Module: TensorFlow::Utils

Included in:
TensorFlow
Defined in:
lib/tensorflow/utils.rb

Class Method Summary collapse

Class Method Details

.check_status(status) ⇒ Object 



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# File 'lib/tensorflow/utils.rb', line 4

def check_status(status)
  if FFI.TF_GetCode(status) != 0
    raise Error, FFI.TF_Message(status)
  end
end

.default_context ⇒ Object 



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# File 'lib/tensorflow/utils.rb', line 10

def default_context
  @default_context ||= Context.new
end

.download_file(url, dest) ⇒ Object 



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# File 'lib/tensorflow/utils.rb', line 108

def download_file(url, dest)
  uri = URI(url)

  temp_dir ||= File.dirname(Tempfile.new("tensorflow"))
  temp_path = "#{temp_dir}/#{Time.now.to_f}" # TODO better name

  # Net::HTTP automatically adds Accept-Encoding for compression
  # of response bodies and automatically decompresses gzip
  # and deflateresponses unless a Range header was sent.
  # https://ruby-doc.org/stdlib-2.6.4/libdoc/net/http/rdoc/Net/HTTP.html
  Net::HTTP.start(uri.host, uri.port, use_ssl: true) do |http|
    request = Net::HTTP::Get.new(uri)

    print("Downloading dataset")
    i = 0
    File.open(temp_path, "wb") do |f|
      http.request(request) do |response|
        response.read_body do |chunk|
          f.write(chunk)

          # print progress
          putc "." if i % 50 == 0
          i += 1
        end
      end
      puts # newline
    end
  end

  FileUtils.mv(temp_path, dest)
end

.execute(op_name, inputs = [], **attrs) ⇒ Object 



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# File 'lib/tensorflow/utils.rb', line 14

def execute(op_name, inputs = [], **attrs)
  context = default_context
  status = FFI.TF_NewStatus # TODO reuse status between ops?
  op = FFI.TFE_NewOp(context, op_name, status)
  check_status status

  attrs.each do |attr_name, attr_value|
    next if attr_value.nil?

    attr_name = attr_name.to_s

    is_list = ::FFI::MemoryPointer.new(:int)
    type = FFI.TFE_OpGetAttrType(op, attr_name, is_list, status)
    check_status status

    case FFI::AttrType[type]
    when :string
      FFI.TFE_OpSetAttrString(op, attr_name, attr_value, attr_value.bytesize)
    # when :int
    # when :float
    # when :bool
    when :type
      FFI.TFE_OpSetAttrType(op, attr_name, attr_value)
    when :shape
      # TODO set value properly
      FFI.TFE_OpSetAttrShape(op, attr_name, nil, 0, status)
      check_status status
    # when :tensor
    # when :placeholder
    # when :func
    else
      raise "Unknown type: #{FFI::AttrType[type]}"
    end
  end

  inputs.each do |input|
    input = TensorFlow.convert_to_tensor(input) unless input.respond_to?(:to_ptr)
    FFI.TFE_OpAddInput(op, input, status)
    check_status status
  end

  retvals = ::FFI::MemoryPointer.new(:pointer)
  num_retvals = ::FFI::MemoryPointer.new(:int)
  num_retvals.write_int(retvals.size)
  FFI.TFE_Execute(op, retvals, num_retvals, status)
  check_status status

  if num_retvals.read_int > 0
    handle = retvals.read_pointer
    type = FFI.TFE_TensorHandleDataType(handle)

    case FFI::DataType[type]
    when :resource
      handle
    else
      Tensor.new(pointer: handle)
    end
  end
ensure
  FFI.TF_DeleteStatus(status) if status
  FFI.TFE_DeleteOp(op) if op
end

.infer_type(value) ⇒ Object 



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# File 'lib/tensorflow/utils.rb', line 77

def infer_type(value)
  if value.all? { |v| v.is_a?(String) }
    :string
  elsif value.all? { |v| v == true || v == false }
    :bool
  elsif value.all? { |v| v.is_a?(Integer) }
    if value.all? { |v| v >= -2147483648 && v <= 2147483647 }
      :int32
    else
      :int64
    end
  elsif value.all? { |v| v.is_a?(Complex) }
    :complex128
  elsif value.all? { |v| v.is_a?(Numeric) }
    :float
  else
    raise Error, "Unable to infer data type"
  end
end

.load_dataset(path, url) ⇒ Object 



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# File 'lib/tensorflow/utils.rb', line 97

def load_dataset(path, url)
  # TODO handle this better
  raise "No HOME" unless ENV["HOME"]
  datasets_dir = "#{ENV["HOME"]}/.keras/datasets"
  FileUtils.mkdir_p(datasets_dir)

  path = "#{datasets_dir}/#{path}"
  Utils.download_file(url, path) unless File.exist?(path)
  Npy.load_npz(path)
end