Not getting global steps in TensorFlow - tensorflow2.0

Question

When I run following code, I don't get global steps until 5000.
First,
When I run this code, output is what I expect.
from __future__ import absolute_import, division, print_function, unicode_literals
import tensorflow as tf
import pandas as pd
CSV_COLUMN_NAMES = ['SepalLength', 'SepalWidth', 'PetalLength', 'PetalWidth', 'Species']
SPECIES = ['Setosa', 'Versicolor', 'Virginica']
train_path = tf.keras.utils.get_file(
"iris_training.csv", "https://storage.googleapis.com/download.tensorflow.org/data/iris_training.csv")
test_path = tf.keras.utils.get_file(
"iris_test.csv", "https://storage.googleapis.com/download.tensorflow.org/data/iris_test.csv")
train = pd.read_csv(train_path, names=CSV_COLUMN_NAMES, header=0)
test = pd.read_csv(test_path, names=CSV_COLUMN_NAMES, header=0)
train_y = train.pop('Species')
test_y = test.pop('Species')
def input_fn(features, labels, training=True, batch_size=256):
# Convert the inputs to a Dataset.
dataset = tf.data.Dataset.from_tensor_slices((dict(features), labels))
# Shuffle and repeat if you are in training mode.
if training:
dataset = dataset.shuffle(1000).repeat()
return dataset.batch(batch_size)
my_feature_columns = []
for key in train.keys():
my_feature_columns.append(tf.feature_column.numeric_column(key=key))
#print(my_feature_columns)
But,
After adding classifier code, I don't get global steps.
This is addition of code after writing code above:
classifier = tf.estimator.DNNClassifier(
feature_columns=my_feature_columns,
# Two hidden layers of 30 and 10 nodes respectively.
hidden_units=[30, 10],
# The model must choose between 3 classes.
n_classes=3)
classifier.train(
input_fn=lambda: input_fn(train, train_y, training=True),
steps=5000)
Instead of getting global steps until 5000, I get this output
WARNING:tensorflow:Using temporary folder as model directory: /tmp/tmpfl0bqu11
WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 1061 vs previous value: 1061. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize
I write the same code that my teacher demo but he could run this code. I can't.
How could I get global steps?