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OperatorKernels.md

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Supported Operators and Data Types

This file is automatically generated from the registered kernels by this script. Do not modify directly.

Execution Providers

Operators implemented by CPUExecutionProvider

Op Name Parameters OpSet Version Types Supported
Operator Domain: ai.onnx
Abs in X:T
out Y:T		 13+ T = tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
[6, 12] 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		 14+ T = tensor(double), tensor(float), tensor(int32), tensor(int64)
13 T = tensor(double), tensor(float), tensor(int32), tensor(int64)
[7, 12] 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)		 13+ T = tensor(double), tensor(float), tensor(int32), tensor(int8), tensor(uint8)
[11, 12] T = tensor(double), tensor(float), tensor(int32), tensor(int8), tensor(uint8)
[1, 10] T = tensor(float), tensor(int32), tensor(int8), tensor(uint8)
ArgMin in data:T
out reduced:tensor(int64)		 13+ T = tensor(double), tensor(float), tensor(int32)
[11, 12] T = tensor(double), tensor(float), tensor(int32)
[1, 10] T = tensor(float), tensor(int32)
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 T = tensor(float)
[7, 9] T = tensor(float)
BatchNormalization in X:T
in scale:T
in B:T
in input_mean:U
in input_var:U
out Y:T
out running_mean:U
out running_var:U

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

or

in X:T
in scale:T1
in B:T1
in input_mean:T2
in input_var:T2
out Y:T
out running_mean:T2
out running_var:T2		 15+ T = tensor(double), tensor(float)
T1 = tensor(double), tensor(float)
T2 = tensor(double), tensor(float)
14 T = tensor(double), tensor(float)
U = tensor(double), tensor(float)
[9, 13] T = tensor(double), tensor(float)
[7, 8] T = tensor(double), tensor(float)
BitShift in X:T
in Y:T
out Z:T		 11+ T = tensor(uint32), tensor(uint64), tensor(uint8)
BlackmanWindow in size:T1
out output:T2		 17+ T1 = tensor(int32), tensor(int64)
T2 = tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Cast in input:T1
out output:T2		 13+ 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(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)
[6, 12] 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(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)
Ceil in X:T
out Y:T		 13+ T = tensor(float)
[6, 12] T = tensor(float)
Celu in X:T
out Y:T		 12+ T = tensor(float)
Clip in input:T
in min:T
in max:T
out output:T

or

in input:T
out output:T		 13+ T = tensor(double), tensor(float), tensor(int64), tensor(int8), tensor(uint64), tensor(uint8)
12 T = tensor(double), tensor(float), tensor(int64), tensor(int8), tensor(uint64), tensor(uint8)
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		 13+ 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)
[11, 12] 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		 14+ T = tensor(double), tensor(float), tensor(int32), tensor(int64)
T2 = tensor(int32), tensor(int64)
[11, 13] T = tensor(double), tensor(float), tensor(int32), tensor(int64)
T2 = tensor(int32), tensor(int64)
DFT in input:T1
in dft_length:T2
out output:T1		 17+ T1 = tensor(double), tensor(float)
T2 = tensor(int32), tensor(int64)
DepthToSpace in input:T
out output:T		 13+ T = tensor(double), tensor(float)
[11, 12] T = tensor(double), tensor(float)
[1, 10] T = tensor(double), tensor(float)
DequantizeLinear in x:T
in x_scale:tensor(float)
in x_zero_point:T
out y:tensor(float)		 13+ T = tensor(int32), tensor(int8), tensor(uint8)
[10, 12] T = tensor(int32), tensor(int8), tensor(uint8)
Det in X:T
out Y:T		 11+ T = tensor(float)
Div in A:T
in B:T
out C:T		 14+ T = tensor(double), tensor(float), tensor(int32), tensor(int64)
13 T = tensor(double), tensor(float), tensor(int32), tensor(int64)
[7, 12] T = tensor(double), tensor(float), tensor(int32), tensor(int64)
Dropout in data:T
in ratio:T1
in training_mode:T2
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		 13+ T = tensor(double), tensor(float)
T1 = tensor(double), tensor(float)
T2 = tensor(bool)
12 T = tensor(double), tensor(float)
T1 = tensor(double), tensor(float)
T2 = tensor(bool)
[10, 11] T = tensor(double), tensor(float), tensor(float16)
T1 = tensor(bool)
[7, 9] T = tensor(double), tensor(float), tensor(float16)
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)
Einsum in Inputs:T
out Output:T		 12+ T = tensor(double), tensor(float), 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		 13+ T = tensor(bool), tensor(double), tensor(float), tensor(int32), tensor(int64)
T1 = tensor(bool)
[11, 12] T = tensor(bool), tensor(double), tensor(float), tensor(int32), tensor(int64)
T1 = tensor(bool)
[7, 10] T = tensor(bool), tensor(double), tensor(float), tensor(int32), tensor(int64)
T1 = tensor(bool)
Erf in input:T
out output:T		 13+ T = tensor(float)
[9, 12] T = tensor(float)
Exp in input:T
out output:T		 13+ T = tensor(double), tensor(float)
[6, 12] T = tensor(double), tensor(float)
Expand in input:T
in shape:tensor(int64)
out output:T		 13+ T = 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, 12] T = 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)
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		 13+ 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)
[11, 12] 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)
[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)
Floor in X:T
out Y:T		 13+ T = tensor(float)
[6, 12] 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		 14+ T = tensor(double), tensor(float)
T1 = tensor(int32)
[7, 13] T = tensor(double), tensor(float)
T1 = tensor(int32)
Gather in data:T
in indices:Tind
out output:T		 13+ 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)
[11, 12] 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		 13+ 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)
[11, 12] 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		 13+ 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)
indices = tensor(int64)
12 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)
indices = 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)
indices = tensor(int64)
Gemm in A:T
in B:T
in C:T
out Y:T		 13+ T = tensor(double), tensor(float)
[11, 12] T = tensor(double), tensor(float)
[9, 10] T = tensor(double), tensor(float)
[7, 8] T = tensor(double), 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		 13+ T = tensor(double), tensor(float), tensor(int32), tensor(int64)
T1 = tensor(bool)
[9, 12] T = tensor(double), tensor(float), tensor(int32), tensor(int64)
T1 = tensor(bool)
[7, 8] T = tensor(double), tensor(float)
T1 = tensor(bool)
GreaterOrEqual in A:T
in B:T
out C:T1		 16+ T = tensor(double), tensor(float), tensor(int32), tensor(int64)
T1 = tensor(bool)
[12, 15] T = tensor(double), tensor(float), tensor(int32), tensor(int64)
T1 = tensor(bool)
GridSample in X:T1
in grid:T1
out Y:T2		 16+ T1 = tensor(float)
T2 = tensor(float)
HammingWindow in size:T1
out output:T2		 17+ T1 = tensor(int32), tensor(int64)
T2 = tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
HannWindow in size:T1
out output:T2		 17+ T1 = tensor(int32), tensor(int64)
T2 = tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
HardSigmoid in X:T
out Y:T		 6+ T = tensor(float)
Hardmax in input:T
out output:T		 13+ T = tensor(float)
[11, 12] T = tensor(float)
[1, 10] T = tensor(float)
Identity in input:T
out output:T

