neulab/docprompting-conala huggingface dataset:
tf.raw_ops.TensorArrayGradV3 Creates a TensorArray for storing the gradients of values in the given handle.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorArrayGradV3  
tf.raw_ops.TensorArrayGradV3(
    handle, flow_in, source, name=None
)
 If the given TensorArray gradient already exists, returns a reference to it. Locks the size of the original TensorArray by disabling its dynamic size flag. A note about the input flow_in: The handle flow_in forces the execution of the gradient lookup to occur only after certain other operations have occurred. For example, when the forward TensorArray is dynamically sized, writes to this TensorArray may resize the object. The gradient TensorArray is statically sized based on the size of the forward TensorArray when this operation executes. Furthermore, the size of the forward TensorArray is frozen by this call. As a result, the flow is used to ensure that the call to generate the gradient TensorArray only happens after all writes are executed. In the case of dynamically sized TensorArrays, gradient computation should only be performed on read operations that have themselves been chained via flow to occur only after all writes have executed. That way the final size of the forward TensorArray is known when this operation is called. A note about the source attribute: TensorArray gradient calls use an accumulator TensorArray object. If multiple gradients are calculated and run in the same session, the multiple gradient nodes may accidentally flow through the same accumulator TensorArray. This double counts and generally breaks the TensorArray gradient flow. The solution is to identify which gradient call this particular TensorArray gradient is being called in. This is performed by identifying a unique string (e.g. "gradients", "gradients_1", ...) from the input gradient Tensor's name. This string is used as a suffix when creating the TensorArray gradient object here (the attribute source). The attribute source is added as a suffix to the forward TensorArray's name when performing the creation / lookup, so that each separate gradient calculation gets its own TensorArray accumulator.
 


 Args
  handle   A Tensor of type resource. The handle to the forward TensorArray.  
  flow_in   A Tensor of type float32. A float scalar that enforces proper chaining of operations.  
  source   A string. The gradient source string, used to decide which gradient TensorArray to return.  
  name   A name for the operation (optional).   
 


 Returns   A tuple of Tensor objects (grad_handle, flow_out).     grad_handle   A Tensor of type resource.  
  flow_out   A Tensor of type float32.
tf.raw_ops.TensorArrayGradWithShape Creates a TensorArray for storing multiple gradients of values in the given handle.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorArrayGradWithShape  
tf.raw_ops.TensorArrayGradWithShape(
    handle, flow_in, shape_to_prepend, source, name=None
)
 Similar to TensorArrayGradV3. However it creates an accumulator with an expanded shape compared to the input TensorArray whose gradient is being computed. This enables multiple gradients for the same TensorArray to be calculated using the same accumulator.
 


 Args
  handle   A Tensor of type resource. The handle to the forward TensorArray.  
  flow_in   A Tensor of type float32. A float scalar that enforces proper chaining of operations.  
  shape_to_prepend   A Tensor of type int32. An int32 vector representing a shape. Elements in the gradient accumulator will have shape which is this shape_to_prepend value concatenated with shape of the elements in the TensorArray corresponding to the input handle.  
  source   A string. The gradient source string, used to decide which gradient TensorArray to return.  
  name   A name for the operation (optional).   
 


 Returns   A tuple of Tensor objects (grad_handle, flow_out).     grad_handle   A Tensor of type resource.  
  flow_out   A Tensor of type float32.
tf.raw_ops.TensorArrayPack  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorArrayPack  
tf.raw_ops.TensorArrayPack(
    handle, flow_in, dtype, element_shape=None, name=None
)

 


 Args
  handle   A Tensor of type mutable string.  
  flow_in   A Tensor of type float32.  
  dtype   A tf.DType.  
  element_shape   An optional tf.TensorShape or list of ints. Defaults to None.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type dtype.
tf.raw_ops.TensorArrayRead  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorArrayRead  
tf.raw_ops.TensorArrayRead(
    handle, index, flow_in, dtype, name=None
)

 


 Args
  handle   A Tensor of type mutable string.  
  index   A Tensor of type int32.  
  flow_in   A Tensor of type float32.  
  dtype   A tf.DType.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type dtype.
tf.raw_ops.TensorArrayReadV2 Deprecated. Use TensorArrayReadV3  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorArrayReadV2  
tf.raw_ops.TensorArrayReadV2(
    handle, index, flow_in, dtype, name=None
)

 


 Args
  handle   A Tensor of type string.  
  index   A Tensor of type int32.  
  flow_in   A Tensor of type float32.  
  dtype   A tf.DType.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type dtype.
tf.raw_ops.TensorArrayReadV3 Read an element from the TensorArray into output value.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorArrayReadV3  
tf.raw_ops.TensorArrayReadV3(
    handle, index, flow_in, dtype, name=None
)

 


