python-tensorflowHow can I access the 'inputs' attribute in the 'tensorflow_estimator.python.estimator.api._v2.estimator' module?

The inputs attribute in the tensorflow_estimator.python.estimator.api._v2.estimator module can be accessed by creating an instance of the tf.estimator.Estimator class. This class takes in a model function that defines the model's architecture, as well as a set of tf.estimator.RunConfig objects that define the runtime environment for the estimator. The inputs attribute can then be accessed by calling the inputs method on the tf.estimator.Estimator instance.

Example code

import tensorflow as tf

def my_model_fn(features, labels, mode):
    # define model architecture
    pass

run_config = tf.estimator.RunConfig(model_dir='/tmp/model_dir')
estimator = tf.estimator.Estimator(model_fn=my_model_fn, config=run_config)
inputs = estimator.inputs

Code explanation

• import tensorflow as tf: imports the TensorFlow library into the current Python environment.
• def my_model_fn(features, labels, mode):: defines a model function that takes in feature data, label data, and a mode (train, evaluate, or predict) as input arguments.
• run_config = tf.estimator.RunConfig(model_dir='/tmp/model_dir'): creates a tf.estimator.RunConfig object that defines the runtime environment for the estimator.
• estimator = tf.estimator.Estimator(model_fn=my_model_fn, config=run_config): creates an instance of the tf.estimator.Estimator class using the model function and runtime environment defined above.
• inputs = estimator.inputs: accesses the inputs attribute of the tf.estimator.Estimator instance.

Helpful links

• TensorFlow Estimators
• tf.estimator.Estimator

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