or

in input:V
out output:V		 16+ V = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), 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)), 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)
[14, 15] V = 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)), 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)
13 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, 12] 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		 16+ B = tensor(bool)
V = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), 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)), 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)
[13, 15] B = tensor(bool)
V = 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)), 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)
[11, 12] 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)
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		 13+ T1 = tensor(float), tensor(float16)
T2 = tensor(bool)
[9, 12] T1 = tensor(float), tensor(float16)
T2 = tensor(bool)
LRN in X:T
out Y:T		 13+ T = tensor(float)
[1, 12] 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		 14+ T = tensor(double), tensor(float)
T1 = tensor(int32)
[7, 13] T = tensor(double), tensor(float)
T1 = tensor(int32)
LayerNormalization in X:T
in Scale:T
in B:T
out Y:T
out Mean:U
out InvStdDev:U

or

in X:T
in Scale:V
in B:V
out Y:V
out Mean:U
out InvStdDev:U		 1+ T = tensor(double), tensor(float)
U = tensor(double), tensor(float)
V = tensor(double), tensor(float)
LeakyRelu in X:T
out Y:T		 16+ T = tensor(float)
[6, 15] T = tensor(float)
Less in A:T
in B:T
out C:T1		 13+ T = tensor(double), tensor(float), tensor(int32), tensor(int64)
T1 = tensor(bool)
[9, 12] T = tensor(double), tensor(float), tensor(int32), tensor(int64)
T1 = tensor(bool)
[7, 8] T = tensor(double), tensor(float)
T1 = tensor(bool)
LessOrEqual in A:T
in B:T
out C:T1		 16+ T = tensor(double), tensor(float), tensor(int32), tensor(int64)
T1 = tensor(bool)
[12, 15] T = tensor(double), tensor(float), tensor(int32), tensor(int64)
T1 = tensor(bool)
Log in input:T
out output:T		 13+ T = tensor(double), tensor(float)
[6, 12] T = tensor(double), tensor(float)
LogSoftmax in input:T
out output:T		 13+ T = tensor(double), tensor(float)
[11, 12] 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		 16+ B = tensor(bool)
I = tensor(int64)
V = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8)), 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)), 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)
[13, 15] B = tensor(bool)
I = tensor(int64)
V = 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)), 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)
[11, 12] 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(double), 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		 13+ T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
[9, 12] 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(int8), tensor(uint8)
T2 = tensor(int8), tensor(uint8)
T3 = tensor(int32)
Max in data_0:T
out max:T		 13+ T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
12 T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
[8, 11] T = tensor(double), tensor(float)
[6, 7] T = 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)
[8, 11] I = tensor(int64)
T = tensor(double), tensor(float)
[1, 7] T = 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		 13+ T = tensor(float)
[8, 12] T = tensor(float)
[6, 7] T = tensor(float)
MeanVarianceNormalization in X:T
out Y:T

