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