14319828903

Committed 07 Apr 2025 09:27PM UTC coverage: 97.259% (+0.2%) from 97.035%

Build # 14319828903

Build Type

Pull #86

github

Committed by

web-flow

Commit Message

Merge 44b7c25ee into e9c323c4f

Pull Request Pull Request #86: Smallclasses

Run Details

2275 of 2409 new or added lines in 54 files covered. (94.44%)

1 existing line in 1 file now uncovered.

11637 of 11965 relevant lines covered (97.26%)

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94.29

/nnodely/nnodely.py

# Extern packages
import random, torch
import numpy as np

# Main operators
from nnodely.operators.network import Network
from nnodely.operators.trainer import Trainer
from nnodely.operators.loader import Loader
from nnodely.operators.validator import Validator
from nnodely.operators.exporter import Exporter

# nnodely packages
from nnodely.visualizer import TextVisualizer, Visualizer
from nnodely.basic.modeldef import ModelDef
from nnodely.basic.relation import NeuObj

from nnodely.support.utils import ReadOnlyDict

from nnodely.support.logger import logging, nnLogger
log = nnLogger(__name__, logging.INFO)


def clearNames(names:str|None = None):
    NeuObj.clearNames(names)

class Modely(Network, Trainer, Loader, Validator, Exporter):
    """
    Create the main object, the nnodely object, that will be used to create the network, train and export it.

    Parameters
    ----------
    visualizer : str, Visualizer, optional
        The visualizer to be used. Default is the 'Standard' visualizer.
    exporter : str, Exporter, optional
        The exporter to be used. Default is the 'Standard' exporter.
    seed : int, optional
        Set the seed for all the random modules inside the nnodely framework. Default is None.
    workspace : str
        The path of the workspace where all the exported files will be saved.
    log_internal : bool
        Whether or not save the logs. Default is False.
    save_history : bool
        Whether or not save the history. Default is False.

    Example
    -------
        >>> model = Modely()
    """
    def __init__(self,
                 visualizer:str|Visualizer|None = 'Standard',
                 exporter:str|Exporter|None = 'Standard',
                 seed:int|None = None,
                 workspace:str|None = None,
                 log_internal:bool = False,
                 save_history:bool = False):

        # Visualizer
        if visualizer == 'Standard':
            self.visualizer = TextVisualizer(1)
        elif visualizer != None:
            self.visualizer = visualizer
        else:
            self.visualizer = Visualizer()
        self.visualizer.setModely(self)

        ## Set the random seed for reproducibility
        if seed is not None:
            self.resetSeed(seed)

        # Save internal
        self.log_internal = log_internal
        if self.log_internal == True:
            self.internals = {}

        # Models definition
        self._model_def = ModelDef()
        self._model = None
        self._neuralized = False
        self._traced = False

        Network.__init__(self)
        Loader.__init__(self)
        Trainer.__init__(self)
        Validator.__init__(self)
        Exporter.__init__(self, exporter, workspace, save_history=save_history)

    @property
    def neuralized(self):
        return self._neuralized

    @neuralized.setter
    def neuralized(self, value):
        raise AttributeError("Cannot modify read-only property 'neuralized' use neuralizeModel() instead.")

    @property
    def traced(self):
        return self._traced

    @traced.setter
    def traced(self, value):
        raise AttributeError("Cannot modify read-only property 'traced'.")

    @property
    def parameters(self):
        return ReadOnlyDict({key:value.detach().numpy().tolist() for key,value in self._model.all_parameters.items()})

    @property
    def constants(self):
        return ReadOnlyDict({key:value.detach().numpy().tolist() for key,value in self._model.all_constants})

    @property
    def states(self):
        return {key:value.detach().numpy().tolist() for key,value in self._states.items()}

    @property
    def performance(self):
        return ReadOnlyDict(self._performance)

    @property
    def json(self):
        return ReadOnlyDict(self._model_def._ModelDef__json)

    def resetSeed(self, seed):
        """
        Resets the random seed for reproducibility.

        This method sets the seed for various random number generators used in the project to ensure reproducibility of results.

        :param seed: The seed value to be used for the random number generators.
        :type seed: int

