|
| Node | ngraph.opset1.ops.absolute (NodeInput node, Optional[str] name=None) |
| | Return node which applies f(x) = abs(x) to the input node element-wise. More...
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| |
| Node | ngraph.opset1.ops.acos (NodeInput node, Optional[str] name=None) |
| | Apply inverse cosine function on the input node element-wise. More...
|
| |
| Node | ngraph.opset1.ops.add (NodeInput left_node, NodeInput right_node, str auto_broadcast="NUMPY", Optional[str] name=None) |
| | Return node which applies f(x) = A+B to the input nodes element-wise. More...
|
| |
| Node | ngraph.opset1.ops.asin (NodeInput node, Optional[str] name=None) |
| | Apply inverse sine function on the input node element-wise. More...
|
| |
| Node | ngraph.opset1.ops.atan (NodeInput node, Optional[str] name=None) |
| | Apply inverse tangent function on the input node element-wise. More...
|
| |
| Node | ngraph.opset1.ops.avg_pool (NodeInput data_batch, List[int] strides, TensorShape pads_begin, TensorShape pads_end, TensorShape kernel_shape, bool exclude_pad, str rounding_type="floor", Optional[str] auto_pad=None, Optional[str] name=None) |
| | Return average pooling node. More...
|
| |
| Node | ngraph.opset1.ops.batch_norm_inference (NodeInput data, NodeInput gamma, NodeInput beta, NodeInput mean, NodeInput variance, float epsilon, Optional[str] name=None) |
| | Perform layer normalizes a input tensor by mean and variance with appling scale and offset. More...
|
| |
| Node | ngraph.opset1.ops.binary_convolution (NodeInput data, NodeInput filters, List[int] strides, List[int] pads_begin, List[int] pads_end, List[int] dilations, str mode, float pad_value, str auto_pad="EXPLICIT", Optional[str] name=None) |
| | Create node performing convolution with binary weights, binary input and integer output. More...
|
| |
| Node | ngraph.opset1.ops.broadcast (NodeInput data, NodeInput target_shape, Optional[NodeInput] axes_mapping=None, str mode="NUMPY", Optional[str] name=None) |
| | Create a node which broadcasts the input node's values along specified axes to a desired shape. More...
|
| |
| Node | ngraph.opset1.ops.ctc_greedy_decoder (NodeInput data, NodeInput sequence_mask, bool merge_repeated=True, Optional[str] name=None) |
| | Perform greedy decoding on the logits given in input (best path). More...
|
| |
| Node | ngraph.opset1.ops.ceiling (NodeInput node, Optional[str] name=None) |
| | Return node which applies ceiling to the input node element-wise. More...
|
| |
| Node | ngraph.opset1.ops.clamp (NodeInput data, ScalarData min_value, ScalarData max_value, Optional[str] name=None) |
| | Perform clamp element-wise on data from input node. More...
|
| |
| Node | ngraph.opset1.ops.concat (List[NodeInput] nodes, int axis, Optional[str] name=None) |
| | Concatenate input nodes into single new node along specified axis. More...
|
| |
| Constant | ngraph.opset1.ops.constant (NumericData value, NumericType dtype=None, Optional[str] name=None) |
| | Create a Constant node from provided value. More...
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| |
| Node | ngraph.opset1.ops.convert (NodeInput data, Union[str, NumericType] destination_type, Optional[str] name=None) |
| | Return node which casts input node values to specified type. More...
|
| |
| Node | ngraph.opset1.ops.convert_like (NodeInput data, NodeInput like, Optional[str] name=None) |
| | Return node which casts data node values to the type of another node. More...
|
| |
| Node | ngraph.opset1.ops.convolution (NodeInput data, NodeInput filters, List[int] strides, List[int] pads_begin, List[int] pads_end, List[int] dilations, str auto_pad="EXPLICIT", Optional[str] name=None) |
| | Return node performing batched convolution operation. More...
|
| |
| Node | ngraph.opset1.ops.convolution_backprop_data (NodeInput data, NodeInput filters, List[int] strides, Optional[NodeInput] output_shape=None, Optional[List[int]] pads_begin=None, Optional[List[int]] pads_end=None, Optional[List[int]] dilations=None, Optional[str] auto_pad=None, Optional[List[int]] output_padding=None, Optional[str] name=None) |
| | Create node performing a batched-convolution backprop data operation. More...
