14359872492

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

Build # 14359872492

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Pull #86

github

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web-flow

Commit Message

Merge ec719935a into e9c323c4f

Pull Request Pull Request #86: Smallclasses

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/nnodely/operators/exporter.py

from nnodely.exporter.standardexporter import StandardExporter
from nnodely.exporter.emptyexporter import EmptyExporter
from nnodely.basic.model import Model
from nnodely.basic.modeldef import ModelDef
from nnodely.support.utils import check, enforce_types


class Exporter:
    @enforce_types
    def __init__(self, exporter:EmptyExporter|str|None=None, workspace:str|None=None, *, save_history:bool=False):
        check(type(self) is not Exporter, TypeError, "Exporter class cannot be instantiated directly")

        # Exporter
        if exporter == 'Standard':
            self.exporter = StandardExporter(workspace, self.visualizer, save_history=save_history)
        elif exporter != None:
            self.exporter = exporter
        else:
            self.exporter = EmptyExporter()

    @enforce_types
    def getWorkspace(self):
        return self.exporter.getWorkspace()

    @enforce_types
    def saveTorchModel(self, name:str='net', model_folder:str|None=None, *, models:str|None=None) -> None:
        """
        Saves the neural network model in PyTorch format.

        Parameters
        ----------
        name : str, optional
            The name of the saved model file. Default is 'net'.
        model_folder : str or None, optional
            The folder to save the model file in. Default is None.
        models : list or None, optional
            A list of model names to save. If None, the entire model is saved. Default is None.

        Raises
        ------
        RuntimeError
            If the model is not neuralized.

        Examples
        --------
        .. image:: https://colab.research.google.com/assets/colab-badge.svg
            :target: https://colab.research.google.com/github/tonegas/nnodely/blob/main/examples/export.ipynb
            :alt: Open in Colab

        Example usage:
            >>> model = Modely()
            >>> model.neuralizeModel()
            >>> model.saveTorchModel(name='example_model', model_folder='path/to/save')
        """
        check(self.neuralized == True, RuntimeError, 'The model is not neuralized yet!')
        if models is not None:
            if name == 'net':
                name += '_' + '_'.join(models)
            model_def = ModelDef()
            model_def.update(model_dict={key: self._model_dict[key] for key in models if key in self._model_dict})
            model_def.setBuildWindow(self._model_def['Info']['SampleTime'])
            model_def.updateParameters(self._model)
            model = Model(model_def.__json)
        else:
            model = self._model
        self.exporter.saveTorchModel(model, name, model_folder)

    @enforce_types
    def loadTorchModel(self, name:str='net', model_folder:str|None=None) -> None:
        """
        Loads a neural network model from a PyTorch format file.

        Parameters
        ----------
        name : str, optional
            The name of the model file to load. Default is 'net'.
        model_folder : str or None, optional
            The folder to load the model file from. Default is None.

        Raises
        ------
        RuntimeError
            If the model is not neuralized.

        Examples
        --------
        .. image:: https://colab.research.google.com/assets/colab-badge.svg
            :target: https://colab.research.google.com/github/tonegas/nnodely/blob/main/examples/export.ipynb
            :alt: Open in Colab

        Example usage:
            >>> model = Modely()
            >>> model.neuralizeModel()
            >>> model.loadTorchModel(name='example_model', model_folder='path/to/load')
        """
        check(self.neuralized == True, RuntimeError, 'The model is not neuralized yet.')
        self.exporter.loadTorchModel(self._model, name, model_folder)

    @enforce_types
    def saveModel(self, name:str='net', model_path:str|None=None, *, models:str|None=None) -> None:
        ## TODO: Add tests passing the attribute 'models'
        """
        Saves the neural network model definition in a json file.

        Parameters
        ----------
        name : str, optional
            The name of the saved model file. Default is 'net'.
        model_path : str or None, optional
            The path to save the model file. Default is None.
        models : list or None, optional
            A list of model names to save. If None, the entire model is saved. Default is None.

