docstr: Validate the second dimension is the same for 2d results and all fields share the same dimensionality
  For example, time aligned results with dimension of (features, pred_length), the pred_length shall be the same
  :param values:
  :return:
code: def check_shape(cls, values):
      """
      Validate the second dimension is the same for 2d results and all fields share the same dimensionality
      For example, time aligned results with dimension of (features, pred_length), the pred_length shall be the same
      :param values:
      :return:
      """
      dim = np.array(values.get("target")).ndim
      assert (
          0 < dim <= 2
      ), "expected the feature importances array to be in the dimension of 1d or 2d only but got {dim}d from target"
      for key, value in values.items():
          if value:
              assert (
                  np.array(value).ndim == dim
              ), f"dimension mismatch {key} with dim {np.array(value).ndim} and target with dim {dim} "
      if dim == 1:
          return values
      shape = np.shape(values.get("target"))[dim - 1]
      for key, value in values.items():
          if value:
              assert (
                  np.shape(value)[dim - 1] == shape
              ), f"shape mismatch {key} with shape {np.shape(value)} and target with shape {shape} "
      return values
  
file_path: gluonts/src/gluonts/ext/rotbaum/_types.py
imports: from typing import List, Union, Optional
  import numpy
  from gluonts.pydantic import BaseModel, root_validator
label_desc: Use image node_id 1 for calling the FeatureImportanceResult obj's underlying member method code with example usage: obj.check_shape(cls, values) and returns: values, values