Interpolate 11 exposed to Python (#16465)
This commit is contained in:
Tomasz Dołbniak
GitHub
parent
5290822f8b
commit
951c5fdae9
@ -73,6 +73,12 @@ OpenVINO Python API
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openvino.runtime.opset10
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.. autosummary::
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:toctree: _autosummary
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:template: custom-module-template.rst
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openvino.runtime.opset11
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.. autosummary::
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:toctree: _autosummary
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:template: custom-module-template.rst
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@ -95,4 +101,4 @@ OpenVINO Python API
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:maxdepth: 2
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:hidden:
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compatibility
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compatibility
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@ -55,6 +55,7 @@ packages = [
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"openvino.runtime.opset8",
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"openvino.runtime.opset9",
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"openvino.runtime.opset10",
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"openvino.runtime.opset11",
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"openvino.runtime.utils",
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"openvino.runtime.op",
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"openvino.runtime.op.util",
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@ -18,180 +18,180 @@ from ngraph.impl import Node
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from ngraph.impl import PartialShape
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from ngraph.helpers import function_from_cnn
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from ngraph.helpers import function_to_cnn
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from ngraph.opset10 import absolute
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from ngraph.opset10 import absolute as abs
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from ngraph.opset10 import acos
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from ngraph.opset10 import acosh
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from ngraph.opset10 import adaptive_avg_pool
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from ngraph.opset10 import adaptive_max_pool
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from ngraph.opset10 import add
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from ngraph.opset10 import asin
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from ngraph.opset10 import asinh
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from ngraph.opset10 import assign
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from ngraph.opset10 import atan
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from ngraph.opset10 import atanh
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from ngraph.opset10 import avg_pool
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from ngraph.opset10 import batch_norm_inference
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from ngraph.opset10 import batch_to_space
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from ngraph.opset10 import binary_convolution
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from ngraph.opset10 import broadcast
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from ngraph.opset10 import bucketize
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from ngraph.opset10 import ceiling
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from ngraph.opset10 import ceiling as ceil
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from ngraph.opset10 import clamp
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from ngraph.opset10 import concat
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from ngraph.opset10 import constant
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from ngraph.opset10 import convert
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from ngraph.opset10 import convert_like
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from ngraph.opset10 import convolution
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from ngraph.opset10 import convolution_backprop_data
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from ngraph.opset10 import cos
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from ngraph.opset10 import cosh
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from ngraph.opset10 import ctc_greedy_decoder
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from ngraph.opset10 import ctc_greedy_decoder_seq_len
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from ngraph.opset10 import ctc_loss
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from ngraph.opset10 import cum_sum
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from ngraph.opset10 import cum_sum as cumsum
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from ngraph.opset10 import deformable_convolution
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from ngraph.opset10 import deformable_psroi_pooling
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from ngraph.opset10 import depth_to_space
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from ngraph.opset10 import detection_output
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from ngraph.opset10 import dft
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from ngraph.opset10 import divide
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from ngraph.opset10 import einsum
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from ngraph.opset10 import elu
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from ngraph.opset10 import embedding_bag_offsets_sum
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from ngraph.opset10 import embedding_bag_packed_sum
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from ngraph.opset10 import embedding_segments_sum
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from ngraph.opset10 import extract_image_patches
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from ngraph.opset10 import equal
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from ngraph.opset10 import erf
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from ngraph.opset10 import exp
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from ngraph.opset10 import eye
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from ngraph.opset10 import fake_quantize
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from ngraph.opset10 import floor
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from ngraph.opset10 import floor_mod
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from ngraph.opset10 import gather
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from ngraph.opset10 import gather_elements
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from ngraph.opset10 import gather_nd
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from ngraph.opset10 import gather_tree
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from ngraph.opset10 import gelu
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from ngraph.opset10 import generate_proposals
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from ngraph.opset10 import greater
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from ngraph.opset10 import greater_equal
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from ngraph.opset10 import grid_sample
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from ngraph.opset10 import grn
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from ngraph.opset10 import group_convolution
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from ngraph.opset10 import group_convolution_backprop_data
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from ngraph.opset10 import gru_cell
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from ngraph.opset10 import gru_sequence
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from ngraph.opset10 import hard_sigmoid
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from ngraph.opset10 import hsigmoid
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from ngraph.opset10 import hswish
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from ngraph.opset10 import idft
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from ngraph.opset10 import if_op
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from ngraph.opset10 import interpolate
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from ngraph.opset10 import irdft
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from ngraph.opset10 import is_finite
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from ngraph.opset10 import is_inf
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from ngraph.opset10 import is_nan
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from ngraph.opset10 import i420_to_bgr
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from ngraph.opset10 import i420_to_rgb
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from ngraph.opset10 import less
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from ngraph.opset10 import less_equal
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from ngraph.opset10 import log
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from ngraph.opset10 import logical_and
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from ngraph.opset10 import logical_not
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from ngraph.opset10 import logical_or
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from ngraph.opset10 import logical_xor
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from ngraph.opset10 import log_softmax
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from ngraph.opset10 import loop
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from ngraph.opset10 import lrn
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from ngraph.opset10 import lstm_cell
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from ngraph.opset10 import lstm_sequence
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from ngraph.opset10 import matmul
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from ngraph.opset10 import matrix_nms
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from ngraph.opset10 import max_pool
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from ngraph.opset10 import maximum
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from ngraph.opset10 import minimum
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from ngraph.opset10 import mish
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from ngraph.opset10 import mod
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from ngraph.opset10 import multiclass_nms
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from ngraph.opset10 import multiply