or

in input:T
out output:T		 13+ T = tensor(float)
[9, 12] T = tensor(float)
[1, 8] T = tensor(float)
MelWeightMatrix in num_mel_bins:T1
in dft_length:T1
in sample_rate:T1
in lower_edge_hertz:T2
in upper_edge_hertz:T2
out output:T3		 17+ T1 = tensor(int32), tensor(int64)
T2 = tensor(float)
T3 = tensor(double), tensor(float), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Min in data_0:T
out min:T		 13+ T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
12 T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
[8, 11] T = tensor(double), tensor(float)
[6, 7] T = tensor(float)
Mod in A:T
in B:T
out C:T		 13+ T = tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
[10, 12] 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		 14+ T = tensor(double), tensor(float), tensor(int32), tensor(int64)
13 T = tensor(double), tensor(float), tensor(int32), tensor(int64)
[7, 12] 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		 13+ T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8)
[6, 12] T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8)
NonZero in X:T
out Y:tensor(int64)		 13+ T = tensor(bool), tensor(float), tensor(int32), tensor(int64), tensor(uint8)
[9, 12] T = tensor(bool), tensor(float), tensor(int32), tensor(int64), tensor(uint8)
Not in X:T
out Y:T		 1+ T = 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)
Optional in input:V
out output:O		 15+ O = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8))
V = 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)), 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)
OptionalGetElement in input:O
out output:V		 15+ O = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8))
V = 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)), 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)
OptionalHasElement in input:O
out output:B		 15+ B = tensor(bool)
O = optional(seq(tensor(bfloat16))), optional(seq(tensor(bool))), optional(seq(tensor(double))), optional(seq(tensor(float))), optional(seq(tensor(float16))), optional(seq(tensor(int16))), optional(seq(tensor(int32))), optional(seq(tensor(int64))), optional(seq(tensor(int8))), optional(seq(tensor(string))), optional(seq(tensor(uint16))), optional(seq(tensor(uint32))), optional(seq(tensor(uint64))), optional(seq(tensor(uint8))), optional(tensor(bfloat16)), optional(tensor(bool)), optional(tensor(double)), optional(tensor(float)), optional(tensor(float16)), optional(tensor(int16)), optional(tensor(int32)), optional(tensor(int64)), optional(tensor(int8)), optional(tensor(string)), optional(tensor(uint16)), optional(tensor(uint32)), optional(tensor(uint64)), optional(tensor(uint8))
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		 16+ T = tensor(float)
[9, 15] T = tensor(float)
[7, 8] 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		 13+ T = tensor(bool), tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint32), tensor(uint64), tensor(uint8)
[11, 12] T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint32), tensor(uint64), tensor(uint8)
[2, 10] T = tensor(double), 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		 15+ T = tensor(double), tensor(float), tensor(int32), tensor(int64)
T1 = tensor(double), tensor(float), tensor(int32), tensor(int64)
[13, 14] T = tensor(double), tensor(float), tensor(int32), tensor(int64)
T1 = tensor(double), tensor(float), tensor(int32), tensor(int64)
12 T = tensor(double), tensor(float), tensor(int32), tensor(int64)
T1 = tensor(double), tensor(float), tensor(int32), tensor(int64)
[7, 11] 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(int8), tensor(uint8)
T2 = tensor(int8), tensor(uint8)
T3 = tensor(int8), 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(int8), tensor(uint8)
T2 = tensor(int8), tensor(uint8)
T3 = tensor(int8), tensor(uint8)
QuantizeLinear in x:T1
in y_scale:tensor(float)
in y_zero_point:T2
out y:T2		 13+ T1 = tensor(float)
T2 = tensor(int8), tensor(uint8)
[10, 12] 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		 14+ T = tensor(float)
T1 = tensor(int32)
[7, 13] 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		 13+ T = tensor(double), tensor(float)
[6, 12] T = tensor(double), tensor(float)
ReduceL1 in data:T
out reduced:T		 13+ T = tensor(float), tensor(int32)
[11, 12] T = tensor(float), tensor(int32)
[1, 10] T = tensor(float), tensor(int32)
ReduceL2 in data:T
out reduced:T		 13+ T = tensor(float), tensor(int32)
[11, 12] T = tensor(float), tensor(int32)
[1, 10] T = tensor(float), tensor(int32)
ReduceLogSum in data:T
out reduced:T		 13+ T = tensor(float), tensor(int32)
[11, 12] T = tensor(float), tensor(int32)
[1, 10] T = tensor(float), tensor(int32)
ReduceLogSumExp in data:T
out reduced:T		 13+ T = tensor(double), tensor(float), tensor(int32)
[11, 12] T = tensor(double), tensor(float), tensor(int32)
[1, 10] T = tensor(double), tensor(float), tensor(int32)
ReduceMax in data:T
out reduced:T		 13+ T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
12 T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
11 T = tensor(double), tensor(float), tensor(int32), tensor(int64)
[1, 10] T = tensor(double), tensor(float), tensor(int32), tensor(int64)
ReduceMean in data:T
out reduced:T		 13+ T = tensor(double), tensor(float), tensor(int32)
[11, 12] T = tensor(double), tensor(float), tensor(int32)
[1, 10] T = tensor(double), tensor(float), tensor(int32)
ReduceMin in data:T
out reduced:T		 13+ T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
12 T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
11 T = tensor(double), tensor(float), tensor(int32), tensor(int64)
[1, 10] T = tensor(double), tensor(float), tensor(int32), tensor(int64)
ReduceProd in data:T
out reduced:T		 13+ T = tensor(float), tensor(int32), tensor(int64)
[11, 12] T = tensor(float), tensor(int32), tensor(int64)
[1, 10] T = tensor(float), tensor(int32), tensor(int64)
ReduceSum in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T		 13+ T = tensor(double), tensor(float), tensor(int32), tensor(int64)
[11, 12] T = tensor(double), tensor(float), tensor(int32), tensor(int64)
[1, 10] T = tensor(double), tensor(float), tensor(int32), tensor(int64)
ReduceSumSquare in data:T
out reduced:T		 13+ T = tensor(double), tensor(float), tensor(int32)
[11, 12] T = tensor(double), tensor(float), tensor(int32)
[1, 10] T = tensor(double), tensor(float), tensor(int32)
Relu in X:T
out Y:T		 14+ T = tensor(double), tensor(float), tensor(int32), tensor(int8)
13 T = tensor(double), tensor(float)
[6, 12] T = tensor(double), tensor(float)
Reshape in data:T
in shape:tensor(int64)
out reshaped:T

