1 # 2 # Copyright (C) 2018 The Android Open Source Project 3 # 4 # Licensed under the Apache License, Version 2.0 (the "License"); 5 # you may not use this file except in compliance with the License. 6 # You may obtain a copy of the License at 7 # 8 # http://www.apache.org/licenses/LICENSE-2.0 9 # 10 # Unless required by applicable law or agreed to in writing, software 11 # distributed under the License is distributed on an "AS IS" BASIS, 12 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 13 # See the License for the specific language governing permissions and 14 # limitations under the License. 15 # 16 17 layout = BoolScalar("layout", False) # NHWC 18 19 # TEST 1: ROI_POOLING_1, outputShape = [2, 2], spatialScale = [0.5, 0.5] 20 i1 = Input("in", "TENSOR_FLOAT32", "{1, 4, 4, 1}") 21 roi1 = Input("roi", "TENSOR_FLOAT32", "{5, 4}") 22 o1 = Output("out", "TENSOR_FLOAT32", "{5, 2, 2, 1}") 23 Model().Operation("ROI_POOLING", i1, roi1, [0, 0, 0, 0, 0], 2, 2, 2.0, 2.0, layout).To(o1) 24 25 quant8 = DataTypeConverter().Identify({ 26 i1: ("TENSOR_QUANT8_ASYMM", 0.25, 128), 27 roi1: ("TENSOR_QUANT16_ASYMM", 0.125, 0), 28 o1: ("TENSOR_QUANT8_ASYMM", 0.25, 128) 29 }) 30 31 # Instantiate an example 32 Example({ 33 i1: [ 34 -10, -1, 4, -5, 35 -8, -2, 9, 1, 36 7, -2, 3, -7, 37 -2, 10, -3, 5 38 ], 39 roi1: [ 40 2, 2, 4, 4, 41 0, 0, 6, 6, 42 2, 0, 4, 6, 43 0, 2, 6, 4, 44 8, 8, 8, 8 # empty region 45 ], 46 o1: [ 47 -2, 9, -2, 3, 48 -1, 9, 10, 5, 49 -1, 9, 10, 3, 50 -2, 9, 7, 3, 51 0, 0, 0, 0 52 ] 53 }).AddNchw(i1, o1, layout).AddVariations("relaxed", quant8, "float16") 54 55 56 # TEST 2: ROI_POOLING_2, outputShape = [2, 3], spatialScale = 0.25 57 i2 = Input("in", "TENSOR_FLOAT32", "{4, 4, 8, 2}") 58 roi2 = Input("roi", "TENSOR_FLOAT32", "{4, 4}") 59 o2 = Output("out", "TENSOR_FLOAT32", "{4, 2, 3, 2}") 60 Model().Operation("ROI_POOLING", i2, roi2, [0, 0, 3, 3], 2, 3, 4.0, 4.0, layout).To(o2) 61 62 quant8 = DataTypeConverter().Identify({ 63 i2: ("TENSOR_QUANT8_ASYMM", 0.04, 0), 64 roi2: ("TENSOR_QUANT16_ASYMM", 0.125, 0), 65 o2: ("TENSOR_QUANT8_ASYMM", 0.04, 0) 66 }) 67 68 # Instantiate an example 69 Example({ 70 i2: [ 71 8.84, 8.88, 7.41, 5.60, 9.95, 4.37, 0.10, 7.64, 6.50, 9.47, 72 7.55, 3.00, 0.89, 3.01, 6.30, 4.40, 1.64, 6.74, 6.16, 8.60, 73 5.85, 3.17, 7.12, 6.79, 5.77, 6.62, 5.13, 8.44, 5.08, 7.12, 74 2.84, 1.19, 8.37, 0.90, 7.86, 9.69, 1.97, 1.31, 4.42, 9.89, 75 0.18, 9.00, 9.30, 0.44, 5.05, 6.47, 1.09, 9.50, 1.30, 2.18, 76 2.05, 7.74, 7.66, 0.65, 4.18, 7.14, 5.35, 7.90, 1.04, 1.47, 77 9.01, 0.95, 4.07, 0.65, 78 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 79 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 80 