neulab/docprompting-conala huggingface dataset:
tf.raw_ops.ExperimentalDatasetCardinality Returns the cardinality of input_dataset.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalDatasetCardinality  
tf.raw_ops.ExperimentalDatasetCardinality(
    input_dataset, name=None
)
 Returns the cardinality of input_dataset.
 


 Args
  input_dataset   A Tensor of type variant. A variant tensor representing the dataset to return cardinality for.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type int64.
tf.raw_ops.ExperimentalDatasetToTFRecord Writes the given dataset to the given file using the TFRecord format.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalDatasetToTFRecord  
tf.raw_ops.ExperimentalDatasetToTFRecord(
    input_dataset, filename, compression_type, name=None
)

 


 Args
  input_dataset   A Tensor of type variant. A variant tensor representing the dataset to write.  
  filename   A Tensor of type string. A scalar string tensor representing the filename to use.  
  compression_type   A Tensor of type string. A scalar string tensor containing either (i) the empty string (no compression), (ii) "ZLIB", or (iii) "GZIP".  
  name   A name for the operation (optional).   
 


 Returns   The created Operation.
tf.raw_ops.ExperimentalDenseToSparseBatchDataset Creates a dataset that batches input elements into a SparseTensor.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalDenseToSparseBatchDataset  
tf.raw_ops.ExperimentalDenseToSparseBatchDataset(
    input_dataset, batch_size, row_shape, output_types, output_shapes, name=None
)

 


 Args
  input_dataset   A Tensor of type variant. A handle to an input dataset. Must have a single component.  
  batch_size   A Tensor of type int64. A scalar representing the number of elements to accumulate in a batch.  
  row_shape   A Tensor of type int64. A vector representing the dense shape of each row in the produced SparseTensor. The shape may be partially specified, using -1 to indicate that a particular dimension should use the maximum size of all batch elements.  
  output_types   A list of tf.DTypes that has length >= 1.  
  output_shapes   A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.
tf.raw_ops.ExperimentalDirectedInterleaveDataset A substitute for InterleaveDataset on a fixed list of N datasets.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalDirectedInterleaveDataset  
tf.raw_ops.ExperimentalDirectedInterleaveDataset(
    selector_input_dataset, data_input_datasets, output_types, output_shapes,
    name=None
)

 


 Args
  selector_input_dataset   A Tensor of type variant. A dataset of scalar DT_INT64 elements that determines which of the N data inputs should produce the next output element.  
  data_input_datasets   A list of at least 1 Tensor objects with type variant. N datasets with the same type that will be interleaved according to the values of selector_input_dataset.  
  output_types   A list of tf.DTypes that has length >= 1.  
  output_shapes   A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.
tf.raw_ops.ExperimentalGroupByReducerDataset Creates a dataset that computes a group-by on input_dataset.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalGroupByReducerDataset  
tf.raw_ops.ExperimentalGroupByReducerDataset(
    input_dataset, key_func_other_arguments, init_func_other_arguments,
    reduce_func_other_arguments, finalize_func_other_arguments, key_func, init_func,
    reduce_func, finalize_func, output_types, output_shapes, name=None
)
 Creates a dataset that computes a group-by on input_dataset.
 


 Args
  input_dataset   A Tensor of type variant. A variant tensor representing the input dataset.  
  key_func_other_arguments   A list of Tensor objects. A list of tensors, typically values that were captured when building a closure for key_func.  
  init_func_other_arguments   A list of Tensor objects. A list of tensors, typically values that were captured when building a closure for init_func.  
  reduce_func_other_arguments   A list of Tensor objects. A list of tensors, typically values that were captured when building a closure for reduce_func.  
  finalize_func_other_arguments   A list of Tensor objects. A list of tensors, typically values that were captured when building a closure for finalize_func.  
  key_func   A function decorated with @Defun. A function mapping an element of input_dataset, concatenated with key_func_other_arguments to a scalar value of type DT_INT64.  
  init_func   A function decorated with @Defun. A function mapping a key of type DT_INT64, concatenated with init_func_other_arguments to the initial reducer state.  
  reduce_func   A function decorated with @Defun. A function mapping the current reducer state and an element of input_dataset, concatenated with reduce_func_other_arguments to a new reducer state.  
  finalize_func   A function decorated with @Defun. A function mapping the final reducer state to an output element.  
  output_types   A list of tf.DTypes that has length >= 1.  
  output_shapes   A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.
tf.raw_ops.ExperimentalGroupByWindowDataset Creates a dataset that computes a windowed group-by on input_dataset.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalGroupByWindowDataset  
tf.raw_ops.ExperimentalGroupByWindowDataset(
    input_dataset, key_func_other_arguments, reduce_func_other_arguments,
    window_size_func_other_arguments, key_func, reduce_func, window_size_func,
    output_types, output_shapes, name=None
)
 //
 


