jax.lax.conv_with_general_padding
Warning
This page was created from a pull request (#9655).
jax.lax.conv_with_general_paddingΒΆ
- jax.lax.conv_with_general_padding(lhs, rhs, window_strides, padding, lhs_dilation, rhs_dilation, precision=None, preferred_element_type=None)[source]ΒΆ
Convenience wrapper around conv_general_dilated.
- Parameters
lhs (
Any) β a rank n+2 dimensional input array.rhs (
Any) β a rank n+2 dimensional array of kernel weights.window_strides (
Sequence[int]) β a sequence of n integers, representing the inter-window strides.padding (
Union[str,Sequence[Tuple[int,int]]]) β either the string βSAMEβ, the string βVALIDβ, or a sequence of n (low, high) integer pairs that give the padding to apply before and after each spatial dimension.lhs_dilation (
Optional[Sequence[int]]) β None, or a sequence of n integers, giving the dilation factor to apply in each spatial dimension of lhs. LHS dilation is also known as transposed convolution.rhs_dilation (
Optional[Sequence[int]]) β None, or a sequence of n integers, giving the dilation factor to apply in each spatial dimension of rhs. RHS dilation is also known as atrous convolution.precision (
Union[None,str,Any,Tuple[str,str],Tuple[Any,Any]]) β Optional. EitherNone, which means the default precision for the backend, aPrecisionenum value (Precision.DEFAULT,Precision.HIGHorPrecision.HIGHEST) or a tuple of twoPrecisionenums indicating precision oflhs`andrhs.preferred_element_type (
Optional[Any]) β Optional. EitherNone, which means the default accumulation type for the input types, or a datatype, indicating to accumulate results to and return a result with that datatype.
- Return type
- Returns
An array containing the convolution result.