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Op Name | Parameters | OpSet Version | Types Supported |
---|---|---|---|
Operator Domain: ai.onnx.ml | |||
Abs | (in X:T, out Y:T) | 6+ | T = tensor(int32), tensor(int16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(int64), tensor(double) |
Acos | (in input:T, out output:T) | 7+ | T = tensor(float) |
Acosh | (in input:T, out output:T) | 9+ | T = tensor(float) |
Add | (in A:T, in B:T, out C:T) | 7+ | T = tensor(int32), tensor(float), tensor(int64), tensor(double) |
Affine | (in X:T, out Y:T) | 1+ | T = tensor(float) |
And | (in A:T, in B:T, out C:T1) | 7+ | T = tensor(bool) |
T1 = tensor(bool) | |||
ArgMax | (in data:T, out reduced:tensor(int64)) | 1+ | T = tensor(int32), tensor(float) |
ArgMin | (in data:T, out reduced:tensor(int64)) | 1+ | T = tensor(int32), tensor(float) |
ArrayFeatureExtractor | (in X:T, in Y:tensor(int64), out Z:T) | 1+ | T = tensor(string), tensor(int32), tensor(float), tensor(int64), tensor(double) |
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) | 10+ | T = tensor(float) |
[7, 9] | T = tensor(float) | ||
BatchNormalization | (in X:T, in scale:T, in B:T, in mean:T, in var:T, out Y:T, out mean:T, out var:T, out saved_mean:T, out saved_var:T) | [7, 9] | B = tensor(float) |
X = tensor(float) | |||
mean = tensor(float) | |||
scale = tensor(float) | |||
var = tensor(float) | |||
Binarizer | (in X:T, out Y:T) | 1+ | T = tensor(float) |
Cast | (in input:T1, out output:T2) | 9+ | T1 = tensor(string) |
T2 = tensor(int32), tensor(bool), tensor(int16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) | |||
[6, 9] | T1 = tensor(int32), tensor(bool), tensor(int16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) | ||
T2 = tensor(int32), tensor(bool), tensor(int16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) | |||
CastMap | (in X:T1, out Y:T2) | 1+ | T1 = unknown |
T2 = tensor(string), tensor(float), tensor(int64) | |||
CategoryMapper | (in X:T1, out Y:T2) | 1+ | T1 = tensor(string), tensor(int64) |
T2 = tensor(string), tensor(int64) | |||
Ceil | (in X:T, out Y:T) | 6+ | T = tensor(float) |
Clip | (in input:T, out output:T) | 6+ | T = tensor(float) |
Compress | (in input:T, in condition:T1, out output:T) | 9+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
T1 = tensor(bool) | |||
Concat | (in inputs:T, out concat_result:T) | 4+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
ConstantOfShape | (in input:T1, out output:T2) | 9+ | T1 = tensor(int64) |
T2 = tensor(int32), tensor(bool), tensor(int16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) | |||
Conv | (in X:T, in W:T, in B:T, out Y:T) | 1+ | 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) | 1+ | 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) |
DepthToSpace | (in input:T, out output:T) | [1, 4] | T = tensor(float) |
DequantizeLinear | (in x:T, in x_scale:tensor(float), in x_zero_point:T, out y:tensor(float)) | 10+ | x = tensor(uint8), unknown |
x_scale = tensor(float) | |||
x_zero_point = tensor(uint8), unknown | |||
y = tensor(float) | |||
DictVectorizer | (in X:T1, out Y:T2) | 1+ | T1 = unknown |
T2 = tensor(string), tensor(float), tensor(int64), tensor(double) | |||
Div | (in A:T, in B:T, out C:T) | 7+ | T = tensor(int32), tensor(float), tensor(int64), tensor(double) |
Dropout | (in data:T, out output:T, out mask:T) or (in data:T, out output:T, out mask:T1) | 10+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
T1 = tensor(bool) | |||
[7, 9] | T = tensor(float), tensor(MLFloat16), tensor(double) | ||
T1 = tensor(bool) | |||
DynamicSlice | (in data:T, in starts:Tind, in ends:Tind, in axes:Tind, out output:T) | 1+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Tind = tensor(int32), tensor(int64) | |||
Elu | (in X:T, out Y:T) | 6+ | T = tensor(float) |
Equal | (in A:T, in B:T, out C:T1) | 11+ | T = tensor(float) |
T1 = tensor(bool) | |||
7+ | T = tensor(int32), tensor(bool), tensor(int64) | ||
T1 = tensor(bool) | |||
Erf | (in input:T, out output:T) | 9+ | T = tensor(float) |
Exp | (in input:T, out output:T) | 6+ | T = tensor(float), tensor(double) |
