Class: TensorStream::Operation

Inherits:
Tensor
  • Object
show all
Defined in:
lib/tensor_stream/operation.rb

Overview

TensorStream class that defines an operation

Direct Known Subclasses

ControlFlow

Instance Attribute Summary collapse

Attributes inherited from Tensor

#breakpoint, #consumers, #data_type, #device, #given_name, #graph, #internal, #is_const, #native_buffer, #shape, #source, #value

Class Method Summary collapse

Instance Method Summary collapse

Methods inherited from Tensor

#!=, #*, #**, #+, #-, #-@, #/, #<, #<=, #==, #>, #>=, #[], #and, #auto_math, #breakpoint!, cast_dtype, #collect, detect_type, #dot, #dtype, #eval, #first, #internal?, #matmul, #print!, reset_counters, #to_a, #to_f, #to_i

Methods included from OpHelper

#_op, #cons, #dtype_eval, #format_source, #fp_type?, #i_cons, #i_op, #shape_eval, #val_to_dtype

Constructor Details

#initialize(operation, *args) ⇒ Operation

Returns a new instance of Operation.



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# File 'lib/tensor_stream/operation.rb', line 7

def initialize(operation, *args)
  options = if args.last.is_a?(Hash)
    args.pop
  else
    {}
  end

  inputs = args

  setup_initial_state(options)

  @operation = operation
  @rank = options[:rank] || 0
  @name = [@graph.get_name_scope, options[:name] || set_name].compact.reject(&:empty?).join('/')
  @internal = options[:internal]
  @given_name = @name

  @options = options

  @inputs = inputs.map { |i| options[:preserve_params_type] ? i : TensorStream.convert_to_tensor(i) }
  @data_type = set_data_type(options[:data_type])
  @is_const = infer_const
  @shape = TensorShape.new(infer_shape)
  @graph.add_node(self)
end

Instance Attribute Details

#inputs ⇒ Object

Returns the value of attribute inputs.



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# File 'lib/tensor_stream/operation.rb', line 4

def inputs
  @inputs
end

#name ⇒ Object

Returns the value of attribute name.



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# File 'lib/tensor_stream/operation.rb', line 4

def name
  @name
end

#operation ⇒ Object

Returns the value of attribute operation.



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# File 'lib/tensor_stream/operation.rb', line 4

def operation
  @operation
end

#options ⇒ Object

Returns the value of attribute options.



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# File 'lib/tensor_stream/operation.rb', line 4

def options
  @options
end

#outputs ⇒ Object (readonly)

Returns the value of attribute outputs.



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# File 'lib/tensor_stream/operation.rb', line 5

def outputs
  @outputs
end

#rank ⇒ Object

Returns the value of attribute rank.



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# File 'lib/tensor_stream/operation.rb', line 4

def rank
  @rank
end

Class Method Details

.empty_matrix?(input) ⇒ Boolean

Returns:

  • (Boolean) 


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# File 'lib/tensor_stream/operation.rb', line 45

def self.empty_matrix?(input)
  if input.is_a?(Array)
    input.each do |input|
      if input.is_a?(Array)
        return false unless empty_matrix?(input)
      elsif input != 0 || input != 0.0
        return false
      end
    end
  end

  true
end

Instance Method Details

#infer_const ⇒ Object 



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# File 'lib/tensor_stream/operation.rb', line 59

def infer_const
  return false if breakpoint
  case operation
  when :random_normal, :random_uniform, :glorot_uniform, :print
    false
  else
    non_const = @inputs.compact.find { |input| !input.is_const }
    non_const ? false : true
  end
end

#op ⇒ Object 



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# File 'lib/tensor_stream/operation.rb', line 226

def op
  self
end

#run ⇒ Object 



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# File 'lib/tensor_stream/operation.rb', line 222

def run
  eval
end

#set_data_type(passed_data_type) ⇒ Object 



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# File 'lib/tensor_stream/operation.rb', line 70

def set_data_type(passed_data_type)
  case operation
  when :greater, :less, :equal, :not_equal, :greater_equal, :less_equal, :logical_and
    :boolean
  when :shape, :rank
    :int32
  when :random_normal, :random_uniform, :glorot_uniform
    passed_data_type || :float32
  when :index
    if @inputs[0].is_a?(ControlFlow)

      if @inputs[1].is_const
        @inputs[0].inputs[@inputs[1].value].data_type
      else
        :unknown
      end
    else
      @inputs[0].data_type
    end
  else
    return passed_data_type if passed_data_type

    if @inputs[0]
      @inputs[0].data_type
    elsif @inputs[1]
      @inputs[1].data_type
    else
      :unknown
    end
  end
end

#to_h ⇒ Object 



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# File 'lib/tensor_stream/operation.rb', line 37

def to_h
  {
    op: operation,
    name: name,
    operands: hashify_tensor(inputs)
  }
end

