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OperatorKernels.md

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1279 lines (1265 loc) · 235 KB

Supported Operators and Data Types

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

Execution Providers


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)
AffineGrid in theta:T1
in size:T2
out grid:T1
20+ T1 = tensor(double), tensor(float)
T2 = tensor(int64)
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
19+ T = tensor(float)
[11, 18] 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)
BitwiseAnd in A:T
in B:T
out C:T
18+ T = tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
BitwiseNot in X:T
out Y:T
18+ T = tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
BitwiseOr in A:T
in B:T
out C:T
18+ T = tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
BitwiseXor in A:T
in B:T
out C:T
18+ T = tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), 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
19+ T1 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), 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(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
[13, 18] T1 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), 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(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), 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(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), 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(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), 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(double), tensor(float)
[6, 12] T = tensor(double), 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(int32), tensor(int64), tensor(int8), tensor(uint32), tensor(uint64), tensor(uint8)
12 T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint32), tensor(uint64), tensor(uint8)
11 T = tensor(float)
[6, 10] T = tensor(float)
Col2Im in input:T
in image_shape:tensor(int64)
in block_shape:tensor(int64)
out output:T
18+ 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
20+ T1 = tensor(int64)
T2 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
[9, 19] 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
in axis:tensor(int64)
out output:T1

or

in input:T1
in dft_length:T2
out output:T1
20+ T1 = tensor(double), tensor(float)
T2 = tensor(int32), tensor(int64)
[17, 19] 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)

or

in x:T1
in x_scale:T2
in x_zero_point:T1
out y:T2
19+ T1 = tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int32), tensor(int8), tensor(uint8)
T2 = tensor(float), tensor(float16)
[13, 18] 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
19+ T = tensor(bool), tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(string)
T1 = tensor(bool)
[13, 18] 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(double), tensor(float)
[6, 12] T = tensor(double), 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:T2
out Y:T1
20+ T1 = tensor(double), tensor(float)
T2 = tensor(double), tensor(float)
[16, 19] 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
19+ 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(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), 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(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
[16, 18] 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
19+ 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(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), 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(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
[16, 18] 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
20+ T1 = tensor(double), tensor(float), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz)
T2 = tensor(bool)
[10, 19] T1 = tensor(double), tensor(float)
T2 = tensor(bool)
IsNaN in X:T1
out Y:T2
20+ T1 = tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz)
T2 = tensor(bool)
[13, 19] T1 = tensor(double), tensor(float), tensor(float16)
T2 = tensor(bool)
[9, 12] T1 = tensor(double), 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
17+ T = tensor(double), tensor(float)
U = tensor(float)
[1, 16] 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
19+ 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(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), 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(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
[16, 18] 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
18+ T = tensor(float)
[11, 17] 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
18+ 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)), 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)
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)
[15, 17] 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
18+ 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)), 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)
[15, 17] 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
in axes:Tind
out output:T

or

in data:T
in pads:tensor(int64)
in constant_value:T
out output:T

or

in data:T
out output:T
19+ T = tensor(bool), tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint32), tensor(uint64), tensor(uint8)
18 T = tensor(bool), tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint32), tensor(uint64), tensor(uint8)
[13, 17] 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:T1
in y_zero_point:T2
out y:T2

