code: def concatenate(tensors, axis=0):
      """
      Join a sequence of arrays along an existing axis.
  
      Parameters
      ----------
      a1, a2, ... : sequence of array_like
          The tensors must have the same shape, except in the dimension
          corresponding to `axis` (the first, by default).
      axis : int, optional
          The axis along which the tensors will be joined.  Default is 0.
  
      Returns
      -------
      res : Tensor
          The concatenated tensor.
  
      See Also
      --------
      array_split : Split a tensor into multiple sub-arrays of equal or
                    near-equal size.
      split : Split tensor into a list of multiple sub-tensors of equal size.
      hsplit : Split tensor into multiple sub-tensors horizontally (column wise)
      vsplit : Split tensor into multiple sub-tensors vertically (row wise)
      dsplit : Split tensor into multiple sub-tensors along the 3rd axis (depth).
      stack : Stack a sequence of tensors along a new axis.
      hstack : Stack tensors in sequence horizontally (column wise)
      vstack : Stack tensors in sequence vertically (row wise)
      dstack : Stack tensors in sequence depth wise (along third dimension)
  
      Examples
      --------
      >>> import mars.tensor as mt
  
      >>> a = mt.array([[1, 2], [3, 4]])
      >>> b = mt.array([[5, 6]])
      >>> mt.concatenate((a, b), axis=0).execute()
      array([[1, 2],
             [3, 4],
             [5, 6]])
      >>> mt.concatenate((a, b.T), axis=1).execute()
      array([[1, 2, 5],
             [3, 4, 6]])
  
      """
      if axis is None:
          axis = 0
      tensors = [astensor(t) for t in tensors]
  
      axis = validate_axis(tensors[0].ndim, axis)
      dtype = np.result_type(*(t.dtype for t in tensors))
      sparse = all(t.issparse() for t in tensors)
  
      op = TensorConcatenate(axis=axis, dtype=dtype, sparse=sparse)
      return op(tensors)
  
imports: import itertools
  import operator
  import tempfile
  from collections.abc import Iterable
  import numpy
  from ...None import opcodes
  from ...serialization.serializables import AnyField, BoolField, StringField, TupleField, SliceField
  from ..array_utils import device, as_same_device
  from ..utils import validate_axis, unify_chunks
  from ..datasource import tensor
  from ..operands import TensorOperand, TensorOperandMixin
  from ..indexing.slice import TensorSlice
label_desc: Use image node_id 3 for calling a global function with example usage: concatenate(tensors, axis) and returns: op