or

in data:T
out reshaped:T		 14+ 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)
13 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)
[5, 12] 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)
[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		 13+ T1 = tensor(float), tensor(int32), tensor(int8), tensor(uint8)
[11, 12] T1 = tensor(float), tensor(int32), tensor(int8), tensor(uint8)
10 T = tensor(float), tensor(int32), tensor(int8), 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		 16+ T1 = tensor(double), tensor(float)
T2 = tensor(int64)
[10, 15] T1 = tensor(double), tensor(float)
T2 = tensor(int64)
Round in X:T
out Y:T		 11+ T = tensor(double), tensor(float), tensor(float16)
STFT in signal:T1
in frame_step:T2
in window:T1
in frame_length:T2
out output:T1		 17+ T1 = tensor(double), tensor(float)
T2 = tensor(int32), tensor(int64)
Scale in input:T
out output:T		 1+ T = tensor(float)
ScaledTanh in input:T
out output:T		 1+ T = tensor(float)
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		 16+ 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)
[11, 15] 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] 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 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		 16+ 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)
[13, 15] 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)
[11, 12] 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		 16+ 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)
[13, 15] 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)
[11, 12] 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)
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		 15+ 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(int64)
[13, 14] 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(int64)
[1, 12] 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(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		 13+ T = tensor(double), tensor(float)
[6, 12] T = tensor(double), tensor(float)
Sign in input:T
out output:T		 13+ 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)
[9, 12] 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)
SimplifiedLayerNormalization in X:T
in scale:V
out Y:V
out inv_std_var:U		 1+ T = tensor(double), tensor(float)
U = tensor(double), tensor(float)
V = tensor(double), tensor(float)
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		 13+ 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)
[1, 12] 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		 13+ 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)
[11, 12] 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)
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)
[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)
Softmax in input:T
out output:T		 13+ T = tensor(double), tensor(float)
[11, 12] 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		 13+ T = tensor(double), tensor(float)
[1, 12] T = tensor(double), tensor(float)
Split in input:T
in split:T
out outputs...:T

or

in input:T
in split:tensor(int64)
out outputs:T

or

in input:T
out outputs:T		 13+ T = tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint8)
[11, 12] T = tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint8)
[2, 10] T = tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint8)
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(int64), tensor(string)
Sqrt in X:T
out Y:T		 13+ T = tensor(double), tensor(float)
[6, 12] T = tensor(double), tensor(float)
Squeeze in data:T
in axes:tensor(int64)
out squeezed:T

or

in data:T
out squeezed:T		 13+ 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)
[11, 12] 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+ X = tensor(string)
Sub in A:T
in B:T
out C:T		 14+ T = tensor(double), tensor(float), tensor(int32), tensor(int64)
13 T = tensor(double), tensor(float), tensor(int32), tensor(int64)
[7, 12] T = tensor(double), tensor(float), tensor(int32), tensor(int64)
Sum in data_0:T
out sum:T		 13+ T = tensor(double), tensor(float)
[8, 12] T = tensor(double), tensor(float)
[6, 7] T = tensor(double), tensor(float)
Tan in input:T
out output:T		 7+ T = tensor(float)
Tanh in input:T
out output:T		 13+ T = tensor(double), tensor(float)
[6, 12] T = tensor(double), 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		 13+ 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)
[6, 12] 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(double), tensor(float), tensor(int32), tensor(int64)
10 I = tensor(int64)
T = tensor(double), tensor(float)
[1, 9] I = tensor(int64)
T = tensor(double), tensor(float)
Transpose in data:T
out transposed:T		 13+ 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, 12] 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)
Trilu in input:T
in k:tensor(int64)
out output:T		 14+ T = tensor(double), tensor(float), tensor(int64)
Unique in X:T
out Y:T
out indices:tensor(int64)
out inverse_indices:tensor(int64)
out counts:tensor(int64)		 11+ T = tensor(float), tensor(int64), tensor(int8), tensor(string)
Unsqueeze in data:T
in axes:tensor(int64)
out expanded:T

