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 import collections 17 18 TestCase = collections.namedtuple("TestCase", [ 19 "inp", "inp_data", "k", "out_values", "out_values_data", "out_indices", 20 "out_indices_data" 21 ]) 22 23 test_cases = [ 24 TestCase( 25 inp=Input("input", "TENSOR_FLOAT32", "{2, 2}"), 26 inp_data=[-2.0, 0.2, 0.8, 0.1], 27 k=Int32Scalar("k", 2), 28 out_values=Output("out_values", "TENSOR_FLOAT32", "{2, 2}"), 29 out_values_data=[0.2, -2.0, 0.8, 0.1], 30 out_indices=Output("out_indices", "TENSOR_INT32", "{2, 2}"), 31 out_indices_data=[1, 0, 0, 1]), 32 TestCase( 33 inp=Input("input", "TENSOR_FLOAT32", "{2, 3}"), 34 inp_data=[-2.0, -3.0, 0.2, 0.8, 0.1, -0.1], 35 k=Int32Scalar("k", 2), 36 out_values=Output("out_values", "TENSOR_FLOAT32", "{2, 2}"), 37 out_values_data=[0.2, -2.0, 0.8, 0.1], 38 out_indices=Output("out_indices", "TENSOR_INT32", "{2, 2}"), 39 out_indices_data=[2, 0, 0, 1]), 40 TestCase( 41 inp=Input("input", "TENSOR_FLOAT32", "{2, 4}"), 42 inp_data=[-2.0, -3.0, -4.0, 0.2, 0.8, 0.1, -0.1, -0.8], 43 k=Int32Scalar("k", 2), 44 out_values=Output("out_values", "TENSOR_FLOAT32", "{2, 2}"), 45 out_values_data=[0.2, -2.0, 0.8, 0.1], 46 out_indices=Output("out_indices", "TENSOR_INT32", "{2, 2}"), 47 out_indices_data=[3, 0, 0, 1]), 48 TestCase( 49 inp=Input("input", "TENSOR_FLOAT32", "{8}"), 50 inp_data=[-2.0, -3.0, -4.0, 0.2, 0.8, 0.1, -0.1, -0.8], 51 k=Int32Scalar("k", 2), 52 out_values=Output("out_values", "TENSOR_FLOAT32", "{2}"), 53 out_values_data=[0.8, 0.2], 54 out_indices=Output("out_indices", "TENSOR_INT32", "{2}"), 55 out_indices_data=[4, 3]), 56 TestCase( 57 inp=Input("input", "TENSOR_QUANT8_ASYMM", "{2, 3}, 2.0, 128"), 58 inp_data=[1, 2, 3, 251, 250, 249], 59 k=Int32Scalar("k", 2), 60 out_values=Output("out_values", "TENSOR_QUANT8_ASYMM", "{2, 2}, 2.0, 128"), 61 out_values_data=[3, 2, 251, 250], 62 out_indices=Output("out_indices", "TENSOR_INT32", "{2, 2}"), 63 out_indices_data=[2, 1, 0, 1]), 64 TestCase( 65 inp=Input("input", "TENSOR_INT32", "{2, 3}"), 66 inp_data=[1, 2, 3, 10251, 10250, 10249], 67 k=Int32Scalar("k", 2), 68 out_values=Output("out_values", "TENSOR_INT32", "{2, 2}"), 69 out_values_data=[3, 2, 10251, 10250], 70 out_indices=Output("out_indices", "TENSOR_INT32", "{2, 2}"), 71 out_indices_data=[2, 1, 0, 1]), 72 ] 73 74 for test_case in test_cases: 75 model = Model().Operation("TOPK_V2", test_case.inp, test_case.k).To( 76 test_case.out_values, test_case.out_indices) 77 Example({ 78 test_case.inp: test_case.inp_data, 79 test_case.out_values: test_case.out_values_data, 80 test_case.out_indices: test_case.out_indices_data 81 }, model=model).AddVariations("relaxed", "float16") 82