Expand | (in input:T, in shape:tensor(int64), out output:T) | 8+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
EyeLike | (in input:T1, out output:T2) | 9+ | T1 = tensor(uint64), tensor(int32), tensor(float), tensor(int64), tensor(double) |
T2 = tensor(uint64), tensor(int32), tensor(float), tensor(int64), tensor(double) | |||
FeatureVectorizer | (in X:T1, out Y:tensor(float)) | 1+ | T1 = tensor(int32), tensor(float), tensor(int64), tensor(double) |
Flatten | (in input:T, out output:T) | 9+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
[1, 8] | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) | ||
Floor | (in X:T, out Y:T) | 6+ | T = tensor(float) |
GRU | (in X:T, in W:T, in R:T, in B:T, in sequence_lens:T1, in initial_h:T, out Y:T, out Y_h:T) | 7+ | T = tensor(float), tensor(double) |
T1 = tensor(int32) | |||
Gather | (in data:T, in indices:Tind, out output:T) | 1+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Tind = tensor(int32), tensor(int64) | |||
Gemm | (in A:T, in B:T, in C:T, out Y:T) | [7, 9] | T = tensor(float) |
GlobalAveragePool | (in X:T, out Y:T) | 1+ | T = tensor(float) |
GlobalLpPool | (in X:T, out Y:T) | 2+ | T = tensor(float) |
GlobalMaxPool | (in X:T, out Y:T) | 1+ | T = tensor(float) |
Greater | (in A:T, in B:T, out C:T1) | 9+ | T = tensor(int32), tensor(int64) |
T1 = tensor(bool) | |||
[7, 9] | T = tensor(float) | ||
T1 = tensor(bool) | |||
HardSigmoid | (in X:T, out Y:T) | 6+ | T = tensor(float) |
Hardmax | (in input:T, out output:T) | 1+ | T = tensor(float) |
Identity | (in input:T, out output:T) | 1+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
If | (in cond:B, out outputs:V) | 1+ | B = tensor(bool) |
V = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) | |||
ImageScaler | (in input:T, out output:T) | 1+ | T = tensor(float) |
Imputer | (in X:T, out Y:T) | 1+ | T = tensor(float), tensor(int64) |
InstanceNormalization | (in input:T, in scale:T, in B:T, out output:T) | 6+ | T = tensor(float) |
IsInf | (in X:T1, out Y:T2) | 10+ | T1 = tensor(float), tensor(double) |
T2 = tensor(bool) | |||
IsNaN | (in X:T1, out Y:T2) | 9+ | T1 = tensor(float), tensor(MLFloat16) |
T2 = tensor(bool) | |||
LRN | (in X:T, out Y:T) | 1+ | T = tensor(float) |
LSTM | (in X:T, in W:T, in R:T, in B:T, in sequence_lens:T1, in initial_h:T, in initial_c:T, in P:T, out Y:T, out Y_h:T, out Y_c:T) | 7+ | T = tensor(float), tensor(double) |
T1 = tensor(int32) | |||
LabelEncoder | (in X:T1, out Y:T2) | 2+ | T1 = tensor(string), tensor(float), tensor(int64) |
T2 = tensor(string), tensor(float), tensor(int64) | |||
[1, 1] | T1 = tensor(string), tensor(int64) | ||
T2 = tensor(string), tensor(int64) | |||
LeakyRelu | (in X:T, out Y:T) | 6+ | T = tensor(float) |
Less | (in A:T, in B:T, out C:T1) | 9+ | T = tensor(int32), tensor(int64) |
T1 = tensor(bool) | |||
[7, 9] | T = tensor(float) | ||
T1 = tensor(bool) | |||
LinearClassifier | (in X:T1, out Y:T2, out Z:tensor(float)) | 1+ | T1 = tensor(int32), tensor(float), tensor(int64), tensor(double) |
T2 = tensor(string), tensor(int64) | |||
LinearRegressor | (in X:T, out Y:tensor(float)) | 1+ | T = tensor(float) |
Log | (in input:T, out output:T) | 6+ | T = tensor(float) |
LogSoftmax | (in input:T, out output:T) | 1+ | T = tensor(float) |
Loop | (in M:I, in cond:B, in v_initial:V, out v_final_and_scan_outputs:V) | 1+ | B = tensor(bool) |
I = tensor(int64) | |||
V = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) | |||
LpNormalization | (in input:T, out output:T) | 1+ | T = tensor(float) |
LpPool | (in X:T, out Y:T) | 2+ | T = tensor(float) |
MatMul | (in A:T, in B:T, out Y:T) | [1, 9] | T = tensor(float), tensor(double) |
[9, 9] | T = tensor(uint64), tensor(int32), tensor(int64), tensor(uint32) | ||
MatMulInteger | (in A:T1, in B:T2, in a_zero_point:T1, in b_zero_point:T2, out Y:T3) | 10+ | T1 = tensor(uint8) |
T2 = tensor(uint8) | |||
T3 = tensor(int32) | |||
Max | (in data_0:T, out max:T) | 8+ | T = tensor(float), tensor(double) |
[6, 7] | T = tensor(float) | ||
MaxPool | (in X:T, out Y:T) or (in X:T, out Y:T, out Indices:I) | 10+ | I = tensor(int64) |