 Args
  handle   A Tensor of type resource. The handle to a TensorArray.  
  index   A Tensor of type int32.  
  flow_in   A Tensor of type float32. A float scalar that enforces proper chaining of operations.  
  dtype   A tf.DType. The type of the elem that is returned.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type dtype.
tf.raw_ops.TensorArrayScatter  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorArrayScatter  
tf.raw_ops.TensorArrayScatter(
    handle, indices, value, flow_in, name=None
)

 


 Args
  handle   A Tensor of type mutable string.  
  indices   A Tensor of type int32.  
  value   A Tensor.  
  flow_in   A Tensor of type float32.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type float32.
tf.raw_ops.TensorArrayScatterV2 Deprecated. Use TensorArrayScatterV3  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorArrayScatterV2  
tf.raw_ops.TensorArrayScatterV2(
    handle, indices, value, flow_in, name=None
)

 


 Args
  handle   A Tensor of type string.  
  indices   A Tensor of type int32.  
  value   A Tensor.  
  flow_in   A Tensor of type float32.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type float32.
tf.raw_ops.TensorArrayScatterV3 Scatter the data from the input value into specific TensorArray elements.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorArrayScatterV3  
tf.raw_ops.TensorArrayScatterV3(
    handle, indices, value, flow_in, name=None
)
 indices must be a vector, its length must match the first dim of value.
 


 Args
  handle   A Tensor of type resource. The handle to a TensorArray.  
  indices   A Tensor of type int32. The locations at which to write the tensor elements.  
  value   A Tensor. The concatenated tensor to write to the TensorArray.  
  flow_in   A Tensor of type float32. A float scalar that enforces proper chaining of operations.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type float32.
tf.raw_ops.TensorArraySize  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorArraySize  
tf.raw_ops.TensorArraySize(
    handle, flow_in, name=None
)

 


 Args
  handle   A Tensor of type mutable string.  
  flow_in   A Tensor of type float32.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type int32.
tf.raw_ops.TensorArraySizeV2 Deprecated. Use TensorArraySizeV3  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorArraySizeV2  
tf.raw_ops.TensorArraySizeV2(
    handle, flow_in, name=None
)

 


 Args
  handle   A Tensor of type string.  
  flow_in   A Tensor of type float32.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type int32.
tf.raw_ops.TensorArraySizeV3 Get the current size of the TensorArray.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorArraySizeV3  
tf.raw_ops.TensorArraySizeV3(
    handle, flow_in, name=None
)

 


 Args
  handle   A Tensor of type resource. The handle to a TensorArray (output of TensorArray or TensorArrayGrad).  
  flow_in   A Tensor of type float32. A float scalar that enforces proper chaining of operations.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type int32.
tf.raw_ops.TensorArraySplit  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorArraySplit  
tf.raw_ops.TensorArraySplit(
    handle, value, lengths, flow_in, name=None
)

 


 Args
  handle   A Tensor of type mutable string.  
  value   A Tensor.  
  lengths   A Tensor of type int64.  
  flow_in   A Tensor of type float32.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type float32.
tf.raw_ops.TensorArraySplitV2 Deprecated. Use TensorArraySplitV3  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorArraySplitV2  
tf.raw_ops.TensorArraySplitV2(
    handle, value, lengths, flow_in, name=None
)

 


 Args
  handle   A Tensor of type string.  
  value   A Tensor.  
  lengths   A Tensor of type int64.  
  flow_in   A Tensor of type float32.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type float32.
tf.raw_ops.TensorArraySplitV3 Split the data from the input value into TensorArray elements.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorArraySplitV3  
tf.raw_ops.TensorArraySplitV3(
    handle, value, lengths, flow_in, name=None
)
 Assuming that lengths takes on values (n0, n1, ..., n(T-1)) and that value has shape (n0 + n1 + ... + n(T-1) x d0 x d1 x ...), this splits values into a TensorArray with T tensors. TensorArray index t will be the subtensor of values with starting position (n0 + n1 + ... + n(t-1), 0, 0, ...) and having size nt x d0 x d1 x ...
 


