Python sonnet.Conv3D() Examples

The following are 6 code examples of sonnet.Conv3D(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module sonnet , or try the search function .
Example #1
Source File: i3d.py    From I3D-Tensorflow with Apache License 2.0 6 votes vote down vote up 
def _build(self, inputs, is_training):
    """Connects the module to inputs.

    Args:
      inputs: Inputs to the Unit3D component.
      is_training: whether to use training mode for snt.BatchNorm (boolean).

    Returns:
      Outputs from the module.
    """
    net = snt.Conv3D(output_channels=self._output_channels,
                     kernel_shape=self._kernel_shape,
                     stride=self._stride,
                     padding=snt.SAME,
                     use_bias=self._use_bias)(inputs)
    if self._use_batch_norm:
      bn = snt.BatchNorm()
      net = bn(net, is_training=is_training, test_local_stats=False)
    if self._activation_fn is not None:
      net = self._activation_fn(net)
    return net
Example #2
Source File: i3d.py    From ACAM_Demo with MIT License 6 votes vote down vote up 
def _build(self, inputs, is_training):
    """Connects the module to inputs.

    Args:
      inputs: Inputs to the Unit3D component.
      is_training: whether to use training mode for snt.BatchNorm (boolean).

    Returns:
      Outputs from the module.
    """
    net = snt.Conv3D(output_channels=self._output_channels,
                     kernel_shape=self._kernel_shape,
                     stride=self._stride,
                     padding=snt.SAME,
                     use_bias=self._use_bias)(inputs)
    if self._use_batch_norm:
      bn = snt.BatchNorm()
      #################### Warning batchnorm is hard coded to is_training=False #################
      # net = bn(net, is_training=is_training, test_local_stats=False)
      net = bn(net, is_training=False, test_local_stats=False)
    if self._activation_fn is not None:
      net = self._activation_fn(net)
    return net
Example #3
Source File: i3dtf.py    From kinetics_i3d_pytorch with MIT License 6 votes vote down vote up 
def _build(self, inputs, is_training):
        """Connects the module to inputs.

    Args:
    inputs: Inputs to the Unit3Dtf component.
    is_training: whether to use training mode for snt.BatchNorm (boolean).

    Returns:
    Outputs from the module.
        """
        net = snt.Conv3D(
            output_channels=self._output_channels,
            kernel_shape=self._kernel_shape,
            stride=self._stride,
            padding=snt.SAME,
            use_bias=self._use_bias)(inputs)
        if self._use_batch_norm:
            bn = snt.BatchNorm()
            net = bn(net, is_training=is_training, test_local_stats=False)
        if self._activation_fn is not None:
            net = self._activation_fn(net)

        return net
Example #4
Source File: i3d.py    From kinetics-i3d with Apache License 2.0 6 votes vote down vote up 
def _build(self, inputs, is_training):
    """Connects the module to inputs.

    Args:
      inputs: Inputs to the Unit3D component.
      is_training: whether to use training mode for snt.BatchNorm (boolean).

    Returns:
      Outputs from the module.
    """
    net = snt.Conv3D(output_channels=self._output_channels,
                     kernel_shape=self._kernel_shape,
                     stride=self._stride,
                     padding=snt.SAME,
                     use_bias=self._use_bias)(inputs)
    if self._use_batch_norm:
      bn = snt.BatchNorm()
      net = bn(net, is_training=is_training, test_local_stats=False)
    if self._activation_fn is not None:
      net = self._activation_fn(net)
    return net
Example #5
Source File: i3d.py    From visil with Apache License 2.0 6 votes vote down vote up 
def _build(self, inputs, is_training):
    """Connects the module to inputs.

    Args:
      inputs: Inputs to the Unit3D component.
      is_training: whether to use training mode for snt.BatchNorm (boolean).

    Returns:
      Outputs from the module.
    """
    net = snt.Conv3D(output_channels=self._output_channels,
                     kernel_shape=self._kernel_shape,
                     stride=self._stride,
                     padding=snt.SAME,
                     use_bias=self._use_bias)(inputs)
    if self._use_batch_norm:
      bn = snt.BatchNorm()
      net = bn(net, is_training=is_training, test_local_stats=False)
    if self._activation_fn is not None:
      net = self._activation_fn(net)
    return net
Example #6
Source File: i3d.py    From STPN with Apache License 2.0 6 votes vote down vote up 
def _build(self, inputs, is_training):
    """Connects the module to inputs.

    Args:
      inputs: Inputs to the Unit3D component.
      is_training: whether to use training mode for snt.BatchNorm (boolean).

    Returns:
      Outputs from the module.
    """
    net = snt.Conv3D(output_channels=self._output_channels,
                     kernel_shape=self._kernel_shape,
                     stride=self._stride,
                     padding=snt.SAME,
                     use_bias=self._use_bias)(inputs)
    if self._use_batch_norm:
      bn = snt.BatchNorm()
      net = bn(net, is_training=is_training, test_local_stats=False)
    if self._activation_fn is not None:
      net = self._activation_fn(net)
    return net