OperatorKernels.md

Supported Operators Data Types

This file is automatically generated from the def files via this script. Do not modify directly and instead edit operator definitions.

Operators implemented by CPUExecutionProvider

Op Name	Parameters	OpSet Version	Types Supported
Operator Domain: ai.onnx.ml
Abs	(in X:T, out Y:T)	6+	T = tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Acos	(in input:T, out output:T)	7+	T = tensor(float)
Acosh	(in input:T, out output:T)	9+	T = tensor(float)
Add	(in A:T, in B:T, out C:T)	7+	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
Affine	(in X:T, out Y:T)	1+	T = tensor(float)
And	(in A:T, in B:T, out C:T1)	7+	T = tensor(bool)
			T1 = tensor(bool)
ArgMax	(in data:T, out reduced:tensor(int64))	12+	T = tensor(float), tensor(int32)
		[1, 10]	T = tensor(float), tensor(int32)
		[11, 11]	T = tensor(float), tensor(int32)
ArgMin	(in data:T, out reduced:tensor(int64))	12+	T = tensor(float), tensor(int32)
		[1, 10]	T = tensor(float), tensor(int32)
		[11, 11]	T = tensor(float), tensor(int32)
ArrayFeatureExtractor	(in X:T, in Y:tensor(int64), out Z:T)	1+	T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(string)
Asin	(in input:T, out output:T)	7+	T = tensor(float)
Asinh	(in input:T, out output:T)	9+	T = tensor(float)
Atan	(in input:T, out output:T)	7+	T = tensor(float)
Atanh	(in input:T, out output:T)	9+	T = tensor(float)
AveragePool	(in X:T, out Y:T)	11+	T = tensor(float)
		[10, 10]	T = tensor(float)
		[7, 9]	T = tensor(float)
BatchNormalization	(in X:T, in scale:T, in B:T, in mean:T, in var:T, in training_mode:T1, out Y:T, out output_mean:T, out output_var:T, out saved_mean:T, out saved_var:T) or (in X:T, in scale:T, in B:T, in mean:T, in var:T, out Y:T, out mean:T, out var:T, out saved_mean:T, out saved_var:T)	[7, 9]	T = tensor(double), tensor(float)
Binarizer	(in X:T, out Y:T)	1+	T = tensor(float)
BitShift	(in X:T, in Y:T, out Z:T)	11+	T = tensor(uint32), tensor(uint64), tensor(uint8)
Cast	(in input:T1, out output:T2)	9+	T1 = tensor(string)
			T2 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[6, 9]	T1 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			T2 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
CastMap	(in X:T1, out Y:T2)	1+	T1 = map(int64,tensor(float)), map(int64,tensor(string))
			T2 = tensor(float), tensor(int64), tensor(string)
CategoryMapper	(in X:T1, out Y:T2)	1+	T1 = tensor(int64), tensor(string)
			T2 = tensor(int64), tensor(string)
Ceil	(in X:T, out Y:T)	6+	T = tensor(float)
Clip	(in input:T, in min:T, in max:T, out output:T) or (in input:T, out output:T)	12+	T = tensor(double), tensor(float), tensor(int64), tensor(int8), tensor(uint64), tensor(uint8)
		[11, 11]	T = tensor(float)
		[6, 10]	T = tensor(float)
Compress	(in input:T, in condition:T1, out output:T)	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			T1 = tensor(bool)
		[9, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			T1 = tensor(bool)
Concat	(in inputs:T, out concat_result:T)	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[4, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
ConcatFromSequence	(in input_sequence:S, out concat_result:T)	11+	S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
ConstantOfShape	(in input:T1, out output:T2)	9+	T1 = tensor(int64)
			T2 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Conv	(in X:T, in W:T, in B:T, out Y:T)	11+	T = tensor(float)
		[1, 10]	T = tensor(float)
ConvInteger	(in x:T1, in w:T2, in x_zero_point:T1, in w_zero_point:T2, out y:T3)	10+	T1 = tensor(uint8)
			T2 = tensor(uint8)
			T3 = tensor(int32)
ConvTranspose	(in X:T, in W:T, in B:T, out Y:T)	11+	T = tensor(float)
		[1, 10]	T = tensor(float)
Cos	(in input:T, out output:T)	7+	T = tensor(float)
Cosh	(in input:T, out output:T)	9+	T = tensor(float)
Crop	(in input:T, out output:T)	1+	T = tensor(float)
CumSum	(in x:T, in axis:T2, out y:T)	11+	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
			T2 = tensor(int32), tensor(int64)
DepthToSpace	(in input:T, out output:T)	11+	T = tensor(float)
		[1, 10]	T = tensor(float)
DequantizeLinear	(in x:T, in x_scale:tensor(float), in x_zero_point:T, out y:tensor(float))	10+	T = tensor(int8), tensor(uint8)
Det	(in X:T, out Y:T)	11+	T = tensor(float)
DictVectorizer	(in X:T1, out Y:T2)	1+	T1 = map(int64,tensor(double)), map(int64,tensor(float)), map(int64,tensor(string)), map(string,tensor(double)), map(string,tensor(float)), map(string,tensor(int64))
			T2 = tensor(double), tensor(float), tensor(int64), tensor(string)
Div	(in A:T, in B:T, out C:T)	7+	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
Dropout	(in data:T, in ratio:T1, out output:T, out mask:T2) or (in data:T, out output:T, out mask:T) or (in data:T, out output:T, out mask:T1)	10+	T = tensor(double), tensor(float), tensor(float16)
			T1 = tensor(bool)
		[7, 9]	T = tensor(double), tensor(float), tensor(float16)
			T1 = tensor(bool)
DynamicQuantizeLinear	(in x:T1, out y:T2, out y_scale:tensor(float), out y_zero_point:T2)	11+	T2 = tensor(uint8)
DynamicSlice	(in data:T, in starts:Tind, in ends:Tind, in axes:Tind, out output:T)	1+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			Tind = tensor(int32), tensor(int64)
Elu	(in X:T, out Y:T)	6+	T = tensor(float)
Equal	(in A:T, in B:T, out C:T1)	11+	T = tensor(bool), tensor(float), tensor(int32), tensor(int64)
			T1 = tensor(bool)
		[7, 10]	T = tensor(bool), tensor(int32), tensor(int64)
			T1 = tensor(bool)
Erf	(in input:T, out output:T)	9+	T = tensor(float)
