| # Copyright 2020 The TensorFlow Authors. All Rights Reserved. |
| # |
| # Licensed under the Apache License, Version 2.0 (the "License"); |
| # you may not use this file except in compliance with the License. |
| # You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an "AS IS" BASIS, |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| # ============================================================================== |
| """Test configs for strided_slice operators.""" |
| from __future__ import absolute_import |
| from __future__ import division |
| from __future__ import print_function |
| |
| import tensorflow.compat.v1 as tf |
| from tensorflow.lite.testing.zip_test_utils import create_tensor_data |
| from tensorflow.lite.testing.zip_test_utils import make_zip_of_tests |
| from tensorflow.lite.testing.zip_test_utils import register_make_test_function |
| |
| |
| def _make_shape_to_strided_slice_test(options, |
| test_parameters, |
| expected_tf_failures=0): |
| """Utility function to make shape_to_strided_slice_tests.""" |
| |
| def build_graph(parameters): |
| """Build graph for shape_stride_slice test.""" |
| input_tensor = tf.compat.v1.placeholder( |
| dtype=parameters["dtype"], |
| name="input", |
| shape=parameters["dynamic_input_shape"]) |
| begin = parameters["begin"] |
| end = parameters["end"] |
| strides = parameters["strides"] |
| tensors = [input_tensor] |
| out = tf.strided_slice( |
| tf.shape(input_tensor), |
| begin, |
| end, |
| strides, |
| begin_mask=parameters["begin_mask"], |
| end_mask=parameters["end_mask"]) |
| return tensors, [out] |
| |
| def build_inputs(parameters, sess, inputs, outputs): |
| """Build inputs for stride_slice test.""" |
| input_values = create_tensor_data( |
| parameters["dtype"], |
| parameters["input_shape"], |
| min_value=-1, |
| max_value=1) |
| values = [input_values] |
| |
| return values, sess.run(outputs, feed_dict=dict(zip(inputs, values))) |
| |
| make_zip_of_tests( |
| options, |
| test_parameters, |
| build_graph, |
| build_inputs, |
| expected_tf_failures=expected_tf_failures) |
| |
| |
| @register_make_test_function() |
| def make_shape_to_strided_slice_tests(options): |
| """Make a set of tests to do shape op into strided_slice.""" |
| |
| test_parameters = [ |
| # Test dynamic shape into strided slice quantization works. |
| { |
| "dtype": [tf.float32], |
| "dynamic_input_shape": [[None, 2, 2, 5]], |
| "input_shape": [[12, 2, 2, 5]], |
| "strides": [[1]], |
| "begin": [[0]], |
| "end": [[1]], |
| "begin_mask": [0], |
| "end_mask": [0], |
| "fully_quantize": [False, True], |
| "dynamic_range_quantize": [False], |
| }, |
| { |
| "dtype": [tf.float32], |
| "dynamic_input_shape": [[None, 2, 2, 5]], |
| "input_shape": [[12, 2, 2, 5]], |
| "strides": [[1]], |
| "begin": [[0]], |
| "end": [[1]], |
| "begin_mask": [0], |
| "end_mask": [0], |
| "fully_quantize": [False], |
| "dynamic_range_quantize": [True], |
| }, |
| ] |
| _make_shape_to_strided_slice_test( |
| options, test_parameters, expected_tf_failures=0) |