        Raises
        ------
        RuntimeError
            If the network has not been defined.

        Examples
        --------
        .. image:: https://colab.research.google.com/assets/colab-badge.svg
            :target: https://colab.research.google.com/github/tonegas/nnodely/blob/main/examples/export.ipynb
            :alt: Open in Colab

        Example usage:
            >>> model = Modely()
            >>> model.neuralizeModel()
            >>> model.saveModel(name='example_model', model_path='path/to/save')
        """
        if models is not None:
            if name == 'net':
                name += '_' + '_'.join(models)
            model_def = ModelDef()
            model_def.update(
                model_dict={key: self._model_def.__model_dict[key] for key in models if key in self._model_def.__model_dict})
            model_def.setBuildWindow(self._model_def['Info']['SampleTime'])
            model_def.updateParameters(self._model)
        else:
            model_def = self._model_def
        check(model_def.isDefined(), RuntimeError, "The network has not been defined.")
        self.exporter.saveModel(model_def.getJson(), name, model_path)

    @enforce_types
    def loadModel(self, name:str='net', model_folder:str|None=None) -> None:
        """
        Loads a neural network model from a json file containing the model definition.

        Parameters
        ----------
        name : str or None, optional
            The name of the model file to load. Default is 'net'.
        model_folder : str or None, optional
            The folder to load the model file from. Default is None.

        Raises
        ------
        RuntimeError
            If there is an error loading the network.

        Examples
        --------
        .. image:: https://colab.research.google.com/assets/colab-badge.svg
            :target: https://colab.research.google.com/github/tonegas/nnodely/blob/main/examples/export.ipynb
            :alt: Open in Colab

        Example usage:
            >>> model = Modely()
            >>> model.loadModel(name='example_model', model_folder='path/to/load')
        """
        model_def = self.exporter.loadModel(name, model_folder)
        check(model_def, RuntimeError, "Error to load the network.")
        self._model_def = ModelDef(model_def)
        self._model = None
        self._neuralized = False
        self._traced = False

    @enforce_types
    def exportPythonModel(self, name:str='net', model_path:str|None=None, *, models:str|None=None) -> None:
        """
        Exports the neural network model as a standalone PyTorch Module class.

        Parameters
        ----------
        name : str, optional
            The name of the exported model file. Default is 'net'.
        model_path : str or None, optional
            The path to save the exported model file. Default is None.
        models : list or None, optional
            A list of model names to export. If None, the entire model is exported. Default is None.

        Raises
        ------
        RuntimeError
            If the network has not been defined.
            If the model is traced and cannot be exported to Python.
            If the model is not neuralized.

        Examples
        --------
        .. image:: https://colab.research.google.com/assets/colab-badge.svg
            :target: https://colab.research.google.com/github/tonegas/nnodely/blob/main/examples/export.ipynb
            :alt: Open in Colab

        Example usage:
            >>> model = Modely(name='example_model')
            >>> model.neuralizeModel()
            >>> model.exportPythonModel(name='example_model', model_path='path/to/export')
        """
        if models is not None:
            if name == 'net':
                name += '_' + '_'.join(models)
            model_def = ModelDef()
            model_def.update(
                model_dict={key: self._model_def.__model_dict[key] for key in models if key in self._model_def.__model_dict})
            model_def.setBuildWindow(self._model_def['Info']['SampleTime'])
            model_def.updateParameters(self._model)
            model = Model(model_def.__json)
        else:
            model_def = self._model_def
            model = self._model
        # check(model_def['States'] == {}, TypeError, "The network has state variables. The export to python is not possible.")
        check(model_def.isDefined(), RuntimeError, "The network has not been defined.")
        check(self._traced == False, RuntimeError,
              'The model is traced and cannot be exported to Python.\n Run neuralizeModel() to recreate a standard model.')
        check(self.neuralized == True, RuntimeError, 'The model is not neuralized yet.')
        self.exporter.saveModel(model_def.getJson(), name, model_path)
        self.exporter.exportPythonModel(model_def, model, name, model_path)

    @enforce_types
    def importPythonModel(self, name:str='net', model_folder:str|None=None) -> None:
        """
        Imports a neural network model from a standalone PyTorch Module class.