T = tensor(float) | |||
[1, 7] | T = tensor(float) | ||
[8, 9] | I = tensor(int64) | ||
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) | 9+ | T1 = tensor(float) |
T2 = tensor(int64) | |||
Mean | (in data_0:T, out mean:T) | 8+ | T = tensor(float) |
[6, 7] | T = tensor(float) | ||
MeanVarianceNormalization | (in X:T, out Y:T) or (in input:T, out output:T) | 9+ | T = tensor(float) |
[1, 8] | T = tensor(float) | ||
Min | (in data_0:T, out min:T) | 8+ | T = tensor(float) |
[6, 7] | T = tensor(float) | ||
Mod | (in A:T, in B:T, out C:T) | 10+ | T = tensor(int32), tensor(int16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Mul | (in A:T, in B:T, out C:T) | 7+ | T = tensor(int32), tensor(float), tensor(int64), tensor(double) |
Multinomial | (in input:T1, out output:T2) | 7+ | T1 = tensor(float) |
T2 = tensor(int32), tensor(int64) | |||
Neg | (in X:T, out Y:T) | 6+ | T = tensor(int32), tensor(float), unknown |
NonZero | (in X:T, out Y:tensor(int64)) | 9+ | T = tensor(int32), tensor(float), tensor(bool), tensor(int64) |
Normalizer | (in X:T, out Y:tensor(float)) | 1+ | T = tensor(int32), tensor(float), tensor(int64), tensor(double) |
Not | (in X:T, out Y:T) | 1+ | T = tensor(bool) |
T1 = tensor(bool) | |||
OneHot | (in indices:T1, in depth:T2, in values:T3, out output:T3) | 9+ | T1 = tensor(int32), tensor(float), tensor(int64) |
T2 = tensor(int32), tensor(float), tensor(int64) | |||
T3 = tensor(string), tensor(int32), tensor(float), tensor(int64) | |||
OneHotEncoder | (in X:T, out Y:tensor(float)) | 1+ | T = tensor(string), tensor(float), tensor(int64), tensor(double) |
Or | (in A:T, in B:T, out C:T1) | 7+ | T = tensor(bool) |
T1 = tensor(bool) | |||
PRelu | (in X:T, in slope:T, out Y:T) | [7, 9] | T = tensor(float) |
Pad | (in data:T, out output:T) | 2+ | T = tensor(float) |
ParametricSoftplus | (in X:T, out Y:T) | 1+ | T = tensor(float) |
Pow | (in X:T, in Y:T, out Z:T) | 7+ | T = tensor(float), tensor(double) |
QLinearConv | (in x:T1, in x_scale:tensor(float), in x_zero_point:T1, in w:T2, in w_scale:tensor(float), in w_zero_point:T2, in y_scale:tensor(float), in y_zero_point:T3, in B:T4, out y:T3) | 10+ | T1 = tensor(uint8) |
T2 = tensor(uint8) | |||
T3 = tensor(uint8) | |||
T4 = tensor(int32) | |||
QLinearMatMul | (in a:T1, in a_scale:tensor(float), in a_zero_point:T1, in b:T2, in b_scale:tensor(float), in b_zero_point:T2, in y_scale:tensor(float), in y_zero_point:T3, out y:T3) | 10+ | T1 = tensor(uint8) |
T2 = tensor(uint8) | |||
T3 = tensor(uint8) | |||
QuantizeLinear | (in x:T1, in y_scale:tensor(float), in y_zero_point:T2, out y:T2) | 10+ | x = tensor(float) |
y = tensor(uint8), unknown | |||
y_zero_point = tensor(uint8), unknown | |||
RNN | (in X:T, in W:T, in R:T, in B:T, in sequence_lens:T1, in initial_h:T, out Y:T, out Y_h:T) | 7+ | T = tensor(float) |
T1 = tensor(int32) | |||
RandomNormal | (out output:T) | 1+ | T = tensor(float), tensor(double) |
RandomNormalLike | (in input:T1, out output:T2) | 1+ | T1 = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
T2 = tensor(float), tensor(double) | |||
RandomUniform | (out output:T) | 1+ | T = tensor(float), tensor(double) |
RandomUniformLike | (in input:T1, out output:T2) | 1+ | T1 = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
T2 = tensor(float), tensor(double) | |||
Reciprocal | (in X:T, out Y:T) | 6+ | T = tensor(float) |
ReduceL1 | (in data:T, out reduced:T) | 1+ | T = tensor(int32), tensor(float) |
ReduceL2 | (in data:T, out reduced:T) | 1+ | T = tensor(int32), tensor(float) |
ReduceLogSum | (in data:T, out reduced:T) | 1+ | T = tensor(int32), tensor(float) |
ReduceLogSumExp | (in data:T, out reduced:T) | 1+ | T = tensor(int32), tensor(float) |
ReduceMax | (in data:T, out reduced:T) | 1+ | T = tensor(int32), tensor(float) |
ReduceMean | (in data:T, out reduced:T) | 1+ | T = tensor(int32), tensor(float) |
ReduceMin | (in data:T, out reduced:T) | 1+ | T = tensor(int32), tensor(float) |
ReduceProd | (in data:T, out reduced:T) | 1+ | T = tensor(int32), tensor(float) |
ReduceSum | (in data:T, out reduced:T) | 1+ | T = tensor(int32), tensor(float), tensor(double) |
