14359872492

Committed 09 Apr 2025 02:33PM UTC coverage: 97.602% (+0.6%) from 97.035%

Build # 14359872492

Build Type

Pull #86

github

Committed by

web-flow

Commit Message

Merge ec719935a into e9c323c4f

Pull Request Pull Request #86: Smallclasses

Run Details

2291 of 2418 new or added lines in 54 files covered. (94.75%)

3 existing lines in 1 file now uncovered.

11683 of 11970 relevant lines covered (97.6%)

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94.44

/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
from nnodely.operators.memory import Memory

# 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(Memory, 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

        Memory.__init__(self)
        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	from nnodely.operators.memory import Memory	1✔
12
13	# nnodely packages
14	from nnodely.visualizer import TextVisualizer, Visualizer	1✔
15	from nnodely.basic.modeldef import ModelDef	1✔
16	from nnodely.basic.relation import NeuObj	1✔
17
18	from nnodely.support.utils import ReadOnlyDict	1✔
19
20	from nnodely.support.logger import logging, nnLogger	1✔
21	log = nnLogger(__name__, logging.INFO)	1✔
22
23
24	def clearNames(names:str\|None = None):	1✔
25	NeuObj.clearNames(names)	1✔
26
27	class Modely(Memory, Network, Trainer, Loader, Validator, Exporter):	1✔
28	"""
29	Create the main object, the nnodely object, that will be used to create the network, train and export it.
30
31	Parameters
32	----------
33	visualizer : str, Visualizer, optional
34	The visualizer to be used. Default is the 'Standard' visualizer.
35	exporter : str, Exporter, optional
36	The exporter to be used. Default is the 'Standard' exporter.
37	seed : int, optional
38	Set the seed for all the random modules inside the nnodely framework. Default is None.
39	workspace : str
40	The path of the workspace where all the exported files will be saved.
41	log_internal : bool
42	Whether or not save the logs. Default is False.
43	save_history : bool
44	Whether or not save the history. Default is False.
45
46	Example
47	-------
48	>>> model = Modely()
49	"""
50	def __init__(self,	1✔
51	visualizer:str\|Visualizer\|None = 'Standard',
52	exporter:str\|Exporter\|None = 'Standard',
53	seed:int\|None = None,
54	workspace:str\|None = None,
55	log_internal:bool = False,
56	save_history:bool = False):
57
58	# Visualizer
59	if visualizer == 'Standard':	1✔
60	self.visualizer = TextVisualizer(1)	1✔
61	elif visualizer != None:	1✔
62	self.visualizer = visualizer	1✔
63	else:
64	self.visualizer = Visualizer()	1✔
65	self.visualizer.setModely(self)	1✔
66
67	## Set the random seed for reproducibility
68	if seed is not None:	1✔
69	self.resetSeed(seed)	1✔
70
71	# Save internal
72	self.log_internal = log_internal	1✔
73	if self.log_internal == True:	1✔
74	self.internals = {}	1✔
75
76	# Models definition
77	self._model_def = ModelDef()	1✔
78	self._model = None	1✔
79	self._neuralized = False	1✔
80	self._traced = False	1✔
81
82	Memory.__init__(self)	1✔
83	Network.__init__(self)	1✔
84	Loader.__init__(self)	1✔
85	Trainer.__init__(self)	1✔
86	Validator.__init__(self)	1✔
87	Exporter.__init__(self, exporter, workspace, save_history=save_history)	1✔
88
89	@property	1✔
90	def neuralized(self):	1✔
91	return self._neuralized	1✔
92
93	@neuralized.setter	1✔
94	def neuralized(self, value):	1✔
NEW 95	raise AttributeError("Cannot modify read-only property 'neuralized' use neuralizeModel() instead.")	×
96
97	@property	1✔
98	def traced(self):	1✔
99	return self._traced	1✔
100
101	@traced.setter	1✔
102	def traced(self, value):	1✔
NEW 103	raise AttributeError("Cannot modify read-only property 'traced'.")	×
104
105	@property	1✔
106	def parameters(self):	1✔
107	return ReadOnlyDict({key:value.detach().numpy().tolist() for key,value in self._model.all_parameters.items()})	1✔
108
109	@property	1✔
110	def constants(self):	1✔
NEW 111	return ReadOnlyDict({key:value.detach().numpy().tolist() for key,value in self._model.all_constants})	×
112
113	@property	1✔
114	def states(self):	1✔
115	return {key:value.detach().numpy().tolist() for key,value in self._states.items()}	1✔
116
117	@property	1✔
118	def performance(self):	1✔
NEW 119	return ReadOnlyDict(self._performance)	×
120
121	@property	1✔
122	def json(self):	1✔
123	return ReadOnlyDict(self._model_def._ModelDef__json)	1✔
124
125	def resetSeed(self, seed):	1✔
126	"""
127	Resets the random seed for reproducibility.
128
129	This method sets the seed for various random number generators used in the project to ensure reproducibility of results.
130
131	:param seed: The seed value to be used for the random number generators.
132	:type seed: int
133
134	Example:
135	>>> model = nnodely()
136	>>> model.resetSeed(42)
137	"""
138	torch.manual_seed(seed) ## set the pytorch seed	1✔
139	torch.cuda.manual_seed_all(seed)	1✔
140	random.seed(seed) ## set the random module seed	1✔
141	np.random.seed(seed) ## set the numpy seed	1✔
142
143
144	nnodely = Modely	1✔

tonegas / nnodely / 14359872492

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