neulab/docprompting-conala huggingface dataset:
tf.raw_ops.ReaderReadV2 Returns the next record (key, value pair) produced by a Reader.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ReaderReadV2  
tf.raw_ops.ReaderReadV2(
    reader_handle, queue_handle, name=None
)
 Will dequeue from the input queue if necessary (e.g. when the Reader needs to start reading from a new file since it has finished with the previous file).
 


 Args
  reader_handle   A Tensor of type resource. Handle to a Reader.  
  queue_handle   A Tensor of type resource. Handle to a Queue, with string work items.  
  name   A name for the operation (optional).   
 


 Returns   A tuple of Tensor objects (key, value).     key   A Tensor of type string.  
  value   A Tensor of type string.
tf.raw_ops.ReaderReset Restore a Reader to its initial clean state.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ReaderReset  
tf.raw_ops.ReaderReset(
    reader_handle, name=None
)

 


 Args
  reader_handle   A Tensor of type mutable string. Handle to a Reader.  
  name   A name for the operation (optional).   
 


 Returns   The created Operation.
tf.raw_ops.ReaderResetV2 Restore a Reader to its initial clean state.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ReaderResetV2  
tf.raw_ops.ReaderResetV2(
    reader_handle, name=None
)

 


 Args
  reader_handle   A Tensor of type resource. Handle to a Reader.  
  name   A name for the operation (optional).   
 


 Returns   The created Operation.
tf.raw_ops.ReaderRestoreState Restore a reader to a previously saved state.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ReaderRestoreState  
tf.raw_ops.ReaderRestoreState(
    reader_handle, state, name=None
)
 Not all Readers support being restored, so this can produce an Unimplemented error.
 


 Args
  reader_handle   A Tensor of type mutable string. Handle to a Reader.  
  state   A Tensor of type string. Result of a ReaderSerializeState of a Reader with type matching reader_handle.  
  name   A name for the operation (optional).   
 


 Returns   The created Operation.
tf.raw_ops.ReaderRestoreStateV2 Restore a reader to a previously saved state.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ReaderRestoreStateV2  
tf.raw_ops.ReaderRestoreStateV2(
    reader_handle, state, name=None
)
 Not all Readers support being restored, so this can produce an Unimplemented error.
 


 Args
  reader_handle   A Tensor of type resource. Handle to a Reader.  
  state   A Tensor of type string. Result of a ReaderSerializeState of a Reader with type matching reader_handle.  
  name   A name for the operation (optional).   
 


 Returns   The created Operation.
tf.raw_ops.ReaderSerializeState Produce a string tensor that encodes the state of a Reader.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ReaderSerializeState  
tf.raw_ops.ReaderSerializeState(
    reader_handle, name=None
)
 Not all Readers support being serialized, so this can produce an Unimplemented error.
 


 Args
  reader_handle   A Tensor of type mutable string. Handle to a Reader.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type string.
tf.raw_ops.ReaderSerializeStateV2 Produce a string tensor that encodes the state of a Reader.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ReaderSerializeStateV2  
tf.raw_ops.ReaderSerializeStateV2(
    reader_handle, name=None
)
 Not all Readers support being serialized, so this can produce an Unimplemented error.
 


 Args
  reader_handle   A Tensor of type resource. Handle to a Reader.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type string.
tf.raw_ops.ReadFile Reads and outputs the entire contents of the input filename.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ReadFile  
tf.raw_ops.ReadFile(
    filename, name=None
)

 


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


 Returns   A Tensor of type string.
tf.raw_ops.ReadVariableOp Reads the value of a variable.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ReadVariableOp  
tf.raw_ops.ReadVariableOp(
    resource, dtype, name=None
)
 The tensor returned by this operation is immutable. The value returned by this operation is guaranteed to be influenced by all the writes on which this operation depends directly or indirectly, and to not be influenced by any of the writes which depend directly or indirectly on this operation.
 


 Args
  resource   A Tensor of type resource. handle to the resource in which to store the variable.  
  dtype   A tf.DType. the dtype of the value.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type dtype.
tf.raw_ops.Real   Returns the real part of a complex number.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.Real  
tf.raw_ops.Real(
    input, Tout=tf.dtypes.float32, name=None
)
 Given a tensor input of complex numbers, this operation returns a tensor of type float that is the real part of each element in input. All elements in input must be complex numbers of the form \(a + bj\), where a is the real part returned by this operation and b is the imaginary part. For example: # tensor 'input' is [-2.25 + 4.75j, 3.25 + 5.75j]
tf.real(input) ==> [-2.25, 3.25]

 


 Args
  input   A Tensor. Must be one of the following types: complex64, complex128.  
  Tout   An optional tf.DType from: tf.float32, tf.float64. Defaults to tf.float32.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type Tout.
tf.raw_ops.RealDiv Returns x / y element-wise for real types.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.RealDiv  
tf.raw_ops.RealDiv(
    x, y, name=None
)
 If x and y are reals, this will return the floating-point division. 
Note: Div supports broadcasting. More about broadcasting here

 


 Args
  x   A Tensor. Must be one of the following types: bfloat16, half, float32, float64, uint8, int8, uint16, int16, int32, int64, complex64, complex128.  
  y   A Tensor. Must have the same type as x.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as x.
tf.raw_ops.RebatchDataset 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.RebatchDataset  
tf.raw_ops.RebatchDataset(
    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_workers.
 


