tf.contrib.training.parse_values

tf.contrib.training.parse_values(
    values,
    type_map,
    ignore_unknown=False
)

Defined in tensorflow/contrib/training/python/training/hparam.py.

Parses hyperparameter values from a string into a python map.

values is a string containing comma-separated name=value pairs. For each pair, the value of the hyperparameter named name is set to value.

If a hyperparameter name appears multiple times in values, a ValueError is raised (e.g. 'a=1,a=2', 'a[1]=1,a[1]=2').

If a hyperparameter name in both an index assignment and scalar assignment, a ValueError is raised. (e.g. 'a=[1,2,3],a[0] = 1').

The hyperparameter name may contain '.' symbols, which will result in an attribute name that is only accessible through the getattr and setattr functions. (And must be first explicit added through add_hparam.)

WARNING: Use of '.' in your variable names is allowed, but is not well supported and not recommended.

The value in name=value must follows the syntax according to the type of the parameter:

  • Scalar integer: A Python-parsable integer point value. E.g.: 1, 100, -12.
  • Scalar float: A Python-parsable floating point value. E.g.: 1.0, -.54e89.
  • Boolean: Either true or false.
  • Scalar string: A non-empty sequence of characters, excluding comma, spaces, and square brackets. E.g.: foo, bar_1.
  • List: A comma separated list of scalar values of the parameter type enclosed in square brackets. E.g.: [1,2,3], [1.0,1e-12], [high,low].

When index assignment is used, the corresponding type_map key should be the list name. E.g. for "arr[1]=0" the type_map must have the key "arr" (not "arr[1]").

Args:

  • values: String. Comma separated list of name=value pairs where 'value' must follow the syntax described above.
  • type_map: A dictionary mapping hyperparameter names to types. Note every parameter name in values must be a key in type_map. The values must conform to the types indicated, where a value V is said to conform to a type T if either V has type T, or V is a list of elements of type T. Hence, for a multidimensional parameter 'x' taking float values, 'x=[0.1,0.2]' will parse successfully if type_map['x'] = float.
  • ignore_unknown: Bool. Whether values that are missing a type in type_map should be ignored. If set to True, a ValueError will not be raised for unknown hyperparameter type.

Returns:

A python map mapping each name to either: * A scalar value. * A list of scalar values. * A dictionary mapping index numbers to scalar values. (e.g. "x=5,L=[1,2],arr[1]=3" results in {'x':5,'L':[1,2],'arr':{1:3}}")

Raises:

  • ValueError: If there is a problem with input.
    • If values cannot be parsed.
    • If a list is assigned to a list index (e.g. 'a[1] = [1,2,3]').
    • If the same rvalue is assigned two different values (e.g. 'a=1,a=2', 'a[1]=1,a[1]=2', or 'a=1,a=[1]')