ReduceSumSquare | (in data:T, out reduced:T) | 1+ | T = tensor(int32), tensor(float), tensor(double) |
Relu | (in X:T, out Y:T) | 6+ | T = tensor(float) |
Reshape | (in data:T, in shape:tensor(int64), out reshaped:T) or (in data:T, out reshaped:T) | 5+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
shape = tensor(int64) | |||
Reshape_1 | [1, 4] | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) | |
Resize | (in X:T, in scales:tensor(float), out Y:T) | 10+ | T = tensor(int32), tensor(float), tensor(uint8) |
ReverseSequence | (in input:T, in sequence_lens:tensor(int64), out Y:T) | 10+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
RoiAlign | (in X:T1, in rois:T1, in batch_indices:T2, out Y:T1) | 10+ | T = tensor(float), tensor(double) |
T2 = tensor(int64) | |||
SVMClassifier | (in X:T1, out Y:T2, out Z:tensor(float)) | 1+ | T1 = tensor(int32), tensor(float), tensor(int64), tensor(double) |
T2 = tensor(string), tensor(int64) | |||
SVMRegressor | (in X:T, out Y:tensor(float)) | 1+ | T = tensor(float) |
Scale | (in input:T, out output:T) | 1+ | T = tensor(float) |
ScaledTanh | (in input:T, out output:T) | 1+ | T = tensor(float) |
Scaler | (in X:T, out Y:tensor(float)) | 1+ | T = tensor(int32), tensor(float), tensor(int64), tensor(double) |
Scan | (in sequence_lens:I, in initial_state_and_scan_inputs:V, out final_state_and_scan_outputs:V) or (in initial_state_and_scan_inputs:V, out final_state_and_scan_outputs:V) | 9+ | I = tensor(int64) |
V = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) | |||
[8, 8] | I = tensor(int64) | ||
V = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) | |||
Scatter | (in data:T, in indices:Tind, in updates:T, out output:T) | 9+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Tind = tensor(int32), tensor(int64) | |||
Selu | (in X:T, out Y:T) | 6+ | T = tensor(float) |
Shape | (in data:T, out shape:T1) | 1+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
T1 = tensor(int64) | |||
Shrink | (in input:T, out output:T) | 9+ | T = tensor(int32), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Sigmoid | (in X:T, out Y:T) | 6+ | T = tensor(float) |
Sign | (in input:T, out output:T) | 9+ | T = tensor(int32), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Sin | (in input:T, out output:T) | 7+ | T = tensor(float), tensor(double) |
Sinh | (in input:T, out output:T) | 9+ | T = tensor(float) |
Size | (in data:T, out size:T1) | 1+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(int64), tensor(double) |
T1 = tensor(int64) | |||
Slice | (in data:T, out output:T) or (in data:T, in starts:Tind, in ends:Tind, in axes:Tind, in steps:Tind, out output:T) | 10+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Tind = tensor(int32), tensor(int64) | |||
[1, 9] | T = tensor(int32), tensor(bool), tensor(int16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) | ||
Softmax | (in input:T, out output:T) | 1+ | T = tensor(float) |
Softplus | (in X:T, out Y:T) | 1+ | T = tensor(float) |
Softsign | (in input:T, out output:T) | 1+ | T = tensor(float) |
SpaceToDepth | (in input:T, out output:T) | 1+ | T = tensor(float) |
Split | (in input:T, out outputs:T) or (in input:T, in split:T, out outputs...:T) | 2+ | T = tensor(string), tensor(int32), tensor(float) |
Sqrt | (in X:T, out Y:T) | 6+ | T = tensor(float), tensor(double) |
Squeeze | (in data:T, out squeezed:T) | 1+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
StringNormalizer | (in X:tensor(string), out Y:tensor(string)) | 10+ | T = tensor(string) |
Sub | (in A:T, in B:T, out C:T) | 7+ | T = tensor(int32), tensor(float), tensor(int64), tensor(double) |
Sum | (in data_0:T, out sum:T) | 8+ | T = tensor(float) |
[6, 7] | T = tensor(float) | ||
Tan | (in input:T, out output:T) | 7+ | T = tensor(float) |
Tanh | (in input:T, out output:T) | 6+ | T = tensor(float) |
TfIdfVectorizer | (in X:T, out Y:T1) | 9+ | T = tensor(string), tensor(int32), tensor(int64) |
T1 = tensor(float) | |||
ThresholdedRelu | (in X:T, out Y:T) | 1+ | T = tensor(float) |
10+ | T = tensor(float) | ||
