megengine.module.Pad

class Pad(pad_witdth, mode='constant', constant_val=0.0)[源代码]

Pad is python warpper for padding opr in megbrain, can padding in random one of the max 7 dimensions. Supported constant, edge(replicate) and reflect mode, constatnt is the default mode.

Methods

apply(fn)

Applies function fn to all the modules within this module, including itself.

buffers([recursive])

Returns an iterable for the buffers of the module.

children(**kwargs)

Returns an iterable for all the submodules that are direct attributes of this module.

disable_quantize([value])

Sets module's quantize_disabled attribute and return module.

eval()

Sets training mode of all the modules within this module (including itself) to False.

forward(src)

load_state_dict(state_dict[, strict])

Loads a given dictionary created by state_dict into this module.

modules(**kwargs)

Returns an iterable for all the modules within this module, including itself.

named_buffers([prefix, recursive])

Returns an iterable for key buffer pairs of the module, where key is the dotted path from this module to the buffer.

named_children(**kwargs)

Returns an iterable of key-submodule pairs for all the submodules that are direct attributes of this module, where 'key' is the attribute name of submodules.

named_modules([prefix])

Returns an iterable of key-module pairs for all the modules within this module, including itself, where 'key' is the dotted path from this module to the submodules.

named_parameters([prefix, recursive])

Returns an iterable for key Parameter pairs of the module, where key is the dotted path from this module to the Parameter.

named_tensors([prefix, recursive])

Returns an iterable for key tensor pairs of the module, where key is the dotted path from this module to the tensor.

parameters([recursive])

Returns an iterable for the Parameter of the module.

register_forward_hook(hook)

Registers a hook to handle forward results.

register_forward_pre_hook(hook)

Registers a hook to handle forward inputs.

replace_param(params, start_pos[, seen])

Replaces module's parameters with params, used by ParamPack to

state_dict([rst, prefix, keep_var])

tensors([recursive])

Returns an iterable for the Tensor of the module.

train([mode, recursive])

Sets training mode of all the modules within this module (including itself) to mode.

zero_grad()

Sets all parameters' grads to zero