Exp	(in input:T, out output:T)	6+	T = tensor(double), tensor(float)
Expand	(in input:T, in shape:tensor(int64), out output:T)	8+	T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
EyeLike	(in input:T1, out output:T2)	9+	T1 = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(uint64)
			T2 = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(uint64)
FeatureVectorizer	(in X:T1, out Y:tensor(float))	1+	T1 = tensor(double), tensor(float), tensor(int32), tensor(int64)
Flatten	(in input:T, out output:T)	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 8]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[9, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Floor	(in X:T, out Y:T)	6+	T = tensor(float)
GRU	(in X:T, in W:T, in R:T, in B:T, in sequence_lens:T1, in initial_h:T, out Y:T, out Y_h:T)	7+	T = tensor(double), tensor(float)
			T1 = tensor(int32)
Gather	(in data:T, in indices:Tind, out output:T)	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			Tind = tensor(int32), tensor(int64)
		[1, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			Tind = tensor(int32), tensor(int64)
GatherElements	(in data:T, in indices:Tind, out output:T)	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			Tind = tensor(int32), tensor(int64)
GatherND	(in data:T, in indices:tensor(int64), out output:T)	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			Tind = tensor(int64)
Gemm	(in A:T, in B:T, in C:T, out Y:T)	11+	T = tensor(float)
		[7, 8]	T = tensor(float)
		[9, 10]	T = tensor(float)
GlobalAveragePool	(in X:T, out Y:T)	1+	T = tensor(float)
GlobalLpPool	(in X:T, out Y:T)	2+	T = tensor(float)
GlobalMaxPool	(in X:T, out Y:T)	1+	T = tensor(float)
Greater	(in A:T, in B:T, out C:T1)	9+	T = tensor(int32), tensor(int64)
			T1 = tensor(bool)
		[7, 9]	T = tensor(float)
			T1 = tensor(bool)
HardSigmoid	(in X:T, out Y:T)	6+	T = tensor(float)
Hardmax	(in input:T, out output:T)	11+	T = tensor(float)
		[1, 10]	T = tensor(float)
Identity	(in input:T, out output:T)	1+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
If	(in cond:B, out outputs:V)	11+	B = tensor(bool)
			V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 10]	B = tensor(bool)
			V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
ImageScaler	(in input:T, out output:T)	1+	T = tensor(float)
Imputer	(in X:T, out Y:T)	1+	T = tensor(float), tensor(int64)
InstanceNormalization	(in input:T, in scale:T, in B:T, out output:T)	6+	T = tensor(float)
IsInf	(in X:T1, out Y:T2)	10+	T1 = tensor(double), tensor(float)
			T2 = tensor(bool)
IsNaN	(in X:T1, out Y:T2)	9+	T1 = tensor(float), tensor(float16)
			T2 = tensor(bool)
LRN	(in X:T, out Y:T)	1+	T = tensor(float)
LSTM	(in X:T, in W:T, in R:T, in B:T, in sequence_lens:T1, in initial_h:T, in initial_c:T, in P:T, out Y:T, out Y_h:T, out Y_c:T)	7+	T = tensor(double), tensor(float)
			T1 = tensor(int32)
LabelEncoder	(in X:T1, out Y:T2)	2+	T1 = tensor(float), tensor(int64), tensor(string)
			T2 = tensor(float), tensor(int64), tensor(string)
		[1, 1]	T1 = tensor(int64), tensor(string)
			T2 = tensor(int64), tensor(string)
LayerNormalization	(in X:T, in scale:T, in B:T, out Y:T, out mean:U, out inv_std_var:U)	1+	T = tensor(double), tensor(float)
LeakyRelu	(in X:T, out Y:T)	6+	T = tensor(float)
Less	(in A:T, in B:T, out C:T1)	9+	T = tensor(int32), tensor(int64)
			T1 = tensor(bool)
		[7, 9]	T = tensor(double), tensor(float)
			T1 = tensor(bool)
LinearClassifier	(in X:T1, out Y:T2, out Z:tensor(float))	1+	T1 = tensor(double), tensor(float), tensor(int32), tensor(int64)
			T2 = tensor(int64), tensor(string)
LinearRegressor	(in X:T, out Y:tensor(float))	1+	T = tensor(float)
Log	(in input:T, out output:T)	6+	T = tensor(float)
LogSoftmax	(in input:T, out output:T)	11+	T = tensor(double), tensor(float)
		[1, 10]	T = tensor(double), tensor(float)
Loop	(in M:I, in cond:B, in v_initial:V, out v_final_and_scan_outputs:V)	11+	B = tensor(bool)
			I = tensor(int64)
			V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 10]	B = tensor(bool)
			I = tensor(int64)
			V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
LpNormalization	(in input:T, out output:T)	1+	T = tensor(float)
LpPool	(in X:T, out Y:T)	11+	T = tensor(float)
		[2, 10]	T = tensor(float)
MatMul	(in A:T, in B:T, out Y:T)	9+	T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		[1, 8]	T = tensor(double), tensor(float)
MatMulInteger	(in A:T1, in B:T2, in a_zero_point:T1, in b_zero_point:T2, out Y:T3)	10+	T1 = tensor(uint8)
			T2 = tensor(int8), tensor(uint8)
			T3 = tensor(int32)
Max	(in data_0:T, out max:T)	12+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
			T1 = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		[6, 7]	T = tensor(float)
		[8, 11]	T = tensor(double), tensor(float)
			T1 = tensor(double), tensor(float)
MaxPool	(in X:T, out Y:T) or (in X:T, out Y:T, out Indices:I)	12+	I = tensor(int64)
			T = tensor(double), tensor(float), tensor(int8), tensor(uint8)
		[1, 7]	T = tensor(float)
		[8, 11]	I = tensor(int64)
			T = tensor(double), tensor(float)
MaxRoiPool	(in X:T, in rois:T, out Y:T)	1+	T = tensor(float)
MaxUnpool	(in X:T1, in I:T2, in output_shape:T2, out output:T1)	11+	T1 = tensor(float)
			T2 = tensor(int64)
		[9, 10]	T1 = tensor(float)
			T2 = tensor(int64)
Mean	(in data_0:T, out mean:T)	8+	T = tensor(float)
		[6, 7]	T = tensor(float)
MeanVarianceNormalization	(in X:T, out Y:T) or (in input:T, out output:T)	9+	T = tensor(float)
		[1, 8]	T = tensor(float)
