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TellMeStepOrLossHook Constructor

Description

Constructs an object of the TellMeStepOrLossHook class. TellMeStepOrLossHook is used to notify the bottom-layer software of the serial number of the current step and the total number of steps or the current loss and the target loss.

Prototype

def __init__(self,step=None,total_step=None,loss=None,final_loss=None)

Options

Option

Input/Output

Description

step

Input

Tensor name of the current step.

total_step

Input

Total number of training steps of the training script.

loss

Input

Tensor name of the current loss.

final_loss

Input

Target loss of the training script.

Returns

An object of the TellMeStepOrLossHook class

Restrictions

The bottom-layer software is notified of the serial number of step or loss each time the number of Iterations_per_loops increases. When Iterations_per_loop is greater than 1, the bottom-layer software cannot be notified of the preceding information for every increase. As a result, some bottom-layer software functions that depend on the hook function result may be affected.

Examples

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from npu_bridge.npu_init import *
est = NPUEstimator(
        model_fn=model_fn,
        config=config,
        params=params)
hooks = []
max_steps = 10000
# Splitting by step: In this example, the tensor name of the current step is global_step:0, and the total number of steps is 10000. Set this option based on the actual tensor name and total number of steps.
my_hook = TellMeStepOrLossHook(step='global_step:0', total_step=max_steps)
# Splitting by loss: In this example, the tensor name of the loss is loss:0, and the target loss is 7.1. Configure this option based on the tensor name of the actual loss and the value of the target loss.
# my_hook = TellMeStepOrLossHook(loss='loss:0', final_loss=7.1)
hooks.append(my_hook)
# Start training.
est.train(
          input_fn=imagenet_train.input_fn,
          max_steps=max_steps 
          hooks=hooks)