or

in x:T1
in y_scale:tensor(float)
in y_zero_point:T2
out y:T2
19+ T1 = tensor(float), tensor(float16)
T2 = tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int8), tensor(uint8)
[13, 18] 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
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(float), tensor(int32), tensor(int64)
[13, 17] 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)
ReduceL2 in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(float), tensor(int32), tensor(int64)
[13, 17] 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)
ReduceLogSum in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(float), tensor(int32), tensor(int64)
[13, 17] 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)
ReduceLogSumExp in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(double), tensor(float), tensor(int32), tensor(int64)
[13, 17] 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)
ReduceMax in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
20+ T = tensor(bool), tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
[18, 19] T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
[13, 17] 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
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(double), tensor(float), tensor(int32)
[13, 17] 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
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
20+ T = tensor(bool), tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
[18, 19] T = tensor(double), tensor(float), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
[13, 17] 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
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(float), tensor(int32), tensor(int64)
[13, 17] 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
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(double), tensor(float), tensor(int32), tensor(int64)
[13, 17] 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)
RegexFullMatch in X:T1
out Y:T2
20+ T1 = tensor(string)
T2 = tensor(bool)
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
19+ T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
shape = tensor(int64)
[14, 18] 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
19+ T1 = tensor(float), tensor(int32), tensor(int8), tensor(uint8)
18 T1 = tensor(float), tensor(int32), tensor(int8), tensor(uint8)
[13, 17] 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
19+ V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
[16, 18] 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
18+ 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)
[16, 17] 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
18+ 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)
[16, 17] 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
19+ T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
T1 = tensor(int64)
[15, 18] 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
19+ 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)
[13, 18] 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
18+ 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, 17] 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)
[2, 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)
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(float16), 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)
StringConcat in X:T
in Y:T
out Z:T
20+ T = tensor(string)
StringNormalizer in X:tensor(string)
out Y:tensor(string)
10+ X = tensor(string)
StringSplit in X:T1
out Y:T2
out Z:T3
20+ T1 = tensor(string)
T2 = tensor(string)
T3 = tensor(int64)
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(string), 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(string), 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(double), 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
4+ T1 = tensor(double), tensor(float), tensor(int64), tensor(string)
T2 = tensor(double), tensor(float), tensor(int16), tensor(int64), tensor(string)
[2, 3] 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 weights:T
in bias:T
in mask_index:M
in past:T
in relative_position_bias:T
in past_sequence_length:M
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:F
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
in decoder_input_ids:I
in logits_processor: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(int16), tensor(int32), tensor(int8), tensor(uint16), 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)
GreedySearch in input_ids:I
in max_length:I
in min_length:I
in repetition_penalty:T
in vocab_mask:I
in prefix_vocab_mask:I
in attention_mask:I
out sequences:I
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)
MatMulBnb4 in A:T1
in B:T2
in absmax:T1
out Y:T1
1+ T1 = tensor(float)
T2 = tensor(uint8)
MatMulFpQ4 in A:T1
in B:T2
in B_shape:T3
out Y:T1
1+ T1 = tensor(float)
T2 = tensor(uint8)
T3 = tensor(int64)
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)
MatMulNBits in A:T1
in B:T2
in scales:T1
in zero_points:T2
out Y:T1
1+ T1 = tensor(float)
T2 = tensor(uint8)
MaxpoolWithMask in X:T
in M:tensor(int32)
out Y:T
1+ T = tensor(float)
MultiHeadAttention in query:T
in key:T
in value:T
in bias:T
in key_padding_mask:M
in relative_position_bias:T
in past_key:T
in past_value:T
out output:T
out present_key:T
out present_value:T
1+ T = 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)
QLinearSoftmax 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)
QLinearWhere in condition:B
in X:T
in x_scale:TF
in x_zero_point:T
in Y:T
in y_scale:TF
in y_zero_point:T
in z_scale:TF
in z_zero_point:T
out Z: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(int16), tensor(int8), tensor(uint16), tensor(uint8)
QuickGelu in X:T
out Y:T
1+ T = tensor(float)
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)
RotaryEmbedding in input:T
in position_ids:M
in cos_cache:T
in sin_cache:T
out output:T
1+ M = tensor(int64)
T = tensor(float)
SampleOp in X:T
out Y:T
1+ T = tensor(float)
Sampling in input_ids:I
in max_length:I
in min_length:I
in repetition_penalty:T
in vocab_mask:I
in prefix_vocab_mask:I
in attention_mask:I
in presence_mask:I
in seed:I
out sequences:I
out filtered_logits: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
out input_skip_bias_sum:T
1+ T = tensor(double), tensor(float)
SkipSimplifiedLayerNormalization in input:T
in skip:T
in gamma:T
in bias:T
out output:T
out mean:U
out inv_std_var:U
out input_skip_bias_sum:T
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)
WhisperBeamSearch in input_ids:F
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
in decoder_input_ids:I
in logits_processor:I
in cross_qk_layer_head:I
in extra_decoding_ids:I
out sequences:I
out sequences_scores:T
out scores:T
out cross_qk:V
out non_speech_probs:T
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)
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)
[1, 11] T = tensor(double), tensor(float), tensor(float16)
ArgMin in data:T
out reduced:tensor(int64)
[1, 11] 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
19+ T1 = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e5m2), 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(float8e4m3fn), tensor(float8e5m2), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
[13, 18] 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(float8e4m3fn), tensor(float8e5m2), 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(float8e4m3fn), tensor(float8e5m2), 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(float8e4m3fn), tensor(float8e5m2), 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)

or

in x:T1
in x_scale:T2
in x_zero_point:T1
out y:T2
19+ T1 = tensor(float8e4m3fn), tensor(float8e5m2), tensor(int8), tensor(uint8)
T2 = tensor(float), tensor(float16)
[13, 18] T = tensor(int8), tensor(uint8)
[10, 12] 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
19+ V = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), 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(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
[14, 18] 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
19+ B = tensor(bool)
V = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), 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(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
[13, 18] 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
17+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16)
U = tensor(float)
[1, 16] 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
19+ B = tensor(bool)
I = tensor(int64)
V = seq(tensor(bfloat16)), seq(tensor(bool)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), 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(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
[13, 18] 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(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), 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(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), 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(float8e4m3fn)), seq(tensor(float8e4m3fnuz)), seq(tensor(float8e5m2)), seq(tensor(float8e5m2fnuz)), 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(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), 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)
Mod in A:T
in B:T
out C:T
13+ T = tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
[10, 12] T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
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(bfloat16), 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
in axes:Tind
out output:T

or

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:T1
in y_zero_point:T2
out y:T2

