jactorch.nn.cnn.functional#

Classes

`ConvBorderMode`
`ConvPaddingMode`

Functions

`compute_padding_shape`(input_size, ...)
`padding_nd`(input, kernel_size, padding, ...)

Class ConvBorderMode

class ConvBorderMode[source]#

Bases: JacEnum

__new__(value)#

classmethod assert_valid(value)#: Assert if the value is a valid choice.

classmethod choice_names()#: Returns the list of the name of all possible choices.

classmethod choice_objs()#: Returns the list of the object of all possible choices.

classmethod choice_values()#: Returns the list of the value of all possible choices.

classmethod from_string(string)[source]#

classmethod is_valid(value)#: Check if the value is a valid choice.

classmethod type_name()#: Return the type name of the enum.

CONSTANT = 'constant'#

REFLECT = 'reflect'#

REPLICATE = 'replicate'#

ZEROS = 'zeros'#

Class ConvPaddingMode

class ConvPaddingMode[source]#

Bases: JacEnum

__new__(value)#

classmethod assert_valid(value)#: Assert if the value is a valid choice.

classmethod choice_names()#: Returns the list of the name of all possible choices.

classmethod choice_objs()#: Returns the list of the object of all possible choices.

classmethod choice_values()#: Returns the list of the value of all possible choices.

classmethod from_string(value)#

Parameters:: value (str | JacEnum)
Return type:: JacEnum

classmethod is_valid(value)#: Check if the value is a valid choice.

classmethod type_name()#: Return the type name of the enum.

DEFAULT = 'default'#

SAME = 'same'#

TENSORFLOW = 'tensorflow'#

VALID = 'valid'#

Functions

compute_padding_shape(input_size, kernel_size, padding, mode)[source]#

padding_nd(input, kernel_size, padding, padding_mode, border_mode, use_pytorch_padding_mode=False)[source]#