or

in data:T
out expanded:T		 13+ 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)
[11, 12] 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		 9 T = tensor(float), tensor(int32), tensor(int8), tensor(uint8)
[7, 8] T = tensor(float), tensor(int32), tensor(int8), tensor(uint8)
Where in condition:B
in X:T
in Y:T
out output:T		 16+ T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(string), tensor(uint8)
[9, 15] T = tensor(double), 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)
Operator Domain: ai.onnx.ml
ArrayFeatureExtractor in X:T
in Y:tensor(int64)
out Z:T		 1+ T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(string)
Binarizer in X:T
out Y:T		 1+ T = tensor(float)
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)
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)
FeatureVectorizer in X:T1
out Y:tensor(float)		 1+ T1 = tensor(double), tensor(float), tensor(int32), tensor(int64)
Imputer in X:T
out Y:T		 1+ T = tensor(float), tensor(int64)
LabelEncoder in X:T1
out Y:T2		 2+ T1 = tensor(float), tensor(int64), tensor(string)
T2 = tensor(float), tensor(int64), tensor(string)
1 T1 = tensor(int64), tensor(string)
T2 = tensor(int64), tensor(string)
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)
Normalizer in X:T
out Y:tensor(float)		 1+ T = tensor(double), tensor(float), tensor(int32), tensor(int64)
OneHotEncoder in X:T
out Y:tensor(float)		 1+ T = tensor(double), tensor(float), tensor(int64), tensor(string)
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)
Scaler in X:T
out Y:tensor(float)		 1+ T = tensor(double), tensor(float), tensor(int32), tensor(int64)
TreeEnsembleClassifier in X:T1
out Y:T2
out Z:tensor(float)		 3+ T1 = tensor(double), tensor(float), tensor(int32), tensor(int64)
T2 = tensor(int64), tensor(string)
[1, 2] T1 = tensor(double), tensor(float), tensor(int32), tensor(int64)
T2 = tensor(int64), tensor(string)
TreeEnsembleRegressor in X:T
out Y:tensor(float)		 3+ T = tensor(double), tensor(float)
[1, 2] T = tensor(double), tensor(float)
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
in past:T
in extra_add:T
out output:T
out present: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)
BeamSearch in input_ids:I
in max_length:I
in min_length:I
in num_beams:I
in num_return_sequences:I
in length_penalty:T
in repetition_penalty:T
in vocab_mask:M
in prefix_vocab_mask:M
in attention_mask:I
out sequences:I
out sequences_scores:T
out scores:T		 1+ T = tensor(float)
BiasGelu in A:T
in B:T
out C:T		 1+ T = tensor(float)
BifurcationDetector in src_tokens:T
in cur_tokens:T
in prev_suffix_match_idx:T
in pred_tokens:T
out tokens:T
out suffix_match_idx:T		 1+ T = tensor(int64)
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+ T1 = 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)
DynamicQuantizeLSTM in X:T
in W:T2
in R:T2
in B:T
in sequence_lens:T1
in initial_h:T
in initial_c:T
in P:T
in W_scale:T
in W_zero_point:T2
in R_scale:T
in R_zero_point:T2
out Y:T
out Y_h:T
out Y_c:T		 1+ T = tensor(float)
T1 = tensor(int32)
T2 = tensor(int8), tensor(uint8)
DynamicQuantizeMatMul in A:T1
in B:T2
in b_scale:T1
in b_zero_point:T2
in bias:T1
out Y:T1		 1+ T1 = tensor(float)
T2 = tensor(int8), tensor(uint8)
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
in position_ids:T1
out output:T
out mask_index:T1
out embedding_sum:T		 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
in Z: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)
FusedMatMul in A:T
in B: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)
GridSample in X:T1
in Grid:T1
out Y:T2		 1+ T1 = tensor(float)
T2 = tensor(float)
Inverse in X:T
out Y:T		 1+ T = tensor(double), tensor(float), tensor(float16)
MatMulInteger16 in A:T1
in B:T2
out Y:T3		 1+ T1 = tensor(int16)
T2 = tensor(int16)
T3 = tensor(int32)
MatMulIntegerToFloat in A:T1
in B:T2
in a_scale:T3
in b_scale:T3
in a_zero_point:T1
in b_zero_point:T2
in bias:T3
out Y:T3		 1+ T1 = tensor(int8), tensor(uint8)
T2 = tensor(int8), tensor(uint8)
T3 = tensor(float)
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(double), tensor(float), tensor(int32), tensor(int64), tensor(string), tensor(uint32), tensor(uint64)
T2 = tensor(int32), tensor(uint32)
NGramRepeatBlock in input_ids:Tid
in scores:T
out scores_out:T		 1+ T = tensor(float)
Tid = tensor(int64)
NhwcMaxPool in x:T
out y:T		 1+ T = tensor(int8), tensor(uint8)
Pad in data:T
in pads:tensor(int64)
in value:T
out output:T		 1+ T = tensor(float)
QAttention in input:T1
in weight:T2
in bias:T3
in input_scale:T3
in weight_scale:T3
in mask_index:T4
in input_zero_point:T1
in weight_zero_point:T2
in past:T3
out output:T3
out present:T3		 1+ T1 = tensor(uint8)
T2 = tensor(int8), tensor(uint8)
T3 = tensor(float)
T4 = tensor(int32)
QEmbedLayerNormalization in input_ids:T1
in segment_ids:T1
in word_embedding_quant:T2
in position_embedding_quant:T2
in segment_embedding:T2
in gamma_quant:T2
in beta_quant:T2
in mask:T1
in word_embedding_scale:T
in position_embedding_scale:T
in segment_embedding_scale:T
in gamma_scale:T
in beta_scale:T
in word_embedding_zero_point:T2
in position_embedding_zero_point:T2
in segment_embedding_zero_point:T2
in gamma_zero_point:T2
in beta_zero_point:T2
out layernorm_out:T
out mask_index_out:T1		 1+ T = tensor(float)
QGemm in A:TA
in a_scale:T
in a_zero_point:TA
in B:TB
in b_scale:T
in b_zero_point:TB
in C:TC
in y_scale:T
in y_zero_point:TYZ
out Y:TY		 1+ T = tensor(float)
TA = tensor(int8), tensor(uint8)
TB = tensor(int8), tensor(uint8)
TC = tensor(int32)
TY = tensor(float), tensor(int8), tensor(uint8)
TYZ = tensor(int8), tensor(uint8)
QLinearAdd in A:T
in A_scale:tensor(float)
in A_zero_point:T
in B:T
in B_scale:tensor(float)
in B_zero_point:T
in C_scale:tensor(float)
in C_zero_point:T
out C:T		 1+ T = tensor(int8), tensor(uint8)
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		 1+ T1 = tensor(int8), tensor(uint8)
T2 = tensor(int8), tensor(uint8)
T3 = tensor(int8), tensor(uint8)
T4 = tensor(int32)
QLinearLeakyRelu in X:T
in X_scale:tensor(float)
in X_zero_point:T
in Y_scale:tensor(float)
in Y_zero_point:T
out Y:T		 1+ T = tensor(int8), tensor(uint8)
QLinearMul in A:T
in A_scale:tensor(float)
in A_zero_point:T
in B:T
in B_scale:tensor(float)
in B_zero_point:T
in C_scale:tensor(float)
in C_zero_point:T
out C:T		 1+ T = tensor(int8), tensor(uint8)
QLinearSigmoid in X:T
in X_scale:tensor(float)
in X_zero_point:T
in Y_scale:tensor(float)
in Y_zero_point:T
out Y:T		 1+ T = tensor(int8), tensor(uint8)
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)
SparseToDenseMatMul in A:T
in B:T1
out Y:T1		 1+ T = sparse_tensor(double), sparse_tensor(float), sparse_tensor(int32), sparse_tensor(int64), sparse_tensor(uint32), sparse_tensor(uint64)
T1 = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
Tokenizer in X:T
out Y:T		 1+ T = tensor(string)
TransposeMatMul in A:T
in B:T
out Y:T		 1+ T = tensor(float)
Trilu in X:T
in k:tensor(int64)
out Y:T		 1+ T = tensor(double), tensor(float), tensor(int64)
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
Abs in X:T
out Y:T		 13+ T = tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
[6, 12] 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		 14+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
13 T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
[7, 12] 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 T = tensor(double), tensor(float), tensor(float16)
[7, 9] T = tensor(double), tensor(float), tensor(float16)
BatchNormalization in X:T
in scale:T
in B:T
in input_mean:U
in input_var:U
out Y:T
out running_mean:U
out running_var:U