#to_math(name_only = false, max_depth = 99, _cur_depth = 0) ⇒ Object 



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# File 'lib/tensor_stream/operation.rb', line 102

def to_math(name_only = false, max_depth = 99, _cur_depth = 0)
  return @name if max_depth.zero?

  sub_input = auto_math(inputs[0], name_only, max_depth - 1, _cur_depth + 1)
  sub_input2 = auto_math(inputs[1], name_only, max_depth - 1, _cur_depth + 1) if inputs[1]

  out = case operation
  when :argmax
    "argmax(#{sub_input},#{options[:axis]})"
  when :negate
    "-#{sub_input}"
  when :index
    "#{sub_input}[#{sub_input2}]"
  when :slice
    "#{sub_input}[#{sub_input2}]"
  when :assign_sub
    "(#{inputs[0] ? inputs[0].name : 'self'} -= #{auto_math(inputs[1], name_only, 1)})"
  when :assign_add
    "(#{inputs[0] ? inputs[0].name : 'self'} += #{auto_math(inputs[1], name_only, 1)})"
  when :assign
    "(#{inputs[0] ? inputs[0].name : 'self'} = #{auto_math(inputs[1], name_only, 1)})"
  when :sin, :cos, :tanh
    "#{operation}(#{sub_input})"
  when :add
    "(#{sub_input} + #{sub_input2})"
  when :sub
    "(#{sub_input} - #{sub_input2})"
  when :pow
    "(#{sub_input}^#{sub_input2})"
  when :div
    "(#{sub_input} / #{sub_input2})"
  when :mul
    if auto_math(inputs[0]) == 1
      sub_input2
    elsif auto_math(inputs[1]) == 1
      sub_input
    else
      "(#{sub_input} * #{sub_input2})"
    end
  when :sum
    "sum(|#{sub_input}|,  axis=#{sub_input2})"
  when :mean
    "mean(|#{sub_input}|, axis=#{sub_input2})"
  when :prod
    "prod(|#{sub_input}|,  axis=#{sub_input2})"
  when :gradients
    "gradient(#{sub_input})"
  when :stop_gradient
    sub_input
  when :matmul
    "#{sub_input}.matmul(#{sub_input2})"
  when :eye
    "eye(#{sub_input})"
  when :transpose
    "transpose(#{sub_input})"
  when :shape
    "#{sub_input}.shape"
  when :exp
    "e^#{sub_input})"
  when :ones
    "ones(#{sub_input})"
  when :ones_like
    "ones_like(#{sub_input})"
  when :flow_group
    "flow_group(#{inputs.collect { |i| auto_math(i, name_only, max_depth - 1, _cur_depth) }.join(',')})"
  when :zeros
    "zeros(#{sub_input})"
  when :reshape
    "reshape(#{sub_input},#{sub_input2})"
  when :rank
    "#{sub_input}.rank"
  when :cond
    "(#{auto_math(options[:pred], name_only, max_depth - 1, _cur_depth)} ? #{sub_input} : #{sub_input2})"
  when :less
    "#{sub_input} < #{sub_input2}"
  when :less_equal
    "#{sub_input} <= #{sub_input2}"
  when :greater
    "#{sub_input} > #{sub_input2}"
  when :greater_equal
    "#{sub_input} >= #{sub_input2}"
  when :square
    "#{sub_input}\u00B2"
  when :log
    "log(#{sub_input})"
  when :identity
    "identity(#{sub_input})"
  when :print
    "print(#{sub_input})"
  when :pad
    "pad(#{sub_input},#{auto_math(options[:paddings])})"
  when :equal
    "#{sub_input} == #{sub_input2}"
  when :not_equal
    "#{sub_input} != #{sub_input2}"
  when :logical_and
    "#{sub_input} && #{sub_input2}"
  when :sqrt
    "sqrt(#{sub_input})"
  when :log1p
    "log1p(#{sub_input})"
  when :zeros_like
    "zeros_like(#{sub_input})"
  when :where
    "where(#{auto_math(options[:pred], name_only, max_depth - 1, _cur_depth)}, #{sub_input}, #{sub_input2})"
  when :max
    "max(#{sub_input},#{sub_input2})"
  when :cast
    "cast(#{sub_input}, #{data_type})"
  when :broadcast_transform
    "broadcast_transform(#{sub_input},#{sub_input2})"
  when :broadcast_gradient_args
    "broadcast_transform(#{sub_input},#{sub_input2})"
  else
    "#{operation}(#{sub_input})" if sub_input
    "#{operation}(#{sub_input}, #{sub_input2})" if sub_input && sub_input2
  end
  ["\n",(_cur_depth + 1).times.collect { ' ' }, out].flatten.join
end

#to_s ⇒ Object 



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# File 'lib/tensor_stream/operation.rb', line 33

def to_s
  @name
end