Min	(in data_0:T, out min:T)	12+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
			T1 = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		[6, 7]	T = tensor(float)
		[8, 11]	T = tensor(float)
			T1 = tensor(float)
Mod	(in A:T, in B:T, out C:T)	10+	T = tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Mul	(in A:T, in B:T, out C:T)	7+	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
Multinomial	(in input:T1, out output:T2)	7+	T1 = tensor(float)
			T2 = tensor(int32), tensor(int64)
Neg	(in X:T, out Y:T)	6+	T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8)
NonZero	(in X:T, out Y:tensor(int64))	9+	T = tensor(bool), tensor(float), tensor(int32), tensor(int64), tensor(uint8)
Normalizer	(in X:T, out Y:tensor(float))	1+	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
Not	(in X:T, out Y:T)	1+	T = tensor(bool)
			T1 = tensor(bool)
OneHot	(in indices:T1, in depth:T2, in values:T3, out output:T3)	11+	T1 = tensor(float), tensor(int32), tensor(int64)
			T2 = tensor(float), tensor(int32), tensor(int64)
			T3 = tensor(float), tensor(int32), tensor(int64), tensor(string)
		[9, 10]	T1 = tensor(float), tensor(int32), tensor(int64)
			T2 = tensor(float), tensor(int32), tensor(int64)
			T3 = tensor(float), tensor(int32), tensor(int64), tensor(string)
OneHotEncoder	(in X:T, out Y:tensor(float))	1+	T = tensor(double), tensor(float), tensor(int64), tensor(string)
Or	(in A:T, in B:T, out C:T1)	7+	T = tensor(bool)
			T1 = tensor(bool)
PRelu	(in X:T, in slope:T, out Y:T)	[7, 9]	T = tensor(float)
Pad	(in data:T, in pads:tensor(int64), in constant_value:T, out output:T) or (in data:T, out output:T)	11+	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
		[2, 10]	T = tensor(float)
ParametricSoftplus	(in X:T, out Y:T)	1+	T = tensor(float)
Pow	(in X:T, in Y:T, out Z:T) or (in X:T, in Y:T1, out Z:T)	7+	T = tensor(double), tensor(float)
QLinearConv	(in x:T1, in x_scale:tensor(float), in x_zero_point:T1, in w:T2, in w_scale:tensor(float), in w_zero_point:T2, in y_scale:tensor(float), in y_zero_point:T3, in B:T4, out y:T3)	10+	T1 = tensor(uint8)
			T2 = tensor(uint8)
			T3 = tensor(uint8)
			T4 = tensor(int32)
QLinearMatMul	(in a:T1, in a_scale:tensor(float), in a_zero_point:T1, in b:T2, in b_scale:tensor(float), in b_zero_point:T2, in y_scale:tensor(float), in y_zero_point:T3, out y:T3)	10+	T1 = tensor(uint8)
			T2 = tensor(uint8)
			T3 = tensor(uint8)
QuantizeLinear	(in x:T1, in y_scale:tensor(float), in y_zero_point:T2, out y:T2)	10+	T1 = tensor(float)
			T2 = tensor(int8), tensor(uint8)
RNN	(in X:T, in W:T, in R:T, in B:T, in sequence_lens:T1, in initial_h:T, out Y:T, out Y_h:T)	7+	T = tensor(float)
			T1 = tensor(int32)
RandomNormal	(out output:T)	1+	T = tensor(double), tensor(float)
RandomNormalLike	(in input:T1, out output:T2)	1+	T1 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			T2 = tensor(double), tensor(float)
RandomUniform	(out output:T)	1+	T = tensor(double), tensor(float)
RandomUniformLike	(in input:T1, out output:T2)	1+	T1 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			T2 = tensor(double), tensor(float)
Range	(in start:T, in limit:T, in delta:T, out output:T)	11+	T = tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64)
Reciprocal	(in X:T, out Y:T)	6+	T = tensor(float)
ReduceL1	(in data:T, out reduced:T)	11+	T = tensor(float), tensor(int32)
		[1, 10]	T = tensor(float), tensor(int32)
ReduceL2	(in data:T, out reduced:T)	11+	T = tensor(float), tensor(int32)
		[1, 10]	T = tensor(float), tensor(int32)
ReduceLogSum	(in data:T, out reduced:T)	11+	T = tensor(float), tensor(int32)
		[1, 10]	T = tensor(float), tensor(int32)
ReduceLogSumExp	(in data:T, out reduced:T)	11+	T = tensor(float), tensor(int32)
		[1, 10]	T = tensor(float), tensor(int32)
ReduceMax	(in data:T, out reduced:T)	11+	T = tensor(float), tensor(int32), tensor(int64)
		12+	T = tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
		[1, 10]	T = tensor(float), tensor(int32), tensor(int64)
ReduceMean	(in data:T, out reduced:T)	11+	T = tensor(float), tensor(int32)
		[1, 10]	T = tensor(float), tensor(int32)
ReduceMin	(in data:T, out reduced:T)	11+	T = tensor(float), tensor(int32), tensor(int64)
		12+	T = tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
		[1, 10]	T = tensor(float), tensor(int32), tensor(int64)
ReduceProd	(in data:T, out reduced:T)	11+	T = tensor(float), tensor(int32), tensor(int64)
		[1, 10]	T = tensor(float), tensor(int32), tensor(int64)
ReduceSum	(in data:T, out reduced:T)	11+	T = tensor(float), tensor(int32), tensor(int64)
		[1, 10]	T = tensor(float), tensor(int32), tensor(int64)
ReduceSumSquare	(in data:T, out reduced:T)	11+	T = tensor(float), tensor(int32)
		[1, 10]	T = tensor(float), tensor(int32)
Relu	(in X:T, out Y:T)	6+	T = tensor(float)
Reshape	(in data:T, in shape:tensor(int64), out reshaped:T) or (in data:T, out reshaped:T)	5+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			shape = tensor(int64)
Reshape_1		[1, 4]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Resize	(in X:T, in scales:tensor(float), out Y:T) or (in X:T1, in roi:T2, in scales:tensor(float), in sizes:tensor(int64), out Y:T1)	11+	T1 = tensor(float), tensor(int32), tensor(uint8)
		[10, 10]	T = tensor(float), tensor(int32), tensor(uint8)
ReverseSequence	(in input:T, in sequence_lens:tensor(int64), out Y:T)	10+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
RoiAlign	(in X:T1, in rois:T1, in batch_indices:T2, out Y:T1)	10+	T = tensor(double), tensor(float)
			T2 = tensor(int64)
