neulab/docprompting-conala huggingface dataset:
tf.raw_ops.DebugGradientRefIdentity Identity op for gradient debugging.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DebugGradientRefIdentity  
tf.raw_ops.DebugGradientRefIdentity(
    input, name=None
)
 This op is hidden from public in Python. It is used by TensorFlow Debugger to register gradient tensors for gradient debugging. This op operates on reference-type tensors.
 


 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.DebugIdentity Provides an identity mapping of the non-Ref type input tensor for debugging.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DebugIdentity  
tf.raw_ops.DebugIdentity(
    input, device_name='', tensor_name='', debug_urls=[],
    gated_grpc=False, name=None
)
 Provides an identity mapping of the non-Ref type input tensor for debugging.
 


 Args
  input   A Tensor. Input tensor, non-Reference type  
  device_name   An optional string. Defaults to "". Name of the device on which the tensor resides.  
  tensor_name   An optional string. Defaults to "". Name of the input tensor.  
  debug_urls   An optional list of strings. Defaults to []. List of URLs to debug targets, e.g., file:///foo/tfdbg_dump, grpc:://localhost:11011  
  gated_grpc   An optional bool. Defaults to False. Whether this op will be gated. If any of the debug_urls of this debug node is of the grpc:// scheme, when the value of this attribute is set to True, the data will not actually be sent via the grpc stream unless this debug op has been enabled at the debug_url. If all of the debug_urls of this debug node are of the grpc:// scheme and the debug op is enabled at none of them, the output will be an empty Tensor.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as input.
tf.raw_ops.DebugIdentityV2 Debug Identity V2 Op.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DebugIdentityV2  
tf.raw_ops.DebugIdentityV2(
    input, tfdbg_context_id='', op_name='', output_slot=-1,
    tensor_debug_mode=-1, debug_urls=[], circular_buffer_size=1000,
    tfdbg_run_id='', name=None
)
 Provides an identity mapping from input to output, while writing the content of the input tensor by calling DebugEventsWriter. The semantics of the input tensor depends on tensor_debug_mode. In typical usage, the input tensor comes directly from the user computation only when graph_debug_mode is FULL_TENSOR (see protobuf/debug_event.proto for a list of all the possible values of graph_debug_mode). For the other debug modes, the input tensor should be produced by an additional op or subgraph that computes summary information about one or more tensors.
 


 Args
  input   A Tensor. Input tensor, non-Reference type  
  tfdbg_context_id   An optional string. Defaults to "". A tfdbg-generated ID for the context that the op belongs to, e.g., a concrete compiled tf.function.  
  op_name   An optional string. Defaults to "". Optional. Name of the op that the debug op is concerned with. Used only for single-tensor trace.  
  output_slot   An optional int. Defaults to -1. Optional. Output slot index of the tensor that the debug op is concerned with. Used only for single-tensor trace.  
  tensor_debug_mode   An optional int. Defaults to -1. TensorDebugMode enum value. See debug_event.proto for details.  
  debug_urls   An optional list of strings. Defaults to []. List of URLs to debug targets, e.g., file:///foo/tfdbg_dump.  
  circular_buffer_size   An optional int. Defaults to 1000.  
  tfdbg_run_id   An optional string. Defaults to "".  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as input.
tf.raw_ops.DebugNanCount Debug NaN Value Counter Op.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DebugNanCount  
tf.raw_ops.DebugNanCount(
    input, device_name='', tensor_name='', debug_urls=[],
    gated_grpc=False, name=None
)
 Counts number of NaNs in the input tensor, for debugging.
 