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from ngraph.opset10 import mvn
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from ngraph.opset10 import negative
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from ngraph.opset10 import non_max_suppression
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from ngraph.opset10 import non_zero
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from ngraph.opset10 import normalize_l2
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from ngraph.opset10 import not_equal
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from ngraph.opset10 import nv12_to_bgr
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from ngraph.opset10 import nv12_to_rgb
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from ngraph.opset10 import one_hot
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from ngraph.opset10 import pad
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from ngraph.opset10 import parameter
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from ngraph.opset10 import power
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from ngraph.opset10 import prelu
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from ngraph.opset10 import prior_box
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from ngraph.opset10 import prior_box_clustered
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from ngraph.opset10 import psroi_pooling
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from ngraph.opset10 import proposal
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from ngraph.opset10 import random_uniform
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from ngraph.opset10 import range
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from ngraph.opset10 import rdft
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from ngraph.opset10 import read_value
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from ngraph.opset10 import reduce_l1
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from ngraph.opset10 import reduce_l2
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from ngraph.opset10 import reduce_logical_and
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from ngraph.opset10 import reduce_logical_or
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from ngraph.opset10 import reduce_max
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from ngraph.opset10 import reduce_mean
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from ngraph.opset10 import reduce_min
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from ngraph.opset10 import reduce_prod
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from ngraph.opset10 import reduce_sum
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from ngraph.opset10 import region_yolo
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from ngraph.opset10 import reorg_yolo
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from ngraph.opset10 import relu
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from ngraph.opset10 import reshape
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from ngraph.opset10 import result
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from ngraph.opset10 import reverse_sequence
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from ngraph.opset10 import rnn_cell
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from ngraph.opset10 import rnn_sequence
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from ngraph.opset10 import roi_align
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from ngraph.opset10 import roi_pooling
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from ngraph.opset10 import roll
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from ngraph.opset10 import round
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from ngraph.opset10 import scatter_elements_update
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from ngraph.opset10 import scatter_update
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from ngraph.opset10 import select
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from ngraph.opset10 import selu
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from ngraph.opset10 import shape_of
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from ngraph.opset10 import shuffle_channels
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from ngraph.opset10 import sigmoid
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from ngraph.opset10 import sign
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from ngraph.opset10 import sin
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from ngraph.opset10 import sinh
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from ngraph.opset10 import slice
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from ngraph.opset10 import softmax
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from ngraph.opset10 import softplus
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from ngraph.opset10 import softsign
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from ngraph.opset10 import space_to_batch
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from ngraph.opset10 import space_to_depth
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from ngraph.opset10 import split
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from ngraph.opset10 import sqrt
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from ngraph.opset10 import squared_difference
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from ngraph.opset10 import squeeze
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from ngraph.opset10 import strided_slice
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from ngraph.opset10 import subtract
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from ngraph.opset10 import swish
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from ngraph.opset10 import tan
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from ngraph.opset10 import tanh
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from ngraph.opset10 import tensor_iterator
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from ngraph.opset10 import tile
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from ngraph.opset10 import topk
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from ngraph.opset10 import transpose
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from ngraph.opset10 import unique
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from ngraph.opset10 import unsqueeze
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from ngraph.opset10 import variadic_split
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from ngraph.opset11 import absolute
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from ngraph.opset11 import absolute as abs
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from ngraph.opset11 import acos
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from ngraph.opset11 import acosh
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from ngraph.opset11 import adaptive_avg_pool
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from ngraph.opset11 import adaptive_max_pool
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from ngraph.opset11 import add
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from ngraph.opset11 import asin
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from ngraph.opset11 import asinh
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from ngraph.opset11 import assign
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from ngraph.opset11 import atan
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from ngraph.opset11 import atanh
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from ngraph.opset11 import avg_pool
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from ngraph.opset11 import batch_norm_inference
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from ngraph.opset11 import batch_to_space
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from ngraph.opset11 import binary_convolution
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from ngraph.opset11 import broadcast
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from ngraph.opset11 import bucketize
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from ngraph.opset11 import ceiling
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from ngraph.opset11 import ceiling as ceil
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from ngraph.opset11 import clamp
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from ngraph.opset11 import concat
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from ngraph.opset11 import constant
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from ngraph.opset11 import convert
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from ngraph.opset11 import convert_like
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from ngraph.opset11 import convolution
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from ngraph.opset11 import convolution_backprop_data
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from ngraph.opset11 import cos
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from ngraph.opset11 import cosh
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from ngraph.opset11 import ctc_greedy_decoder
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from ngraph.opset11 import ctc_greedy_decoder_seq_len
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from ngraph.opset11 import ctc_loss
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from ngraph.opset11 import cum_sum
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from ngraph.opset11 import cum_sum as cumsum
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from ngraph.opset11 import deformable_convolution
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from ngraph.opset11 import deformable_psroi_pooling
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from ngraph.opset11 import depth_to_space
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from ngraph.opset11 import detection_output
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from ngraph.opset11 import dft
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from ngraph.opset11 import divide
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from ngraph.opset11 import einsum
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from ngraph.opset11 import elu
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from ngraph.opset11 import embedding_bag_offsets_sum
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from ngraph.opset11 import embedding_bag_packed_sum
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from ngraph.opset11 import embedding_segments_sum
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from ngraph.opset11 import extract_image_patches
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from ngraph.opset11 import equal
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from ngraph.opset11 import erf
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from ngraph.opset11 import exp
