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: dilation set to 1 (default) 20 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 3, 3, 1}") 21 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [.25, .25, .25, .25]) 22 b1 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) 23 o1 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 1}") 24 Model().Operation("CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 0, layout, 1, 1).To(o1) 25 26 # Additional data type 27 quant8 = DataTypeConverter().Identify({ 28 i1: ("TENSOR_QUANT8_ASYMM", 0.5, 0), 29 f1: ("TENSOR_QUANT8_ASYMM", 0.125, 0), 30 b1: ("TENSOR_INT32", 0.0625, 0), 31 o1: ("TENSOR_QUANT8_ASYMM", 0.125, 0) 32 }) 33 34 # Instantiate an example 35 example = Example({ 36 i1: [1.0, 1.0, 1.0, 1.0, 0.5, 1.0, 1.0, 1.0, 1.0], 37 o1: [.875, .875, .875, .875] 38 }).AddNchw(i1, o1, layout).AddInput(f1, b1).AddVariations("relaxed", quant8, "float16") 39 40 41 # TEST 2: dilation set to 3 42 i2 = Input("op1", "TENSOR_FLOAT32", "{1, 9, 9, 1}") 43 f2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 3, 3, 1}", [1, 2, 3, 4, 5, 6, 7, 8, 9]) 44 b2 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) 45 o2 = Output("op4", "TENSOR_FLOAT32", "{1, 3, 3, 1}") 46 Model().Operation("CONV_2D", i2, f2, b2, 0, 0, 0, 0, 1, 1, 0, layout, 3, 3).To(o2) 47 48 # Additional data type 49 quant8 = DataTypeConverter().Identify({ 50 i2: ("TENSOR_QUANT8_ASYMM", 0.5, 0), 51 f2: ("TENSOR_QUANT8_ASYMM", 0.125, 0), 52 b2: ("TENSOR_INT32", 0.0625, 0), 53 o2: ("TENSOR_QUANT8_ASYMM", 0.125, 0) 54 }) 55 56 # Instantiate an example 57 example = Example({ 58 i2: [0, 0, 0, 0, 0, 0, 0, 0, 0, 59 0, 0, 0, 0, 0, 0, 0, 0, 0, 60 0, 0, 0, 0, 0, 0, 0, 0, 0, 61 0, 0, 0, 1, 1, 1, 0, 0, 0, 62 0, 0, 0, 1, 1, 1, 0, 0, 0, 63 0, 0, 0, 1, 1, 1, 0, 0, 0, 64 0, 0, 0, 0, 0, 0, 0, 0, 0, 65 0, 0, 0, 0, 0, 0, 0, 0, 0, 66 0, 0, 0, 0, 0, 0, 0, 0, 0], 67 o2: [5, 5, 5, 5, 5, 5, 5, 5, 5] 68 }).AddNchw(i2, o2, layout).AddInput(f2, b2).AddVariations("relaxed", quant8, "float16") 69 70 # TEST 3: same as test 1 but with implicit VALID padding 71 i1 = Input("op1", "TENSOR_FLOAT32", "{1, 3, 3, 1}") 72 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [.25, .25, .25, .25]) 73 b1 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) 74 o1 = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 1}") 75 Model().Operation("CONV_2D", i1, f1, b1, 2, 1, 1, 0, layout, 1, 1).To(o1) 76 77 # Additional data type 78 quant8 = DataTypeConverter().Identify({ 79 i1: ("TENSOR_QUANT8_ASYMM", 0.5, 0), 80 f1: ("TENSOR_QUANT8_ASYMM", 0.125, 0), 81 b1: ("TENSOR_INT32", 0.0625, 0), 82 o1: ("TENSOR_QUANT8_ASYMM", 0.125, 0) 83 }) 84 85 # Instantiate an example 86 example = Example({ 87 i1: [1.0, 1.0, 1.0, 1.0, 0.5, 1.0, 1.0, 1.0, 1.0], 88 o1: [.875, .875, .875, .875] 89 }, name="valid_padding").AddNchw(i1, o1, layout).AddInput(f1, b1).AddVariations("relaxed", quant8, "float16") 90 91 92 # TEST 4: same as test 2 but with implicit VALID padding 93 i2 = Input("op1", "TENSOR_FLOAT32", "{1, 9, 9, 1}") 94 f2 = Parameter("op2", "TENSOR_FLOAT32", "{1, 3, 3, 1}", [1, 2, 3, 4, 5, 6, 7, 8, 9]) 95 b2 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) 96 o2 = Output("op4", "TENSOR_FLOAT32", "{1, 3, 3, 1}") 97 Model().Operation("CONV_2D", i2, f2, b2, 2, 1, 1, 0, layout, 3, 3).To(o2) 98 99 # Additional data type 100 quant8 = DataTypeConverter().Identify({ 101 i2: ("TENSOR_QUANT8_ASYMM", 0.5, 0), 102 f2: ("TENSOR_QUANT8_ASYMM", 0.125, 0), 103 b2: ("TENSOR_INT32", 0.0625, 0), 104 o2: ("TENSOR_QUANT8_ASYMM", 0.125, 0) 105 }) 106 107 # Instantiate an example 108 example = Example({ 109 i2: [0, 0, 0, 0, 0, 0, 0, 0, 0, 110 0, 0, 0, 0, 0, 0, 0, 0, 0, 111 0, 0, 0, 0, 0, 0, 0, 0, 0, 112 0, 0, 0, 1, 1, 1, 0, 0, 0, 113 0, 0, 0, 1, 1, 1, 0, 0, 0, 114 0, 0, 0, 1, 1, 1, 0, 0, 0, 115 0, 0, 0, 0, 0, 0, 0, 0, 0, 116 0, 0, 0, 0, 0, 0, 0, 0, 0, 117 0, 0, 0, 0, 0, 0, 0, 0, 0], 118 o2: [5, 5, 5, 5, 5, 5, 5, 5, 5] 119 }, name="valid_padding").AddNchw(i2, o2, layout).AddInput(f2, b2).AddVariations("relaxed", quant8, "float16") 120 121 122 # TEST 5: dilation set to 3, SAME padding 123 i3 = Input("op1", "TENSOR_FLOAT32", "{1, 6, 6, 1}") 124 f3 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [1, 2, 3, 4]) 125 b3 = Parameter("op3", "TENSOR_FLOAT32", "{1}", [0]) 126 o3 = Output("op4", "TENSOR_FLOAT32", "{1, 3, 3, 1}") 127 Model().Operation("CONV_2D", i3, f3, b3, 1, 2, 2, 0, layout, 3, 3).To(o3) 128 129 # Additional data type 130 quant8 = DataTypeConverter().Identify({ 131 i3: ("TENSOR_QUANT8_ASYMM", 0.5, 0), 132 f3: ("TENSOR_QUANT8_ASYMM", 0.125, 0), 133 b3: ("TENSOR_INT32", 0.0625, 0), 134 o3: ("TENSOR_QUANT8_ASYMM", 0.125, 0) 135 }) 136 137 # Instantiate an example 138 example = Example({ 139 i3: [0, 0, 0, 0, 0, 0, 140 0, 0, 0, 0, 0, 0, 141 0, 0, 4, 3, 0, 0, 142 0, 0, 2, 1, 0, 0, 143 0, 0, 0, 0, 0, 0, 144 0, 0, 0, 0, 0, 0], 145 o3: [16, 0, 9, 0, 0, 0, 4, 0, 1] 146 }).AddNchw(i3, o3, layout).AddInput(f3, b3).AddVariations("relaxed", quant8, "float16") 147