or

in x:T1
in y_scale:tensor(float)
in y_zero_point:T2
out y:T2
19+ T1 = tensor(float), tensor(float16)
T2 = tensor(float8e4m3fn), tensor(float8e5m2), tensor(int8), tensor(uint8)
[13, 18] 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(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
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(double), tensor(float), tensor(float16), tensor(int32)
[1, 17] T = tensor(double), tensor(float), tensor(float16), tensor(int32)
ReduceL2 in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(double), tensor(float), tensor(float16), tensor(int32)
[1, 17] T = tensor(double), tensor(float), tensor(float16), tensor(int32)
ReduceLogSum in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(double), tensor(float), tensor(float16)
[1, 17] T = tensor(double), tensor(float), tensor(float16)
ReduceLogSumExp in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(double), tensor(float), tensor(float16)
[1, 17] T = tensor(double), tensor(float), tensor(float16)
ReduceMax in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
[1, 17] T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
ReduceMean in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(double), tensor(float), tensor(float16), tensor(int32)
[1, 17] T = tensor(double), tensor(float), tensor(float16), tensor(int32)
ReduceMin in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
[1, 17] T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(int8), tensor(uint8)
ReduceProd in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(double), tensor(float), tensor(float16), tensor(int32)
[1, 17] 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)
[1, 12] T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
ReduceSumSquare in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(double), tensor(float), tensor(float16)
[1, 17] 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
19+ T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
shape = tensor(int64)
[14, 18] 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
19+ V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
[16, 18] 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
19+ T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
T1 = tensor(int64)
[15, 18] 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)
Sign in input:T
out output: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)
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
18+ 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)
[13, 17] 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(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
10 I = tensor(int64)
T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
[1, 9] T = tensor(double), tensor(float), tensor(float16), tensor(int32), tensor(int64)
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(bfloat16), 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 weights:T
in bias:T
in mask_index:M
in past:T
in relative_position_bias:T
in past_sequence_length:M
out output:T
out present:T
1+ T = tensor(float), tensor(float16)
BeamSearch in input_ids:F
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
in decoder_input_ids:I
in logits_processor:I
out sequences:I
out sequences_scores:T
out scores:T
1+ T = tensor(float), tensor(float16)
BiasAdd in X:T
in bias:T
in skip:T
out Y: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)
BiasSplitGelu in X:T
in bias:T
out Y:T
1+ T = 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)
DecoderMaskedMultiHeadAttention in query:T
in key:T
in value:T
in mask_index:M
in relative_position_bias:T
in past_key:T
in past_value:T
in past_sequence_length:M
in beam_width:M
in cache_indirection:M
in bias:T
out output:T
out present_key:T
out present_value:T
out qk:V
1+ T = tensor(float), tensor(float16)
DecoderMaskedSelfAttention in input:T
in weights:T
in bias:T
in mask_index:M
in past:T
in relative_position_bias:T
in past_sequence_length:M
in beam_width:M
in cache_indirection:M
out output:T
out present: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)
DequantizeWithOrder in input:Q
in scale_input:S
out output:F
1+ F = tensor(float), tensor(float16)
Q = tensor(int8)
S = tensor(float)
DynamicTimeWarping in input:F
out output:I
1+ F = tensor(float)
I = tensor(int32)
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)
GatedRelativePositionBias in query_layer:T
in query_bias:T
in rel_pos:T
in weight:T
in bias:T
in eco_a:T
in token_offset:M
out output:T
1+ T = tensor(float), tensor(float16)
Gelu in X:T
out Y:T
1+ T = tensor(double), tensor(float), tensor(float16)
GemmFloat8 in A:TA
in B:TB
in C:TC
in scaleA:TS
in scaleB:TS
in scaleY:TS
out Y:TR
1+ TA = tensor(bfloat16), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e5m2)
TB = tensor(bfloat16), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e5m2)
TR = tensor(bfloat16), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e5m2)
TS = tensor(float)
GreedySearch in input_ids:I
in max_length:I
in min_length:I
in repetition_penalty:T
in vocab_mask:I
in prefix_vocab_mask:I
in attention_mask:I
out sequences:I
1+ T = tensor(float), tensor(float16)
GridSample in X:T1
in Grid:T1
out Y:T2
1+ T1 = tensor(float)
T2 = tensor(float)
GroupNorm in X:T
in gamma:M
in beta:M
out Y:T
1+ T = tensor(float), tensor(float16)
GroupQueryAttention in query:T
in key:T
in value:T
in past_key:T
in past_value:T
in seqlens_k:M
in total_sequence_length:M
in cos_cache:T
in sin_cache:T
out output:T
out present_key:T
out present_value:T
1+ M = tensor(int32)
T = tensor(bfloat16), tensor(float16)
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)
MatMulBnb4 in A:T1
in B:T2
in absmax:T1
out Y:T1
1+ T1 = tensor(bfloat16), tensor(float), tensor(float16)
T2 = tensor(uint8)
MatMulNBits in A:T1
in B:T2
in scales:T1
in zero_points:T2
out Y:T1
1+ T1 = tensor(float), tensor(float16)
T2 = tensor(uint8)
MoE in input:T
in router_probs:T
in fc1_experts_weights:T
in fc2_experts_weights:T
in fc1_experts_bias:T
in fc2_experts_bias:T
out output:T
1+ T = tensor(float), tensor(float16)
MultiHeadAttention in query:T
in key:T
in value:T
in bias:T
in key_padding_mask:M
in relative_position_bias:T
in past_key:T
in past_value:T
out output:T
out present_key:T
out present_value: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)
NhwcConv in X:T
in W:T
in B:T
out Y:T
1+ T = tensor(float), tensor(float16)
PackedAttention in input:T
in weights:T
in bias:T
in token_offset:M
in cumulative_sequence_length:M
in relative_position_bias:T
out output:T
1+ T = tensor(float), tensor(float16)
PackedMultiHeadAttention in query:T
in key:T
in value:T
in bias:T
in token_offset:M
in cumulative_sequence_length:M
in relative_position_bias:T
out output:T
1+ T = tensor(float), tensor(float16)
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)
QOrderedAttention in input:Q
in scale_input:S
in scale_Q_gemm:S
in scale_K_gemm:S
in scale_V_gemm:S
in Q_weight:Q
in K_weight:Q
in V_weight:Q
in scale_Q_weight:S
in scale_K_weight:S
in scale_V_weight:S
in Q_bias:S
in K_bias:S
in V_bias:S
in scale_QKT_gemm:S
in scale_QKT_softmax:S
in scale_values_gemm:S
in mask_index:G
in past:Q
in relative_position_bias:S
out output:Q
