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74 lines
2.5 KiB
Python
74 lines
2.5 KiB
Python
# Copyright (c) 2013,2014, GPy authors (see AUTHORS.txt).
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# Copyright (c) 2015, James Hensman
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# Licensed under the BSD 3-clause license (see LICENSE.txt)
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import sys
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from .parameterization import Parameterized
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import numpy as np
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class Mapping(Parameterized):
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"""
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Base model for shared mapping behaviours
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"""
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def __init__(self, input_dim, output_dim, name='mapping'):
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self.input_dim = input_dim
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self.output_dim = output_dim
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super(Mapping, self).__init__(name=name)
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def f(self, X):
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raise NotImplementedError
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def gradients_X(self, dL_dF, X):
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raise NotImplementedError
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def update_gradients(self, dL_dF, X):
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raise NotImplementedError
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def to_dict(self):
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raise NotImplementedError
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def _save_to_input_dict(self):
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input_dict = {}
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input_dict["input_dim"] = self.input_dim
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input_dict["output_dim"] = self.output_dim
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input_dict["name"] = self.name
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return input_dict
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@staticmethod
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def from_dict(input_dict):
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"""
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Instantiate an object of a derived class using the information
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in input_dict (built by the to_dict method of the derived class).
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More specifically, after reading the derived class from input_dict,
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it calls the method _build_from_input_dict of the derived class.
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Note: This method should not be overrided in the derived class. In case
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it is needed, please override _build_from_input_dict instate.
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:param dict input_dict: Dictionary with all the information needed to
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instantiate the object.
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"""
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import copy
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input_dict = copy.deepcopy(input_dict)
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mapping_class = input_dict.pop('class')
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input_dict["name"] = str(input_dict["name"])
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import GPy
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mapping_class = eval(mapping_class)
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return mapping_class._build_from_input_dict(mapping_class, input_dict)
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@staticmethod
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def _build_from_input_dict(mapping_class, input_dict):
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return mapping_class(**input_dict)
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class Bijective_mapping(Mapping):
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"""
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This is a mapping that is bijective, i.e. you can go from X to f and
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also back from f to X. The inverse mapping is called g().
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"""
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def __init__(self, input_dim, output_dim, name='bijective_mapping'):
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super(Bijective_mapping, self).__init__(name=name)
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def g(self, f):
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"""Inverse mapping from output domain of the function to the inputs."""
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raise NotImplementedError
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