Class: TensorStream::Operation

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

Overview

TensorStream class that defines an operation

Direct Known Subclasses

ControlFlow, DynamicStitch

Instance Attribute Summary collapse

Attributes inherited from Tensor

#given_name, #graph, #internal, #native_buffer, #source, #value

Instance Method Summary collapse

Methods included from OpHelper

#_op, #cons, #format_source, #fp_type?, #i_cons, #i_op, #i_var, #int_type?, #reduced_shape, #shape_eval, #shape_full_specified, #shapes_fully_specified_and_equal

Methods inherited from Tensor

#auto_math, #breakpoint!, cast_dtype, #collect, detect_type, #dtype, #eval, #first, #internal?, #print!, reset_counters, #to_a, #to_f, #to_i

Methods included from TensorMixins

#!=, #%, #*, #**, #+, #-, #-@, #/, #<, #<=, #==, #>, #>=, #[], #and, #cast, #ceil, #dot, #floor, #log, #matmul, #reduce, #reshape, #round, #var, #zero?

Constructor Details

#initialize(graph, inputs: [], options: {}) ⇒ Operation

Returns a new instance of Operation.



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# File 'lib/tensor_stream/operation.rb', line 10

def initialize(graph, inputs: [], options: {})
  @consumers = Set.new
  @outputs = []
  @op = self
  @graph = graph
  @inputs = inputs
  @options = options
end

Instance Attribute Details

#breakpoint ⇒ Object

Returns the value of attribute breakpoint.



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

def breakpoint
  @breakpoint
end

#consumers ⇒ Object

Returns the value of attribute consumers.



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

def consumers
  @consumers
end

#data_type ⇒ Object (readonly)

Returns the value of attribute data_type.



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# File 'lib/tensor_stream/operation.rb', line 8

def data_type
  @data_type
end

#device ⇒ Object

Returns the value of attribute device.



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

def device
  @device
end

#inputs ⇒ Object

Returns the value of attribute inputs.



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

def inputs
  @inputs
end

#is_const ⇒ Object (readonly)

Returns the value of attribute is_const.



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# File 'lib/tensor_stream/operation.rb', line 8

def is_const
  @is_const
end

#name ⇒ Object

Returns the value of attribute name.



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

def name
  @name
end

#operation ⇒ Object

Returns the value of attribute operation.



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

def operation
  @operation
end

#options ⇒ Object (readonly)

Returns the value of attribute options.



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# File 'lib/tensor_stream/operation.rb', line 8

def options
  @options
end

#outputs ⇒ Object (readonly)

Returns the value of attribute outputs.



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# File 'lib/tensor_stream/operation.rb', line 8

def outputs
  @outputs
end

#rank ⇒ Object

Returns the value of attribute rank.



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

def rank
  @rank
end

#shape ⇒ Object (readonly)

Returns the value of attribute shape.



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# File 'lib/tensor_stream/operation.rb', line 8

def shape
  @shape
end

Instance Method Details

#const_value ⇒ Object 



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

def const_value
  @options ? @options[:value] : nil
end

#container_buffer ⇒ Object 



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# File 'lib/tensor_stream/operation.rb', line 41

def container_buffer
  @options[:container] ? @options[:container].buffer : nil
end

#infer_const ⇒ Object 



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# File 'lib/tensor_stream/operation.rb', line 57

def infer_const
  return false if breakpoint

  case operation
  when :random_standard_normal, :random_uniform, :truncated_normal, :glorot_uniform, :print, :check_numerics
    false
  when :const
    true
  when :placeholder
    false
  when :variable_v2, :assign, :assign_add, :assign_sub
    false
  else
    non_const = @inputs.compact.find { |input| !input.is_const }
    non_const ? false : true
  end
end

#inspect ⇒ Object 



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# File 'lib/tensor_stream/operation.rb', line 19

def inspect
  "Op(#{operation} name: #{name} shape: #{@shape || "?"} data_type: #{data_type})"
end

#op ⇒ Object 



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# File 'lib/tensor_stream/operation.rb', line 244

def op
  self
end

#run ⇒ Object 



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# File 'lib/tensor_stream/operation.rb', line 240

def run
  eval
end

#set_data_type(passed_data_type) ⇒ Object 



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# File 'lib/tensor_stream/operation.rb', line 79

def set_data_type(passed_data_type)
  case operation
  when :where
    @inputs[1].data_type
  when :case
    if @inputs[2]
      @inputs[2].data_type
    else
      @inputs[1].data_type
    end
  when :case_grad
    @inputs[2].data_type
  when :placeholder, :variable_v2, :const
    options[:data_type]
  when :fill
    @inputs[1].data_type
  when :logical_and
    :boolean
  when :shape, :rank, :shape_n
    options[:out_type] || :int32
  when :zeros, :ones
    options[:dtype] || :float32
  when :random_standard_normal, :random_uniform, :glorot_uniform, :truncated_normal
    passed_data_type || :float32
  when :concat
    @inputs[1].data_type
  when :conv2d_backprop_input
    @inputs[1].data_type
  when :index
    if @inputs[0].is_a?(ControlFlow)
      if @inputs[1].is_const
        @inputs[0].inputs[@inputs[1].const_value].data_type
      else
        :unknown
      end
    else
      @inputs[0].data_type
    end
  else
    OpMaker.infer_data_type(self, self, passed_data_type)
  end
end

#set_input(index, value) ⇒ Object 



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

def set_input(index, value)
  @inputs[index] = value
  @shape = TensorShape.new(TensorStream::InferShape.infer_shape(self))
  @rank = @shape.rank
  @is_const = infer_const
  @data_type = set_data_type(@options[:data_type])
end

#set_name ⇒ Object 



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# File 'lib/tensor_stream/operation.rb', line 75

def set_name
  @operation.to_s
end

#set_option(key, value) ⇒ Object 



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# File 'lib/tensor_stream/operation.rb', line 53

def set_option(key, value)
  @options.merge!(key.to_sym => value)
end

#to_h ⇒ Object 



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# File 'lib/tensor_stream/operation.rb', line 27

def to_h
  {
    op: operation.to_s,
    name: name.to_s,
    data_type: @data_type,
    inputs: @inputs.map(&:name),
    attrs: serialize_options,
  }
end

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



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# File 'lib/tensor_stream/operation.rb', line 122

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 :mat_mul
          "#{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 :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", Array.new(cur_depth + 1) { " " }, out].flatten.join
end

#to_s ⇒ Object 



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# File 'lib/tensor_stream/operation.rb', line 23

def to_s
  @name
end