1+ G = tensor(int32)
Q = tensor(int8)
S = tensor(float)
QOrderedGelu in X:Q
in scale_X:S
in scale_Y:S
out Y:Q
1+ Q = tensor(int8)
S = tensor(float)
QOrderedLayerNormalization in X:Q
in scale_X:S
in scale:F
in B:F
in scale_Y:S
out Y:Q
1+ F = tensor(float), tensor(float16)
Q = tensor(int8)
S = tensor(float)
QOrderedLongformerAttention in input:Q
in scale_input:S
in weight:Q
in scale_weight:S
in bias:S
in scale_bias:S
in scale_qkv_gemm:S
in mask:F
in global_weight:Q
in scale_global_weight:S
in global_bias:S
in scale_global_gemm:S
in global:G
in scale_output:S
out output:Q
1+ F = tensor(float16)
G = tensor(int32)
Q = tensor(int8)
S = tensor(float)
QOrderedMatMul in A:Q
in scale_A:S
in B:Q
in scale_B:S
in scale_Y:S
in bias:S
in C:Q
in scale_C:S
out Y:Q
1+ Q = tensor(int8)
S = tensor(float)
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)
QuantizeWithOrder in input:F
in scale_input:S
out output:Q
1+ F = tensor(float), tensor(float16)
Q = tensor(int8)
S = tensor(float)
QuickGelu in X:T
out Y:T
1+ T = tensor(double), tensor(float), tensor(float16)
RelativePositionBias in bias_table:T
in query_length:U
in key_length:U
out output:T
1+ T = tensor(float), tensor(float16)
RemovePadding in input:T
in sequence_token_count:M
out output:T
out token_offset:M
out cumulated_seq_len:M
out max_seq_len:M
1+ T = tensor(float), tensor(float16)
RestorePadding in input:T
in token_offset:M
out output:T
1+ T = tensor(float), tensor(float16)
Rfft in X:T
out Y:T
1+ T = tensor(double), tensor(float), tensor(float16)
RotaryEmbedding in input:T
in position_ids:M
in cos_cache:T
in sin_cache:T
out output:T
1+ M = tensor(int64)
T = tensor(bfloat16), tensor(float), tensor(float16)
Sampling in input_ids:I
in max_length:I
in min_length:I
in repetition_penalty:T
in vocab_mask:I
in prefix_vocab_mask:I
in attention_mask:I
in presence_mask:I
in seed:I
out sequences:I
out filtered_logits:T
1+ T = tensor(float), tensor(float16)
SkipGroupNorm in X:T
in gamma:M
in beta:M
in skip:T
in bias:T
out Y:T
out S:T
1+ T = 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
out input_skip_bias_sum:T
1+ T = tensor(float), tensor(float16)
SkipSimplifiedLayerNormalization in input:T
in skip:T
in gamma:T
in bias:T
out output:T
out mean:U
out inv_std_var:U
out input_skip_bias_sum:T
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)
UnfoldTensor in input:T
out output:T
1+ T = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
WhisperBeamSearch in input_ids:F
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
in decoder_input_ids:I
in logits_processor:I
in cross_qk_layer_head:I
in extra_decoding_ids:I
out sequences:I
out sequences_scores:T
out scores:T
out cross_qk:V
out non_speech_probs:T
1+ T = tensor(float), tensor(float16)
Op Name Parameters OpSet Version Types Supported
Operator Domain: ai.onnx
Abs in X:T
out Y:T
13+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8)
6+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8)
Acos in input:T
out output:T
7+ T = tensor(float), tensor(float16)
Acosh in input:T
out output:T
9+ T = tensor(float), tensor(float16)
Add in A:T
in B:T
out C:T
14+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
13+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
7+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Affine in X:T
out Y:T
1+ T = tensor(float), tensor(float16)
And in A:T
in B:T
out C:T1
7+ T = tensor(bool)
ArgMax in data:T
out reduced:tensor(int64)
13+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
12+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
11+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
1+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
ArgMin in data:T
out reduced:tensor(int64)
13+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
12+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
11+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
1+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Asin in input:T
out output:T
7+ T = tensor(float), tensor(float16)
Asinh in input:T
out output:T
9+ T = tensor(float), tensor(float16)
Atan in input:T
out output:T
7+ T = tensor(float), tensor(float16)
Atanh in input:T
out output:T
9+ T = tensor(float), tensor(float16)
AveragePool in X:T
out Y:T
19+ T = tensor(float), tensor(float16)
11+ T = tensor(float), tensor(float16)
10+ T = tensor(float), tensor(float16)
7+ T = 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(float), tensor(float16)
14+ T = tensor(float), tensor(float16)
9+ T = tensor(float), tensor(float16)
7+ T = tensor(float), tensor(float16)
BitShift in X:T
in Y:T
out Z:T
11+ T = tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
BitwiseAnd in A:T
in B:T
out C:T
18+ T = tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
BitwiseNot in X:T
out Y:T
18+ T = tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
BitwiseOr in A:T
in B:T
out C:T
18+ T = tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
BitwiseXor in A:T
in B:T
out C:T
18+ T = 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(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
T2 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
9+ T1 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
T2 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
6+ T1 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
T2 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
CastLike in input:T1
in target_type:T2
out output:T2
15+ T1 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
T2 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Ceil in X:T
out Y:T
13+ T = tensor(float), tensor(float16)
6+ T = tensor(float), tensor(float16)
Celu in X:T
out Y:T
12+ T = 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(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
12+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
11+ T = tensor(float), tensor(float16)
6+ T = tensor(float), tensor(float16)
Concat in inputs:T
out concat_result:T
13+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
11+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
4+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
ConcatFromSequence in input_sequence:S
out concat_result:T
11+ T = 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(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
ConstantOfShape in input:T1
out output:T2
9+ T1 = tensor(int64)
T2 = tensor(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), tensor(float16)
1+ T = tensor(float), tensor(float16)
ConvInteger in x:T1
in w:T2
in x_zero_point:T1
in w_zero_point:T2
out y:T3
10+ T1 = tensor(int8), tensor(uint8)
T2 = tensor(int8), tensor(uint8)
T3 = tensor(int32)
ConvTranspose in X:T
in W:T
in B:T
out Y:T
11+ T = tensor(float), tensor(float16)
1+ T = tensor(float), tensor(float16)
Cos in input:T
out output:T
7+ T = tensor(float), tensor(float16)
Cosh in input:T
out output:T
9+ T = tensor(float), tensor(float16)
Crop in input:T
out output:T
1+ T = tensor(float), tensor(float16)
CumSum in x:T
in axis:T2
out y:T
14+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
11+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
DFT in input:T1
in dft_length:T2
in axis:tensor(int64)
out output:T1

