Module: GRX

Defined in:
lib/grx.rb,
lib/grx/nn.rb,
lib/grx/data.rb,
lib/grx/loss.rb,
lib/grx/c_api.rb,
lib/grx/optim.rb,
lib/grx/utils.rb,
lib/grx/errors.rb,
lib/grx/tensor.rb,
lib/grx/storage.rb,
lib/grx/version.rb,
lib/grx/serialization.rb

Defined Under Namespace

Modules: CAPI, Data, Loss, NN, Optim, Serialization, Utils Classes: DimensionError, Error, ShapeError, Storage, StorageError, Tensor

Constant Summary collapse

VERSION = 
"0.2.1"

Class Method Summary collapse

Class Method Details

.c_loaded? ⇒ Boolean

Returns:

  • (Boolean) 


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# File 'lib/grx.rb', line 54

def self.c_loaded?
  CAPI::LOADED
end

.mode ⇒ Object 



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# File 'lib/grx.rb', line 58

def self.mode
  CAPI::LOADED ? :c : :ruby
end

.ones(shape, requires_grad: false) ⇒ Object 



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# File 'lib/grx.rb', line 30

def self.ones(shape, requires_grad: false)
  Tensor.ones(shape, requires_grad: requires_grad)
end

.rand(shape, requires_grad: false) ⇒ Object 



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# File 'lib/grx.rb', line 34

def self.rand(shape, requires_grad: false)
  n = shape.reduce(1, :*)
  Tensor.create(Array.new(n) { ::Kernel.rand }, shape, requires_grad: requires_grad)
end

.randn(shape, requires_grad: false) ⇒ Object 



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# File 'lib/grx.rb', line 39

def self.randn(shape, requires_grad: false)
  # Box-Muller from Ruby (C backend executes faster via he_normal)
  n = shape.reduce(1, :*)
  data = []
  (n / 2.0).ceil.times do
    u1 = ::Kernel.rand
    u1 = ::Kernel.rand while u1 < 1e-15
    u2 = ::Kernel.rand
    r  = Math.sqrt(-2.0 * Math.log(u1))
    data << (r * Math.cos(2 * Math::PI * u2))
    data << (r * Math.sin(2 * Math::PI * u2))
  end
  Tensor.create(data.first(n), shape, requires_grad: requires_grad)
end

.simd_mode ⇒ Object 



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# File 'lib/grx.rb', line 62

def self.simd_mode
  CAPI.simd_mode
end

.tensor(data, shape, requires_grad: false) ⇒ Object

Quick factory helpers



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# File 'lib/grx.rb', line 22

def self.tensor(data, shape, requires_grad: false)
  Tensor.create(data, shape, requires_grad: requires_grad)
end

.zeros(shape, requires_grad: false) ⇒ Object 



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# File 'lib/grx.rb', line 26

def self.zeros(shape, requires_grad: false)
  Tensor.zeros(shape, requires_grad: requires_grad)
end