226 lines
12 KiB
Plaintext
226 lines
12 KiB
Plaintext
---
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title: IMFIL (v0.26)
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description: API reference for qiskit.aqua.components.optimizers.IMFIL in qiskit v0.26
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in_page_toc_min_heading_level: 1
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python_api_type: class
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python_api_name: qiskit.aqua.components.optimizers.IMFIL
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---
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<span id="qiskit-aqua-components-optimizers-imfil" />
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# qiskit.aqua.components.optimizers.IMFIL
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<Class id="qiskit.aqua.components.optimizers.IMFIL" isDedicatedPage={true} github="https://github.com/qiskit-community/qiskit-aqua/tree/stable/0.9/qiskit/aqua/components/optimizers/imfil.py" signature="IMFIL(maxiter=1000)" modifiers="class">
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IMplicit FILtering algorithm.
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Implicit filtering is a way to solve bound-constrained optimization problems for which derivatives are not available. In comparison to methods that use interpolation to reconstruct the function and its higher derivatives, implicit filtering builds upon coordinate search followed by interpolation to get an approximate gradient.
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Uses skquant.opt installed with pip install scikit-quant. For further detail, please refer to [https://github.com/scikit-quant/scikit-quant](https://github.com/scikit-quant/scikit-quant) and [https://qat4chem.lbl.gov/software](https://qat4chem.lbl.gov/software).
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**Parameters**
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**maxiter** (`int`) – Maximum number of function evaluations.
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**Raises**
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[**MissingOptionalLibraryError**](qiskit.aqua.MissingOptionalLibraryError "qiskit.aqua.MissingOptionalLibraryError") – scikit-quant not installed
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### \_\_init\_\_
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<Function id="qiskit.aqua.components.optimizers.IMFIL.__init__" signature="__init__(maxiter=1000)">
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**Parameters**
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**maxiter** (`int`) – Maximum number of function evaluations.
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**Raises**
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[**MissingOptionalLibraryError**](qiskit.aqua.MissingOptionalLibraryError "qiskit.aqua.MissingOptionalLibraryError") – scikit-quant not installed
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</Function>
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## Methods
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| -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------- |
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| [`__init__`](#qiskit.aqua.components.optimizers.IMFIL.__init__ "qiskit.aqua.components.optimizers.IMFIL.__init__")(\[maxiter]) | **type maxiter**`int` |
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| [`get_support_level`](#qiskit.aqua.components.optimizers.IMFIL.get_support_level "qiskit.aqua.components.optimizers.IMFIL.get_support_level")() | Returns support level dictionary. |
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| [`gradient_num_diff`](#qiskit.aqua.components.optimizers.IMFIL.gradient_num_diff "qiskit.aqua.components.optimizers.IMFIL.gradient_num_diff")(x\_center, f, epsilon\[, …]) | We compute the gradient with the numeric differentiation in the parallel way, around the point x\_center. |
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| [`optimize`](#qiskit.aqua.components.optimizers.IMFIL.optimize "qiskit.aqua.components.optimizers.IMFIL.optimize")(num\_vars, objective\_function\[, …]) | Runs the optimization. |
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| [`print_options`](#qiskit.aqua.components.optimizers.IMFIL.print_options "qiskit.aqua.components.optimizers.IMFIL.print_options")() | Print algorithm-specific options. |
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| [`set_max_evals_grouped`](#qiskit.aqua.components.optimizers.IMFIL.set_max_evals_grouped "qiskit.aqua.components.optimizers.IMFIL.set_max_evals_grouped")(limit) | Set max evals grouped |
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| [`set_options`](#qiskit.aqua.components.optimizers.IMFIL.set_options "qiskit.aqua.components.optimizers.IMFIL.set_options")(\*\*kwargs) | Sets or updates values in the options dictionary. |