Round	(in X:T, out Y:T)	11+	T = tensor(double), tensor(float), tensor(float16)
SVMClassifier	(in X:T1, out Y:T2, out Z:tensor(float))	1+	T1 = tensor(double), tensor(float), tensor(int32), tensor(int64)
			T2 = tensor(int64), tensor(string)
SVMRegressor	(in X:T, out Y:tensor(float))	1+	T = tensor(float)
Scale	(in input:T, out output:T)	1+	T = tensor(float)
ScaledTanh	(in input:T, out output:T)	1+	T = tensor(float)
Scaler	(in X:T, out Y:tensor(float))	1+	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
Scan	(in initial_state_and_scan_inputs:V, out final_state_and_scan_outputs:V) or (in sequence_lens:I, in initial_state_and_scan_inputs:V, out final_state_and_scan_outputs:V)	11+	I = tensor(int64)
			V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[8, 8]	I = tensor(int64)
			V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[9, 10]	I = tensor(int64)
			V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Scatter	(in data:T, in indices:Tind, in updates:T, out output:T)	[9, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			Tind = tensor(int32), tensor(int64)
ScatterElements	(in data:T, in indices:Tind, in updates:T, out output:T)	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			Tind = tensor(int32), tensor(int64)
ScatterND	(in data:T, in indices:tensor(int64), in updates:T, out output:T)	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			Tind = tensor(int64)
Selu	(in X:T, out Y:T)	6+	T = tensor(float)
SequenceAt	(in input_sequence:S, in position:I, out tensor:T)	11+	I = tensor(int32), tensor(int64)
			S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
			T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
SequenceConstruct	(in inputs:T, out output_sequence:S)	11+	S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
			T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
SequenceEmpty	(out output:S)	11+	S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
SequenceErase	(in input_sequence:S, in position:I, out output_sequence:S)	11+	I = tensor(int32), tensor(int64)
			S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
SequenceInsert	(in input_sequence:S, in tensor:T, in position:I, out output_sequence:S)	11+	I = tensor(int32), tensor(int64)
			S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
SequenceLength	(in input_sequence:S, out length:I)	11+	I = tensor(int64)
			S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
Shape	(in data:T, out shape:T1)	1+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			T1 = tensor(int64)
Shrink	(in input:T, out output:T)	9+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Sigmoid	(in X:T, out Y:T)	6+	T = tensor(float)
Sign	(in input:T, out output:T)	9+	T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Sin	(in input:T, out output:T)	7+	T = tensor(double), tensor(float)
Sinh	(in input:T, out output:T)	9+	T = tensor(float)
Size	(in data:T, out size:T1)	1+	T = tensor(bool), tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			T1 = tensor(int64)
Slice	(in data:T, in starts:Tind, in ends:Tind, in axes:Tind, in steps:Tind, out output:T) or (in data:T, out output:T)	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			Tind = tensor(int32), tensor(int64)
		[1, 9]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[10, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			Tind = tensor(int32), tensor(int64)
Softmax	(in input:T, out output:T)	11+	T = tensor(double), tensor(float)
		[1, 10]	T = tensor(double), tensor(float)
Softplus	(in X:T, out Y:T)	1+	T = tensor(float)
Softsign	(in input:T, out output:T)	1+	T = tensor(float)
SpaceToDepth	(in input:T, out output:T)	1+	T = tensor(float)
Split	(in input:T, in split:T, out outputs...:T) or (in input:T, out outputs:T)	11+	T = tensor(float), tensor(int32), tensor(int64), tensor(string)
		[2, 10]	T = tensor(float), tensor(int32), tensor(int64), tensor(string)
SplitToSequence	(in input:T, in split:I, out output_sequence:S)	11+	I = tensor(int32), tensor(int64)
			S = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
			T = tensor(double), tensor(float), tensor(int32), tensor(string)
Sqrt	(in X:T, out Y:T)	6+	T = tensor(double), tensor(float)
Squeeze	(in data:T, out squeezed:T)	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
StringNormalizer	(in X:tensor(string), out Y:tensor(string))	10+	T = tensor(string)
Sub	(in A:T, in B:T, out C:T)	7+	T = tensor(double), tensor(float), tensor(int32), tensor(int64)
Sum	(in data_0:T, out sum:T)	8+	T = tensor(float)
		[6, 7]	T = tensor(float)
Tan	(in input:T, out output:T)	7+	T = tensor(float)
Tanh	(in input:T, out output:T)	6+	T = tensor(float)
TfIdfVectorizer	(in X:T, out Y:T1)	9+	T = tensor(int32), tensor(int64), tensor(string)
			T1 = tensor(float)
ThresholdedRelu	(in X:T, out Y:T)	10+	T = tensor(float)
		[1, 9]	T = tensor(float)
Tile	(in input:T, in repeats:T1, out output:T) or (in input:T, in tiles:T, in axis:T, out output:T)	6+	T = tensor(bool), tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			T1 = tensor(int64)
TopK	(in X:T, in K:tensor(int64), out Values:T, out Indices:I) or (in X:T, out Values:T, out Indices:I)	11+	I = tensor(int64)
			T = tensor(float), tensor(int64)
		[1, 9]	I = tensor(int64)
			T = tensor(float)
		[10, 10]	I = tensor(int64)
			T = tensor(float)
Transpose	(in data:T, out transposed:T)	1+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
TreeEnsembleClassifier	(in X:T1, out Y:T2, out Z:tensor(float))	1+	T1 = tensor(double), tensor(float), tensor(int32), tensor(int64)
