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 pad.""" 16from __future__ import absolute_import 17from __future__ import division 18from __future__ import print_function 19 20import numpy as np 21import tensorflow.compat.v1 as tf 22from tensorflow.lite.testing.zip_test_utils import create_tensor_data 23from tensorflow.lite.testing.zip_test_utils import make_zip_of_tests 24from tensorflow.lite.testing.zip_test_utils import register_make_test_function 25 26 27@register_make_test_function() 28def make_pad_tests(options): 29 """Make a set of tests to do pad.""" 30 31 # TODO(nupurgarg): Add test for tf.uint8. 32 test_parameters = [ 33 # 4D: 34 { 35 "dtype": [tf.int32, tf.int64, tf.float32], 36 "input_shape": [[1, 1, 2, 1], [2, 1, 1, 1]], 37 "paddings": [[[0, 0], [0, 1], [2, 3], [0, 0]], 38 [[0, 1], [0, 0], [0, 0], [2, 3]]], 39 "constant_paddings": [True, False], 40 "fully_quantize": [False], 41 "quant_16x8": [False] 42 }, 43 # 2D: 44 { 45 "dtype": [tf.int32, tf.int64, tf.float32], 46 "input_shape": [[1, 2]], 47 "paddings": [[[0, 1], [2, 3]]], 48 "constant_paddings": [True, False], 49 "fully_quantize": [False], 50 "quant_16x8": [False] 51 }, 52 # 1D: 53 { 54 "dtype": [tf.int32], 55 "input_shape": [[1]], 56 "paddings": [[[1, 2]]], 57 "constant_paddings": [False], 58 "fully_quantize": [False], 59 "quant_16x8": [False] 60 }, 61 # 4D: 62 { 63 "dtype": [tf.float32], 64 "input_shape": [[1, 1, 2, 1], [2, 1, 1, 1]], 65 "paddings": [[[0, 0], [0, 1], [2, 3], [0, 0]], 66 [[0, 1], [0, 0], [0, 0], [2, 3]], 67 [[0, 0], [0, 0], [0, 0], [0, 0]]], 68 "constant_paddings": [True], 69 "fully_quantize": [True], 70 "quant_16x8": [False, True] 71 }, 72 # 2D: 73 { 74 "dtype": [tf.float32], 75 "input_shape": [[1, 2]], 76 "paddings": [[[0, 1], [2, 3]]], 77 "constant_paddings": [True], 78 "fully_quantize": [True], 79 "quant_16x8": [False, True], 80 }, 81 # 1D: 82 { 83 "dtype": [tf.float32], 84 "input_shape": [[1]], 85 "paddings": [[[1, 2]]], 86 "constant_paddings": [True], 87 "fully_quantize": [True], 88 "quant_16x8": [False, True], 89 }, 90 ] 91 92 def build_graph(parameters): 93 """Build a pad graph given `parameters`.""" 94 input_tensor = tf.compat.v1.placeholder( 95 dtype=parameters["dtype"], 96 name="input", 97 shape=parameters["input_shape"]) 98 99 # Get paddings as either a placeholder or constants. 100 if parameters["constant_paddings"]: 101 paddings = parameters["paddings"] 102 input_tensors = [input_tensor] 103 else: 104 shape = [len(parameters["paddings"]), 2] 105 paddings = tf.compat.v1.placeholder( 106 dtype=tf.int32, name="padding", shape=shape) 107 input_tensors = [input_tensor, paddings] 108 109 out = tf.pad(input_tensor, paddings=paddings) 110 return input_tensors, [out] 111 112 def build_inputs(parameters, sess, inputs, outputs): 113 """Build inputs for pad op.""" 114 115 values = [ 116 create_tensor_data( 117 parameters["dtype"], 118 parameters["input_shape"], 119 min_value=-1, 120 max_value=1) 121 ] 122 if not parameters["constant_paddings"]: 123 values.append(np.array(parameters["paddings"])) 124 return values, sess.run(outputs, feed_dict=dict(zip(inputs, values))) 125 126 make_zip_of_tests(options, test_parameters, build_graph, build_inputs) 127