        Parameters
        ----------
        name : str or None, optional
            The name of the model file to import. Default is 'net'.
        model_folder : str or None, optional
            The folder to import the model file from. Default is None.

        Raises
        ------
        RuntimeError
            If there is an error loading the network.

        Examples
        --------
        .. image:: https://colab.research.google.com/assets/colab-badge.svg
            :target: https://colab.research.google.com/github/tonegas/nnodely/blob/main/examples/export.ipynb
            :alt: Open in Colab

        Example usage:
            >>> model = Modely()
            >>> model.importPythonModel(name='example_model', model_folder='path/to/import')
        """
        model_def = self.exporter.loadModel(name, model_folder)
        check(model_def is not None, RuntimeError, "Error to load the network.")
        self.neuralizeModel(model_def=model_def)
        self._model = self.exporter.importPythonModel(name, model_folder)
        self._traced = True
        self._model_def.updateParameters(self._model)

    @enforce_types
    def exportONNX(self, inputs_order:list|None=None, outputs_order:list|None=None, name:str='net', model_folder:str|None=None, *, models:str|list|None=None) -> None:
        """
        Exports the neural network model to an ONNX file.

        .. note::
            The input_order may contain all the inputs and states of the model in the order that you want to export them.

        Parameters
        ----------
        inputs_order : list
            The order of the input and state variables.
        outputs_order : list
            The order of the output variables.
        models : list or None, optional
            A list of model names to export. If None, the entire model is exported. Default is None.
        name : str, optional
            The name of the exported ONNX file. Default is 'net'.
        model_folder : str or None, optional
            The folder to save the exported ONNX file. Default is None.

        Raises
        ------
        RuntimeError
            If the network has not been defined.
            If the model is traced and cannot be exported to ONNX.
            If the model is not neuralized.
            If the model is loaded and not created.

        Examples
        --------
        .. image:: https://colab.research.google.com/assets/colab-badge.svg
            :target: https://colab.research.google.com/github/tonegas/nnodely/blob/main/examples/export.ipynb
            :alt: Open in Colab

        Example usage:
            >>> input1 = Input('input1').last()
            >>> input2 = Input('input2').last()
            >>> out = Output('output1', input1+input2)

            >>> model = Modely()
            >>> model.neuralizeModel()
            >>> model.exportONNX(inputs_order=['input1', 'input2'], outputs_order=['output1'], name='example_model', model_folder='path/to/export')
        """
        check(self._model_def.isDefined(), RuntimeError, "The network has not been defined.")
        check(self.traced == False, RuntimeError,
              'The model is traced and cannot be exported to ONNX.\n Run neuralizeModel() to recreate a standard model.')
        check(self.neuralized == True, RuntimeError, 'The model is not neuralized yet.')
        # TODO replace with getJson(model = models) # generate the subtree json of a model
        # From here --------------
        model_dict = self._model_def.getModelDict()
        check(model_dict != {}, RuntimeError, 'The model is loaded but is not .')
        model_def = ModelDef()
        if models is not None:
            if name == 'net':
                name += '_' + '_'.join(models)
            model_def.update(
                model_dict={key: model_dict[key] for key in models if key in model_dict})
        else:
            model_def.update(model_dict=model_dict)
        model_def.setBuildWindow(self._model_def['Info']['SampleTime'])
        model_def.updateParameters(self._model)
        # To here -------------- Are removed
        model = Model(model_def.getJson())
        model.update()
        self.exporter.exportONNX(model_def, model, inputs_order, outputs_order, name, model_folder)

    @enforce_types
    def onnxInference(self, inputs:dict, path:str) -> dict:
        """
        Run an inference session using an onnx model previously exported using the nnodely framework.

