20075618707

Committed 09 Dec 2025 07:16PM UTC coverage: 96.949% (-0.8%) from 97.767%

Build # 20075618707

Build Type

Pull #109

github

Committed by

tonegas

Commit Message

Improved the coverage on train

Pull Request Pull Request #109: New version of nnodely

Run Details

878 of 893 new or added lines in 37 files covered. (98.32%)

157 existing lines in 5 files now uncovered.

13091 of 13503 relevant lines covered (96.95%)

0.97 hits per line

Source File
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93.1

/nnodely/visualizer/emptyvisualizer.py

from nnodely.support.logger import logging, nnLogger

log = nnLogger(__name__, logging.INFO)

RESET_SEQ = "\033[0m"
COLOR_SEQ = "\033[%dm"
COLOR_BOLD_SEQ = "\033[1;%dm"
BOLD_SEQ = "\033[1m"
BLACK, RED, GREEN, YELLOW, BLUE, MAGENTA, CYAN, WHITE = range(8)

def color(msg, color_val = GREEN, bold = False):
    if bold:
        return COLOR_BOLD_SEQ % (30 + color_val) + msg + RESET_SEQ
    return COLOR_SEQ % (30 + color_val) + msg + RESET_SEQ

class EmptyVisualizer:
    def __init__(self):
        pass

    def setModely(self, modely):
        self.modely = modely

    def showModel(self, model):
        pass

    def showaddMinimize(self,variable_name):
        pass

    def showModelInputWindow(self):
        pass

    def showModelRelationSamples(self):
        pass

    def showBuiltModel(self):
        pass

    def showWeights(self, weights = None):
        pass

    def showFunctions(self, functions = None):
        pass

    def showWeightsInTrain(self, batch = None, epoch = None, weights = None):
        pass

    def showDataset(self, name):
        pass

    def showStartTraining(self):
        pass

    def showTraining(self, epoch, train_losses, val_losses):
        pass

    def showEndTraining(self, epoch, train_losses, val_losses):
        pass

    def showTrainParams(self):
        pass

    def showTrainingTime(self, time):
        pass

    def showResult(self, name_data):
        pass

    def showResults(self):
        pass

    def saveModel(self, name, path):
        pass

    def loadModel(self, name, path):
        pass

    def exportModel(self, name, path):
        pass

    def importModel(self, name, path):
        pass

    def exportReport(self, name, path):
        pass

1	from nnodely.support.logger import logging, nnLogger	1✔
2
3	log = nnLogger(__name__, logging.INFO)	1✔
4
5	RESET_SEQ = "\033[0m"	1✔
6	COLOR_SEQ = "\033[%dm"	1✔
7	COLOR_BOLD_SEQ = "\033[1;%dm"	1✔
8	BOLD_SEQ = "\033[1m"	1✔
9	BLACK, RED, GREEN, YELLOW, BLUE, MAGENTA, CYAN, WHITE = range(8)	1✔
10
11	def color(msg, color_val = GREEN, bold = False):	1✔
12	if bold:	1✔
13	return COLOR_BOLD_SEQ % (30 + color_val) + msg + RESET_SEQ	1✔
14	return COLOR_SEQ % (30 + color_val) + msg + RESET_SEQ	1✔
15
16	class EmptyVisualizer:	1✔
17	def __init__(self):	1✔
18	pass	1✔
19
20	def setModely(self, modely):	1✔
21	self.modely = modely	1✔
22
23	def showModel(self, model):	1✔
24	pass	1✔
25
26	def showaddMinimize(self,variable_name):	1✔
27	pass	1✔
28
29	def showModelInputWindow(self):	1✔
30	pass	1✔
31
32	def showModelRelationSamples(self):	1✔
33	pass	×
34
35	def showBuiltModel(self):	1✔
36	pass	1✔
37
38	def showWeights(self, weights = None):	1✔
39	pass	×
40
41	def showFunctions(self, functions = None):	1✔
42	pass	×
43
44	def showWeightsInTrain(self, batch = None, epoch = None, weights = None):	1✔
45	pass	1✔
46
47	def showDataset(self, name):	1✔
48	pass	1✔
49
50	def showStartTraining(self):	1✔
51	pass	1✔
52
53	def showTraining(self, epoch, train_losses, val_losses):	1✔
54	pass	1✔
55
56	def showEndTraining(self, epoch, train_losses, val_losses):	1✔
57	pass	1✔
58
59	def showTrainParams(self):	1✔
60	pass	1✔
61
62	def showTrainingTime(self, time):	1✔
63	pass	1✔
64
65	def showResult(self, name_data):	1✔
66	pass	1✔
67
68	def showResults(self):	1✔
UNCOV 69	pass	×
70
71	def saveModel(self, name, path):	1✔
72	pass	1✔
73
74	def loadModel(self, name, path):	1✔
75	pass	1✔
76
77	def exportModel(self, name, path):	1✔
78	pass	1✔
79
80	def importModel(self, name, path):	1✔
81	pass	1✔
82
83	def exportReport(self, name, path):	1✔
84	pass	1✔

tonegas / nnodely / 20075618707

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