Tile | (in input:T, in tiles:T, in axis:T, out output:T) or (in input:T, in repeats:T1, out output:T) | 6+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(int64), tensor(double) |
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) | 10+ | I = tensor(int64) |
T = tensor(float) | |||
[1, 9] | I = tensor(int64) | ||
T = tensor(float) | |||
Transpose | (in data:T, out transposed:T) | 1+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
TreeEnsembleClassifier | (in X:T1, out Y:T2, out Z:tensor(float)) | 1+ | T1 = tensor(int32), tensor(float), tensor(int64), tensor(double) |
T2 = tensor(string), tensor(int64) | |||
TreeEnsembleRegressor | (in X:T, out Y:tensor(float)) | 1+ | T = tensor(float) |
Unsqueeze | (in data:T, out expanded:T) | 1+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Upsample | (in X:T, out Y:T) or (in X:T, in scales:tensor(float), out Y:T) | [7, 9] | T = tensor(int32), tensor(float), tensor(uint8) |
Where | (in condition:B, in X:T, in Y:T, out output:T) | 9+ | T = tensor(string), tensor(int32), tensor(float) |
Xor | (in A:T, in B:T, out C:T1) | 7+ | T = tensor(bool) |
T1 = tensor(bool) | |||
ZipMap | (in X:tensor(float), out Z:T) | 1+ | T = unknown |
Operator Domain: com.microsoft | |||
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(float), tensor(double) |
T1 = tensor(int32) | |||
ConvTransposeWithDynamicPads | (in X:T, in W:T, in Pads:tensor(int64), in B:T, out Y:T) | 1+ | T = tensor(float) |
CropAndResize | (in X:T1, in rois:T1, in batch_indices:T2, in crop_size:T2, out Y:T1) | 1+ | T = tensor(float) |
T2 = tensor(int32) | |||
ExpandDims | (in X:T, in axis:tensor(int32), out Y:T) | 1+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
axis = tensor(int32) | |||
FusedConv | (in X:T, in W:T, in B:T, out Y:T) | 1+ | T = tensor(float) |
FusedGemm | (in A:T, in B:T, in C:T, out Y:T) | 1+ | T = tensor(float) |
GatherND | (in data:T, in indices:Tind, out output:T) | 1+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(string), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Tind = tensor(int32), tensor(int64) | |||
MaxpoolWithMask | (in X:T, in M:tensor(int32), out Y:T) | 1+ | X = tensor(float) |
MurmurHash3 | (in X:T1, out Y:T2) | 1+ | T1 = tensor(string), tensor(int32), tensor(uint32) |
T2 = tensor(int32), tensor(uint32) | |||
Pad | (in data:T, in pads:tensor(int64), in value:T, out output:T) | 1+ | T = tensor(float) |
Range | (in start:T, in limit:T, in delta:T, out Y:T) | 1+ | T = tensor(int32), tensor(float), tensor(int64), tensor(int16), tensor(double) |
SampleOp | (in X:T, out Y:T) | 1+ | T = tensor(float) |
Tokenizer | (in X:T, out Y:T) | 1+ | T = tensor(string) |
Unique | (in x:T, out y:T, out idx:tensor(int64), out counts:tensor(int64)) | 1+ | T = tensor(float) |
WordConvEmbedding | (in Sequence:T, in W:T1, in B:T1, in C:T1, out Y:T1) | 1+ | T = tensor(int32) |
T1 = tensor(float) | |||
Operator Domain: com.microsoft.nchwc | |||
AveragePool | (in X:T, out Y:T) | 1+ | T = tensor(float) |
Conv | (in X:T, in W:T, in B:T, in Sum:T, out Y:T) | 1+ | T = tensor(float) |
GlobalAveragePool | (in X:T, out Y:T) | 1+ | T = tensor(float) |
GlobalMaxPool | (in X:T, out Y:T) | 1+ | T = tensor(float) |
MaxPool | (in X:T, out Y:T) | 1+ | T = tensor(float) |
ReorderInput | (in X:T, out Y:T) | 1+ | T = tensor(float) |
ReorderOutput | (in X:T, out Y:T) | 1+ | T = tensor(float) |
Op Name | Parameters | OpSet Version | Types Supported |
---|---|---|---|
Operator Domain: ai.onnx.ml | |||
Abs | (in X:T, out Y:T) | 6+ | T = tensor(int32), tensor(int16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Add | (in A:T, in B:T, out C:T) | 7+ | T = tensor(int32), tensor(uint32), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Affine | (in X:T, out Y:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
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+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
ArgMin | (in data:T, out reduced:tensor(int64)) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
AveragePool | (in X:T, out Y:T) | 10+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
[7, 9] | I = tensor(int64) | ||