 Args
  handle   A Tensor of type resource. The handle to a TensorArray.  
  value   A Tensor. The concatenated tensor to write to the TensorArray.  
  lengths   A Tensor of type int64. The vector of lengths, how to split the rows of value into the TensorArray.  
  flow_in   A Tensor of type float32. A float scalar that enforces proper chaining of operations.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type float32.
tf.raw_ops.TensorArrayUnpack  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorArrayUnpack  
tf.raw_ops.TensorArrayUnpack(
    handle, value, flow_in, name=None
)

 


 Args
  handle   A Tensor of type mutable string.  
  value   A Tensor.  
  flow_in   A Tensor of type float32.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type float32.
tf.raw_ops.TensorArrayV2 Deprecated. Use TensorArrayV3  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorArrayV2  
tf.raw_ops.TensorArrayV2(
    size, dtype, element_shape=None, dynamic_size=False, clear_after_read=True,
    tensor_array_name='', name=None
)

 


 Args
  size   A Tensor of type int32.  
  dtype   A tf.DType.  
  element_shape   An optional tf.TensorShape or list of ints. Defaults to None.  
  dynamic_size   An optional bool. Defaults to False.  
  clear_after_read   An optional bool. Defaults to True.  
  tensor_array_name   An optional string. Defaults to "".  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type string.
tf.raw_ops.TensorArrayV3 An array of Tensors of given size.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorArrayV3  
tf.raw_ops.TensorArrayV3(
    size, dtype, element_shape=None, dynamic_size=False, clear_after_read=True,
    identical_element_shapes=False, tensor_array_name='', name=None
)
 Write data via Write and read via Read or Pack.
 


 Args
  size   A Tensor of type int32. The size of the array.  
  dtype   A tf.DType. The type of the elements on the tensor_array.  
  element_shape   An optional tf.TensorShape or list of ints. Defaults to None. The expected shape of an element, if known. Used to validate the shapes of TensorArray elements. If this shape is not fully specified, gathering zero-size TensorArrays is an error.  
  dynamic_size   An optional bool. Defaults to False. A boolean that determines whether writes to the TensorArray are allowed to grow the size. By default, this is not allowed.  
  clear_after_read   An optional bool. Defaults to True. If true (default), Tensors in the TensorArray are cleared after being read. This disables multiple read semantics but allows early release of memory.  
  identical_element_shapes   An optional bool. Defaults to False. If true (default is false), then all elements in the TensorArray will be expected to have have identical shapes. This allows certain behaviors, like dynamically checking for consistent shapes on write, and being able to fill in properly shaped zero tensors on stack -- even if the element_shape attribute is not fully defined.  
  tensor_array_name   An optional string. Defaults to "". Overrides the name used for the temporary tensor_array resource. Default value is the name of the 'TensorArray' op (which is guaranteed unique).  
  name   A name for the operation (optional).   
 


 Returns   A tuple of Tensor objects (handle, flow).     handle   A Tensor of type resource.  
  flow   A Tensor of type float32.
tf.raw_ops.TensorArrayWrite  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorArrayWrite  
tf.raw_ops.TensorArrayWrite(
    handle, index, value, flow_in, name=None
)

 


 Args
  handle   A Tensor of type mutable string.  
  index   A Tensor of type int32.  
  value   A Tensor.  
  flow_in   A Tensor of type float32.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type float32.
tf.raw_ops.TensorArrayWriteV2 Deprecated. Use TensorArrayGradV3  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorArrayWriteV2  
tf.raw_ops.TensorArrayWriteV2(
    handle, index, value, flow_in, name=None
)

 


 Args
  handle   A Tensor of type string.  
  index   A Tensor of type int32.  
  value   A Tensor.  
  flow_in   A Tensor of type float32.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type float32.
tf.raw_ops.TensorArrayWriteV3 Push an element onto the tensor_array.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorArrayWriteV3  
tf.raw_ops.TensorArrayWriteV3(
    handle, index, value, flow_in, name=None
)

 


 Args
  handle   A Tensor of type resource. The handle to a TensorArray.  
  index   A Tensor of type int32. The position to write to inside the TensorArray.  
  value   A Tensor. The tensor to write to the TensorArray.  
  flow_in   A Tensor of type float32. A float scalar that enforces proper chaining of operations.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type float32.
tf.raw_ops.TensorDataset Creates a dataset that emits components as a tuple of tensors once.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorDataset  
tf.raw_ops.TensorDataset(
    components, output_shapes, name=None
)

 


 Args
  components   A list of Tensor objects.  
  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.TensorListConcat Concats all tensors in the list along the 0th dimension.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorListConcat  
tf.raw_ops.TensorListConcat(
    input_handle, element_dtype, element_shape=None, name=None
)
 Requires that all tensors have the same shape except the first dimension. input_handle: The input list. tensor: The concated result. lengths: Output tensor containing sizes of the 0th dimension of tensors in the list, used for computing the gradient.
 


 Args
  input_handle   A Tensor of type variant.  
  element_dtype   A tf.DType.  
  element_shape   An optional tf.TensorShape or list of ints. Defaults to None.  
  name   A name for the operation (optional).   
 


