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.gitattributes CHANGED
@@ -36,3 +36,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
36
  densevid_eval/clevr_data/total_change_captions_reformat.json filter=lfs diff=lfs merge=lfs -text
37
  densevid_eval/clevr_data/change_captions.json filter=lfs diff=lfs merge=lfs -text
38
  densevid_eval/clevr_data/train_change_captions.json filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
36
  densevid_eval/clevr_data/total_change_captions_reformat.json filter=lfs diff=lfs merge=lfs -text
37
  densevid_eval/clevr_data/change_captions.json filter=lfs diff=lfs merge=lfs -text
38
  densevid_eval/clevr_data/train_change_captions.json filter=lfs diff=lfs merge=lfs -text
39
+ spot_best/model.chkpt filter=lfs diff=lfs merge=lfs -text
40
+ edit_best/model.chkpt filter=lfs diff=lfs merge=lfs -text
41
+ clevr_best/model.chkpt filter=lfs diff=lfs merge=lfs -text
42
+ filter_files/clevr_similarity_scores.json filter=lfs diff=lfs merge=lfs -text
clevr_best/model.cfg.json ADDED
@@ -0,0 +1,115 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "config": "./config/mmvid_config.yaml",
3
+ "resume": null,
4
+ "save_model": "./results/clevr_2025_07_04_09_48_seed52_ema-1_mmvid/model",
5
+ "save_mode": "best",
6
+ "res_root_dir": "./results",
7
+ "debug": false,
8
+ "seed": 52,
9
+ "no_cuda": false,
10
+ "no_pin_memory": true,
11
+ "cuda": true,
12
+ "dalle_param": {
13
+ "vae": {
14
+ "which_vae": "vqgan1024",
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+ "vae_path": "./pretrained_vqgan/clevr_epoch=000035.ckpt",
16
+ "image_size": 224
17
+ },
18
+ "bert": {
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+ "num_text_tokens": 0,
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+ "text_seq_len": 24,
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+ "dim": 768,
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+ "loss_img_weight": 7,
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+ "text_feature_dim": 0,
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+ "fixed_language_model": null,
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+ "text_emb_bottleneck": null,
26
+ "which_transformer": "openai_clip_visual",
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+ "num_targets": 4,
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+ "num_visuals": 0,
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+ "use_separate_visual_emb": false,
30
+ "beit": true,
31
+ "insert_sep": false,
32
+ "openai_clip_path": "./ckpt/ViT-B-32.pt",
33
+ "vision_layers": 12,
34
+ "rel": true,
35
+ "vid": true
36
+ },
37
+ "skip_params": [
38
+ "to_logits_vid.1.bias",
39
+ "to_logits_vid.1.weight",
40
+ "to_logits_vid.0.bias",
41
+ "to_logits_vid.0.weight",
42
+ "to_logits_rel.1.bias",
43
+ "to_logits_rel.1.weight",
44
+ "to_logits_rel.0.bias",
45
+ "to_logits_rel.0.weight",
46
+ "to_logits.1.bias",
47
+ "to_logits.1.weight",
48
+ "to_logits.0.bias",
49
+ "to_logits.0.weight",
50
+ "to_logits_text.1.bias",
51
+ "to_logits_text.1.weight",
52
+ "to_logits_text.0.bias",
53
+ "to_logits_text.0.weight",
54
+ "image_emb.weight"
55
+ ],
56
+ "freeze": false,
57
+ "use_lora": false,
58
+ "lora_config": {
59
+ "r": 8,
60
+ "lora_alpha": 16,
61
+ "lora_dropout": 0.1,
62
+ "bias": "none"
63
+ }
64
+ },
65
+ "decoder_param": {
66
+ "max_n_sen": 12,
67
+ "max_t_len": 24,
68
+ "max_v_len": 4,
69
+ "exp_id": "init",
70
+ "hidden_size": 512,
71
+ "intermediate_size": 2048,
72
+ "num_hidden_layers": 2,
73
+ "num_attention_heads": 8,
74
+ "mask_prob": 0.0,
75
+ "hidden_dropout_prob": 0.1,
76
+ "label_smoothing": 0.1,
77
+ "recurrent": false,
78
+ "untied": false,
79
+ "mtrans": true,
80
+ "use_beam": false,
81
+ "vocab_size": 80,
82
+ "mask_token_id": 7
83
+ },
84
+ "dset_name": "clevr",
85
+ "data_dir": "/home/sunjiayang/VFI4IDC_test/IDC_scratch_model/densevid_eval/clevr_data",
86
+ "video_feature_dir": "./data/clevr/CLEVR_processed",
87
+ "word2idx_path": "./cache/clevr_word2idx.json",
88
+ "glove_path": "./cache/yc2_vocab_glove.pt",
89
+ "eval_tool_dir": "/home/sunjiayang/VFI4IDC_test/IDC_scratch_model/densevid_eval",
90
+ "filtered": true,
91
+ "filter_file_path": "./filter_files/clevr_similarity_scores.json",
92
+ "max_k": 2,
93
+ "num_frames": 9,
94
+ "recurrent": false,
95
+ "untied": false,
96
+ "mtrans": true,
97
+ "use_beam": false,
98
+ "image_size": 224,
99
+ "n_epoch": 40,
100
+ "batch_size": 16,
101
+ "val_batch_size": 32,
102
+ "max_es_cnt": 50,
103
+ "lr": 5e-05,
104
+ "lr_finetune": 5e-05,
105
+ "lr_warmup_proportion": 0.1,
106
+ "grad_clip": 1,
107
+ "weight_decay": 0.01,
108
+ "ema_decay": -1,
109
+ "num_workers": 8,
110
+ "temperature": 0.5,
111
+ "pretrained_model": "./ckpt/img_size224_layer12_clevr_wovisual_softmax/dalle.pt",
112
+ "res_dir": "./results/clevr_2025_07_04_09_48_seed52_ema-1_mmvid",
113
+ "log": "./results/clevr_2025_07_04_09_48_seed52_ema-1_mmvid/model",
114
+ "pin_memory": false
115
+ }
clevr_best/model.chkpt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:22c231029ab6d7b13b8c315916337b978c24966978d1918c5dc5274f7c1e083a
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+ size 1968010418
clevr_best/model_best_greedy_pred_val_all_metrics.json ADDED
@@ -0,0 +1,30 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "total_results": {
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+ "Bleu_1": 0.8420700803383588,
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+ "Bleu_2": 0.7579372490465773,
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+ "Bleu_3": 0.6636594870114211,
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+ "Bleu_4": 0.5672140810891073,
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+ "METEOR": 0.4165370010265982,
8
+ "ROUGE_L": 0.7472314257366539,
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+ "CIDEr": 1.3562307002208966
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+ },
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+ "change_results": {
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+ "Bleu_1": 0.845858001605002,
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+ "Bleu_2": 0.7597243391607108,
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+ "Bleu_3": 0.6624295759271439,
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+ "Bleu_4": 0.5606241976791171,
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+ "METEOR": 0.3908916952169497,
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+ "ROUGE_L": 0.7253092620179556,
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+ "CIDEr": 1.21632819242502
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+ },
20
+ "unchange_results": {
21
+ "Bleu_1": 0.8266600960945653,
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+ "Bleu_2": 0.7505478349738592,
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+ "Bleu_3": 0.6747631146158112,
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+ "Bleu_4": 0.6366370861460098,
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+ "METEOR": 0.5254467142365439,
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+ "ROUGE_L": 0.7691535894553523,
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+ "CIDEr": 1.1470175404358385
28
+ },
29
+ "type_results": null
30
+ }
densevid_eval/LICENCE ADDED
@@ -0,0 +1,21 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ MIT License
2
+
3
+ Copyright (c) 2017 Ranjay Krishna
4
+
5
+ Permission is hereby granted, free of charge, to any person obtaining a copy
6
+ of this software and associated documentation files (the "Software"), to deal
7
+ in the Software without restriction, including without limitation the rights
8
+ to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
9
+ copies of the Software, and to permit persons to whom the Software is
10
+ furnished to do so, subject to the following conditions:
11
+
12
+ The above copyright notice and this permission notice shall be included in all
13
+ copies or substantial portions of the Software.
14
+
15
+ THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16
+ IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17
+ FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18
+ AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19
+ LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20
+ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21
+ SOFTWARE.
densevid_eval/__init__.py ADDED
File without changes
densevid_eval/convert_to_coco.py ADDED
@@ -0,0 +1,19 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import os
2
+ import json
3
+
4
+ with open("./clevr_data/test_all_captions.json", "r") as f:
5
+ captions = json.load(f)
6
+
7
+ print(captions.keys())
8
+
9
+ coco_res = {"images": [], "annotations": []}
10
+
11
+ caption_id = 0
12
+ for k, v in captions.items():
13
+ coco_res["images"].append({"file_name": k, "id": k})
14
+ for i, caption in enumerate(v):
15
+ coco_res["annotations"].append({"image_id": k, "caption": caption, "id": caption_id})
16
+ caption_id += 1
17
+
18
+ with open("./clevr_data/clevr_total_change_captions_reformat.json", "w") as f:
19
+ json.dump(coco_res, f)
densevid_eval/evaluate.py ADDED
@@ -0,0 +1,304 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # --------------------------------------------------------
2
+ # Dense-Captioning Events in Videos Eval
3
+ # Copyright (c) 2017 Ranjay Krishna
4
+ # Licensed under The MIT License [see LICENSE for details]
5
+ # Written by Ranjay Krishna
6
+ # --------------------------------------------------------
7
+
8
+ import argparse
9
+ import string
10
+ import json
11
+ import sys
12
+ sys.path.insert(0, './coco-caption') # Hack to allow the import of pycocoeval
13
+
14
+ from pycocoevalcap.tokenizer.ptbtokenizer import PTBTokenizer
15
+ from pycocoevalcap.bleu.bleu import Bleu
16
+ from pycocoevalcap.meteor.meteor import Meteor
17
+ from pycocoevalcap.rouge.rouge import Rouge
18
+ from pycocoevalcap.cider.cider import Cider
19
+ from pycocoevalcap.spice.spice import Spice
20
+ from sets import Set
21
+ import numpy as np
22
+
23
+ def remove_nonascii(text):
24
+ return ''.join([i if ord(i) < 128 else ' ' for i in text])
25
+
26
+ class ANETcaptions(object):
27
+ PREDICTION_FIELDS = ['results', 'version', 'external_data']
28
+
29
+ def __init__(self, ground_truth_filenames=None, prediction_filename=None,
30
+ tious=None, max_proposals=1000,
31
+ prediction_fields=PREDICTION_FIELDS, verbose=False):
32
+ # Check that the gt and submission files exist and load them
33
+ if len(tious) == 0:
34
+ raise IOError('Please input a valid tIoU.')
35
+ if not ground_truth_filenames:
36
+ raise IOError('Please input a valid ground truth file.')
37
+ if not prediction_filename:
38
+ raise IOError('Please input a valid prediction file.')
39
+
40
+ self.verbose = verbose
41
+ self.tious = tious
42
+ self.max_proposals = max_proposals
43
+ self.pred_fields = prediction_fields
44
+ self.ground_truths = self.import_ground_truths(ground_truth_filenames)
45
+ self.prediction = self.import_prediction(prediction_filename)
46
+ self.tokenizer = PTBTokenizer()
47
+
48
+ # Set up scorers, if not verbose, we only use the one we're
49
+ # testing on: METEOR
50
+ if self.verbose:
51
+ self.scorers = [
52
+ (Bleu(4), ["Bleu_1", "Bleu_2", "Bleu_3", "Bleu_4"]),
53
+ (Meteor(),"METEOR"),
54
+ (Rouge(), "ROUGE_L"),
55
+ (Cider(), "CIDEr"),
56
+ (Spice(), "SPICE")
57
+ ]
58
+ else:
59
+ self.scorers = [(Meteor(), "METEOR")]
60
+
61
+ def import_prediction(self, prediction_filename):
62
+ if self.verbose:
63
+ print "| Loading submission..."
64
+ submission = json.load(open(prediction_filename))
65
+ if not all([field in submission.keys() for field in self.pred_fields]):
66
+ raise IOError('Please input a valid ground truth file.')
67
+ # Ensure that every video is limited to the correct maximum number of proposals.
68
+ results = {}
69
+ len_captions = 0
70
+ for vid_id in submission['results']:
71
+ results[vid_id] = submission['results'][vid_id][:self.max_proposals]
72
+ len_captions+= len(submission['results'][vid_id][:self.max_proposals])
73
+ print('len of results:', len(results))
74
+ print('len of captions:', len_captions)
75
+ return results
76
+
77
+ def import_ground_truths(self, filenames):
78
+ gts = []
79
+ self.n_ref_vids = Set()
80
+ for filename in filenames:
81
+ gt = json.load(open(filename))
82
+ self.n_ref_vids.update(gt.keys())
83
+ gts.append(gt)
84
+ if self.verbose:
85
+ print "| Loading GT. #files: %d, #videos: %d" % (len(filenames), len(self.n_ref_vids))
86
+ return gts
87
+
88
+ def iou(self, interval_1, interval_2):
89
+ start_i, end_i = interval_1[0], interval_1[1]
90
+ start, end = interval_2[0], interval_2[1]
91
+ intersection = max(0, min(end, end_i) - max(start, start_i))
92
+ union = min(max(end, end_i) - min(start, start_i), end-start + end_i-start_i)
93
+ iou = float(intersection) / (union + 1e-8)
94
+ return iou
95
+
96
+ def check_gt_exists(self, vid_id):
97
+ for gt in self.ground_truths:
98
+ if vid_id in gt:
99
+ return True
100
+ return False
101
+
102
+ def get_gt_vid_ids(self):
103
+ vid_ids = set([])
104
+ for gt in self.ground_truths:
105
+ vid_ids |= set(gt.keys())
106
+ return list(vid_ids)
107
+
108
+ def evaluate(self):
109
+ aggregator = {}
110
+ self.scores = {}
111
+ for tiou in self.tious:
112
+ scores = self.evaluate_tiou(tiou)
113
+ for metric, score in scores.items():
114
+ if metric not in self.scores:
115
+ self.scores[metric] = []
116
+ self.scores[metric].append(score)
117
+ if self.verbose:
118
+ self.scores['Recall'] = []
119
+ self.scores['Precision'] = []
120
+ for tiou in self.tious:
121
+ precision, recall = self.evaluate_detection(tiou)
122
+ self.scores['Recall'].append(recall)
123
+ self.scores['Precision'].append(precision)
124
+
125
+ def evaluate_detection(self, tiou):
126
+ gt_vid_ids = self.get_gt_vid_ids()
127
+ # Recall is the percentage of ground truth that is covered by the predictions
128
+ # Precision is the percentage of predictions that are valid
129
+ recall = [0] * len(gt_vid_ids)
130
+ precision = [0] * len(gt_vid_ids)
131
+ for vid_i, vid_id in enumerate(gt_vid_ids):
132
+ best_recall = 0
133
+ best_precision = 0
134
+ for gt in self.ground_truths:
135
+ if vid_id not in gt:
136
+ continue
137
+ refs = gt[vid_id]
138
+ ref_set_covered = set([])
139
+ pred_set_covered = set([])
140
+ num_gt = 0
141
+ num_pred = 0
142
+ if vid_id in self.prediction:
143
+ for pred_i, pred in enumerate(self.prediction[vid_id]):
144
+ pred_timestamp = pred['timestamp']
145
+ for ref_i, ref_timestamp in enumerate(refs['timestamps']):
146
+ if self.iou(pred_timestamp, ref_timestamp) > tiou:
147
+ ref_set_covered.add(ref_i)
148
+ pred_set_covered.add(pred_i)
149
+
150
+ new_precision = float(len(pred_set_covered)) / (pred_i + 1)
151
+ best_precision = max(best_precision, new_precision)
152
+ new_recall = float(len(ref_set_covered)) / len(refs['timestamps'])
153
+ best_recall = max(best_recall, new_recall)
154
+ recall[vid_i] = best_recall
155
+ precision[vid_i] = best_precision
156
+ return sum(precision) / len(precision), sum(recall) / len(recall)
157
+
158
+ def evaluate_tiou(self, tiou):
159
+ # This method averages the tIoU precision from METEOR, Bleu, etc. across videos
160
+ res = {}
161
+ gts = {}
162
+ gt_vid_ids = self.get_gt_vid_ids()
163
+
164
+ unique_index = 0
165
+
166
+ # video id to unique caption ids mapping
167
+ vid2capid = {}
168
+
169
+ cur_res = {}
170
+ cur_gts = {}
171
+
172
+ for vid_id in gt_vid_ids:
173
+
174
+ vid2capid[vid_id] = []
175
+
176
+ # If the video does not have a prediction, then Vwe give it no matches
177
+ # We set it to empty, and use this as a sanity check later on
178
+ if vid_id not in self.prediction:
179
+ pass
180
+
181
+ # If we do have a prediction, then we find the scores based on all the
182
+ # valid tIoU overlaps
183
+ else:
184
+ # For each prediction, we look at the tIoU with ground truth
185
+ for i,pred in enumerate(self.prediction[vid_id]):
186
+ has_added = False
187
+ for gt in self.ground_truths:
188
+ if vid_id not in gt:
189
+ print('skipped')
190
+ continue
191
+ gt_captions = gt[vid_id]
192
+ for caption_idx, caption_timestamp in enumerate(gt_captions['timestamps']):
193
+ if True or self.iou(pred['timestamp'], caption_timestamp) >= tiou:
194
+ gt_caption = gt_captions['sentences'][i] # for now we use gt proposal
195
+ cur_res[unique_index] = [{'caption': remove_nonascii(pred['sentence'])}]
196
+ cur_gts[unique_index] = [{'caption': remove_nonascii(gt_caption)}] # for now we use gt proposal
197
+ #cur_gts[unique_index] = [{'caption': remove_nonascii(gt_captions['sentences'][caption_idx])}]
198
+ vid2capid[vid_id].append(unique_index)
199
+ unique_index += 1
200
+ has_added = True
201
+ break # for now we use gt proposal
202
+
203
+ # If the predicted caption does not overlap with any ground truth,
204
+ # we should compare it with garbage
205
+ if not has_added:
206
+ cur_res[unique_index] = [{'caption': remove_nonascii(pred['sentence'])}]
207
+ cur_gts[unique_index] = [{'caption': 'abc123!@#'}]
208
+ vid2capid[vid_id].append(unique_index)
209
+ unique_index += 1
210
+
211
+ # Each scorer will compute across all videos and take average score
212
+ output = {}
213
+
214
+ # call tokenizer here for all predictions and gts
215
+ tokenize_res = self.tokenizer.tokenize(cur_res)
216
+ tokenize_gts = self.tokenizer.tokenize(cur_gts)
217
+
218
+ # reshape back
219
+ for vid in vid2capid.keys():
220
+ res[vid] = {index:tokenize_res[index] for index in vid2capid[vid]}
221
+ gts[vid] = {index:tokenize_gts[index] for index in vid2capid[vid]}
222
+
223
+ for scorer, method in self.scorers:
224
+ if self.verbose:
225
+ print 'computing %s score...'%(scorer.method())
226
+
227
+ # For each video, take all the valid pairs (based from tIoU) and compute the score
228
+ all_scores = {}
229
+
230
+ if method == "SPICE": # don't want to compute spice for 10000 times
231
+ print("getting spice score...")
232
+ score, scores = scorer.compute_score(tokenize_gts, tokenize_res)
233
+ all_scores[0] = score
234
+ else:
235
+ for i,vid_id in enumerate(gt_vid_ids):
236
+ if len(res[vid_id]) == 0 or len(gts[vid_id]) == 0:
237
+ if type(method) == list:
238
+ score = [0] * len(method)
239
+ else:
240
+ score = 0
241
+ else:
242
+ score, scores = scorer.compute_score(gts[vid_id], res[vid_id])
243
+ all_scores[vid_id] = score
244
+
245
+ #print all_scores.values()
246
+ if type(method) == list:
247
+ scores = np.mean(all_scores.values(), axis=0)
248
+ for m in xrange(len(method)):
249
+ output[method[m]] = scores[m]
250
+ if self.verbose:
251
+ print "Calculated tIoU: %1.1f, %s: %0.3f" % (tiou, method[m], output[method[m]])
252
+ else:
253
+ output[method] = np.mean(all_scores.values())
254
+ if self.verbose:
255
+ print "Calculated tIoU: %1.1f, %s: %0.3f" % (tiou, method, output[method])
256
+ return output
257
+
258
+ def main(args):
259
+ # Call coco eval
260
+ evaluator = ANETcaptions(ground_truth_filenames=args.references,
261
+ prediction_filename=args.submission,
262
+ tious=args.tious,
263
+ max_proposals=args.max_proposals_per_video,
264
+ verbose=args.verbose)
265
+ evaluator.evaluate()
266
+
267
+ # Output the results
268
+ if args.verbose:
269
+ for i, tiou in enumerate(args.tious):
270
+ print '-' * 80
271
+ print "tIoU: " , tiou
272
+ print '-' * 80
273
+ for metric in evaluator.scores:
274
+ score = evaluator.scores[metric][i]
275
+ print '| %s: %2.4f'%(metric, 100*score)
276
+
277
+ # Print the averages
278
+ print '-' * 80
279
+ print "Average across all tIoUs"
280
+ print '-' * 80
281
+ output = {}
282
+ for metric in evaluator.scores:
283
+ score = evaluator.scores[metric]
284
+ print '| %s: %2.4f'%(metric, 100 * sum(score) / float(len(score)))
285
+ output[metric] = 100 * sum(score) / float(len(score))
286
+ json.dump(output,open(args.output,'w'))
287
+ print(output)
288
+ if __name__=='__main__':
289
+ parser = argparse.ArgumentParser(description='Evaluate the results stored in a submissions file.')
