Class: Tensorflow::Tensor

Inherits:
Object
  • Object
show all
Includes:
Operators, TensorMixin
Defined in:
lib/tensorflow/tensor.rb

Class Method Summary collapse

Instance Method Summary collapse

Methods included from TensorMixin

#numo, #shape

Methods included from Operators

#%, #*, #**, #+, #-, #-@, #/

Constructor Details

#initialize(value, dtype: nil, shape: []) ⇒ Tensor

Returns a new instance of Tensor.



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# File 'lib/tensorflow/tensor.rb', line 48

def initialize(value, dtype: nil, shape: [])
  value = case value
            when Numo::NArray
              value
            when Array
              # We convert all arrays to narrays. This makes it a lot easier to support multidimensional arrays
              result = Numo::NArray.cast(value)
            else
              TensorData.value_with_shape(value, dtype, shape)
          end

  tensor_data = TensorData.new(value, dtype: dtype, shape: shape)
  dtype = tensor_data.dtype
  shape = tensor_data.shape

  if shape && shape.size > 0
    dims_ptr = ::FFI::MemoryPointer.new(:int64, shape.size)
    dims_ptr.write_array_of_int64(shape)
  else
    dims_ptr = nil
  end

  @pointer = FFI.TF_NewTensor(dtype,
                              dims_ptr, shape ? shape.size : 0,
                              tensor_data, tensor_data.byte_size,
                              TensorData::Deallocator, nil)

  ObjectSpace.define_finalizer(self, self.class.finalize(@pointer))
end

Class Method Details

.finalize(pointer) ⇒ Object 



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# File 'lib/tensorflow/tensor.rb', line 6

def self.finalize(pointer)
  proc do
    FFI.TF_DeleteTensor(pointer)
  end
end

.from_pointer(pointer) ⇒ Object 



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# File 'lib/tensorflow/tensor.rb', line 41

def self.from_pointer(pointer)
  result = self.allocate
  result.instance_variable_set(:@pointer, pointer)
  ObjectSpace.define_finalizer(result, self.finalize(pointer))
  result
end

.from_proto(proto) ⇒ Object 



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# File 'lib/tensorflow/tensor.rb', line 27

def self.from_proto(proto)
  proto = proto.is_a?(TensorProto) ? proto : TensorProto.decode(proto)
  shape = proto.tensor_shape.dim.map(&:size)
  dtype = FFI::DataType[DataType.resolve(proto.dtype)]
  numo_klass = TensorData::DTYPE_TO_NUMO_TYPE_MAP[dtype]
  value = if shape.empty?
            array = numo_klass.from_binary(proto.tensor_content)
            array[0]
           else
             numo_klass.from_binary(proto.tensor_content, shape)
           end
  self.new(value, dtype:dtype, shape:shape)
end

.from_value(value, dtype: nil) ⇒ Object 



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# File 'lib/tensorflow/tensor.rb', line 12

def self.from_value(value, dtype: nil)
  case value
    when Tensor
      value
    when Graph::Operation
      value
    when Eager::TensorHandle
      value.tensor
    when Data::Dataset
      value.variant_tensor
    else
      Tensor.new(value, dtype: dtype)
  end
end

Instance Method Details

#byte_size ⇒ Object 



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# File 'lib/tensorflow/tensor.rb', line 94

def byte_size
  FFI.TF_TensorByteSize(self)
end

#data ⇒ Object 



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# File 'lib/tensorflow/tensor.rb', line 103

def data
  TensorData.from_pointer(FFI.TF_TensorData(self), self.byte_size, self.dtype, self.shape)
end

#dtype ⇒ Object 



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# File 'lib/tensorflow/tensor.rb', line 82

def dtype
  FFI.TF_TensorType(self)
end

#inspect ⇒ Object 



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# File 'lib/tensorflow/tensor.rb', line 98

def inspect
  inspection = %w(numo shape dtype).map { |v| "#{v}: #{send(v).inspect}"}
  "#<#{self.class} #{inspection.join(", ")}>"
end

#to_ptr ⇒ Object 



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# File 'lib/tensorflow/tensor.rb', line 90

def to_ptr
  @pointer
end

#to_s ⇒ Object 



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# File 'lib/tensorflow/tensor.rb', line 86

def to_s
  inspect
end

#value ⇒ Object 



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# File 'lib/tensorflow/tensor.rb', line 78

def value
  self.data.value
end