 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.RebatchDatasetV2 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.RebatchDatasetV2  
tf.raw_ops.RebatchDatasetV2(
    input_dataset, batch_sizes, drop_remainder, output_types, output_shapes,
    name=None
)
 Creates a dataset that rebatches elements from input_dataset into new batch sizes.
 


 Args
  input_dataset   A Tensor of type variant. A variant tensor representing the input dataset.  
  batch_sizes   A Tensor of type int64. A vector of integers representing the size of batches to produce. These values are cycled through in order.  
  drop_remainder   A Tensor of type bool.  
  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.Reciprocal   Computes the reciprocal of x element-wise.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.Reciprocal  
tf.raw_ops.Reciprocal(
    x, name=None
)
 I.e., \(y = 1 / x\).
 


 Args
  x   A Tensor. Must be one of the following types: bfloat16, half, float32, float64, int8, int16, int32, int64, complex64, complex128.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as x.
tf.raw_ops.ReciprocalGrad Computes the gradient for the inverse of x wrt its input.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ReciprocalGrad  
tf.raw_ops.ReciprocalGrad(
    y, dy, name=None
)
 Specifically, grad = -dy * y*y, where y = 1/x, and dy is the corresponding input gradient.
 


 Args
  y   A Tensor. Must be one of the following types: bfloat16, half, float32, float64, complex64, complex128.  
  dy   A Tensor. Must have the same type as y.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as y.
tf.raw_ops.RecordInput Emits randomized records.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.RecordInput  
tf.raw_ops.RecordInput(
    file_pattern, file_random_seed=301, file_shuffle_shift_ratio=0,
    file_buffer_size=10000, file_parallelism=16, batch_size=32,
    compression_type='', name=None
)

 


 Args
  file_pattern   A string. Glob pattern for the data files.  
  file_random_seed   An optional int. Defaults to 301. Random seeds used to produce randomized records.  
  file_shuffle_shift_ratio   An optional float. Defaults to 0. Shifts the list of files after the list is randomly shuffled.  
  file_buffer_size   An optional int. Defaults to 10000. The randomization shuffling buffer.  
  file_parallelism   An optional int. Defaults to 16. How many sstables are opened and concurrently iterated over.  
  batch_size   An optional int. Defaults to 32. The batch size.  
  compression_type   An optional string. Defaults to "". The type of compression for the file. Currently ZLIB and GZIP are supported. Defaults to none.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type string.
tf.raw_ops.Recv Receives the named tensor from send_device on recv_device.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.Recv  
tf.raw_ops.Recv(
    tensor_type, tensor_name, send_device, send_device_incarnation, recv_device,
    client_terminated=False, name=None
)

 


 Args
  tensor_type   A tf.DType.  
  tensor_name   A string. The name of the tensor to receive.  
  send_device   A string. The name of the device sending the tensor.  
  send_device_incarnation   An int. The current incarnation of send_device.  
  recv_device   A string. The name of the device receiving the tensor.  
  client_terminated   An optional bool. Defaults to False. If set to true, this indicates that the node was added to the graph as a result of a client-side feed or fetch of Tensor data, in which case the corresponding send or recv is expected to be managed locally by the caller.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type tensor_type.
tf.raw_ops.RecvTPUEmbeddingActivations An op that receives embedding activations on the TPU.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.RecvTPUEmbeddingActivations  
tf.raw_ops.RecvTPUEmbeddingActivations(
    num_outputs, config, name=None
)
 The TPU system performs the embedding lookups and aggregations specified by the arguments to TPUEmbeddingEnqueue(Integer/Sparse/SparseTensor)Batch. The results of these aggregations are visible to the Tensorflow Graph as the outputs of a RecvTPUEmbeddingActivations op. This op returns a list containing one Tensor of activations per table specified in the model. There can be at most one RecvTPUEmbeddingActivations op in the TPU graph.
 


 Args
  num_outputs   An int that is >= 1. The number of output activation tensors, equal to the number of embedding tables in the model.  
  config   A string. Serialized TPUEmbeddingConfiguration proto.  
  name   A name for the operation (optional).   
 


