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.
-
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