290
+ parser.add_argument('-s', '--submission', type=str, default='sample_submission.json',
291
+ help='sample submission file for ActivityNet Captions Challenge.')
292
+ parser.add_argument('-r', '--references', type=str, nargs='+', default=['data/val_1.json'],
293
+ help='reference files with ground truth captions to compare results against. delimited (,) str')
294
+ parser.add_argument('-o', '--output', type=str, default='result.json',
295
+ help='output file with final language metrics.')
296
+ parser.add_argument('--tious', type=float, nargs='+', default=[0.3],
297
+ help='Choose the tIoUs to average over.')
298
+ parser.add_argument('-ppv', '--max-proposals-per-video', type=int, default=1000,
299
+ help='maximum propoasls per video.')
300
+ parser.add_argument('-v', '--verbose', action='store_true',
301
+ help='Print intermediate steps.')
302
+ args = parser.parse_args()
303
+
304
+ main(args)
densevid_eval/get_caption_stat.py ADDED
@@ -0,0 +1,70 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import json
2
+ import argparse
3
+ import nltk
4
+
5
+
6
+ def save_json_pretty(data, file_path):
7
+ """save formatted json, use this one for some json config files"""
8
+ with open(file_path, "w") as f:
9
+ f.write(json.dumps(data, indent=4, sort_keys=True))
10
+
11
+
12
+ def load_json(file_path):
13
+ with open(file_path, "r") as f:
14
+ return json.load(f)
15
+
16
+
17
+ def flat_list_of_lists(l):
18
+ """flatten a list of lists [[1,2], [3,4]] to [1,2,3,4]"""
19
+ return [item for sublist in l for item in sublist]
20
+
21
+
22
+ def get_args():
23
+ parser = argparse.ArgumentParser()
24
+ parser.add_argument("-s", "--submission", type=str, help="submission file")
25
+ parser.add_argument("-v", "--verbose", action="store_true", help="print info")
26
+ parser.add_argument("-r", "--reference", type=str, help="GT reference, used to collect the video ids")
27
+ parser.add_argument("-o", "--output", type=str, help="save path")
28
+ return parser.parse_args()
29
+
30
+
31
+ def get_sen_stat(list_of_str):
32
+ """list_of_str, list(str), str could be a sentence a paragraph"""
33
+ tokenized = [nltk.tokenize.word_tokenize(sen.lower()) for sen in list_of_str]
34
+ num_sen = len(list_of_str)
35
+ lengths = [len(e) for e in tokenized]
36
+ avg_len = 1.0 * sum(lengths) / len(lengths)
37
+ full_vocab = set(flat_list_of_lists(tokenized))
38
+ return {"vocab_size": len(full_vocab), "avg_sen_len": avg_len, "num_sen": num_sen}
39
+
40
+
41
+ def eval_cap():
42
+ """Get vocab size, average length, etc """
43
+ args = get_args()
44
+
45
+ # load data
46
+ sub_data = json.load(open(args.submission, "r"))
47
+ ref_data = json.load(open(args.reference, "r"))
48
+ sub_data = sub_data["results"] if "results" in sub_data else sub_data
49
+ ref_data = ref_data["results"] if "results" in ref_data else ref_data
50
+ sub_data = {k: v for k, v in sub_data.items() if k in ref_data}
51
+
52
+ submission_data_entries = flat_list_of_lists(sub_data.values())
53
+ submission_sentences = [e["sentence"] for e in submission_data_entries]
54
+ submission_stat = get_sen_stat(submission_sentences)
55
+
56
+ if args.verbose:
57
+ for k in submission_stat:
58
+ print("{} submission {}".format(k, submission_stat[k]))
59
+ final_res = {"submission": submission_stat}
60
+
61
+ if "gt_sentence" in submission_data_entries[0]:
62
+ gt_sentences = [e["gt_sentence"] for e in submission_data_entries]
63
+ gt_stat = get_sen_stat(gt_sentences) # only one reference is used here!!!
64
+ final_res["gt_stat"] = gt_stat
65
+
66
+ save_json_pretty(final_res, args.output)
67
+ return final_res
68
+
69
+ if __name__ == '__main__':
70
+ eval_cap()
densevid_eval/merge_dicts_by_prefix.py ADDED
@@ -0,0 +1,40 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import json
2
+ import glob
3
+ import argparse
4
+
5
+
6
+ def merge_dicts(list_dicts):
7
+ merged_dict = list_dicts[0].copy()
8
+ for i in range(1, len(list_dicts)):
9
+ merged_dict.update(list_dicts[i])
10
+ return merged_dict
11
+
12
+
13
+ def save_json_pretty(data, file_path):
14
+ """save formatted json, use this one for some json config files"""
15
+ with open(file_path, "w") as f:
16
+ f.write(json.dumps(data, indent=4, sort_keys=True))
17
+
18
+
19
+ def load_json(file_path):
20
+ with open(file_path, "r") as f:
21
+ return json.load(f)
22
+
23
+
24
+ def merge_main():
25
+ parser = argparse.ArgumentParser()
26
+ parser.add_argument("-t", "--template", type=str,
27
+ help="path template for glob.glob, all files with the same template will be merged")
28
+ parser.add_argument("-o", "--output", type=str, help="path to the output")
29
+ args = parser.parse_args()
30
+
31
+ print("args.template {}".format(args.template))
32
+ prefix_filepaths = glob.glob(args.template) # list of filepaths
33
+ print("Loading {} files:\n{}".format(len(prefix_filepaths), "\n".join(prefix_filepaths)))
34
+ merged_dict = merge_dicts([load_json(e) for e in prefix_filepaths])
35
+
36
+ save_json_pretty(merged_dict, args.output)
37
+
38
+
39
+ if __name__ == '__main__':
40
+ merge_main()
densevid_eval/para-evaluate.py ADDED
@@ -0,0 +1,211 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # --------------------------------------------------------
2
+ # Dense-Captioning Events in Videos Eval
3
+ # Copyright (c) 2017 Ranjay Krishna
4
+ # Licensed under The MIT License [see LICENSE for details]
5
+ # Written by Ranjay Krishna
6
+ # --------------------------------------------------------
7
+
8
+ import argparse
9
+ import json
10
+ import sys
11
+ import os
12
+
13
+ from pycocoevalcap.tokenizer.ptbtokenizer import PTBTokenizer
14
+ from pycocoevalcap.bleu.bleu import Bleu
15
+ from pycocoevalcap.meteor.meteor import Meteor
16
+ from pycocoevalcap.rouge.rouge import Rouge
17
+ from pycocoevalcap.cider.cider import Cider
18
+ import numpy as np
19
+
20
+ import re
21
+ def parse_sent(sent):
22
+ res = re.sub('[^a-zA-Z]', ' ', sent)
23
+ res = res.strip().lower().split()
24
+ return res
25
+
26
+ def parse_para(para):
27
+ para = para.replace('..', '.')
28
+ para = para.replace('.', ' endofsent')
29
+ return parse_sent(para)
30
+
31
+ class ANETcaptions(object):
32
+
33
+ def __init__(self, ground_truth_filenames=None, prediction_filename=None,
34
+ verbose=False, all_scorer=False):
35
+ # Check that the gt and submission files exist and load them
36
+ if not ground_truth_filenames:
37
+ raise IOError('Please input a valid ground truth file.')
38
+ if not prediction_filename:
39
+ raise IOError('Please input a valid prediction file.')
40
+
41
+ self.verbose = verbose
42
+ self.all_scorer = all_scorer
43
+ self.ground_truths = self.import_ground_truths(ground_truth_filenames)
44
+ self.prediction = self.import_prediction(prediction_filename)
45
+ self.tokenizer = PTBTokenizer()
46
+
47
+ # Set up scorers, if not verbose, we only use the one we're
48
+ # testing on: METEOR
49
+ if self.verbose or self.all_scorer:
50
+ self.scorers = [
51
+ (Bleu(4), ["Bleu_1", "Bleu_2", "Bleu_3", "Bleu_4"]),
52
+ (Meteor(),"METEOR"),
53
+ (Rouge(), "ROUGE_L"),
54
+ (Cider(), "CIDEr")
55
+ ]
56
+ else:
57
+ self.scorers = [(Meteor(), "METEOR")]
58
+
59
+ def ensure_caption_key(self, data):
60
+ if len(data) == 0:
61
+ return data
62
+ if not list(data.keys())[0].startswith('v_'):
63
+ data = {'v_' + k: data[k] for k in data}
64
+ return data
65
+
66
+ def import_prediction(self, prediction_filename):
67
+ if self.verbose:
68
+ print("| Loading submission... {}".format(prediction_filename))
69
+ submission = json.load(open(prediction_filename))['results']
70
+ # change to paragraph format
71
+ para_submission = {}
72
+ for id in submission.keys():
73
+ para_submission[id] = ''
74
+ for info in submission[id]:
75
+ para_submission[id] += info['sentence'] + '. '
76
+ for para in para_submission.values():
77
+ assert(type(para) == str or type(para) == unicode)
78
+ # Ensure that every video is limited to the correct maximum number of proposals.
79
+ return self.ensure_caption_key(para_submission)
80
+
81
+ def import_ground_truths(self, filenames):
82
+ gts = []
83
+ self.n_ref_vids = set()
84
+ for filename in filenames:
85
+ gt = json.load(open(filename))
86
+ self.n_ref_vids.update(gt.keys())
87
+ gts.append(self.ensure_caption_key(gt))
88
+ if self.verbose:
89
+ print("| Loading GT. #files: %d, #videos: %d" % (len(filenames), len(self.n_ref_vids)))
90
+ return gts
91
+
92
+ def check_gt_exists(self, vid_id):
93
+ for gt in self.ground_truths:
94
+ if vid_id in gt:
95
+ return True
96
+ return False
97
+
98
+ def get_gt_vid_ids(self):
99
+ vid_ids = set([])
100
+ for gt in self.ground_truths:
101
+ vid_ids |= set(gt.keys())
102
+ return list(vid_ids)
103
+
104
+ def evaluate(self):
105
+ self.scores = self.evaluate_para()
106
+
107
+ def evaluate_para(self):
108
+ # This method averages the tIoU precision from METEOR, Bleu, etc. across videos
109
+ gt_vid_ids = self.get_gt_vid_ids()
110
+ vid2idx = {k: i for i, k in enumerate(gt_vid_ids)}
111
+ gts = {vid2idx[k]: [] for k in gt_vid_ids}
112
+ for i, gt in enumerate(self.ground_truths):
113
+ for k in gt_vid_ids:
114
+ if k not in gt:
115
+ continue
116
+ # gts[vid2idx[k]].append(' '.join(parse_sent(gt[k])))
117
+ for sent in gt[k]:
118
+ gts[vid2idx[k]].append(' '.join(parse_sent(sent)))
119
+ res = {vid2idx[k]: [' '.join(parse_sent(self.prediction[k]))] \
120
+ if k in self.prediction and len(self.prediction[k]) > 0 else [''] for k in gt_vid_ids}
121
+ para_res = {vid2idx[k]: [' '.join(parse_para(self.prediction[k]))] \
122
+ if k in self.prediction and len(self.prediction[k]) > 0 else [''] for k in gt_vid_ids}
123
+
124
+ # Each scorer will compute across all videos and take average score
125
+ output = {}
126
+ num = len(res)
127
+ hard_samples = {}
128
+ easy_samples = {}
129
+ for scorer, method in self.scorers:
130
+ if self.verbose:
131
+ print('computing %s score...'%(scorer.method()))
132
+
133
+ if method != 'Self_Bleu':
134
+ score, scores = scorer.compute_score(gts, res)
135
+ else:
136
+ score, scores = scorer.compute_score(gts, para_res)
137
+ scores = np.asarray(scores)
138
+
139
+ if type(method) == list:
140
+ for m in range(len(method)):
141
+ output[method[m]] = score[m]
142
+ if self.verbose:
143
+ print("%s: %0.3f" % (method[m], output[method[m]]))
144
+ for m, i in enumerate(scores.argmin(1)):
145
+ if i not in hard_samples:
146
+ hard_samples[i] = []
147
+ hard_samples[i].append(method[m])
148
+ for m, i in enumerate(scores.argmax(1)):
149
+ if i not in easy_samples:
150
+ easy_samples[i] = []
151
+ easy_samples[i].append(method[m])
152
+ else:
153
+ output[method] = score
154
+ if self.verbose:
155
+ print("%s: %0.3f" % (method, output[method]))
156
+ i = scores.argmin()
157
+ if i not in hard_samples:
158
+ hard_samples[i] = []
159
+ hard_samples[i].append(method)
160
+ i = scores.argmax()
161
+ if i not in easy_samples:
162
+ easy_samples[i] = []
163
+ easy_samples[i].append(method)
164
+ print('# scored video =', num)
165
+
166
+ self.hard_samples = {gt_vid_ids[i]: v for i, v in hard_samples.items()}
167
+ self.easy_samples = {gt_vid_ids[i]: v for i, v in easy_samples.items()}
168
+ return output
169
+
170
+ def main(args):
171
+ # Call coco eval
172
+ evaluator = ANETcaptions(ground_truth_filenames=args.references,
173
+ prediction_filename=args.submission,
174
+ verbose=args.verbose,
175
+ all_scorer=args.all_scorer)
176
+ evaluator.evaluate()
177
+ output = {}
178
+ # Output the results
179
+ for metric, score in evaluator.scores.items():
180
+ print('| %s: %2.4f'%(metric, 100*score))
181
+ output[metric] = score
182
+ json.dump(output, open(args.output, 'w'))
183
+ print(output)
184
+
185
+ import time
186
+ if __name__=='__main__':
187
+ parser = argparse.ArgumentParser(description='Evaluate the results stored in a submissions file.')
188
+ parser.add_argument('-s', '--submission', type=str, default='sample_submission.json',
189
+ help='sample submission file for ActivityNet Captions Challenge.')
190
+ parser.add_argument('-r', '--references', type=str, nargs='+', required=True,
191
+ help='reference files with ground truth captions to compare results against. delimited (,) str')
192
+ parser.add_argument('-o', '--output', type=str, default=None, help='output file with final language metrics.')
193
+ parser.add_argument('-v', '--verbose', action='store_true',
194
+ help='Print intermediate steps.')
195
+ parser.add_argument('--time', '--t', action = 'store_true',
196
+ help = 'Count running time.')
197
+ parser.add_argument('--all_scorer', '--a', action = 'store_true',
198
+ help = 'Use all scorer.')
199
+ args = parser.parse_args()
200
+
201
+ if args.output is None:
202
+ r_path = args.submission
203
+ r_path_splits = r_path.split(".")
204
+ r_path_splits = r_path_splits[:-1] + ["_metric", r_path_splits[-1]]
205
+ args.output = ".".join(r_path_splits)
206
+
207
+ if args.time:
208
+ start_time = time.time()
209
+ main(args)
210
+ if args.time:
211
+ print('time = %.2f' % (time.time() - start_time))
edit_best/model.cfg.json ADDED
@@ -0,0 +1,114 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "config": "./config/mmvid_edit_config.yaml",
3
+ "resume": null,
4
+ "save_model": "./results/edit_2025_07_07_08_55_seed42_ema-1_mmvid/model",
5
+ "save_mode": "best",
6
+ "res_root_dir": "./results",
7
+ "debug": false,
8
+ "seed": 42,
9
+ "no_cuda": false,
10
+ "no_pin_memory": true,
11
+ "cuda": true,
12
+ "dalle_param": {
13
+ "vae": {
14
+ "which_vae": "vqgan1024",
15
+ "vae_path": "./pretrained_vqgan/edit_epoch=000050.ckpt",
16
+ "image_size": 224
17
+ },
18
+ "bert": {
19
+ "num_text_tokens": 0,
20
+ "text_seq_len": 24,
21
+ "dim": 768,
22
+ "loss_img_weight": 7,
23
+ "text_feature_dim": 0,
24
+ "fixed_language_model": null,
25
+ "text_emb_bottleneck": null,
26
+ "which_transformer": "openai_clip_visual",
27
+ "num_targets": 4,
28
+ "num_visuals": 0,
29
+ "beit": true,
30
+ "use_separate_visual_emb": false,
31
+ "insert_sep": false,
32
+ "openai_clip_path": "./ckpt/ViT-B-32.pt",
33
+ "vision_layers": 12
34
+ },
35
+ "skip_params": [
36
+ "to_logits_vid.1.bias",
37
+ "to_logits_vid.1.weight",
38
+ "to_logits_vid.0.bias",
39
+ "to_logits_vid.0.weight",