        .. note:: Feed-Forward ONNX model
            For feed-forward models, the onnx model expect all the inputs and states to have 3 dimensions. The first dimension is the batch size, the second is the time window and the third is the feature dimension.
        .. note:: Recurrent ONNX model
            For recurrent models, the onnx model expect all the inputs to have 4 dimensions. The first dimension is the prediction horizon, the second is the batch size, the third is the time window and the fourth is the feature dimension.
            For recurrent models, the onnx model expect all the States to have 3 dimensions. The first dimension is the batch size, the second is the time window, the third is the feature dimension

        Parameters
        ----------
        inputs : dict
            A dictionary containing the input and state variables to be used to make the inference.
            State variables are mandatory and are used to initialize the states of the model.
        path : str
            The path to the ONNX file to use.

        Raises
        ------
        RuntimeError
            If the shape of the inputs are not equals to the ones defined in the onnx model.
            If the batch size is not equal for all the inputs and states.

        Examples
        --------
        .. image:: https://colab.research.google.com/assets/colab-badge.svg
            :target: https://colab.research.google.com/github/tonegas/nnodely/blob/main/examples/export.ipynb
            :alt: Open in Colab

        Example - Feed-Forward:
            >>> x = Input('x')

            >>> onnx_model_path = path/to/net.onnx
            >>> dummy_input = {'x':np.ones(shape=(3, 1, 1)).astype(np.float32)}
            >>> predictions = Modely().onnxInference(dummy_input, onnx_model_path)
        Example - Recurrent:
            >>> x = Input('x')
            >>> y = State('y')

            >>> onnx_model_path = path/to/net.onnx
            >>> dummy_input = {'x':np.ones(shape=(3, 1, 1, 1)).astype(np.float32)
                                'y':np.ones(shape=(1, 1, 1)).astype(np.float32)}
            >>> predictions = Modely().onnxInference(dummy_input, onnx_model_path)
        """
        return self.exporter.onnxInference(inputs, path)

    @enforce_types
    def exportReport(self, name:str='net', model_folder:None=None) -> None:
        """
        Generates a PDF report with plots containing the results of the training and validation of the neural network.

        Parameters
        ----------
        name : str, optional
            The name of the exported report file. Default is 'net'.
        model_folder : str or None, optional
            The folder to save the exported report file. Default is None.

        Examples
        --------
        .. image:: https://colab.research.google.com/assets/colab-badge.svg
            :target: https://colab.research.google.com/github/tonegas/nnodely/blob/main/examples/export.ipynb
            :alt: Open in Colab

        Example usage:
            >>> model = Modely()
            >>> model.neuralizeModel()
            >>> model.trainModel(train_dataset='train_dataset', validation_dataset='val_dataset', num_of_epochs=10)
            >>> model.exportReport(name='example_model', model_folder='path/to/export')
        """
        self.exporter.exportReport(self, name, model_folder)