|
| |
| Node | ngraph.opset1.ops.cos (NodeInput node, Optional[str] name=None) |
| | Apply cosine function on the input node element-wise. More...
|
| |
| Node | ngraph.opset1.ops.cosh (NodeInput node, Optional[str] name=None) |
| | Apply hyperbolic cosine function on the input node element-wise. More...
|
| |
| Node | ngraph.opset1.ops.deformable_convolution (NodeInput data, NodeInput deformable_values, NodeInput filters, List[int] strides, List[int] pads_begin, List[int] pads_end, List[int] dilations, str auto_pad="EXPLICIT", int group=1, int deformable_group=1, Optional[str] name=None) |
| | Create node performing deformable convolution. More...
|
| |
| Node | ngraph.opset1.ops.deformable_psroi_pooling (NodeInput feature_maps, NodeInput coords, int output_dim, float spatial_scale, int group_size=1, str mode="bilinear_deformable", int spatial_bins_x=1, int spatial_bins_y=1, float trans_std=1.0, int part_size=1, Optional[NodeInput] offsets=None, Optional[str] name=None) |
| | Return node performing DeformablePSROIPooling operation. More...
|
| |
| Node | ngraph.opset1.ops.depth_to_space (Node node, str mode, int block_size=1, str name=None) |
| | Rearranges input tensor from depth into blocks of spatial data. More...
|
| |
| Node | ngraph.opset1.ops.detection_output (Node box_logits, Node class_preds, Node proposals, dict attrs, NodeInput aux_class_preds=None, NodeInput aux_box_preds=None, Optional[str] name=None) |
| | Generate the detection output using information on location and confidence predictions. More...
|
| |
| Node | ngraph.opset1.ops.divide (NodeInput left_node, NodeInput right_node, str auto_broadcast="NUMPY", Optional[str] name=None) |
| | Return node which applies f(x) = A/B to the input nodes element-wise. More...
|
| |
| Node | ngraph.opset1.ops.elu (NodeInput data, NumericType alpha, Optional[str] name=None) |
| | Perform Exponential Linear Unit operation element-wise on data from input node. More...
|
| |
| Node | ngraph.opset1.ops.equal (NodeInput left_node, NodeInput right_node, str auto_broadcast="NUMPY", Optional[str] name=None) |
| | Return node which checks if input nodes are equal element-wise. More...
|
| |
| Node | ngraph.opset1.ops.erf (NodeInput node, Optional[str] name=None) |
| | Return node which calculates Gauss error function element-wise with given tensor. More...
|
| |
| Node | ngraph.opset1.ops.exp (NodeInput node, Optional[str] name=None) |
| | Return node which applies exponential function to the input node element-wise. More...
|
| |
| Node | ngraph.opset1.ops.fake_quantize (NodeInput data, NodeInput input_low, NodeInput input_high, NodeInput output_low, NodeInput output_high, int levels, str auto_broadcast="NUMPY", Optional[str] name=None) |
| | Perform an element-wise linear quantization on input data. More...
|
| |
| Node | ngraph.opset1.ops.floor (NodeInput node, Optional[str] name=None) |
| | Return node which applies floor to the input node element-wise. More...
|
| |
| Node | ngraph.opset1.ops.floor_mod (NodeInput left_node, NodeInput right_node, str auto_broadcast="NUMPY", Optional[str] name=None) |
| | Return node performing element-wise FloorMod (division reminder) with two given tensors. More...
|
| |
| Node | ngraph.opset1.ops.gather (NodeInput data, NodeInput indices, NodeInput axis, Optional[str] name=None) |
| | Return Gather node which takes slices from axis of data according to indices. More...
|
| |
| Node | ngraph.opset1.ops.gather_tree (NodeInput step_ids, NodeInput parent_idx, NodeInput max_seq_len, NodeInput end_token, Optional[str] name=None) |
| | Perform GatherTree operation. More...
|
| |
| Node | ngraph.opset1.ops.greater (NodeInput left_node, NodeInput right_node, str auto_broadcast="NUMPY", Optional[str] name=None) |
| | Return node which checks if left input node is greater than the right node element-wise. More...