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from ngraph.opset11 import eye
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from ngraph.opset11 import fake_quantize
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from ngraph.opset11 import floor
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from ngraph.opset11 import floor_mod
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from ngraph.opset11 import gather
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from ngraph.opset11 import gather_elements
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from ngraph.opset11 import gather_nd
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from ngraph.opset11 import gather_tree
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from ngraph.opset11 import gelu
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from ngraph.opset11 import generate_proposals
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from ngraph.opset11 import greater
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from ngraph.opset11 import greater_equal
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from ngraph.opset11 import grid_sample
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from ngraph.opset11 import grn
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from ngraph.opset11 import group_convolution
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from ngraph.opset11 import group_convolution_backprop_data
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from ngraph.opset11 import gru_cell
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from ngraph.opset11 import gru_sequence
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from ngraph.opset11 import hard_sigmoid
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from ngraph.opset11 import hsigmoid
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from ngraph.opset11 import hswish
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from ngraph.opset11 import idft
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from ngraph.opset11 import if_op
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from ngraph.opset11 import interpolate
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from ngraph.opset11 import irdft
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from ngraph.opset11 import is_finite
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from ngraph.opset11 import is_inf
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from ngraph.opset11 import is_nan
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from ngraph.opset11 import i420_to_bgr
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from ngraph.opset11 import i420_to_rgb
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from ngraph.opset11 import less
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from ngraph.opset11 import less_equal
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from ngraph.opset11 import log
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from ngraph.opset11 import logical_and
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from ngraph.opset11 import logical_not
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from ngraph.opset11 import logical_or
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from ngraph.opset11 import logical_xor
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from ngraph.opset11 import log_softmax
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from ngraph.opset11 import loop
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from ngraph.opset11 import lrn
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from ngraph.opset11 import lstm_cell
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from ngraph.opset11 import lstm_sequence
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from ngraph.opset11 import matmul
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from ngraph.opset11 import matrix_nms
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from ngraph.opset11 import max_pool
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from ngraph.opset11 import maximum
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from ngraph.opset11 import minimum
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from ngraph.opset11 import mish
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from ngraph.opset11 import mod
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from ngraph.opset11 import multiclass_nms
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from ngraph.opset11 import multiply
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from ngraph.opset11 import mvn
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from ngraph.opset11 import negative
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from ngraph.opset11 import non_max_suppression
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from ngraph.opset11 import non_zero
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from ngraph.opset11 import normalize_l2
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from ngraph.opset11 import not_equal
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from ngraph.opset11 import nv12_to_bgr
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from ngraph.opset11 import nv12_to_rgb
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from ngraph.opset11 import one_hot
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from ngraph.opset11 import pad
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from ngraph.opset11 import parameter
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from ngraph.opset11 import power
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from ngraph.opset11 import prelu
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from ngraph.opset11 import prior_box
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from ngraph.opset11 import prior_box_clustered
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from ngraph.opset11 import psroi_pooling
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from ngraph.opset11 import proposal
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from ngraph.opset11 import random_uniform
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from ngraph.opset11 import range
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from ngraph.opset11 import rdft
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from ngraph.opset11 import read_value
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from ngraph.opset11 import reduce_l1
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from ngraph.opset11 import reduce_l2
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from ngraph.opset11 import reduce_logical_and
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from ngraph.opset11 import reduce_logical_or
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from ngraph.opset11 import reduce_max
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from ngraph.opset11 import reduce_mean
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from ngraph.opset11 import reduce_min
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from ngraph.opset11 import reduce_prod
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from ngraph.opset11 import reduce_sum
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from ngraph.opset11 import region_yolo
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from ngraph.opset11 import reorg_yolo
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from ngraph.opset11 import relu
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from ngraph.opset11 import reshape
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from ngraph.opset11 import result
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from ngraph.opset11 import reverse_sequence
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from ngraph.opset11 import rnn_cell
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from ngraph.opset11 import rnn_sequence
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from ngraph.opset11 import roi_align
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from ngraph.opset11 import roi_pooling
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from ngraph.opset11 import roll
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from ngraph.opset11 import round
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from ngraph.opset11 import scatter_elements_update
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from ngraph.opset11 import scatter_update
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from ngraph.opset11 import select
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from ngraph.opset11 import selu
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from ngraph.opset11 import shape_of
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from ngraph.opset11 import shuffle_channels
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from ngraph.opset11 import sigmoid
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from ngraph.opset11 import sign
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from ngraph.opset11 import sin
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from ngraph.opset11 import sinh
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from ngraph.opset11 import slice
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from ngraph.opset11 import softmax
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from ngraph.opset11 import softplus
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from ngraph.opset11 import softsign
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from ngraph.opset11 import space_to_batch
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from ngraph.opset11 import space_to_depth
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from ngraph.opset11 import split
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from ngraph.opset11 import sqrt
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from ngraph.opset11 import squared_difference
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from ngraph.opset11 import squeeze
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from ngraph.opset11 import strided_slice
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from ngraph.opset11 import subtract
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from ngraph.opset11 import swish
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from ngraph.opset11 import tan
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from ngraph.opset11 import tanh
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from ngraph.opset11 import tensor_iterator
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from ngraph.opset11 import tile
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from ngraph.opset11 import topk
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from ngraph.opset11 import transpose
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from ngraph.opset11 import unique
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from ngraph.opset11 import unsqueeze
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from ngraph.opset11 import variadic_split