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 81 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 82 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 83 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 84 0.00, 0.00, 0.00, 0.00, 85 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 86 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 87 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 88 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 89 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 90 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 91 0.00, 0.00, 0.00, 0.00, 92 5.47, 2.64, 0.86, 4.86, 2.38, 2.45, 8.77, 0.06, 3.60, 9.28, 93 5.84, 8.97, 6.89, 1.43, 3.90, 5.91, 7.40, 9.25, 3.12, 4.92, 94 1.87, 3.22, 9.50, 6.73, 2.07, 7.30, 3.07, 4.97, 0.24, 8.91, 95 1.09, 0.27, 7.29, 6.94, 2.31, 6.88, 4.33, 1.37, 0.86, 0.46, 96 6.07, 3.81, 0.86, 6.99, 4.36, 1.92, 8.19, 3.57, 7.90, 6.78, 97 4.64, 6.82, 6.18, 9.63, 2.63, 2.33, 1.36, 2.70, 9.99, 9.85, 98 8.06, 4.80, 7.80, 5.43 99 ], 100 roi2: [ 101 4, 4, 24, 8, 102 4, 4, 28, 12, 103 7, 1, 25, 11, # test rounding 104 1, 7, 5, 11 # test roi with shape smaller than output 105 ], 106 o2: [ 107 6.16, 8.60, 7.12, 6.79, 5.13, 8.44, 7.86, 9.69, 4.42, 9.89, 9.30, 6.47, 108 7.86, 9.89, 9.30, 9.89, 9.30, 9.50, 7.86, 9.89, 9.30, 9.89, 9.30, 9.50, 109 9.50, 6.73, 9.50, 9.28, 6.89, 8.97, 6.18, 9.63, 9.99, 9.85, 9.99, 9.85, 110 7.29, 6.94, 7.29, 6.94, 2.31, 6.88, 7.90, 6.78, 7.90, 6.82, 4.64, 6.82 111 ] 112 }).AddNchw(i2, o2, layout).AddVariations("relaxed", quant8, "float16") 113 114 115 # TEST 3: ROI_POOLING_3, outputShape = [2, 2], spatialScale = [0.5, 1] 116 i3 = Input("in", "TENSOR_FLOAT32", "{4, 4, 4, 1}") 117 roi3 = Input("roi", "TENSOR_FLOAT32", "{5, 4}") 118 o3 = Output("out", "TENSOR_FLOAT32", "{5, 2, 2, 1}") 119 Model().Operation("ROI_POOLING", i3, roi3, [2, 2, 2, 2, 2], 2, 2, 2.0, 1.0, layout).To(o3) 120 121 quant8 = DataTypeConverter().Identify({ 122 i3: ("TENSOR_QUANT8_ASYMM", 0.25, 128), 123 roi3: ("TENSOR_QUANT16_ASYMM", 0.125, 0), 124 o3: ("TENSOR_QUANT8_ASYMM", 0.25, 128) 125 }) 126 127 # Instantiate an example 128 Example({ 129 i3: [ 130 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 131 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 132 -10, -1, 4, -5, 133 -8, -2, 9, 1, 134 7, -2, 3, -7, 135 -2, 10, -3, 5, 136 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 137 ], 138 roi3: [ 139 1, 2, 2, 4, 140 0, 0, 3, 6, 141 1, 0, 2, 6, 142 0, 2, 3, 4, 143 0, 0, 0, 0 144 ], 145 o3: [ 146 -2, 9, -2, 3, 147 -1, 9, 10, 5, 148 -1, 9, 10, 3, 149 -2, 9, 7, 3, 150 -10, -10, -10, -10 151 ] 152 }).AddNchw(i3, o3, layout).AddVariations("relaxed", quant8, "float16") 153
