class ascendie.Network
- 类说明
- 成员变量
- def add_input(self: Network, name: str, type: DataType, dim: Dims) -> Tensor
- def mark_output(self: Network, tensor: Tensor) -> None
- def get_output(self: Network, index: int) -> Tensor
- def add_activation(self: Network, input: Tensor, kind: ActivationKind) -> ActivationLayer
- def add_constant(self: Network, dimensions: Dims, weights: WeightsBuf) -> ConstantLayer
- def add_convolution(self: Network, input: Tensor, numOutputMap: int, kernelHW: Dims, weights: WeightsBuf, bias: WeightsBuf) -> ConvolutionLayer
- def add_pooling(self: Network, input: Tensor, kind: PoolingKind, windowSize: Dims, Dims = Dims([])) -> AscendIE::PoolingLayer
- def add_elementwise(self: Network, input0: Tensor, input1: Tensor, op: ElementWiseOperation) -> ElementWiseLayer
- def add_matrix_multiply(self: Network, input0: Tensor, type0: MatrixOperation, input1: Tensor, type1: MatrixOperation) -> MatrixMultiplyLayer
- def add_shuffle(self: Network, input: Tensor) -> ShuffleLayer
- def add_reduce(self: Network, input: Tensor, operation: ReduceOperation, reduceAxes: int, keepDimensions: bool) -> ReduceLayer
- def add_shape(self: Network, input: Tensor) -> ShapeLayer