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# Extend Node class to support binary operators
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177
src/bindings/python/src/compatibility/ngraph/opset11/__init__.py
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177
src/bindings/python/src/compatibility/ngraph/opset11/__init__.py
Normal file
@ -0,0 +1,177 @@
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# Copyright (C) 2018-2023 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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from ngraph.opset1.ops import absolute
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from ngraph.opset1.ops import absolute as abs
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from ngraph.opset1.ops import acos
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from ngraph.opset4.ops import acosh
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from ngraph.opset8.ops import adaptive_avg_pool
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from ngraph.opset8.ops import adaptive_max_pool
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from ngraph.opset1.ops import add
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from ngraph.opset1.ops import asin
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from ngraph.opset4.ops import asinh
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from ngraph.opset3.ops import assign
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from ngraph.opset1.ops import atan
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from ngraph.opset4.ops import atanh
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from ngraph.opset1.ops import avg_pool
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from ngraph.opset5.ops import batch_norm_inference
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from ngraph.opset2.ops import batch_to_space
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from ngraph.opset1.ops import binary_convolution
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from ngraph.opset3.ops import broadcast
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from ngraph.opset3.ops import bucketize
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from ngraph.opset1.ops import ceiling
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from ngraph.opset1.ops import ceiling as ceil
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from ngraph.opset1.ops import clamp
|
||||
from ngraph.opset1.ops import concat
|
||||
from ngraph.opset1.ops import constant
|
||||
from ngraph.opset1.ops import convert
|
||||
from ngraph.opset1.ops import convert_like
|
||||
from ngraph.opset1.ops import convolution
|
||||
from ngraph.opset1.ops import convolution_backprop_data
|
||||
from ngraph.opset1.ops import cos
|
||||
from ngraph.opset1.ops import cosh
|
||||
from ngraph.opset1.ops import ctc_greedy_decoder
|
||||
from ngraph.opset6.ops import ctc_greedy_decoder_seq_len
|
||||
from ngraph.opset4.ops import ctc_loss
|
||||
from ngraph.opset3.ops import cum_sum
|
||||
from ngraph.opset3.ops import cum_sum as cumsum
|
||||
from ngraph.opset8.ops import deformable_convolution
|
||||
from ngraph.opset1.ops import deformable_psroi_pooling
|
||||
from ngraph.opset1.ops import depth_to_space
|
||||
from ngraph.opset8.ops import detection_output
|
||||
from ngraph.opset7.ops import dft
|
||||
from ngraph.opset1.ops import divide
|
||||
from ngraph.opset7.ops import einsum
|
||||
from ngraph.opset1.ops import elu
|
||||
from ngraph.opset3.ops import embedding_bag_offsets_sum
|
||||
from ngraph.opset3.ops import embedding_bag_packed_sum
|
||||
from ngraph.opset3.ops import embedding_segments_sum
|
||||
from ngraph.opset3.ops import extract_image_patches
|
||||
from ngraph.opset1.ops import equal
|
||||
from ngraph.opset1.ops import erf
|
||||
from ngraph.opset1.ops import exp
|
||||
from ngraph.opset9.ops import eye
|
||||
from ngraph.opset1.ops import fake_quantize
|
||||
from ngraph.opset1.ops import floor
|
||||
from ngraph.opset1.ops import floor_mod
|
||||
from ngraph.opset8.ops import gather
|
||||
from ngraph.opset6.ops import gather_elements
|
||||
from ngraph.opset8.ops import gather_nd
|
||||
from ngraph.opset1.ops import gather_tree
|
||||
from ngraph.opset7.ops import gelu
|
||||
from ngraph.opset9.ops import generate_proposals
|
||||
from ngraph.opset1.ops import greater
|
||||
from ngraph.opset1.ops import greater_equal
|
||||
from ngraph.opset9.ops import grid_sample
|
||||
from ngraph.opset1.ops import grn
|
||||
from ngraph.opset1.ops import group_convolution
|
||||
from ngraph.opset1.ops import group_convolution_backprop_data
|
||||
from ngraph.opset3.ops import gru_cell
|
||||
from ngraph.opset5.ops import gru_sequence
|
||||
from ngraph.opset1.ops import hard_sigmoid
|
||||
from ngraph.opset5.ops import hsigmoid
|
||||
from ngraph.opset4.ops import hswish
|
||||
from ngraph.opset7.ops import idft
|
||||
from ngraph.opset8.ops import if_op
|
||||
from ngraph.opset11.ops import interpolate
|
||||
from ngraph.opset9.ops import irdft
|
||||
from ngraph.opset10.ops import is_finite
|
||||
from ngraph.opset10.ops import is_inf
|
||||
from ngraph.opset10.ops import is_nan
|
||||
from ngraph.opset8.ops import i420_to_bgr
|
||||
from ngraph.opset8.ops import i420_to_rgb
|
||||
from ngraph.opset1.ops import less
|
||||
from ngraph.opset1.ops import less_equal
|
||||
from ngraph.opset1.ops import log
|
||||
from ngraph.opset1.ops import logical_and
|
||||
from ngraph.opset1.ops import logical_not
|
||||
from ngraph.opset1.ops import logical_or
|
||||
from ngraph.opset1.ops import logical_xor
|
||||
from ngraph.opset5.ops import log_softmax
|
||||
from ngraph.opset5.ops import loop
|
||||
from ngraph.opset1.ops import lrn
|
||||
from ngraph.opset4.ops import lstm_cell
|
||||
from ngraph.opset5.ops import lstm_sequence
|
||||
from ngraph.opset1.ops import matmul
|
||||
from ngraph.opset8.ops import matrix_nms
|
||||
from ngraph.opset8.ops import max_pool
|
||||
from ngraph.opset1.ops import maximum
|
||||
from ngraph.opset1.ops import minimum
|
||||
from ngraph.opset4.ops import mish
|
||||
from ngraph.opset1.ops import mod
|
||||
from ngraph.opset9.ops import multiclass_nms
|
||||
from ngraph.opset1.ops import multiply
|
||||
from ngraph.opset6.ops import mvn
|
||||
from ngraph.opset1.ops import negative
|
||||
from ngraph.opset9.ops import non_max_suppression
|
||||
from ngraph.opset3.ops import non_zero
|
||||
from ngraph.opset1.ops import normalize_l2
|
||||
from ngraph.opset1.ops import not_equal
|
||||
from ngraph.opset8.ops import nv12_to_bgr
|
||||
from ngraph.opset8.ops import nv12_to_rgb
|
||||
from ngraph.opset1.ops import one_hot
|
||||
from ngraph.opset1.ops import pad
|
||||
from ngraph.opset1.ops import parameter
|
||||
from ngraph.opset1.ops import power
|
||||
from ngraph.opset1.ops import prelu
|
||||
from ngraph.opset8.ops import prior_box
|
||||
from ngraph.opset1.ops import prior_box_clustered
|
||||
from ngraph.opset1.ops import psroi_pooling
|
||||
from ngraph.opset4.ops import proposal
|
||||
from ngraph.opset8.ops import random_uniform
|
||||
from ngraph.opset1.ops import range
|
||||
from ngraph.opset9.ops import rdft
|
||||
from ngraph.opset3.ops import read_value
|
||||
from ngraph.opset4.ops import reduce_l1
|
||||
from ngraph.opset4.ops import reduce_l2
|
||||
from ngraph.opset1.ops import reduce_logical_and
|
||||
from ngraph.opset1.ops import reduce_logical_or
|
||||
from ngraph.opset1.ops import reduce_max
|
||||
from ngraph.opset1.ops import reduce_mean
|
||||
from ngraph.opset1.ops import reduce_min
|
||||
from ngraph.opset1.ops import reduce_prod
|
||||
from ngraph.opset1.ops import reduce_sum
|
||||
from ngraph.opset1.ops import region_yolo
|
||||
from ngraph.opset2.ops import reorg_yolo
|
||||
from ngraph.opset1.ops import relu
|
||||
from ngraph.opset1.ops import reshape
|
||||
from ngraph.opset1.ops import result
|
||||
from ngraph.opset1.ops import reverse_sequence
|
||||
from ngraph.opset3.ops import rnn_cell
|
||||
from ngraph.opset5.ops import rnn_sequence
|
||||
from ngraph.opset9.ops import roi_align
|
||||
from ngraph.opset2.ops import roi_pooling
|
||||
from ngraph.opset7.ops import roll
|
||||
from ngraph.opset5.ops import round
|
||||
from ngraph.opset3.ops import scatter_elements_update
|
||||
from ngraph.opset3.ops import scatter_update
|
||||
from ngraph.opset1.ops import select
|
||||
from ngraph.opset1.ops import selu
|
||||
from ngraph.opset3.ops import shape_of
|
||||
from ngraph.opset3.ops import shuffle_channels
|
||||
from ngraph.opset1.ops import sigmoid
|
||||
from ngraph.opset1.ops import sign
|
||||
from ngraph.opset1.ops import sin
|
||||
from ngraph.opset1.ops import sinh
|
||||
from ngraph.opset8.ops import slice
|
||||
from ngraph.opset8.ops import softmax
|
||||
from ngraph.opset4.ops import softplus
|
||||
from ngraph.opset9.ops import softsign
|
||||
from ngraph.opset2.ops import space_to_batch
|
||||
from ngraph.opset1.ops import space_to_depth
|
||||
from ngraph.opset1.ops import split
|
||||
from ngraph.opset1.ops import sqrt
|
||||
from ngraph.opset1.ops import squared_difference
|
||||
from ngraph.opset1.ops import squeeze
|
||||
from ngraph.opset1.ops import strided_slice
|
||||
from ngraph.opset1.ops import subtract
|
||||
from ngraph.opset4.ops import swish
|
||||
from ngraph.opset1.ops import tan
|
||||
from ngraph.opset1.ops import tanh
|
||||
from ngraph.opset1.ops import tensor_iterator
|
||||
from ngraph.opset1.ops import tile
|
||||
from ngraph.opset3.ops import topk
|
||||
from ngraph.opset1.ops import transpose
|
||||
from ngraph.opset10.ops import unique
|
||||
from ngraph.opset1.ops import unsqueeze
|
||||
from ngraph.opset1.ops import variadic_split
|
||||
77
src/bindings/python/src/compatibility/ngraph/opset11/ops.py
Normal file
77
src/bindings/python/src/compatibility/ngraph/opset11/ops.py
Normal file
@ -0,0 +1,77 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
# Copyright (C) 2018-2023 Intel Corporation
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
|
||||
"""Factory functions for all openvino ops."""
|
||||
from functools import partial
|
||||
from typing import List, Optional
|
||||
|
||||
from ngraph.impl import Node
|
||||
from ngraph.opset_utils import _get_node_factory
|
||||
from ngraph.utils.decorators import nameable_op
|
||||
from ngraph.utils.types import (
|
||||
NodeInput,
|
||||
as_nodes,
|
||||
)
|
||||
|
||||
_get_node_factory_opset11 = partial(_get_node_factory, "opset11")
|
||||
|
||||
# -------------------------------------------- ops ------------------------------------------------
|
||||
|
||||
|
||||
@nameable_op
|
||||
def interpolate(
|
||||
image: NodeInput,
|
||||
scales_or_sizes: NodeInput,
|
||||
mode: str,
|
||||
shape_calculation_mode: str,
|
||||
pads_begin: Optional[List[int]] = None,
|
||||
pads_end: Optional[List[int]] = None,
|
||||
coordinate_transformation_mode: str = "half_pixel",
|
||||
nearest_mode: str = "round_prefer_floor",
|
||||
antialias: bool = False,
|
||||
cube_coeff: float = -0.75,
|
||||
axes: Optional[NodeInput] = None,
|
||||
name: Optional[str] = None,
|
||||
) -> Node:
|
||||
"""Perfors the interpolation of the input tensor.
