Module: Tensorflow::Ops

Included in:
Tensorflow
Defined in:
lib/tensorflow/ops/ops.rb,
lib/tensorflow/ops/gradients.rb

Class Method Summary collapse

Instance Method Summary collapse

Class Method Details

.broadcast_mul(vector, matrix) ⇒ Object 



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# File 'lib/tensorflow/ops/gradients.rb', line 3

def self.broadcast_mul(vector, matrix)
  vector = Tensorflow.expand_dims(vector, -1)
  vector * matrix
end

Instance Method Details

#cast(x, destination_dtype, source_dtype: nil, truncate: false) ⇒ Object 



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

def cast(x, destination_dtype, source_dtype: nil, truncate: false)
  RawOps.cast(x, srct: source_dtype, dstt: destination_dtype, truncate: truncate)
end

#constant(value, dtype: nil, shape: [], name: 'Const') ⇒ Object 



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# File 'lib/tensorflow/ops/ops.rb', line 8

def constant(value, dtype: nil, shape: [], name: 'Const')
  tensor = value.is_a?(Tensor) ? value : Tensor.new(value, dtype: dtype, shape: shape)
  RawOps.const(value: tensor, dtype: tensor.dtype, name: name)
end

#expand_dims(input, axis) ⇒ Object 



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# File 'lib/tensorflow/ops/ops.rb', line 13

def expand_dims(input, axis)
  RawOps.expand_dims(input, axis)
end

#fill(dims, value, dtype: nil) ⇒ Object 



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# File 'lib/tensorflow/ops/ops.rb', line 17

def fill(dims, value, dtype: nil)
  RawOps.fill(dims, value, typeT: dtype)
end

#identity(input) ⇒ Object 



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# File 'lib/tensorflow/ops/ops.rb', line 21

def identity(input)
  RawOps.identity(input)
end

#ones(dims, dtype: :float) ⇒ Object 



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# File 'lib/tensorflow/ops/ops.rb', line 25

def ones(dims, dtype: :float)
  fill(dims, 1, dtype: dtype)
end

#pack(values, n: nil, typeT: nil, axis: 0) ⇒ Object 



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# File 'lib/tensorflow/ops/ops.rb', line 29

def pack(values, n: nil, typeT: nil, axis: 0)
  typeT ||= TensorData.figure_dtype(values)
  n ||= values.count
  RawOps.pack(values, n: n, typeT: typeT, axis: axis)
end

#placeholder(dtype, name: 'Placeholder', shape: nil) ⇒ Object 



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# File 'lib/tensorflow/ops/ops.rb', line 35

def placeholder(dtype, name: 'Placeholder', shape: nil)
  RawOps.placeholder(dtype: dtype, shape: shape, name: name)
end

#prevent_gradient(input, typeT: nil, message: "") ⇒ Object 



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# File 'lib/tensorflow/ops/ops.rb', line 39

def prevent_gradient(input, typeT: nil, message: "")
  RawOps.prevent_gradient(input, typeT: typeT, message: message, name: "PreventGradient")
end

#range(start, limit = nil, delta = 1) ⇒ Object 



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# File 'lib/tensorflow/ops/ops.rb', line 47

def range(start, limit = nil, delta = 1)
  unless limit
    limit = start
    start = 0
  end
  RawOps.range(start, limit, delta)
end

#rank(input, typeT: nil) ⇒ Object 



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# File 'lib/tensorflow/ops/ops.rb', line 43

def rank(input, typeT: nil)
  RawOps.rank(input, typeT: typeT)
end

#reshape(tensor, shape) ⇒ Object 



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# File 'lib/tensorflow/ops/ops.rb', line 55

def reshape(tensor, shape)
  RawOps.reshape(tensor, shape, typeT: tensor.output_types.first)
end

#shape(input, out_type) ⇒ Object 



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# File 'lib/tensorflow/ops/ops.rb', line 59

def shape(input, out_type)
  RawOps.shape(input, out_type: out_type)
end

#split(value, split_dim, num_split: nil, typeT: nil) ⇒ Object 



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# File 'lib/tensorflow/ops/ops.rb', line 63

def split(value, split_dim, num_split: nil, typeT: nil)
  RawOps.split(split_dim, value, num_split: num_split, typeT: typeT)
end

#split_v(value, size_splits, split_dim = 0, num_split: nil, typeT: nil, tlen: nil) ⇒ Object 



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# File 'lib/tensorflow/ops/ops.rb', line 67

def split_v(value, size_splits, split_dim=0, num_split: nil, typeT: nil, tlen: nil)
  num_split ||= size_splits.length
  RawOps.split_v(value, size_splits, split_dim, num_split: num_split, typeT: typeT, tlen: tlen)
end

#squeeze(input, axis: nil) ⇒ Object 



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# File 'lib/tensorflow/ops/ops.rb', line 72

def squeeze(input, axis: nil)
  RawOps.squeeze(input, squeeze_dims: axis)
end

#timestamp ⇒ Object 



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# File 'lib/tensorflow/ops/ops.rb', line 76

def timestamp
  RawOps.timestamp
end

#transpose(x, perm: [1, 0]) ⇒ Object 



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# File 'lib/tensorflow/ops/ops.rb', line 80

def transpose(x, perm: [1, 0])
  RawOps.transpose(x, perm)
end

#where(condition, x: nil, y: nil) ⇒ Object 



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# File 'lib/tensorflow/ops/ops.rb', line 84

def where(condition, x: nil, y: nil)
  if x.nil? && y.nil?
    RawOps.where(condition)
  elsif x && y
    RawOps.select_v2(condition, x, y)
  else
    raise(Error::InvalidArgumentError, "x and y must both be non nil or both be nil")
  end
end

#zeros(dims, dtype: :float) ⇒ Object 



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

def zeros(dims, dtype: :float)
  fill(dims, 0, dtype: dtype)
end

#zeros_like(x) ⇒ Object 



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

def zeros_like(x)
  RawOps.zeros_like(x)
end