 Args
  input   A Tensor. Input tensor, non-Reference type.  
  device_name   An optional string. Defaults to "".  
  tensor_name   An optional string. Defaults to "". Name of the input tensor.  
  debug_urls   An optional list of strings. Defaults to []. List of URLs to debug targets, e.g., file:///foo/tfdbg_dump, grpc:://localhost:11011.  
  gated_grpc   An optional bool. Defaults to False. Whether this op will be gated. If any of the debug_urls of this debug node is of the grpc:// scheme, when the value of this attribute is set to True, the data will not actually be sent via the grpc stream unless this debug op has been enabled at the debug_url. If all of the debug_urls of this debug node are of the grpc:// scheme and the debug op is enabled at none of them, the output will be an empty Tensor.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type int64.
tf.raw_ops.DecodeAndCropJpeg Decode and Crop a JPEG-encoded image to a uint8 tensor.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DecodeAndCropJpeg  
tf.raw_ops.DecodeAndCropJpeg(
    contents, crop_window, channels=0, ratio=1, fancy_upscaling=True,
    try_recover_truncated=False, acceptable_fraction=1, dct_method='',
    name=None
)
 The attr channels indicates the desired number of color channels for the decoded image. Accepted values are:  0: Use the number of channels in the JPEG-encoded image. 1: output a grayscale image. 3: output an RGB image.  If needed, the JPEG-encoded image is transformed to match the requested number of color channels. The attr ratio allows downscaling the image by an integer factor during decoding. Allowed values are: 1, 2, 4, and 8. This is much faster than downscaling the image later. It is equivalent to a combination of decode and crop, but much faster by only decoding partial jpeg image.
 


 Args
  contents   A Tensor of type string. 0-D. The JPEG-encoded image.  
  crop_window   A Tensor of type int32. 1-D. The crop window: [crop_y, crop_x, crop_height, crop_width].  
  channels   An optional int. Defaults to 0. Number of color channels for the decoded image.  
  ratio   An optional int. Defaults to 1. Downscaling ratio.  
  fancy_upscaling   An optional bool. Defaults to True. If true use a slower but nicer upscaling of the chroma planes (yuv420/422 only).  
  try_recover_truncated   An optional bool. Defaults to False. If true try to recover an image from truncated input.  
  acceptable_fraction   An optional float. Defaults to 1. The minimum required fraction of lines before a truncated input is accepted.  
  dct_method   An optional string. Defaults to "". string specifying a hint about the algorithm used for decompression. Defaults to "" which maps to a system-specific default. Currently valid values are ["INTEGER_FAST", "INTEGER_ACCURATE"]. The hint may be ignored (e.g., the internal jpeg library changes to a version that does not have that specific option.)  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type uint8.
tf.raw_ops.DecodeBase64 Decode web-safe base64-encoded strings.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DecodeBase64  
tf.raw_ops.DecodeBase64(
    input, name=None
)
 Input may or may not have padding at the end. See EncodeBase64 for padding. Web-safe means that input must use - and _ instead of + and /.
 


 Args
  input   A Tensor of type string. Base64 strings to decode.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type string.
tf.raw_ops.DecodeBmp Decode the first frame of a BMP-encoded image to a uint8 tensor.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DecodeBmp  
tf.raw_ops.DecodeBmp(
    contents, channels=0, name=None
)
 The attr channels indicates the desired number of color channels for the decoded image. Accepted values are:  0: Use the number of channels in the BMP-encoded image. 3: output an RGB image. 4: output an RGBA image. 
 


 Args
  contents   A Tensor of type string. 0-D. The BMP-encoded image.  
  channels   An optional int. Defaults to 0.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type uint8.
tf.raw_ops.DecodeCompressed Decompress strings.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DecodeCompressed  
tf.raw_ops.DecodeCompressed(
    bytes, compression_type='', name=None
)
 This op decompresses each element of the bytes input Tensor, which is assumed to be compressed using the given compression_type. The output is a string Tensor of the same shape as bytes, each element containing the decompressed data from the corresponding element in bytes.
 