|
||||
|
||||
:param image: The node providing input tensor with data for interpolation.
|
||||
:param scales_or_sizes:
|
||||
1D tensor providing information used to calculate the output shape
|
||||
of the operation. It might contain floats (scales) or integers(sizes).
|
||||
:param mode: Specifies type of interpolation. Possible values are: nearest, linear,
|
||||
linear_onnx, cubic, bilinear_pillow, bicubic_pillow.
|
||||
:param shape_calculation_mode:
|
||||
Specifies how the scales_or_sizes input should be interpreted.
|
||||
:param pads_begin: Specifies the number of pixels to add to the beginning of the image
|
||||
being interpolated. Default is None.
|
||||
:param pads_end: Specifies the number of pixels to add to the end of the image being
|
||||
interpolated. Default is None.
|
||||
:param coordinate_transformation_mode:
|
||||
Specifies how to transform the coordinate in the resized tensor to the
|
||||
coordinate in the original tensor. Default is "half_pixel".
|
||||
:param nearest_mode: Specifies round mode when mode == nearest and is used only when
|
||||
mode == nearest. Default is "round_prefer_floor".
|
||||
:param antialias: Specifies whether to perform anti-aliasing. Default is False.
|
||||
:param cube_coeff: Specifies the parameter a for cubic interpolation. Default is -0.75.
|
||||
:param axes: 1D tensor specifying dimension indices where interpolation is applied.
|
||||
The default is None.
|
||||
:param name: Optional name for the output node. The default is None.
|
||||
:return: Node representing the interpolation operation.
|
||||
"""
|
||||
attrs = {
|
||||
"mode": mode,
|
||||
"shape_calculation_mode": shape_calculation_mode,
|
||||
"coordinate_transformation_mode": coordinate_transformation_mode,
|
||||
"nearest_mode": nearest_mode,
|
||||
"antialias": antialias,
|
||||
"cube_coeff": cube_coeff,
|
||||
}
|
||||
|
||||
attrs["pads_begin"] = [] if pads_begin is None else pads_begin
|
||||
attrs["pads_end"] = [] if pads_end is None else pads_end
|
||||
|
||||
inputs = as_nodes(image, scales_or_sizes) if axes is None else as_nodes(image, scales_or_sizes, axes)
|
||||
|
||||
return _get_node_factory_opset11().create("Interpolate", inputs, attrs)
|
||||
@ -12,7 +12,7 @@ from ngraph.impl import Node, Output
|
||||
|
||||
from ngraph.exceptions import UserInputError
|
||||
|
||||
DEFAULT_OPSET = "opset10"
|
||||
DEFAULT_OPSET = "opset11"
|
||||
|
||||
|
||||
class NodeFactory(object):
|
||||
|
||||
@ -82,7 +82,7 @@ private:
|
||||
return it->second();
|
||||
}
|
||||
|
||||
const ngraph::OpSet& m_opset = ngraph::get_opset10();
|
||||
const ngraph::OpSet& m_opset = ngraph::get_opset11();
|
||||
std::unordered_map<std::string, std::shared_ptr<ngraph::Variable>> m_variables;
|
||||
};
|
||||
} // namespace
|
||||
|
||||
@ -56,6 +56,7 @@ from openvino.runtime import opset7
|
||||
from openvino.runtime import opset8
|
||||
from openvino.runtime import opset9
|
||||
from openvino.runtime import opset10
|
||||
from openvino.runtime import opset11
|
||||
|
||||
# Import properties API
|
||||
from openvino._pyopenvino import properties
|
||||
@ -66,19 +67,19 @@ from openvino.runtime.ie_api import compile_model
|
||||
|
||||
|
||||
# Extend Node class to support binary operators
|
||||
Node.__add__ = opset10.add
|
||||
Node.__sub__ = opset10.subtract
|
||||
Node.__mul__ = opset10.multiply
|
||||
Node.__div__ = opset10.divide
|
||||
Node.__truediv__ = opset10.divide
|
||||
Node.__radd__ = lambda left, right: opset10.add(right, left)
|
||||
Node.__rsub__ = lambda left, right: opset10.subtract(right, left)
|
||||
Node.__rmul__ = lambda left, right: opset10.multiply(right, left)
|
||||
Node.__rdiv__ = lambda left, right: opset10.divide(right, left)
|
||||
Node.__rtruediv__ = lambda left, right: opset10.divide(right, left)
|
||||
Node.__eq__ = opset10.equal
|
||||
Node.__ne__ = opset10.not_equal
|
||||
Node.__lt__ = opset10.less
|
||||
Node.__le__ = opset10.less_equal
|
||||
Node.__gt__ = opset10.greater
|
||||
Node.__ge__ = opset10.greater_equal
|
||||
Node.__add__ = opset11.add
|
||||
Node.__sub__ = opset11.subtract
|
||||
Node.__mul__ = opset11.multiply
|
||||
Node.__div__ = opset11.divide
|
||||
Node.__truediv__ = opset11.divide
|
||||
Node.__radd__ = lambda left, right: opset11.add(right, left)
|
||||
Node.__rsub__ = lambda left, right: opset11.subtract(right, left)
|
||||
Node.__rmul__ = lambda left, right: opset11.multiply(right, left)
|
||||
Node.__rdiv__ = lambda left, right: opset11.divide(right, left)
|
||||
Node.__rtruediv__ = lambda left, right: opset11.divide(right, left)
|
||||
Node.__eq__ = opset11.equal
|
||||
Node.__ne__ = opset11.not_equal
|
||||
Node.__lt__ = opset11.less
|
||||
Node.__le__ = opset11.less_equal
|
||||
Node.__gt__ = opset11.greater
|
||||
Node.__ge__ = opset11.greater_equal
|
||||
|
||||
178
src/bindings/python/src/openvino/runtime/opset11/__init__.py
Normal file
178
src/bindings/python/src/openvino/runtime/opset11/__init__.py
Normal file
@ -0,0 +1,178 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
# Copyright (C) 2018-2023 Intel Corporation
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
|
||||
from openvino.runtime.opset1.ops import absolute
|
||||
from openvino.runtime.opset1.ops import absolute as abs
|
||||
from openvino.runtime.opset1.ops import acos
|
||||
from openvino.runtime.opset4.ops import acosh
|
||||
from openvino.runtime.opset8.ops import adaptive_avg_pool
|
||||
from openvino.runtime.opset8.ops import adaptive_max_pool
|
||||
from openvino.runtime.opset1.ops import add
|
||||
from openvino.runtime.opset1.ops import asin
|
||||
from openvino.runtime.opset4.ops import asinh
|
||||
from openvino.runtime.opset3.ops import assign
|
||||
from openvino.runtime.opset1.ops import atan
|
||||
from openvino.runtime.opset4.ops import atanh
|
||||
from openvino.runtime.opset1.ops import avg_pool
|
||||
from openvino.runtime.opset5.ops import batch_norm_inference
|