|
| |
| Node | ngraph.opset1.ops.greater_equal (NodeInput left_node, NodeInput right_node, str auto_broadcast="NUMPY", Optional[str] name=None) |
| | Return node which checks if left node is greater or equal to the right node element-wise. More...
|
| |
| Node | ngraph.opset1.ops.grn (Node data, float bias, Optional[str] name=None) |
| | Perform Global Response Normalization with L2 norm (across channels only). More...
|
| |
| Node | ngraph.opset1.ops.group_convolution (NodeInput data, NodeInput filters, List[int] strides, List[int] pads_begin, List[int] pads_end, List[int] dilations, str auto_pad="EXPLICIT", Optional[str] name=None) |
| | Perform Group Convolution operation on data from input node. More...
|
| |
| Node | ngraph.opset1.ops.group_convolution_backprop_data (NodeInput data, NodeInput filters, List[int] strides, Optional[NodeInput] output_shape=None, Optional[List[int]] pads_begin=None, Optional[List[int]] pads_end=None, Optional[List[int]] dilations=None, str auto_pad="EXPLICIT", Optional[List[int]] output_padding=None, Optional[str] name=None) |
| | Perform Group Convolution operation on data from input node. More...
|
| |
| Node | ngraph.opset1.ops.hard_sigmoid (Node data, NodeInput alpha, NodeInput beta, Optional[str] name=None) |
| | Perform Hard Sigmoid operation element-wise on data from input node. More...
|
| |
| Node | ngraph.opset1.ops.interpolate (Node image, NodeInput output_shape, dict attrs, Optional[str] name=None) |
| | Perform interpolation of independent slices in input tensor. More...
|
| |
| Node | ngraph.opset1.ops.less (NodeInput left_node, NodeInput right_node, str auto_broadcast="NUMPY", Optional[str] name=None) |
| | Return node which checks if left input node is less than the right node element-wise. More...
|
| |
| Node | ngraph.opset1.ops.less_equal (NodeInput left_node, NodeInput right_node, str auto_broadcast="NUMPY", Optional[str] name=None) |
| | Return node which checks if left input node is less or equal the right node element-wise. More...
|
| |
| Node | ngraph.opset1.ops.log (NodeInput node, Optional[str] name=None) |
| | Return node which applies natural logarithm to the input node element-wise. More...
|
| |
| Node | ngraph.opset1.ops.logical_and (NodeInput left_node, NodeInput right_node, str auto_broadcast="NUMPY", Optional[str] name=None) |
| | Return node which perform logical and operation on input nodes element-wise. More...
|
| |
| Node | ngraph.opset1.ops.logical_not (NodeInput node, Optional[str] name=None) |
| | Return node which applies element-wise logical negation to the input node. More...
|
| |
| Node | ngraph.opset1.ops.logical_or (NodeInput left_node, NodeInput right_node, str auto_broadcast="NUMPY", Optional[str] name=None) |
| | Return node which performs logical OR operation on input nodes element-wise. More...
|
| |
| Node | ngraph.opset1.ops.logical_xor (NodeInput left_node, NodeInput right_node, str auto_broadcast="NUMPY", Optional[str] name=None) |
| | Return node which performs logical XOR operation on input nodes element-wise. More...
|
| |
| Node | ngraph.opset1.ops.lrn (NodeInput data, NodeInput axes, float alpha=1, float beta=0.5, float bias=1, int size=5, Optional[str] name=None) |
| | Return a node which performs element-wise Local Response Normalization (LRN) operation. More...
|
| |
| Node | ngraph.opset1.ops.lstm_cell (NodeInput X, NodeInput initial_hidden_state, NodeInput initial_cell_state, NodeInput W, NodeInput R, NodeInput B, int hidden_size, List[str] activations=None, List[float] activations_alpha=None, List[float] activations_beta=None, float clip=0.0, Optional[str] name=None) |
| | Return a node which performs LSTMCell operation. More...
|
| |
| Node | ngraph.opset1.ops.lstm_sequence (NodeInput X, NodeInput initial_hidden_state, NodeInput initial_cell_state, NodeInput sequence_lengths, NodeInput W, NodeInput R, NodeInput B, int hidden_size, str direction, List[str] activations=None, List[float] activations_alpha=None, List[float] activations_beta=None, float clip=0.0, Optional[str] name=None) |
| | Return a node which performs LSTMSequence operation. More...
