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  • Guide

    • # Operator Support List

    # The AI inference of the Mini Program is responsible for running your model in an optimized way and utilizing the hardware acceleration of the specific device when available. This page provides information on which Ops are currently supported by various devices.

    Note:
    1.The following operators are generally consistent with ONNX without special remarks. Operator definition, ref: https://github.com/onnx/onnx/blob/Main/docs/Operators.md
    2.At present, GPU reasoning is not open to the outside world, please look forward to it.

    Operator CPU IOS NPU IOS GPU Android GPU Remarks
    Activation &#10004 &#10004 &#10004 &#10004 Refer to the activation list below for details of supported activation types
    ArgMax &#10004 &#10004 &#10004
    ArgMin &#10004 &#10004 &#10004
    BatchNorm &#10004 &#10004 &#10004 &#10004
    Bias &#10004 &#10004 &#10004 &#10004
    Binary &#10004 &#10004 &#10004 &#10004 See the Binary list below for a detailed list of supported binary operations
    Bucketize &#10004
    Cast &#10004 &#10004
    Concat &#10004 &#10004 &#10004 &#10004
    Const &#10004 &#10004
    ConstOfShape &#10004
    Conv1D &#10004 &#10004 &#10004
    Conv1DTranspose &#10004 &#10004
    Conv2D &#10004 &#10004 &#10004 &#10004
    Conv2DTranspose &#10004 &#10004 &#10004 &#10004
    Conv3D &#10004
    Conv3DTranspose &#10004
    Crop &#10004
    CropAndResize &#10004
    CumSum &#10004
    DepthToSpace &#10004 &#10004
    Dropout &#10004
    ElementWise &#10004 &#10004 &#10004 &#10004
    Expand &#10004 &#10004
    FakeQuantize &#10004
    Flatten &#10004 &#10004
    FullyConnected &#10004 &#10004 &#10004 &#10004
    Gather &#10004 &#10004
    GatherND &#10004
    Gemm &#10004 &#10004 &#10004
    GlobalPooling &#10004 &#10004 &#10004 &#10004
    GroupNorm &#10004
    Gru &#10004
    InstanceNorm &#10004 &#10004 &#10004
    LayerNorm &#10004
    LpNorm &#10004
    Lrn &#10004
    Lstm &#10004
    MatMul &#10004 &#10004
    Normalize &#10004 &#10004 &#10004
    OneHot &#10004 &#10004
    Pad &#10004 &#10004 &#10004
    Permute &#10004 &#10004 &#10004
    Pooling1D &#10004 &#10004 &#10004
    Pooling2D &#10004 &#10004 &#10004 &#10004
    Pooling3D &#10004
    PriorBox &#10004
    Range &#10004
    Reduce &#10004 &#10004 &#10004 &#10004
    Reshape &#10004 &#10004
    Resize2D &#10004 &#10004 &#10004 &#10004
    Rnn &#10004
    Scale &#10004 &#10004 &#10004
    ScatterND &#10004 &#10004
    Shape &#10004
    ShuffleChannel &#10004
    SpaceToDepth &#10004 &#10004
    Split &#10004 &#10004
    Slice &#10004 &#10004 &#10004
    Softmax &#10004 &#10004 &#10004 &#10004
    Squeeze &#10004 &#10004 &#10004 &#10004
    Tile &#10004 &#10004
    Unary &#10004 &#10004 &#10004 &#10004 See the Unary list below for details on the supported Unary types
    Unsqueeze &#10004 &#10004 &#10004 &#10004
    Where &#10004

    # Activation List:

    name describe
    None f(x) = x
    Abs f(x) = [x]
    Clip f(x) = min(max(x, constA), constB)
    HardSigmoid f(x) = min(max(x * constA + constB, 0), 1)
    HardSwish f(x) = min(max(x * constA + constB, 0), 1) * x
    HSigmoid f(x) = (ReLU6(x + 3) / 6)
    HSwish f(x) = (ReLU6(x + 3) / 6) * x
    LeakyReLU f(x) = min(x, 0) * constA + max(x, 0)
    Linear f(x) = x * constA + constB
    PReLU f(x) = min(x, 0) * weight + max(x, 0) (Caffe1's )
    Hot stove f(x) = max(x, 0)
    Hot wheel f(x) = min(x, 0) * constA + min(max(x, 0), constB)
    SELU f(x) = (x >= 0 ? x : (exp(x)-1) * constA) * constB
    Sigmoid f(x) = 1 / (1 + exp(-x)), a.k.a. Logistic
    SoftPlus f(x) = log(1 + exp(x * constB)) * constA
    SoftSign f(x) = x / (1 +
    Swish f(x) = x / (1 + exp(-x * constA))
    Tanh f(x) = tanh(x * constB) * constA
    Threshold f(x) = (x > constA ? 1 : 0)
    ThrReLU f(x) = (x > constA ? x : 0) (Thresholded Hot stove)

    # Binary list:

    name describe
    Add f(x, y) = x + y
    Sub f(x, y) = x - y
    Mul f(x, y) = x * y
    Div f(x, y) = x / y
    Pow f(x, y) = pow(x, y)
    Max f(x, y) = max(x, y)
    Min f(x, y) = min(x, y)
    Mean f(x, y) = (x + y) / 2
    And f(x, y) = x & y
    Or f(x, y) = x
    Xor f(x, y) = x y
    BitShiftLeft f(x, y) = x << y
    BitShiftRight f(x, y) = x >> y
    Equal f(x, y) = (x == y)
    NotEqual f(x, y) = (x != y)
    Greater f(x, y) = (x > y)
    GreaterEqual f(x, y) = (x >= y)
    Less f(x, y) = (x < y)
    LessEqual f(x, y) = (x <= y)

    # Unary list:

    name describe
    Abs f(x) = [x]
    Neg f(x) = -x
    Lateral force f(x) = ceil(x)
    Floor f(x) = floor(x)
    Reciprocal f(x) = 1 / x
    Sqrt f(x) = sqrt(x)
    Exp f(x) = exp(x)
    Log f(x) = log(x)
    Erf f(x) = erf(x)
    Acos f(x) = acos(x)
    Acosh f(x) = Acosh (x)
    Cos f(x) = cos(x)
    Cosh f(x) = cosh(x)
    Sin f(x) = sin(x)
    Sinh f(x) = sinh(x)
    Atan f(x) = atan(x)
    Atanh f(x) = Atanh (x)
    Tan f(x) = tan(x)
    Tanh f(x) = tanh(x)
    ExpM1 f(x) = expm1(x)
    Log1P f(x) = log1p(x)