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 "tensorflow/core/framework/allocator.h" 19 #include "tensorflow/core/framework/fake_input.h" 20 #include "tensorflow/core/framework/node_def_builder.h" 21 #include "tensorflow/core/framework/op_kernel.h" 22 #include "tensorflow/core/framework/tensor.h" 23 #include "tensorflow/core/framework/tensor_testutil.h" 24 #include "tensorflow/core/framework/types.h" 25 #include "tensorflow/core/framework/types.pb.h" 26 #include "tensorflow/core/kernels/ops_testutil.h" 27 #include "tensorflow/core/kernels/ops_util.h" 28 #include "tensorflow/core/kernels/quantization_utils.h" 29 #include "tensorflow/core/lib/core/status_test_util.h" 30 #include "tensorflow/core/platform/test.h" 31 32 namespace tensorflow { 33 34 class QuantizedPoolingTest : public OpsTestBase { 35 protected: 36 }; 37 38 TEST_F(QuantizedPoolingTest, SmallAveragePooling) { 39 const int ksize = 2; 40 const int stride = 2; 41 TF_ASSERT_OK(NodeDefBuilder("quantized_avg_pool_op", "QuantizedAvgPool") 42 .Input(FakeInput(DT_QUINT8)) 43 .Input(FakeInput(DT_FLOAT)) 44 .Input(FakeInput(DT_FLOAT)) 45 .Attr("T", DataTypeToEnum<quint8>::v()) 46 .Attr("ksize", {1, ksize, ksize, 1}) 47 .Attr("strides", {1, stride, stride, 1}) 48 .Attr("padding", "SAME") 49 .Finalize(node_def())); 50 TF_ASSERT_OK(InitOp()); 51 const float input_min = 0.0f; 52 const float input_max = 255.0f; 53 const int input_height = 4; 54 const int input_width = 4; 55 const int input_channels = 2; 56 Tensor input_float(DT_FLOAT, {1, input_height, input_width, input_channels}); 57 test::FillValues<float>( 58 &input_float, 59 {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 60 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32}); 61 Tensor input_quantized = 62 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); 63 64 const int expected_width = input_width / stride; 65 const int expected_height = input_height / stride; 66 Tensor expected_float(DT_FLOAT, 67 {1, expected_height, expected_width, input_channels}); 68 test::FillValues<float>(&expected_float, {6, 7, 10, 11, 22, 23, 26, 27}); 69 70 AddInputFromArray<quint8>(input_quantized.shape(), 71 input_quantized.flat<quint8>()); 72 AddInputFromArray<float>(TensorShape({1}), {input_min}); 73 AddInputFromArray<float>(TensorShape({1}), {input_max}); 74 TF_ASSERT_OK(RunOpKernel()); 75 const Tensor& output_quantized = *GetOutput(0); 76 const float output_min = GetOutput(1)->flat<float>()(0); 77 const float output_max = GetOutput(2)->flat<float>()(0); 78 Tensor output_float = 79 QuantizedTensorToFloat<quint8>(output_quantized, output_min, output_max); 80 test::ExpectTensorNear<float>(expected_float, output_float, 0.2); 81 } 82 83 TEST_F(QuantizedPoolingTest, SmallMaxPooling) { 84 const int ksize = 2; 85 const int stride = 2; 86 TF_ASSERT_OK(NodeDefBuilder("quantized_max_pool_op", "QuantizedMaxPool") 87 .Input(FakeInput(DT_QUINT8)) 88 .Input(FakeInput(DT_FLOAT)) 89 .Input(FakeInput(DT_FLOAT)) 90 .Attr("T", DataTypeToEnum<quint8>::v()) 91 .Attr("ksize", {1, ksize, ksize, 1}) 92 .Attr("strides", {1, stride, stride, 1}) 93 .Attr("padding", "SAME") 94 .Finalize(node_def())); 95 TF_ASSERT_OK(InitOp()); 96 const float input_min = 0.0f; 97 const float input_max = 255.0f; 98 const int input_height = 4; 99 const int input_width = 4; 100 const int input_channels = 2; 101 Tensor input_float(DT_FLOAT, {1, input_height, input_width, input_channels}); 102 test::FillValues<float>( 103 &input_float, 104 {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 105 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32}); 106 Tensor input_quantized = 107 FloatTensorToQuantized<quint8>(input_float, input_min, input_max); 108 109 const int expected_width = input_width / stride; 110 const int expected_height = input_height / stride; 111 Tensor expected_float(DT_FLOAT, 112 {1, expected_height, expected_width, input_channels}); 113 test::FillValues<float>(&expected_float, {11, 12, 15, 16, 27, 28, 31, 32}); 114 115 AddInputFromArray<quint8>(input_quantized.shape(), 116 input_quantized.flat<quint8>()); 117 AddInputFromArray<float>(TensorShape({1}), {input_min}); 118 AddInputFromArray<float>(TensorShape({1}), {input_max}); 119 TF_ASSERT_OK(RunOpKernel()); 120 const Tensor& output_quantized = *GetOutput(0); 121 const float output_min = GetOutput(1)->flat<float>()(0); 122 const float output_max = GetOutput(2)->flat<float>()(0); 123 Tensor output_float = 124 QuantizedTensorToFloat<quint8>(output_quantized, output_min, output_max); 125 test::ExpectTensorNear<float>(expected_float, output_float, 0.2); 126 } 127 128 } // namespace tensorflow 129
