Files
openvino/model-optimizer/unit_tests/mo/utils/pipeline_config_test.py
Evgeny Lazarev 4547818fb1 Move TF OD API docs to code + several fixes for TF OD API models conversion (#7377)
* Refactored code, updated comments and documentation related to TF OD API models pre-processing.

* Improved MO messages related to pre-processor block removal during conversion of the TD OD API models. Remove mean/scale if padding is used and mean/scale is applied before resize

* Updated TF OD API transformation and documentation for SSD models

* Updated comments and documentation for the ObjectDetectionAPIMaskRCNNSigmoidReplacement transformation

* Updated comments and documentation for the ObjectDetectionAPIMaskRCNNROIPoolingSecondReplacement transformation

* Updated comments and documentation for the ObjectDetectionAPIPSROIPoolingReplacement transformation

* Updated comments and documentation for the ObjectDetectionAPIProposalReplacement transformation

* Updated comments and documentation for the ObjectDetectionAPIDetectionOutputReplacement transformation

* Minor code style fixes

* Fixed unit tests for ObjectDetectionAPIPreprocessor2Replacement transformation

* Improved unit test for pipeline.config parser. Fixed very long bug with incorrect test data for the PipelineConfig parser class

* Code style fixes

* Get rid of "coordinates_swap_method" parameter in the JSON configuration file for TF OD API models

* Code style fixes and minor refactoring

* Simplied code related to swapping Proposal coordinates

* Removed incorrectly removed code

* Fixed code review comments about the code comments
2021-09-08 10:03:01 +03:00

138 lines
4.8 KiB
Python

# Copyright (C) 2018-2021 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import unittest.mock
from mo.utils.error import Error
from mo.utils.pipeline_config import PipelineConfig
file_content = """model {
faster_rcnn {
num_classes: 90
image_resizer {
keep_aspect_ratio_resizer {
min_dimension: 600
max_dimension: 1024
pad_to_max_dimension: true
}
}
feature_extractor {
type: "faster_rcnn_inception_v2"
first_stage_features_stride: 16
}
first_stage_anchor_generator {
grid_anchor_generator {
height_stride: 16
width_stride: 16
scales: 0.25
scales: 0.5
scales: 1.0
scales: 2.0
aspect_ratios: 0.5
aspect_ratios: 1.0
aspect_ratios: 2.0
}
}
first_stage_box_predictor_conv_hyperparams {
op: CONV
regularizer {
l2_regularizer {
weight: 0.0
}
}
initializer {
truncated_normal_initializer {
stddev: 0.00999999977648
}
}
}
first_stage_nms_score_threshold: 0.0
first_stage_nms_iou_threshold: 0.699999988079
first_stage_max_proposals: 100
first_stage_localization_loss_weight: 2.0
first_stage_objectness_loss_weight: 1.0
initial_crop_size: 14
maxpool_kernel_size: 2
maxpool_stride: 2
second_stage_box_predictor {
mask_rcnn_box_predictor {
fc_hyperparams {
op: FC
regularizer {
l2_regularizer {
weight: 0.0
}
}
initializer {
variance_scaling_initializer {
factor: 1.0
uniform: true
mode: FAN_AVG
}
}
}
use_dropout: false
dropout_keep_probability: 1.0
}
}
second_stage_post_processing {
batch_non_max_suppression {
score_threshold: 0.300000011921
iou_threshold: 0.600000023842
max_detections_per_class: 100
max_total_detections: 200
}
score_converter: SOFTMAX
}
second_stage_localization_loss_weight: 2.0
second_stage_classification_loss_weight: 1.0
}
}
"""
class TestingSimpleProtoParser(unittest.TestCase):
def test_pipeline_config_not_existing_file(self):
self.assertRaises(Error, PipelineConfig, "/abc/def")
def test_pipeline_config_non_model_file(self):
with unittest.mock.patch('builtins.open', unittest.mock.mock_open(read_data="non_model {}")):
self.assertRaises(Error, PipelineConfig, __file__)
def test_pipeline_config_existing_file(self):
with unittest.mock.patch('builtins.open', unittest.mock.mock_open(read_data=file_content)):
pipeline_config = PipelineConfig(__file__)
expected_result = {'resizer_min_dimension': 600,
'first_stage_nms_score_threshold': 0.0,
'anchor_generator_aspect_ratios': [0.5, 1.0, 2.0],
'num_classes': 90,
'anchor_generator_scales': [0.25, 0.5, 1.0, 2.0],
'first_stage_max_proposals': 100,
'first_stage_nms_iou_threshold': 0.699999988079,
'resizer_max_dimension': 1024,
'initial_crop_size': 14,
'frcnn_variance_height': 5.0,
'frcnn_variance_width': 5.0,
'frcnn_variance_x': 10.0,
'frcnn_variance_y': 10.0,
'ssd_anchor_generator_base_anchor_width': 1.0,
'ssd_anchor_generator_base_anchor_height': 1.0,
'anchor_generator_height': 256,
'anchor_generator_width': 256,
'anchor_generator_height_stride': 16,
'anchor_generator_width_stride': 16,
'ssd_anchor_generator_min_scale': 0.2,
'ssd_anchor_generator_max_scale': 0.95,
'ssd_anchor_generator_interpolated_scale_aspect_ratio': 1.0,
'use_matmul_crop_and_resize': False,
'add_background_class': True,
'share_box_across_classes': False,
'pad_to_max_dimension': True,
'postprocessing_score_threshold': 0.300000011921,
'postprocessing_score_converter': 'SOFTMAX',
'postprocessing_iou_threshold': 0.600000023842,
'postprocessing_max_detections_per_class': 100,
'postprocessing_max_total_detections': 200,
}
self.assertDictEqual(pipeline_config._model_params, expected_result)