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Contents
# We use a generic interface for methods (*args, **options)
# and this class to determine the C++ method to call
#
# This is needed since LibTorch uses function overloading,
# which isn't available in Ruby or Python
#
# PyTorch uses this approach, but the parser/dispatcher is written in C++
#
# We could generate Ruby methods directly, but an advantage of this approach is
# arguments and keyword arguments can be used interchangably like in Python,
# making it easier to port code
module Torch
module Native
module Dispatcher
class << self
def bind
functions = Generator.grouped_functions
bind_functions(::Torch, :define_singleton_method, functions[:torch])
bind_functions(::Torch::Tensor, :define_method, functions[:tensor])
bind_functions(::Torch::NN, :define_singleton_method, functions[:nn])
end
def bind_functions(context, def_method, functions)
functions.group_by(&:ruby_name).sort_by { |g, _| g }.each do |name, funcs|
if def_method == :define_method
funcs.map! { |f| Function.new(f.function) }
funcs.each { |f| f.args.reject! { |a| a[:name] == "self" } }
end
defined = def_method == :define_method ? context.method_defined?(name) : context.respond_to?(name)
next if defined && name != "clone"
parser = Parser.new(funcs)
context.send(def_method, name) do |*args, **options|
result = parser.parse(args, options)
raise ArgumentError, result[:error] if result[:error]
send(result[:name], *result[:args])
end
end
end
end
end
end
end
Torch::Native::Dispatcher.bind
Version data entries
18 entries across 18 versions & 1 rubygems