:mod:`blueoil.networks.segmentation.lm_segnet_v0`
=================================================

.. py:module:: blueoil.networks.segmentation.lm_segnet_v0


Module Contents
---------------

Classes
~~~~~~~

.. autoapisummary::

   blueoil.networks.segmentation.lm_segnet_v0.LmSegnetV0
   blueoil.networks.segmentation.lm_segnet_v0.LmSegnetV0Quantize



.. py:class:: LmSegnetV0(*args, **kwargs)

   Bases: :class:`blueoil.networks.segmentation.base.SegnetBase`

   LM customized SegNet Network.

   .. method:: _get_lmnet_block(self, is_training, channels_data_format)


   .. method:: _max_pool_with_argmax(self, inputs=None, ksize=None, strides=None, padding=None, name='')


   .. method:: _unpool_with_argmax(self, inputs=None, mask=None, ksize=None, name='')


   .. method:: base(self, images, is_training, *args, **kwargs)

      Base function contains inference.

      :param images: Input images.
      :param is_training: A flag for if is training.

      :returns: Inference result.
      :rtype: tf.Tensor



.. py:class:: LmSegnetV0Quantize(activation_quantizer=None, activation_quantizer_kwargs={}, weight_quantizer=None, weight_quantizer_kwargs={}, *args, **kwargs)

   Bases: :class:`blueoil.networks.segmentation.lm_segnet_v0.LmSegnetV0`

   LM customized Segnet quantize network.

   Following `args` are used for inference: ``activation_quantizer``, ``activation_quantizer_kwargs``,
   ``weight_quantizer``, ``weight_quantizer_kwargs``.

   :param activation_quantizer: Weight quantizater. See more at `blueoil.quantizations`.
   :type activation_quantizer: callable
   :param activation_quantizer_kwargs: Kwargs for `activation_quantizer`.
   :type activation_quantizer_kwargs: dict
   :param weight_quantizer: Activation quantizater. See more at `blueoil.quantizations`.
   :type weight_quantizer: callable
   :param weight_quantizer_kwargs: Kwargs for `weight_quantizer`.
   :type weight_quantizer_kwargs: dict

   .. method:: _quantized_variable_getter(getter, name, weight_quantization=None, *args, **kwargs)
      :staticmethod:

      Get the quantized variables.

      Use if to choose or skip the target should be quantized.

      :param getter: Default from tensorflow.
      :param name: Default from tensorflow.
      :param weight_quantization: Callable object which quantize variable.
      :param args: Args.
      :param kwargs: Kwargs.