40
+ "to_logits_rel.1.bias",
41
+ "to_logits_rel.1.weight",
42
+ "to_logits_rel.0.bias",
43
+ "to_logits_rel.0.weight",
44
+ "to_logits.1.bias",
45
+ "to_logits.1.weight",
46
+ "to_logits.0.bias",
47
+ "to_logits.0.weight",
48
+ "to_logits_text.1.bias",
49
+ "to_logits_text.1.weight",
50
+ "to_logits_text.0.bias",
51
+ "to_logits_text.0.weight",
52
+ "image_emb.weight"
53
+ ],
54
+ "freeze": false,
55
+ "use_lora": false,
56
+ "lora_config": {
57
+ "r": 8,
58
+ "lora_alpha": 16,
59
+ "lora_dropout": 0.1,
60
+ "bias": "none"
61
+ }
62
+ },
63
+ "decoder_param": {
64
+ "max_n_sen": 12,
65
+ "max_t_len": 24,
66
+ "max_v_len": 4,
67
+ "exp_id": "init",
68
+ "hidden_size": 512,
69
+ "intermediate_size": 2048,
70
+ "num_hidden_layers": 2,
71
+ "num_attention_heads": 8,
72
+ "mask_prob": 0.0,
73
+ "hidden_dropout_prob": 0.1,
74
+ "label_smoothing": 0.1,
75
+ "recurrent": false,
76
+ "untied": false,
77
+ "mtrans": true,
78
+ "use_beam": false,
79
+ "vocab_size": 524,
80
+ "mask_token_id": 7
81
+ },
82
+ "dset_name": "edit",
83
+ "data_dir": "/home/sunjiayang/VFI4IDC_test/IDC_scratch_model/densevid_eval/edit_data",
84
+ "video_feature_dir": "./data/edit/IER_processed",
85
+ "word2idx_path": "./cache/edit_word2idx2.json",
86
+ "glove_path": "./cache/yc2_vocab_glove.pt",
87
+ "eval_tool_dir": "/home/sunjiayang/VFI4IDC_test/IDC_scratch_model/densevid_eval",
88
+ "filtered": true,
89
+ "filter_file_path": "./filter_files/edit_similarity_scores.json",
90
+ "max_k": 5,
91
+ "num_frames": 9,
92
+ "recurrent": false,
93
+ "untied": false,
94
+ "mtrans": true,
95
+ "use_beam": false,
96
+ "image_size": 224,
97
+ "n_epoch": 40,
98
+ "batch_size": 16,
99
+ "val_batch_size": 32,
100
+ "max_es_cnt": 50,
101
+ "lr": 5e-05,
102
+ "lr_finetune": 5e-05,
103
+ "lr_warmup_proportion": 0.1,
104
+ "grad_clip": 1,
105
+ "weight_decay": 0.01,
106
+ "ema_decay": -1,
107
+ "num_workers": 4,
108
+ "temperature": 0.5,
109
+ "metric_reference": "CIDEr",
110
+ "pretrained_model": "./ckpt/img_size224_layer12_edit_wovisual_beit_softmax/dalle.pt",
111
+ "res_dir": "./results/edit_2025_07_07_08_55_seed42_ema-1_mmvid",
112
+ "log": "./results/edit_2025_07_07_08_55_seed42_ema-1_mmvid/model",
113
+ "pin_memory": false
114
+ }
edit_best/model.chkpt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:3062766ac2cb2af3b75e426ec50f7768e6cb32453ae6c1ce1f2c071f90fc8a64
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+ size 1970745522
edit_best/model_best_greedy_pred_val_all_metrics.json ADDED
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+ {
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+ "total_results": {
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+ "Bleu_1": 0.4647026246276841,
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+ "Bleu_2": 0.3235925596450469,
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+ "Bleu_3": 0.19645683528000984,
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+ "Bleu_4": 0.11655278004974493,
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+ "METEOR": 0.1590985553848711,
8
+ "ROUGE_L": 0.43158686120935513,
9
+ "CIDEr": 0.40558600060220157
10
+ }
11
+ }
filter_files/clevr_similarity_scores.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:feabafa5ce69279a1db8763d3c01ddda14317da6aa20f96ccfe1beb897683946
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+ size 189315048
filter_files/edit_similarity_scores.json ADDED
The diff for this file is too large to render. See raw diff
 
filter_files/spot_similarity_scores.json ADDED
The diff for this file is too large to render. See raw diff
 
filtered-spot-captions/filter_test.json ADDED
The diff for this file is too large to render. See raw diff
 
filtered-spot-captions/filter_train.json ADDED
The diff for this file is too large to render. See raw diff
 
spot_best/model.chkpt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:020adc4d56fcc9bbf8865558970a86160c2ead44d58ebd82846c53ce8037a7e0
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+ size 1321505210
stage1_spot_best/log.txt ADDED
@@ -0,0 +1,1007 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Name: train_image_text_4layer_spot_novisual_beit_softmax Time: 2025-07-05 17:06:52.060263
2
+ --------------------------------------------------
3
+ Name: train_image_text_4layer_spot_novisual_beit_softmax Time: 2025-07-05 17:09:48.177979
4
+ --------------------------------------------------
5
+ iter 0000000; MSM 7.0730; REL 1.4800; VID 2.8448; CONST 0.0000; lr 1e-06
6
+ Name: train_image_text_4layer_spot_novisual_beit_softmax Time: 2025-07-05 17:13:42.644630
7
+ --------------------------------------------------
8
+ iter 0000000; MSM 7.0757; REL 1.4800; VID 2.8448; CONST 0.0000; lr 1e-06
9
+ iter 0000200; MSM 4.7919; REL 1.3864; VID 1.3869; CONST 0.0000; lr 6.258524381211508e-05
10
+ iter 0000400; MSM 4.6439; REL 1.3864; VID 2.7761; CONST 0.0000; lr 7.064207302019181e-05
11
+ iter 0000600; MSM 2.7617; REL 1.3869; VID 1.2018; CONST 0.0000; lr 7.535501598163163e-05
12
+ iter 0000800; MSM 2.8117; REL 1.3871; VID 1.2757; CONST 0.0000; lr 7.869890222826853e-05
13
+ iter 0001000; MSM 0.4446; REL 1.3863; VID 1.4332; CONST 0.0000; lr 8.129262190605753e-05
14
+ iter 0001200; MSM 1.4418; REL 1.3863; VID 1.4829; CONST 0.0000; lr 8.341184518970836e-05
15
+ iter 0001400; MSM 1.3585; REL 1.3866; VID 1.9270; CONST 0.0000; lr 8.520362294558676e-05
16
+ iter 0001600; MSM 0.9381; REL 1.3865; VID 1.1143; CONST 0.0000; lr 8.675573143634527e-05
17
+ iter 0001800; MSM 0.3504; REL 1.3866; VID 0.8501; CONST 0.0000; lr 8.812478815114817e-05
18
+ iter 0002000; MSM 2.7011; REL 1.3820; VID 2.2949; CONST 0.0000; lr 8.934945111413428e-05
19
+ iter 0002200; MSM 1.0522; REL 1.4052; VID 3.1450; CONST 0.0000; lr 9.045729352049622e-05
20
+ iter 0002400; MSM 0.3224; REL 1.0380; VID 0.8708; CONST 0.0000; lr 9.146867439778508e-05
21
+ iter 0002600; MSM 1.4655; REL 2.2905; VID 1.3866; CONST 0.0000; lr 9.239905461596146e-05
22
+ iter 0002800; MSM 1.3275; REL 1.2480; VID 1.0370; CONST 0.0000; lr 9.326045215366348e-05
23
+ iter 0003000; MSM 0.9741; REL 1.0739; VID 2.3977; CONST 0.0000; lr 9.406239407557407e-05
24
+ iter 0003200; MSM 0.6732; REL 0.9766; VID 1.3614; CONST 0.0000; lr 9.4812560644422e-05
25
+ iter 0003400; MSM 0.6303; REL 0.8554; VID 0.5234; CONST 0.0000; lr 9.551723381842911e-05
26
+ iter 0003600; MSM 0.3827; REL 1.1000; VID 1.4225; CONST 0.0000; lr 9.61816173592249e-05
27
+ iter 0003800; MSM 0.2617; REL 1.4248; VID 0.4668; CONST 0.0000; lr 9.681007027622012e-05
28
+ iter 0004000; MSM 0.7107; REL 0.7835; VID 0.9838; CONST 0.0000; lr 9.7406280322211e-05
29
+ iter 0004200; MSM 0.2569; REL 0.3413; VID 1.0890; CONST 0.0000; lr 9.797339511510329e-05
30
+ iter 0004400; MSM 0.3244; REL 1.3934; VID 1.3817; CONST 0.0000; lr 9.851412272857295e-05
31
+ iter 0004600; MSM 0.6503; REL 0.1564; VID 3.7332; CONST 0.0000; lr 9.903080990421993e-05
32
+ iter 0004800; MSM 1.8135; REL 1.8582; VID 2.8121; CONST 0.0000; lr 9.952550360586183e-05
33
+ iter 0005000; MSM 1.1037; REL 1.6146; VID 0.9576; CONST 0.0000; lr 0.0001
34
+ iter 0005200; MSM 0.3554; REL 1.7847; VID 0.7454; CONST 0.0000; lr 0.0001
35
+ iter 0005400; MSM 0.3313; REL 0.3185; VID 0.8664; CONST 0.0000; lr 0.0001
36
+ iter 0005600; MSM 0.2058; REL 0.5306; VID 0.6826; CONST 0.0000; lr 0.0001
37
+ iter 0005800; MSM 1.0962; REL 1.6637; VID 1.7308; CONST 0.0000; lr 0.0001
38
+ iter 0006000; MSM 0.2766; REL 0.6253; VID 0.9339; CONST 0.0000; lr 0.0001
39
+ iter 0006200; MSM 0.6157; REL 2.1663; VID 0.8669; CONST 0.0000; lr 0.0001
40
+ iter 0006400; MSM 1.2666; REL 1.0583; VID 1.1395; CONST 0.0000; lr 0.0001
41
+ iter 0006600; MSM 0.6589; REL 1.0784; VID 0.3453; CONST 0.0000; lr 0.0001
42
+ iter 0006800; MSM 1.0229; REL 3.6412; VID 3.8820; CONST 0.0000; lr 0.0001
43
+ iter 0007000; MSM 0.2894; REL 1.0493; VID 0.2894; CONST 0.0000; lr 0.0001
44
+ iter 0007200; MSM 0.4485; REL 1.5747; VID 1.7021; CONST 0.0000; lr 0.0001
45
+ iter 0007400; MSM 0.5064; REL 0.3376; VID 0.6103; CONST 0.0000; lr 0.0001
46
+ iter 0007600; MSM 1.3031; REL 0.4443; VID 1.7458; CONST 0.0000; lr 0.0001
47
+ iter 0007800; MSM 0.5332; REL 0.2147; VID 0.9363; CONST 0.0000; lr 0.0001
48
+ iter 0008000; MSM 0.2202; REL 0.4927; VID 0.9525; CONST 0.0000; lr 0.0001
49
+ iter 0008200; MSM 2.4804; REL 1.6103; VID 2.6614; CONST 0.0000; lr 0.0001
50
+ iter 0008400; MSM 0.3719; REL 0.9540; VID 1.2691; CONST 0.0000; lr 0.0001
51
+ iter 0008600; MSM 0.6137; REL 1.0957; VID 0.5131; CONST 0.0000; lr 0.0001
52
+ iter 0008800; MSM 0.4576; REL 1.0892; VID 0.3289; CONST 0.0000; lr 0.0001
53
+ iter 0009000; MSM 0.8317; REL 1.1622; VID 0.9327; CONST 0.0000; lr 0.0001
54
+ iter 0009200; MSM 2.4190; REL 1.7703; VID 2.8440; CONST 0.0000; lr 0.0001
55
+ iter 0009400; MSM 0.8552; REL 0.5874; VID 1.7203; CONST 0.0000; lr 0.0001
56
+ iter 0009600; MSM 0.2766; REL 1.6716; VID 0.9973; CONST 0.0000; lr 0.0001
57
+ iter 0009800; MSM 0.5350; REL 0.5707; VID 0.4255; CONST 0.0000; lr 0.0001
58
+ iter 0010000; MSM 0.1899; REL 0.2301; VID 1.4898; CONST 0.0000; lr 0.0001
59
+ iter 0010200; MSM 0.2483; REL 0.8169; VID 1.5314; CONST 0.0000; lr 0.0001
60
+ iter 0010400; MSM 0.8956; REL 0.0000; VID 2.7740; CONST 0.0000; lr 0.0001
61
+ iter 0010600; MSM 0.3726; REL 0.8434; VID 0.4145; CONST 0.0000; lr 0.0001
62
+ iter 0010800; MSM 0.4895; REL 0.8228; VID 0.4207; CONST 0.0000; lr 0.0001
63
+ iter 0011000; MSM 0.4797; REL 1.0054; VID 0.4407; CONST 0.0000; lr 0.0001
64
+ iter 0011200; MSM 0.2132; REL 0.0983; VID 0.9128; CONST 0.0000; lr 0.0001
65
+ iter 0011400; MSM 0.2876; REL 1.0793; VID 0.9140; CONST 0.0000; lr 0.0001
66
+ iter 0011600; MSM 2.9885; REL 0.6229; VID 2.2220; CONST 0.0000; lr 0.0001
67
+ iter 0011800; MSM 0.2088; REL 0.2241; VID 0.3234; CONST 0.0000; lr 0.0001
68
+ iter 0012000; MSM 0.3776; REL 0.5590; VID 0.7056; CONST 0.0000; lr 0.0001
69
+ iter 0012200; MSM 0.3856; REL 1.9053; VID 0.6509; CONST 0.0000; lr 0.0001
70
+ iter 0012400; MSM 0.1166; REL 2.3510; VID 1.4147; CONST 0.0000; lr 0.0001
71
+ iter 0012600; MSM 0.3117; REL 0.2127; VID 0.8640; CONST 0.0000; lr 0.0001
72
+ iter 0012800; MSM 2.3298; REL 3.9129; VID 1.8764; CONST 0.0000; lr 0.0001
73
+ iter 0013000; MSM 0.1975; REL 0.9485; VID 1.0797; CONST 0.0000; lr 0.0001
74
+ iter 0013200; MSM 0.2000; REL 1.8044; VID 3.0530; CONST 0.0000; lr 0.0001
75
+ iter 0013400; MSM 0.2540; REL 0.7120; VID 0.5403; CONST 0.0000; lr 0.0001
76
+ iter 0013600; MSM 0.2135; REL 0.1636; VID 1.6278; CONST 0.0000; lr 0.0001
77
+ iter 0013800; MSM 0.3446; REL 1.2313; VID 0.5073; CONST 0.0000; lr 0.0001
78
+ iter 0014000; MSM 0.3298; REL 1.3379; VID 0.9271; CONST 0.0000; lr 0.0001
79
+ iter 0014200; MSM 0.2288; REL 1.3080; VID 0.8094; CONST 0.0000; lr 0.0001
80
+ iter 0014400; MSM 0.4463; REL 0.3531; VID 0.9008; CONST 0.0000; lr 0.0001
81
+ iter 0014600; MSM 0.3779; REL 0.3339; VID 1.3171; CONST 0.0000; lr 0.0001
82
+ iter 0014800; MSM 1.0337; REL 0.3407; VID 1.6345; CONST 0.0000; lr 0.0001
83
+ iter 0015000; MSM 0.3770; REL 0.4420; VID 0.3488; CONST 0.0000; lr 0.0001
84
+ iter 0015200; MSM 0.2443; REL 0.7286; VID 0.9572; CONST 0.0000; lr 0.0001
85
+ iter 0015400; MSM 0.2940; REL 0.8966; VID 0.3009; CONST 0.0000; lr 0.0001
86
+ iter 0015600; MSM 0.4583; REL 0.1569; VID 1.5456; CONST 0.0000; lr 0.0001
87
+ iter 0015800; MSM 0.4134; REL 0.6012; VID 1.4440; CONST 0.0000; lr 0.0001
88
+ iter 0016000; MSM 0.4663; REL 1.5631; VID 1.4455; CONST 0.0000; lr 0.0001
89
+ iter 0016200; MSM 0.2149; REL 1.7674; VID 0.4534; CONST 0.0000; lr 0.0001
90
+ iter 0016400; MSM 0.1929; REL 1.7164; VID 0.7870; CONST 0.0000; lr 0.0001
91
+ iter 0016600; MSM 0.1500; REL 1.9928; VID 1.5772; CONST 0.0000; lr 0.0001
92
+ iter 0016800; MSM 0.2135; REL 0.2991; VID 0.3275; CONST 0.0000; lr 0.0001
93
+ iter 0017000; MSM 0.3169; REL 1.0706; VID 0.6995; CONST 0.0000; lr 0.0001
94
+ iter 0017200; MSM 0.2815; REL 0.2055; VID 1.0044; CONST 0.0000; lr 0.0001
95
+ iter 0017400; MSM 0.3545; REL 0.3181; VID 0.2980; CONST 0.0000; lr 0.0001
96
+ iter 0017600; MSM 0.2859; REL 0.0989; VID 0.9992; CONST 0.0000; lr 0.0001
97
+ iter 0017800; MSM 0.9475; REL 0.1905; VID 1.6072; CONST 0.0000; lr 0.0001
98
+ iter 0018000; MSM 0.3241; REL 0.6478; VID 0.2976; CONST 0.0000; lr 0.0001
99
+ iter 0018200; MSM 0.6847; REL 0.4397; VID 0.2075; CONST 0.0000; lr 0.0001
100
+ iter 0018400; MSM 2.4486; REL 0.3789; VID 3.0943; CONST 0.0000; lr 0.0001
101
+ iter 0018600; MSM 0.2235; REL 0.6783; VID 1.0172; CONST 0.0000; lr 0.0001
102
+ iter 0018800; MSM 1.9115; REL 0.0000; VID 2.8250; CONST 0.0000; lr 0.0001
103
+ iter 0019000; MSM 0.2144; REL 1.9256; VID 0.3589; CONST 0.0000; lr 0.0001
104
+ iter 0019200; MSM 0.2384; REL 1.0311; VID 0.9828; CONST 0.0000; lr 0.0001
105
+ iter 0019400; MSM 0.4263; REL 0.6469; VID 0.5428; CONST 0.0000; lr 0.0001
106
+ iter 0019600; MSM 1.1722; REL 0.5901; VID 2.8788; CONST 0.0000; lr 0.0001
107
+ iter 0019800; MSM 0.2699; REL 0.2980; VID 0.4833; CONST 0.0000; lr 0.0001
108
+ iter 0020000; MSM 0.2520; REL 0.6872; VID 0.3875; CONST 0.0000; lr 0.0001
109
+ iter 0020200; MSM 0.3237; REL 0.0843; VID 0.5529; CONST 0.0000; lr 0.0001
110
+ iter 0020400; MSM 0.5807; REL 0.3822; VID 1.0104; CONST 0.0000; lr 0.0001
111
+ iter 0020600; MSM 0.2252; REL 2.0080; VID 0.8988; CONST 0.0000; lr 0.0001
112
+ iter 0020800; MSM 0.2260; REL 2.1123; VID 0.8389; CONST 0.0000; lr 0.0001
113
+ iter 0021000; MSM 0.2632; REL 0.2790; VID 3.2646; CONST 0.0000; lr 0.0001
114
+ iter 0021200; MSM 0.2097; REL 0.9169; VID 0.4345; CONST 0.0000; lr 0.0001
115
+ iter 0021400; MSM 0.4724; REL 0.5627; VID 1.0635; CONST 0.0000; lr 0.0001
116
+ iter 0021600; MSM 0.2035; REL 0.5681; VID 1.1287; CONST 0.0000; lr 0.0001
117
+ iter 0021800; MSM 0.2310; REL 2.3132; VID 0.3801; CONST 0.0000; lr 0.0001
118
+ iter 0022000; MSM 0.7849; REL 2.0101; VID 0.5182; CONST 0.0000; lr 0.0001
119
+ iter 0022200; MSM 0.2900; REL 0.6502; VID 1.1098; CONST 0.0000; lr 0.0001
120
+ iter 0022400; MSM 0.1469; REL 0.7023; VID 0.9765; CONST 0.0000; lr 0.0001
121
+ iter 0022600; MSM 2.0483; REL 0.8741; VID 2.9738; CONST 0.0000; lr 0.0001
122
+ iter 0022800; MSM 0.6756; REL 0.5077; VID 1.0173; CONST 0.0000; lr 0.0001
123
+ iter 0023000; MSM 0.3537; REL 0.8035; VID 1.0680; CONST 0.0000; lr 0.0001
