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  • 指南

    • # 算子支持列表

    # 小程序AI推理负责以最优化的方式运行您的模型，并在可用时利用特定设备的硬件加速。此页面提供关于目前各设备支持哪些Op的信息。

    注：
    1.以下算子若无特殊备注说明，一般符合ONNX 算子定义，参考：https://github.com/onnx/onnx/blob/main/docs/Operators.md
    2.目前GPU推理暂未对外开放，敬请期待。

    Operator CPU IOS NPU IOS GPU Android GPU 备注
    Activation ✔ ✔ ✔ ✔ 详细支持的Activation种类参考下方Activation列表
    ArgMax ✔ ✔ ✔
    ArgMin ✔ ✔ ✔
    BatchNorm ✔ ✔ ✔ ✔
    Bias ✔ ✔ ✔ ✔
    Binary ✔ ✔ ✔ ✔ 详细支持的Binary操作种类参考下方Binary列表
    Bucketize ✔
    Cast ✔ ✔
    Concat ✔ ✔ ✔ ✔
    Const ✔ ✔
    ConstOfShape ✔
    Conv1D ✔ ✔ ✔
    Conv1DTranspose ✔ ✔
    Conv2D ✔ ✔ ✔ ✔
    Conv2DTranspose ✔ ✔ ✔ ✔
    Conv3D ✔
    Conv3DTranspose ✔
    Crop ✔
    CropAndResize ✔
    CumSum ✔
    DepthToSpace ✔ ✔
    Dropout ✔
    ElementWise ✔ ✔ ✔ ✔
    Expand ✔ ✔
    FakeQuantize ✔
    Flatten ✔ ✔
    FullyConnected ✔ ✔ ✔ ✔
    Gather ✔ ✔
    GatherND ✔
    Gemm ✔ ✔ ✔
    GlobalPooling ✔ ✔ ✔ ✔
    GroupNorm ✔
    Gru ✔
    InstanceNorm ✔ ✔ ✔
    LayerNorm ✔
    LpNorm ✔
    Lrn ✔
    Lstm ✔
    MatMul ✔ ✔
    Normalize ✔ ✔ ✔
    OneHot ✔ ✔
    Pad ✔ ✔ ✔
    Permute ✔ ✔ ✔
    Pooling1D ✔ ✔ ✔
    Pooling2D ✔ ✔ ✔ ✔
    Pooling3D ✔
    PriorBox ✔
    Range ✔
    Reduce ✔ ✔ ✔ ✔
    Reshape ✔ ✔
    Resize2D ✔ ✔ ✔ ✔
    Rnn ✔
    Scale ✔ ✔ ✔
    ScatterND ✔ ✔
    Shape ✔
    ShuffleChannel ✔
    SpaceToDepth ✔ ✔
    Split ✔ ✔
    Slice ✔ ✔ ✔
    Softmax ✔ ✔ ✔ ✔
    Squeeze ✔ ✔ ✔ ✔
    Tile ✔ ✔
    Unary ✔ ✔ ✔ ✔ 详细支持的Unary种类参考下方Unary列表
    Unsqueeze ✔ ✔ ✔ ✔
    Where ✔

    # Activation列表:

    名称 描述
    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)
    ReLU f(x) = max(x, 0)
    ReLUN 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 + |x|)
    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 ReLU)

    # Binary列表:

    名称 描述
    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 | y
    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列表:

    名称 描述
    Abs f(x) = [x]
    Neg f(x) = -x
    Celi 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)