			T2 = tensor(int64), tensor(string)
TreeEnsembleRegressor	(in X:T, out Y:tensor(float))	1+	T = tensor(double), tensor(float)
Unique	(in X:T, out Y:T, out indices:tensor(int64), out inverse_indices:tensor(int64), out counts:tensor(int64))	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Unsqueeze	(in data:T, out expanded:T)	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Upsample	(in X:T, in scales:tensor(float), out Y:T) or (in X:T, out Y:T)	[7, 9]	T = tensor(float), tensor(int32), tensor(uint8)
Where	(in condition:B, in X:T, in Y:T, out output:T)	9+	T = tensor(float), tensor(int32), tensor(int64), tensor(string), tensor(uint8)
Xor	(in A:T, in B:T, out C:T1)	7+	T = tensor(bool)
			T1 = tensor(bool)
ZipMap	(in X:tensor(float), out Z:T)	1+	T = seq(map(int64,tensor(float))), seq(map(string,tensor(float)))
Operator Domain: com.microsoft
Attention	(in input:T, in weight:T, in bias:T, in mask_index:M, out output:T)	1+	T = tensor(float)
AttnLSTM	(in X:T, in W:T, in R:T, in B:T, in sequence_lens:T1, in initial_h:T, in initial_c:T, in P:T, in QW:T, in MW:T, in V:T, in M:T, in memory_seq_lens:T1, in AW:T, out Y:T, out Y_h:T, out Y_c:T)	1+	T = tensor(double), tensor(float)
			T1 = tensor(int32)
BiasGelu	(in A:T, in B:T, out C:T)	1+	T = tensor(float)
CDist	(in A:T, in B:T, out C:T)	1+	T = tensor(double), tensor(float)
ConvTransposeWithDynamicPads	(in X:T, in W:T, in Pads:tensor(int64), in B:T, out Y:T)	1+	T = tensor(float)
CropAndResize	(in X:T1, in rois:T1, in batch_indices:T2, in crop_size:T2, out Y:T1)	1+	T = tensor(float)
			T2 = tensor(int32)
DequantizeLinear	(in x:T1, in x_scale:T2, in x_zero_point:T1, out y:T2)	1+	T1 = tensor(int8), tensor(uint8)
			T2 = tensor(float)
EmbedLayerNormalization	(in input_ids:T1, in segment_ids:T1, in word_embedding:T, in position_embedding:T, in segment_embedding:T, in gamma:T, in beta:T, in mask:T1, out output:T, out mask_index:T1)	1+	T = tensor(float)
ExpandDims	(in X:T, in axis:tensor(int32), out Y:T)	1+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			axis = tensor(int32)
FastGelu	(in X:T, in bias:T, out Y:T)	1+	T = tensor(float)
FusedConv	(in X:T, in W:T, in B:T, out Y:T)	1+	T = tensor(float)
FusedGemm	(in A:T, in B:T, in C:T, out Y:T)	1+	T = tensor(float)
GatherND	(in data:T, in indices:Tind, out output:T)	1+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			Tind = tensor(int32), tensor(int64)
Gelu	(in X:T, out Y:T)	1+	T = tensor(float)
MatMulInteger16	(in A:T1, in B:T2, out Y:T3)	1+	T1 = tensor(int16)
			T2 = tensor(int16)
			T3 = tensor(int32)
MaxpoolWithMask	(in X:T, in M:tensor(int32), out Y:T)	1+	X = tensor(float)
MurmurHash3	(in X:T1, out Y:T2)	1+	T1 = tensor(int32), tensor(string), tensor(uint32)
			T2 = tensor(int32), tensor(uint32)
Pad	(in data:T, in pads:tensor(int64), in value:T, out output:T)	1+	T = tensor(float)
QuantizeLinear	(in x:T1, in y_scale:T1, in y_zero_point:T2, out y:T2)	1+	T1 = tensor(float)
			T2 = tensor(int8), tensor(uint8)
Range	(in start:T, in limit:T, in delta:T, out Y:T)	1+	T = tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64)
SampleOp	(in X:T, out Y:T)	1+	T = tensor(float)
SkipLayerNormalization	(in input:T, in skip:T, in gamma:T, in beta:T, in bias:T, out output:T, out mean:U, out inv_std_var:U)	1+	T = tensor(double), tensor(float)
Tokenizer	(in X:T, out Y:T)	1+	T = tensor(string)
Unique	(in x:T, out y:T, out idx:tensor(int64), out counts:tensor(int64))	1+	T = tensor(float)
WordConvEmbedding	(in Sequence:T, in W:T1, in B:T1, in C:T1, out Y:T1)	1+	T = tensor(int32)
			T1 = tensor(float)
Operator Domain: com.microsoft.nchwc
AveragePool	(in X:T, out Y:T)	1+	T = tensor(float)
Conv	(in X:T, in W:T, in B:T, in Sum:T, out Y:T)	1+	T = tensor(float)
GlobalAveragePool	(in X:T, out Y:T)	1+	T = tensor(float)
GlobalMaxPool	(in X:T, out Y:T)	1+	T = tensor(float)
MaxPool	(in X:T, out Y:T)	1+	T = tensor(float)
ReorderInput	(in X:T, out Y:T)	1+	T = tensor(float)
ReorderOutput	(in X:T, out Y:T)	1+	T = tensor(float)
Upsample	(in X:T, out Y:T)	1+	T = tensor(float)

Operators implemented by CUDAExecutionProvider

Op Name	Parameters	OpSet Version	Types Supported
Operator Domain: ai.onnx.ml
Abs	(in X:T, out Y:T)	6+	T = tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Add	(in A:T, in B:T, out C:T)	7+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
Affine	(in X:T, out Y:T)	1+	T = tensor(double), tensor(float), tensor(float16)
And	(in A:T, in B:T, out C:T1)	7+	T = tensor(bool)
			T1 = tensor(bool)
ArgMax	(in data:T, out reduced:tensor(int64))	11+	T = tensor(double), tensor(float), tensor(float16)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16)
ArgMin	(in data:T, out reduced:tensor(int64))	11+	T = tensor(double), tensor(float), tensor(float16)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16)
AveragePool	(in X:T, out Y:T)	11+	T = tensor(double), tensor(float), tensor(float16)
		[10, 10]	I = tensor(int64)
			T = tensor(double), tensor(float), tensor(float16)
		[7, 9]	I = tensor(int64)
			T = tensor(double), tensor(float), tensor(float16)
BatchNormalization	(in X:T, in scale:T, in B:T, in mean:T, in var:T, in training_mode:T1, out Y:T, out output_mean:T, out output_var:T, out saved_mean:T, out saved_var:T) or (in X:T, in scale:T, in B:T, in mean:T, in var:T, out Y:T, out mean:T, out var:T, out saved_mean:T, out saved_var:T)	9+	T = tensor(double), tensor(float), tensor(float16)
		[7, 8]	T = tensor(double), tensor(float), tensor(float16)