124
+ iter 0023200; MSM 0.4817; REL 1.6575; VID 1.2945; CONST 0.0000; lr 0.0001
125
+ iter 0023400; MSM 0.1260; REL 0.2181; VID 0.3230; CONST 0.0000; lr 0.0001
126
+ iter 0023600; MSM 0.5853; REL 0.5854; VID 0.9243; CONST 0.0000; lr 0.0001
127
+ iter 0023800; MSM 0.2148; REL 1.1743; VID 0.2236; CONST 0.0000; lr 0.0001
128
+ iter 0024000; MSM 0.1482; REL 1.6082; VID 1.0063; CONST 0.0000; lr 0.0001
129
+ iter 0024200; MSM 0.4739; REL 0.7397; VID 1.3144; CONST 0.0000; lr 0.0001
130
+ iter 0024400; MSM 0.6448; REL 1.3809; VID 0.9448; CONST 0.0000; lr 0.0001
131
+ iter 0024600; MSM 1.1193; REL 0.0000; VID 2.7761; CONST 0.0000; lr 0.0001
132
+ iter 0024800; MSM 0.6300; REL 0.5439; VID 0.9948; CONST 0.0000; lr 0.0001
133
+ iter 0025000; MSM 0.2843; REL 0.2302; VID 0.7646; CONST 0.0000; lr 0.0001
134
+ iter 0025200; MSM 0.3149; REL 0.8952; VID 1.0985; CONST 0.0000; lr 0.0001
135
+ iter 0025400; MSM 0.3048; REL 1.6427; VID 1.5607; CONST 0.0000; lr 0.0001
136
+ iter 0025600; MSM 0.5708; REL 0.2974; VID 1.6238; CONST 0.0000; lr 0.0001
137
+ iter 0025800; MSM 0.2794; REL 0.1766; VID 0.2592; CONST 0.0000; lr 0.0001
138
+ iter 0026000; MSM 0.2837; REL 0.9592; VID 0.9325; CONST 0.0000; lr 0.0001
139
+ iter 0026200; MSM 0.3282; REL 0.6374; VID 0.7388; CONST 0.0000; lr 0.0001
140
+ iter 0026400; MSM 2.0561; REL 2.4098; VID 1.6629; CONST 0.0000; lr 0.0001
141
+ iter 0026600; MSM 0.5074; REL 1.6541; VID 0.2501; CONST 0.0000; lr 0.0001
142
+ iter 0026800; MSM 1.8140; REL 1.1230; VID 2.8734; CONST 0.0000; lr 0.0001
143
+ iter 0027000; MSM 0.2153; REL 0.4860; VID 0.6740; CONST 0.0000; lr 0.0001
144
+ iter 0027200; MSM 0.3578; REL 0.9660; VID 1.2618; CONST 0.0000; lr 0.0001
145
+ iter 0027400; MSM 0.4565; REL 0.0700; VID 0.5977; CONST 0.0000; lr 0.0001
146
+ iter 0027600; MSM 2.0818; REL 0.8742; VID 1.6976; CONST 0.0000; lr 0.0001
147
+ iter 0027800; MSM 0.2175; REL 0.0672; VID 0.3340; CONST 0.0000; lr 0.0001
148
+ iter 0028000; MSM 0.2710; REL 0.2936; VID 0.9741; CONST 0.0000; lr 0.0001
149
+ iter 0028200; MSM 0.1594; REL 0.1652; VID 0.9551; CONST 0.0000; lr 0.0001
150
+ iter 0028400; MSM 0.8783; REL 1.0196; VID 1.8466; CONST 0.0000; lr 0.0001
151
+ iter 0028600; MSM 0.3330; REL 0.3634; VID 0.5030; CONST 0.0000; lr 0.0001
152
+ iter 0028800; MSM 0.3025; REL 0.2050; VID 0.2730; CONST 0.0000; lr 0.0001
153
+ iter 0029000; MSM 0.2212; REL 0.2095; VID 1.0778; CONST 0.0000; lr 0.0001
154
+ iter 0029200; MSM 0.6297; REL 0.3338; VID 1.4930; CONST 0.0000; lr 0.0001
155
+ iter 0029400; MSM 1.0917; REL 1.1364; VID 1.6394; CONST 0.0000; lr 0.0001
156
+ iter 0029600; MSM 0.3731; REL 0.2116; VID 0.5634; CONST 0.0000; lr 0.0001
157
+ iter 0029800; MSM 0.3331; REL 2.1349; VID 0.6663; CONST 0.0000; lr 0.0001
158
+ iter 0030000; MSM 0.6178; REL 1.4554; VID 0.8163; CONST 0.0000; lr 0.0001
159
+ iter 0030200; MSM 0.3069; REL 0.2612; VID 0.9159; CONST 0.0000; lr 0.0001
160
+ iter 0030400; MSM 0.2265; REL 0.2654; VID 0.7697; CONST 0.0000; lr 0.0001
161
+ iter 0030600; MSM 0.2109; REL 0.6389; VID 0.8434; CONST 0.0000; lr 0.0001
162
+ iter 0030800; MSM 0.2306; REL 0.1347; VID 1.0749; CONST 0.0000; lr 0.0001
163
+ iter 0031000; MSM 0.2399; REL 0.1131; VID 1.7893; CONST 0.0000; lr 0.0001
164
+ iter 0031200; MSM 0.5107; REL 0.1130; VID 0.7939; CONST 0.0000; lr 0.0001
165
+ iter 0031400; MSM 0.3441; REL 0.8955; VID 0.3252; CONST 0.0000; lr 0.0001
166
+ iter 0031600; MSM 1.1189; REL 1.2925; VID 1.6127; CONST 0.0000; lr 0.0001
167
+ iter 0031800; MSM 0.2982; REL 0.7791; VID 0.9954; CONST 0.0000; lr 0.0001
168
+ iter 0032000; MSM 2.1692; REL 0.3525; VID 2.1896; CONST 0.0000; lr 0.0001
169
+ iter 0032200; MSM 0.1245; REL 0.8456; VID 1.0500; CONST 0.0000; lr 0.0001
170
+ iter 0032400; MSM 0.0998; REL 0.2649; VID 0.2901; CONST 0.0000; lr 0.0001
171
+ iter 0032600; MSM 0.2850; REL 0.2154; VID 1.0254; CONST 0.0000; lr 0.0001
172
+ iter 0032800; MSM 0.2877; REL 1.9792; VID 1.1796; CONST 0.0000; lr 0.0001
173
+ iter 0033000; MSM 0.8585; REL 0.8982; VID 1.5561; CONST 0.0000; lr 0.0001
174
+ iter 0033200; MSM 0.4718; REL 0.1400; VID 0.2913; CONST 0.0000; lr 0.0001
175
+ iter 0033400; MSM 0.3997; REL 0.5137; VID 0.9151; CONST 0.0000; lr 0.0001
176
+ iter 0033600; MSM 0.1043; REL 0.4395; VID 0.4546; CONST 0.0000; lr 0.0001
177
+ iter 0033800; MSM 0.3710; REL 1.8411; VID 1.4668; CONST 0.0000; lr 0.0001
178
+ iter 0034000; MSM 0.4416; REL 1.0474; VID 1.5934; CONST 0.0000; lr 0.0001
179
+ iter 0034200; MSM 0.4298; REL 0.2680; VID 0.3962; CONST 0.0000; lr 0.0001
180
+ iter 0034400; MSM 0.1245; REL 1.3203; VID 0.1845; CONST 0.0000; lr 0.0001
181
+ iter 0034600; MSM 0.1764; REL 0.1697; VID 0.8702; CONST 0.0000; lr 0.0001
182
+ iter 0034800; MSM 0.3926; REL 0.5636; VID 1.2856; CONST 0.0000; lr 0.0001
183
+ iter 0035000; MSM 0.2018; REL 0.1563; VID 0.5392; CONST 0.0000; lr 0.0001
184
+ iter 0035200; MSM 0.2156; REL 0.8723; VID 1.4545; CONST 0.0000; lr 0.0001
185
+ iter 0035400; MSM 0.2920; REL 0.1380; VID 1.6641; CONST 0.0000; lr 0.0001
186
+ iter 0035600; MSM 2.0885; REL 0.0000; VID 2.7761; CONST 0.0000; lr 0.0001
187
+ iter 0035800; MSM 0.2602; REL 0.0708; VID 1.1498; CONST 0.0000; lr 0.0001
188
+ iter 0036000; MSM 0.1616; REL 0.1360; VID 0.2327; CONST 0.0000; lr 0.0001
189
+ iter 0036200; MSM 1.0899; REL 0.2818; VID 1.8223; CONST 0.0000; lr 0.0001
190
+ iter 0036400; MSM 0.1014; REL 2.0884; VID 0.9522; CONST 0.0000; lr 0.0001
191
+ iter 0036600; MSM 0.3058; REL 0.0886; VID 1.1741; CONST 0.0000; lr 0.0001
192
+ iter 0036800; MSM 0.3641; REL 0.0965; VID 1.8257; CONST 0.0000; lr 0.0001
193
+ iter 0037000; MSM 0.1786; REL 0.0468; VID 0.6969; CONST 0.0000; lr 0.0001
194
+ iter 0037200; MSM 0.1166; REL 0.0847; VID 0.2963; CONST 0.0000; lr 0.0001
195
+ iter 0037400; MSM 0.0970; REL 1.0098; VID 1.2836; CONST 0.0000; lr 0.0001
196
+ iter 0037600; MSM 0.1757; REL 1.2895; VID 0.7466; CONST 0.0000; lr 0.0001
197
+ iter 0037800; MSM 1.3240; REL 0.1697; VID 1.8783; CONST 0.0000; lr 0.0001
198
+ iter 0038000; MSM 0.2008; REL 0.0711; VID 0.4620; CONST 0.0000; lr 0.0001
199
+ iter 0038200; MSM 0.2117; REL 0.0383; VID 0.9631; CONST 0.0000; lr 0.0001
200
+ iter 0038400; MSM 0.6702; REL 1.1070; VID 1.0502; CONST 0.0000; lr 0.0001
201
+ iter 0038600; MSM 0.1663; REL 0.2700; VID 0.3322; CONST 0.0000; lr 0.0001
202
+ iter 0038800; MSM 0.3163; REL 0.0537; VID 1.9460; CONST 0.0000; lr 0.0001
203
+ iter 0039000; MSM 0.3771; REL 0.0825; VID 0.2488; CONST 0.0000; lr 0.0001
204
+ iter 0039200; MSM 0.1047; REL 1.1368; VID 0.3072; CONST 0.0000; lr 0.0001
205
+ iter 0039400; MSM 0.2024; REL 0.1401; VID 0.2925; CONST 0.0000; lr 0.0001
206
+ iter 0039600; MSM 0.4978; REL 0.2796; VID 0.1993; CONST 0.0000; lr 0.0001
207
+ iter 0039800; MSM 0.4164; REL 0.2482; VID 0.9372; CONST 0.0000; lr 0.0001
208
+ iter 0040000; MSM 0.2964; REL 0.1792; VID 0.3884; CONST 0.0000; lr 0.0001
209
+ iter 0040200; MSM 0.3335; REL 1.1086; VID 0.3755; CONST 0.0000; lr 0.0001
210
+ iter 0040400; MSM 0.1613; REL 1.7044; VID 0.9992; CONST 0.0000; lr 0.0001
211
+ iter 0040600; MSM 0.2170; REL 0.1091; VID 0.2677; CONST 0.0000; lr 0.0001
212
+ iter 0040800; MSM 0.5294; REL 0.0804; VID 1.7153; CONST 0.0000; lr 0.0001
213
+ iter 0041000; MSM 0.1491; REL 0.1947; VID 0.1855; CONST 0.0000; lr 0.0001
214
+ iter 0041200; MSM 0.3730; REL 0.0837; VID 0.6405; CONST 0.0000; lr 0.0001
215
+ iter 0041400; MSM 0.2375; REL 0.7878; VID 0.8974; CONST 0.0000; lr 0.0001
216
+ iter 0041600; MSM 0.1338; REL 0.8492; VID 1.1418; CONST 0.0000; lr 0.0001
217
+ iter 0041800; MSM 0.5818; REL 0.0709; VID 0.9931; CONST 0.0000; lr 0.0001
218
+ iter 0042000; MSM 0.3204; REL 0.1150; VID 0.2943; CONST 0.0000; lr 0.0001
219
+ iter 0042200; MSM 0.3045; REL 0.4012; VID 0.3916; CONST 0.0000; lr 0.0001
220
+ iter 0042400; MSM 0.2084; REL 0.2145; VID 1.5859; CONST 0.0000; lr 0.0001
221
+ iter 0042600; MSM 0.4936; REL 0.3377; VID 1.1153; CONST 0.0000; lr 0.0001
222
+ iter 0042800; MSM 0.3661; REL 0.3209; VID 1.4593; CONST 0.0000; lr 0.0001
223
+ iter 0043000; MSM 0.1173; REL 0.8237; VID 0.3957; CONST 0.0000; lr 0.0001
224
+ iter 0043200; MSM 0.1545; REL 2.2155; VID 0.8706; CONST 0.0000; lr 0.0001
225
+ iter 0043400; MSM 0.6946; REL 0.2137; VID 1.6675; CONST 0.0000; lr 0.0001
226
+ iter 0043600; MSM 2.3268; REL 0.0310; VID 1.6265; CONST 0.0000; lr 0.0001
227
+ iter 0043800; MSM 0.2751; REL 0.1512; VID 0.5811; CONST 0.0000; lr 0.0001
228
+ iter 0044000; MSM 0.3523; REL 0.1600; VID 1.9177; CONST 0.0000; lr 0.0001
229
+ iter 0044200; MSM 0.2154; REL 0.1211; VID 1.7617; CONST 0.0000; lr 0.0001
230
+ iter 0044400; MSM 0.4151; REL 0.3375; VID 0.9726; CONST 0.0000; lr 0.0001
231
+ iter 0044600; MSM 0.1969; REL 0.0394; VID 0.6435; CONST 0.0000; lr 0.0001
232
+ iter 0044800; MSM 0.5615; REL 0.0567; VID 1.6656; CONST 0.0000; lr 0.0001
233
+ iter 0045000; MSM 0.2290; REL 0.1270; VID 1.5453; CONST 0.0000; lr 0.0001
234
+ iter 0045200; MSM 0.3737; REL 0.2420; VID 1.5312; CONST 0.0000; lr 0.0001
235
+ iter 0045400; MSM 0.5837; REL 0.1842; VID 1.1838; CONST 0.0000; lr 0.0001
236
+ iter 0045600; MSM 0.1932; REL 0.1102; VID 0.2399; CONST 0.0000; lr 0.0001
237
+ iter 0045800; MSM 0.1535; REL 0.2558; VID 0.1229; CONST 0.0000; lr 0.0001
238
+ iter 0046000; MSM 0.3849; REL 0.1034; VID 0.2137; CONST 0.0000; lr 0.0001
239
+ iter 0046200; MSM 1.6337; REL 0.1054; VID 1.5380; CONST 0.0000; lr 0.0001
240
+ iter 0046400; MSM 1.8598; REL 3.9875; VID 1.4863; CONST 0.0000; lr 0.0001
241
+ iter 0046600; MSM 0.1342; REL 2.3059; VID 0.2146; CONST 0.0000; lr 0.0001
242
+ iter 0046800; MSM 0.1964; REL 0.6942; VID 0.3521; CONST 0.0000; lr 0.0001
243
+ iter 0047000; MSM 0.4918; REL 0.4390; VID 1.0087; CONST 0.0000; lr 0.0001
244
+ iter 0047200; MSM 0.2874; REL 1.4248; VID 0.1797; CONST 0.0000; lr 0.0001
245
+ iter 0047400; MSM 0.2045; REL 2.4232; VID 1.2766; CONST 0.0000; lr 0.0001
246
+ iter 0047600; MSM 0.2747; REL 0.1146; VID 0.3473; CONST 0.0000; lr 0.0001
247
+ iter 0047800; MSM 0.1346; REL 0.1010; VID 0.1437; CONST 0.0000; lr 0.0001
248
+ iter 0048000; MSM 0.5086; REL 0.0884; VID 1.3990; CONST 0.0000; lr 0.0001
249
+ iter 0048200; MSM 0.2988; REL 0.0930; VID 1.3904; CONST 0.0000; lr 0.0001
250
+ iter 0048400; MSM 0.3792; REL 0.1110; VID 1.0042; CONST 0.0000; lr 0.0001
251
+ iter 0048600; MSM 0.1660; REL 0.0523; VID 1.1858; CONST 0.0000; lr 0.0001
252
+ iter 0048800; MSM 0.1302; REL 0.0924; VID 0.2201; CONST 0.0000; lr 0.0001
253
+ iter 0049000; MSM 0.1310; REL 0.2289; VID 0.2615; CONST 0.0000; lr 0.0001
254
+ iter 0049200; MSM 0.4556; REL 0.0352; VID 2.9775; CONST 0.0000; lr 0.0001
255
+ iter 0049400; MSM 0.0834; REL 1.3691; VID 0.0998; CONST 0.0000; lr 0.0001
256
+ iter 0049600; MSM 0.3564; REL 0.1547; VID 1.1860; CONST 0.0000; lr 0.0001
257
+ iter 0049800; MSM 0.3634; REL 0.2633; VID 2.8900; CONST 0.0000; lr 0.0001
258
+ iter 0050000; MSM 0.4595; REL 0.0350; VID 1.1908; CONST 0.0000; lr 0.0001
259
+ iter 0050200; MSM 0.2407; REL 0.2518; VID 0.8214; CONST 0.0000; lr 0.0001
260
+ iter 0050400; MSM 0.4157; REL 0.1018; VID 0.5101; CONST 0.0000; lr 0.0001
261
+ iter 0050600; MSM 0.5158; REL 0.0474; VID 0.4313; CONST 0.0000; lr 0.0001
262
+ iter 0050800; MSM 0.2283; REL 0.1867; VID 0.8181; CONST 0.0000; lr 0.0001
263
+ iter 0051000; MSM 0.1125; REL 0.0825; VID 1.7602; CONST 0.0000; lr 0.0001
264
+ iter 0051200; MSM 0.2395; REL 0.0514; VID 1.1012; CONST 0.0000; lr 0.0001
265
+ iter 0051400; MSM 0.1685; REL 0.1136; VID 0.7468; CONST 0.0000; lr 0.0001
266
+ iter 0051600; MSM 0.3284; REL 0.0547; VID 0.8058; CONST 0.0000; lr 0.0001
267
+ iter 0051800; MSM 0.2528; REL 0.0291; VID 0.3037; CONST 0.0000; lr 0.0001
268
+ iter 0052000; MSM 0.2270; REL 0.1106; VID 0.7876; CONST 0.0000; lr 0.0001
269
+ iter 0052200; MSM 0.1518; REL 0.1157; VID 0.8686; CONST 0.0000; lr 0.0001
270
+ iter 0052400; MSM 0.8709; REL 0.0553; VID 1.5737; CONST 0.0000; lr 0.0001
271
+ iter 0052600; MSM 0.4361; REL 0.7190; VID 1.5912; CONST 0.0000; lr 0.0001
272
+ iter 0052800; MSM 0.2629; REL 0.0838; VID 0.1777; CONST 0.0000; lr 0.0001
273
+ iter 0053000; MSM 0.3807; REL 0.1099; VID 0.8048; CONST 0.0000; lr 0.0001
274
+ iter 0053200; MSM 0.6462; REL 0.0103; VID 1.7104; CONST 0.0000; lr 0.0001
275
+ iter 0053400; MSM 0.1965; REL 0.2704; VID 0.4104; CONST 0.0000; lr 0.0001
276
+ iter 0053600; MSM 0.1184; REL 0.0408; VID 0.8957; CONST 0.0000; lr 0.0001
277
+ iter 0053800; MSM 0.1683; REL 0.0323; VID 1.1083; CONST 0.0000; lr 0.0001
278
+ iter 0054000; MSM 0.2816; REL 0.3281; VID 0.9505; CONST 0.0000; lr 0.0001
279
+ iter 0054200; MSM 0.4918; REL 0.2931; VID 1.5245; CONST 0.0000; lr 0.0001
280
+ iter 0054400; MSM 0.3160; REL 0.0392; VID 0.9707; CONST 0.0000; lr 0.0001
281
+ iter 0054600; MSM 0.4206; REL 0.0313; VID 0.1869; CONST 0.0000; lr 0.0001
282
+ iter 0054800; MSM 0.1354; REL 0.0487; VID 0.3519; CONST 0.0000; lr 0.0001
283
+ iter 0055000; MSM 0.2608; REL 0.0691; VID 0.3629; CONST 0.0000; lr 0.0001
284
+ iter 0055200; MSM 0.7191; REL 0.1452; VID 2.9512; CONST 0.0000; lr 0.0001
285
+ iter 0055400; MSM 0.2236; REL 0.0507; VID 0.8342; CONST 0.0000; lr 0.0001
286
+ iter 0055600; MSM 0.1596; REL 0.0938; VID 0.2318; CONST 0.0000; lr 0.0001
287
+ iter 0055800; MSM 0.2508; REL 0.1853; VID 0.5456; CONST 0.0000; lr 0.0001
288
+ iter 0056000; MSM 1.1815; REL 0.1416; VID 1.5157; CONST 0.0000; lr 0.0001
289
+ iter 0056200; MSM 0.1914; REL 0.5154; VID 0.2544; CONST 0.0000; lr 0.0001
290
+ iter 0056400; MSM 0.2713; REL 0.1309; VID 1.4742; CONST 0.0000; lr 0.0001
291
+ iter 0056600; MSM 0.2233; REL 0.0426; VID 0.3315; CONST 0.0000; lr 0.0001
292
+ iter 0056800; MSM 0.1505; REL 0.7601; VID 3.0650; CONST 0.0000; lr 0.0001
293
+ iter 0057000; MSM 0.2394; REL 0.0826; VID 0.2570; CONST 0.0000; lr 0.0001
294
+ iter 0057200; MSM 0.7969; REL 0.9186; VID 2.5618; CONST 0.0000; lr 0.0001
295
+ iter 0057400; MSM 0.2655; REL 0.8793; VID 0.1375; CONST 0.0000; lr 0.0001
296
+ iter 0057600; MSM 0.4987; REL 0.2134; VID 4.1898; CONST 0.0000; lr 0.0001
297
+ iter 0057800; MSM 0.9575; REL 0.0322; VID 1.4977; CONST 0.0000; lr 0.0001
298
+ iter 0058000; MSM 0.1485; REL 0.2753; VID 0.3628; CONST 0.0000; lr 0.0001
299
+ iter 0058200; MSM 0.1397; REL 1.9203; VID 0.8112; CONST 0.0000; lr 0.0001
300
+ iter 0058400; MSM 0.6494; REL 0.0106; VID 0.4084; CONST 0.0000; lr 0.0001
