code: def __call__(self, tensors):
      if len(set(t.ndim for t in tensors)) != 1:
          raise ValueError(
              "all the input tensors must have same number of dimensions"
          )
  
      axis = self._axis
      shapes = [t.shape[:axis] + t.shape[axis + 1 :] for t in tensors]
      if len(set(shapes)) != 1:
          raise ValueError(
              "all the input tensor dimensions "
              "except for the concatenation axis must match exactly"
          )
  
      shape = [
          0 if i == axis else tensors[0].shape[i]
          for i in range(tensors[0].ndim)
      ]
      shape[axis] = sum(t.shape[axis] for t in tensors)
  
      if any(np.isnan(s) for i, s in enumerate(shape) if i != axis):
          raise ValueError(
              "cannot concatenate tensor with unknown shape"
          )
  
      return self.new_tensor(tensors, shape=tuple(shape))
  
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 8 for calling the TensorConcatenate obj's underlying member method code with example usage: obj.__call__(tensors) and returns: self