 Returns   A list of num_outputs Tensor objects with type float32.
tf.raw_ops.ReduceDataset Reduces the input dataset to a singleton using a reduce function.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ReduceDataset  
tf.raw_ops.ReduceDataset(
    input_dataset, initial_state, other_arguments, f, output_types, output_shapes,
    use_inter_op_parallelism=True, name=None
)

 


 Args
  input_dataset   A Tensor of type variant. A variant tensor representing the input dataset.  
  initial_state   A list of Tensor objects. A nested structure of tensors, representing the initial state of the transformation.  
  other_arguments   A list of Tensor objects.  
  f   A function decorated with @Defun. A function that maps (old_state, input_element) to new_state. It must take two arguments and return a nested structures of tensors. The structure of new_state must match the structure of initial_state.  
  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.  
  name   A name for the operation (optional).   
 


 Returns   A list of Tensor objects of type output_types.
tf.raw_ops.ReduceJoin   Joins a string Tensor across the given dimensions.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.ReduceJoin  
tf.raw_ops.ReduceJoin(
    inputs, reduction_indices, keep_dims=False, separator='', name=None
)
 Computes the string join across dimensions in the given string Tensor of shape [\\(d_0, d_1, ..., d_{n-1}\\)]. Returns a new Tensor created by joining the input strings with the given separator (default: empty string). Negative indices are counted backwards from the end, with -1 being equivalent to n - 1. If indices are not specified, joins across all dimensions beginning from n - 1 through 0. For example: # tensor `a` is [["a", "b"], ["c", "d"]]
tf.reduce_join(a, 0) ==> ["ac", "bd"]
tf.reduce_join(a, 1) ==> ["ab", "cd"]
tf.reduce_join(a, -2) = tf.reduce_join(a, 0) ==> ["ac", "bd"]
tf.reduce_join(a, -1) = tf.reduce_join(a, 1) ==> ["ab", "cd"]
tf.reduce_join(a, 0, keep_dims=True) ==> [["ac", "bd"]]
tf.reduce_join(a, 1, keep_dims=True) ==> [["ab"], ["cd"]]
tf.reduce_join(a, 0, separator=".") ==> ["a.c", "b.d"]
tf.reduce_join(a, [0, 1]) ==> "acbd"
tf.reduce_join(a, [1, 0]) ==> "abcd"
tf.reduce_join(a, []) ==> [["a", "b"], ["c", "d"]]
tf.reduce_join(a) = tf.reduce_join(a, [1, 0]) ==> "abcd"

 


 Args
  inputs   A Tensor of type string. The input to be joined. All reduced indices must have non-zero size.  
  reduction_indices   A Tensor of type int32. The dimensions to reduce over. Dimensions are reduced in the order specified. Omitting reduction_indices is equivalent to passing [n-1, n-2, ..., 0]. Negative indices from -n to -1 are supported.  
  keep_dims   An optional bool. Defaults to False. If True, retain reduced dimensions with length 1.  
  separator   An optional string. Defaults to "". The separator to use when joining.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type string.
tf.raw_ops.RefEnter Creates or finds a child frame, and makes data available to the child frame.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.RefEnter  
tf.raw_ops.RefEnter(
    data, frame_name, is_constant=False, parallel_iterations=10, name=None
)
 The unique frame_name is used by the Executor to identify frames. If is_constant is true, output is a constant in the child frame; otherwise it may be changed in the child frame. At most parallel_iterations iterations are run in parallel in the child frame.
 


 Args
  data   A mutable Tensor. The tensor to be made available to the child frame.  
  frame_name   A string. The name of the child frame.  
  is_constant   An optional bool. Defaults to False. If true, the output is constant within the child frame.  
  parallel_iterations   An optional int. Defaults to 10. The number of iterations allowed to run in parallel.  
  name   A name for the operation (optional).   
 


 Returns   A mutable Tensor. Has the same type as data.
tf.raw_ops.RefExit Exits the current frame to its parent frame.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.RefExit  
tf.raw_ops.RefExit(
    data, name=None
)
 Exit makes its input data available to the parent frame.
 


 Args
  data   A mutable Tensor. The tensor to be made available to the parent frame.  
  name   A name for the operation (optional).   
 


 Returns   A mutable Tensor. Has the same type as data.
tf.raw_ops.RefIdentity Return the same ref tensor as the input ref tensor.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.RefIdentity  
tf.raw_ops.RefIdentity(
    input, name=None
)

 


 Args
  input   A mutable Tensor.  
  name   A name for the operation (optional).   
 


 Returns   A mutable Tensor. Has the same type as input.
tf.raw_ops.RefMerge Forwards the value of an available tensor from inputs to output.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.RefMerge  
tf.raw_ops.RefMerge(
    inputs, name=None
)
 Merge waits for at least one of the tensors in inputs to become available. It is usually combined with Switch to implement branching. Merge forwards the first tensor for become available to output, and sets value_index to its index in inputs.
 


