1# Copyright 2019 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"""Test configs for tile.""" 16import tensorflow.compat.v1 as tf 17from tensorflow.lite.testing.zip_test_utils import create_tensor_data 18from tensorflow.lite.testing.zip_test_utils import make_zip_of_tests 19from tensorflow.lite.testing.zip_test_utils import register_make_test_function 20 21 22@register_make_test_function() 23def make_tile_tests(options): 24 """Make a set of tests to do tile.""" 25 test_parameters = [ 26 { 27 "input_dtype": [tf.float32, tf.int32, tf.bool, tf.string], 28 "input_shape": [[3, 2, 1], [2, 2, 2]], 29 "multiplier_dtype": [tf.int32, tf.int64], 30 "multiplier_shape": [[3]] 31 }, 32 { 33 "input_dtype": [tf.float32, tf.int32], 34 "input_shape": [[]], 35 "multiplier_dtype": [tf.int32, tf.int64], 36 "multiplier_shape": [[0]] 37 }, 38 { 39 "input_dtype": [tf.float32], 40 "input_shape": [[3, 2, 1]], 41 "multiplier_dtype": [tf.int32, tf.int64], 42 "multiplier_shape": [[3]], 43 "fully_quantize": [True], 44 # The input range is used to create representative dataset for both 45 # input and multiplier so it needs to be positive. 46 "input_range": [(1, 10)], 47 } 48 ] 49 50 def build_graph(parameters): 51 """Build the tile op testing graph.""" 52 input_value = tf.compat.v1.placeholder( 53 dtype=parameters["input_dtype"], 54 shape=parameters["input_shape"], 55 name="input") 56 multiplier_value = tf.compat.v1.placeholder( 57 dtype=parameters["multiplier_dtype"], 58 shape=parameters["multiplier_shape"], 59 name="multiplier") 60 out = tf.tile(input_value, multiplier_value) 61 return [input_value, multiplier_value], [out] 62 63 def build_inputs(parameters, sess, inputs, outputs): 64 min_value, max_value = parameters.get("input_range", (-10, 10)) 65 input_value = create_tensor_data( 66 parameters["input_dtype"], 67 parameters["input_shape"], 68 min_value=min_value, 69 max_value=max_value) 70 multipliers_value = create_tensor_data( 71 parameters["multiplier_dtype"], 72 parameters["multiplier_shape"], 73 min_value=0) 74 return [input_value, multipliers_value], sess.run( 75 outputs, 76 feed_dict={ 77 inputs[0]: input_value, 78 inputs[1]: multipliers_value 79 }) 80 81 make_zip_of_tests(options, test_parameters, build_graph, build_inputs) 82