or

in input:T1
in dft_length:T2
out output:T1
17+ T1 = tensor(float), tensor(float16)
T2 = tensor(int64)
DepthToSpace in input:T
out output:T
13+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
11+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
1+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
DequantizeLinear in x:T
in x_scale:tensor(float)
in x_zero_point:T
out y:tensor(float)

or

in x:T1
in x_scale:T2
in x_zero_point:T1
out y:T2
13+ T = tensor(int32), tensor(int8), tensor(uint8)
10+ T = tensor(int32), tensor(int8), tensor(uint8)
Div in A:T
in B:T
out C:T
14+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
13+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
7+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
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
7+ T = tensor(float), tensor(float16)
DynamicQuantizeLinear in x:T1
out y:T2
out y_scale:tensor(float)
out y_zero_point:T2
11+ T1 = tensor(float)
T2 = tensor(int8), tensor(uint8)
Einsum in Inputs:T
out Output:T
12+ T = tensor(float), tensor(float16)
Elu in X:T
out Y:T
6+ T = tensor(float), tensor(float16)
Equal in A:T
in B:T
out C:T1
13+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
T1 = tensor(bool)
11+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
T1 = tensor(bool)
7+ T = tensor(float), tensor(float16)
T1 = tensor(bool)
Erf in input:T
out output:T
13+ T = tensor(float), tensor(float16)
9+ T = tensor(float), tensor(float16)
Exp in input:T
out output:T
13+ T = tensor(float), tensor(float16)
6+ T = tensor(float), tensor(float16)
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(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
8+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
EyeLike in input:T1
out output:T2
9+ T1 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
T2 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Flatten in input:T
out output:T
13+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
11+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
9+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
1+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Floor in X:T
out Y:T
13+ T = tensor(float), tensor(float16)
6+ T = 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(float), tensor(float16)
7+ T = tensor(float), tensor(float16)
Gather in data:T
in indices:Tind
out output:T
13+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Tind = tensor(int32), tensor(int64)
11+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Tind = tensor(int32), tensor(int64)
1+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Tind = tensor(int32), tensor(int64)
GatherElements in data:T
in indices:Tind
out output:T
13+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Tind = tensor(int32), tensor(int64)
11+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Tind = tensor(int32), tensor(int64)
GatherND in data:T
in indices:tensor(int64)
out output:T
13+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
12+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
11+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Gemm in A:T
in B:T
in C:T
out Y:T
13+ T = tensor(float), tensor(float16)
11+ T = tensor(float), tensor(float16)
9+ T = tensor(float), tensor(float16)
7+ T = tensor(float), tensor(float16)
GlobalAveragePool in X:T
out Y:T
1+ T = tensor(float), tensor(float16)
GlobalLpPool in X:T
out Y:T
2+ T = tensor(float), tensor(float16)
GlobalMaxPool in X:T
out Y:T
1+ T = tensor(float), tensor(float16)
Greater in A:T
in B:T
out C:T1
13+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
T1 = tensor(bool)
9+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
T1 = tensor(bool)
7+ T = tensor(float), tensor(float16)
T1 = tensor(bool)
GreaterOrEqual in A:T
in B:T
out C:T1
16+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
T1 = tensor(bool)
12+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
T1 = tensor(bool)
GridSample in X:T1
in grid:T2
out Y:T1
16+ T1 = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
T2 = tensor(float), tensor(float16)
HardSigmoid in X:T
out Y:T
6+ T = tensor(float), tensor(float16)
Hardmax in input:T
out output:T
13+ T = tensor(float), tensor(float16)
11+ T = tensor(float), tensor(float16)
1+ T = tensor(float), tensor(float16)
Identity in input:T
out output:T

