Class: TensorStream::Session

Inherits:
Object
  • Object
show all
Includes:
StringHelper
Defined in:
lib/tensor_stream/session.rb

Overview

TensorStream class that defines a session

Instance Attribute Summary collapse

Class Method Summary collapse

Instance Method Summary collapse

Methods included from StringHelper

#camelize, #constantize, #symbolize_keys, #underscore

Constructor Details

#initialize(evaluator = nil, thread_pool_class: Concurrent::ImmediateExecutor, log_device_placement: false, profile_enabled: false, evaluator_options: {}) ⇒ Session

Returns a new instance of Session.



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# File 'lib/tensor_stream/session.rb', line 9

def initialize(evaluator = nil, thread_pool_class: Concurrent::ImmediateExecutor, log_device_placement: false, profile_enabled: false, evaluator_options: {})
  @thread_pool = thread_pool_class.new
  @closed = false
  @session_cache = {}
  @randomizer = {}
  @log_device_placement = log_device_placement
  @evaluator_options = evaluator_options.merge(profile_enabled: profile_enabled)
  get_evaluator_classes(evaluator)
  @evaluators = {}
end

Instance Attribute Details

#closed ⇒ Object (readonly)

Returns the value of attribute closed.



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# File 'lib/tensor_stream/session.rb', line 6

def closed
  @closed
end

#last_session_context ⇒ Object (readonly)

Returns the value of attribute last_session_context.



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# File 'lib/tensor_stream/session.rb', line 6

def last_session_context
  @last_session_context
end

#randomizer ⇒ Object

Returns the value of attribute randomizer.



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

def randomizer
  @randomizer
end

#session_cache ⇒ Object (readonly)

Returns the value of attribute session_cache.



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# File 'lib/tensor_stream/session.rb', line 6

def session_cache
  @session_cache
end

#target ⇒ Object (readonly)

Returns the value of attribute target.



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# File 'lib/tensor_stream/session.rb', line 6

def target
  @target
end

Class Method Details

.default_session ⇒ Object 



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# File 'lib/tensor_stream/session.rb', line 28

def self.default_session
  @session ||= Session.new
end

Instance Method Details

#assign_evaluator(tensor) ⇒ Object 



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# File 'lib/tensor_stream/session.rb', line 137

def assign_evaluator(tensor)
  device = @evaluator_classes.map { |klass|
    next nil if tensor.is_a?(Operation) && !klass.ops.include?(tensor.operation.to_sym)
    next klass.default_device if tensor.device.nil?

    klass.query_device(tensor.device)
  }.compact.first

  raise "no evaluator available to execute #{tensor.operation}" if device.nil?

  key = "#{device.evaluator}/#{device.name}"
  if @evaluators.key?(key)
    @evaluators[key]
  else
    @evaluators[key] = [device, device.evaluator.new(self, device)]
  end
end

#clear_session_cache ⇒ Object 



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# File 'lib/tensor_stream/session.rb', line 24

def clear_session_cache
  @session_cache = {}
end

#close ⇒ Object 



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# File 'lib/tensor_stream/session.rb', line 91

def close
  # unlink resources to save memory
  @last_session_context = nil
  @session_cache = {}
  @closed = true
end

#closed? ⇒ Boolean

Returns:

  • (Boolean) 


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# File 'lib/tensor_stream/session.rb', line 98

def closed?
  @closed
end

#delegate_to_evaluator(tensor_arr, session_context, context) ⇒ Object 



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# File 'lib/tensor_stream/session.rb', line 123

def delegate_to_evaluator(tensor_arr, session_context, context)
  if tensor_arr.is_a?(Array)
    tensor_arr.collect do |tensor|
      if tensor.is_a?(Array)
        delegate_to_evaluator(tensor, session_context, context)
      else
        run_with_session_context(tensor, session_context, context)
      end
    end
  else
    run_with_session_context(tensor_arr.op, session_context, context)
  end
end

#dump_internal_ops(tensor) ⇒ Object 



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

def dump_internal_ops(tensor)
  dump_ops(tensor, ->(_k, n) { n.is_a?(Tensor) && n.internal? })
end

#dump_ops(tensor, selector) ⇒ Object 



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# File 'lib/tensor_stream/session.rb', line 110

def dump_ops(tensor, selector)
  graph = tensor.graph
  graph.nodes.select { |k, v| selector.call(k, v) }.collect { |k, node|
    next unless @last_session_context[node.name]

    "#{k} #{node.to_math(true, 1)} = #{@last_session_context[node.name]}"
  }.compact
end

#dump_user_ops(tensor) ⇒ Object 



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# File 'lib/tensor_stream/session.rb', line 106

def dump_user_ops(tensor)
  dump_ops(tensor, ->(_k, n) { n.is_a?(Tensor) && !n.internal? })
end

#get_evaluator_classes(evaluators) ⇒ Object 



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# File 'lib/tensor_stream/session.rb', line 20

def get_evaluator_classes(evaluators)
  @evaluator_classes = TensorStream::EvaluatorUtils.get_evaluator_classes(evaluators)
end

#graph_ml(tensor, filename) ⇒ Object 



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# File 'lib/tensor_stream/session.rb', line 119

def graph_ml(tensor, filename)
  TensorStream::Graphml.new(self).serialize(tensor, filename)
end

#list_devices ⇒ Object 



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# File 'lib/tensor_stream/session.rb', line 83

def list_devices
  TensorStream::Evaluator.evaluators.collect { |_k, v|
    v[:class].query_supported_devices.collect do |device|
      device
    end
  }.flatten
end

#run(*args) ⇒ Object 



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# File 'lib/tensor_stream/session.rb', line 32

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

  @evaluator_options[:thread_pool] = @thread_pool
  @evaluator_options[:log_intermediates] = options[:log_intermediates]

  context = {
    _cache: @session_cache,
    _options: options.merge(@evaluator_options),
    profile: {step: 0, operations: {}},
  }

  # scan for placeholders and assign value
  options[:feed_dict]&.each_key do |k|
    if k.is_a?(Placeholder)
      ph = options[:feed_dict][k]
      context[k.name.to_sym] = ph.is_a?(Tensor) ? ph.op : ph
    elsif k.is_a?(String)
      target_graph = args[0].graph
      node = target_graph.get_node(k)
      raise "Cannot find placeholder with the name of #{k}" if node.operation != :placeholder

      context[k.to_sym] = options[:feed_dict][k]
    elsif k.is_a?(Operation) && k.operation == :placeholder
      context[k.name.to_sym] = options[:feed_dict][k]
    else
      raise "Invalid placeholder type passed key must be a string or a placeholder type"
    end
  end

  args.each { |t| prepare_evaluators(t, context) }
  @last_session_context = context

  if @log_device_placement
    context[:_cache][:placement].each do |k, v|
      puts "#{k} : #{v[0].name}"
    end
  end
  result = args.collect { |e|
    next e.value if e.is_a?(Tensor) && e.is_const && e.value

    value = delegate_to_evaluator(e, context, {})
    recursive_eval(value)
  }
  args.size == 1 ? result.first : result
end