301
+ iter 0058600; MSM 0.3587; REL 0.0779; VID 0.9720; CONST 0.0000; lr 0.0001
302
+ iter 0058800; MSM 0.1810; REL 0.1786; VID 0.2299; CONST 0.0000; lr 0.0001
303
+ iter 0059000; MSM 0.2342; REL 2.8636; VID 1.8148; CONST 0.0000; lr 0.0001
304
+ iter 0059200; MSM 0.1962; REL 0.2796; VID 0.1462; CONST 0.0000; lr 0.0001
305
+ iter 0059400; MSM 0.3524; REL 0.1809; VID 0.4860; CONST 0.0000; lr 0.0001
306
+ iter 0059600; MSM 3.6547; REL 0.0000; VID 2.7728; CONST 0.0000; lr 0.0001
307
+ iter 0059800; MSM 0.9702; REL 0.0200; VID 2.7781; CONST 0.0000; lr 0.0001
308
+ iter 0060000; MSM 0.1322; REL 1.2893; VID 1.5498; CONST 0.0000; lr 0.0001
309
+ iter 0060200; MSM 0.1090; REL 0.1137; VID 0.3294; CONST 0.0000; lr 0.0001
310
+ iter 0060400; MSM 0.4203; REL 0.3037; VID 2.0297; CONST 0.0000; lr 0.0001
311
+ iter 0060600; MSM 0.2291; REL 0.1162; VID 0.8692; CONST 0.0000; lr 0.0001
312
+ iter 0060800; MSM 0.1355; REL 0.0716; VID 1.0386; CONST 0.0000; lr 0.0001
313
+ iter 0061000; MSM 0.2266; REL 1.7051; VID 0.2001; CONST 0.0000; lr 0.0001
314
+ iter 0061200; MSM 0.1419; REL 0.1208; VID 0.3047; CONST 0.0000; lr 0.0001
315
+ iter 0061400; MSM 0.9151; REL 0.0000; VID 2.7967; CONST 0.0000; lr 0.0001
316
+ iter 0061600; MSM 0.2875; REL 0.0284; VID 3.1319; CONST 0.0000; lr 0.0001
317
+ iter 0061800; MSM 0.2798; REL 0.0533; VID 1.3649; CONST 0.0000; lr 0.0001
318
+ iter 0062000; MSM 0.1349; REL 1.2456; VID 0.0837; CONST 0.0000; lr 0.0001
319
+ iter 0062200; MSM 0.2333; REL 0.1638; VID 1.4654; CONST 0.0000; lr 0.0001
320
+ iter 0062400; MSM 1.1439; REL 0.1193; VID 1.5378; CONST 0.0000; lr 0.0001
321
+ iter 0062600; MSM 0.1840; REL 1.8393; VID 0.1114; CONST 0.0000; lr 0.0001
322
+ iter 0062800; MSM 0.1933; REL 0.1813; VID 0.1438; CONST 0.0000; lr 0.0001
323
+ iter 0063000; MSM 0.6531; REL 0.9283; VID 2.1462; CONST 0.0000; lr 0.0001
324
+ iter 0063200; MSM 0.2340; REL 0.0875; VID 0.1749; CONST 0.0000; lr 0.0001
325
+ iter 0063400; MSM 0.4191; REL 0.6158; VID 0.4845; CONST 0.0000; lr 0.0001
326
+ iter 0063600; MSM 0.2611; REL 0.7739; VID 1.5793; CONST 0.0000; lr 0.0001
327
+ iter 0063800; MSM 0.2066; REL 0.0378; VID 1.0221; CONST 0.0000; lr 0.0001
328
+ iter 0064000; MSM 0.4950; REL 1.0546; VID 0.9668; CONST 0.0000; lr 0.0001
329
+ iter 0064200; MSM 0.1336; REL 0.1448; VID 0.8931; CONST 0.0000; lr 0.0001
330
+ iter 0064400; MSM 0.2220; REL 0.1034; VID 0.8076; CONST 0.0000; lr 0.0001
331
+ iter 0064600; MSM 0.2433; REL 0.0494; VID 1.0516; CONST 0.0000; lr 0.0001
332
+ iter 0064800; MSM 0.3284; REL 0.2215; VID 0.8044; CONST 0.0000; lr 0.0001
333
+ iter 0065000; MSM 0.2929; REL 0.1044; VID 0.3654; CONST 0.0000; lr 0.0001
334
+ iter 0065200; MSM 0.1737; REL 0.6641; VID 0.1763; CONST 0.0000; lr 0.0001
335
+ iter 0065400; MSM 0.2336; REL 0.1267; VID 1.5977; CONST 0.0000; lr 0.0001
336
+ iter 0065600; MSM 0.1276; REL 0.0426; VID 0.3794; CONST 0.0000; lr 0.0001
337
+ iter 0065800; MSM 0.3315; REL 0.2828; VID 0.9682; CONST 0.0000; lr 0.0001
338
+ iter 0066000; MSM 0.2078; REL 0.0163; VID 1.5780; CONST 0.0000; lr 0.0001
339
+ iter 0066200; MSM 0.1071; REL 0.1196; VID 0.7652; CONST 0.0000; lr 0.0001
340
+ iter 0066400; MSM 0.0786; REL 0.0609; VID 0.2094; CONST 0.0000; lr 0.0001
341
+ iter 0066600; MSM 0.1007; REL 0.7179; VID 1.1258; CONST 0.0000; lr 0.0001
342
+ iter 0066800; MSM 0.2281; REL 0.1682; VID 0.1921; CONST 0.0000; lr 0.0001
343
+ iter 0067000; MSM 0.4915; REL 0.0248; VID 0.8706; CONST 0.0000; lr 0.0001
344
+ iter 0067200; MSM 0.1582; REL 0.0785; VID 0.2274; CONST 0.0000; lr 0.0001
345
+ iter 0067400; MSM 0.1409; REL 0.0303; VID 1.1074; CONST 0.0000; lr 0.0001
346
+ iter 0067600; MSM 0.1401; REL 0.1855; VID 0.2028; CONST 0.0000; lr 0.0001
347
+ iter 0067800; MSM 0.1351; REL 0.1008; VID 0.1336; CONST 0.0000; lr 0.0001
348
+ iter 0068000; MSM 0.1612; REL 0.1175; VID 0.3736; CONST 0.0000; lr 0.0001
349
+ iter 0068200; MSM 0.1379; REL 0.1494; VID 0.2687; CONST 0.0000; lr 0.0001
350
+ iter 0068400; MSM 0.3115; REL 0.0373; VID 0.5351; CONST 0.0000; lr 0.0001
351
+ iter 0068600; MSM 0.5074; REL 0.0348; VID 1.9871; CONST 0.0000; lr 0.0001
352
+ iter 0068800; MSM 0.1250; REL 0.0565; VID 1.0438; CONST 0.0000; lr 0.0001
353
+ iter 0069000; MSM 0.1263; REL 0.0260; VID 0.7479; CONST 0.0000; lr 0.0001
354
+ iter 0069200; MSM 0.1687; REL 0.2817; VID 0.0966; CONST 0.0000; lr 0.0001
355
+ iter 0069400; MSM 0.2373; REL 0.0225; VID 1.5371; CONST 0.0000; lr 0.0001
356
+ iter 0069600; MSM 0.2246; REL 0.0797; VID 1.0101; CONST 0.0000; lr 0.0001
357
+ iter 0069800; MSM 0.0774; REL 0.0723; VID 0.1215; CONST 0.0000; lr 0.0001
358
+ iter 0070000; MSM 0.1217; REL 0.1239; VID 0.1534; CONST 0.0000; lr 0.0001
359
+ iter 0070200; MSM 0.1308; REL 0.1281; VID 0.2317; CONST 0.0000; lr 0.0001
360
+ iter 0070400; MSM 0.1597; REL 0.1493; VID 0.0630; CONST 0.0000; lr 0.0001
361
+ iter 0070600; MSM 0.6963; REL 0.8653; VID 1.5229; CONST 0.0000; lr 0.0001
362
+ iter 0070800; MSM 0.2345; REL 0.0438; VID 0.9137; CONST 0.0000; lr 0.0001
363
+ iter 0071000; MSM 0.6111; REL 0.0545; VID 0.3146; CONST 0.0000; lr 0.0001
364
+ iter 0071200; MSM 0.0927; REL 0.1672; VID 1.1258; CONST 0.0000; lr 0.0001
365
+ iter 0071400; MSM 0.4616; REL 0.3474; VID 1.1199; CONST 0.0000; lr 0.0001
366
+ iter 0071600; MSM 0.4739; REL 0.0658; VID 1.4936; CONST 0.0000; lr 0.0001
367
+ iter 0071800; MSM 0.3197; REL 0.0465; VID 0.3776; CONST 0.0000; lr 0.0001
368
+ iter 0072000; MSM 0.2673; REL 0.0295; VID 1.0154; CONST 0.0000; lr 0.0001
369
+ iter 0072200; MSM 0.1834; REL 0.1052; VID 1.1064; CONST 0.0000; lr 0.0001
370
+ iter 0072400; MSM 0.3628; REL 2.2151; VID 0.1519; CONST 0.0000; lr 0.0001
371
+ iter 0072600; MSM 0.3487; REL 0.0216; VID 2.3243; CONST 0.0000; lr 0.0001
372
+ iter 0072800; MSM 0.1386; REL 0.7350; VID 0.7377; CONST 0.0000; lr 0.0001
373
+ iter 0073000; MSM 0.3602; REL 0.0311; VID 1.4292; CONST 0.0000; lr 0.0001
374
+ iter 0073200; MSM 0.1005; REL 0.6532; VID 0.7445; CONST 0.0000; lr 0.0001
375
+ iter 0073400; MSM 0.1030; REL 0.0809; VID 0.1127; CONST 0.0000; lr 0.0001
376
+ iter 0073600; MSM 0.2096; REL 0.0373; VID 1.1275; CONST 0.0000; lr 0.0001
377
+ iter 0073800; MSM 0.5706; REL 1.0271; VID 1.7496; CONST 0.0000; lr 0.0001
378
+ iter 0074000; MSM 0.1679; REL 0.0353; VID 0.2028; CONST 0.0000; lr 0.0001
379
+ iter 0074200; MSM 0.1228; REL 0.1226; VID 0.1606; CONST 0.0000; lr 0.0001
380
+ iter 0074400; MSM 0.1630; REL 0.2573; VID 1.9732; CONST 0.0000; lr 0.0001
381
+ iter 0074600; MSM 0.2728; REL 0.2824; VID 2.6848; CONST 0.0000; lr 0.0001
382
+ iter 0074800; MSM 0.3308; REL 0.0263; VID 1.6656; CONST 0.0000; lr 0.0001
383
+ iter 0075000; MSM 0.1456; REL 0.4290; VID 1.1038; CONST 0.0000; lr 0.0001
384
+ iter 0075200; MSM 0.1261; REL 0.1121; VID 0.2578; CONST 0.0000; lr 0.0001
385
+ iter 0075400; MSM 0.0633; REL 0.0291; VID 0.0788; CONST 0.0000; lr 0.0001
386
+ iter 0075600; MSM 0.4426; REL 0.0389; VID 1.5891; CONST 0.0000; lr 0.0001
387
+ iter 0075800; MSM 0.3703; REL 0.0643; VID 0.4108; CONST 0.0000; lr 0.0001
388
+ iter 0076000; MSM 0.5367; REL 0.0836; VID 1.4781; CONST 0.0000; lr 0.0001
389
+ iter 0076200; MSM 0.2521; REL 0.0312; VID 0.8343; CONST 0.0000; lr 0.0001
390
+ iter 0076400; MSM 0.6211; REL 0.1083; VID 1.4375; CONST 0.0000; lr 0.0001
391
+ iter 0076600; MSM 0.5155; REL 0.0451; VID 1.5829; CONST 0.0000; lr 0.0001
392
+ iter 0076800; MSM 0.1130; REL 0.0295; VID 0.1113; CONST 0.0000; lr 0.0001
393
+ iter 0077000; MSM 0.3882; REL 0.0663; VID 0.8233; CONST 0.0000; lr 0.0001
394
+ iter 0077200; MSM 0.0551; REL 0.0401; VID 1.2035; CONST 0.0000; lr 0.0001
395
+ iter 0077400; MSM 0.1185; REL 0.0749; VID 0.1963; CONST 0.0000; lr 0.0001
396
+ iter 0077600; MSM 0.1638; REL 0.0319; VID 1.6515; CONST 0.0000; lr 0.0001
397
+ iter 0077800; MSM 0.4669; REL 0.0576; VID 3.7660; CONST 0.0000; lr 0.0001
398
+ iter 0078000; MSM 0.1914; REL 3.4608; VID 0.7793; CONST 0.0000; lr 0.0001
399
+ iter 0078200; MSM 0.1809; REL 0.0100; VID 0.4310; CONST 0.0000; lr 0.0001
400
+ iter 0078400; MSM 0.1214; REL 0.1499; VID 0.8953; CONST 0.0000; lr 0.0001
401
+ iter 0078600; MSM 1.9513; REL 0.0180; VID 1.5311; CONST 0.0000; lr 0.0001
402
+ iter 0078800; MSM 0.1522; REL 0.0318; VID 0.8873; CONST 0.0000; lr 0.0001
403
+ iter 0079000; MSM 0.1263; REL 0.0492; VID 0.5786; CONST 0.0000; lr 0.0001
404
+ iter 0079200; MSM 0.3397; REL 0.0165; VID 2.9871; CONST 0.0000; lr 0.0001
405
+ iter 0079400; MSM 0.3686; REL 0.0842; VID 1.4974; CONST 0.0000; lr 0.0001
406
+ iter 0079600; MSM 0.1495; REL 0.0636; VID 0.4816; CONST 0.0000; lr 0.0001
407
+ iter 0079800; MSM 2.7186; REL 0.0040; VID 2.8585; CONST 0.0000; lr 0.0001
408
+ iter 0080000; MSM 0.2503; REL 0.0121; VID 0.4291; CONST 0.0000; lr 0.0001
409
+ iter 0080200; MSM 0.1738; REL 0.0308; VID 0.6737; CONST 0.0000; lr 0.0001
410
+ iter 0080400; MSM 0.1321; REL 0.0200; VID 0.5653; CONST 0.0000; lr 0.0001
411
+ iter 0080600; MSM 0.1217; REL 0.0565; VID 0.1056; CONST 0.0000; lr 0.0001
412
+ iter 0080800; MSM 0.2062; REL 0.0232; VID 2.3123; CONST 0.0000; lr 0.0001
413
+ iter 0081000; MSM 0.0725; REL 0.1012; VID 1.0990; CONST 0.0000; lr 0.0001
414
+ iter 0081200; MSM 0.1602; REL 0.0785; VID 0.3768; CONST 0.0000; lr 0.0001
415
+ iter 0081400; MSM 0.3067; REL 0.0078; VID 0.1405; CONST 0.0000; lr 0.0001
416
+ iter 0081600; MSM 0.1858; REL 0.1607; VID 0.3062; CONST 0.0000; lr 0.0001
417
+ iter 0081800; MSM 1.2420; REL 0.0122; VID 1.5962; CONST 0.0000; lr 0.0001
418
+ iter 0082000; MSM 0.1778; REL 0.1498; VID 1.4397; CONST 0.0000; lr 0.0001
419
+ iter 0082200; MSM 0.1620; REL 0.0095; VID 1.2541; CONST 0.0000; lr 0.0001
420
+ iter 0082400; MSM 0.1690; REL 0.1042; VID 0.8939; CONST 0.0000; lr 0.0001
421
+ iter 0082600; MSM 0.2510; REL 0.2106; VID 0.2027; CONST 0.0000; lr 0.0001
422
+ iter 0082800; MSM 0.3443; REL 0.0978; VID 0.1627; CONST 0.0000; lr 0.0001
423
+ iter 0083000; MSM 1.5963; REL 1.9108; VID 1.9441; CONST 0.0000; lr 0.0001
424
+ iter 0083200; MSM 0.3299; REL 0.0076; VID 1.1817; CONST 0.0000; lr 0.0001
425
+ iter 0083400; MSM 0.2582; REL 0.1532; VID 2.2818; CONST 0.0000; lr 0.0001
426
+ iter 0083600; MSM 0.1326; REL 0.1110; VID 0.3382; CONST 0.0000; lr 0.0001
427
+ iter 0083800; MSM 0.3437; REL 0.0152; VID 0.9567; CONST 0.0000; lr 0.0001
428
+ iter 0084000; MSM 0.1132; REL 0.0680; VID 0.0625; CONST 0.0000; lr 0.0001
429
+ iter 0084200; MSM 0.1243; REL 0.0558; VID 0.1880; CONST 0.0000; lr 0.0001
430
+ iter 0084400; MSM 0.1898; REL 0.0192; VID 0.9412; CONST 0.0000; lr 0.0001
431
+ iter 0084600; MSM 0.1059; REL 0.0494; VID 1.0532; CONST 0.0000; lr 0.0001
432
+ iter 0084800; MSM 0.0828; REL 0.2375; VID 0.8972; CONST 0.0000; lr 0.0001
433
+ iter 0085000; MSM 0.1246; REL 0.0072; VID 0.2820; CONST 0.0000; lr 0.0001
434
+ iter 0085200; MSM 0.2474; REL 0.3097; VID 0.3155; CONST 0.0000; lr 0.0001
435
+ iter 0085400; MSM 0.0841; REL 0.0353; VID 0.1116; CONST 0.0000; lr 0.0001
436
+ iter 0085600; MSM 0.0510; REL 0.0395; VID 1.5153; CONST 0.0000; lr 0.0001
437
+ iter 0085800; MSM 0.2124; REL 0.1593; VID 1.1127; CONST 0.0000; lr 0.0001
438
+ iter 0086000; MSM 0.1306; REL 0.0901; VID 0.1097; CONST 0.0000; lr 0.0001
439
+ iter 0086200; MSM 0.1483; REL 0.0409; VID 0.1952; CONST 0.0000; lr 0.0001
440
+ iter 0086400; MSM 0.0774; REL 0.0668; VID 0.8386; CONST 0.0000; lr 0.0001
441
+ iter 0086600; MSM 0.1232; REL 0.0688; VID 0.6267; CONST 0.0000; lr 0.0001
442
+ iter 0086800; MSM 0.1593; REL 0.0294; VID 0.3732; CONST 0.0000; lr 0.0001
443
+ iter 0087000; MSM 0.2314; REL 0.1159; VID 0.2857; CONST 0.0000; lr 0.0001
444
+ iter 0087200; MSM 0.0953; REL 0.0578; VID 1.0062; CONST 0.0000; lr 0.0001
445
+ iter 0087400; MSM 0.4802; REL 0.0381; VID 1.4888; CONST 0.0000; lr 0.0001
446
+ iter 0087600; MSM 0.1139; REL 0.0617; VID 0.2098; CONST 0.0000; lr 0.0001
447
+ iter 0087800; MSM 0.3021; REL 0.0441; VID 1.4492; CONST 0.0000; lr 0.0001
448
+ iter 0088000; MSM 0.0905; REL 0.0371; VID 1.7579; CONST 0.0000; lr 0.0001
449
+ iter 0088200; MSM 0.2020; REL 0.0466; VID 1.7955; CONST 0.0000; lr 0.0001
450
+ iter 0088400; MSM 0.1695; REL 0.0348; VID 1.8897; CONST 0.0000; lr 0.0001
451
+ iter 0088600; MSM 0.2439; REL 0.1600; VID 0.2146; CONST 0.0000; lr 0.0001
452
+ iter 0088800; MSM 0.1100; REL 0.0245; VID 0.1584; CONST 0.0000; lr 0.0001
453
+ iter 0089000; MSM 2.3451; REL 0.0774; VID 3.8645; CONST 0.0000; lr 0.0001
454
+ iter 0089200; MSM 0.0758; REL 0.0448; VID 0.3017; CONST 0.0000; lr 0.0001
455
+ iter 0089400; MSM 0.1623; REL 0.1155; VID 1.5907; CONST 0.0000; lr 0.0001
456
+ iter 0089600; MSM 0.2560; REL 0.0202; VID 1.4958; CONST 0.0000; lr 0.0001
457
+ iter 0089800; MSM 0.2287; REL 0.2301; VID 0.1279; CONST 0.0000; lr 0.0001
458
+ iter 0090000; MSM 0.0975; REL 0.0547; VID 0.8280; CONST 0.0000; lr 0.0001
459
+ iter 0090200; MSM 0.0953; REL 0.0489; VID 0.1985; CONST 0.0000; lr 0.0001
460
+ iter 0090400; MSM 0.1527; REL 0.0530; VID 0.1949; CONST 0.0000; lr 0.0001
461
+ iter 0090600; MSM 0.2545; REL 0.0225; VID 0.0972; CONST 0.0000; lr 0.0001
462
+ iter 0090800; MSM 0.1631; REL 0.0496; VID 0.2026; CONST 0.0000; lr 0.0001
463
+ iter 0091000; MSM 0.2208; REL 0.3182; VID 0.4892; CONST 0.0000; lr 0.0001
464
+ iter 0091200; MSM 0.1796; REL 0.0084; VID 0.0481; CONST 0.0000; lr 0.0001
465
+ iter 0091400; MSM 0.1196; REL 1.9991; VID 0.6475; CONST 0.0000; lr 0.0001
466
+ iter 0091600; MSM 0.1800; REL 0.0580; VID 0.7540; CONST 0.0000; lr 0.0001
467
+ iter 0091800; MSM 0.2249; REL 0.0050; VID 0.1308; CONST 0.0000; lr 0.0001
468
+ iter 0092000; MSM 0.0597; REL 0.0415; VID 0.1197; CONST 0.0000; lr 0.0001
469
+ iter 0092200; MSM 0.2252; REL 0.0503; VID 0.7766; CONST 0.0000; lr 0.0001
470
+ iter 0092400; MSM 0.2250; REL 0.0139; VID 0.1988; CONST 0.0000; lr 0.0001
471
+ iter 0092600; MSM 0.1107; REL 0.1311; VID 0.0583; CONST 0.0000; lr 0.0001
472
+ iter 0092800; MSM 0.1854; REL 0.1301; VID 0.1133; CONST 0.0000; lr 0.0001
473
+ iter 0093000; MSM 0.0509; REL 0.6888; VID 0.0900; CONST 0.0000; lr 0.0001
474
+ iter 0093200; MSM 0.1713; REL 0.0270; VID 1.1206; CONST 0.0000; lr 0.0001
475
+ iter 0093400; MSM 0.1447; REL 0.0220; VID 0.0922; CONST 0.0000; lr 0.0001
476
+ iter 0093600; MSM 0.2419; REL 0.0277; VID 0.3953; CONST 0.0000; lr 0.0001
477
