It creates an input in the network: a place where data, such as features and labels, should be provided.

op_input_variable(shape, dtype = "float32", needs_gradient = FALSE,
  is_sparse = FALSE, dynamic_axes = c(get_default_batch_axis()),
  name = "")

Arguments

shape

- list of ints representing tensor shape integer vector for dimensions of input tensor

needs_gradient

logical whether to conduct backprop on the tensor

is_sparse

logical whether variable is sparse

dynamic_axes

list of dynamic axis (only a single axis can be dynamic, i.e., either batch axis or time axis)

Value

Variable https://www.cntk.ai/pythondocs/cntk.variables.html#cntk.variables.Variable

References

https://www.cntk.ai/pythondocs/cntk.ops.html#cntk.ops.input_variable