message: Add decay/epsilon/updates_collections parameters to Inception v3 arg_scope
diff: @@ -680,6 +680,9 @@ def _reduced_kernel_size_for_small_input(input_tensor, kernel_size):
  def inception_v3_arg_scope(weight_decay=0.00004,
  batch_norm_var_collection='moving_vars',
  + batch_norm_decay=0.9997,
  + batch_norm_epsilon=0.001,
  + updates_collections=ops.GraphKeys.UPDATE_OPS,
  use_fused_batchnorm=True):
  """Defines the default InceptionV3 arg scope.
  @@ -687,6 +690,9 @@ def inception_v3_arg_scope(weight_decay=0.00004,
  weight_decay: The weight decay to use for regularizing the model.
  batch_norm_var_collection: The name of the collection for the batch norm
  variables.
  + batch_norm_decay: Decay for batch norm moving average
  + batch_norm_epsilon: Small float added to variance to avoid division by zero
  + updates_collections: Collections for the update ops of the layer
  use_fused_batchnorm: Enable fused batchnorm.
  Returns:
  @@ -694,11 +700,11 @@ def inception_v3_arg_scope(weight_decay=0.00004,
  """
  batch_norm_params = {
  # Decay for the moving averages.
  - 'decay': 0.9997,
  + 'decay': batch_norm_decay,
  # epsilon to prevent 0s in variance.
  - 'epsilon': 0.001,
  + 'epsilon': batch_norm_epsilon,
  # collection containing update_ops.
  - 'updates_collections': ops.GraphKeys.UPDATE_OPS,
  + 'updates_collections': updates_collections,
  # Use fused batch norm if possible.
  'fused': use_fused_batchnorm,
  # collection containing the moving mean and moving variance.
  