 Args
  input_dataset   A Tensor of type variant.  
  key_func_other_arguments   A list of Tensor objects.  
  reduce_func_other_arguments   A list of Tensor objects.  
  window_size_func_other_arguments   A list of Tensor objects.  
  key_func   A function decorated with @Defun. A function mapping an element of input_dataset, concatenated with key_func_other_arguments to a scalar value of type DT_INT64.  
  reduce_func   A function decorated with @Defun.  
  window_size_func   A function decorated with @Defun.  
  output_types   A list of tf.DTypes that has length >= 1.  
  output_shapes   A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.
tf.raw_ops.ExperimentalIgnoreErrorsDataset Creates a dataset that contains the elements of input_dataset ignoring errors.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalIgnoreErrorsDataset  
tf.raw_ops.ExperimentalIgnoreErrorsDataset(
    input_dataset, output_types, output_shapes, log_warning=False, name=None
)

 


 Args
  input_dataset   A Tensor of type variant.  
  output_types   A list of tf.DTypes that has length >= 1.  
  output_shapes   A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1.  
  log_warning   An optional bool. Defaults to False.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.
tf.raw_ops.ExperimentalIteratorGetDevice Returns the name of the device on which resource has been placed.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalIteratorGetDevice  
tf.raw_ops.ExperimentalIteratorGetDevice(
    resource, name=None
)

 


 Args
  resource   A Tensor of type resource.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type string.
tf.raw_ops.ExperimentalLatencyStatsDataset Records the latency of producing input_dataset elements in a StatsAggregator.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalLatencyStatsDataset  
tf.raw_ops.ExperimentalLatencyStatsDataset(
    input_dataset, tag, output_types, output_shapes, name=None
)

 


 Args
  input_dataset   A Tensor of type variant.  
  tag   A Tensor of type string.  
  output_types   A list of tf.DTypes that has length >= 1.  
  output_shapes   A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.
tf.raw_ops.ExperimentalLMDBDataset  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalLMDBDataset  
tf.raw_ops.ExperimentalLMDBDataset(
    filenames, output_types, output_shapes, name=None
)

 


 Args
  filenames   A Tensor of type string.  
  output_types   A list of tf.DTypes that has length >= 1.  
  output_shapes   A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.
tf.raw_ops.ExperimentalMapAndBatchDataset Creates a dataset that fuses mapping with batching.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalMapAndBatchDataset  
tf.raw_ops.ExperimentalMapAndBatchDataset(
    input_dataset, other_arguments, batch_size, num_parallel_calls, drop_remainder,
    f, output_types, output_shapes, preserve_cardinality=False, name=None
)
 Creates a dataset that applies f to the outputs of input_dataset and then batches batch_size of them. Unlike a "MapDataset", which applies f sequentially, this dataset invokes up to batch_size * num_parallel_batches copies of f in parallel.
 


 Args
  input_dataset   A Tensor of type variant. A variant tensor representing the input dataset.  
  other_arguments   A list of Tensor objects. A list of tensors, typically values that were captured when building a closure for f.  
  batch_size   A Tensor of type int64. A scalar representing the number of elements to accumulate in a batch. It determines the number of concurrent invocations of f that process elements from input_dataset in parallel.  
  num_parallel_calls   A Tensor of type int64. A scalar representing the maximum number of parallel invocations of the map_fn function. Applying the map_fn on consecutive input elements in parallel has the potential to improve input pipeline throughput.  
  drop_remainder   A Tensor of type bool. A scalar representing whether the last batch should be dropped in case its size is smaller than desired.  
  f   A function decorated with @Defun. A function to apply to the outputs of input_dataset.  
  output_types   A list of tf.DTypes that has length >= 1.  
  output_shapes   A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1.  
  preserve_cardinality   An optional bool. Defaults to False.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.
tf.raw_ops.ExperimentalMapDataset Creates a dataset that applies f to the outputs of input_dataset.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalMapDataset  
tf.raw_ops.ExperimentalMapDataset(
    input_dataset, other_arguments, f, output_types, output_shapes,
    use_inter_op_parallelism=True, preserve_cardinality=False, name=None
)

 