or

in input:V
out output:V
16+ V = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
14+ V = 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(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
1+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
If in cond:B
out outputs:V
19+ B = tensor(bool)
V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(float8e4m3fn), tensor(float8e4m3fnuz), tensor(float8e5m2), tensor(float8e5m2fnuz), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
16+ 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)
13+ 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)
11+ B = tensor(bool)
V = tensor(bfloat16), tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
7+ 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(float), tensor(float16)
InstanceNormalization in input:T
in scale:T
in B:T
out output:T
6+ T = tensor(float), tensor(float16)
IsInf in X:T1
out Y:T2
10+ T1 = tensor(float)
T2 = tensor(bool)
IsNaN in X:T1
out Y:T2
13+ T1 = tensor(float), tensor(float16)
T2 = tensor(bool)
9+ T1 = tensor(float), tensor(float16)
T2 = tensor(bool)
LRN in X:T
out Y:T
13+ T = tensor(float), tensor(float16)
1+ T = 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(float), tensor(float16)
7+ T = tensor(float), tensor(float16)
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
17+ T = tensor(float), tensor(float16)
U = tensor(float)
1+ T = tensor(float), tensor(float16)
V = tensor(float), tensor(float16)
LeakyRelu in X:T
out Y:T
16+ T = tensor(float), tensor(float16)
6+ T = tensor(float), tensor(float16)
Less in A:T
in B:T
out C:T1
13+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
T1 = tensor(bool)
9+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
T1 = tensor(bool)
7+ T = tensor(float), tensor(float16)
T1 = tensor(bool)
LessOrEqual in A:T
in B:T
out C:T1
16+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
T1 = tensor(bool)
12+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
T1 = tensor(bool)
Log in input:T
out output:T
13+ T = tensor(float), tensor(float16)
6+ T = tensor(float), tensor(float16)
LogSoftmax in input:T
out output:T
13+ T = tensor(float), tensor(float16)
11+ T = tensor(float), tensor(float16)
1+ T = tensor(float), tensor(float16)
LpNormalization in input:T
out output:T
1+ T = tensor(float), tensor(float16)
LpPool in X:T
out Y:T
18+ T = tensor(float), tensor(float16)
11+ T = tensor(float), tensor(float16)
2+ T = tensor(float), tensor(float16)
MatMul in A:T
in B:T
out Y:T
13+ T = tensor(float), tensor(float16)
9+ T = tensor(float), tensor(float16)
1+ T = 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), tensor(uint8)
T2 = tensor(int8), tensor(uint8)
T3 = tensor(int32)
Max in data_0:T
out max:T
13+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
12+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
8+ T = tensor(float), tensor(float16)
6+ T = 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(float), tensor(float16), tensor(int8), tensor(uint8)
11+ I = tensor(int64)
T = tensor(float), tensor(float16), tensor(int8), tensor(uint8)
10+ I = tensor(int64)
T = tensor(float), tensor(float16), tensor(int8), tensor(uint8)
8+ I = tensor(int64)
T = tensor(float), tensor(float16), tensor(int8), tensor(uint8)
1+ T = tensor(float), tensor(float16)
MaxRoiPool in X:T
in rois:T
out Y:T
1+ T = tensor(float), tensor(float16)
MaxUnpool in X:T1
in I:T2
in output_shape:T2
out output:T1
11+ T1 = tensor(float), tensor(float16)
T2 = tensor(int64)
9+ T1 = tensor(float), tensor(float16)
T2 = tensor(int64)
Mean in data_0:T
out mean:T
13+ T = tensor(float), tensor(float16)
8+ T = tensor(float), tensor(float16)
6+ T = tensor(float), tensor(float16)
MeanVarianceNormalization in X:T
out Y:T

or

in input:T
out output:T
13+ T = tensor(float), tensor(float16)
9+ T = tensor(float), tensor(float16)
1+ T = tensor(float), tensor(float16)
MemcpyFromHost in X:T
out Y:T
1+ T = 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(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(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(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(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
12+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
8+ T = tensor(float), tensor(float16)
6+ T = tensor(float), tensor(float16)
Mod in A:T
in B:T
out C:T
13+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint8)
10+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint8)
Mul in A:T
in B:T
out C:T
14+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
13+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
7+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Neg in X:T
out Y:T
13+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8)
6+ T = 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(int16), tensor(int32), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint8)
9+ T = tensor(bool), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int8), tensor(uint16), tensor(uint32), 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), tensor(uint32), tensor(uint64)
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)
T3 = 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+ T1 = tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
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)
T3 = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
OptionalGetElement in input:O
out output:V
18+ 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)), 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)
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)
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
18+ 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)), 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)
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)
PRelu in X:T
in slope:T
out Y:T
16+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int8)
9+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int8)
7+ T = tensor(float), tensor(float16)
Pad in data:T
in pads:tensor(int64)
in constant_value:T
in axes:Tind
out output:T