1	from nnodely.exporter.standardexporter import StandardExporter	1✔
2	from nnodely.exporter.emptyexporter import EmptyExporter	1✔
3	from nnodely.basic.model import Model	1✔
4	from nnodely.basic.modeldef import ModelDef	1✔
5	from nnodely.support.utils import check, enforce_types	1✔
6
7
8	class Exporter:	1✔
9	@enforce_types	1✔
10	def __init__(self, exporter:EmptyExporter\|str\|None=None, workspace:str\|None=None, *, save_history:bool=False):	1✔
11	check(type(self) is not Exporter, TypeError, "Exporter class cannot be instantiated directly")	1✔
12
13	# Exporter
14	if exporter == 'Standard':	1✔
15	self.exporter = StandardExporter(workspace, self.visualizer, save_history=save_history)	1✔
NEW 16	elif exporter != None:	×
NEW 17	self.exporter = exporter	×
18	else:
NEW 19	self.exporter = EmptyExporter()	×
20
21	@enforce_types	1✔
22	def getWorkspace(self):	1✔
23	return self.exporter.getWorkspace()	1✔
24
25	@enforce_types	1✔
26	def saveTorchModel(self, name:str='net', model_folder:str\|None=None, *, models:str\|None=None) -> None:	1✔
27	"""
28	Saves the neural network model in PyTorch format.
29
30	Parameters
31	----------
32	name : str, optional
33	The name of the saved model file. Default is 'net'.
34	model_folder : str or None, optional
35	The folder to save the model file in. Default is None.
36	models : list or None, optional
37	A list of model names to save. If None, the entire model is saved. Default is None.
38
39	Raises
40	------
41	RuntimeError
42	If the model is not neuralized.
43
44	Examples
45	--------
46	.. image:: https://colab.research.google.com/assets/colab-badge.svg
47	:target: https://colab.research.google.com/github/tonegas/nnodely/blob/main/examples/export.ipynb
48	:alt: Open in Colab
49
50	Example usage:
51	>>> model = Modely()
52	>>> model.neuralizeModel()
53	>>> model.saveTorchModel(name='example_model', model_folder='path/to/save')
54	"""
55	check(self.neuralized == True, RuntimeError, 'The model is not neuralized yet!')	1✔
56	if models is not None:	1✔
NEW 57	if name == 'net':	×
NEW 58	name += '_' + '_'.join(models)	×
NEW 59	model_def = ModelDef()	×
NEW 60	model_def.update(model_dict={key: self._model_dict[key] for key in models if key in self._model_dict})	×
NEW 61	model_def.setBuildWindow(self._model_def['Info']['SampleTime'])	×
NEW 62	model_def.updateParameters(self._model)	×
NEW 63	model = Model(model_def.__json)	×
64	else:
65	model = self._model	1✔
66	self.exporter.saveTorchModel(model, name, model_folder)	1✔
67
68	@enforce_types	1✔
69	def loadTorchModel(self, name:str='net', model_folder:str\|None=None) -> None:	1✔
70	"""
71	Loads a neural network model from a PyTorch format file.
72
73	Parameters
74	----------
75	name : str, optional
76	The name of the model file to load. Default is 'net'.
77	model_folder : str or None, optional
78	The folder to load the model file from. Default is None.
79
80	Raises
81	------
82	RuntimeError
83	If the model is not neuralized.
84
85	Examples
86	--------
87	.. image:: https://colab.research.google.com/assets/colab-badge.svg
88	:target: https://colab.research.google.com/github/tonegas/nnodely/blob/main/examples/export.ipynb
89	:alt: Open in Colab
90
91	Example usage:
92	>>> model = Modely()
93	>>> model.neuralizeModel()
94	>>> model.loadTorchModel(name='example_model', model_folder='path/to/load')
95	"""
96	check(self.neuralized == True, RuntimeError, 'The model is not neuralized yet.')	1✔
97	self.exporter.loadTorchModel(self._model, name, model_folder)	1✔
98
99	@enforce_types	1✔
100	def saveModel(self, name:str='net', model_path:str\|None=None, *, models:str\|None=None) -> None:	1✔
101	## TODO: Add tests passing the attribute 'models'
102	"""
103	Saves the neural network model definition in a json file.
104
105	Parameters
106	----------
107	name : str, optional
108	The name of the saved model file. Default is 'net'.
109	model_path : str or None, optional
110	The path to save the model file. Default is None.
111	models : list or None, optional