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| [`wrap_function`](#qiskit.aqua.components.optimizers.IMFIL.wrap_function "qiskit.aqua.components.optimizers.IMFIL.wrap_function")(function, args) | Wrap the function to implicitly inject the args at the call of the function. |
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## Attributes
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| --------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------- |
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| [`bounds_support_level`](#qiskit.aqua.components.optimizers.IMFIL.bounds_support_level "qiskit.aqua.components.optimizers.IMFIL.bounds_support_level") | Returns bounds support level |
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| [`gradient_support_level`](#qiskit.aqua.components.optimizers.IMFIL.gradient_support_level "qiskit.aqua.components.optimizers.IMFIL.gradient_support_level") | Returns gradient support level |
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| [`initial_point_support_level`](#qiskit.aqua.components.optimizers.IMFIL.initial_point_support_level "qiskit.aqua.components.optimizers.IMFIL.initial_point_support_level") | Returns initial point support level |
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| [`is_bounds_ignored`](#qiskit.aqua.components.optimizers.IMFIL.is_bounds_ignored "qiskit.aqua.components.optimizers.IMFIL.is_bounds_ignored") | Returns is bounds ignored |
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| [`is_bounds_required`](#qiskit.aqua.components.optimizers.IMFIL.is_bounds_required "qiskit.aqua.components.optimizers.IMFIL.is_bounds_required") | Returns is bounds required |
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| [`is_bounds_supported`](#qiskit.aqua.components.optimizers.IMFIL.is_bounds_supported "qiskit.aqua.components.optimizers.IMFIL.is_bounds_supported") | Returns is bounds supported |
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| [`is_gradient_ignored`](#qiskit.aqua.components.optimizers.IMFIL.is_gradient_ignored "qiskit.aqua.components.optimizers.IMFIL.is_gradient_ignored") | Returns is gradient ignored |
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| [`is_gradient_required`](#qiskit.aqua.components.optimizers.IMFIL.is_gradient_required "qiskit.aqua.components.optimizers.IMFIL.is_gradient_required") | Returns is gradient required |
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| [`is_gradient_supported`](#qiskit.aqua.components.optimizers.IMFIL.is_gradient_supported "qiskit.aqua.components.optimizers.IMFIL.is_gradient_supported") | Returns is gradient supported |
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| [`is_initial_point_ignored`](#qiskit.aqua.components.optimizers.IMFIL.is_initial_point_ignored "qiskit.aqua.components.optimizers.IMFIL.is_initial_point_ignored") | Returns is initial point ignored |
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| [`is_initial_point_required`](#qiskit.aqua.components.optimizers.IMFIL.is_initial_point_required "qiskit.aqua.components.optimizers.IMFIL.is_initial_point_required") | Returns is initial point required |
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| [`is_initial_point_supported`](#qiskit.aqua.components.optimizers.IMFIL.is_initial_point_supported "qiskit.aqua.components.optimizers.IMFIL.is_initial_point_supported") | Returns is initial point supported |
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| [`setting`](#qiskit.aqua.components.optimizers.IMFIL.setting "qiskit.aqua.components.optimizers.IMFIL.setting") | Return setting |
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### bounds\_support\_level
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<Attribute id="qiskit.aqua.components.optimizers.IMFIL.bounds_support_level">
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Returns bounds support level
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</Attribute>
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### get\_support\_level
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<Function id="qiskit.aqua.components.optimizers.IMFIL.get_support_level" signature="get_support_level()">
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Returns support level dictionary.
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</Function>
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### gradient\_num\_diff
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<Function id="qiskit.aqua.components.optimizers.IMFIL.gradient_num_diff" signature="gradient_num_diff(x_center, f, epsilon, max_evals_grouped=1)" modifiers="static">
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We compute the gradient with the numeric differentiation in the parallel way, around the point x\_center.
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**Parameters**
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* **x\_center** (*ndarray*) – point around which we compute the gradient
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* **f** (*func*) – the function of which the gradient is to be computed.