or

in data:T
in pads:tensor(int64)
in constant_value:T
out output:T

or

in data:T
out output:T
18+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
13+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
11+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
2+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
ParametricSoftplus in X:T
out Y:T
1+ T = 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(float), tensor(float16), tensor(int32)
T1 = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint8)
13+ T = tensor(float), tensor(float16), tensor(int32)
T1 = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint8)
12+ T = tensor(float), tensor(float16), tensor(int32)
T1 = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint8)
7+ T = tensor(float), tensor(float16)
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:T1
in y_zero_point:T2
out y:T2

or

in x:T1
in y_scale:tensor(float)
in y_zero_point:T2
out y:T2
13+ T1 = tensor(float), tensor(int32)
T2 = tensor(int8), tensor(uint8)
10+ T1 = tensor(float), tensor(int32)
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), tensor(float16)
7+ T = tensor(float), tensor(float16)
Range in start:T
in limit:T
in delta:T
out output:T
11+ T = tensor(float), tensor(int16), tensor(int32), tensor(int64)
Reciprocal in X:T
out Y:T
13+ T = tensor(float), tensor(float16)
6+ T = tensor(float), tensor(float16)
ReduceL1 in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
13+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
11+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
1+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
ReduceL2 in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
13+ T = tensor(float), tensor(float16)
11+ T = tensor(float), tensor(float16)
1+ T = tensor(float), tensor(float16)
ReduceLogSum in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
13+ T = tensor(float), tensor(float16)
11+ T = tensor(float), tensor(float16)
1+ T = tensor(float), tensor(float16)
ReduceLogSumExp in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
13+ T = tensor(float), tensor(float16)
11+ T = tensor(float), tensor(float16)
1+ T = tensor(float), tensor(float16)
ReduceMax in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
13+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
12+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
11+ T = tensor(float), tensor(float16)
1+ T = tensor(float), tensor(float16)
ReduceMean in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
13+ T = tensor(float), tensor(float16)
11+ T = tensor(float), tensor(float16)
1+ T = tensor(float), tensor(float16)
ReduceMin in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
13+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
12+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
11+ T = tensor(float), tensor(float16)
1+ T = tensor(float), tensor(float16)
ReduceProd in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
13+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
11+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
1+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
ReduceSum in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
13+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
11+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
1+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
ReduceSumSquare in data:T
in axes:tensor(int64)
out reduced:T

or

in data:T
out reduced:T
18+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
13+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
11+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
1+ T = tensor(float), tensor(float16), tensor(int32), tensor(int64), tensor(uint32), tensor(uint64)
Relu in X:T
out Y:T
14+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int8)
13+ T = tensor(float), tensor(float16)
6+ T = 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(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(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
5+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
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(float16), tensor(int8), tensor(uint8)
T2 = tensor(float), tensor(float16)
11+ T1 = tensor(float), tensor(float16), tensor(int8), tensor(uint8)
T2 = tensor(float), tensor(float16)
10+ T = tensor(float), tensor(float16)
ReverseSequence in input:T
in sequence_lens:tensor(int64)
out Y:T
10+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
RoiAlign in X:T1
in rois:T1
in batch_indices:T2
out Y:T1
16+ T1 = tensor(float), tensor(float16)
T2 = tensor(int32), tensor(int64)
10+ T1 = tensor(float), tensor(float16)
T2 = tensor(int32), tensor(int64)
Round in X:T
out Y:T
11+ T = 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(float), tensor(float16)
T2 = tensor(int32), tensor(int64)
ScaledTanh in input:T
out output:T
1+ T = tensor(float), tensor(float16)
Scatter in data:T
in indices:Tind
in updates:T
out output:T
13+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Tind = tensor(int32), tensor(int64)
11+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Tind = tensor(int32), tensor(int64)
9+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Tind = tensor(int32), tensor(int64)
ScatterElements in data:T
in indices:Tind
in updates:T
out output:T
16+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Tind = tensor(int32), tensor(int64)
13+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Tind = tensor(int32), tensor(int64)
11+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Tind = tensor(int32), tensor(int64)
ScatterND in data:T
in indices:tensor(int64)
in updates:T
out output:T
16+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
13+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
11+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Selu in X:T
out Y:T
6+ T = 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 = 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(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+ T = 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(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+ T = 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(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(float), tensor(float16), tensor(int16), tensor(int32), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint8)
Sigmoid in X:T
out Y:T
13+ T = tensor(float), tensor(float16)
6+ T = tensor(float), tensor(float16)
Sign in input:T
out output:T
13+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
9+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Sin in input:T
out output:T
7+ T = tensor(float), tensor(float16)
Sinh in input:T
out output:T
9+ T = tensor(float), tensor(float16)
Size in data:T
out size:T1
13+ T = 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(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+ T = 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(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)
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(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+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Tind = tensor(int32), tensor(int64)
10+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Tind = tensor(int32), tensor(int64)
1+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Softmax in input:T
out output:T
13+ T = tensor(float), tensor(float16)
11+ T = tensor(float), tensor(float16)
1+ T = tensor(float), tensor(float16)
Softplus in X:T
out Y:T
1+ T = tensor(float), tensor(float16)
Softsign in input:T
out output:T
1+ T = tensor(float), tensor(float16)
SpaceToDepth in input:T
out output:T
13+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
1+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
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
18+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
13+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
11+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
2+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Sqrt in X:T
out Y:T
13+ T = tensor(float), tensor(float16)
6+ T = 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(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
11+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
1+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Sub in A:T
in B:T
out C:T
14+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
13+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
7+ T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Sum in data_0:T
out sum:T
13+ T = tensor(float), tensor(float16)
8+ T = tensor(float), tensor(float16)
6+ T = tensor(float), tensor(float16)
Tan in input:T
out output:T
7+ T = tensor(float), tensor(float16)
Tanh in input:T
out output:T
13+ T = tensor(float), tensor(float16)
6+ T = tensor(float), tensor(float16)
ThresholdedRelu in X:T
out Y:T
10+ T = tensor(float), tensor(float16)
1+ T = 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(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
6+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
TopK in X:T
in K:tensor(int64)
out Values:T
out Indices:I

