class_docstr: Implements the TF backend ops for a PC auto-batching VM.
docstr: Implements reduce_min for TF backend.
docstr_tok: ["Implements","reduce_min","for","TF","backend","."]
code: def reduce_min(self, t, name=None):
      """Implements reduce_min for TF backend."""
      with tf.name_scope("VM.reduce_min"):
          return tf.reduce_min(input_tensor=t, name=name)
  
imports: import collections
  import contextlib
  import six
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.experimental.auto_batching import instructions
  from tensorflow_probability.python.experimental.auto_batching import xla
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow.python.ops import control_flow_util
label_desc: Use image node_id 17 for calling the TensorFlowBackend obj's underlying member method code with example usage: obj.reduce_min(t, name) and returns: tf