|
| |
| Node | ngraph.opset1.ops.matmul (NodeInput data_a, NodeInput data_b, bool transpose_a, bool transpose_b, Optional[str] name=None) |
| | Return the Matrix Multiplication operation. More...
|
| |
| Node | ngraph.opset1.ops.max_pool (NodeInput data, List[int] strides, List[int] pads_begin, List[int] pads_end, TensorShape kernel_shape, str rounding_type="floor", Optional[str] auto_pad=None, Optional[str] name=None) |
| | Perform max pooling operation with given parameters on provided data. More...
|
| |
| Node | ngraph.opset1.ops.maximum (NodeInput left_node, NodeInput right_node, str auto_broadcast="NUMPY", Optional[str] name=None) |
| | Return node which applies the maximum operation to input nodes elementwise. More...
|
| |
| Node | ngraph.opset1.ops.minimum (NodeInput left_node, NodeInput right_node, str auto_broadcast="NUMPY", Optional[str] name=None) |
| | Return node which applies the minimum operation to input nodes elementwise. More...
|
| |
| Node | ngraph.opset1.ops.mod (NodeInput left_node, NodeInput right_node, str auto_broadcast="NUMPY", Optional[str] name=None) |
| | Return node performing element-wise division reminder with two given tensors. More...
|
| |
| Node | ngraph.opset1.ops.multiply (NodeInput left_node, NodeInput right_node, str auto_broadcast="NUMPY", Optional[str] name=None) |
| | Return node which applies f(x) = A*B to the input nodes elementwise. More...
|
| |
| Node | ngraph.opset1.ops.negative (NodeInput node, Optional[str] name=None) |
| | Return node which applies f(x) = -x to the input node elementwise. More...
|
| |
| Node | ngraph.opset1.ops.non_max_suppression (NodeInput boxes, NodeInput scores, Optional[NodeInput] max_output_boxes_per_class=None, Optional[NodeInput] iou_threshold=None, Optional[NodeInput] score_threshold=None, str box_encoding="corner", bool sort_result_descending=True, Optional[str] name=None) |
| | Return a node which performs NonMaxSuppression. More...
|
| |
| Node | ngraph.opset1.ops.normalize_l2 (NodeInput data, NodeInput axes, float eps, str eps_mode, Optional[str] name=None) |
| | Construct an NormalizeL2 operation. More...
|
| |
| Node | ngraph.opset1.ops.not_equal (NodeInput left_node, NodeInput right_node, str auto_broadcast="NUMPY", Optional[str] name=None) |
| | Return node which checks if input nodes are unequal element-wise. More...
|
| |
| Node | ngraph.opset1.ops.one_hot (NodeInput indices, NodeInput depth, NodeInput on_value, NodeInput off_value, int axis, Optional[str] name=None) |
| | Create node performing one-hot encoding on input data. More...
|
| |
| Node | ngraph.opset1.ops.pad (NodeInput arg, NodeInput pads_begin, NodeInput pads_end, str pad_mode, Optional[NodeInput] arg_pad_value=None, Optional[str] name=None) |
| | Return a generic padding operation. More...
|
| |
| Parameter | ngraph.opset1.ops.parameter (TensorShape shape, NumericType dtype=np.float32, Optional[str] name=None) |
| | Return an ngraph Parameter object. More...
|
| |
| Node | ngraph.opset1.ops.power (NodeInput left_node, NodeInput right_node, str auto_broadcast="NUMPY", Optional[str] name=None) |
| | Return node which perform element-wise exponentiation operation. More...
|
| |
| Node | ngraph.opset1.ops.prelu (NodeInput data, NodeInput slope, Optional[str] name=None) |
| | Perform Parametrized Relu operation element-wise on data from input node. More...
|
| |
| Node | ngraph.opset1.ops.prior_box_clustered (Node output_size, NodeInput image_size, dict attrs, Optional[str] name=None) |
| | Generate prior boxes of specified sizes normalized to the input image size. More...
|
| |
| Node | ngraph.opset1.ops.prior_box (Node layer_shape, NodeInput image_shape, dict attrs, Optional[str] name=None) |
| | Generate prior boxes of specified sizes and aspect ratios across all dimensions. More...
|
| |
| Node | ngraph.opset1.ops.proposal (Node class_probs, Node bbox_deltas, NodeInput image_shape, dict attrs, Optional[str] name=None) |
| | Filter bounding boxes and outputs only those with the highest prediction confidence. More...
