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 transpose.""" 16import numpy as np 17import tensorflow.compat.v1 as tf 18from tensorflow.lite.testing.zip_test_utils import create_tensor_data 19from tensorflow.lite.testing.zip_test_utils import make_zip_of_tests 20from tensorflow.lite.testing.zip_test_utils import register_make_test_function 21 22 23@register_make_test_function() 24def make_transpose_tests(options): 25 """Make a set of tests to do transpose.""" 26 27 # TODO(nupurgarg): Add test for uint8. 28 test_parameters = [{ 29 "dtype": [tf.int32, tf.int64, tf.float32], 30 "input_shape": [[2, 2, 3]], 31 "perm": [[0, 1, 2], [0, 2, 1]], 32 "constant_perm": [True, False], 33 "fully_quantize": [False], 34 }, { 35 "dtype": [tf.float32], 36 "input_shape": [[1, 2, 3, 4]], 37 "perm": [[0, 1, 2, 3], [3, 0, 1, 2]], 38 "constant_perm": [True, False], 39 "fully_quantize": [False], 40 }, { 41 "dtype": [tf.float32], 42 "input_shape": [[1, 2, 3, 4, 5]], 43 "perm": [[4, 3, 2, 1, 0]], 44 "constant_perm": [True, False], 45 "fully_quantize": [False], 46 }, { 47 "dtype": [tf.float32], 48 "input_shape": [[2, 2, 3]], 49 "perm": [[0, 1, 2], [0, 2, 1]], 50 "constant_perm": [True], 51 "fully_quantize": [True], 52 }, { 53 "dtype": [tf.float32], 54 "input_shape": [[1, 2, 3, 4]], 55 "perm": [[0, 1, 2, 3], [3, 0, 1, 2]], 56 "constant_perm": [True], 57 "fully_quantize": [True], 58 }, { 59 "dtype": [tf.float32], 60 "input_shape": [[1, 2, 3, 4, 5]], 61 "perm": [[0, 1, 2, 3, 4], [3, 4, 0, 1, 2]], 62 "constant_perm": [True], 63 "fully_quantize": [True, False], 64 }] 65 66 def build_graph(parameters): 67 """Build a transpose graph given `parameters`.""" 68 input_tensor = tf.compat.v1.placeholder( 69 dtype=parameters["dtype"], 70 name="input", 71 shape=parameters["input_shape"]) 72 73 if parameters["constant_perm"]: 74 perm = parameters["perm"] 75 input_tensors = [input_tensor] 76 else: 77 shape = [len(parameters["perm"]), 2] 78 perm = tf.compat.v1.placeholder(dtype=tf.int32, name="perm", shape=shape) 79 input_tensors = [input_tensor, perm] 80 81 out = tf.transpose(input_tensor, perm=perm) 82 return input_tensors, [out] 83 84 def build_inputs(parameters, sess, inputs, outputs): 85 values = [ 86 create_tensor_data(parameters["dtype"], parameters["input_shape"], 87 min_value=-1, max_value=1) 88 ] 89 if not parameters["constant_perm"]: 90 values.append(np.array(parameters["perm"])) 91 return values, sess.run(outputs, feed_dict=dict(zip(inputs, values))) 92 93 make_zip_of_tests( 94 options, 95 test_parameters, 96 build_graph, 97 build_inputs, 98 expected_tf_failures=9) 99