pysegcnn.core.models.UNet¶
-
class
pysegcnn.core.models.
UNet
(in_channels, nclasses, filters, skip, **kwargs)[source]¶ A slightly modified implementation of U-Net in PyTorch.
Important
Each convolution is followed by a batch normalization layer
Upsampling is implemented by a 2x2 max unpooling operation
- Attributes
- in_channelsint
Number of channels of the input images.
- nclassesint
Number of classes.
- kwargsdict [str]
Additional keyword arguments passed to
pysegcnn.core.layers.Conv2dSame
.- nfilterslist [int]
List of input channels to each convolutional block.
- skipbool
Whether to apply skip connections from the encoder to the decoder.
- epochint
Number of epochs the model was trained.
- encoder
pysegcnn.core.layers.Encoder
The convolutional encoder.
- decoder
pysegcnn.core.layers.Decoder
The convolutional decoder.
- classifier
pysegcnn.core.layers.Conv2dSame
The classification layer, a 1x1 convolution.
-
__init__
(in_channels, nclasses, filters, skip, **kwargs)[source]¶ Initialize.
- Parameters
- in_channelsint
Number of channels of the input images.
- nclassesint
Number of classes.
- filterslist [int]
List of input channels to each convolutional block.
- skipbool
Whether to apply skip connections from the encoder to the decoder.
- **kwargs: `dict` [`str`]
Additional keyword arguments passed to
pysegcnn.core.layers.Conv2dSame
.
Methods
__init__
(in_channels, nclasses, filters, …)Initialize.
add_module
(name, module)Adds a child module to the current module.
apply
(fn)Applies
fn
recursively to every submodule (as returned by.children()
) as well as self.bfloat16
()Casts all floating point parameters and buffers to
bfloat16
datatype.buffers
([recurse])Returns an iterator over module buffers.
children
()Returns an iterator over immediate children modules.
cpu
()Moves all model parameters and buffers to the CPU.
cuda
([device])Moves all model parameters and buffers to the GPU.
double
()Casts all floating point parameters and buffers to
double
datatype.eval
()Sets the module in evaluation mode.
extra_repr
()Set the extra representation of the module
float
()Casts all floating point parameters and buffers to float datatype.
forward
(x)Forward propagation of U-Net.
freeze
()Freeze the weights of a model.
half
()Casts all floating point parameters and buffers to
half
datatype.load
(state_file)Load a model state.
load_state_dict
(state_dict[, strict])Copies parameters and buffers from
state_dict
into this module and its descendants.modules
()Returns an iterator over all modules in the network.
named_buffers
([prefix, recurse])Returns an iterator over module buffers, yielding both the name of the buffer as well as the buffer itself.
named_children
()Returns an iterator over immediate children modules, yielding both the name of the module as well as the module itself.
named_modules
([memo, prefix])Returns an iterator over all modules in the network, yielding both the name of the module as well as the module itself.
named_parameters
([prefix, recurse])Returns an iterator over module parameters, yielding both the name of the parameter as well as the parameter itself.
parameters
([recurse])Returns an iterator over module parameters.
register_backward_hook
(hook)Registers a backward hook on the module.
register_buffer
(name, tensor[, persistent])Adds a buffer to the module.
register_forward_hook
(hook)Registers a forward hook on the module.
register_forward_pre_hook
(hook)Registers a forward pre-hook on the module.
register_parameter
(name, param)Adds a parameter to the module.
requires_grad_
([requires_grad])Change if autograd should record operations on parameters in this module.
save
(state_file, optimizer[, bands])Save the model state.
share_memory
()state_dict
([destination, prefix, keep_vars])Returns a dictionary containing a whole state of the module.
to
(*args, **kwargs)Moves and/or casts the parameters and buffers.
train
([mode])Sets the module in training mode.
type
(dst_type)Casts all parameters and buffers to
dst_type
.unfreeze
()Unfreeze the weights of a model.
zero_grad
()Sets gradients of all model parameters to zero.
Attributes
T_destination
dump_patches
state
Return the model state file.