112	A list of model names to save. If None, the entire model is saved. Default is None.
113
114	Raises
115	------
116	RuntimeError
117	If the network has not been defined.
118
119	Examples
120	--------
121	.. image:: https://colab.research.google.com/assets/colab-badge.svg
122	:target: https://colab.research.google.com/github/tonegas/nnodely/blob/main/examples/export.ipynb
123	:alt: Open in Colab
124
125	Example usage:
126	>>> model = Modely()
127	>>> model.neuralizeModel()
128	>>> model.saveModel(name='example_model', model_path='path/to/save')
129	"""
130	if models is not None:	1✔
NEW 131	if name == 'net':	×
NEW 132	name += '_' + '_'.join(models)	×
NEW 133	model_def = ModelDef()	×
NEW 134	model_def.update(	×
135	model_dict={key: self._model_def.__model_dict[key] for key in models if key in self._model_def.__model_dict})
NEW 136	model_def.setBuildWindow(self._model_def['Info']['SampleTime'])	×
NEW 137	model_def.updateParameters(self._model)	×
138	else:
139	model_def = self._model_def	1✔
140	check(model_def.isDefined(), RuntimeError, "The network has not been defined.")	1✔
141	self.exporter.saveModel(model_def.getJson(), name, model_path)	1✔
142
143	@enforce_types	1✔
144	def loadModel(self, name:str='net', model_folder:str\|None=None) -> None:	1✔
145	"""
146	Loads a neural network model from a json file containing the model definition.
147
148	Parameters
149	----------
150	name : str or None, optional
151	The name of the model file to load. Default is 'net'.
152	model_folder : str or None, optional
153	The folder to load the model file from. Default is None.
154
155	Raises
156	------
157	RuntimeError
158	If there is an error loading the network.
159
160	Examples
161	--------
162	.. image:: https://colab.research.google.com/assets/colab-badge.svg
163	:target: https://colab.research.google.com/github/tonegas/nnodely/blob/main/examples/export.ipynb
164	:alt: Open in Colab
165
166	Example usage:
167	>>> model = Modely()
168	>>> model.loadModel(name='example_model', model_folder='path/to/load')
169	"""
170	model_def = self.exporter.loadModel(name, model_folder)	1✔
171	check(model_def, RuntimeError, "Error to load the network.")	1✔
172	self._model_def = ModelDef(model_def)	1✔
173	self._model = None	1✔
174	self._neuralized = False	1✔
175	self._traced = False	1✔
176
177	@enforce_types	1✔
178	def exportPythonModel(self, name:str='net', model_path:str\|None=None, *, models:str\|None=None) -> None:	1✔
179	"""
180	Exports the neural network model as a standalone PyTorch Module class.
181
182	Parameters
183	----------
184	name : str, optional
185	The name of the exported model file. Default is 'net'.
186	model_path : str or None, optional
187	The path to save the exported model file. Default is None.
188	models : list or None, optional
189	A list of model names to export. If None, the entire model is exported. Default is None.
190
191	Raises
192	------
193	RuntimeError
194	If the network has not been defined.
195	If the model is traced and cannot be exported to Python.
196	If the model is not neuralized.
197
198	Examples
199	--------
200	.. image:: https://colab.research.google.com/assets/colab-badge.svg
201	:target: https://colab.research.google.com/github/tonegas/nnodely/blob/main/examples/export.ipynb
202	:alt: Open in Colab
203
204	Example usage:
205	>>> model = Modely(name='example_model')
206	>>> model.neuralizeModel()
207	>>> model.exportPythonModel(name='example_model', model_path='path/to/export')
208	"""
209	if models is not None:	1✔
NEW 210	if name == 'net':	×
NEW 211	name += '_' + '_'.join(models)	×
NEW 212	model_def = ModelDef()	×
NEW 213	model_def.update(	×
214	model_dict={key: self._model_def.__model_dict[key] for key in models if key in self._model_def.__model_dict})
NEW 215	model_def.setBuildWindow(self._model_def['Info']['SampleTime'])	×
NEW 216	model_def.updateParameters(self._model)	×
NEW 217	model = Model(model_def.__json)	×
218	else:
219	model_def = self._model_def	1✔
220	model = self._model	1✔
