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 add_n.""" 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_add_n_tests(options): 28 """Make a set of tests for AddN op.""" 29 30 test_parameters = [ 31 { 32 "dtype": [tf.float32, tf.int32], 33 "input_shape": [[2, 5, 3, 1]], 34 "num_inputs": [2, 3, 4, 5], 35 "dynamic_range_quantize": [False], 36 }, 37 { 38 "dtype": [tf.float32, tf.int32], 39 "input_shape": [[5]], 40 "num_inputs": [2, 3, 4, 5], 41 "dynamic_range_quantize": [False], 42 }, 43 { 44 "dtype": [tf.float32, tf.int32], 45 "input_shape": [[]], 46 "num_inputs": [2, 3, 4, 5], 47 "dynamic_range_quantize": [False], 48 }, 49 { 50 "dtype": [tf.float32], 51 "input_shape": [[]], 52 "num_inputs": [2, 3, 4, 5], 53 "dynamic_range_quantize": [True], 54 }, 55 ] 56 57 def build_graph(parameters): 58 """Builds the graph given the current parameters.""" 59 input_tensors = [] 60 for i in range(parameters["num_inputs"]): 61 input_tensors.append( 62 tf.compat.v1.placeholder( 63 dtype=parameters["dtype"], 64 name="input_{}".format(i), 65 shape=parameters["input_shape"])) 66 out = tf.add_n(input_tensors) 67 return input_tensors, [out] 68 69 def build_inputs(parameters, sess, inputs, outputs): 70 """Builds operand inputs for op.""" 71 input_data = [] 72 for _ in range(parameters["num_inputs"]): 73 input_data.append( 74 create_tensor_data(parameters["dtype"], parameters["input_shape"])) 75 return input_data, sess.run( 76 outputs, feed_dict={i: d for i, d in zip(inputs, input_data)}) 77 78 make_zip_of_tests(options, test_parameters, build_graph, build_inputs) 79