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

or

in X:T
in scale:T1
in B:T1
in input_mean:T2
in input_var:T2
out Y:T
out running_mean:T2
out running_var:T2		 15+ T = tensor(double), tensor(float), tensor(float16)
T1 = tensor(double), tensor(float), tensor(float16)
T2 = tensor(double), tensor(float), tensor(float16)
14 T = tensor(double), tensor(float), tensor(float16)
U = tensor(double), tensor(float), tensor(float16)
[9, 13] T = tensor(double), tensor(float), tensor(float16)
[7, 8] T = tensor(double), tensor(float), tensor(float16)
Cast in input:T1
out output:T2		 13+ T1 = 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)
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)
[9, 12] 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(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)
[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(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)
Ceil in X:T
out Y:T		 13+ T = tensor(double), tensor(float), tensor(float16)
[6, 12] 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		 13+ T = tensor(double), tensor(float), tensor(float16), tensor(int64), tensor(int8), tensor(uint64), tensor(uint8)
12 T = tensor(double), tensor(float), tensor(float16), tensor(int64), tensor(int8), tensor(uint64), tensor(uint8)
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		 13+ 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)
[11, 12] 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)
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(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(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)
Cos in input:T
out output:T		 7+ 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		 14+ T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
T2 = tensor(int32), tensor(int64)
[11, 13] T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
T2 = tensor(int32), tensor(int64)
DepthToSpace in input:T
out output:T		 13+ T = tensor(double), tensor(float), tensor(float16)
[11, 12] T = tensor(double), tensor(float), tensor(float16)
[1, 10] T = tensor(double), tensor(float), tensor(float16)
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		 14+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
13 T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
[7, 12] T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
Dropout in data:T
in ratio:T1
in training_mode:T2
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		 13+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
T1 = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
T2 = tensor(bool)
12 T = tensor(double), tensor(float), tensor(float16)
T1 = tensor(double), tensor(float), tensor(float16)
T2 = tensor(bool)
[10, 11] 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)
Einsum in Inputs:T
out Output:T		 12+ T = tensor(double), tensor(float), tensor(float16)
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		 13+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
T1 = tensor(bool)
[11, 12] T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
[7, 10] T = tensor(bool), tensor(int32), tensor(int64)
Erf in input:T
out output:T		 13+ T = tensor(double), tensor(float), tensor(float16)
[9, 12] T = tensor(double), tensor(float), tensor(float16)
Exp in input:T
out output:T		 13+ T = tensor(double), tensor(float), tensor(float16)
[6, 12] T = tensor(double), tensor(float), tensor(float16)
Expand in input:T
in shape:tensor(int64)
out output:T		 13+ 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)
[8, 12] 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		 13+ 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)
[11, 12] 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)
[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)
Floor in X:T
out Y:T		 13+ T = tensor(double), tensor(float), tensor(float16)
[6, 12] 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		 14+ T = tensor(double), tensor(float), tensor(float16)
T1 = tensor(int32)
[7, 13] T = tensor(double), tensor(float), tensor(float16)
T1 = tensor(int32)
Gather in data:T
in indices:Tind
out output:T		 13+ 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)
[11, 12] 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		 13+ 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)
[11, 12] 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)
GatherND in data:T
in indices:tensor(int64)
out output:T		 13+ T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int64)
indices = tensor(int64)
12 T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int64)
indices = tensor(int64)
11 T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int64)
indices = tensor(int64)
Gemm in A:T
in B:T
in C:T
out Y:T		 13+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
[11, 12] T = tensor(double), tensor(float), tensor(float16)
[9, 10] T = tensor(double), tensor(float), tensor(float16)
[7, 8] 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		 13+ T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
T1 = tensor(bool)
[9, 12] T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
[7, 8] T = tensor(double), tensor(float), tensor(float16)
GreaterOrEqual in A:T
in B:T
out C:T1		 16+ T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
T1 = tensor(bool)
[12, 15] T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
T1 = tensor(bool)
HardSigmoid in X:T
out Y:T		 6+ T = tensor(double), tensor(float), tensor(float16)
Identity in input:T
out output:T

or

in input:V
out output:V		 14+ V = 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(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), 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)
13 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, 12] 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		 13+ B = tensor(bool)
V = 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)), 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)
[11, 12] 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		 13+ T = tensor(double), tensor(float), tensor(float16)
[1, 12] 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		 14+ T = tensor(double), tensor(float), tensor(float16)
T1 = tensor(int32)
[7, 13] 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 InvStdDev:U