221	# check(model_def['States'] == {}, TypeError, "The network has state variables. The export to python is not possible.")
222	check(model_def.isDefined(), RuntimeError, "The network has not been defined.")	1✔
223	check(self._traced == False, RuntimeError,	1✔
224	'The model is traced and cannot be exported to Python.\n Run neuralizeModel() to recreate a standard model.')
225	check(self.neuralized == True, RuntimeError, 'The model is not neuralized yet.')	1✔
226	self.exporter.saveModel(model_def.getJson(), name, model_path)	1✔
227	self.exporter.exportPythonModel(model_def, model, name, model_path)	1✔
228
229	@enforce_types	1✔
230	def importPythonModel(self, name:str='net', model_folder:str\|None=None) -> None:	1✔
231	"""
232	Imports a neural network model from a standalone PyTorch Module class.
233
234	Parameters
235	----------
236	name : str or None, optional
237	The name of the model file to import. Default is 'net'.
238	model_folder : str or None, optional
239	The folder to import the model file from. Default is None.
240
241	Raises
242	------
243	RuntimeError
244	If there is an error loading the network.
245
246	Examples
247	--------
248	.. image:: https://colab.research.google.com/assets/colab-badge.svg
249	:target: https://colab.research.google.com/github/tonegas/nnodely/blob/main/examples/export.ipynb
250	:alt: Open in Colab
251
252	Example usage:
253	>>> model = Modely()
254	>>> model.importPythonModel(name='example_model', model_folder='path/to/import')
255	"""
256	model_def = self.exporter.loadModel(name, model_folder)	1✔
257	check(model_def is not None, RuntimeError, "Error to load the network.")	1✔
258	self.neuralizeModel(model_def=model_def)	1✔
259	self._model = self.exporter.importPythonModel(name, model_folder)	1✔
260	self._traced = True	1✔
261	self._model_def.updateParameters(self._model)	1✔
262
263	@enforce_types	1✔
264	def exportONNX(self, inputs_order:list\|None=None, outputs_order:list\|None=None, name:str='net', model_folder:str\|None=None, *, models:str\|list\|None=None) -> None:	1✔
265	"""
266	Exports the neural network model to an ONNX file.
267
268	.. note::
269	The input_order may contain all the inputs and states of the model in the order that you want to export them.
270
271	Parameters
272	----------
273	inputs_order : list
274	The order of the input and state variables.
275	outputs_order : list
276	The order of the output variables.
277	models : list or None, optional
278	A list of model names to export. If None, the entire model is exported. Default is None.
279	name : str, optional
280	The name of the exported ONNX file. Default is 'net'.
281	model_folder : str or None, optional
282	The folder to save the exported ONNX file. Default is None.
283
284	Raises
285	------
286	RuntimeError
287	If the network has not been defined.
288	If the model is traced and cannot be exported to ONNX.
289	If the model is not neuralized.
290	If the model is loaded and not created.
291
292	Examples
293	--------
294	.. image:: https://colab.research.google.com/assets/colab-badge.svg
295	:target: https://colab.research.google.com/github/tonegas/nnodely/blob/main/examples/export.ipynb
296	:alt: Open in Colab
297
298	Example usage:
299	>>> input1 = Input('input1').last()
300	>>> input2 = Input('input2').last()
301	>>> out = Output('output1', input1+input2)
302
303	>>> model = Modely()
304	>>> model.neuralizeModel()
305	>>> model.exportONNX(inputs_order=['input1', 'input2'], outputs_order=['output1'], name='example_model', model_folder='path/to/export')
306	"""
307	check(self._model_def.isDefined(), RuntimeError, "The network has not been defined.")	1✔
308	check(self.traced == False, RuntimeError,	1✔
309	'The model is traced and cannot be exported to ONNX.\n Run neuralizeModel() to recreate a standard model.')
310	check(self.neuralized == True, RuntimeError, 'The model is not neuralized yet.')	1✔
311	# TODO replace with getJson(model = models) # generate the subtree json of a model
312	# From here --------------
313	model_dict = self._model_def.getModelDict()	1✔
