tf-estimator-nightly

import tensorflow.compat.v1 as tf tf.disable_v2_behavior() import tensorflow.compat.v1.estimator as estimator # Define a simple linear regressor feature_columns = [tf.feature_column.numeric_column('x', shape=[1])] regressor = estimator.LinearRegressor(feature_columns=feature_columns) # Mock input function def input_fn(): return {'x': [[1.0], [2.0], [3.0]]}, [1.0, 2.0, 3.0] # Train regressor.train(input_fn=input_fn, steps=100) # Predict predictions = regressor.predict(input_fn=input_fn) try: for i, p in enumerate(predictions): print(p['predictions']) if i > 2: break except StopIteration: pass