Source code for mindspore.nn.probability.bijector.invert

# Copyright 2020 Huawei Technologies Co., Ltd
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"""Invert Bijector"""
from mindspore._checkparam import Validator as validator
from .bijector import Bijector


[docs]class Invert(Bijector): r""" Invert Bijector. Compute the inverse function of the input bijector. Args: bijector (Bijector): Base Bijector. name (str): The name of the Bijector. Default: 'Invert' + bijector.name. Supported Platforms: ``Ascend`` ``GPU`` Examples: >>> import mindspore >>> import mindspore.nn as nn >>> import mindspore.nn.probability.bijector as msb >>> from mindspore import Tensor >>> class Net(nn.Cell): ... def __init__(self): ... super(Net, self).__init__() ... self.origin = msb.ScalarAffine(scale=2.0, shift=1.0) ... self.invert = msb.Invert(self.origin) ... ... def construct(self, x_): ... return self.invert.forward(x_) >>> forward = Net() >>> x = np.array([2.0, 3.0, 4.0, 5.0]).astype(np.float32) >>> ans = forward(Tensor(x, dtype=mindspore.float32)) """ def __init__(self, bijector, name=""): param = dict(locals()) validator.check_value_type('bijector', bijector, [Bijector], "Invert") name = name or ('Invert' + bijector.name) param["name"] = name super(Invert, self).__init__(is_constant_jacobian=bijector.is_constant_jacobian, is_injective=bijector.is_injective, name=name, dtype=bijector.dtype, param=param) self._bijector = bijector self._batch_shape = self.bijector.batch_shape self._is_scalar_batch = self.bijector.is_scalar_batch @property def bijector(self): return self._bijector def inverse(self, y): return self.bijector("forward", y) def forward(self, x): return self.bijector("inverse", x) def inverse_log_jacobian(self, y): return self.bijector("forward_log_jacobian", y) def forward_log_jacobian(self, x): return self.bijector("inverse_log_jacobian", x)