Class: Torch::NN::Module
- Inherits:
-
Object
show all
- Includes:
- Utils
- Defined in:
- lib/torch/nn/module.rb
Direct Known Subclasses
AdaptiveAvgPoolNd, AdaptiveMaxPoolNd, AvgPoolNd, BatchNorm, Bilinear, ConstantPadNd, ConvNd, CosineSimilarity, DropoutNd, Embedding, EmbeddingBag, Fold, GroupNorm, Hardshrink, Identity, LPPoolNd, LayerNorm, LeakyReLU, Linear, LocalResponseNorm, LogSigmoid, LogSoftmax, Loss, MaxPoolNd, MaxUnpoolNd, PReLU, PairwiseDistance, RNNBase, ReLU, ReflectionPadNd, ReplicationPadNd, Sequential, Sigmoid, Softmax, Softmax2d, Softmin, Softplus, Softshrink, Softsign, Tanh, Tanhshrink, Unfold
Instance Method Summary
collapse
Methods included from Utils
#_ntuple, #_pair, #_quadrupal, #_single, #_triple
Constructor Details
#initialize ⇒ Module
Returns a new instance of Module.
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# File 'lib/torch/nn/module.rb', line 6
def initialize
@training = true
@parameters = {}
@buffers = {}
@modules = {}
end
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Dynamic Method Handling
This class handles dynamic methods through the method_missing method
#method_missing(method, *args, &block) ⇒ Object
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# File 'lib/torch/nn/module.rb', line 239
def method_missing(method, *args, &block)
name = method.to_s
if named_parameters.key?(name)
named_parameters[name]
elsif named_buffers.key?(name)
named_buffers[name]
elsif named_modules.key?(name)
named_modules[name]
else
super
end
end
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Instance Method Details
#_apply(fn) ⇒ Object
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# File 'lib/torch/nn/module.rb', line 33
def _apply(fn)
children.each do |mod|
mod._apply(fn)
end
instance_variables.each do |key|
param = instance_variable_get(key)
if param.is_a?(Parameter)
param_applied = nil
Torch.no_grad do
param_applied = fn.call(param)
end
instance_variable_set(key, Parameter.new(param_applied, requires_grad: param.requires_grad))
if param.grad
grad_applied = nil
Torch.no_grad do
grad_applied = fn.call(param.grad)
end
instance_variable_get(key).grad = grad_applied.requires_grad!(param.grad.requires_grad)
end
end
end
self
end
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#add_module(name, mod) ⇒ Object
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# File 'lib/torch/nn/module.rb', line 28
def add_module(name, mod)
@modules[name] = mod
end
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#apply(fn) ⇒ Object
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# File 'lib/torch/nn/module.rb', line 62
def apply(fn)
children.each do |mod|
mod.apply(fn)
end
fn.call(self)
self
end
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#buffers ⇒ Object
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# File 'lib/torch/nn/module.rb', line 161
def buffers
named_buffers.values
end
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#call(*input, **kwargs) ⇒ Object
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# File 'lib/torch/nn/module.rb', line 104
def call(*input, **kwargs)
forward(*input, **kwargs)
end
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#children ⇒ Object
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# File 'lib/torch/nn/module.rb', line 169
def children
named_children.values
end
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#cpu ⇒ Object
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# File 'lib/torch/nn/module.rb', line 75
def cpu
_apply ->(t) { t.cpu }
end
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#cuda ⇒ Object
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# File 'lib/torch/nn/module.rb', line 71
def cuda
_apply ->(t) { t.cuda }
end
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#double ⇒ Object
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# File 'lib/torch/nn/module.rb', line 87
def double
_apply ->(t) { t.floating_point? ? t.double : t }
end
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#eval ⇒ Object
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# File 'lib/torch/nn/module.rb', line 201
def eval
train(false)
end
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#float ⇒ Object
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# File 'lib/torch/nn/module.rb', line 83
def float
_apply ->(t) { t.floating_point? ? t.float : t }
end
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#forward ⇒ Object
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# File 'lib/torch/nn/module.rb', line 13
def forward
raise NotImplementedError
end
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#half ⇒ Object
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# File 'lib/torch/nn/module.rb', line 91
def half
_apply ->(t) { t.floating_point? ? t.half : t }
end
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#inspect ⇒ Object
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# File 'lib/torch/nn/module.rb', line 225
def inspect
name = self.class.name.split("::").last
if children.empty?