+ iter 0093800; MSM 0.2006; REL 0.0074; VID 0.7209; CONST 0.0000; lr 0.0001
478
+ iter 0094000; MSM 0.0832; REL 0.0161; VID 0.6854; CONST 0.0000; lr 0.0001
479
+ iter 0094200; MSM 0.1076; REL 0.0104; VID 0.2902; CONST 0.0000; lr 0.0001
480
+ iter 0094400; MSM 0.1373; REL 0.0635; VID 1.5509; CONST 0.0000; lr 0.0001
481
+ iter 0094600; MSM 0.2656; REL 0.0378; VID 1.4192; CONST 0.0000; lr 0.0001
482
+ iter 0094800; MSM 0.0899; REL 0.0332; VID 0.5917; CONST 0.0000; lr 0.0001
483
+ iter 0095000; MSM 0.1038; REL 0.0156; VID 1.1567; CONST 0.0000; lr 0.0001
484
+ iter 0095200; MSM 0.2355; REL 0.5361; VID 1.5478; CONST 0.0000; lr 0.0001
485
+ iter 0095400; MSM 0.0722; REL 0.1295; VID 0.1185; CONST 0.0000; lr 0.0001
486
+ iter 0095600; MSM 0.1373; REL 0.0384; VID 1.6698; CONST 0.0000; lr 0.0001
487
+ iter 0095800; MSM 0.0669; REL 0.0436; VID 0.2136; CONST 0.0000; lr 0.0001
488
+ iter 0096000; MSM 0.1081; REL 0.0717; VID 1.5628; CONST 0.0000; lr 0.0001
489
+ iter 0096200; MSM 0.1370; REL 0.0420; VID 0.9538; CONST 0.0000; lr 0.0001
490
+ iter 0096400; MSM 0.0931; REL 0.0567; VID 0.2482; CONST 0.0000; lr 0.0001
491
+ iter 0096600; MSM 0.1192; REL 0.0322; VID 0.9623; CONST 0.0000; lr 0.0001
492
+ iter 0096800; MSM 1.5356; REL 0.0283; VID 1.4409; CONST 0.0000; lr 0.0001
493
+ iter 0097000; MSM 4.9526; REL 0.1196; VID 2.4906; CONST 0.0000; lr 0.0001
494
+ iter 0097200; MSM 0.1141; REL 1.9540; VID 0.5000; CONST 0.0000; lr 0.0001
495
+ iter 0097400; MSM 0.1017; REL 0.0646; VID 0.4613; CONST 0.0000; lr 0.0001
496
+ iter 0097600; MSM 0.1852; REL 0.0182; VID 0.9707; CONST 0.0000; lr 0.0001
497
+ iter 0097800; MSM 0.0734; REL 0.1156; VID 0.2208; CONST 0.0000; lr 0.0001
498
+ iter 0098000; MSM 0.2251; REL 0.0212; VID 0.2419; CONST 0.0000; lr 0.0001
499
+ iter 0098200; MSM 0.1399; REL 0.1137; VID 0.1530; CONST 0.0000; lr 0.0001
500
+ iter 0098400; MSM 0.3367; REL 0.0204; VID 1.7062; CONST 0.0000; lr 0.0001
501
+ iter 0098600; MSM 0.1721; REL 0.0019; VID 0.5544; CONST 0.0000; lr 0.0001
502
+ iter 0098800; MSM 0.1332; REL 0.0082; VID 0.9030; CONST 0.0000; lr 0.0001
503
+ iter 0099000; MSM 0.2818; REL 0.0121; VID 1.2793; CONST 0.0000; lr 0.0001
504
+ iter 0099200; MSM 0.1047; REL 0.0481; VID 0.4390; CONST 0.0000; lr 0.0001
505
+ iter 0099400; MSM 0.1257; REL 0.0333; VID 0.2337; CONST 0.0000; lr 0.0001
506
+ iter 0099600; MSM 0.0771; REL 0.1897; VID 0.8797; CONST 0.0000; lr 0.0001
507
+ iter 0099800; MSM 0.1474; REL 0.9226; VID 1.0361; CONST 0.0000; lr 0.0001
508
+ iter 0100000; MSM 0.2348; REL 0.0216; VID 0.5811; CONST 0.0000; lr 0.0001
509
+ iter 0100200; MSM 0.2013; REL 0.0013; VID 1.7048; CONST 0.0000; lr 0.0001
510
+ iter 0100400; MSM 0.2474; REL 0.0106; VID 1.4942; CONST 0.0000; lr 0.0001
511
+ iter 0100600; MSM 0.1476; REL 0.0109; VID 1.5348; CONST 0.0000; lr 0.0001
512
+ iter 0100800; MSM 0.0914; REL 0.1437; VID 0.3633; CONST 0.0000; lr 0.0001
513
+ iter 0101000; MSM 0.1057; REL 0.3614; VID 0.1206; CONST 0.0000; lr 0.0001
514
+ iter 0101200; MSM 0.1281; REL 0.1209; VID 0.0391; CONST 0.0000; lr 0.0001
515
+ iter 0101400; MSM 0.0860; REL 0.0455; VID 0.2057; CONST 0.0000; lr 0.0001
516
+ iter 0101600; MSM 0.2226; REL 0.0267; VID 1.6831; CONST 0.0000; lr 0.0001
517
+ iter 0101800; MSM 0.0929; REL 0.0740; VID 1.3019; CONST 0.0000; lr 0.0001
518
+ iter 0102000; MSM 0.0457; REL 0.0743; VID 0.1615; CONST 0.0000; lr 0.0001
519
+ iter 0102200; MSM 0.1323; REL 0.1914; VID 0.7163; CONST 0.0000; lr 0.0001
520
+ iter 0102400; MSM 0.1144; REL 5.5983; VID 1.3788; CONST 0.0000; lr 0.0001
521
+ iter 0102600; MSM 0.0764; REL 0.0097; VID 0.3208; CONST 0.0000; lr 0.0001
522
+ iter 0102800; MSM 0.1295; REL 0.0356; VID 0.2902; CONST 0.0000; lr 0.0001
523
+ iter 0103000; MSM 0.1504; REL 0.1523; VID 1.2867; CONST 0.0000; lr 0.0001
524
+ iter 0103200; MSM 0.0615; REL 0.0291; VID 0.8247; CONST 0.0000; lr 0.0001
525
+ iter 0103400; MSM 0.0740; REL 0.0599; VID 0.9390; CONST 0.0000; lr 0.0001
526
+ iter 0103600; MSM 0.0665; REL 0.1769; VID 0.8991; CONST 0.0000; lr 0.0001
527
+ iter 0103800; MSM 0.0555; REL 0.0478; VID 0.0754; CONST 0.0000; lr 0.0001
528
+ iter 0104000; MSM 0.1266; REL 0.0661; VID 0.1363; CONST 0.0000; lr 0.0001
529
+ iter 0104200; MSM 0.1407; REL 0.0092; VID 0.1252; CONST 0.0000; lr 0.0001
530
+ iter 0104400; MSM 0.1391; REL 0.0094; VID 0.2390; CONST 0.0000; lr 0.0001
531
+ iter 0104600; MSM 0.0823; REL 0.0110; VID 0.5543; CONST 0.0000; lr 0.0001
532
+ iter 0104800; MSM 0.2342; REL 0.0116; VID 1.9164; CONST 0.0000; lr 0.0001
533
+ iter 0105000; MSM 0.0708; REL 0.0284; VID 2.3336; CONST 0.0000; lr 0.0001
534
+ iter 0105200; MSM 2.6157; REL 0.2920; VID 4.1099; CONST 0.0000; lr 0.0001
535
+ iter 0105400; MSM 0.1465; REL 0.8518; VID 1.0360; CONST 0.0000; lr 0.0001
536
+ iter 0105600; MSM 0.1287; REL 0.0264; VID 1.6051; CONST 0.0000; lr 0.0001
537
+ iter 0105800; MSM 0.0769; REL 0.0763; VID 0.0890; CONST 0.0000; lr 0.0001
538
+ iter 0106000; MSM 0.2052; REL 0.0140; VID 0.1550; CONST 0.0000; lr 0.0001
539
+ iter 0106200; MSM 0.1119; REL 0.7789; VID 1.1660; CONST 0.0000; lr 0.0001
540
+ iter 0106400; MSM 0.1354; REL 1.4049; VID 0.8848; CONST 0.0000; lr 0.0001
541
+ iter 0106600; MSM 0.1946; REL 0.0769; VID 0.9067; CONST 0.0000; lr 0.0001
542
+ iter 0106800; MSM 0.0857; REL 0.0248; VID 1.0716; CONST 0.0000; lr 0.0001
543
+ iter 0107000; MSM 0.1200; REL 0.0513; VID 1.4612; CONST 0.0000; lr 0.0001
544
+ iter 0107200; MSM 0.1576; REL 0.2329; VID 0.6212; CONST 0.0000; lr 0.0001
545
+ iter 0107400; MSM 0.1327; REL 0.3410; VID 0.9379; CONST 0.0000; lr 0.0001
546
+ iter 0107600; MSM 0.1375; REL 0.0148; VID 0.5686; CONST 0.0000; lr 0.0001
547
+ iter 0107800; MSM 0.0862; REL 0.0303; VID 0.1083; CONST 0.0000; lr 0.0001
548
+ iter 0108000; MSM 0.0601; REL 0.0766; VID 0.1946; CONST 0.0000; lr 0.0001
549
+ iter 0108200; MSM 0.8302; REL 2.7557; VID 3.6759; CONST 0.0000; lr 0.0001
550
+ iter 0108400; MSM 0.1176; REL 0.1749; VID 0.0498; CONST 0.0000; lr 0.0001
551
+ iter 0108600; MSM 0.1329; REL 0.1629; VID 0.2573; CONST 0.0000; lr 0.0001
552
+ iter 0108800; MSM 0.0365; REL 0.0140; VID 0.1266; CONST 0.0000; lr 0.0001
553
+ iter 0109000; MSM 0.1303; REL 0.0294; VID 0.0470; CONST 0.0000; lr 0.0001
554
+ iter 0109200; MSM 0.0799; REL 0.0126; VID 0.4764; CONST 0.0000; lr 0.0001
555
+ iter 0109400; MSM 0.1630; REL 0.0342; VID 0.8460; CONST 0.0000; lr 0.0001
556
+ iter 0109600; MSM 0.0866; REL 0.1005; VID 0.1220; CONST 0.0000; lr 0.0001
557
+ iter 0109800; MSM 0.0986; REL 0.0032; VID 0.0985; CONST 0.0000; lr 0.0001
558
+ iter 0110000; MSM 0.1011; REL 0.0147; VID 0.1426; CONST 0.0000; lr 0.0001
559
+ iter 0110200; MSM 0.0864; REL 0.0603; VID 1.4389; CONST 0.0000; lr 0.0001
560
+ iter 0110400; MSM 0.1799; REL 3.7839; VID 2.2857; CONST 0.0000; lr 0.0001
561
+ iter 0110600; MSM 0.0864; REL 0.0095; VID 0.6009; CONST 0.0000; lr 0.0001
562
+ iter 0110800; MSM 0.0553; REL 0.0394; VID 0.0718; CONST 0.0000; lr 0.0001
563
+ iter 0111000; MSM 0.1011; REL 0.1859; VID 1.0348; CONST 0.0000; lr 0.0001
564
+ iter 0111200; MSM 0.1262; REL 0.0597; VID 0.6537; CONST 0.0000; lr 0.0001
565
+ iter 0111400; MSM 0.0601; REL 0.0420; VID 1.0663; CONST 0.0000; lr 0.0001
566
+ iter 0111600; MSM 0.0859; REL 0.0319; VID 0.1507; CONST 0.0000; lr 0.0001
567
+ iter 0111800; MSM 0.0887; REL 0.0964; VID 1.2177; CONST 0.0000; lr 0.0001
568
+ iter 0112000; MSM 0.0758; REL 0.0842; VID 0.0847; CONST 0.0000; lr 0.0001
569
+ iter 0112200; MSM 0.0784; REL 2.9657; VID 0.0840; CONST 0.0000; lr 0.0001
570
+ iter 0112400; MSM 0.0588; REL 0.0775; VID 1.2626; CONST 0.0000; lr 0.0001
571
+ iter 0112600; MSM 0.1284; REL 0.0164; VID 0.1911; CONST 0.0000; lr 0.0001
572
+ iter 0112800; MSM 0.1142; REL 0.0000; VID 2.7756; CONST 0.0000; lr 0.0001
573
+ iter 0113000; MSM 0.0500; REL 0.6277; VID 1.0464; CONST 0.0000; lr 0.0001
574
+ iter 0113200; MSM 0.0873; REL 0.0527; VID 0.6144; CONST 0.0000; lr 0.0001
575
+ iter 0113400; MSM 0.2370; REL 0.0055; VID 1.4563; CONST 0.0000; lr 0.0001
576
+ iter 0113600; MSM 0.1625; REL 0.0379; VID 0.2853; CONST 0.0000; lr 0.0001
577
+ iter 0113800; MSM 0.0590; REL 0.4949; VID 0.2764; CONST 0.0000; lr 0.0001
578
+ iter 0114000; MSM 0.1259; REL 1.6043; VID 0.1290; CONST 0.0000; lr 0.0001
579
+ iter 0114200; MSM 0.0726; REL 0.1664; VID 0.1251; CONST 0.0000; lr 0.0001
580
+ iter 0114400; MSM 0.1434; REL 0.0078; VID 0.1348; CONST 0.0000; lr 0.0001
581
+ iter 0114600; MSM 0.1492; REL 0.0771; VID 1.7968; CONST 0.0000; lr 0.0001
582
+ iter 0114800; MSM 0.0869; REL 0.0338; VID 0.1128; CONST 0.0000; lr 0.0001
583
+ iter 0115000; MSM 0.1512; REL 0.5939; VID 1.7655; CONST 0.0000; lr 0.0001
584
+ iter 0115200; MSM 0.0725; REL 0.0399; VID 4.4615; CONST 0.0000; lr 0.0001
585
+ iter 0115400; MSM 0.0380; REL 0.0167; VID 0.9072; CONST 0.0000; lr 0.0001
586
+ iter 0115600; MSM 0.0847; REL 1.7158; VID 0.5814; CONST 0.0000; lr 0.0001
587
+ iter 0115800; MSM 0.0517; REL 0.0150; VID 0.2015; CONST 0.0000; lr 0.0001
588
+ iter 0116000; MSM 0.1666; REL 0.0133; VID 1.4352; CONST 0.0000; lr 0.0001
589
+ iter 0116200; MSM 0.2070; REL 2.9748; VID 1.4149; CONST 0.0000; lr 0.0001
590
+ iter 0116400; MSM 0.0477; REL 0.0561; VID 0.3989; CONST 0.0000; lr 0.0001
591
+ iter 0116600; MSM 0.0943; REL 0.0210; VID 0.0914; CONST 0.0000; lr 0.0001
592
+ iter 0116800; MSM 0.1289; REL 0.0140; VID 0.0659; CONST 0.0000; lr 0.0001
593
+ iter 0117000; MSM 0.0619; REL 1.6535; VID 0.2206; CONST 0.0000; lr 0.0001
594
+ iter 0117200; MSM 0.1893; REL 0.0171; VID 0.6069; CONST 0.0000; lr 0.0001
595
+ iter 0117400; MSM 0.0589; REL 0.0159; VID 1.2866; CONST 0.0000; lr 0.0001
596
+ iter 0117600; MSM 0.0607; REL 0.0171; VID 0.0735; CONST 0.0000; lr 0.0001
597
+ iter 0117800; MSM 0.0666; REL 0.0580; VID 1.2547; CONST 0.0000; lr 0.0001
598
+ iter 0118000; MSM 0.1268; REL 0.0053; VID 0.8404; CONST 0.0000; lr 0.0001
599
+ iter 0118200; MSM 0.1677; REL 0.0091; VID 0.1298; CONST 0.0000; lr 0.0001
600
+ iter 0118400; MSM 0.1712; REL 0.0070; VID 1.4527; CONST 0.0000; lr 0.0001
601
+ iter 0118600; MSM 0.0662; REL 0.0733; VID 0.3211; CONST 0.0000; lr 0.0001
602
+ iter 0118800; MSM 0.1193; REL 1.5129; VID 0.1572; CONST 0.0000; lr 0.0001
603
+ iter 0119000; MSM 0.1100; REL 0.0605; VID 1.4894; CONST 0.0000; lr 0.0001
604
+ iter 0119200; MSM 0.0984; REL 0.0124; VID 0.8921; CONST 0.0000; lr 0.0001
605
+ iter 0119400; MSM 0.0961; REL 0.1456; VID 0.6038; CONST 0.0000; lr 0.0001
606
+ iter 0119600; MSM 0.0464; REL 0.0659; VID 0.2924; CONST 0.0000; lr 0.0001
607
+ iter 0119800; MSM 0.1522; REL 0.0179; VID 1.4520; CONST 0.0000; lr 0.0001
608
+ iter 0120000; MSM 0.6393; REL 0.0533; VID 1.6183; CONST 0.0000; lr 0.0001
609
+ iter 0120200; MSM 0.0457; REL 0.0284; VID 0.4973; CONST 0.0000; lr 0.0001
610
+ iter 0120400; MSM 0.1324; REL 0.0309; VID 0.2104; CONST 0.0000; lr 0.0001
611
+ iter 0120600; MSM 0.0648; REL 0.0235; VID 1.1017; CONST 0.0000; lr 0.0001
612
+ iter 0120800; MSM 0.0372; REL 0.9831; VID 1.2620; CONST 0.0000; lr 0.0001
613
+ iter 0121000; MSM 0.0681; REL 0.0145; VID 0.1059; CONST 0.0000; lr 0.0001
614
+ iter 0121200; MSM 0.0389; REL 0.0265; VID 0.0997; CONST 0.0000; lr 0.0001
615
+ iter 0121400; MSM 0.0953; REL 0.1102; VID 0.0930; CONST 0.0000; lr 0.0001
616
+ iter 0121600; MSM 0.2308; REL 0.0355; VID 2.4932; CONST 0.0000; lr 0.0001
617
+ iter 0121800; MSM 0.0830; REL 0.0632; VID 1.1852; CONST 0.0000; lr 0.0001
618
+ iter 0122000; MSM 0.0351; REL 0.2387; VID 1.6595; CONST 0.0000; lr 0.0001
619
+ iter 0122200; MSM 0.0348; REL 0.0226; VID 0.9679; CONST 0.0000; lr 0.0001
620
+ iter 0122400; MSM 0.1593; REL 0.0112; VID 0.2774; CONST 0.0000; lr 0.0001
621
+ iter 0122600; MSM 0.0675; REL 0.0193; VID 1.1810; CONST 0.0000; lr 0.0001
622
+ iter 0122800; MSM 0.0518; REL 0.0616; VID 0.9757; CONST 0.0000; lr 0.0001
623
+ iter 0123000; MSM 0.0492; REL 0.0073; VID 1.4338; CONST 0.0000; lr 0.0001
624
+ iter 0123200; MSM 0.0799; REL 0.0190; VID 0.0475; CONST 0.0000; lr 0.0001
625
+ iter 0123400; MSM 0.1988; REL 0.0057; VID 1.4384; CONST 0.0000; lr 0.0001
626
+ iter 0123600; MSM 0.1329; REL 0.1182; VID 1.5091; CONST 0.0000; lr 0.0001
627
+ iter 0123800; MSM 0.1033; REL 0.0019; VID 1.2019; CONST 0.0000; lr 0.0001
628
+ iter 0124000; MSM 0.1150; REL 0.0047; VID 0.1341; CONST 0.0000; lr 0.0001
629
+ iter 0124200; MSM 0.0915; REL 0.0227; VID 0.1983; CONST 0.0000; lr 0.0001
630
+ iter 0124400; MSM 0.2170; REL 0.0121; VID 1.4858; CONST 0.0000; lr 0.0001
631
+ iter 0124600; MSM 0.0900; REL 0.0041; VID 1.4657; CONST 0.0000; lr 0.0001
632
+ iter 0124800; MSM 0.0463; REL 0.0291; VID 1.2212; CONST 0.0000; lr 0.0001
633
+ iter 0125000; MSM 0.0384; REL 0.0663; VID 0.1693; CONST 0.0000; lr 0.0001
634
+ iter 0125200; MSM 0.0885; REL 0.0120; VID 0.3462; CONST 0.0000; lr 0.0001
635
+ iter 0125400; MSM 0.1394; REL 0.0208; VID 0.5666; CONST 0.0000; lr 0.0001
636
+ iter 0125600; MSM 0.1926; REL 0.0300; VID 1.0200; CONST 0.0000; lr 0.0001
637
+ iter 0125800; MSM 0.1222; REL 0.0065; VID 0.1446; CONST 0.0000; lr 0.0001
638
+ iter 0126000; MSM 0.0816; REL 0.0385; VID 0.2734; CONST 0.0000; lr 0.0001
639
+ iter 0126200; MSM 0.7201; REL 0.0384; VID 3.2974; CONST 0.0000; lr 0.0001
640
+ iter 0126400; MSM 0.1071; REL 0.0206; VID 0.0721; CONST 0.0000; lr 0.0001
641
+ iter 0126600; MSM 0.3389; REL 0.0000; VID 2.7731; CONST 0.0000; lr 0.0001
642
+ iter 0126800; MSM 0.1181; REL 0.0258; VID 0.1457; CONST 0.0000; lr 0.0001
643
+ iter 0127000; MSM 0.0774; REL 0.0289; VID 0.0553; CONST 0.0000; lr 0.0001
644
+ iter 0127200; MSM 0.0265; REL 0.0375; VID 0.0325; CONST 0.0000; lr 0.0001
645
+ iter 0127400; MSM 0.2119; REL 0.0066; VID 1.4923; CONST 0.0000; lr 0.0001
646
+ iter 0127600; MSM 0.1246; REL 0.0844; VID 0.1313; CONST 0.0000; lr 0.0001
647
+ iter 0127800; MSM 0.1047; REL 0.0339; VID 0.9134; CONST 0.0000; lr 0.0001
648
+ iter 0128000; MSM 0.1483; REL 0.0359; VID 1.8064; CONST 0.0000; lr 0.0001
649
+ iter 0128200; MSM 0.2191; REL 0.0000; VID 2.7734; CONST 0.0000; lr 0.0001
650
+ iter 0128400; MSM 0.0705; REL 0.0389; VID 0.2748; CONST 0.0000; lr 0.0001
651
+ iter 0128600; MSM 0.1403; REL 0.0324; VID 0.0710; CONST 0.0000; lr 0.0001
652
+ iter 0128800; MSM 0.1133; REL 0.0215; VID 0.3470; CONST 0.0000; lr 0.0001
653
+ iter 0129000; MSM 0.1673; REL 0.0074; VID 1.8140; CONST 0.0000; lr 0.0001
654
