tools

static_params_to_dygraph(model, static_tensor_dict)[source]

Simple tool for convert static paramters to dygraph paramters dict.

NOTE The model must both support static graph and dygraph mode.

Parameters
  • model (nn.Layer) – the model of a neural network.

  • static_tensor_dict (string) – path of which locate the saved paramters in static mode. Usualy load by paddle.static.load_program_state.

Returns

a state dict the same as the dygraph mode.

Return type

[tensor dict]

dygraph_params_to_static(model, dygraph_tensor_dict, topo=None)[source]

Simple tool for convert dygraph paramters to static paramters dict.

NOTE The model must both support static graph and dygraph mode.

Parameters
  • model (nn.Layer) – the model of a neural network.

  • dygraph_tensor_dict (string) – path of which locate the saved paramters in static mode.

Returns

a state dict the same as the dygraph mode.

Return type

[tensor dict]

class TimeCostAverage[source]

Bases: object

Simple tool for calcluating time average cost in the process of training and inferencing.

reset()[source]

Reset the recoder state, and reset the cnt to zero.

record(usetime)[source]

Recoding the time cost in current step and accumulating the cnt.

get_average()[source]

Returning the average time cost after the start of training.

get_env_device()[source]

Return the device name of running enviroment.

compare_version(version, pair_version)[source]
Parameters
  • version (str) – The first version string needed to be compared. The format of version string should be as follow : “xxx.yyy.zzz”.

  • pair_version (str) – The second version string needed to be compared. The format of version string should be as follow : “xxx.yyy.zzz”.

Returns

The result of comparasion. 1 means version > pair_version; 0 means

version = pair_version; -1 means version < pair_version.

Return type

int

Examples

>>> compare_version("2.2.1", "2.2.0")
>>> 1
>>> compare_version("2.2.0", "2.2.0")
>>> 0
>>> compare_version("2.2.0-rc0", "2.2.0")
>>> -1
>>> compare_version("2.3.0-rc0", "2.2.0")
>>> 1
get_bool_ids_greater_than(probs, limit=0.5, return_prob=False)[source]

Get idx of the last dimension in probability arrays, which is greater than a limitation.

Parameters
  • probs (List[List[float]]) – The input probability arrays.

  • limit (float) – The limitation for probability.

  • return_prob (bool) – Whether to return the probability

Returns

The index of the last dimension meet the conditions.

Return type

List[List[int]]

get_span(start_ids, end_ids, with_prob=False)[source]

Get span set from position start and end list.

Parameters
  • start_ids (List[int]/List[tuple]) – The start index list.

  • end_ids (List[int]/List[tuple]) – The end index list.

  • with_prob (bool) – If True, each element for start_ids and end_ids is a tuple aslike: (index, probability).

Returns

The span set without overlapping, every id can only be used once .

Return type

set