|
| |
| Node | ngraph.opset1.ops.psroi_pooling (NodeInput input, NodeInput coords, int output_dim, int group_size, float spatial_scale, int spatial_bins_x, int spatial_bins_y, str mode, Optional[str] name=None) |
| | Return a node which produces a PSROIPooling operation. More...
|
| |
| Node | ngraph.opset1.ops.range (Node start, NodeInput stop, NodeInput step, Optional[str] name=None) |
| | Return a node which produces the Range operation. More...
|
| |
| Node | ngraph.opset1.ops.relu (NodeInput node, Optional[str] name=None) |
| | Perform rectified linear unit operation on input node element-wise. More...
|
| |
| Node | ngraph.opset1.ops.reduce_logical_and (NodeInput node, NodeInput reduction_axes, bool keep_dims=False, Optional[str] name=None) |
| | Logical AND reduction operation on input tensor, eliminating the specified reduction axes. More...
|
| |
| Node | ngraph.opset1.ops.reduce_logical_or (NodeInput node, NodeInput reduction_axes, bool keep_dims=False, Optional[str] name=None) |
| | Logical OR reduction operation on input tensor, eliminating the specified reduction axes. More...
|
| |
| Node | ngraph.opset1.ops.reduce_max (NodeInput node, NodeInput reduction_axes, bool keep_dims=False, Optional[str] name=None) |
| | Max-reduction operation on input tensor, eliminating the specified reduction axes. More...
|
| |
| Node | ngraph.opset1.ops.reduce_mean (NodeInput node, NodeInput reduction_axes, bool keep_dims=False, Optional[str] name=None) |
| | Mean-reduction operation on input tensor, eliminating the specified reduction axes. More...
|
| |
| Node | ngraph.opset1.ops.reduce_min (NodeInput node, NodeInput reduction_axes, bool keep_dims=False, Optional[str] name=None) |
| | Min-reduction operation on input tensor, eliminating the specified reduction axes. More...
|
| |
| Node | ngraph.opset1.ops.reduce_prod (NodeInput node, NodeInput reduction_axes, bool keep_dims=False, Optional[str] name=None) |
| | Product-reduction operation on input tensor, eliminating the specified reduction axes. More...
|
| |
| Node | ngraph.opset1.ops.reduce_sum (NodeInput node, NodeInput reduction_axes, bool keep_dims=False, Optional[str] name=None) |
| | Perform element-wise sums of the input tensor, eliminating the specified reduction axes. More...
|
| |
| Node | ngraph.opset1.ops.region_yolo (Node input, int coords, int classes, int num, bool do_softmax, List[int] mask, int axis, int end_axis, List[float] anchors=None, Optional[str] name=None) |
| | Return a node which produces the RegionYolo operation. More...
|
| |
| Node | ngraph.opset1.ops.reshape (NodeInput node, NodeInput output_shape, bool special_zero, Optional[str] name=None) |
| | Return reshaped node according to provided parameters. More...
|
| |
| Node | ngraph.opset1.ops.result (NodeInput data, Optional[str] name=None) |
| | Return a node which represents an output of a graph (Function). More...
|
| |
| Node | ngraph.opset1.ops.reverse_sequence (NodeInput input, NodeInput seq_lengths, NumericData batch_axis, NumericData seq_axis, Optional[str] name=None) |
| | Return a node which produces a ReverseSequence operation. More...
|
| |
| Node | ngraph.opset1.ops.select (NodeInput cond, NodeInput then_node, NodeInput else_node, str auto_broadcast="numpy", Optional[str] name=None) |
| | Perform an element-wise selection operation on input tensors. More...
|
| |
| Node | ngraph.opset1.ops.selu (NodeInput data, NodeInput alpha, NodeInput lambda_value, Optional[str] name=None) |
| | Perform a Scaled Exponential Linear Unit (SELU) operation on input node element-wise. More...
|
| |
| Node | ngraph.opset1.ops.shape_of (NodeInput data, Optional[str] name=None) |
| | Return a node which produces a tensor containing the shape of its input data. More...
|
| |
| Node | ngraph.opset1.ops.sigmoid (NodeInput data, Optional[str] name=None) |
| | Return a node which applies the sigmoid function element-wise. More...