 Args
  input_dataset   A Tensor of type variant.  
  other_arguments   A list of Tensor objects.  
  f   A function decorated with @Defun.  
  output_types   A list of tf.DTypes that has length >= 1.  
  output_shapes   A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1.  
  use_inter_op_parallelism   An optional bool. Defaults to True.  
  preserve_cardinality   An optional bool. Defaults to False.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.
tf.raw_ops.ExperimentalMatchingFilesDataset  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalMatchingFilesDataset  
tf.raw_ops.ExperimentalMatchingFilesDataset(
    patterns, name=None
)

 


 Args
  patterns   A Tensor of type string.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.
tf.raw_ops.ExperimentalMaxIntraOpParallelismDataset Creates a dataset that overrides the maximum intra-op parallelism.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalMaxIntraOpParallelismDataset  
tf.raw_ops.ExperimentalMaxIntraOpParallelismDataset(
    input_dataset, max_intra_op_parallelism, output_types, output_shapes, name=None
)

 


 Args
  input_dataset   A Tensor of type variant.  
  max_intra_op_parallelism   A Tensor of type int64. Identifies the maximum intra-op parallelism to use.  
  output_types   A list of tf.DTypes that has length >= 1.  
  output_shapes   A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.
tf.raw_ops.ExperimentalNonSerializableDataset  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalNonSerializableDataset  
tf.raw_ops.ExperimentalNonSerializableDataset(
    input_dataset, output_types, output_shapes, name=None
)

 


 Args
  input_dataset   A Tensor of type variant.  
  output_types   A list of tf.DTypes that has length >= 1.  
  output_shapes   A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.
tf.raw_ops.ExperimentalParallelInterleaveDataset Creates a dataset that applies f to the outputs of input_dataset.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalParallelInterleaveDataset  
tf.raw_ops.ExperimentalParallelInterleaveDataset(
    input_dataset, other_arguments, cycle_length, block_length, sloppy,
    buffer_output_elements, prefetch_input_elements, f, output_types, output_shapes,
    name=None
)
 The resulting dataset is similar to the InterleaveDataset, with the exception that if retrieving the next value from a dataset would cause the requester to block, it will skip that input dataset. This dataset is especially useful when loading data from a variable-latency datastores (e.g. HDFS, GCS), as it allows the training step to proceed so long as some data is available. !! WARNING !! This dataset is not deterministic!
 


 Args
  input_dataset   A Tensor of type variant.  
  other_arguments   A list of Tensor objects.  
  cycle_length   A Tensor of type int64.  
  block_length   A Tensor of type int64.  
  sloppy   A Tensor of type bool.  
  buffer_output_elements   A Tensor of type int64.  
  prefetch_input_elements   A Tensor of type int64.  
  f   A function decorated with @Defun. A function mapping elements of input_dataset, concatenated with other_arguments, to a Dataset variant that contains elements matching output_types and output_shapes.  
  output_types   A list of tf.DTypes that has length >= 1.  
  output_shapes   A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.
tf.raw_ops.ExperimentalParseExampleDataset Transforms input_dataset containing Example protos as vectors of DT_STRING into a dataset of Tensor or SparseTensor objects representing the parsed features.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalParseExampleDataset  
tf.raw_ops.ExperimentalParseExampleDataset(
    input_dataset, num_parallel_calls, dense_defaults, sparse_keys, dense_keys,
    sparse_types, dense_shapes, output_types, output_shapes, sloppy=False, name=None
)

 


 Args
  input_dataset   A Tensor of type variant.  
  num_parallel_calls   A Tensor of type int64.  
  dense_defaults   A list of Tensor objects with types from: float32, int64, string. A dict mapping string keys to Tensors. The keys of the dict must match the dense_keys of the feature.  
  sparse_keys   A list of strings. A list of string keys in the examples features. The results for these keys will be returned as SparseTensor objects.  
  dense_keys   A list of strings. A list of Ndense string Tensors (scalars). The keys expected in the Examples features associated with dense values.  
  sparse_types   A list of tf.DTypes from: tf.float32, tf.int64, tf.string. A list of DTypes of the same length as sparse_keys. Only tf.float32 (FloatList), tf.int64 (Int64List), and tf.string (BytesList) are supported.  
  dense_shapes   A list of shapes (each a tf.TensorShape or list of ints). List of tuples with the same length as dense_keys. The shape of the data for each dense feature referenced by dense_keys. Required for any input tensors identified by dense_keys. Must be either fully defined, or may contain an unknown first dimension. An unknown first dimension means the feature is treated as having a variable number of blocks, and the output shape along this dimension is considered unknown at graph build time. Padding is applied for minibatch elements smaller than the maximum number of blocks for the given feature along this dimension.  
  output_types   A list of tf.DTypes that has length >= 1. The type list for the return values.  
  output_shapes   A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1. The list of shapes being produced.  
  sloppy   An optional bool. Defaults to False.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.
tf.raw_ops.ExperimentalPrivateThreadPoolDataset Creates a dataset that uses a custom thread pool to compute input_dataset.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalPrivateThreadPoolDataset  
tf.raw_ops.ExperimentalPrivateThreadPoolDataset(
    input_dataset, num_threads, output_types, output_shapes, name=None
)