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* **epsilon** (*float*) – the epsilon used in the numeric differentiation.
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* **max\_evals\_grouped** (*int*) – max evals grouped
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**Returns**
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the gradient computed
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**Return type**
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grad
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</Function>
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### gradient\_support\_level
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<Attribute id="qiskit.aqua.components.optimizers.IMFIL.gradient_support_level">
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Returns gradient support level
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</Attribute>
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### initial\_point\_support\_level
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<Attribute id="qiskit.aqua.components.optimizers.IMFIL.initial_point_support_level">
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Returns initial point support level
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</Attribute>
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### is\_bounds\_ignored
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<Attribute id="qiskit.aqua.components.optimizers.IMFIL.is_bounds_ignored">
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Returns is bounds ignored
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</Attribute>
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### is\_bounds\_required
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<Attribute id="qiskit.aqua.components.optimizers.IMFIL.is_bounds_required">
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Returns is bounds required
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</Attribute>
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### is\_bounds\_supported
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<Attribute id="qiskit.aqua.components.optimizers.IMFIL.is_bounds_supported">
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Returns is bounds supported
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</Attribute>
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### is\_gradient\_ignored
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<Attribute id="qiskit.aqua.components.optimizers.IMFIL.is_gradient_ignored">
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Returns is gradient ignored
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</Attribute>
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### is\_gradient\_required
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<Attribute id="qiskit.aqua.components.optimizers.IMFIL.is_gradient_required">
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Returns is gradient required
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</Attribute>
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### is\_gradient\_supported
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<Attribute id="qiskit.aqua.components.optimizers.IMFIL.is_gradient_supported">
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Returns is gradient supported
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</Attribute>
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### is\_initial\_point\_ignored
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<Attribute id="qiskit.aqua.components.optimizers.IMFIL.is_initial_point_ignored">
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Returns is initial point ignored
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</Attribute>
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### is\_initial\_point\_required
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<Attribute id="qiskit.aqua.components.optimizers.IMFIL.is_initial_point_required">
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Returns is initial point required
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</Attribute>
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### is\_initial\_point\_supported
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<Attribute id="qiskit.aqua.components.optimizers.IMFIL.is_initial_point_supported">
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Returns is initial point supported
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</Attribute>
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### optimize
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<Function id="qiskit.aqua.components.optimizers.IMFIL.optimize" signature="optimize(num_vars, objective_function, gradient_function=None, variable_bounds=None, initial_point=None)">
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Runs the optimization.
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</Function>
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### print\_options
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<Function id="qiskit.aqua.components.optimizers.IMFIL.print_options" signature="print_options()">
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Print algorithm-specific options.
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</Function>
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### set\_max\_evals\_grouped
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<Function id="qiskit.aqua.components.optimizers.IMFIL.set_max_evals_grouped" signature="set_max_evals_grouped(limit)">
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Set max evals grouped
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</Function>
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### set\_options
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<Function id="qiskit.aqua.components.optimizers.IMFIL.set_options" signature="set_options(**kwargs)">
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Sets or updates values in the options dictionary.
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The options dictionary may be used internally by a given optimizer to pass additional optional values for the underlying optimizer/optimization function used. The options dictionary may be initially populated with a set of key/values when the given optimizer is constructed.
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**Parameters**
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**kwargs** (*dict*) – options, given as name=value.
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</Function>
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### setting
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<Attribute id="qiskit.aqua.components.optimizers.IMFIL.setting">
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Return setting
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</Attribute>
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### wrap\_function
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<Function id="qiskit.aqua.components.optimizers.IMFIL.wrap_function" signature="wrap_function(function, args)" modifiers="static">
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Wrap the function to implicitly inject the args at the call of the function.
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**Parameters**
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* **function** (*func*) – the target function
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* **args** (*tuple*) – the args to be injected
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**Returns**
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wrapper
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**Return type**
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function\_wrapper
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</Function>
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</Class>
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