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from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect from typing import Dict, Sequence, Text, Any class Concat(Base): @stat...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class QuantizeLinear(Base): @staticmethod def export(): # type: ()...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Log(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class QLinearMatMul(Base): @staticmethod def export(): # type: () ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Asin(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import math import numpy as np # type: ignore import onnx from ..base import Base from . import expect class LRN(Base): @staticmethod def export(): # type: (...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect from typing import Tuple, Text def einsum_reference_implementation(Eqn, Op...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore from typing import Optional import onnx from ..base import Base from . import expect def gemm_reference_implementation(A, B, C=None,...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Where(Base): @staticmethod def export(): # type: () -> None...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Cos(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Or(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect def one_hot(indices, depth, axis=-1, dtype=np.float32): # type: ignore ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect def reshape_reference_implementation(data, shape): # type: (np.ndarray, np...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Tan(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class DequantizeLinear(Base): @staticmethod def export(): # type: ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Unique(Base): @staticmethod def export_sorted_without_axis()...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class ReduceMin(Base): @staticmethod def export_do_not_keepdims():...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class ReduceL1(Base): @staticmethod def export_do_not_keepdims(): ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class LeakyRelu(Base): @staticmethod def export(): # type: () -> ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect from onnx.backend.sample.ops.abs import abs class Abs(Base): @staticm...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import sys import re from typing import List, Text, Sequence, Any import numpy as np # type: ignore import onnx import onnx.mapping from ..utils import import_recursi...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect def argmax_use_numpy(data, axis=0, keepdims=1): # type: (np.ndarray, int, ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class BitShift(Base): @staticmethod def export_right_unit8(): # t...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Floor(Base): @staticmethod def export(): # type: () -> None...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import math import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Erf(Base): @staticmethod def export(): # type:...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect from onnx import helper class Upsample(Base): @staticmethod def ex...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class ConvInteger(Base): @staticmethod def export(): # type: () ->...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class LogSoftmax(Base): @staticmethod def export(): # type: () ->...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Celu(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect def softmaxcrossentropy(x, target, weight=None, reduction='mean', ignore_in...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class RoiAlign(Base): @staticmethod def export_roialign(): # type:...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Ceil(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Size(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class NonMaxSuppression(Base): @staticmethod def export_nonmaxsupp...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect def apply_adagrad(r, t, x, g, h, norm_coefficient, epsilon, decay_factor): ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect from ..utils import all_numeric_dtypes class Min(Base): @staticmethod ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect from .pool_op_common import get_pad_shape, get_output_shape, pool class Ave...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Mean(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Not(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Mul(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect def pad_impl(data, raw_pads, mode, constant_values=0.0): # type: ignore ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class ReduceMean(Base): @staticmethod def export_do_not_keepdims()...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect from typing import Any, List, Callable, Union, Optional, Text def cartesian...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Round(Base): @staticmethod def export(): # type: () -> None...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import itertools import onnx from ..base import Base from . import expect class Transpose(Base): @staticmethod def export_d...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect def compute_negative_log_likelihood_loss(input, target, weight=None, reduct...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from onnx import TensorProto from ..base import Base from . import expect class DynamicQuantizeLinear(Base): @stati...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Split(Base): @staticmethod def export_1d(): # type: () -> N...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class PRelu(Base): @staticmethod def export(): # type: () -> None...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class GlobalAveragePool(Base): @staticmethod def export(): # type...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect from .pool_op_common import get_output_shape, get_pad_shape, pool class Max...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class MaxUnpool(Base): @staticmethod def export_without_output_sha...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class EyeLike(Base): @staticmethod def export_without_dtype(): # ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect def gather_nd_impl(data, indices, batch_dims): # type: (np.ndarray, np....
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect from onnx import helper # The below Scatter's numpy implementation is from ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect def apply_adam(r, t, x, g, v, h, norm_coefficient, norm_coefficient_post, a...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Compress(Base): @staticmethod def export_compress_0(): # ty...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Relu(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Sub(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore from typing import Any, Sequence import onnx from onnx import NodeProto from ..base import Base from . import expect class TfIdfVect...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect def scatter_nd_impl(data, indices, updates): # type: (np.ndarray, np.nd...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect # The below ScatterElements' numpy implementation is from https://stackover...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Xor(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Unsqueeze(Base): @staticmethod def export_unsqueeze_one_axis...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class ReverseSequence(Base): @staticmethod def export_reverseseque...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Scan(Base): @staticmethod def export_scan_8(): # type: () -...
import numpy as np # type: ignore import itertools from typing import Text, Sequence def get_pad_shape(auto_pad, # type: Text input_spatial_shape, # type: Sequence[int] kernel_spatial_shape, # type: Sequence[int] strides_spatial, # type: Sequence[int] ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class HardSigmoid(Base): @staticmethod def export(): # type: () -...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class ReduceL2(Base): @staticmethod def export_do_not_keepdims(): ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Shape(Base): @staticmethod def export(): # type: () -> None...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class MatMulInteger(Base): @staticmethod def export(): # type: () ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class ReduceProd(Base): @staticmethod def export_do_not_keepdims()...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import random import onnx from ..base import Base from . import expect from onnx import helper def dropout(X, drop_probability=0.5, ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Constant(Base): @staticmethod def export(): # type: () -> N...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Sum(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class ReduceMax(Base): @staticmethod def export_do_not_keepdims():...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Conv(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Greater(Base): @staticmethod def export(): # type: () -> No...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Less(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class CumSum(Base): @staticmethod def export_cumsum_1d(): # type:...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class ReduceSumSquare(Base): @staticmethod def export_do_not_keepd...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore from typing import Any, Tuple import onnx from ..base import Base from . import expect class LSTM_Helper(): def __init__(self, *...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Cosh(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Clip(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Elu(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore from typing import Any, Tuple import onnx from ..base import Base from . import expect class GRU_Helper(): def __init__(self, **...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Sign(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Sinh(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Softplus(Base): @staticmethod def export(): # type: () -> N...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect def topk_sorted_implementation(X, k, axis, largest): # type: ignore so...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Sigmoid(Base): @staticmethod def export(): # type: () -> No...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from onnx.backend.test.case.base import Base from onnx.backend.test.case.node import expect class Squeeze(Base): @s...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Mod(Base): @staticmethod def export_mod_mixed_sign_float64()...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Greater(Base): @staticmethod def export(): # type: () -> No...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Identity(Base): @staticmethod def export(): # type: () -> N...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect def apply_momentum(t, r, x, g, v, norm_coefficient, alpha, beta): # type: ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Exp(Base): @staticmethod def export(): # type: () -> None ...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class ConstantOfShape(Base): @staticmethod def export_float_ones()...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore from typing import Any, Tuple import onnx from ..base import Base from . import expect class RNN_Helper(): def __init__(self, **...
from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class ReduceLogSumExp(Base): @staticmethod def export_do_not_keepd...