"#{name}(#{})"
else
str = String.new
str << "#{name}(\n"
children.each do |name, mod|
str << " (#{name}): #{mod.inspect}\n"
end
str << ")"
end
end
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#load_state_dict(state_dict) ⇒ Object
TODO add strict option TODO match PyTorch behavior
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# File 'lib/torch/nn/module.rb', line 118
def load_state_dict(state_dict)
state_dict.each do |k, input_param|
k1, k2 = k.split(".", 2)
mod = named_modules[k1]
if mod.is_a?(Module)
param = mod.named_parameters[k2]
if param.is_a?(Parameter)
Torch.no_grad do
param.copy!(input_param)
end
else
raise Error, "Unknown parameter: #{k1}"
end
else
raise Error, "Unknown module: #{k1}"
end
end
nil
end
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#modules ⇒ Object
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# File 'lib/torch/nn/module.rb', line 185
def modules
named_modules.values
end
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#named_buffers ⇒ Object
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# File 'lib/torch/nn/module.rb', line 165
def named_buffers
@buffers || {}
end
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#named_children ⇒ Object
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# File 'lib/torch/nn/module.rb', line 173
def named_children
modules = {}
instance_variables.each do |name|
mod = instance_variable_get(name)
modules[name[1..-1]] = mod if mod.is_a?(Module)
end
@modules.each do |name, mod|
modules[name] = mod
end
modules
end
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#named_modules ⇒ Object
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# File 'lib/torch/nn/module.rb', line 189
def named_modules
{"" => self}.merge(named_children)
end
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#named_parameters(prefix: "", recurse: true) ⇒ Object
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# File 'lib/torch/nn/module.rb', line 144
def named_parameters(prefix: "", recurse: true)
params = {}
if recurse
named_children.each do |name, mod|
params.merge!(mod.named_parameters(prefix: "#{name}.", recurse: recurse))
end
end
instance_variables.each do |name|
param = instance_variable_get(name)
params[[prefix, name[1..-1]].join] = param if param.is_a?(Parameter)
end
@parameters.each do |name, param|
params[[prefix, name].join] = param if param
end
params
end
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#parameters ⇒ Object
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# File 'lib/torch/nn/module.rb', line 140
def parameters
named_parameters.values
end
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#register_buffer(name, tensor) ⇒ Object
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# File 'lib/torch/nn/module.rb', line 17
def register_buffer(name, tensor)
@buffers[name] = tensor
instance_variable_set("@#{name}", tensor)
end
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#register_parameter(name, param) ⇒ Object
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# File 'lib/torch/nn/module.rb', line 23
def register_parameter(name, param)
@parameters[name] = param
end
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#requires_grad!(requires_grad: true) ⇒ Object
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# File 'lib/torch/nn/module.rb', line 205
def requires_grad!(requires_grad: true)
parameters.each do |p|
p.requires_grad!(requires_grad)
end
self
end
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#respond_to?(method, include_private = false) ⇒ Boolean
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# File 'lib/torch/nn/module.rb', line 252
def respond_to?(method, include_private = false)
name = method.to_s
named_parameters.key?(name) || named_buffers.key?(name) || named_modules.key?(name) || super
end
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#share_memory ⇒ Object
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# File 'lib/torch/nn/module.rb', line 221
def share_memory
_apply ->(t) { t.share_memory! }
end
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#state_dict(destination: nil) ⇒ Object
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# File 'lib/torch/nn/module.rb', line 108
def state_dict(destination: nil)
destination ||= {}
named_parameters.each do |k, v|
destination[k] = v
end
destination
end
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#to(device) ⇒ Object
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# File 'lib/torch/nn/module.rb', line 96
def to(device)
convert = lambda do |t|
t.to(device)
end
_apply(convert)
end
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#train(mode = true) ⇒ Object
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# File 'lib/torch/nn/module.rb', line 193
def train(mode = true)
@training = mode
children.each do |mod|
mod.train(mode)
end
self
end
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#type(dst_type) ⇒ Object
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# File 'lib/torch/nn/module.rb', line 79
def type(dst_type)
_apply ->(t) { t.type(dst_type) }
end
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#zero_grad ⇒ Object
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# File 'lib/torch/nn/module.rb', line 212
def zero_grad
parameters.each do |param|
if param.grad
param.grad.detach!
param.grad.zero!
end
end
end
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