支持TensorFlow算子清单
该算子规格仅适用于TensorFlow框架(TensorFlow版本为1.15与2.6.5)原生IR定义的网络模型,参数解释请参见TensorFlow官网。如果要查看基于Ascend IR定义的单算子信息,请参见CANN算子清单。
支持的TF算子名称 |
算子分类 |
算子功能 |
---|---|---|
Abs |
math_ops |
Computes the absolute value of a tensor. |
AccumulateNV2 |
math_ops |
Returns the element-wise sum of a list of tensors. |
Acos |
math_ops |
Computes acos of x element-wise. |
Acosh |
math_ops |
Computes inverse hyperbolic cosine of x element-wise. |
Add |
math_ops |
Returns x + y element-wise. |
AddN |
math_ops |
Add all input tensors element wise. |
AddV2 |
math_ops |
Returns x + y element-wise. |
All |
math_ops |
Computes the "logical and" of elements across dimensions of a tensor. |
Any |
math_ops |
Computes the "logical or" of elements across dimensions of a tensor. |
ApproximateEqual |
math_ops |
Returns the truth value of abs(x-y) < tolerance element-wise. |
ArgMax |
math_ops |
Returns the index with the largest value across dimensions of a tensor. |
ArgMin |
math_ops |
Returns the index with the smallest value across dimensions of a tensor. |
Asin |
math_ops |
Computes asin of x element-wise. |
Asinh |
math_ops |
Computes inverse hyperbolic sine of x element-wise. |
Atan |
math_ops |
Computes atan of x element-wise. |
Atan2 |
math_ops |
Computes arctangent of y/x element-wise, respecting signs of the arguments. |
Atanh |
math_ops |
Computes inverse hyperbolic tangent of x element-wise. |
AvgPool |
nn_ops |
Performs average pooling on the input. |
Batch |
batch_ops |
- |
BatchMatMul |
math_ops |
Multiplies slices of two tensors in batches. |
BatchToSpace |
array_ops |
BatchToSpace for 4-D tensors of type T. |
BatchToSpaceND |
array_ops |
BatchToSpace for N-D tensors of type T. |
BesselI0e |
math_ops |
Computes the Bessel i0e function of x element-wise. |
BesselI1e |
math_ops |
Computes the Bessel i1e function of x element-wise. |
Betainc |
math_ops |
Compute the regularized incomplete beta integral \(I_x(a, b)\). |
BiasAdd |
nn_ops |
Adds bias to value. |
Bincount |
math_ops |
Counts the number of occurrences of each value in an integer array. |
BitwiseAnd |
bitwise_ops |
- |
BitwiseOr |
bitwise_ops |
- |
BitwiseXor |
bitwise_ops |
- |
BroadcastTo |
array_ops |
Broadcast an array for a compatible shape. |
Bucketize |
math_ops |
Bucketizes 'input' based on 'boundaries'. |
Cast |
math_ops |
Cast x of type SrcT to y of DstT. |
Ceil |
math_ops |
Returns element-wise smallest integer not less than x. |
CheckNumerics |
array_ops |
Checks a tensor for NaN and Inf values. |
Cholesky |
linalg_ops |
- |
CholeskyGrad |
linalg_ops |
- |
ClipByValue |
math_ops |
Clips tensor values to a specified min and max. |
CompareAndBitpack |
math_ops |
Compare values of input to threshold and pack resulting bits into a uint8. |
Concat |
array_ops |
Concatenates tensors along one dimension. |
ConcatV2 |
array_ops |
- |
Const |
array_ops |
- |
ControlTrigger |
control_flow_ops |
Does nothing. |
Conv2D |
nn_ops |
Computes a 2-D convolution given 4-D input and filter tensors. |
Conv2DBackpropFilter |
nn_ops |
Computes the gradients of convolution with respect to the filter. |
Conv2DBackpropInput |
nn_ops |
Computes the gradients of convolution with respect to the input. |
Conv3D |
nn_ops |
Computes a 3D convolution given 5D "x" and "filter" tensor. |
Cos |
math_ops |
Computes cos of x element-wise. |
Cosh |
math_ops |
Computes hyperbolic cosine of x element-wise. |
Cumprod |
math_ops |
Compute the cumulative product of the tensor x along axis. |
Cumsum |
math_ops |
Compute the cumulative sum of the tensor x along axis. |
DataFormatDimMap |
nn_ops |
Returns the dimension index in the destination data format given the one in. |
DataFormatVecPermute |
nn_ops |
Returns the permuted vector/tensor in the destination data format given the. |
DepthToSpace |
array_ops |
DepthToSpace for tensors of type T. |
DepthwiseConv2dNative |
nn_ops |
Computes a 2-D depthwise convolution given 4-D input and filtertensors. |
DepthwiseConv2dNativeBackpropFilter |
nn_ops |
Computes the gradients of depthwise convolution with respect to the filter. |
DepthwiseConv2dNativeBackpropInput |