        Example:
            >>> model = nnodely()
            >>> model.resetSeed(42)
        """
        torch.manual_seed(seed)  ## set the pytorch seed
        torch.cuda.manual_seed_all(seed)
        random.seed(seed)  ## set the random module seed
        np.random.seed(seed)  ## set the numpy seed


nnodely = Modely

1	# Extern packages
2	import random, torch	1✔
3	import numpy as np	1✔
4
5	# Main operators
6	from nnodely.operators.network import Network	1✔
7	from nnodely.operators.trainer import Trainer	1✔
8	from nnodely.operators.loader import Loader	1✔
9	from nnodely.operators.validator import Validator	1✔
10	from nnodely.operators.exporter import Exporter	1✔
11
12	# nnodely packages
13	from nnodely.visualizer import TextVisualizer, Visualizer	1✔
14	from nnodely.basic.modeldef import ModelDef	1✔
15	from nnodely.basic.relation import NeuObj	1✔
16
17	from nnodely.support.utils import ReadOnlyDict	1✔
18
19	from nnodely.support.logger import logging, nnLogger	1✔
20	log = nnLogger(__name__, logging.INFO)	1✔
21
22
23	def clearNames(names:str\|None = None):	1✔
24	NeuObj.clearNames(names)	1✔
25
26	class Modely(Network, Trainer, Loader, Validator, Exporter):	1✔
27	"""
28	Create the main object, the nnodely object, that will be used to create the network, train and export it.
29
30	Parameters
31	----------
32	visualizer : str, Visualizer, optional
33	The visualizer to be used. Default is the 'Standard' visualizer.
34	exporter : str, Exporter, optional
35	The exporter to be used. Default is the 'Standard' exporter.
36	seed : int, optional
37	Set the seed for all the random modules inside the nnodely framework. Default is None.
38	workspace : str
39	The path of the workspace where all the exported files will be saved.
40	log_internal : bool
41	Whether or not save the logs. Default is False.
42	save_history : bool
43	Whether or not save the history. Default is False.
44
45	Example
46	-------
47	>>> model = Modely()
48	"""
49	def __init__(self,	1✔
50	visualizer:str\|Visualizer\|None = 'Standard',
51	exporter:str\|Exporter\|None = 'Standard',
52	seed:int\|None = None,
53	workspace:str\|None = None,
54	log_internal:bool = False,
55	save_history:bool = False):
56
57	# Visualizer
58	if visualizer == 'Standard':	1✔
59	self.visualizer = TextVisualizer(1)	1✔
60	elif visualizer != None:	1✔
61	self.visualizer = visualizer	1✔
62	else:
63	self.visualizer = Visualizer()	1✔
64	self.visualizer.setModely(self)	1✔
65
66	## Set the random seed for reproducibility
67	if seed is not None:	1✔
68	self.resetSeed(seed)	1✔
69
70	# Save internal
71	self.log_internal = log_internal	1✔
72	if self.log_internal == True:	1✔
73	self.internals = {}	1✔
74
75	# Models definition
76	self._model_def = ModelDef()	1✔
77	self._model = None	1✔
78	self._neuralized = False	1✔
79	self._traced = False	1✔
80
81	Network.__init__(self)	1✔
82	Loader.__init__(self)	1✔
83	Trainer.__init__(self)	1✔
84	Validator.__init__(self)	1✔
85	Exporter.__init__(self, exporter, workspace, save_history=save_history)	1✔
86
87	@property	1✔
88	def neuralized(self):	1✔
89	return self._neuralized	1✔
90
91	@neuralized.setter	1✔
92	def neuralized(self, value):	1✔
NEW 93	raise AttributeError("Cannot modify read-only property 'neuralized' use neuralizeModel() instead.")	×
94
95	@property	1✔
96	def traced(self):	1✔
97	return self._traced	1✔
98
99	@traced.setter	1✔
100	def traced(self, value):	1✔
NEW 101	raise AttributeError("Cannot modify read-only property 'traced'.")	×
102
103	@property	1✔
104	def parameters(self):	1✔
105	return ReadOnlyDict({key:value.detach().numpy().tolist() for key,value in self._model.all_parameters.items()})	1✔
106
107	@property	1✔
108	def constants(self):	1✔
NEW 109	return ReadOnlyDict({key:value.detach().numpy().tolist() for key,value in self._model.all_constants})	×
110
111	@property	1✔
112	def states(self):	1✔
113	return {key:value.detach().numpy().tolist() for key,value in self._states.items()}	1✔
114
115	@property	1✔
116	def performance(self):	1✔
NEW 117	return ReadOnlyDict(self._performance)	×
118
119	@property	1✔
120	def json(self):	1✔
121	return ReadOnlyDict(self._model_def._ModelDef__json)	1✔
122
123	def resetSeed(self, seed):	1✔
124	"""
125	Resets the random seed for reproducibility.
126
127	This method sets the seed for various random number generators used in the project to ensure reproducibility of results.
128
129	:param seed: The seed value to be used for the random number generators.
130	:type seed: int
131
132	Example:
133	>>> model = nnodely()
134	>>> model.resetSeed(42)
135	"""
136	torch.manual_seed(seed) ## set the pytorch seed	1✔
137	torch.cuda.manual_seed_all(seed)	1✔
138	random.seed(seed) ## set the random module seed	1✔
139	np.random.seed(seed) ## set the numpy seed	1✔
140
141
142	nnodely = Modely	1✔

tonegas / nnodely / 14319828903

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