+ iter 0129200; MSM 0.2364; REL 0.0133; VID 1.4454; CONST 0.0000; lr 0.0001
655
+ iter 0129400; MSM 0.0633; REL 0.0120; VID 1.4659; CONST 0.0000; lr 0.0001
656
+ iter 0129600; MSM 0.0263; REL 0.8587; VID 0.0702; CONST 0.0000; lr 0.0001
657
+ iter 0129800; MSM 0.0677; REL 0.0249; VID 0.2897; CONST 0.0000; lr 0.0001
658
+ iter 0130000; MSM 0.0730; REL 0.0943; VID 0.7247; CONST 0.0000; lr 0.0001
659
+ iter 0130200; MSM 0.0364; REL 0.0206; VID 0.8306; CONST 0.0000; lr 0.0001
660
+ iter 0130400; MSM 0.0530; REL 0.0399; VID 0.0461; CONST 0.0000; lr 0.0001
661
+ iter 0130600; MSM 0.0544; REL 0.2726; VID 0.2666; CONST 0.0000; lr 0.0001
662
+ iter 0130800; MSM 0.1090; REL 0.1594; VID 0.1367; CONST 0.0000; lr 0.0001
663
+ iter 0131000; MSM 0.0680; REL 0.1300; VID 0.0803; CONST 0.0000; lr 0.0001
664
+ iter 0131200; MSM 0.0731; REL 0.0179; VID 0.0734; CONST 0.0000; lr 0.0001
665
+ iter 0131400; MSM 0.0342; REL 0.0292; VID 0.0934; CONST 0.0000; lr 0.0001
666
+ iter 0131600; MSM 0.0806; REL 0.0778; VID 1.6701; CONST 0.0000; lr 0.0001
667
+ iter 0131800; MSM 0.0716; REL 0.0180; VID 0.2600; CONST 0.0000; lr 0.0001
668
+ iter 0132000; MSM 0.1771; REL 0.0018; VID 0.0609; CONST 0.0000; lr 0.0001
669
+ iter 0132200; MSM 0.0328; REL 0.0068; VID 0.1186; CONST 0.0000; lr 0.0001
670
+ iter 0132400; MSM 0.4320; REL 0.0336; VID 1.5058; CONST 0.0000; lr 0.0001
671
+ iter 0132600; MSM 0.1017; REL 0.0011; VID 3.4442; CONST 0.0000; lr 0.0001
672
+ iter 0132800; MSM 0.0905; REL 0.0066; VID 0.9660; CONST 0.0000; lr 0.0001
673
+ iter 0133000; MSM 0.0836; REL 0.0087; VID 0.1026; CONST 0.0000; lr 0.0001
674
+ iter 0133200; MSM 0.0967; REL 0.0199; VID 1.0753; CONST 0.0000; lr 0.0001
675
+ iter 0133400; MSM 0.0274; REL 0.0623; VID 1.3595; CONST 0.0000; lr 0.0001
676
+ iter 0133600; MSM 0.0297; REL 0.0031; VID 0.1592; CONST 0.0000; lr 0.0001
677
+ iter 0133800; MSM 0.0845; REL 0.0604; VID 0.8617; CONST 0.0000; lr 0.0001
678
+ iter 0134000; MSM 0.0236; REL 0.0294; VID 0.2266; CONST 0.0000; lr 0.0001
679
+ iter 0134200; MSM 0.0743; REL 0.0360; VID 0.0679; CONST 0.0000; lr 0.0001
680
+ iter 0134400; MSM 0.0374; REL 2.9017; VID 0.0864; CONST 0.0000; lr 0.0001
681
+ iter 0134600; MSM 0.0771; REL 0.0125; VID 1.7894; CONST 0.0000; lr 0.0001
682
+ iter 0134800; MSM 0.0534; REL 0.0271; VID 0.0216; CONST 0.0000; lr 0.0001
683
+ iter 0135000; MSM 0.0895; REL 0.0142; VID 1.9902; CONST 0.0000; lr 0.0001
684
+ iter 0135200; MSM 0.0608; REL 0.0310; VID 1.6914; CONST 0.0000; lr 0.0001
685
+ iter 0135400; MSM 0.1221; REL 0.0287; VID 0.3220; CONST 0.0000; lr 0.0001
686
+ iter 0135600; MSM 0.0804; REL 0.0821; VID 0.1279; CONST 0.0000; lr 0.0001
687
+ iter 0135800; MSM 0.0569; REL 0.0202; VID 0.1385; CONST 0.0000; lr 0.0001
688
+ iter 0136000; MSM 0.0743; REL 0.1184; VID 0.3618; CONST 0.0000; lr 0.0001
689
+ iter 0136200; MSM 0.2137; REL 0.0012; VID 4.3003; CONST 0.0000; lr 0.0001
690
+ iter 0136400; MSM 0.0369; REL 0.0062; VID 0.0921; CONST 0.0000; lr 0.0001
691
+ iter 0136600; MSM 0.0545; REL 1.3999; VID 0.1254; CONST 0.0000; lr 0.0001
692
+ iter 0136800; MSM 0.0191; REL 1.3728; VID 0.2800; CONST 0.0000; lr 0.0001
693
+ iter 0137000; MSM 0.1203; REL 0.2287; VID 0.0617; CONST 0.0000; lr 0.0001
694
+ iter 0137200; MSM 0.0353; REL 0.0669; VID 0.0605; CONST 0.0000; lr 0.0001
695
+ iter 0137400; MSM 0.0915; REL 0.1235; VID 0.1534; CONST 0.0000; lr 0.0001
696
+ iter 0137600; MSM 0.0389; REL 0.0060; VID 1.0249; CONST 0.0000; lr 0.0001
697
+ iter 0137800; MSM 0.1577; REL 0.0136; VID 1.8998; CONST 0.0000; lr 0.0001
698
+ iter 0138000; MSM 0.0642; REL 0.0175; VID 0.1880; CONST 0.0000; lr 0.0001
699
+ iter 0138200; MSM 0.0996; REL 0.0686; VID 0.6848; CONST 0.0000; lr 0.0001
700
+ iter 0138400; MSM 0.0727; REL 0.0069; VID 0.8341; CONST 0.0000; lr 0.0001
701
+ iter 0138600; MSM 0.0340; REL 0.0093; VID 0.0885; CONST 0.0000; lr 0.0001
702
+ iter 0138800; MSM 0.1170; REL 0.0232; VID 0.1074; CONST 0.0000; lr 0.0001
703
+ iter 0139000; MSM 0.0348; REL 0.0272; VID 0.9927; CONST 0.0000; lr 0.0001
704
+ iter 0139200; MSM 0.0396; REL 0.0135; VID 0.1523; CONST 0.0000; lr 0.0001
705
+ iter 0139400; MSM 0.0170; REL 0.0476; VID 0.0492; CONST 0.0000; lr 0.0001
706
+ iter 0139600; MSM 0.0831; REL 0.0101; VID 0.1606; CONST 0.0000; lr 0.0001
707
+ iter 0139800; MSM 0.0829; REL 0.0198; VID 1.5026; CONST 0.0000; lr 0.0001
708
+ iter 0140000; MSM 0.0868; REL 0.0076; VID 0.1458; CONST 0.0000; lr 0.0001
709
+ iter 0140200; MSM 0.1018; REL 0.0423; VID 0.5995; CONST 0.0000; lr 0.0001
710
+ iter 0140400; MSM 0.0941; REL 0.1442; VID 0.0954; CONST 0.0000; lr 0.0001
711
+ iter 0140600; MSM 0.0784; REL 0.0031; VID 1.4524; CONST 0.0000; lr 0.0001
712
+ iter 0140800; MSM 0.0552; REL 0.0146; VID 0.4184; CONST 0.0000; lr 0.0001
713
+ iter 0141000; MSM 0.0729; REL 0.0720; VID 0.1914; CONST 0.0000; lr 0.0001
714
+ iter 0141200; MSM 0.0615; REL 0.0525; VID 1.4071; CONST 0.0000; lr 0.0001
715
+ iter 0141400; MSM 0.0671; REL 0.0128; VID 1.3496; CONST 0.0000; lr 0.0001
716
+ iter 0141600; MSM 0.1042; REL 0.0070; VID 0.1891; CONST 0.0000; lr 0.0001
717
+ iter 0141800; MSM 0.4333; REL 0.0235; VID 1.4829; CONST 0.0000; lr 0.0001
718
+ iter 0142000; MSM 0.1423; REL 0.0364; VID 0.5372; CONST 0.0000; lr 0.0001
719
+ iter 0142200; MSM 0.0736; REL 0.0947; VID 1.8423; CONST 0.0000; lr 0.0001
720
+ iter 0142400; MSM 0.0544; REL 0.0970; VID 0.9126; CONST 0.0000; lr 0.0001
721
+ iter 0142600; MSM 0.0705; REL 0.0153; VID 1.1580; CONST 0.0000; lr 0.0001
722
+ iter 0142800; MSM 0.0699; REL 0.0086; VID 0.2594; CONST 0.0000; lr 0.0001
723
+ iter 0143000; MSM 0.0612; REL 0.0035; VID 0.1692; CONST 0.0000; lr 0.0001
724
+ iter 0143200; MSM 0.1212; REL 0.0189; VID 1.7768; CONST 0.0000; lr 0.0001
725
+ iter 0143400; MSM 0.1024; REL 0.0146; VID 1.5418; CONST 0.0000; lr 0.0001
726
+ iter 0143600; MSM 0.0593; REL 0.0590; VID 0.2966; CONST 0.0000; lr 0.0001
727
+ iter 0143800; MSM 0.1136; REL 4.1799; VID 0.8346; CONST 0.0000; lr 0.0001
728
+ iter 0144000; MSM 0.1177; REL 0.0054; VID 0.0536; CONST 0.0000; lr 0.0001
729
+ iter 0144200; MSM 0.1616; REL 0.0218; VID 1.5042; CONST 0.0000; lr 0.0001
730
+ iter 0144400; MSM 0.0450; REL 0.1144; VID 1.4894; CONST 0.0000; lr 0.0001
731
+ iter 0144600; MSM 0.0676; REL 0.0192; VID 0.0630; CONST 0.0000; lr 0.0001
732
+ iter 0144800; MSM 0.0812; REL 5.0188; VID 0.2276; CONST 0.0000; lr 0.0001
733
+ iter 0145000; MSM 0.0274; REL 0.0024; VID 0.1637; CONST 0.0000; lr 0.0001
734
+ iter 0145200; MSM 0.2054; REL 0.0490; VID 0.1473; CONST 0.0000; lr 0.0001
735
+ iter 0145400; MSM 0.0247; REL 0.3075; VID 0.0852; CONST 0.0000; lr 0.0001
736
+ iter 0145600; MSM 0.0547; REL 0.0096; VID 1.9674; CONST 0.0000; lr 0.0001
737
+ iter 0145800; MSM 0.1133; REL 0.2978; VID 0.3298; CONST 0.0000; lr 0.0001
738
+ iter 0146000; MSM 0.0832; REL 0.0341; VID 0.2010; CONST 0.0000; lr 0.0001
739
+ iter 0146200; MSM 0.0419; REL 0.0101; VID 0.0637; CONST 0.0000; lr 0.0001
740
+ iter 0146400; MSM 0.0793; REL 0.0037; VID 0.0624; CONST 0.0000; lr 0.0001
741
+ iter 0146600; MSM 0.1299; REL 0.0052; VID 1.4691; CONST 0.0000; lr 0.0001
742
+ iter 0146800; MSM 0.1417; REL 0.0071; VID 1.4826; CONST 0.0000; lr 0.0001
743
+ iter 0147000; MSM 0.0983; REL 0.0208; VID 0.0805; CONST 0.0000; lr 0.0001
744
+ iter 0147200; MSM 0.2197; REL 0.0934; VID 0.0811; CONST 0.0000; lr 0.0001
745
+ iter 0147400; MSM 0.0970; REL 0.1439; VID 1.6085; CONST 0.0000; lr 0.0001
746
+ iter 0147600; MSM 0.0694; REL 0.0261; VID 0.0746; CONST 0.0000; lr 0.0001
747
+ iter 0147800; MSM 0.0290; REL 0.0019; VID 0.3193; CONST 0.0000; lr 0.0001
748
+ iter 0148000; MSM 0.0412; REL 0.0016; VID 0.0927; CONST 0.0000; lr 0.0001
749
+ iter 0148200; MSM 0.1322; REL 0.0107; VID 0.0233; CONST 0.0000; lr 0.0001
750
+ iter 0148400; MSM 0.0263; REL 0.0271; VID 0.1557; CONST 0.0000; lr 0.0001
751
+ iter 0148600; MSM 0.0399; REL 0.0670; VID 1.2888; CONST 0.0000; lr 0.0001
752
+ iter 0148800; MSM 0.1661; REL 0.0148; VID 1.5827; CONST 0.0000; lr 0.0001
753
+ iter 0149000; MSM 0.0553; REL 0.0096; VID 0.1610; CONST 0.0000; lr 0.0001
754
+ iter 0149200; MSM 0.0624; REL 0.0272; VID 0.0726; CONST 0.0000; lr 0.0001
755
+ iter 0149400; MSM 0.1446; REL 0.0166; VID 1.5069; CONST 0.0000; lr 0.0001
756
+ iter 0149600; MSM 0.0464; REL 0.0024; VID 0.3466; CONST 0.0000; lr 0.0001
757
+ iter 0149800; MSM 0.0668; REL 0.0464; VID 0.1150; CONST 0.0000; lr 0.0001
758
+ iter 0150000; MSM 0.0421; REL 1.1264; VID 1.5628; CONST 0.0000; lr 0.0001
759
+ iter 0150200; MSM 0.0666; REL 0.1063; VID 0.7016; CONST 0.0000; lr 0.0001
760
+ iter 0150400; MSM 0.0401; REL 0.0058; VID 0.1962; CONST 0.0000; lr 0.0001
761
+ iter 0150600; MSM 0.0543; REL 0.1340; VID 1.2892; CONST 0.0000; lr 0.0001
762
+ iter 0150800; MSM 0.0537; REL 0.0282; VID 0.0744; CONST 0.0000; lr 0.0001
763
+ iter 0151000; MSM 1.0867; REL 0.0234; VID 1.4358; CONST 0.0000; lr 0.0001
764
+ iter 0151200; MSM 0.0739; REL 0.0350; VID 1.4985; CONST 0.0000; lr 0.0001
765
+ iter 0151400; MSM 0.1033; REL 0.0362; VID 1.4699; CONST 0.0000; lr 0.0001
766
+ iter 0151600; MSM 0.8906; REL 0.0117; VID 1.7246; CONST 0.0000; lr 0.0001
767
+ iter 0151800; MSM 0.0820; REL 0.8196; VID 0.8952; CONST 0.0000; lr 0.0001
768
+ iter 0152000; MSM 0.2034; REL 0.0623; VID 1.5229; CONST 0.0000; lr 0.0001
769
+ iter 0152200; MSM 0.0516; REL 0.0096; VID 0.3455; CONST 0.0000; lr 0.0001
770
+ iter 0152400; MSM 0.1203; REL 0.0105; VID 3.0471; CONST 0.0000; lr 0.0001
771
+ iter 0152600; MSM 0.0854; REL 0.7374; VID 0.3528; CONST 0.0000; lr 0.0001
772
+ iter 0152800; MSM 0.0571; REL 0.2931; VID 1.5018; CONST 0.0000; lr 0.0001
773
+ iter 0153000; MSM 0.0786; REL 0.0173; VID 0.0649; CONST 0.0000; lr 0.0001
774
+ iter 0153200; MSM 0.0664; REL 0.0194; VID 0.1336; CONST 0.0000; lr 0.0001
775
+ iter 0153400; MSM 2.4369; REL 0.0066; VID 1.4948; CONST 0.0000; lr 0.0001
776
+ iter 0153600; MSM 0.0764; REL 0.0000; VID 2.7740; CONST 0.0000; lr 0.0001
777
+ iter 0153800; MSM 0.0658; REL 0.0341; VID 0.0748; CONST 0.0000; lr 0.0001
778
+ iter 0154000; MSM 0.1000; REL 4.6567; VID 1.8417; CONST 0.0000; lr 0.0001
779
+ iter 0154200; MSM 0.0441; REL 4.7187; VID 0.0617; CONST 0.0000; lr 0.0001
780
+ iter 0154400; MSM 0.0279; REL 0.0154; VID 0.0506; CONST 0.0000; lr 0.0001
781
+ iter 0154600; MSM 0.0480; REL 0.0080; VID 0.6881; CONST 0.0000; lr 0.0001
782
+ iter 0154800; MSM 0.0933; REL 0.0232; VID 0.1348; CONST 0.0000; lr 0.0001
783
+ iter 0155000; MSM 0.0480; REL 0.0154; VID 1.0776; CONST 0.0000; lr 0.0001
784
+ iter 0155200; MSM 0.0546; REL 0.0497; VID 0.5891; CONST 0.0000; lr 0.0001
785
+ iter 0155400; MSM 0.1643; REL 0.0672; VID 1.4545; CONST 0.0000; lr 0.0001
786
+ iter 0155600; MSM 0.1469; REL 0.0161; VID 0.9593; CONST 0.0000; lr 0.0001
787
+ iter 0155800; MSM 0.0452; REL 0.0107; VID 1.2100; CONST 0.0000; lr 0.0001
788
+ iter 0156000; MSM 0.1025; REL 0.0268; VID 0.1108; CONST 0.0000; lr 0.0001
789
+ iter 0156200; MSM 0.1049; REL 0.0025; VID 1.6169; CONST 0.0000; lr 0.0001
790
+ iter 0156400; MSM 0.0666; REL 0.0109; VID 3.1788; CONST 0.0000; lr 0.0001
791
+ iter 0156600; MSM 0.0656; REL 0.0116; VID 0.6463; CONST 0.0000; lr 0.0001
792
+ iter 0156800; MSM 0.0271; REL 1.9066; VID 0.0831; CONST 0.0000; lr 0.0001
793
+ iter 0157000; MSM 0.0543; REL 0.0146; VID 0.1439; CONST 0.0000; lr 0.0001
794
+ iter 0157200; MSM 0.0564; REL 0.0071; VID 0.1247; CONST 0.0000; lr 0.0001
795
+ iter 0157400; MSM 0.1461; REL 0.0257; VID 2.0726; CONST 0.0000; lr 0.0001
796
+ iter 0157600; MSM 0.1105; REL 0.0047; VID 0.2599; CONST 0.0000; lr 0.0001
797
+ iter 0157800; MSM 0.0631; REL 0.0037; VID 0.2186; CONST 0.0000; lr 0.0001
798
+ iter 0158000; MSM 0.0621; REL 0.0157; VID 0.0811; CONST 0.0000; lr 0.0001
799
+ iter 0158200; MSM 0.0595; REL 0.0239; VID 1.4139; CONST 0.0000; lr 0.0001
800
+ iter 0158400; MSM 1.5939; REL 0.0099; VID 1.4268; CONST 0.0000; lr 0.0001
801
+ iter 0158600; MSM 0.0368; REL 0.0043; VID 0.1559; CONST 0.0000; lr 0.0001
802
+ iter 0158800; MSM 0.0222; REL 0.0245; VID 0.1042; CONST 0.0000; lr 0.0001
803
+ iter 0159000; MSM 0.0239; REL 0.0056; VID 0.1683; CONST 0.0000; lr 0.0001
804
+ iter 0159200; MSM 0.0153; REL 0.0172; VID 1.2905; CONST 0.0000; lr 0.0001
805
+ iter 0159400; MSM 0.0753; REL 0.3953; VID 0.0768; CONST 0.0000; lr 0.0001
806
+ iter 0159600; MSM 0.0740; REL 2.6695; VID 1.4393; CONST 0.0000; lr 0.0001
807
+ iter 0159800; MSM 0.0325; REL 3.4335; VID 1.2947; CONST 0.0000; lr 0.0001
808
+ iter 0160000; MSM 0.0779; REL 0.0235; VID 1.5435; CONST 0.0000; lr 0.0001
809
+ iter 0160200; MSM 0.0450; REL 0.0519; VID 0.0782; CONST 0.0000; lr 0.0001
810
+ iter 0160400; MSM 0.1021; REL 0.0039; VID 2.7838; CONST 0.0000; lr 0.0001
811
+ iter 0160600; MSM 0.0169; REL 0.8952; VID 0.0439; CONST 0.0000; lr 0.0001
812
+ iter 0160800; MSM 0.0841; REL 0.0089; VID 0.1548; CONST 0.0000; lr 0.0001
813
+ iter 0161000; MSM 0.0272; REL 0.0302; VID 0.1882; CONST 0.0000; lr 0.0001
814
+ iter 0161200; MSM 1.1727; REL 2.4885; VID 1.4915; CONST 0.0000; lr 0.0001
815
+ iter 0161400; MSM 0.0293; REL 0.0499; VID 0.2037; CONST 0.0000; lr 0.0001
816
+ iter 0161600; MSM 0.0979; REL 0.0616; VID 0.7780; CONST 0.0000; lr 0.0001
817
+ iter 0161800; MSM 0.1259; REL 0.0064; VID 0.3771; CONST 0.0000; lr 0.0001
818
+ iter 0162000; MSM 0.1210; REL 0.0437; VID 1.4384; CONST 0.0000; lr 0.0001
819
+ iter 0162200; MSM 0.0315; REL 0.0081; VID 1.5461; CONST 0.0000; lr 0.0001
820
+ iter 0162400; MSM 0.0583; REL 0.0296; VID 1.4656; CONST 0.0000; lr 0.0001
821
+ iter 0162600; MSM 0.0534; REL 0.0192; VID 1.3845; CONST 0.0000; lr 0.0001
822
+ iter 0162800; MSM 0.0437; REL 0.0235; VID 0.0961; CONST 0.0000; lr 0.0001
823
+ iter 0163000; MSM 0.1043; REL 0.0110; VID 0.1283; CONST 0.0000; lr 0.0001
824
+ iter 0163200; MSM 0.0834; REL 0.0088; VID 1.4613; CONST 0.0000; lr 0.0001
825
+ iter 0163400; MSM 0.0583; REL 0.0111; VID 1.4308; CONST 0.0000; lr 0.0001
826
+ iter 0163600; MSM 0.0525; REL 0.0171; VID 0.9069; CONST 0.0000; lr 0.0001
827
+ iter 0163800; MSM 0.0343; REL 0.3697; VID 0.0477; CONST 0.0000; lr 0.0001
828
+ iter 0164000; MSM 0.0513; REL 0.0075; VID 1.4269; CONST 0.0000; lr 0.0001
829
+ iter 0164200; MSM 0.1727; REL 0.0389; VID 0.0628; CONST 0.0000; lr 0.0001
830
+ iter 0164400; MSM 0.0781; REL 0.0409; VID 0.0974; CONST 0.0000; lr 0.0001
831