Cast	(in input:T1, out output:T2)	9+	T1 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			T2 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[6, 8]	T1 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			T2 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Ceil	(in X:T, out Y:T)	6+	T = tensor(double), tensor(float), tensor(float16)
Clip	(in input:T, in min:T, in max:T, out output:T) or (in input:T, out output:T)	12+	T = tensor(double), tensor(float), tensor(int64), tensor(int8), tensor(uint64), tensor(uint8)
		[11, 11]	T = tensor(float)
		[6, 10]	T = tensor(float)
Compress	(in input:T, in condition:T1, out output:T)	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			T1 = tensor(bool)
		[9, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			T1 = tensor(bool)
Concat	(in inputs:T, out concat_result:T)	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[4, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
ConstantOfShape	(in input:T1, out output:T2)	9+	T1 = tensor(int64)
			T2 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Conv	(in X:T, in W:T, in B:T, out Y:T)	11+	T = tensor(double), tensor(float), tensor(float16)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16)
ConvTranspose	(in X:T, in W:T, in B:T, out Y:T)	11+	T = tensor(double), tensor(float), tensor(float16)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16)
Crop	(in input:T, out output:T)	1+	T = tensor(double), tensor(float), tensor(float16)
CumSum	(in x:T, in axis:T2, out y:T)	11+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
			T2 = tensor(int32), tensor(int64)
DequantizeLinear	(in x:T, in x_scale:tensor(float), in x_zero_point:T, out y:tensor(float))	10+	T = tensor(int8), tensor(uint8)
Div	(in A:T, in B:T, out C:T)	7+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
Dropout	(in data:T, in ratio:T1, out output:T, out mask:T2) or (in data:T, out output:T, out mask:T) or (in data:T, out output:T, out mask:T1)	10+	T = tensor(double), tensor(float), tensor(float16)
			T1 = tensor(bool)
		[7, 9]	T = tensor(double), tensor(float), tensor(float16)
DynamicSlice	(in data:T, in starts:Tind, in ends:Tind, in axes:Tind, out output:T)	1+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			Tind = tensor(int32), tensor(int64)
Elu	(in X:T, out Y:T)	6+	T = tensor(double), tensor(float), tensor(float16)
Equal	(in A:T, in B:T, out C:T1)	11+	T = tensor(bool), tensor(int32), tensor(int64)
		[7, 10]	T = tensor(bool), tensor(int32), tensor(int64)
Erf	(in input:T, out output:T)	9+	T = tensor(double), tensor(float), tensor(float16)
Exp	(in input:T, out output:T)	6+	T = tensor(double), tensor(float), tensor(float16)
Expand	(in input:T, in shape:tensor(int64), out output:T)	8+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
EyeLike	(in input:T1, out output:T2)	9+	T1 = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(uint64)
			T2 = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(uint64)
Flatten	(in input:T, out output:T)	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 8]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[9, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Floor	(in X:T, out Y:T)	6+	T = tensor(double), tensor(float), tensor(float16)
GRU	(in X:T, in W:T, in R:T, in B:T, in sequence_lens:T1, in initial_h:T, out Y:T, out Y_h:T)	7+	T = tensor(double), tensor(float), tensor(float16)
			T1 = tensor(int32)
Gather	(in data:T, in indices:Tind, out output:T)	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			Tind = tensor(int32), tensor(int64)
		[1, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			Tind = tensor(int32), tensor(int64)
GatherElements	(in data:T, in indices:Tind, out output:T)	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			Tind = tensor(int32), tensor(int64)
Gemm	(in A:T, in B:T, in C:T, out Y:T)	11+	T = tensor(double), tensor(float), tensor(float16)
		[7, 8]	T = tensor(double), tensor(float), tensor(float16)
		[9, 10]	T = tensor(double), tensor(float), tensor(float16)
GlobalAveragePool	(in X:T, out Y:T)	1+	T = tensor(double), tensor(float), tensor(float16)
GlobalMaxPool	(in X:T, out Y:T)	1+	T = tensor(double), tensor(float), tensor(float16)
Greater	(in A:T, in B:T, out C:T1)	9+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
			T1 = tensor(bool)
		[7, 8]	T = tensor(double), tensor(float), tensor(float16)
HardSigmoid	(in X:T, out Y:T)	6+	T = tensor(double), tensor(float), tensor(float16)
Identity	(in input:T, out output:T)	1+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
If	(in cond:B, out outputs:V)	11+	B = tensor(bool)
			V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 10]	B = tensor(bool)
			V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
ImageScaler	(in input:T, out output:T)	1+	T = tensor(double), tensor(float), tensor(float16)
InstanceNormalization	(in input:T, in scale:T, in B:T, out output:T)	6+	T = tensor(double), tensor(float), tensor(float16)
LRN	(in X:T, out Y:T)	1+	T = tensor(double), tensor(float), tensor(float16)
LSTM	(in X:T, in W:T, in R:T, in B:T, in sequence_lens:T1, in initial_h:T, in initial_c:T, in P:T, out Y:T, out Y_h:T, out Y_c:T)	7+	T = tensor(double), tensor(float), tensor(float16)
			T1 = tensor(int32)
LayerNormalization	(in X:T, in scale:T, in B:T, out Y:T, out mean:U, out inv_std_var:U)	1+	T = tensor(double), tensor(float), tensor(float16)
			U = tensor(float)
LeakyRelu	(in X:T, out Y:T)	6+	T = tensor(double), tensor(float), tensor(float16)
Less	(in A:T, in B:T, out C:T1)	9+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
