copy of the License at 6 7 http://www.apache.org/licenses/LICENSE-2.0 8 9 Unless required by applicable law or agreed to in writing, software 10 distributed under the License is distributed on an "AS IS" BASIS, 11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 See the License for the specific language governing permissions and 13 limitations under the License. 14 ==============================================================================*/ 15 16 #define EIGEN_USE_THREADS 17 18 #include <functional> 19 20 #include "tensorflow/core/framework/allocator.h" 21 #include "tensorflow/core/framework/fake_input.h" 22 #include "tensorflow/core/framework/node_def_builder.h" 23 #include "tensorflow/core/framework/op_kernel.h" 24 #include "tensorflow/core/framework/tensor.h" 25 #include "tensorflow/core/framework/tensor_testutil.h" 26 #include "tensorflow/core/framework/types.h" 27 #include "tensorflow/core/framework/types.pb.h" 28 #include "tensorflow/core/kernels/ops_testutil.h" 29 #include "tensorflow/core/kernels/ops_util.h" 30 #include "tensorflow/core/kernels/quantization_utils.h" 31 #include "tensorflow/core/lib/core/status_test_util.h" 32 #include "tensorflow/core/platform/test.h" 33 34 namespace tensorflow { 35 36 class QuantizedBiasAddTest : public OpsTestBase { 37 protected: 38 }; 39 40 TEST_F(QuantizedBiasAddTest, Small) { 41 TF_ASSERT_OK(NodeDefBuilder("quantized_bias_add_op", "QuantizedBiasAdd") 42 .Input(FakeInput(DT_QUINT8)) 43 .Input(FakeInput(DT_QUINT8)) 44 .Input(FakeInput(DT_FLOAT)) 45 .Input(FakeInput(DT_FLOAT)) 46 .Input(FakeInput(DT_FLOAT)) 47 .Input(FakeInput(DT_FLOAT)) 48 .Attr("out_type", DataTypeToEnum<qint32>::v()) 49 .Finalize(node_def())); 50 TF_ASSERT_OK(InitOp()); 51 const float input_min = 0.0f; 52 const float input_max = 60.0f; 53 const int input_height = 2; 54 const int input_width = 3; 55 Tensor input_float(DT_FLOAT, {input_height, input_width}); 56 test::FillValues<float>(&input_float, 57 {10.0f, 20.0f, 30.0f, 40.0f, 50.0f, 60.0f}); 58 Tensor input_quantized = 59 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); 60 61 const float bias_min = 0.0f; 62 const float bias_max = 3.0f; 63 const int bias_width = 3; 64 Tensor bias_float(DT_FLOAT, {bias_width}); 65 test::FillValues<float>(&bias_float, {1.0f, 2.0f, 3.0f}); 66 Tensor bias_quantized = 67 FloatTensorToQuantized<quint8>(bias_float, bias_min, bias_max); 68 69 Tensor expected_float(DT_FLOAT, {input_height, input_width}); 70 test::FillValues<float>(&expected_float, 71 {11.0f, 22.0f, 33.0f, 41.0f, 52.0f, 63.0f}); 72 73 AddInputFromArray<quint8>(input_quantized.shape(), 74 input_quantized.flat<quint8>()); 75 AddInputFromArray<quint8>(bias_quantized.shape(), 76 bias_quantized.flat<quint8>()); 77 AddInputFromArray<float>(TensorShape({1}), {input_min}); 78 AddInputFromArray<float>(TensorShape({1}), {input_max}); 79 AddInputFromArray<float>(TensorShape({1}), {bias_min}); 80 AddInputFromArray<float>(TensorShape({1}), {bias_max}); 81 TF_ASSERT_OK(RunOpKernel()); 82 const Tensor& output_quantized = *GetOutput(0); 83 const float output_min = GetOutput(1)->flat<float>()(0); 84 const float output_max = GetOutput(2)->flat<float>()(0); 85 Tensor output_float = 86 QuantizedTensorToFloat<qint32>(output_quantized, output_min, output_max); 87 test::ExpectTensorNear<float>(expected_float, output_float, 0.2); 88 } 89 90 TEST_F(QuantizedBiasAddTest, RealData) { 91 TF_ASSERT_OK(NodeDefBuilder("quantized_bias_add_op", "QuantizedBiasAdd") 92 .Input(FakeInput(DT_QUINT8)) 93 .Input(FakeInput(DT_QUINT8)) 94 .Input(FakeInput(DT_FLOAT)) 95 .Input(FakeInput(DT_FLOAT)) 96 .Input(FakeInput(DT_FLOAT)) 97 .Input(FakeInput(DT_FLOAT)) 98 .Attr("out_type", DataTypeToEnum<qint32>::v()) 