 Args
  inputs   A list of at least 1 mutable Tensor objects with the same type. The input tensors, exactly one of which will become available.  
  name   A name for the operation (optional).   
 


 Returns   A tuple of Tensor objects (output, value_index).     output   A mutable Tensor. Has the same type as inputs.  
  value_index   A Tensor of type int32.
tf.raw_ops.RefNextIteration Makes its input available to the next iteration.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.RefNextIteration  
tf.raw_ops.RefNextIteration(
    data, name=None
)

 


 Args
  data   A mutable Tensor. The tensor to be made available to the next iteration.  
  name   A name for the operation (optional).   
 


 Returns   A mutable Tensor. Has the same type as data.
tf.raw_ops.RefSelect Forwards the indexth element of inputs to output.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.RefSelect  
tf.raw_ops.RefSelect(
    index, inputs, name=None
)

 


 Args
  index   A Tensor of type int32. A scalar that determines the input that gets selected.  
  inputs   A list of at least 1 mutable Tensor objects with the same type. A list of ref tensors, one of which will be forwarded to output.  
  name   A name for the operation (optional).   
 


 Returns   A mutable Tensor. Has the same type as inputs.
tf.raw_ops.RefSwitch Forwards the ref tensor data to the output port determined by pred.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.RefSwitch  
tf.raw_ops.RefSwitch(
    data, pred, name=None
)
 If pred is true, the data input is forwarded to output_true. Otherwise, the data goes to output_false. See also Switch and Merge.
 


 Args
  data   A mutable Tensor. The ref tensor to be forwarded to the appropriate output.  
  pred   A Tensor of type bool. A scalar that specifies which output port will receive data.  
  name   A name for the operation (optional).   
 


 Returns   A tuple of Tensor objects (output_false, output_true).     output_false   A mutable Tensor. Has the same type as data.  
  output_true   A mutable Tensor. Has the same type as data.
tf.raw_ops.RegexFullMatch   Check if the input matches the regex pattern.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.RegexFullMatch  
tf.raw_ops.RegexFullMatch(
    input, pattern, name=None
)
 The input is a string tensor of any shape. The pattern is a scalar string tensor which is applied to every element of the input tensor. The boolean values (True or False) of the output tensor indicate if the input matches the regex pattern provided. The pattern follows the re2 syntax (https://github.com/google/re2/wiki/Syntax) Examples: 
tf.strings.regex_full_match(["TF lib", "lib TF"], ".*lib$")
<tf.Tensor: shape=(2,), dtype=bool, numpy=array([ True, False])>
tf.strings.regex_full_match(["TF lib", "lib TF"], ".*TF$")
<tf.Tensor: shape=(2,), dtype=bool, numpy=array([False,  True])>

 


 Args
  input   A Tensor of type string. A string tensor of the text to be processed.  
  pattern   A Tensor of type string. A scalar string tensor containing the regular expression to match the input.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type bool.
tf.raw_ops.RegexReplace Replaces matches of the pattern regular expression in input with the  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.RegexReplace  
tf.raw_ops.RegexReplace(
    input, pattern, rewrite, replace_global=True, name=None
)
 replacement string provided in rewrite. It follows the re2 syntax (https://github.com/google/re2/wiki/Syntax) Args: input: A Tensor of type string. The text to be processed. pattern: A Tensor of type string. The regular expression to be matched in the input strings. rewrite: A Tensor of type string. The rewrite string to be substituted for the pattern expression where it is matched in the input strings. replace_global: An optional bool. Defaults to True. If True, the replacement is global (that is, all matches of the pattern regular expression in each input string are rewritten), otherwise the rewrite substitution is only made for the first pattern match. name: A name for the operation (optional). Returns: A Tensor of type string.
tf.raw_ops.RegisterDataset Registers a dataset with the tf.data service.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.RegisterDataset  
tf.raw_ops.RegisterDataset(
    dataset, address, protocol, external_state_policy, name=None
)

 


 Args
  dataset   A Tensor of type variant.  
  address   A Tensor of type string.  
  protocol   A Tensor of type string.  
  external_state_policy   An int.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type int64.
tf.raw_ops.Relu Computes rectified linear: max(features, 0).  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.Relu  
tf.raw_ops.Relu(
    features, name=None
)
 See: https://en.wikipedia.org/wiki/Rectifier_(neural_networks) Example usage: >>> tf.nn.relu([-2., 0., -0., 3.]).numpy()
array([ 0.,  0., -0.,  3.], dtype=float32)

 


 Args
  features   A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, int64, bfloat16, uint16, half, uint32, uint64, qint8.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as features.