			T1 = tensor(bool)
		[7, 8]	T = tensor(double), tensor(float), tensor(float16)
Log	(in input:T, out output:T)	6+	T = tensor(double), tensor(float), tensor(float16)
Loop	(in M:I, in cond:B, in v_initial:V, out v_final_and_scan_outputs:V)	11+	B = tensor(bool)
			I = tensor(int64)
			V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 10]	B = tensor(bool)
			I = tensor(int64)
			V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
MatMul	(in A:T, in B:T, out Y:T)	9+	T = tensor(double), tensor(float), tensor(float16)
		[1, 8]	T = tensor(double), tensor(float), tensor(float16)
MatMulInteger	(in A:T1, in B:T2, in a_zero_point:T1, in b_zero_point:T2, out Y:T3)	10+	T1 = tensor(int8)
			T2 = tensor(int8)
			T3 = tensor(int32)
Max	(in data_0:T, out max:T)	12+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		[6, 7]	T = tensor(double), tensor(float), tensor(float16)
		[8, 11]	T = tensor(double), tensor(float), tensor(float16)
MaxPool	(in X:T, out Y:T) or (in X:T, out Y:T, out Indices:I)	12+	T = tensor(double), tensor(float), tensor(float16), tensor(int8), tensor(uint8)
		[1, 7]	I = tensor(int64)
			T = tensor(double), tensor(float), tensor(float16)
		[10, 10]	I = tensor(int64)
			T = tensor(double), tensor(float), tensor(float16)
		[11, 11]	I = tensor(int64)
			T = tensor(double), tensor(float), tensor(float16)
		[8, 9]	I = tensor(int64)
			T = tensor(double), tensor(float), tensor(float16)
MemcpyFromHost	(in X:T, out Y:T)	1+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
MemcpyToHost	(in X:T, out Y:T)	1+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Min	(in data_0:T, out min:T)	12+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		[6, 7]	T = tensor(double), tensor(float), tensor(float16)
		[8, 11]	T = tensor(double), tensor(float), tensor(float16)
Mul	(in A:T, in B:T, out C:T)	7+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
Neg	(in X:T, out Y:T)	6+	T = tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8)
NonZero	(in X:T, out Y:tensor(int64))	9+	T = tensor(bool), tensor(float), tensor(int32), tensor(int64), tensor(uint8)
Not	(in X:T, out Y:T)	1+	T = tensor(bool)
			T1 = tensor(bool)
Or	(in A:T, in B:T, out C:T1)	7+	T = tensor(bool)
			T1 = tensor(bool)
PRelu	(in X:T, in slope:T, out Y:T)	7+	T = tensor(double), tensor(float), tensor(float16)
Pad	(in data:T, in pads:tensor(int64), in constant_value:T, out output:T) or (in data:T, out output:T)	11+	T = tensor(double), tensor(float), tensor(float16)
		[2, 10]	T = tensor(double), tensor(float), tensor(float16)
ParametricSoftplus	(in X:T, out Y:T)	1+	T = tensor(double), tensor(float), tensor(float16)
Pow	(in X:T, in Y:T, out Z:T) or (in X:T, in Y:T1, out Z:T)	7+	T = tensor(double), tensor(float), tensor(float16)
QuantizeLinear	(in x:T1, in y_scale:tensor(float), in y_zero_point:T2, out y:T2)	10+	T1 = tensor(float)
			T2 = tensor(int8), tensor(uint8)
RNN	(in X:T, in W:T, in R:T, in B:T, in sequence_lens:T1, in initial_h:T, out Y:T, out Y_h:T)	7+	T = tensor(double), tensor(float), tensor(float16)
			T1 = tensor(int32)
Range	(in start:T, in limit:T, in delta:T, out output:T)	11+	T = tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64)
Reciprocal	(in X:T, out Y:T)	6+	T = tensor(double), tensor(float), tensor(float16)
ReduceL1	(in data:T, out reduced:T)	11+	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
ReduceL2	(in data:T, out reduced:T)	11+	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
ReduceLogSum	(in data:T, out reduced:T)	11+	T = tensor(double), tensor(float), tensor(float16)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16)
ReduceLogSumExp	(in data:T, out reduced:T)	11+	T = tensor(double), tensor(float), tensor(float16)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16)
ReduceMax	(in data:T, out reduced:T)	12+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int8), tensor(uint8)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
		[11, 11]	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
ReduceMean	(in data:T, out reduced:T)	11+	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
ReduceMin	(in data:T, out reduced:T)	12+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int8), tensor(uint8)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
		[11, 11]	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
ReduceProd	(in data:T, out reduced:T)	11+	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
ReduceSum	(in data:T, out reduced:T)	11+	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16), tensor(int32)
ReduceSumSquare	(in data:T, out reduced:T)	11+	T = tensor(double), tensor(float), tensor(float16)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16)
Relu	(in X:T, out Y:T)	6+	T = tensor(double), tensor(float), tensor(float16)
Reshape	(in data:T, in shape:tensor(int64), out reshaped:T) or (in data:T, out reshaped:T)	5+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			shape = tensor(int64)
Reshape_1		[1, 4]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Resize	(in X:T, in scales:tensor(float), out Y:T) or (in X:T1, in roi:T2, in scales:tensor(float), in sizes:tensor(int64), out Y:T1)	11+	T1 = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(uint8)
		[10, 10]	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(uint8)
ReverseSequence	(in input:T, in sequence_lens:tensor(int64), out Y:T)	10+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
RoiAlign	(in X:T1, in rois:T1, in batch_indices:T2, out Y:T1)	10+	T = tensor(double), tensor(float)
