BVhNdZddlmZddlmZddlmZdZdZ d dZd d Z y) zSpecial functions that only make sense for AutoGraph. These functions are meant to ensure feature parity between Python and AutoGraph, so that the exact same code works in both modes. In general, AutoGraph will replace these calls. )data_structures) constant_op) tensor_utilc||ytj|ryt|ttfr|ryt dt dj t|)z$Validates the inputs of tensor_list.NzDelement_dtype and element_shape are required when elements are emptyzFunknown type for elements: {}; only Tensor, list and tuple are allowed)r is_tf_type isinstancelisttuple ValueErrorformattype)elements element_dtype element_shapes b/home/dcms/DCMS/lib/python3.12/site-packages/tensorflow/python/autograph/lang/special_functions.py_validate_list_constructorrsi=#< H% 4-(    X' ))cZtj|rtj|S|S)z8Casts a value to be staged at the same level as another.)rrrconstant)value like_values rmatch_staging_levelr.s&J'    && ,rNc|t||||rtj|||Stj|||S)aCreates an tensor list and populates it with the given elements. This function provides a more uniform access to tensor lists and tensor arrays, and allows optional initialization. Note: this function is a simplified wrapper. If you need greater control, it is recommended to use the underlying implementation directly. Args: elements: Iterable[tf.Tensor, ...], the elements to initially fill the list with element_dtype: Optional[tf.DType], data type for the elements in the list; required if the list is empty element_shape: Optional[tf.TensorShape], shape for the elements in the list; required if the list is empty use_tensor_array: bool, whether to use the more compatible but restrictive tf.TensorArray implementation Returns: Union[tf.Tensor, tf.TensorArray], the new list. Raises: ValueError: for invalid arguments )rrtf_tensor_array_newtf_tensor_list_new)rrruse_tensor_arrays r tensor_listr5sI4X}mD  . .x/< >>  - -h .; ==rcn|rd}|}nd}tj|tj||S)a"Stacks the input, if it admits the notion of stacking. For example, a list of tensors can be stacked into a larger tensor. This function is similar to tf.stack, but it accepts non-lists and lists of non-tensors as arguments. In the latter case, the function does nothing. Args: list_or_tensor: Any element_dtype: tf.DType, optional dtypedtype for the elements in the list. Required if the input is stackable, and the list is untyped. strict: bool, if True an error is raised if the input is not stackable. Otherwise the function is a no-op. Returns: Any, if the input is stackable, the result will be a tf.Tensor. Otherwise, if strict=False, the result will be list_or_tensor. Raises: ValueError: if strict=True and the input is not stackable. ctd|z)Nz%%s must be stackable when strict=True)r xs r raise_errorzstack..raise_errorns >B CCrc|S)Nr s rzstack..rsar)r original_call)r list_stack ListStackOpts)list_or_tensorrstrictr"r&s rstackr+XsC* DMM  # ###%]D EEr)NNF)NT) __doc__%tensorflow.python.autograph.operatorsrtensorflow.python.frameworkrrrrrr+r$rrr/s7B33)&#"!& =FEr