||||
from openvino.runtime.opset2.ops import batch_to_space
|
||||
from openvino.runtime.opset1.ops import binary_convolution
|
||||
from openvino.runtime.opset3.ops import broadcast
|
||||
from openvino.runtime.opset3.ops import bucketize
|
||||
from openvino.runtime.opset1.ops import ceiling
|
||||
from openvino.runtime.opset1.ops import ceiling as ceil
|
||||
from openvino.runtime.opset1.ops import clamp
|
||||
from openvino.runtime.opset1.ops import concat
|
||||
from openvino.runtime.opset1.ops import constant
|
||||
from openvino.runtime.opset1.ops import convert
|
||||
from openvino.runtime.opset1.ops import convert_like
|
||||
from openvino.runtime.opset1.ops import convolution
|
||||
from openvino.runtime.opset1.ops import convolution_backprop_data
|
||||
from openvino.runtime.opset1.ops import cos
|
||||
from openvino.runtime.opset1.ops import cosh
|
||||
from openvino.runtime.opset1.ops import ctc_greedy_decoder
|
||||
from openvino.runtime.opset6.ops import ctc_greedy_decoder_seq_len
|
||||
from openvino.runtime.opset4.ops import ctc_loss
|
||||
from openvino.runtime.opset3.ops import cum_sum
|
||||
from openvino.runtime.opset3.ops import cum_sum as cumsum
|
||||
from openvino.runtime.opset8.ops import deformable_convolution
|
||||
from openvino.runtime.opset1.ops import deformable_psroi_pooling
|
||||
from openvino.runtime.opset1.ops import depth_to_space
|
||||
from openvino.runtime.opset8.ops import detection_output
|
||||
from openvino.runtime.opset7.ops import dft
|
||||
from openvino.runtime.opset1.ops import divide
|
||||
from openvino.runtime.opset7.ops import einsum
|
||||
from openvino.runtime.opset1.ops import elu
|
||||
from openvino.runtime.opset3.ops import embedding_bag_offsets_sum
|
||||
from openvino.runtime.opset3.ops import embedding_bag_packed_sum
|
||||
from openvino.runtime.opset3.ops import embedding_segments_sum
|
||||
from openvino.runtime.opset3.ops import extract_image_patches
|
||||
from openvino.runtime.opset1.ops import equal
|
||||
from openvino.runtime.opset1.ops import erf
|
||||
from openvino.runtime.opset1.ops import exp
|
||||
from openvino.runtime.opset9.ops import eye
|
||||
from openvino.runtime.opset1.ops import fake_quantize
|
||||
from openvino.runtime.opset1.ops import floor
|
||||
from openvino.runtime.opset1.ops import floor_mod
|
||||
from openvino.runtime.opset8.ops import gather
|
||||
from openvino.runtime.opset6.ops import gather_elements
|
||||
from openvino.runtime.opset8.ops import gather_nd
|
||||
from openvino.runtime.opset1.ops import gather_tree
|
||||
from openvino.runtime.opset7.ops import gelu
|
||||
from openvino.runtime.opset9.ops import generate_proposals
|
||||
from openvino.runtime.opset1.ops import greater
|
||||
from openvino.runtime.opset1.ops import greater_equal
|
||||
from openvino.runtime.opset9.ops import grid_sample
|
||||
from openvino.runtime.opset1.ops import grn
|
||||
from openvino.runtime.opset1.ops import group_convolution
|
||||
from openvino.runtime.opset1.ops import group_convolution_backprop_data
|
||||
from openvino.runtime.opset3.ops import gru_cell
|
||||
from openvino.runtime.opset5.ops import gru_sequence
|
||||
from openvino.runtime.opset1.ops import hard_sigmoid
|
||||
from openvino.runtime.opset5.ops import hsigmoid
|
||||
from openvino.runtime.opset4.ops import hswish
|
||||
from openvino.runtime.opset7.ops import idft
|
||||
from openvino.runtime.opset8.ops import if_op
|
||||
from openvino.runtime.opset11.ops import interpolate
|
||||
from openvino.runtime.opset9.ops import irdft
|
||||
from openvino.runtime.opset10.ops import is_finite
|
||||
from openvino.runtime.opset10.ops import is_inf
|
||||
from openvino.runtime.opset10.ops import is_nan
|
||||
from openvino.runtime.opset8.ops import i420_to_bgr
|
||||
from openvino.runtime.opset8.ops import i420_to_rgb
|
||||
from openvino.runtime.opset1.ops import less
|
||||
from openvino.runtime.opset1.ops import less_equal
|
||||
from openvino.runtime.opset1.ops import log
|
||||
from openvino.runtime.opset1.ops import logical_and
|
||||
from openvino.runtime.opset1.ops import logical_not
|
||||
from openvino.runtime.opset1.ops import logical_or
|
||||
from openvino.runtime.opset1.ops import logical_xor
|
||||
from openvino.runtime.opset5.ops import log_softmax
|
||||
from openvino.runtime.opset5.ops import loop
|
||||
from openvino.runtime.opset1.ops import lrn
|
||||
from openvino.runtime.opset4.ops import lstm_cell
|
||||
from openvino.runtime.opset5.ops import lstm_sequence
|
||||
from openvino.runtime.opset1.ops import matmul
|
||||
from openvino.runtime.opset8.ops import matrix_nms
|
||||
from openvino.runtime.opset8.ops import max_pool
|
||||
from openvino.runtime.opset1.ops import maximum
|
||||
from openvino.runtime.opset1.ops import minimum
|
||||
from openvino.runtime.opset4.ops import mish
|
||||
from openvino.runtime.opset1.ops import mod
|
||||
from openvino.runtime.opset9.ops import multiclass_nms
|
||||
from openvino.runtime.opset1.ops import multiply
|
||||
from openvino.runtime.opset6.ops import mvn
|
||||
from openvino.runtime.opset1.ops import negative
|
||||
from openvino.runtime.opset9.ops import non_max_suppression
|
||||
from openvino.runtime.opset3.ops import non_zero
|
||||
from openvino.runtime.opset1.ops import normalize_l2
|
||||
from openvino.runtime.opset1.ops import not_equal
|
||||
from openvino.runtime.opset8.ops import nv12_to_bgr
|
||||
from openvino.runtime.opset8.ops import nv12_to_rgb
|
||||
from openvino.runtime.opset1.ops import one_hot
|
||||
from openvino.runtime.opset1.ops import pad
|
||||
from openvino.runtime.opset1.ops import parameter
|
||||
from openvino.runtime.opset1.ops import power
|
||||
from openvino.runtime.opset1.ops import prelu
|
||||
from openvino.runtime.opset8.ops import prior_box
|
||||
from openvino.runtime.opset1.ops import prior_box_clustered
|
||||
from openvino.runtime.opset1.ops import psroi_pooling
|
||||