			T2 = tensor(int64)
Round	(in X:T, out Y:T)	11+	T = tensor(double), tensor(float), tensor(float16)
ScaledTanh	(in input:T, out output:T)	1+	T = tensor(double), tensor(float), tensor(float16)
Scan	(in initial_state_and_scan_inputs:V, out final_state_and_scan_outputs:V) or (in sequence_lens:I, in initial_state_and_scan_inputs:V, out final_state_and_scan_outputs:V)	11+	I = tensor(int64)
			V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[8, 8]	I = tensor(int64)
			V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[9, 10]	I = tensor(int64)
			V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Scatter	(in data:T, in indices:Tind, in updates:T, out output:T)	[9, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			Tind = tensor(int32), tensor(int64)
ScatterElements	(in data:T, in indices:Tind, in updates:T, out output:T)	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			Tind = tensor(int32), tensor(int64)
Selu	(in X:T, out Y:T)	6+	T = tensor(double), tensor(float), tensor(float16)
Shape	(in data:T, out shape:T1)	1+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			T1 = tensor(int64)
Shrink	(in input:T, out output:T)	9+	T = tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Sigmoid	(in X:T, out Y:T)	6+	T = tensor(double), tensor(float), tensor(float16)
Slice	(in data:T, in starts:Tind, in ends:Tind, in axes:Tind, in steps:Tind, out output:T) or (in data:T, out output:T)	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			Tind = tensor(float), tensor(int32), tensor(int64)
		[1, 9]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			Tind = tensor(float), tensor(int32), tensor(int64)
		[10, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
			Tind = tensor(float), tensor(int32), tensor(int64)
Softmax	(in input:T, out output:T)	11+	T = tensor(double), tensor(float), tensor(float16)
		[1, 10]	T = tensor(double), tensor(float), tensor(float16)
Softplus	(in X:T, out Y:T)	1+	T = tensor(double), tensor(float), tensor(float16)
Softsign	(in input:T, out output:T)	1+	T = tensor(double), tensor(float), tensor(float16)
Split	(in input:T, in split:T, out outputs...:T) or (in input:T, out outputs:T)	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[2, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Sqrt	(in X:T, out Y:T)	6+	T = tensor(double), tensor(float), tensor(float16)
Squeeze	(in data:T, out squeezed:T)	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Sub	(in A:T, in B:T, out C:T)	7+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
Sum	(in data_0:T, out sum:T)	8+	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
		[6, 7]	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
Tanh	(in input:T, out output:T)	6+	T = tensor(double), tensor(float), tensor(float16)
ThresholdedRelu	(in X:T, out Y:T)	1+	T = tensor(double), tensor(float), tensor(float16)
		10+	T = tensor(double), tensor(float), tensor(float16)
Tile	(in input:T, in repeats:T1, out output:T) or (in input:T, in tiles:T, in axis:T, out output:T)	6+	T = tensor(double), tensor(float), tensor(float16)
			T1 = tensor(int64)
TopK	(in X:T, in K:tensor(int64), out Values:T, out Indices:I) or (in X:T, out Values:T, out Indices:I)	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 9]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[10, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Transpose	(in data:T, out transposed:T)	1+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Unsqueeze	(in data:T, out expanded:T)	11+	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
		[1, 10]	T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Upsample	(in X:T, in scales:tensor(float), out Y:T) or (in X:T, out Y:T)	[7, 9]	T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(uint8)
Where	(in condition:B, in X:T, in Y:T, out output:T)	9+	B = tensor(bool)
			T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint8)
Xor	(in A:T, in B:T, out C:T1)	7+	T = tensor(bool)
			T1 = tensor(bool)
Operator Domain: com.microsoft
Attention	(in input:T, in weight:T, in bias:T, in mask_index:M, out output:T)	1+	T = tensor(float), tensor(float16)
BiasGelu	(in A:T, in B:T, out C:T)	1+	T = tensor(double), tensor(float), tensor(float16)
ConvTransposeWithDynamicPads	(in X:T, in W:T, in Pads:tensor(int64), in B:T, out Y:T)	1+	T = tensor(float)
DequantizeLinear	(in x:T1, in x_scale:T2, in x_zero_point:T1, out y:T2)	1+	T1 = tensor(int8), tensor(uint8)
			T2 = tensor(float16)
EmbedLayerNormalization	(in input_ids:T1, in segment_ids:T1, in word_embedding:T, in position_embedding:T, in segment_embedding:T, in gamma:T, in beta:T, in mask:T1, out output:T, out mask_index:T1)	1+	T = tensor(float), tensor(float16)
FastGelu	(in X:T, in bias:T, out Y:T)	1+	T = tensor(float), tensor(float16)
Gelu	(in X:T, out Y:T)	1+	T = tensor(double), tensor(float), tensor(float16)
Irfft	(in X:T, out Y:T)	1+	T = tensor(double), tensor(float), tensor(float16)
QuantizeLinear	(in x:T1, in y_scale:T1, in y_zero_point:T2, out y:T2)	1+	T1 = tensor(float16)
			T2 = tensor(int8), tensor(uint8)
Rfft	(in X:T, out Y:T)	1+	T = tensor(double), tensor(float), tensor(float16)
SkipLayerNormalization	(in input:T, in skip:T, in gamma:T, in beta:T, in bias:T, out output:T, out mean:U, out inv_std_var:U)	1+	T = tensor(float), tensor(float16)

Operators implemented by DnnlExecutionProvider

Op Name	Parameters	OpSet Version	Types Supported
Operator Domain: ai.onnx.ml
Gemm	(in A:T, in B:T, in C:T, out Y:T)	7+	T = tensor(float)