314	check(model_dict != {}, RuntimeError, 'The model is loaded but is not .')	1✔
315	model_def = ModelDef()	1✔
316	if models is not None:	1✔
317	if name == 'net':	1✔
318	name += '_' + '_'.join(models)	1✔
319	model_def.update(	1✔
320	model_dict={key: model_dict[key] for key in models if key in model_dict})
321	else:
322	model_def.update(model_dict=model_dict)	1✔
323	model_def.setBuildWindow(self._model_def['Info']['SampleTime'])	1✔
324	model_def.updateParameters(self._model)	1✔
325	# To here -------------- Are removed
326	model = Model(model_def.getJson())	1✔
327	model.update()	1✔
328	self.exporter.exportONNX(model_def, model, inputs_order, outputs_order, name, model_folder)	1✔
329
330	@enforce_types	1✔
331	def onnxInference(self, inputs:dict, path:str) -> dict:	1✔
332	"""
333	Run an inference session using an onnx model previously exported using the nnodely framework.
334
335	.. note:: Feed-Forward ONNX model
336	For feed-forward models, the onnx model expect all the inputs and states to have 3 dimensions. The first dimension is the batch size, the second is the time window and the third is the feature dimension.
337	.. note:: Recurrent ONNX model
338	For recurrent models, the onnx model expect all the inputs to have 4 dimensions. The first dimension is the prediction horizon, the second is the batch size, the third is the time window and the fourth is the feature dimension.
339	For recurrent models, the onnx model expect all the States to have 3 dimensions. The first dimension is the batch size, the second is the time window, the third is the feature dimension
340
341	Parameters
342	----------
343	inputs : dict
344	A dictionary containing the input and state variables to be used to make the inference.
345	State variables are mandatory and are used to initialize the states of the model.
346	path : str
347	The path to the ONNX file to use.
348
349	Raises
350	------
351	RuntimeError
352	If the shape of the inputs are not equals to the ones defined in the onnx model.
353	If the batch size is not equal for all the inputs and states.
354
355	Examples
356	--------
357	.. image:: https://colab.research.google.com/assets/colab-badge.svg
358	:target: https://colab.research.google.com/github/tonegas/nnodely/blob/main/examples/export.ipynb
359	:alt: Open in Colab
360
361	Example - Feed-Forward:
362	>>> x = Input('x')
363
364	>>> onnx_model_path = path/to/net.onnx
365	>>> dummy_input = {'x':np.ones(shape=(3, 1, 1)).astype(np.float32)}
366	>>> predictions = Modely().onnxInference(dummy_input, onnx_model_path)
367	Example - Recurrent:
368	>>> x = Input('x')
369	>>> y = State('y')
370
371	>>> onnx_model_path = path/to/net.onnx
372	>>> dummy_input = {'x':np.ones(shape=(3, 1, 1, 1)).astype(np.float32)
373	'y':np.ones(shape=(1, 1, 1)).astype(np.float32)}
374	>>> predictions = Modely().onnxInference(dummy_input, onnx_model_path)
375	"""
376	return self.exporter.onnxInference(inputs, path)	1✔
377
378	@enforce_types	1✔
379	def exportReport(self, name:str='net', model_folder:None=None) -> None:	1✔
380	"""
381	Generates a PDF report with plots containing the results of the training and validation of the neural network.
382
383	Parameters
384	----------
385	name : str, optional
386	The name of the exported report file. Default is 'net'.
387	model_folder : str or None, optional
388	The folder to save the exported report file. Default is None.
389
390	Examples
391	--------
392	.. image:: https://colab.research.google.com/assets/colab-badge.svg
393	:target: https://colab.research.google.com/github/tonegas/nnodely/blob/main/examples/export.ipynb
394	:alt: Open in Colab
395
396	Example usage:
397	>>> model = Modely()
398	>>> model.neuralizeModel()
399	>>> model.trainModel(train_dataset='train_dataset', validation_dataset='val_dataset', num_of_epochs=10)
400	>>> model.exportReport(name='example_model', model_folder='path/to/export')
401	"""
402	self.exporter.exportReport(self, name, model_folder)	1✔

tonegas / nnodely / 14359872492

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