T = tensor(float), tensor(MLFloat16), tensor(double) | |||
BatchNormalization | (in X:T, in scale:T, in B:T, in mean:T, in var:T, out Y:T, out mean:T, out var:T, out saved_mean:T, out saved_var:T) | 9+ | B = tensor(float), tensor(MLFloat16), tensor(double) |
X = tensor(float), tensor(MLFloat16), tensor(double) | |||
mean = tensor(float), tensor(MLFloat16), tensor(double) | |||
scale = tensor(float), tensor(MLFloat16), tensor(double) | |||
var = tensor(float), tensor(MLFloat16), tensor(double) | |||
[7, 8] | B = tensor(float), tensor(MLFloat16), tensor(double) | ||
X = tensor(float), tensor(MLFloat16), tensor(double) | |||
mean = tensor(float), tensor(MLFloat16), tensor(double) | |||
scale = tensor(float), tensor(MLFloat16), tensor(double) | |||
var = tensor(float), tensor(MLFloat16), tensor(double) | |||
Cast | (in input:T1, out output:T2) | 9+ | T1 = tensor(int32), tensor(bool), tensor(int16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
T2 = tensor(int32), tensor(bool), tensor(int16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) | |||
[6, 8] | T1 = tensor(int32), tensor(bool), tensor(int16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) | ||
T2 = tensor(int32), tensor(bool), tensor(int16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) | |||
Ceil | (in X:T, out Y:T) | 6+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
Compress | (in input:T, in condition:T1, out output:T) | 9+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
T1 = tensor(bool) | |||
Concat | (in inputs:T, out concat_result:T) | 4+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
ConstantOfShape | (in input:T1, out output:T2) | 9+ | T1 = tensor(int64) |
T2 = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) | |||
Conv | (in X:T, in W:T, in B:T, out Y:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
ConvTranspose | (in X:T, in W:T, in B:T, out Y:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
Crop | (in input:T, out output:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
Div | (in A:T, in B:T, out C:T) | 7+ | T = tensor(int32), tensor(uint32), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Dropout | (in data:T, out output:T, out mask:T) or (in data:T, out output:T, out mask:T1) | 10+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
T1 = tensor(bool) | |||
[7, 9] | T = tensor(float), tensor(MLFloat16), tensor(double) | ||
DynamicSlice | (in data:T, in starts:Tind, in ends:Tind, in axes:Tind, out output:T) | 1+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Tind = tensor(int32), tensor(int64) | |||
Elu | (in X:T, out Y:T) | 6+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
Equal | (in A:T, in B:T, out C:T1) | 7+ | T = tensor(int32), tensor(bool), tensor(int64) |
Erf | (in input:T, out output:T) | 9+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
Exp | (in input:T, out output:T) | 6+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
Expand | (in input:T, in shape:tensor(int64), out output:T) | 8+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Flatten | (in input:T, out output:T) | 9+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
[1, 8] | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) | ||
Floor | (in X:T, out Y:T) | 6+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
GRU | (in X:T, in W:T, in R:T, in B:T, in sequence_lens:T1, in initial_h:T, out Y:T, out Y_h:T) | 7+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
T1 = tensor(int32) | |||
Gather | (in data:T, in indices:Tind, out output:T) | 1+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Tind = tensor(int32), tensor(int64) | |||
Gemm | (in A:T, in B:T, in C:T, out Y:T) | 9+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
[7, 8] | T = tensor(float), tensor(MLFloat16), tensor(double) | ||
GlobalAveragePool | (in X:T, out Y:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
GlobalMaxPool | (in X:T, out Y:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
Greater | (in A:T, in B:T, out C:T1) | 9+ | T = tensor(int32), tensor(uint32), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