or

in X:T
out Values:T
out Indices:I
11+ I = tensor(int64)
T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
10+ I = tensor(int64)
T = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
1+ I = tensor(int64)
T = 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(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
1+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Trilu in input:T
in k:tensor(int64)
out output:T
14+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Unsqueeze in data:T
in axes:tensor(int64)
out expanded:T

or

in data:T
out expanded:T
13+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
11+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
1+ T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Upsample in X:T
in scales:tensor(float)
out Y:T

or

in X:T
out Y:T
10+ T = tensor(float), tensor(float16)
9+ T = tensor(float), tensor(float16)
7+ T = tensor(float), tensor(float16)
Where in condition:B
in X:T
in Y:T
out output:T
16+ B = tensor(bool)
T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
9+ B = tensor(bool)
T = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)
Xor in A:T
in B:T
out C:T1
7+ T = tensor(bool)
Operator Domain: com.microsoft
Attention in input:T
in weights:T
in bias:T
in mask_index:M
in past:T
in relative_position_bias:T
in past_sequence_length:M
out output:T
out present:T
1+ M = tensor(int32)
T = tensor(float), tensor(float16)
BiasAdd in X:T
in bias:T
in skip:T
out Y:T
1+ T = tensor(float), tensor(float16)
BiasGelu in A:T
in B:T
out C:T
1+ T = tensor(float), tensor(float16)
BiasSplitGelu in X:T
in bias:T
out Y: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), tensor(float16)
DequantizeLinear in x:T1
in x_scale:T2
in x_zero_point:T1
out y:T2
1+ T1 = tensor(int32), tensor(int8), tensor(uint8)
T2 = tensor(float), 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)
FusedMatMul in A:T
in B:T
out Y:T
1+ T = tensor(float), tensor(float16)
FusedMatMulActivation in A:T
in B:T
out Y:T
1+ T = tensor(float), tensor(float16)
Gelu in X:T
out Y:T
1+ T = tensor(float), tensor(float16)
GroupNorm in X:T
in gamma:M
in beta:M
out Y:T
1+ M = tensor(float), tensor(float16)
T = tensor(float), tensor(float16)
MultiHeadAttention in query:T
in key:T
in value:T
in bias:T
in key_padding_mask:M
in relative_position_bias:T
in past_key:T
in past_value:T
out output:T
out present_key:T
out present_value:T
1+ M = tensor(int32)
T = tensor(float), tensor(float16)
NhwcConv in X:T
in W:T
in B:T
out Y:T
1+ T = tensor(float), tensor(float16)
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)
QLinearAveragePool 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)
QLinearConcat in Y_scale:TF
in Y_zero_point:T8
in inputs:TV
out Y:T8
1+ T8 = tensor(int8), tensor(uint8)
TF = tensor(float)
TV = tensor(float), tensor(int8), tensor(uint8)
QLinearGlobalAveragePool 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)
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), tensor(float16), tensor(int32)
T2 = tensor(int8), tensor(uint8)
QuickGelu in X:T
out Y:T
1+ T = tensor(float), tensor(float16)
RotaryEmbedding in input:T
in position_ids:M
in cos_cache:T
in sin_cache:T
out output:T
1+ M = tensor(int64)
T = 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
out input_skip_bias_sum:T
1+ T = tensor(float), tensor(float16)
Operator Domain: com.microsoft.dml
DmlFusedAdd in A:T
in B:T
out C:T
1+ T = tensor(float), tensor(float16)
DmlFusedBatchNormalization 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
1+ T = tensor(float), tensor(float16)
DmlFusedConv in X:T
in W:T
in B:T
out Y:T
1+ T = tensor(float), tensor(float16)
DmlFusedConvTranspose in X:T
in W:T
in B:T
out Y:T
1+ T = tensor(float), tensor(float16)
DmlFusedGemm in A:T
in B:T
in C:T
out Y:T
1+ T = tensor(float), tensor(float16)
DmlFusedInstanceNormalization in input:T
in scale:T
in B:T
out output:T
1+ T = tensor(float), tensor(float16)
DmlFusedMatMul in A:T
in B:T
out Y:T
1+ T = tensor(float), tensor(float16)
DmlFusedMeanVarianceNormalization in input:T
out output:T
1+ T = tensor(float), tensor(float16)
DmlFusedSum in data_0:T
out sum:T
1+ T = tensor(float), tensor(float16)