nn_ops |
Computes the gradients of depthwise convolution with respect to the input. |
Dequantize |
array_ops |
Dequantize the 'input' tensor into a float Tensor. |
Diag |
array_ops |
Returns a diagonal tensor with a given diagonal values. |
DiagPart |
array_ops |
Returns the diagonal part of the tensor. |
Div |
math_ops |
Returns x / y element-wise. |
DivNoNan |
math_ops |
Returns 0 if the denominator is zero. |
Elu |
nn_ops |
Computes exponential linear: exp(features) - 1 if < 0, features otherwise. |
Empty |
array_ops |
Creates a tensor with the given shape. |
Enter |
control_flow_ops |
- |
Equal |
math_ops |
Returns the truth value of (x == y) element-wise. |
Erf |
math_ops |
Computes the Gauss error function of x element-wise. |
Erfc |
math_ops |
Computes the complementary error function of x element-wise. |
Exit |
control_flow_ops |
- |
Exp |
math_ops |
Computes exponential of x element-wise. |
ExpandDims |
array_ops |
Inserts a dimension of 1 into a tensor's shape. |
Expm1 |
math_ops |
Computes exponential of x - 1 element-wise. |
ExtractImagePatches |
array_ops |
Extract patches from images and put them in the "depth" output dimension. |
FakeQuantWithMinMaxArgs |
array_ops |
Fake-quantize the 'inputs' tensor, type float to 'outputs' tensor of same type. |
FakeQuantWithMinMaxVars |
array_ops |
Fake-quantize the 'inputs' tensor of type float via global float scalars min. |
FakeQuantWithMinMaxVarsPerChannel |
array_ops |
Fake-quantize the 'inputs' tensor of type float and one of the shapes: [d],. |
Fill |
array_ops |
Creates a tensor filled with a scalar value. |
Floor |
math_ops |
Returns element-wise largest integer not greater than x. |
FloorDiv |
math_ops |
Returns x // y element-wise. |
FloorMod |
math_ops |
Returns element-wise remainder of division. |
FractionalAvgPool |
nn_ops |
Performs fractional average pooling on the input. |
FractionalAvgPoolGrad |
nn_ops |
- |
FractionalMaxPool |
nn_ops |
Performs fractional max pooling on the input. |
FractionalMaxPoolGrad |
nn_ops |
- |
FusedBatchNorm |
nn_ops |
Batch normalization. |
FusedBatchNormV2 |
nn_ops |
Batch normalization. |
Gather |
array_ops |
Gather slices from params according to indices. |
GatherNd |
array_ops |
Gather slices from params into a Tensor with shape specified by indices. |
GatherV2 |
array_ops |
Gather slices from params axis according to indices. |
Greater |
math_ops |
Returns the truth value of (x > y) element-wise. |
GreaterEqual |
math_ops |
Returns the truth value of (x >= y) element-wise. |
GuaranteeConst |
array_ops |
Gives a guarantee to the TF runtime that the input tensor is a constant. |
HistogramFixedWidth |
math_ops |
Return histogram of values. |
Identity |
array_ops |
Return a tensor with the same shape and contents as the input tensor or value. |
IdentityN |
array_ops |
Returns a list of tensors with the same shapes and contents as the input. |
Igamma |
math_ops |
Compute the lower regularized incomplete Gamma function P(a, x). |
Igammac |
math_ops |
Compute the upper regularized incomplete Gamma function Q(a, x). |
IgammaGradA |
math_ops |
- |
InplaceAdd |
array_ops |
Adds v into specified rows of x. |
InplaceSub |
array_ops |
Subtracts v into specified rows of x. |
InplaceUpdate |
array_ops |
Updates specified rows with values in v. |
InTopK |
nn_ops |
Says whether the targets are in the top K predictions. |
InTopKV2 |
nn_ops |
Says whether the targets are in the top K predictions. |
Inv |
math_ops |
Computes the reciprocal of x element-wise. |
Invert |
bitwise_ops |
- |
InvertPermutation |
array_ops |
Computes the inverse permutation of a tensor. |
IsVariableInitialized |
state_ops |
Checks whether a tensor has been initialized. |
L2Loss |
nn_ops |
L2 Loss. |
Less |
math_ops |
Returns the truth value of (x < y) element-wise. |
LessEqual |
math_ops |
Returns the truth value of (x <= y) element-wise. |
LinSpace |
math_ops |
Generates values in an interval. |
ListDiff |
array_ops |
- |
Log |
math_ops |
Computes natural logarithm of x element-wise. |
Log1p |
math_ops |
Computes natural logarithm of (1 + x) element-wise. |
LogicalAnd |
