118 lines
6.2 KiB
Python
118 lines
6.2 KiB
Python
# type: ignore
|
|
from . import ops
|
|
from __future__ import annotations
|
|
from openvino._pyopenvino.op import tensor_iterator
|
|
from openvino.opset1.ops import absolute
|
|
from openvino.opset1.ops import absolute as abs
|
|
from openvino.opset1.ops import acos
|
|
from openvino.opset1.ops import add
|
|
from openvino.opset1.ops import asin
|
|
from openvino.opset1.ops import atan
|
|
from openvino.opset1.ops import avg_pool
|
|
from openvino.opset1.ops import batch_norm_inference
|
|
from openvino.opset1.ops import binary_convolution
|
|
from openvino.opset1.ops import broadcast
|
|
from openvino.opset1.ops import ceiling
|
|
from openvino.opset1.ops import ceiling as ceil
|
|
from openvino.opset1.ops import clamp
|
|
from openvino.opset1.ops import concat
|
|
from openvino.opset1.ops import constant
|
|
from openvino.opset1.ops import convert
|
|
from openvino.opset1.ops import convert_like
|
|
from openvino.opset1.ops import convolution
|
|
from openvino.opset1.ops import convolution_backprop_data
|
|
from openvino.opset1.ops import cos
|
|
from openvino.opset1.ops import cosh
|
|
from openvino.opset1.ops import ctc_greedy_decoder
|
|
from openvino.opset1.ops import deformable_convolution
|
|
from openvino.opset1.ops import deformable_psroi_pooling
|
|
from openvino.opset1.ops import depth_to_space
|
|
from openvino.opset1.ops import detection_output
|
|
from openvino.opset1.ops import divide
|
|
from openvino.opset1.ops import elu
|
|
from openvino.opset1.ops import equal
|
|
from openvino.opset1.ops import erf
|
|
from openvino.opset1.ops import exp
|
|
from openvino.opset1.ops import fake_quantize
|
|
from openvino.opset1.ops import floor
|
|
from openvino.opset1.ops import floor_mod
|
|
from openvino.opset1.ops import gather
|
|
from openvino.opset1.ops import gather_tree
|
|
from openvino.opset1.ops import greater
|
|
from openvino.opset1.ops import greater_equal
|
|
from openvino.opset1.ops import grn
|
|
from openvino.opset1.ops import group_convolution
|
|
from openvino.opset1.ops import group_convolution_backprop_data
|
|
from openvino.opset1.ops import hard_sigmoid
|
|
from openvino.opset1.ops import interpolate
|
|
from openvino.opset1.ops import less
|
|
from openvino.opset1.ops import less_equal
|
|
from openvino.opset1.ops import log
|
|
from openvino.opset1.ops import logical_and
|
|
from openvino.opset1.ops import logical_not
|
|
from openvino.opset1.ops import logical_or
|
|
from openvino.opset1.ops import logical_xor
|
|
from openvino.opset1.ops import lrn
|
|
from openvino.opset1.ops import lstm_cell
|
|
from openvino.opset1.ops import matmul
|
|
from openvino.opset1.ops import max_pool
|
|
from openvino.opset1.ops import maximum
|
|
from openvino.opset1.ops import minimum
|
|
from openvino.opset1.ops import mod
|
|
from openvino.opset1.ops import multiply
|
|
from openvino.opset1.ops import negative
|
|
from openvino.opset1.ops import non_max_suppression
|
|
from openvino.opset1.ops import normalize_l2
|
|
from openvino.opset1.ops import not_equal
|
|
from openvino.opset1.ops import one_hot
|
|
from openvino.opset1.ops import pad
|
|
from openvino.opset1.ops import parameter
|
|
from openvino.opset1.ops import power
|
|
from openvino.opset1.ops import prelu
|
|
from openvino.opset1.ops import prior_box
|
|
from openvino.opset1.ops import prior_box_clustered
|
|
from openvino.opset1.ops import proposal
