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Python module

conv

Conv1D​

class max.pipelines.nn.conv.Conv1D(filter: Value | TensorValue | Shape | Dim | int | float | integer | floating | ndarray, stride: int = 1, padding: int = 0, dilation: int = 1, groups: int = 1, bias: bool = False)

A 1D convolution over an input signal composed of several input planes.

bias​

bias*: bool* = False

dilation​

dilation*: int* = 1

filter​

filter*: Value | TensorValue | Shape | Dim | int | float | integer | floating | ndarray*

groups​

groups*: int* = 1

padding​

padding*: int* = 0

stride​

stride*: int* = 1

Conv2D​

class max.pipelines.nn.conv.Conv2D(filter: Value | TensorValue | Shape | Dim | int | float | integer | floating | ndarray, stride: int | Tuple[int, int] = (1, 1), padding: int | Tuple[int, int, int, int] = (0, 0, 0, 0), dilation: int | Tuple[int, int] = (1, 1), groups: int = 1, bias: bool = False)

A 2D convolution over an input signal composed of several input planes.

bias​

bias*: bool* = False

dilation​

dilation*: int | Tuple[int, int]* = (1, 1)

filter​

filter*: Value | TensorValue | Shape | Dim | int | float | integer | floating | ndarray*

groups​

groups*: int* = 1

padding​

padding*: int | Tuple[int, int, int, int]* = (0, 0, 0, 0)

stride​

stride*: int | Tuple[int, int]* = (1, 1)