class_docstr: Stem layer at the begining of the network.
class_docstr_tok: ["Stem","layer","at","the","begining","of","the","network","."]
code: def __init__(self, global_params, stem_filters, name=None):
      super().__init__(name=name)
      self._conv_stem = tf.keras.layers.Conv2D(
          filters=round_filters(
              stem_filters, global_params, global_params.fix_head_stem
          ),
          kernel_size=[3, 3],
          strides=[2, 2],
          kernel_initializer=conv_kernel_initializer,
          padding="same",
          data_format=global_params.data_format,
          use_bias=False,
      )
      self._bn = global_params.batch_norm(
          axis=(
              1 if global_params.data_format == "channels_first" else -1
          ),
          momentum=global_params.batch_norm_momentum,
          epsilon=global_params.batch_norm_epsilon,
      )
      self._relu_fn = global_params.relu_fn or tf.nn.swish
  
imports: import collections
  import itertools
  import math
  from absl import logging
  import numpy
  import six
  from six.moves import xrange
  import tensorflow
  import utils
label_desc: Use image node_id 1 to create a new Stem object from inherited base classes: tf.keras.layers with example: obj = Stem(global_params, stem_filters, name)