math_ops |
Returns the truth value of x AND y element-wise. |
LogicalNot |
math_ops |
Returns the truth value of NOT x element-wise. |
LogicalOr |
math_ops |
Returns the truth value of x OR y element-wise. |
LogMatrixDeterminant |
linalg_ops |
- |
LogSoftmax |
nn_ops |
Computes log softmax activations. |
LoopCond |
control_flow_ops |
Forwards the input to the output. |
LowerBound |
array_ops |
- |
LRN |
nn_ops |
Local Response Normalization. |
MatMul |
math_ops |
Multiply the matrix "a" by the matrix "b". |
MatrixBandPart |
array_ops |
Copy a tensor setting everything outside a central band in each innermost matrix. |
MatrixDeterminant |
linalg_ops |
- |
MatrixDiag |
array_ops |
Returns a batched diagonal tensor with a given batched diagonal values. |
MatrixDiagPart |
array_ops |
Returns the batched diagonal part of a batched tensor. |
MatrixInverse |
linalg_ops |
- |
MatrixSetDiag |
array_ops |
Returns a batched matrix tensor with new batched diagonal values. |
MatrixSolve |
linalg_ops |
- |
MatrixSolveLs |
linalg_ops |
- |
MatrixTriangularSolve |
linalg_ops |
- |
Max |
math_ops |
Computes the maximum of elements across dimensions of a tensor. |
Maximum |
math_ops |
Returns the max of x and y (i.e. |
MaxPool |
nn_ops |
Performs max pooling on the input. |
MaxPoolV2 |
nn_ops |
Performs max pooling on the input. |
MaxPool3D |
nn_ops |
Performs 3D max pooling on the input. |
MaxPoolWithArgmax |
nn_ops |
Performs max pooling on the input and outputs both max values and indices. |
Mean |
math_ops |
Computes the mean of elements across dimensions of a tensor. |
Merge |
control_flow_ops |
Forwards the value of an available tensor from inputs to output. |
Min |
math_ops |
Computes the minimum of elements across dimensions of a tensor. |
Minimum |
math_ops |
Returns the min of x and y (i.e. |
MirrorPad |
array_ops |
Pads a tensor with mirrored values. |
MirrorPadGrad |
array_ops |
- |
Mod |
math_ops |
Returns element-wise remainder of division. |
Mul |
math_ops |
- |
Multinomial |
random_ops |
Draws samples from a multinomial distribution. |
Neg |
math_ops |
- |
NextIteration |
control_flow_ops |
Makes its input available to the next iteration. |
NoOp |
no_op |
Does nothing. |
NotEqual |
math_ops |
Returns the truth value of (x != y) element-wise. |
NthElement |
nn_ops |
Finds values of the n-th order statistic for the last dimension. |
OneHot |
array_ops |
Returns a one-hot tensor. |
OnesLike |
array_ops |
Returns a tensor of ones with the same shape and type as x. |
Pack |
array_ops |
- |
Pad |
array_ops |
- |
ParallelConcat |
array_ops |
- |
ParameterizedTruncatedNormal |
random_ops |
Outputs random values from a normal distribution. |
Placeholder |
array_ops |
- |
PlaceholderWithDefault |
array_ops |
- |
PopulationCount |
bitwise_ops |
- |
Pow |
math_ops |
Computes the power of one value to another. |
PreventGradient |
array_ops |
- |
Prod |
math_ops |
Computes the product of elements across dimensions of a tensor. |
Qr |
linalg_ops |
- |
RandomGamma |
random_ops |
Outputs random values from the Gamma distribution(s) described by alpha. |
RandomGammaGrad |
random_ops |
- |
RandomShuffle |
random_ops |
Randomly shuffles a tensor along its first dimension. |
RandomStandardNormal |
random_ops |
- |
RandomUniform |
random_ops |
Outputs random values from a uniform distribution. |
Range |
math_ops |
Creates a sequence of numbers. |
RandomUniformInt |
random_ops |
Outputs random integers from a uniform distribution. |
Rank |
array_ops |
Returns the rank of a tensor. |
ReadVariableOp |
resource_variable_ops |
- |
RealDiv |
math_ops |
Returns x / y element-wise for real types. |
Reciprocal |
math_ops |
Computes the reciprocal of x element-wise. |
RefEnter |
control_flow_ops |
- |
RefExit |
control_flow_ops |
- |
RefMerge |
control_flow_ops |
- |
RefNextIteration |
control_flow_ops |
Makes its input available to the next iteration. |
RefSwitch |
control_flow_ops |
Forwards the ref tensor data to the output port determined by pred. |
Relu |
nn_ops |
Computes rectified linear: max(features, 0). |
Relu6 |
nn_ops |
Computes rectified linear 6: min(max(features, 0), 6). |