|
| |
| Node | ngraph.opset1.ops.sign (NodeInput node, Optional[str] name=None) |
| | Perform element-wise sign operation. More...
|
| |
| Node | ngraph.opset1.ops.sin (NodeInput node, Optional[str] name=None) |
| | Apply sine function on the input node element-wise. More...
|
| |
| Node | ngraph.opset1.ops.sinh (NodeInput node, Optional[str] name=None) |
| | Apply hyperbolic sine function on the input node element-wise. More...
|
| |
| Node | ngraph.opset1.ops.softmax (NodeInput data, int axis, Optional[str] name=None) |
| | Apply softmax operation on each element of input tensor. More...
|
| |
| Node | ngraph.opset1.ops.space_to_depth (Node data, str mode, int block_size=1, str name=None) |
| | Perform SpaceToDepth operation on the input tensor. More...
|
| |
| Node | ngraph.opset1.ops.split (NodeInput data, NodeInput axis, int num_splits, Optional[str] name=None) |
| | Return a node which splits the input tensor into same-length slices. More...
|
| |
| Node | ngraph.opset1.ops.sqrt (NodeInput node, Optional[str] name=None) |
| | Return node which applies square root to the input node element-wise. More...
|
| |
| Node | ngraph.opset1.ops.squared_difference (NodeInput x1, NodeInput x2, str auto_broadcast="NUMPY", Optional[str] name=None) |
| | Perform an element-wise squared difference between two tensors. More...
|
| |
| Node | ngraph.opset1.ops.squeeze (NodeInput data, NodeInput axes, Optional[str] name=None) |
| | Perform squeeze operation on input tensor. More...
|
| |
| Node | ngraph.opset1.ops.strided_slice (NodeInput data, NodeInput begin, NodeInput end, NodeInput strides, List[int] begin_mask, List[int] end_mask, Optional[List[int]] new_axis_mask=None, Optional[List[int]] shrink_axis_mask=None, Optional[List[int]] ellipsis_mask=None, Optional[str] name=None) |
| | Return a node which dynamically repeats(replicates) the input data tensor. More...
|
| |
| Node | ngraph.opset1.ops.subtract (NodeInput left_node, NodeInput right_node, str auto_broadcast="NUMPY", Optional[str] name=None) |
| | Return node which applies f(x) = A-B to the input nodes element-wise. More...
|
| |
| Node | ngraph.opset1.ops.tan (NodeInput node, Optional[str] name=None) |
| | Apply tangent function on the input node element-wise. More...
|
| |
| Node | ngraph.opset1.ops.tanh (NodeInput node, Optional[str] name=None) |
| | Return node which applies hyperbolic tangent to the input node element-wise. More...
|
| |
| Node | ngraph.opset1.ops.tensor_iterator (List[Node] inputs, GraphBody graph_body, List[TensorIteratorSliceInputDesc] slice_input_desc, List[TensorIteratorMergedInputDesc] merged_input_desc, List[TensorIteratorInvariantInputDesc] invariant_input_desc, List[TensorIteratorBodyOutputDesc] body_output_desc, List[TensorIteratorConcatOutputDesc] concat_output_desc, Optional[str] name=None) |
| | Perform recurrent execution of the network described in the body, iterating through the data. More...
|
| |
| Node | ngraph.opset1.ops.tile (NodeInput data, NodeInput repeats, Optional[str] name=None) |
| | Return a node which dynamically repeats(replicates) the input data tensor. More...
|
| |
| Node | ngraph.opset1.ops.topk (NodeInput data, NodeInput k, int axis, str mode, str sort, Optional[str] name=None) |
| | Return a node which performs TopK. More...
|
| |
| Node | ngraph.opset1.ops.transpose (NodeInput data, NodeInput input_order, Optional[str] name=None) |
| | Return a node which transposes the data in the input tensor. More...
|
| |
| Node | ngraph.opset1.ops.unsqueeze (NodeInput data, NodeInput axes, Optional[str] name=None) |
| | Perform unsqueeze operation on input tensor. More...
|
| |
| Node | ngraph.opset1.ops.variadic_split (NodeInput data, NodeInput axis, NodeInput split_lengths, Optional[str] name=None) |
| | Return a node which splits the input tensor into variadic length slices. More...
|
| |
