1# Copyright 2020 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 batchmatmul.""" 16from __future__ import absolute_import 17from __future__ import division 18from __future__ import print_function 19 20import tensorflow 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("make_batchmatmul_tests") 27def make_batchmatmul_tests(options): 28 """Make a set of tests to do basic batch matrix multiply.""" 29 30 test_parameters = [ 31 { 32 "dtype": [tf.float32], 33 "shapes": [((3, 4, 7), (7, 9), (3, 4, 7), (7, 9)), 34 ((None, 4, 5), (None, 5, 6), (3, 4, 5), (3, 5, 6)), 35 ((None, 1, 3, 4), (None, 4, 2), (2, 1, 3, 4), (5, 4, 2))], 36 "adjoint_b": [False, True], 37 "adjoint_a": [False, True], 38 "rhs_constant": [False], 39 "fully_quantize": [False, True], 40 }, 41 ] 42 43 def swap_last_two_dims(*args): 44 """Return a tuple with the last two dimensions swapped.""" 45 return args[:-2] + (args[-1],) + (args[-2],) 46 47 def build_graph(parameters): 48 """Build a simple graph with BatchMatMul.""" 49 placeholder0_shape = parameters["shapes"][0] 50 adj_a = parameters["adjoint_a"] 51 adj_b = parameters["adjoint_b"] 52 rhs_constant = parameters["rhs_constant"] 53 if adj_a: 54 placeholder0_shape = swap_last_two_dims(*placeholder0_shape) 55 input0_tensor = tf.compat.v1.placeholder( 56 dtype=parameters["dtype"], shape=placeholder0_shape) 57 if rhs_constant: 58 if adj_b: 59 constant1_shape = swap_last_two_dims(*parameters["shapes"][3]) 60 else: 61 constant1_shape = parameters["shapes"][3] 62 data = create_tensor_data( 63 parameters["dtype"], constant1_shape, min_value=-1.0, max_value=1.0) 64 input1_constant = tf.constant( 65 data, shape=constant1_shape, dtype=parameters["dtype"]) 66 out = tf.matmul( 67 input0_tensor, input1_constant, adjoint_a=adj_a, adjoint_b=adj_b) 68 return [input0_tensor], [out] 69 else: 70 if adj_b: 71 placeholder1_shape = swap_last_two_dims(*parameters["shapes"][1]) 72 else: 73 placeholder1_shape = parameters["shapes"][1] 74 input1_tensor = tf.compat.v1.placeholder( 75 dtype=parameters["dtype"], shape=placeholder1_shape) 76 out = tf.matmul( 77 input0_tensor, input1_tensor, adjoint_a=adj_a, adjoint_b=adj_b) 78 return [input0_tensor, input1_tensor], [out] 79 80 def build_inputs(parameters, sess, inputs, outputs): 81 """Feed inputs, assign variables, and freeze graph.""" 82 input0_shape = parameters["shapes"][2] 83 adj_a = parameters["adjoint_a"] 84 adj_b = parameters["adjoint_b"] 85 rhs_constant = parameters["rhs_constant"] 86 if adj_a: 87 input0_shape = swap_last_two_dims(*input0_shape) 88 input0_value = create_tensor_data( 89 parameters["dtype"], input0_shape, min_value=-1.0, max_value=1.0) 90 if rhs_constant: 91 output_values = sess.run( 92 outputs, feed_dict=dict(zip(inputs, [input0_value]))) 93 return [input0_value], output_values 94 else: 95 input1_shape = parameters["shapes"][3] if not adj_b else \ 96 swap_last_two_dims(*parameters["shapes"][3]) 97 input1_value = create_tensor_data( 98 parameters["dtype"], input1_shape, min_value=-1.0, max_value=1.0) 99 output_values = sess.run( 100 outputs, feed_dict=dict(zip(inputs, [input0_value, input1_value]))) 101 return [input0_value, input1_value], output_values 102 103 options.use_experimental_converter = True 104 make_zip_of_tests( 105 options, 106 test_parameters, 107 build_graph, 108 build_inputs, 109 expected_tf_failures=0) 110