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# File 'lib/tensor_stream/math_gradients.rb', line 25
def self._propagate(grad, tensor, stop_tensor, nodes_to_compute, stop_gradients = [])
return grad if stop_tensor.equal?(tensor)
return nil if stop_gradients && _include?(stop_gradients, tensor)
return nil unless tensor.is_a?(Operation)
computed_op = _compute_derivative(tensor, grad)
if computed_op.is_a?(Array)
grads = computed_op.each_with_index.collect { |op_grad, index|
next if op_grad.nil?
next unless nodes_to_compute.include?(tensor.inputs[index].name)
_propagate(op_grad, tensor.inputs[index], stop_tensor, nodes_to_compute, stop_gradients)
}.compact
return nil if grads.empty?
grads.size > 1 ? ts.add_n(grads) : grads[0]
else
if computed_op.nil?
return nil
end
_propagate(computed_op, tensor.inputs[0], stop_tensor, nodes_to_compute, stop_gradients)
end
end
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