+ iter 0164600; MSM 0.0657; REL 0.0223; VID 0.2472; CONST 0.0000; lr 0.0001
832
+ iter 0164800; MSM 0.0214; REL 0.0092; VID 1.5831; CONST 0.0000; lr 0.0001
833
+ iter 0165000; MSM 0.0629; REL 0.0604; VID 0.8094; CONST 0.0000; lr 0.0001
834
+ iter 0165200; MSM 0.0944; REL 0.0785; VID 1.4297; CONST 0.0000; lr 0.0001
835
+ iter 0165400; MSM 0.0902; REL 0.0087; VID 1.4210; CONST 0.0000; lr 0.0001
836
+ iter 0165600; MSM 0.0454; REL 0.0083; VID 0.8410; CONST 0.0000; lr 0.0001
837
+ iter 0165800; MSM 0.0549; REL 0.0027; VID 0.1422; CONST 0.0000; lr 0.0001
838
+ iter 0166000; MSM 0.0558; REL 0.0074; VID 0.0355; CONST 0.0000; lr 0.0001
839
+ iter 0166200; MSM 0.0309; REL 0.0168; VID 0.6831; CONST 0.0000; lr 0.0001
840
+ iter 0166400; MSM 0.1133; REL 0.3074; VID 0.0450; CONST 0.0000; lr 0.0001
841
+ iter 0166600; MSM 0.1140; REL 0.0135; VID 0.8225; CONST 0.0000; lr 0.0001
842
+ iter 0166800; MSM 0.0710; REL 0.0595; VID 0.0315; CONST 0.0000; lr 0.0001
843
+ iter 0167000; MSM 0.0574; REL 0.0055; VID 0.0362; CONST 0.0000; lr 0.0001
844
+ iter 0167200; MSM 0.0428; REL 0.0132; VID 0.0933; CONST 0.0000; lr 0.0001
845
+ iter 0167400; MSM 0.0470; REL 0.2155; VID 0.1351; CONST 0.0000; lr 0.0001
846
+ iter 0167600; MSM 0.0339; REL 0.0218; VID 0.0452; CONST 0.0000; lr 0.0001
847
+ iter 0167800; MSM 0.0828; REL 0.0170; VID 0.1198; CONST 0.0000; lr 0.0001
848
+ iter 0168000; MSM 0.0729; REL 0.2375; VID 0.2014; CONST 0.0000; lr 0.0001
849
+ iter 0168200; MSM 0.0477; REL 3.7902; VID 0.8823; CONST 0.0000; lr 0.0001
850
+ iter 0168400; MSM 0.0208; REL 0.0056; VID 0.1950; CONST 0.0000; lr 0.0001
851
+ iter 0168600; MSM 0.0348; REL 0.0163; VID 0.0495; CONST 0.0000; lr 0.0001
852
+ iter 0168800; MSM 0.0535; REL 0.0175; VID 0.0692; CONST 0.0000; lr 0.0001
853
+ iter 0169000; MSM 0.0483; REL 3.2906; VID 0.0588; CONST 0.0000; lr 0.0001
854
+ iter 0169200; MSM 0.0598; REL 0.0094; VID 0.0691; CONST 0.0000; lr 0.0001
855
+ iter 0169400; MSM 0.0368; REL 0.0027; VID 0.1106; CONST 0.0000; lr 0.0001
856
+ iter 0169600; MSM 0.0452; REL 0.3810; VID 2.7093; CONST 0.0000; lr 0.0001
857
+ iter 0169800; MSM 0.1090; REL 0.0238; VID 1.4785; CONST 0.0000; lr 0.0001
858
+ iter 0170000; MSM 0.0612; REL 3.2868; VID 0.1274; CONST 0.0000; lr 0.0001
859
+ iter 0170200; MSM 0.0976; REL 0.0159; VID 1.1900; CONST 0.0000; lr 0.0001
860
+ iter 0170400; MSM 0.0551; REL 0.0152; VID 0.6120; CONST 0.0000; lr 0.0001
861
+ iter 0170600; MSM 0.0420; REL 0.0117; VID 0.1324; CONST 0.0000; lr 0.0001
862
+ iter 0170800; MSM 0.0503; REL 0.0187; VID 0.1270; CONST 0.0000; lr 0.0001
863
+ iter 0171000; MSM 0.0479; REL 0.0134; VID 0.8867; CONST 0.0000; lr 0.0001
864
+ iter 0171200; MSM 0.0515; REL 0.0097; VID 0.1166; CONST 0.0000; lr 0.0001
865
+ iter 0171400; MSM 0.0811; REL 0.1205; VID 0.3153; CONST 0.0000; lr 0.0001
866
+ iter 0171600; MSM 0.0375; REL 0.0189; VID 0.3177; CONST 0.0000; lr 0.0001
867
+ iter 0171800; MSM 0.0975; REL 4.6046; VID 1.6741; CONST 0.0000; lr 0.0001
868
+ iter 0172000; MSM 0.0630; REL 0.0138; VID 0.0538; CONST 0.0000; lr 0.0001
869
+ iter 0172200; MSM 0.0462; REL 0.0048; VID 0.1541; CONST 0.0000; lr 0.0001
870
+ iter 0172400; MSM 0.0394; REL 0.0752; VID 0.0506; CONST 0.0000; lr 0.0001
871
+ iter 0172600; MSM 0.0801; REL 0.0293; VID 1.4325; CONST 0.0000; lr 0.0001
872
+ iter 0172800; MSM 0.0691; REL 0.3758; VID 0.2156; CONST 0.0000; lr 0.0001
873
+ iter 0173000; MSM 0.0475; REL 0.0288; VID 0.7728; CONST 0.0000; lr 0.0001
874
+ iter 0173200; MSM 0.0790; REL 0.0039; VID 0.8106; CONST 0.0000; lr 0.0001
875
+ iter 0173400; MSM 0.0753; REL 0.0055; VID 0.8349; CONST 0.0000; lr 0.0001
876
+ iter 0173600; MSM 0.0327; REL 0.0094; VID 0.3839; CONST 0.0000; lr 0.0001
877
+ iter 0173800; MSM 0.1078; REL 0.0050; VID 0.0253; CONST 0.0000; lr 0.0001
878
+ iter 0174000; MSM 0.0649; REL 0.0174; VID 0.3197; CONST 0.0000; lr 0.0001
879
+ iter 0174200; MSM 0.0227; REL 0.0200; VID 0.1190; CONST 0.0000; lr 0.0001
880
+ iter 0174400; MSM 0.0555; REL 0.0211; VID 0.7340; CONST 0.0000; lr 0.0001
881
+ iter 0174600; MSM 0.0446; REL 0.2769; VID 1.8779; CONST 0.0000; lr 0.0001
882
+ iter 0174800; MSM 0.0342; REL 0.0027; VID 0.0380; CONST 0.0000; lr 0.0001
883
+ iter 0175000; MSM 0.0410; REL 0.0076; VID 0.6792; CONST 0.0000; lr 0.0001
884
+ iter 0175200; MSM 0.0530; REL 0.0099; VID 0.6733; CONST 0.0000; lr 0.0001
885
+ iter 0175400; MSM 0.0320; REL 0.0426; VID 1.4602; CONST 0.0000; lr 0.0001
886
+ iter 0175600; MSM 0.0796; REL 0.0432; VID 1.7816; CONST 0.0000; lr 0.0001
887
+ iter 0175800; MSM 0.1312; REL 0.0184; VID 0.0910; CONST 0.0000; lr 0.0001
888
+ iter 0176000; MSM 0.0432; REL 0.0124; VID 0.5986; CONST 0.0000; lr 0.0001
889
+ iter 0176200; MSM 0.0790; REL 0.0015; VID 1.5356; CONST 0.0000; lr 0.0001
890
+ iter 0176400; MSM 0.0723; REL 0.0242; VID 0.0389; CONST 0.0000; lr 0.0001
891
+ iter 0176600; MSM 0.0404; REL 0.4054; VID 0.2268; CONST 0.0000; lr 0.0001
892
+ iter 0176800; MSM 0.0874; REL 0.0255; VID 0.0597; CONST 0.0000; lr 0.0001
893
+ iter 0177000; MSM 0.3272; REL 0.0032; VID 0.2147; CONST 0.0000; lr 0.0001
894
+ iter 0177200; MSM 0.2376; REL 0.0620; VID 0.1163; CONST 0.0000; lr 0.0001
895
+ iter 0177400; MSM 0.0744; REL 0.0507; VID 0.0606; CONST 0.0000; lr 0.0001
896
+ iter 0177600; MSM 0.1170; REL 0.0276; VID 0.7705; CONST 0.0000; lr 0.0001
897
+ iter 0177800; MSM 0.0978; REL 0.0021; VID 0.0236; CONST 0.0000; lr 0.0001
898
+ iter 0178000; MSM 1.0003; REL 0.0021; VID 1.4051; CONST 0.0000; lr 0.0001
899
+ iter 0178200; MSM 0.0654; REL 0.0135; VID 1.2558; CONST 0.0000; lr 0.0001
900
+ iter 0178400; MSM 0.0965; REL 0.0106; VID 0.7536; CONST 0.0000; lr 0.0001
901
+ iter 0178600; MSM 0.1293; REL 0.0133; VID 0.0449; CONST 0.0000; lr 0.0001
902
+ iter 0178800; MSM 0.0529; REL 0.1190; VID 1.4007; CONST 0.0000; lr 0.0001
903
+ iter 0179000; MSM 0.0688; REL 0.0271; VID 0.0666; CONST 0.0000; lr 0.0001
904
+ iter 0179200; MSM 0.1270; REL 0.0360; VID 1.6120; CONST 0.0000; lr 0.0001
905
+ iter 0179400; MSM 0.2628; REL 0.0056; VID 0.0962; CONST 0.0000; lr 0.0001
906
+ iter 0179600; MSM 0.0499; REL 0.0229; VID 0.1274; CONST 0.0000; lr 0.0001
907
+ iter 0179800; MSM 0.1644; REL 0.0049; VID 0.0551; CONST 0.0000; lr 0.0001
908
+ iter 0180000; MSM 0.0672; REL 0.3354; VID 1.4426; CONST 0.0000; lr 0.0001
909
+ iter 0180200; MSM 0.0525; REL 0.0021; VID 1.0858; CONST 0.0000; lr 0.0001
910
+ iter 0180400; MSM 0.0701; REL 0.0056; VID 0.0488; CONST 0.0000; lr 0.0001
911
+ iter 0180600; MSM 0.0215; REL 0.0134; VID 0.1066; CONST 0.0000; lr 0.0001
912
+ iter 0180800; MSM 0.0413; REL 0.0023; VID 0.1553; CONST 0.0000; lr 0.0001
913
+ iter 0181000; MSM 0.0990; REL 0.3896; VID 0.0808; CONST 0.0000; lr 0.0001
914
+ iter 0181200; MSM 0.0463; REL 0.0059; VID 1.4351; CONST 0.0000; lr 0.0001
915
+ iter 0181400; MSM 0.0520; REL 0.0454; VID 0.1060; CONST 0.0000; lr 0.0001
916
+ iter 0181600; MSM 0.1780; REL 0.0087; VID 0.0898; CONST 0.0000; lr 0.0001
917
+ iter 0181800; MSM 0.0742; REL 0.0037; VID 0.0945; CONST 0.0000; lr 0.0001
918
+ iter 0182000; MSM 0.0770; REL 0.0099; VID 0.0902; CONST 0.0000; lr 0.0001
919
+ iter 0182200; MSM 0.0180; REL 0.0055; VID 1.5491; CONST 0.0000; lr 0.0001
920
+ iter 0182400; MSM 0.0116; REL 0.1137; VID 0.0553; CONST 0.0000; lr 0.0001
921
+ iter 0182600; MSM 0.1037; REL 0.0235; VID 0.0214; CONST 0.0000; lr 0.0001
922
+ iter 0182800; MSM 0.0399; REL 0.0056; VID 1.7640; CONST 0.0000; lr 0.0001
923
+ iter 0183000; MSM 0.0467; REL 3.8594; VID 0.2215; CONST 0.0000; lr 0.0001
924
+ iter 0183200; MSM 0.0488; REL 0.0101; VID 0.0693; CONST 0.0000; lr 0.0001
925
+ iter 0183400; MSM 0.0940; REL 0.0461; VID 4.5127; CONST 0.0000; lr 0.0001
926
+ iter 0183600; MSM 0.0639; REL 0.1391; VID 0.1513; CONST 0.0000; lr 0.0001
927
+ iter 0183800; MSM 0.0970; REL 0.0047; VID 0.1835; CONST 0.0000; lr 0.0001
928
+ iter 0184000; MSM 0.0426; REL 0.0278; VID 0.8590; CONST 0.0000; lr 0.0001
929
+ iter 0184200; MSM 0.1157; REL 0.0747; VID 0.0608; CONST 0.0000; lr 0.0001
930
+ iter 0184400; MSM 0.1133; REL 0.0207; VID 1.2683; CONST 0.0000; lr 0.0001
931
+ iter 0184600; MSM 0.0259; REL 0.0056; VID 0.0408; CONST 0.0000; lr 0.0001
932
+ iter 0184800; MSM 0.1004; REL 2.9718; VID 4.0035; CONST 0.0000; lr 0.0001
933
+ iter 0185000; MSM 0.0289; REL 0.0161; VID 0.0838; CONST 0.0000; lr 0.0001
934
+ iter 0185200; MSM 0.0465; REL 0.0076; VID 0.0415; CONST 0.0000; lr 0.0001
935
+ iter 0185400; MSM 0.0370; REL 0.0042; VID 0.7021; CONST 0.0000; lr 0.0001
936
+ iter 0185600; MSM 0.0572; REL 0.0102; VID 0.1164; CONST 0.0000; lr 0.0001
937
+ iter 0185800; MSM 0.0492; REL 0.0157; VID 0.0531; CONST 0.0000; lr 0.0001
938
+ iter 0186000; MSM 0.0427; REL 0.0093; VID 1.7909; CONST 0.0000; lr 0.0001
939
+ iter 0186200; MSM 0.0230; REL 0.0076; VID 1.1720; CONST 0.0000; lr 0.0001
940
+ iter 0186400; MSM 0.0350; REL 0.0142; VID 0.0234; CONST 0.0000; lr 0.0001
941
+ iter 0186600; MSM 0.0547; REL 0.0313; VID 0.3184; CONST 0.0000; lr 0.0001
942
+ iter 0186800; MSM 0.0617; REL 0.0079; VID 0.0705; CONST 0.0000; lr 0.0001
943
+ iter 0187000; MSM 0.0295; REL 0.0162; VID 0.0423; CONST 0.0000; lr 0.0001
944
+ iter 0187200; MSM 0.0906; REL 0.0093; VID 0.0793; CONST 0.0000; lr 0.0001
945
+ iter 0187400; MSM 0.0139; REL 0.0051; VID 0.0538; CONST 0.0000; lr 0.0001
946
+ iter 0187600; MSM 0.0308; REL 0.0272; VID 0.2298; CONST 0.0000; lr 0.0001
947
+ iter 0187800; MSM 0.1130; REL 0.0162; VID 0.0288; CONST 0.0000; lr 0.0001
948
+ iter 0188000; MSM 0.0840; REL 0.0214; VID 0.1676; CONST 0.0000; lr 0.0001
949
+ iter 0188200; MSM 0.0388; REL 0.0093; VID 0.0625; CONST 0.0000; lr 0.0001
950
+ iter 0188400; MSM 0.0892; REL 0.0451; VID 0.8465; CONST 0.0000; lr 0.0001
951
+ iter 0188600; MSM 0.1160; REL 0.0082; VID 0.0504; CONST 0.0000; lr 0.0001
952
+ iter 0188800; MSM 0.0381; REL 0.1701; VID 0.0271; CONST 0.0000; lr 0.0001
953
+ iter 0189000; MSM 0.0498; REL 0.0223; VID 1.3956; CONST 0.0000; lr 0.0001
954
+ iter 0189200; MSM 0.0473; REL 0.0078; VID 0.4238; CONST 0.0000; lr 0.0001
955
+ iter 0189400; MSM 0.0686; REL 0.0237; VID 1.6829; CONST 0.0000; lr 0.0001
956
+ iter 0189600; MSM 0.0190; REL 0.5529; VID 1.6591; CONST 0.0000; lr 0.0001
957
+ iter 0189800; MSM 0.0542; REL 0.0043; VID 0.0402; CONST 0.0000; lr 0.0001
958
+ iter 0190000; MSM 0.0214; REL 0.6901; VID 0.0321; CONST 0.0000; lr 0.0001
959
+ iter 0190200; MSM 0.0749; REL 0.0293; VID 0.0694; CONST 0.0000; lr 0.0001
960
+ iter 0190400; MSM 0.1258; REL 0.0139; VID 0.0294; CONST 0.0000; lr 0.0001
961
+ iter 0190600; MSM 0.0265; REL 0.0058; VID 0.0959; CONST 0.0000; lr 0.0001
962
+ iter 0190800; MSM 0.1472; REL 0.0149; VID 1.9790; CONST 0.0000; lr 0.0001
963
+ iter 0191000; MSM 0.1249; REL 0.0163; VID 0.8729; CONST 0.0000; lr 0.0001
964
+ iter 0191200; MSM 0.0262; REL 0.0126; VID 0.1434; CONST 0.0000; lr 0.0001
965
+ iter 0191400; MSM 0.0446; REL 0.0143; VID 0.0433; CONST 0.0000; lr 0.0001
966
+ iter 0191600; MSM 0.0457; REL 0.0053; VID 0.0880; CONST 0.0000; lr 0.0001
967
+ iter 0191800; MSM 0.0539; REL 0.0112; VID 0.2351; CONST 0.0000; lr 0.0001
968
+ iter 0192000; MSM 0.0643; REL 0.0043; VID 0.0635; CONST 0.0000; lr 0.0001
969
+ iter 0192200; MSM 0.0199; REL 0.0203; VID 1.4245; CONST 0.0000; lr 0.0001
970
+ iter 0192400; MSM 0.0471; REL 0.1410; VID 0.0813; CONST 0.0000; lr 0.0001
971
+ iter 0192600; MSM 0.1839; REL 0.3834; VID 0.0854; CONST 0.0000; lr 0.0001
972
+ iter 0192800; MSM 0.1191; REL 0.0271; VID 1.4159; CONST 0.0000; lr 0.0001
973
+ iter 0193000; MSM 0.0784; REL 0.0051; VID 1.4866; CONST 0.0000; lr 0.0001
974
+ iter 0193200; MSM 0.1098; REL 0.0200; VID 0.0329; CONST 0.0000; lr 0.0001
975
+ iter 0193400; MSM 0.0381; REL 0.0297; VID 0.1591; CONST 0.0000; lr 0.0001
976
+ iter 0193600; MSM 0.2797; REL 0.0381; VID 1.8439; CONST 0.0000; lr 0.0001
977
+ iter 0193800; MSM 0.0544; REL 0.0254; VID 3.6698; CONST 0.0000; lr 0.0001
978
+ iter 0194000; MSM 0.0514; REL 0.0204; VID 0.0352; CONST 0.0000; lr 0.0001
979
+ iter 0194200; MSM 0.0908; REL 0.0026; VID 1.4729; CONST 0.0000; lr 0.0001
980
+ iter 0194400; MSM 0.0691; REL 0.0085; VID 0.8850; CONST 0.0000; lr 0.0001
981
+ iter 0194600; MSM 0.0614; REL 0.0111; VID 0.0714; CONST 0.0000; lr 0.0001
982
+ iter 0194800; MSM 0.0978; REL 0.0095; VID 0.1037; CONST 0.0000; lr 0.0001
983
+ iter 0195000; MSM 0.0591; REL 0.1987; VID 0.1044; CONST 0.0000; lr 0.0001
984
+ iter 0195200; MSM 0.0656; REL 0.0034; VID 1.5324; CONST 0.0000; lr 0.0001
985
+ iter 0195400; MSM 0.0198; REL 0.0699; VID 0.0337; CONST 0.0000; lr 0.0001
986
+ iter 0195600; MSM 0.0669; REL 0.0030; VID 1.4273; CONST 0.0000; lr 0.0001
987
+ iter 0195800; MSM 0.0126; REL 0.0660; VID 0.0267; CONST 0.0000; lr 0.0001
988
+ iter 0196000; MSM 0.2760; REL 0.0620; VID 0.0308; CONST 0.0000; lr 0.0001
989
+ iter 0196200; MSM 0.0880; REL 2.2863; VID 0.1108; CONST 0.0000; lr 0.0001
990
+ iter 0196400; MSM 0.0398; REL 0.0170; VID 0.5002; CONST 0.0000; lr 0.0001
991
+ iter 0196600; MSM 0.0302; REL 0.0080; VID 0.1573; CONST 0.0000; lr 0.0001
992
+ iter 0196800; MSM 0.1055; REL 0.0188; VID 1.4155; CONST 0.0000; lr 0.0001
993
+ iter 0197000; MSM 0.0606; REL 0.0409; VID 0.1642; CONST 0.0000; lr 0.0001
994
+ iter 0197200; MSM 0.0754; REL 0.0110; VID 0.0648; CONST 0.0000; lr 0.0001
995
+ iter 0197400; MSM 0.0534; REL 0.0051; VID 0.6536; CONST 0.0000; lr 0.0001
996
+ iter 0197600; MSM 0.1112; REL 0.0021; VID 2.1521; CONST 0.0000; lr 0.0001
997
+ iter 0197800; MSM 0.0525; REL 0.1024; VID 0.0552; CONST 0.0000; lr 0.0001
998
+ iter 0198000; MSM 0.0643; REL 0.0387; VID 0.9123; CONST 0.0000; lr 0.0001
999
+ iter 0198200; MSM 0.0766; REL 2.6710; VID 0.0567; CONST 0.0000; lr 0.0001
1000
+ iter 0198400; MSM 0.0344; REL 0.0064; VID 1.2951; CONST 0.0000; lr 0.0001
1001
+ iter 0198600; MSM 0.0273; REL 0.0040; VID 0.0699; CONST 0.0000; lr 0.0001
1002
+ iter 0198800; MSM 0.0251; REL 0.0099; VID 0.0374; CONST 0.0000; lr 0.0001
1003
+ iter 0199000; MSM 0.1095; REL 0.0027; VID 1.4446; CONST 0.0000; lr 0.0001
1004
+ iter 0199200; MSM 0.0620; REL 0.0289; VID 0.0491; CONST 0.0000; lr 0.0001
1005
+ iter 0199400; MSM 0.0697; REL 0.0153; VID 1.4263; CONST 0.0000; lr 0.0001
1006
+ iter 0199600; MSM 0.2364; REL 0.0023; VID 0.0216; CONST 0.0000; lr 0.0001
1007
+ iter 0199800; MSM 0.0348; REL 2.8578; VID 1.4539; CONST 0.0000; lr 0.0001