Reshape |
array_ops |
Reshapes a tensor. |
ReverseSequence |
array_ops |
Reverses variable length slices. |
ReverseV2 |
array_ops |
- |
RightShift |
bitwise_ops |
- |
Rint |
math_ops |
Returns element-wise integer closest to x. |
Round |
math_ops |
Rounds the values of a tensor to the nearest integer, element-wise. |
Rsqrt |
math_ops |
Computes reciprocal of square root of x element-wise. |
SegmentMax |
math_ops |
Computes the maximum along segments of a tensor. |
Select |
math_ops |
- |
Selu |
nn_ops |
Computes scaled exponential linear: scale * alpha * (exp(features) - 1). |
Shape |
array_ops |
Returns the shape of a tensor. |
ShapeN |
array_ops |
Returns shape of tensors. |
Sigmoid |
math_ops |
Computes sigmoid of x element-wise. |
Sign |
math_ops |
Returns an element-wise indication of the sign of a number. |
Sin |
math_ops |
Computes sin of x element-wise. |
Sinh |
math_ops |
Computes hyperbolic sine of x element-wise. |
Size |
array_ops |
Returns the size of a tensor. |
Slice |
array_ops |
Return a slice from 'input'. |
Snapshot |
array_ops |
Returns a copy of the input tensor. |
Softmax |
nn_ops |
Computes softmax activations. |
Softplus |
nn_ops |
Computes softplus: log(exp(features) + 1). |
Softsign |
nn_ops |
Computes softsign: features / (abs(features) + 1). |
SpaceToBatch |
array_ops |
SpaceToBatch for 4-D tensors of type T. |
SpaceToBatchND |
array_ops |
SpaceToBatch for N-D tensors of type T. |
SpaceToDepth |
array_ops |
SpaceToDepth for tensors of type T. |
Split |
array_ops |
Splits a tensor into num_split tensors along one dimension. |
SplitV |
array_ops |
Splits a tensor into num_split tensors along one dimension. |
Sqrt |
math_ops |
Computes square root of x element-wise. |
Square |
math_ops |
Computes square of x element-wise. |
SquaredDifference |
math_ops |
Returns (x - y)(x - y) element-wise. |
Squeeze |
array_ops |
Removes dimensions of size 1 from the shape of a tensor. |
StatelessMultinomial |
stateless_random_ops |
- |
StopGradient |
array_ops |
Stops gradient computation. |
StridedSlice |
array_ops |
Return a strided slice from input. |
Sub |
math_ops |
- |
Sum |
math_ops |
Computes the sum of elements across dimensions of a tensor. |
Svd |
linalg_ops |
- |
Switch |
control_flow_ops |
Forwards data to the output port determined by pred. |
Tan |
math_ops |
Computes tan of x element-wise. |
Tanh |
math_ops |
Computes hyperbolic tangent of x element-wise. |
Tile |
array_ops |
Constructs a tensor by tiling a given tensor. |
TopK |
nn_ops |
Finds values and indices of the k largest elements for the last dimension. |
TopKV2 |
nn_ops |
- |
Transpose |
array_ops |
Shuffle dimensions of x according to a permutation. |
TruncateDiv |
math_ops |
Returns x / y element-wise for integer types. |
TruncatedNormal |
random_ops |
Outputs random values from a truncated normal distribution. |
TruncateMod |
math_ops |
Returns element-wise remainder of division. |
Unbatch |
batch_ops |
- |
UnbatchGrad |
batch_ops |
- |
Unique |
array_ops |
Finds unique elements in a 1-D tensor. |
UniqueWithCounts |
array_ops |
Finds unique elements in a 1-D tensor. |
Unpack |
array_ops |
- |
UnravelIndex |
array_ops |
Converts a flat index or array of flat indices into a tuple of. |
UnsortedSegmentMin |
math_ops |
Computes the minimum along segments of a tensor. |
UnsortedSegmentProd |
math_ops |
Computes the product along segments of a tensor. |
UnsortedSegmentSum |
math_ops |
Computes the sum along segments of a tensor. |
UpperBound |
array_ops |
- |
Variable |
state_ops |
Holds state in the form of a tensor that persists across steps. |
Where |
array_ops |
Returns locations of nonzero / true values in a tensor. |
Xdivy |
math_ops |
Returns 0 if x == 0, and x / y otherwise, elementwise. |
Xlogy |
math_ops |
Returns 0 if x == 0, and x * log(y) otherwise, elementwise. |
ZerosLike |
array_ops |
Returns a tensor of zeros with the same shape and type as x. |
Zeta |
math_ops |
Compute the Hurwitz zeta function \((x, q)\). |
_Retval |
function_ops |
- |
LeakyRelu |
nn_ops |
- |
FusedBatchNormV3 |
nn_ops/mkl_nn_ops |
- |