|
|
from openvino.opset1.ops import psroi_pooling
|
|
from openvino.opset1.ops import range
|
|
from openvino.opset1.ops import reduce_logical_and
|
|
from openvino.opset1.ops import reduce_logical_or
|
|
from openvino.opset1.ops import reduce_max
|
|
from openvino.opset1.ops import reduce_mean
|
|
from openvino.opset1.ops import reduce_min
|
|
from openvino.opset1.ops import reduce_prod
|
|
from openvino.opset1.ops import reduce_sum
|
|
from openvino.opset1.ops import region_yolo
|
|
from openvino.opset1.ops import relu
|
|
from openvino.opset1.ops import reshape
|
|
from openvino.opset1.ops import result
|
|
from openvino.opset1.ops import reverse_sequence
|
|
from openvino.opset1.ops import select
|
|
from openvino.opset1.ops import selu
|
|
from openvino.opset1.ops import shape_of
|
|
from openvino.opset1.ops import sigmoid
|
|
from openvino.opset1.ops import sign
|
|
from openvino.opset1.ops import sin
|
|
from openvino.opset1.ops import sinh
|
|
from openvino.opset1.ops import softmax
|
|
from openvino.opset1.ops import space_to_depth
|
|
from openvino.opset1.ops import split
|
|
from openvino.opset1.ops import sqrt
|
|
from openvino.opset1.ops import squared_difference
|
|
from openvino.opset1.ops import squeeze
|
|
from openvino.opset1.ops import strided_slice
|
|
from openvino.opset1.ops import subtract
|
|
from openvino.opset1.ops import tan
|
|
from openvino.opset1.ops import tanh
|
|
from openvino.opset1.ops import tile
|
|
from openvino.opset1.ops import topk
|
|
from openvino.opset1.ops import transpose
|
|
from openvino.opset1.ops import unsqueeze
|
|
from openvino.opset1.ops import variadic_split
|
|
from openvino.opset2.ops import batch_to_space
|
|
from openvino.opset2.ops import gelu
|
|
from openvino.opset2.ops import mvn
|
|
from openvino.opset2.ops import reorg_yolo
|
|
from openvino.opset2.ops import roi_pooling
|
|
from openvino.opset2.ops import space_to_batch
|
|
__all__ = ['abs', 'absolute', 'acos', 'add', 'asin', 'atan', 'avg_pool', 'batch_norm_inference', 'batch_to_space', 'binary_convolution', 'broadcast', 'ceil', 'ceiling', 'clamp', 'concat', 'constant', 'convert', 'convert_like', 'convolution', 'convolution_backprop_data', 'cos', 'cosh', 'ctc_greedy_decoder', 'deformable_convolution', 'deformable_psroi_pooling', 'depth_to_space', 'detection_output', 'divide', 'elu', 'equal', 'erf', 'exp', 'fake_quantize', 'floor', 'floor_mod', 'gather', 'gather_tree', 'gelu', 'greater', 'greater_equal', 'grn', 'group_convolution', 'group_convolution_backprop_data', 'hard_sigmoid', 'interpolate', 'less', 'less_equal', 'log', 'logical_and', 'logical_not', 'logical_or', 'logical_xor', 'lrn', 'lstm_cell', 'matmul', 'max_pool', 'maximum', 'minimum', 'mod', 'multiply', 'mvn', 'negative', 'non_max_suppression', 'normalize_l2', 'not_equal', 'one_hot', 'ops', 'pad', 'parameter', 'power', 'prelu', 'prior_box', 'prior_box_clustered', 'proposal', 'psroi_pooling', 'range', 'reduce_logical_and', 'reduce_logical_or', 'reduce_max', 'reduce_mean', 'reduce_min', 'reduce_prod', 'reduce_sum', 'region_yolo', 'relu', 'reorg_yolo', 'reshape', 'result', 'reverse_sequence', 'roi_pooling', 'select', 'selu', 'shape_of', 'sigmoid', 'sign', 'sin', 'sinh', 'softmax', 'space_to_batch', 'space_to_depth', 'split', 'sqrt', 'squared_difference', 'squeeze', 'strided_slice', 'subtract', 'tan', 'tanh', 'tensor_iterator', 'tile', 'topk', 'transpose', 'unsqueeze', 'variadic_split']
|