from openvino.runtime.opset4.ops import proposal
|
||||
from openvino.runtime.opset1.ops import range
|
||||
from openvino.runtime.opset8.ops import random_uniform
|
||||
from openvino.runtime.opset9.ops import rdft
|
||||
from openvino.runtime.opset3.ops import read_value
|
||||
from openvino.runtime.opset4.ops import reduce_l1
|
||||
from openvino.runtime.opset4.ops import reduce_l2
|
||||
from openvino.runtime.opset1.ops import reduce_logical_and
|
||||
from openvino.runtime.opset1.ops import reduce_logical_or
|
||||
from openvino.runtime.opset1.ops import reduce_max
|
||||
from openvino.runtime.opset1.ops import reduce_mean
|
||||
from openvino.runtime.opset1.ops import reduce_min
|
||||
from openvino.runtime.opset1.ops import reduce_prod
|
||||
from openvino.runtime.opset1.ops import reduce_sum
|
||||
from openvino.runtime.opset1.ops import region_yolo
|
||||
from openvino.runtime.opset2.ops import reorg_yolo
|
||||
from openvino.runtime.opset1.ops import relu
|
||||
from openvino.runtime.opset1.ops import reshape
|
||||
from openvino.runtime.opset1.ops import result
|
||||
from openvino.runtime.opset1.ops import reverse_sequence
|
||||
from openvino.runtime.opset3.ops import rnn_cell
|
||||
from openvino.runtime.opset5.ops import rnn_sequence
|
||||
from openvino.runtime.opset9.ops import roi_align
|
||||
from openvino.runtime.opset2.ops import roi_pooling
|
||||
from openvino.runtime.opset7.ops import roll
|
||||
from openvino.runtime.opset5.ops import round
|
||||
from openvino.runtime.opset3.ops import scatter_elements_update
|
||||
from openvino.runtime.opset3.ops import scatter_update
|
||||
from openvino.runtime.opset1.ops import select
|
||||
from openvino.runtime.opset1.ops import selu
|
||||
from openvino.runtime.opset3.ops import shape_of
|
||||
from openvino.runtime.opset3.ops import shuffle_channels
|
||||
from openvino.runtime.opset1.ops import sigmoid
|
||||
from openvino.runtime.opset1.ops import sign
|
||||
from openvino.runtime.opset1.ops import sin
|
||||
from openvino.runtime.opset1.ops import sinh
|
||||
from openvino.runtime.opset8.ops import slice
|
||||
from openvino.runtime.opset8.ops import softmax
|
||||
from openvino.runtime.opset4.ops import softplus
|
||||
from openvino.runtime.opset9.ops import softsign
|
||||
from openvino.runtime.opset2.ops import space_to_batch
|
||||
from openvino.runtime.opset1.ops import space_to_depth
|
||||
from openvino.runtime.opset1.ops import split
|
||||
from openvino.runtime.opset1.ops import sqrt
|
||||
from openvino.runtime.opset1.ops import squared_difference
|
||||
from openvino.runtime.opset1.ops import squeeze
|
||||
from openvino.runtime.opset1.ops import strided_slice
|
||||
from openvino.runtime.opset1.ops import subtract
|
||||
from openvino.runtime.opset4.ops import swish
|
||||
from openvino.runtime.opset1.ops import tan
|
||||
from openvino.runtime.opset1.ops import tanh
|
||||
from openvino.runtime.opset1.ops import tensor_iterator
|
||||
from openvino.runtime.opset1.ops import tile
|
||||
from openvino.runtime.opset3.ops import topk
|
||||
from openvino.runtime.opset1.ops import transpose
|
||||
from openvino.runtime.opset10.ops import unique
|
||||
from openvino.runtime.opset1.ops import unsqueeze
|
||||
from openvino.runtime.opset1.ops import variadic_split
|
||||
77
src/bindings/python/src/openvino/runtime/opset11/ops.py
Normal file
77
src/bindings/python/src/openvino/runtime/opset11/ops.py
Normal file
@ -0,0 +1,77 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
# Copyright (C) 2018-2023 Intel Corporation
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
|
||||
"""Factory functions for all openvino ops."""
|
||||
from functools import partial
|
||||
from typing import List, Optional
|
||||
|
||||
from openvino.runtime import Node
|
||||
from openvino.runtime.opset_utils import _get_node_factory
|
||||
from openvino.runtime.utils.decorators import nameable_op
|
||||
from openvino.runtime.utils.types import (
|
||||
NodeInput,
|
||||
as_nodes,
|
||||
)
|
||||
|
||||
_get_node_factory_opset11 = partial(_get_node_factory, "opset11")
|
||||
|
||||
# -------------------------------------------- ops ------------------------------------------------
|
||||
|
||||
|
||||
@nameable_op
|
||||
def interpolate(
|
||||
image: NodeInput,
|
||||
scales_or_sizes: NodeInput,
|
||||
mode: str,
|
||||
shape_calculation_mode: str,
|
||||
pads_begin: Optional[List[int]] = None,
|
||||
pads_end: Optional[List[int]] = None,
|
||||
coordinate_transformation_mode: str = "half_pixel",
|
||||
nearest_mode: str = "round_prefer_floor",
|
||||
antialias: bool = False,
|
||||
cube_coeff: float = -0.75,
|
||||
axes: Optional[NodeInput] = None,
|
||||
name: Optional[str] = None,
|
||||
) -> Node:
|
||||
"""Perfors the interpolation of the input tensor.
|
||||
|
||||
:param image: The node providing input tensor with data for interpolation.
|
||||
:param scales_or_sizes:
|
||||
1D tensor providing information used to calculate the output shape
|
||||
of the operation. It might contain floats (scales) or integers(sizes).
|
||||
:param mode: Specifies type of interpolation. Possible values are: nearest, linear,
|
||||
linear_onnx, cubic, bilinear_pillow, bicubic_pillow.
|
||||
:param shape_calculation_mode:
|
||||
Specifies how the scales_or_sizes input should be interpreted.
|
||||
:param pads_begin: Specifies the number of pixels to add to the beginning of the image
|
||||
being interpolated. Default is None.
|
||||
:param pads_end: Specifies the number of pixels to add to the end of the image being
|
||||
interpolated. Default is None.
|
||||
:param coordinate_transformation_mode:
|
||||
Specifies how to transform the coordinate in the resized tensor to the
|
||||
coordinate in the original tensor. Default is "half_pixel".
|
||||
:param nearest_mode: Specifies round mode when mode == nearest and is used only when
|
||||
mode == nearest. Default is "round_prefer_floor".
