auto_channel_prune_search

Description

This API is used to calculate the sparsity sensitivity (affecting accuracy) and sparsity gain (affecting performance) of each channel based on the user model. Then the search policy searches for the optimal layer-by-layer channel sparsity ratio based on the input to balance accuracy and performance. Finally, a configuration file is generated.

Constraints

None

Prototype

auto_channel_prune_search(graph, output_nodes, config, input_data, output_cfg, sensitivity, search_alg)

Parameter Description

Option	Input/Return	Meaning	Restriction
graph	Input	tf.Graph training graph that contains automatic differentiation.	A tf.Graph.
output_nodes	Input	Name of the model output node.	A list of strings.
config	Input	Path of the auto channel pruning search configuration file. Simplified configuration file generated based on AutoChannelPruneConfig in the basic_info.proto file. The basic_info.proto file is stored in Installation directory /amct_tensorflow/proto/basic_info.proto. For details about the parameters in the basic_info.proto file and the example of the generated auto channel pruning search configuration file, see Simplified Configuration File for Auto Channel Pruning Search.	A string
input_data	Input	Calibration data provided by the user.	Data type: list. The content is the corresponding feed_dict data.
output_cfg	Input/Return	Path of the output channel pruning configuration file.	A string
sensitivity	Input	Sensitivity calculation method.	A string Subclass of SensitivityBase. string indicates an existing method. Currently, the value can be TaylorLossSensitivity. The subclass is the instantiation of the subclass of SensitivityBase and can be inherited and defined by users. The default value is TaylorLossSensitivity.
search_alg	Input	Method of searching for channels to be sparsified.	A string Subclass of SearchChannelBase. string indicates an existing method. Currently, the value can be GreedySearch. The subclass is the instantiation of the subclass of SearchChannelBase and can be inherited and defined by users. The default value is GreedySearch.

Returns

None

Outputs

Auto channel pruning configuration file.

This file needs to be transferred to the channel sparsity API for subsequent services.

Examples

import amct_tensorflow as amct
# Construct feed_dict data.
input_data = np.random.uniform(-10, 10, (2, 14, 14, 64)).astype(np.str_)
feed_dict = [{'input:0': input_data}]

amct.auto_channel_prune_search(
     graph=graph, 
     output_nodes=[operation_name_1, operation_name_2],
     config='./tmp/sample.cfg', 
     input_data=feed_dict,  
     output_cfg='./tmp/output.cfg', 
     sensitivity='TaylorLossSensitivity', 
     search_alg='GreedySearch')

Parent topic: Auto Channel Pruning Search APIs