or

in X:T
in Scale:V
in B:V
out Y:V
out Mean:U
out InvStdDev:U		 1+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
U = tensor(double), tensor(float)
V = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
LeakyRelu in X:T
out Y:T		 16+ T = tensor(double), tensor(float), tensor(float16)
[6, 15] T = tensor(double), tensor(float), tensor(float16)
Less in A:T
in B:T
out C:T1		 13+ T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
T1 = tensor(bool)
[9, 12] T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
[7, 8] T = tensor(double), tensor(float), tensor(float16)
LessOrEqual in A:T
in B:T
out C:T1		 16+ T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
T1 = tensor(bool)
[12, 15] T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
T1 = tensor(bool)
Log in input:T
out output:T		 13+ T = tensor(double), tensor(float), tensor(float16)
[6, 12] T = tensor(double), tensor(float), tensor(float16)
LogSoftmax in input:T
out output:T		 13+ T = tensor(double), tensor(float), tensor(float16)
[11, 12] T = tensor(double), tensor(float), tensor(float16)
[1, 10] 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		 13+ B = tensor(bool)
I = tensor(int64)
V = 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)), 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)
[11, 12] 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		 13+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
[9, 12] 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		 13+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
12 T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
[6, 11] T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
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(float16), tensor(int8), tensor(uint8)
11 I = tensor(int64)
T = tensor(double), tensor(float), tensor(float16)
10 I = tensor(int64)
T = tensor(double), tensor(float), tensor(float16)
[8, 9] I = tensor(int64)
T = tensor(double), tensor(float), tensor(float16)
[1, 7] T = tensor(double), tensor(float), tensor(float16)
MemcpyFromHost in X:T
out Y:T		 1+ T = 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(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), 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 = 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(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), 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		 13+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
12 T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
[6, 11] T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
Mul in A:T
in B:T
out C:T		 14+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
13 T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
[7, 12] T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
Neg in X:T
out Y:T		 13+ T = tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8)
[6, 12] T = tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8)
NonZero in X:T
out Y:tensor(int64)		 13+ T = tensor(bool), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint8)
[9, 12] T = tensor(bool), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint8)
Not in X:T
out Y:T		 1+ T = tensor(bool)
OneHot in indices:T1
in depth:T2
in values:T3
out output:T3		 11+ T1 = tensor(int32), tensor(int64)
T2 = tensor(int32), tensor(int64)
T3 = tensor(float), tensor(float16), tensor(int64)
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		 16+ T = tensor(double), tensor(float), tensor(float16)
[9, 15] T = tensor(double), tensor(float), tensor(float16)
[7, 8] 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		 13+ T = tensor(bool), tensor(double), tensor(float), tensor(float16)
[11, 12] 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		 15+ T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
T1 = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
[13, 14] T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
T1 = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
12 T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
T1 = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
[7, 11] 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		 14+ T = tensor(double), tensor(float), tensor(float16)
T1 = tensor(int32)
[7, 13] T = tensor(double), tensor(float), tensor(float16)
T1 = tensor(int32)
RandomNormal out output:T 1+ T = tensor(double), tensor(float), tensor(float16)
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), tensor(float16)
RandomUniform out output:T 1+ T = tensor(double), tensor(float), tensor(float16)
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), tensor(float16)
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		 13+ T = tensor(double), tensor(float), tensor(float16)
[6, 12] T = tensor(double), tensor(float), tensor(float16)
ReduceL1 in data:T
out reduced:T		 13+ T = tensor(double), tensor(float), tensor(float16), tensor(int32)
[11, 12] 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		 13+ T = tensor(double), tensor(float), tensor(float16), tensor(int32)
[11, 12] 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		 13+ T = tensor(double), tensor(float), tensor(float16)
[11, 12] T = tensor(double), tensor(float), tensor(float16)
[1, 10] T = tensor(double), tensor(float), tensor(float16)
ReduceLogSumExp in data:T
out reduced:T		 13+ T = tensor(double), tensor(float), tensor(float16)
[11, 12] T = tensor(double), tensor(float), tensor(float16)
[1, 10] T = tensor(double), tensor(float), tensor(float16)
ReduceMax in data:T
out reduced:T		 13+ T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
12 T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
11 T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
[1, 10] T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
ReduceMean in data:T
out reduced:T		 13+ T = tensor(double), tensor(float), tensor(float16), tensor(int32)
[11, 12] 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		 14+ T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
13 T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
12 T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
11 T = tensor(double), tensor(float), tensor(float16), tensor(int32)
[1, 10] T = tensor(double), tensor(float), tensor(float16), tensor(int32)
ReduceProd in data:T
out reduced:T		 13+ T = tensor(double), tensor(float), tensor(float16), tensor(int32)
[11, 12] T = tensor(double), tensor(float), tensor(float16), tensor(int32)
[1, 10] T = tensor(double), tensor(float), tensor(float16), tensor(int32)
ReduceSum in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T		 13+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
[11, 12] T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
[1, 10] T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
ReduceSumSquare in data:T
out reduced:T		 13+ T = tensor(double), tensor(float), tensor(float16)
[11, 12] T = tensor(double), tensor(float), tensor(float16)
[1, 10] T = tensor(double), tensor(float), tensor(float16)
Relu in X:T
out Y:T		 14+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
13 T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
[6, 12] 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		 14+ 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)
13 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)
[5, 12] 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)
[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		 13+ T1 = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(uint8)
[11, 12] T1 = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(uint8)
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+ T1 = 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		 16+ 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)
[11, 15] 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)
[9, 10] 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 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(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		 13+ 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)
[11, 12] 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)
ScatterND in data:T
in indices:tensor(int64)
in updates:T
out output:T		 13+ 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)
[11, 12] 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)
Selu in X:T
out Y:T		 6+ T = tensor(double), tensor(float), tensor(float16)
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(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(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(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(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(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(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(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(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8))
Shape in data:T
out shape:T1		 15+ 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)
[13, 14] 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)
[1, 12] 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		 13+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
[6, 12] T = tensor(double), tensor(float), tensor(float16)
SimplifiedLayerNormalization in X:T
in scale:V
out Y:V
out inv_std_var:U		 1+ T = tensor(double), tensor(float), tensor(float16)
U = tensor(double), tensor(float)
V = tensor(double), tensor(float), tensor(float16)
Sin in input:T
out output:T		 7+ T = tensor(double), tensor(float), tensor(float16)
Size in data:T
out size:T1		 13+ 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(int64)
[1, 12] 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(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		 13+ 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)
[11, 12] 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)
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)
[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)
Softmax in input:T
out output:T		 13+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
[11, 12] 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)
SpaceToDepth in input:T
out output:T		 13+ T = tensor(double), tensor(float), tensor(float16)
[1, 12] T = tensor(double), tensor(float), tensor(float16)
Split in input:T
in split:T
out outputs...:T

