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.""" 16from __future__ import absolute_import 17from __future__ import division 18from __future__ import print_function 19 20import tensorflow.compat.v1 as tf 21from tensorflow.lite.testing.zip_test_utils import create_tensor_data 22from tensorflow.lite.testing.zip_test_utils import make_zip_of_tests 23from tensorflow.lite.testing.zip_test_utils import register_make_test_function 24 25 26@register_make_test_function() 27def make_tile_tests(options): 28 """Make a set of tests to do tile.""" 29 test_parameters = [{ 30 "input_dtype": [tf.float32, tf.int32, tf.bool, tf.string], 31 "input_shape": [[3, 2, 1], [2, 2, 2]], 32 "multiplier_dtype": [tf.int32, tf.int64], 33 "multiplier_shape": [[3]] 34 }] 35 36 def build_graph(parameters): 37 """Build the tile op testing graph.""" 38 input_value = tf.compat.v1.placeholder( 39 dtype=parameters["input_dtype"], 40 shape=parameters["input_shape"], 41 name="input") 42 multiplier_value = tf.compat.v1.placeholder( 43 dtype=parameters["multiplier_dtype"], 44 shape=parameters["multiplier_shape"], 45 name="multiplier") 46 out = tf.tile(input_value, multiplier_value) 47 return [input_value, multiplier_value], [out] 48 49 def build_inputs(parameters, sess, inputs, outputs): 50 input_value = create_tensor_data(parameters["input_dtype"], 51 parameters["input_shape"]) 52 multipliers_value = create_tensor_data( 53 parameters["multiplier_dtype"], 54 parameters["multiplier_shape"], 55 min_value=0) 56 return [input_value, multipliers_value], sess.run( 57 outputs, 58 feed_dict={ 59 inputs[0]: input_value, 60 inputs[1]: multipliers_value 61 }) 62 63 make_zip_of_tests(options, test_parameters, build_graph, build_inputs) 64