 Returns   A tuple of Tensor objects (tensor, lengths).     tensor   A Tensor of type element_dtype.  
  lengths   A Tensor of type int64.
tf.raw_ops.TensorListConcatLists  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorListConcatLists  
tf.raw_ops.TensorListConcatLists(
    input_a, input_b, element_dtype, name=None
)

 


 Args
  input_a   A Tensor of type variant.  
  input_b   A Tensor of type variant.  
  element_dtype   A tf.DType.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.
tf.raw_ops.TensorListConcatV2 Concats all tensors in the list along the 0th dimension.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorListConcatV2  
tf.raw_ops.TensorListConcatV2(
    input_handle, element_shape, leading_dims, element_dtype, name=None
)
 Requires that all tensors have the same shape except the first dimension. input_handle: The input list. element_shape: The shape of the uninitialized elements in the list. If the first dimension is not -1, it is assumed that all list elements have the same leading dim. leading_dims: The list of leading dims of uninitialized list elements. Used if the leading dim of input_handle.element_shape or the element_shape input arg is not already set. tensor: The concated result. lengths: Output tensor containing sizes of the 0th dimension of tensors in the list, used for computing the gradient.
 


 Args
  input_handle   A Tensor of type variant.  
  element_shape   A Tensor. Must be one of the following types: int32, int64.  
  leading_dims   A Tensor of type int64.  
  element_dtype   A tf.DType.  
  name   A name for the operation (optional).   
 


 Returns   A tuple of Tensor objects (tensor, lengths).     tensor   A Tensor of type element_dtype.  
  lengths   A Tensor of type int64.
tf.raw_ops.TensorListElementShape The shape of the elements of the given list, as a tensor.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorListElementShape  
tf.raw_ops.TensorListElementShape(
    input_handle, shape_type, name=None
)
 input_handle: the list element_shape: the shape of elements of the list
 


 Args
  input_handle   A Tensor of type variant.  
  shape_type   A tf.DType from: tf.int32, tf.int64.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type shape_type.
tf.raw_ops.TensorListFromTensor Creates a TensorList which, when stacked, has the value of tensor.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorListFromTensor  
tf.raw_ops.TensorListFromTensor(
    tensor, element_shape, name=None
)
 Each tensor in the result list corresponds to one row of the input tensor. tensor: The input tensor. output_handle: The list.
 


 Args
  tensor   A Tensor.  
  element_shape   A Tensor. Must be one of the following types: int32, int64.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.
tf.raw_ops.TensorListGather Creates a Tensor by indexing into the TensorList.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorListGather  
tf.raw_ops.TensorListGather(
    input_handle, indices, element_shape, element_dtype, name=None
)
 Each row in the produced Tensor corresponds to the element in the TensorList specified by the given index (see tf.gather). input_handle: The input tensor list. indices: The indices used to index into the list. values: The tensor.
 


 Args
  input_handle   A Tensor of type variant.  
  indices   A Tensor of type int32.  
  element_shape   A Tensor of type int32.  
  element_dtype   A tf.DType.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type element_dtype.
tf.raw_ops.TensorListGetItem Returns the item in the list with the given index.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorListGetItem  
tf.raw_ops.TensorListGetItem(
    input_handle, index, element_shape, element_dtype, name=None
)
 input_handle: the list index: the position in the list from which an element will be retrieved item: the element at that position
 


 Args
  input_handle   A Tensor of type variant.  
  index   A Tensor of type int32.  
  element_shape   A Tensor of type int32.  
  element_dtype   A tf.DType.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type element_dtype.
tf.raw_ops.TensorListLength Returns the number of tensors in the input tensor list.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorListLength  
tf.raw_ops.TensorListLength(
    input_handle, name=None
)
 input_handle: the input list length: the number of tensors in the list
 


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


 Returns   A Tensor of type int32.
tf.raw_ops.TensorListPopBack Returns the last element of the input list as well as a list with all but that element.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorListPopBack  
tf.raw_ops.TensorListPopBack(
    input_handle, element_shape, element_dtype, name=None
)
 Fails if the list is empty. input_handle: the input list tensor: the withdrawn last element of the list element_dtype: the type of elements in the list element_shape: the shape of the output tensor
 


 Args
  input_handle   A Tensor of type variant.  
  element_shape   A Tensor of type int32.  
  element_dtype   A tf.DType.  
  name   A name for the operation (optional).   
 


 Returns   A tuple of Tensor objects (output_handle, tensor).     output_handle   A Tensor of type variant.  
  tensor   A Tensor of type element_dtype.
tf.raw_ops.TensorListPushBack Returns a list which has the passed-in Tensor as last element and the other elements of the given list in input_handle.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.TensorListPushBack  
tf.raw_ops.TensorListPushBack(
    input_handle, tensor, name=None
)
 tensor: The tensor to put on the list. input_handle: The old list. output_handle: A list with the elements of the old list followed by tensor. element_dtype: the type of elements in the list. element_shape: a shape compatible with that of elements in the list.
 


 Args
  input_handle   A Tensor of type variant.  
  tensor   A Tensor.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type variant.