如何从 tf.estimator.Estimator 中获取最后一个 global_step
How to get the last global_step from an tf.estimator.Estimator
如何在 train(...)
完成后从 tf.estimator.Estimator
中获取最后一个 global_step
?例如,一个典型的基于 Estimator 的训练程序可能是这样设置的:
n_epochs = 10
model_dir = '/path/to/model_dir'
def model_fn(features, labels, mode, params):
# some code to build the model
pass
def input_fn():
ds = tf.data.Dataset() # obviously with specifying a data source
# manipulate the dataset
return ds
run_config = tf.estimator.RunConfig(model_dir=model_dir)
estimator = tf.estimator.Estimator(model_fn=model_fn, config=run_config)
for epoch in range(n_epochs):
estimator.train(input_fn=input_fn)
# Now I want to do something which requires to know the last global step, how to get it?
my_custom_eval_method(global_step)
只有 evaluate()
方法 returns 包含 global_step
作为字段的字典。如果出于某种原因我不能或不想使用此方法,我如何获得 global_step
?
只需在训练循环之前创建一个钩子:
class GlobalStepHook(tf.train.SessionRunHook):
def __init__(self):
self._global_step_tensor = None
self.value = None
def begin(self):
self._global_step_tensor = tf.train.get_global_step()
def after_run(self, run_context, run_values):
self.value = run_context.session.run(self._global_step_tensor)
def __str__(self):
return str(self.value)
global_step = GlobalStepHook()
for epoch in range(n_epochs):
estimator.train(input_fn=input_fn, hooks=[global_step])
# Now the global_step hook contains the latest value of global_step
my_custom_eval_method(global_step.value)
最近,我发现估算器有 api get_variable_value
global_step = estimator.get_variable_value("global_step")
如何在 train(...)
完成后从 tf.estimator.Estimator
中获取最后一个 global_step
?例如,一个典型的基于 Estimator 的训练程序可能是这样设置的:
n_epochs = 10
model_dir = '/path/to/model_dir'
def model_fn(features, labels, mode, params):
# some code to build the model
pass
def input_fn():
ds = tf.data.Dataset() # obviously with specifying a data source
# manipulate the dataset
return ds
run_config = tf.estimator.RunConfig(model_dir=model_dir)
estimator = tf.estimator.Estimator(model_fn=model_fn, config=run_config)
for epoch in range(n_epochs):
estimator.train(input_fn=input_fn)
# Now I want to do something which requires to know the last global step, how to get it?
my_custom_eval_method(global_step)
只有 evaluate()
方法 returns 包含 global_step
作为字段的字典。如果出于某种原因我不能或不想使用此方法,我如何获得 global_step
?
只需在训练循环之前创建一个钩子:
class GlobalStepHook(tf.train.SessionRunHook):
def __init__(self):
self._global_step_tensor = None
self.value = None
def begin(self):
self._global_step_tensor = tf.train.get_global_step()
def after_run(self, run_context, run_values):
self.value = run_context.session.run(self._global_step_tensor)
def __str__(self):
return str(self.value)
global_step = GlobalStepHook()
for epoch in range(n_epochs):
estimator.train(input_fn=input_fn, hooks=[global_step])
# Now the global_step hook contains the latest value of global_step
my_custom_eval_method(global_step.value)
最近,我发现估算器有 api get_variable_value
global_step = estimator.get_variable_value("global_step")