T1 = tensor(bool) | |||
[7, 8] | T = tensor(float), tensor(MLFloat16), tensor(double) | ||
HardSigmoid | (in X:T, out Y:T) | 6+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
Identity | (in input:T, out output:T) | 1+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
ImageScaler | (in input:T, out output:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
InstanceNormalization | (in input:T, in scale:T, in B:T, out output:T) | 6+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
LRN | (in X:T, out Y:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
LSTM | (in X:T, in W:T, in R:T, in B:T, in sequence_lens:T1, in initial_h:T, in initial_c:T, in P:T, out Y:T, out Y_h:T, out Y_c:T) | 7+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
T1 = tensor(int32) | |||
LeakyRelu | (in X:T, out Y:T) | 6+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
Log | (in input:T, out output:T) | 6+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
MatMul | (in A:T, in B:T, out Y:T) | 9+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
[1, 8] | T = tensor(float), tensor(MLFloat16), tensor(double) | ||
Max | (in data_0:T, out max:T) | 8+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
[6, 7] | T = tensor(float), tensor(MLFloat16), tensor(double) | ||
MaxPool | (in X:T, out Y:T) or (in X:T, out Y:T, out Indices:I) | 10+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
[1, 7] | I = tensor(int64) | ||
T = tensor(float), tensor(MLFloat16), tensor(double) | |||
[8, 9] | I = tensor(int64) | ||
T = tensor(float), tensor(MLFloat16), tensor(double) | |||
MemcpyFromHost | (in X:T, out Y:T) | 1+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
MemcpyToHost | (in X:T, out Y:T) | 1+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Min | (in data_0:T, out min:T) | 8+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
[6, 7] | T = tensor(float), tensor(MLFloat16), tensor(double) | ||
Mul | (in A:T, in B:T, out C:T) | 7+ | T = tensor(int32), tensor(uint32), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Neg | (in X:T, out Y:T) | 6+ | T = tensor(int32), tensor(int16), unknown, tensor(float), tensor(MLFloat16), tensor(int64), tensor(double) |
Or | (in A:T, in B:T, out C:T1) | 7+ | T = tensor(bool) |
T1 = tensor(bool) | |||
PRelu | (in X:T, in slope:T, out Y:T) | 7+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
Pad | (in data:T, out output:T) | 2+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
ParametricSoftplus | (in X:T, out Y:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
Pow | (in X:T, in Y:T, out Z:T) | 7+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
RNN | (in X:T, in W:T, in R:T, in B:T, in sequence_lens:T1, in initial_h:T, out Y:T, out Y_h:T) | 7+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
T1 = tensor(int32) | |||
Reciprocal | (in X:T, out Y:T) | 6+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
ReduceL1 | (in data:T, out reduced:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
ReduceL2 | (in data:T, out reduced:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
ReduceLogSum | (in data:T, out reduced:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
ReduceLogSumExp | (in data:T, out reduced:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
ReduceMax | (in data:T, out reduced:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
ReduceMean | (in data:T, out reduced:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
ReduceMin | (in data:T, out reduced:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
ReduceProd | (in data:T, out reduced:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
ReduceSum | (in data:T, out reduced:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
ReduceSumSquare | (in data:T, out reduced:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
Relu | (in X:T, out Y:T) | 6+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
Reshape | (in data:T, in shape:tensor(int64), out reshaped:T) or (in data:T, out reshaped:T) | 5+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
shape = tensor(int64) | |||