 


 Args
  input_dataset   A Tensor of type variant.  
  num_threads   A Tensor of type int64. Identifies the number of threads to use for the private threadpool.  
  output_types   A list of tf.DTypes that has length >= 1.  
  output_shapes   A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.
tf.raw_ops.ExperimentalRandomDataset Creates a Dataset that returns pseudorandom numbers.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalRandomDataset  
tf.raw_ops.ExperimentalRandomDataset(
    seed, seed2, output_types, output_shapes, name=None
)

 


 Args
  seed   A Tensor of type int64. A scalar seed for the random number generator. If either seed or seed2 is set to be non-zero, the random number generator is seeded by the given seed. Otherwise, a random seed is used.  
  seed2   A Tensor of type int64. A second scalar seed to avoid seed collision.  
  output_types   A list of tf.DTypes that has length >= 1.  
  output_shapes   A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.
tf.raw_ops.ExperimentalRebatchDataset Creates a dataset that changes the batch size.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalRebatchDataset  
tf.raw_ops.ExperimentalRebatchDataset(
    input_dataset, num_replicas, output_types, output_shapes, use_fallback=True,
    name=None
)
 Creates a dataset that changes the batch size of the dataset to current batch size // num_replicas.
 


 Args
  input_dataset   A Tensor of type variant. A variant tensor representing the input dataset.  
  num_replicas   A Tensor of type int64. A scalar representing the number of replicas to distribute this batch across. As a result of this transformation the current batch size would end up being divided by this parameter.  
  output_types   A list of tf.DTypes that has length >= 1.  
  output_shapes   A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1.  
  use_fallback   An optional bool. Defaults to True.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.
tf.raw_ops.ExperimentalScanDataset Creates a dataset successively reduces f over the elements of input_dataset.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalScanDataset  
tf.raw_ops.ExperimentalScanDataset(
    input_dataset, initial_state, other_arguments, f, output_types, output_shapes,
    preserve_cardinality=False, name=None
)

 


 Args
  input_dataset   A Tensor of type variant.  
  initial_state   A list of Tensor objects.  
  other_arguments   A list of Tensor objects.  
  f   A function decorated with @Defun.  
  output_types   A list of tf.DTypes that has length >= 1.  
  output_shapes   A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1.  
  preserve_cardinality   An optional bool. Defaults to False.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.
tf.raw_ops.ExperimentalSetStatsAggregatorDataset  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalSetStatsAggregatorDataset  
tf.raw_ops.ExperimentalSetStatsAggregatorDataset(
    input_dataset, stats_aggregator, tag, counter_prefix, output_types,
    output_shapes, name=None
)

 


 Args
  input_dataset   A Tensor of type variant.  
  stats_aggregator   A Tensor of type resource.  
  tag   A Tensor of type string.  
  counter_prefix   A Tensor of type string.  
  output_types   A list of tf.DTypes that has length >= 1.  
  output_shapes   A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.
tf.raw_ops.ExperimentalSleepDataset  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalSleepDataset  
tf.raw_ops.ExperimentalSleepDataset(
    input_dataset, sleep_microseconds, output_types, output_shapes, name=None
)

 


 Args
  input_dataset   A Tensor of type variant.  
  sleep_microseconds   A Tensor of type int64.  
  output_types   A list of tf.DTypes that has length >= 1.  
  output_shapes   A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.
tf.raw_ops.ExperimentalSlidingWindowDataset Creates a dataset that passes a sliding window over input_dataset.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ExperimentalSlidingWindowDataset  
tf.raw_ops.ExperimentalSlidingWindowDataset(
    input_dataset, window_size, window_shift, window_stride, output_types,
    output_shapes, name=None
)

 


 Args
  input_dataset   A Tensor of type variant.  
  window_size   A Tensor of type int64. A scalar representing the number of elements in the sliding window.  
  window_shift   A Tensor of type int64. A scalar representing the steps moving the sliding window forward in one iteration. It must be positive.  
  window_stride   A Tensor of type int64. A scalar representing the stride of the input elements of the sliding window. It must be positive.  
  output_types   A list of tf.DTypes that has length >= 1.  
  output_shapes   A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.