|
||||
:param antialias: Specifies whether to perform anti-aliasing. Default is False.
|
||||
:param cube_coeff: Specifies the parameter a for cubic interpolation. Default is -0.75.
|
||||
:param axes: 1D tensor specifying dimension indices where interpolation is applied.
|
||||
The default is None.
|
||||
:param name: Optional name for the output node. The default is None.
|
||||
:return: Node representing the interpolation operation.
|
||||
"""
|
||||
attrs = {
|
||||
"mode": mode,
|
||||
"shape_calculation_mode": shape_calculation_mode,
|
||||
"coordinate_transformation_mode": coordinate_transformation_mode,
|
||||
"nearest_mode": nearest_mode,
|
||||
"antialias": antialias,
|
||||
"cube_coeff": cube_coeff,
|
||||
}
|
||||
|
||||
attrs["pads_begin"] = [] if pads_begin is None else pads_begin
|
||||
attrs["pads_end"] = [] if pads_end is None else pads_end
|
||||
|
||||
inputs = as_nodes(image, scales_or_sizes) if axes is None else as_nodes(image, scales_or_sizes, axes)
|
||||
|
||||
return _get_node_factory_opset11().create("Interpolate", inputs, attrs)
|
||||
@ -13,7 +13,7 @@ from openvino.runtime import Node, Output
|
||||
|
||||
from openvino.runtime.exceptions import UserInputError
|
||||
|
||||
DEFAULT_OPSET = "opset10"
|
||||
DEFAULT_OPSET = "opset11"
|
||||
|
||||
|
||||
class NodeFactory(object):
|
||||
|
||||
@ -79,7 +79,7 @@ private:
|
||||
return it->second();
|
||||
}
|
||||
|
||||
const ov::OpSet& m_opset = ov::get_opset10();
|
||||
const ov::OpSet& m_opset = ov::get_opset11();
|
||||
std::unordered_map<std::string, std::shared_ptr<ov::op::util::Variable>> m_variables;
|
||||
};
|
||||
} // namespace
|
||||
|
||||
@ -11,7 +11,8 @@ from openvino.runtime.utils.types import make_constant_node
|
||||
|
||||
import openvino.runtime.opset1 as ov_opset1
|
||||
import openvino.runtime.opset5 as ov_opset5
|
||||
import openvino.runtime.opset10 as ov
|
||||
import openvino.runtime.opset10 as ov_opset10
|
||||
import openvino.runtime.opset11 as ov
|
||||
from openvino.runtime import Type
|
||||
|
||||
np_types = [np.float32, np.int32]
|
||||
@ -2145,8 +2146,29 @@ def test_interpolate_opset10(dtype, expected_shape, shape_calculation_mode):
|
||||
axes = [2, 3]
|
||||
mode = "cubic"
|
||||
|
||||
node = ov.interpolate(image=image_node, output_shape=output_shape, scales=scales,
|
||||
axes=axes, mode=mode,
|
||||
node = ov_opset10.interpolate(image=image_node, output_shape=output_shape, scales=scales,
|
||||
axes=axes, mode=mode, shape_calculation_mode=shape_calculation_mode)
|
||||
assert node.get_type_name() == "Interpolate"
|
||||
assert node.get_output_size() == 1
|
||||
assert list(node.get_output_shape(0)) == expected_shape
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
("expected_shape", "shape_calculation_mode", "input_value"),
|
||||
[
|
||||
([1, 3, 64, 64], "scales", np.array([1 / 16, 1 / 16], dtype=np.float32)),
|
||||
([1, 3, 256, 256], "sizes", np.array([256, 256], dtype=np.int32)),
|
||||
],
|
||||
)
|
||||
@pytest.mark.parametrize("dtype", np_types)
|
||||
def test_interpolate_opset11(dtype, expected_shape, shape_calculation_mode, input_value):
|
||||
|
||||
image_shape = [1, 3, 1024, 1024]
|
||||
image_node = ov.parameter(image_shape, dtype, name="Image")
|
||||
axes = [2, 3]
|
||||
mode = "bilinear_pillow"
|
||||
|
||||
node = ov.interpolate(image=image_node, scales_or_sizes=input_value, axes=axes, mode=mode,
|
||||
shape_calculation_mode=shape_calculation_mode)
|
||||
assert node.get_type_name() == "Interpolate"
|
||||
assert node.get_output_size() == 1
|
||||
|
||||
@ -11,6 +11,7 @@ import ngraph as ng
|
||||
import ngraph.opset1 as ng_opset1
|
||||
import ngraph.opset5 as ng_opset5
|
||||
import ngraph.opset10 as ng_opset10
|
||||
import ngraph.opset11 as ng_opset11
|
||||
from ngraph.utils.types import make_constant_node
|
||||
from ngraph.exceptions import UserInputError
|
||||
from ngraph.impl import Type
|
||||
@ -2259,13 +2260,33 @@ def test_interpolate_opset10(dtype, expected_shape, shape_calculation_mode):
|
||||
mode = "cubic"
|
||||
|
||||
node = ng_opset10.interpolate(image=image_node, output_shape=output_shape, scales=scales,
|
||||
axes=axes,
|
||||
mode=mode, shape_calculation_mode=shape_calculation_mode)
|
||||
axes=axes,mode=mode, shape_calculation_mode=shape_calculation_mode)
|
||||
assert node.get_type_name() == "Interpolate"
|
||||
assert node.get_output_size() == 1
|
||||
assert list(node.get_output_shape(0)) == expected_shape
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
("expected_shape", "shape_calculation_mode", "input_value"),
|
||||
[
|
||||
([1, 3, 64, 64], "scales", np.array([1 / 16, 1 / 16], dtype=np.float32)),
|
||||
([1, 3, 256, 256], "sizes", np.array([256, 256], dtype=np.int32)),
|
||||
],
|
||||
)
|
||||
@pytest.mark.parametrize("dtype", np_types)
|
||||
def test_interpolate_opset11(dtype, expected_shape, shape_calculation_mode, input_value):
|
||||
|
||||
image_shape = [1, 3, 1024, 1024]
|
||||
image_node = ng.parameter(image_shape, dtype, name="Image")
|
||||
axes = [2, 3]
|
||||
mode = "bilinear_pillow"
|
||||
|
||||
node = ng_opset11.interpolate(image=image_node, scales_or_sizes=input_value, axes=axes, mode=mode,
|
||||
shape_calculation_mode=shape_calculation_mode)
|
||||
assert node.get_type_name() == "Interpolate"
|
||||
assert node.get_output_size() == 1
|
||||
assert list(node.get_output_shape(0)) == expected_shape
|
||||
|
||||
def test_is_finite_opset10():
|
||||
input_shape = [1, 2, 3, 4]
|
||||
input_node = ng.parameter(input_shape, np.float32, name="InputData")
|
||||
|
||||
Loading…
Reference in New Issue
Block a user