99 .Finalize(node_def())); 100 TF_ASSERT_OK(InitOp()); 101 const float input_min = -2164.25f; 102 const float input_max = 2006.27f; 103 const int input_height = 1; 104 const int input_width = 64; 105 Tensor input_float(DT_FLOAT, {input_height, input_width}); 106 test::FillValues<float>( 107 &input_float, 108 {-1014.12, -157.382, -810.17, 1435.28, 1016.37, 219.684, -316.054, 109 -2164.25, 2006.27, -547.444, 857.376, 404.376, 9.72115, 332.588, 110 194.385, -286.57, 26.062, 23.1125, 110.436, 247.055, -127.683, 111 -376.275, -124.81, -846.826, -77.1507, 305.581, -202.747, 12.9528, 112 9.64886, 872.686, 40.9069, 197.816, 44.16, -306.768, -1457.52, 113 -368.939, -1049.42, -486.353, 1745.87, 95.7695, 395.773, -254.333, 114 -404.27, 787.16, -2.44114, 199.37, -1024.08, 784.901, 235.055, 115 -42.7295, 241.498, -245.365, 470.763, 186.159, 186.579, -220.163, 116 1304.58, 386.272, -358.853, -755.996, 360.109, -866.007, 55.2828, 117 -508.801}); 118 Tensor input_quantized = 119 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); 120 121 const float bias_min = -0.739539f; 122 const float bias_max = 0.641057f; 123 const int bias_width = 64; 124 Tensor bias_float(DT_FLOAT, {bias_width}); 125 test::FillValues<float>( 126 &bias_float, 127 {-0.294619, -0.0670519, 0.261507, -0.126274, 0.127229, -0.176945, 128 -0.251223, 0.231086, 0.453694, 0.415666, -0.288733, 0.508717, 129 0.211551, 0.0435907, -0.582383, -0.308779, 0.0696883, -0.438122, 130 0.114, 0.433964, 0.109883, 0.284931, -0.149661, 0.108657, 131 0.458333, -0.130231, -0.35805, -0.123206, -0.437968, 0.0282411, 132 0.628818, -0.0522173, -0.0233403, 0.124863, 0.217165, 0.262294, 133 -0.171005, -0.254693, -0.200433, -0.287354, 0.488166, -0.0354688, 134 -0.118091, -0.590444, 0.491537, -0.739539, 0.083117, 0.282482, 135 0.275269, -0.36574, 0.107476, 0.0511428, -0.136887, -0.0149852, 136 -0.259694, 0.641057, 0.264054, -0.295126, -0.0218791, 0.361211, 137 0.012448, 0.0709718, -0.392394, -0.434215}); 138 Tensor bias_quantized = 139 FloatTensorToQuantized<quint8>(bias_float, bias_min, bias_max); 140 141 Tensor expected_float(DT_FLOAT, {input_height, input_width}); 142 test::FillValues<float>( 143 &expected_float, 144 {-1014.42, -157.449, -809.908, 1435.16, 1016.5, 219.507, -316.305, 145 -2164.02, 2006.73, -547.028, 857.088, 404.885, 9.9327, 332.632, 146 193.803, -286.878, 26.1317, 22.6744, 110.55, 247.489, -127.573, 147 -375.99, -124.959, -846.717, -76.6923, 305.451, -203.105, 12.8296, 148 9.21089, 872.714, 41.5357, 197.764, 44.1367, -306.643, -1457.3, 149 -368.677, -1049.6, -486.608, 1745.67, 95.4821, 396.261, -254.368, 150 -404.388, 786.57, -1.94961, 198.63, -1024.0, 785.183, 235.33, 151 -43.0953, 241.605, -245.314, 470.627, 186.144, 186.319, -219.522, 152 1304.84, 385.977, -358.874, -755.635, 360.122, -865.936, 54.8904, 153 -509.235}); 154 155 AddInputFromArray<quint8>(input_quantized.shape(), 156 input_quantized.flat<quint8>()); 157 AddInputFromArray<quint8>(bias_quantized.shape(), 158 bias_quantized.flat<quint8>()); 159 AddInputFromArray<float>(TensorShape({1}), {input_min}); 160 AddInputFromArray<float>(TensorShape({1}), {input_max}); 161 AddInputFromArray<float>(TensorShape({1}), {bias_min}); 162 AddInputFromArray<float>(TensorShape({1}), {bias_max}); 163 TF_ASSERT_OK(RunOpKernel()); 164 const Tensor& output_quantized = *GetOutput(0); 165 const float output_min = GetOutput(1)->flat<float>()(0); 166 const float output_max = GetOutput(2)->flat<float>()(0); 167 Tensor output_float = 168 QuantizedTensorToFloat<qint32>(output_quantized, output_min, output_max); 169 test::ExpectTensorNear<float>(expected_float, output_float, 20.0); 170 } 171 172 } // namespace tensorflow 173