Reshape_1 | [1, 4] | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) | |
Resize | (in X:T, in scales:tensor(float), out Y:T) | 10+ | T = tensor(int32), tensor(float), tensor(MLFloat16), tensor(uint8), tensor(double) |
ScaledTanh | (in input:T, out output:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
Selu | (in X:T, out Y:T) | 6+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
Shape | (in data:T, out shape:T1) | 1+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
T1 = tensor(int64) | |||
Shrink | (in input:T, out output:T) | 9+ | T = tensor(int32), tensor(int16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Sigmoid | (in X:T, out Y:T) | 6+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
Slice | (in data:T, out output:T) or (in data:T, in starts:Tind, in ends:Tind, in axes:Tind, in steps:Tind, out output:T) | 10+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Tind = tensor(int32), tensor(int64) | |||
[1, 9] | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) | ||
Tind = tensor(int32), tensor(int64) | |||
Softmax | (in input:T, out output:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
Softplus | (in X:T, out Y:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
Softsign | (in input:T, out output:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
Split | (in input:T, out outputs:T) or (in input:T, in split:T, out outputs...:T) | 2+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Sqrt | (in X:T, out Y:T) | 6+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
Squeeze | (in data:T, out squeezed:T) | 1+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Sub | (in A:T, in B:T, out C:T) | 7+ | T = tensor(int32), tensor(uint32), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Sum | (in data_0:T, out sum:T) | 8+ | T = tensor(int32), tensor(uint32), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
[6, 7] | T = tensor(int32), tensor(uint32), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) | ||
Tanh | (in input:T, out output:T) | 6+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
ThresholdedRelu | (in X:T, out Y:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
10+ | T = tensor(float), tensor(MLFloat16), tensor(double) | ||
Tile | (in input:T, in tiles:T, in axis:T, out output:T) or (in input:T, in repeats:T1, out output:T) | 6+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
T1 = tensor(int64) | |||
Transpose | (in data:T, out transposed:T) | 1+ | T = tensor(float), tensor(MLFloat16), tensor(double) |
Unsqueeze | (in data:T, out expanded:T) | 1+ | T = tensor(int32), tensor(bool), tensor(int16), tensor(bfloat16), tensor(uint8), unknown, tensor(uint32), tensor(uint16), tensor(float), tensor(uint64), tensor(MLFloat16), tensor(int64), tensor(double) |
Upsample | (in X:T, out Y:T) or (in X:T, in scales:tensor(float), out Y:T) | [7, 9] | T = tensor(int32), tensor(float), tensor(MLFloat16), tensor(uint8), tensor(double) |
Xor | (in A:T, in B:T, out C:T1) | 7+ | T = tensor(bool) |
T1 = tensor(bool) | |||
Operator Domain: com.microsoft | |||
ConvTransposeWithDynamicPads | (in X:T, in W:T, in Pads:tensor(int64), in B:T, out Y:T) | 1+ | T = tensor(float) |
Op Name | Parameters | OpSet Version | Types Supported |
---|---|---|---|
Operator Domain: ai.onnx.ml | |||
AveragePool | (in X:T, out Y:T) | [7, 8] | T = tensor(float) |
BatchNormalization | (in X:T, in scale:T, in B:T, in mean:T, in var:T, out Y:T, out mean:T, out var:T, out saved_mean:T, out saved_var:T) | 7+ | T = tensor(float) |
Conv | (in X:T, in W:T, in B:T, out Y:T) | 1+ | T = tensor(float) |
Gemm | (in A:T, in B:T, in C:T, out Y:T) | 7+ | T = tensor(float) |
GlobalAveragePool | (in X:T, out Y:T) | [1, 8] | T = tensor(float) |
GlobalMaxPool | (in X:T, out Y:T) | [1, 8] | T = tensor(float) |
LRN | (in X:T, out Y:T) | 1+ | T = tensor(float) |
MaxPool | (in X:T, out Y:T) or (in X:T, out Y:T, out Indices:I) | [1, 7] | T = tensor(float) |
[8, 8] | T = tensor(float) | ||
Relu | (in X:T, out Y:T) | 6+ | T = tensor(float) |
Sum | (in data_0:T, out sum:T) | 6+ | T = tensor(float) |
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