or

in input:T
in split:tensor(int64)
out outputs:T

or

in input:T
out outputs:T		 13+ 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)
[11, 12] 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		 13+ T = tensor(double), tensor(float), tensor(float16)
[6, 12] T = tensor(double), tensor(float), tensor(float16)
Squeeze in data:T
in axes:tensor(int64)
out squeezed:T

or

in data:T
out squeezed:T		 13+ 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)
[11, 12] 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		 14+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
13 T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
[7, 12] T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
Sum in data_0:T
out sum:T		 13+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
[8, 12] T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
[6, 7] T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
Tanh in input:T
out output:T		 13+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
[6, 12] T = tensor(double), tensor(float), tensor(float16)
ThresholdedRelu in X:T
out Y:T		 10+ T = tensor(double), tensor(float), tensor(float16)
1+ 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		 13+ T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
T1 = tensor(int64)
[6, 12] T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
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(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 I = tensor(int64)
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)
Transpose in data:T
out transposed:T		 13+ 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, 12] 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)
Trilu in input:T
in k:tensor(int64)
out output:T		 14+ 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
in axes:tensor(int64)
out expanded:T

or

in data:T
out expanded:T		 13+ 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)
[11, 12] 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		 9 T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(uint8)
[7, 8] T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(uint8)
Where in condition:B
in X:T
in Y:T
out output:T		 16+ B = tensor(bool)
T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint8)
[9, 15] B = tensor(bool)
T = tensor(double), 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
in past:T
in extra_add:T
out output:T
out present:T		 1+ T = tensor(float), tensor(float16)
BeamSearch in input_ids:I
in max_length:I
in min_length:I
in num_beams:I
in num_return_sequences:I
in length_penalty:T
in repetition_penalty:T
in vocab_mask:M
in prefix_vocab_mask:M
in attention_mask:I
out sequences:I
out sequences_scores:T
out scores:T		 1+ T = tensor(float), tensor(float16)
BiasDropout in data:T
in bias:T
in residual:T
in ratio:T1
in training_mode:T2
out output:T
out mask:T2		 1+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
T1 = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
T2 = tensor(bool)
BiasGelu in A:T
in B:T
out C:T		 1+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
BiasSoftmax in data:T
in bias:T
out output:T		 1+ T = tensor(double), tensor(float), tensor(float16)
BitmaskBiasDropout in data:T
in bias:T
in residual:T
in ratio:T1
in training_mode:T2
out output:T
out mask:T3		 1+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
T1 = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
T2 = tensor(bool)
T3 = tensor(uint32)
BitmaskDropout in data:T
in ratio:T1
in training_mode:T2
out output:T
out mask:T3		 1+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
T1 = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
T2 = tensor(bool)
T3 = tensor(uint32)
ComplexMul in A:T
in B:T
out C:T		 1+ T = tensor(float), tensor(float16)
ComplexMulConj in A:T
in B:T
out C:T		 1+ T = 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)
DecoderAttention in query:T
in key:T
in q_weight:T
in kv_weight:T
in bias:T
in key_padding_mask:B
in key_cache:T
in value_cache:T
in static_kv:B
in use_past:B
in has_layer_state:B
in has_key_padding_mask:B
out output:T
out new_key_cache:T
out new_value_cache:T		 1+ T = tensor(float), tensor(float16)
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
in position_ids:T1
out output:T
out mask_index:T1
out embedding_sum:T		 1+ T = tensor(float), tensor(float16)
FastGelu in X:T
in bias:T
out Y:T		 1+ T = tensor(bfloat16), tensor(float), tensor(float16)
FusedConv in X:T
in W:T
in B:T
in Z:T
out Y:T		 1+ T = tensor(float)
FusedMatMul in A:T
in B:T
out Y:T		 1+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
Gelu in X:T
out Y:T		 1+ T = tensor(double), tensor(float), tensor(float16)
GridSample in X:T1
in Grid:T1
out Y:T2		 1+ T1 = tensor(float)
T2 = tensor(float)
Inverse 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)
LongformerAttention in input:T
in weight:T
in bias:T
in mask:T
in global_weight:T
in global_bias:T
in global:G
out output:T		 1+ T = tensor(float), tensor(float16)
NGramRepeatBlock in input_ids:Tid
in scores:T
out scores_out:T		 1+ T = tensor(float)
Tid = tensor(int64)
QAttention in input:T1
in weight:T2
in bias:T3
in input_scale:T3
in weight_scale:T3
in mask_index:T4
in input_zero_point:T1
in weight_zero_point:T2
in past:T3
out output:T3
out present:T3		 1+ T1 = tensor(int8)
T2 = tensor(int8)
T3 = tensor(float), tensor(float16)
T4 = tensor(int32)
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)
TransposeMatMul in A:T
in B:T
out Y:T		 1+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
Trilu in X:T
in k:tensor(int64)
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)