runtime-modeling/model_def.py
def _call_se(self, input_tensor):
    """Call Squeeze and Excitation layer.

    Args:
      input_tensor: Tensor, a single input tensor for Squeeze/Excitation layer.

    Returns:
      A output tensor, which should have the same shape as input.
    """
    se_tensor = tf.reduce_mean(input_tensor, self._spatial_dims, keepdims=True)
    se_tensor = self._se_expand(tf.nn.relu(self._se_reduce(se_tensor)))
    tf.logging.info('Built Squeeze and Excitation with tensor shape: %s' %
                    (se_tensor.shape))
    return tf.sigmoid(se_tensor) * input_tensor
Call Squeeze and Excitation layer.

    Args:
      input_tensor: Tensor, a single input tensor for Squeeze/Excitation layer.

    Returns:
      A output tensor, which should have the same shape as input.
    
Call Squeeze and Excitation layer.
Call Squeeze and Excitation layer .
def _call_se(self, input_tensor):
    se_tensor = tf.reduce_mean(input_tensor, self._spatial_dims, keepdims=True)
    se_tensor = self._se_expand(tf.nn.relu(self._se_reduce(se_tensor)))
    tf.logging.info('Built Squeeze and Excitation with tensor shape: %s' %
                    (se_tensor.shape))
    return tf.sigmoid(se_tensor) * input_tensor
def _call_se ( self , input_tensor ) : se_tensor = tf . reduce_mean ( input_tensor , self . _spatial_dims , keepdims = True ) se_tensor = self . _se_expand ( tf . nn . relu ( self . _se_reduce ( se_tensor ) ) ) tf . logging . info ( 'Built Squeeze and Excitation with tensor shape: %s' % ( se_tensor . shape ) ) return tf . sigmoid ( se_tensor ) * input_tensor
Call Squeeze and Excitation layer.
Call Squeeze and Excitation layer .
"""Call Squeeze and Excitation layer.

    Args:
      input_tensor: Tensor, a single input tensor for Squeeze/Excitation layer.

    Returns:
      A output tensor, which should have the same shape as input.
    """
A output tensor, which should have the same shape as input.
A output tensor which should have the same shape as input .
self
input_tensor
Tensor, a single input tensor for Squeeze/Excitation layer.
Tensor a single input tensor for Squeeze / Excitation layer .