 Args
  bytes   A Tensor of type string. A Tensor of string which is compressed.  
  compression_type   An optional string. Defaults to "". A scalar containing either (i) the empty string (no compression), (ii) "ZLIB", or (iii) "GZIP".  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type string.
tf.raw_ops.DecodeCSV Convert CSV records to tensors. Each column maps to one tensor.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DecodeCSV  
tf.raw_ops.DecodeCSV(
    records, record_defaults, field_delim=',', use_quote_delim=True,
    na_value='', select_cols=[], name=None
)
 RFC 4180 format is expected for the CSV records. (https://tools.ietf.org/html/rfc4180) Note that we allow leading and trailing spaces with int or float field.
 


 Args
  records   A Tensor of type string. Each string is a record/row in the csv and all records should have the same format.  
  record_defaults   A list of Tensor objects with types from: float32, float64, int32, int64, string. One tensor per column of the input record, with either a scalar default value for that column or an empty vector if the column is required.  
  field_delim   An optional string. Defaults to ",". char delimiter to separate fields in a record.  
  use_quote_delim   An optional bool. Defaults to True. If false, treats double quotation marks as regular characters inside of the string fields (ignoring RFC 4180, Section 2, Bullet 5).  
  na_value   An optional string. Defaults to "". Additional string to recognize as NA/NaN.  
  select_cols   An optional list of ints. Defaults to [].  
  name   A name for the operation (optional).   
 


 Returns   A list of Tensor objects. Has the same type as record_defaults.
tf.raw_ops.DecodeGif   Decode the frame(s) of a GIF-encoded image to a uint8 tensor.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DecodeGif  
tf.raw_ops.DecodeGif(
    contents, name=None
)
 GIF images with frame or transparency compression are not supported. On Linux and MacOS systems, convert animated GIFs from compressed to uncompressed by running: convert $src.gif -coalesce $dst.gif
 This op also supports decoding JPEGs and PNGs, though it is cleaner to use tf.io.decode_image.
 


 Args
  contents   A Tensor of type string. 0-D. The GIF-encoded image.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type uint8.
tf.raw_ops.DecodeImage Function for decode_bmp, decode_gif, decode_jpeg, and decode_png.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DecodeImage  
tf.raw_ops.DecodeImage(
    contents, channels=0, dtype=tf.dtypes.uint8, expand_animations=True, name=None
)
 Detects whether an image is a BMP, GIF, JPEG, or PNG, and performs the appropriate operation to convert the input bytes string into a Tensor of type dtype. 
Note: decode_gif returns a 4-D array [num_frames, height, width, 3], as opposed to decode_bmp, decode_jpeg and decode_png, which return 3-D arrays [height, width, num_channels]. Make sure to take this into account when constructing your graph if you are intermixing GIF files with BMP, JPEG, and/or PNG files. Alternately, set the expand_animations argument of this function to False, in which case the op will return 3-dimensional tensors and will truncate animated GIF files to the first frame.


Note: If the first frame of an animated GIF does not occupy the entire canvas (maximum frame width x maximum frame height), then it fills the unoccupied areas (in the first frame) with zeros (black). For frames after the first frame that does not occupy the entire canvas, it uses the previous frame to fill the unoccupied areas.

 


 Args
  contents   A Tensor of type string. 0-D. The encoded image bytes.  
  channels   An optional int. Defaults to 0. Number of color channels for the decoded image.  
  dtype   An optional tf.DType from: tf.uint8, tf.uint16, tf.float32. Defaults to tf.uint8. The desired DType of the returned Tensor.  
  expand_animations   An optional bool. Defaults to True. Controls the output shape of the returned op. If True, the returned op will produce a 3-D tensor for PNG, JPEG, and BMP files; and a 4-D tensor for all GIFs, whether animated or not. If, False, the returned op will produce a 3-D tensor for all file types and will truncate animated GIFs to the first frame.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type dtype.
tf.raw_ops.DecodeJpeg Decode a JPEG-encoded image to a uint8 tensor.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DecodeJpeg  
tf.raw_ops.DecodeJpeg(
    contents, channels=0, ratio=1, fancy_upscaling=True,
    try_recover_truncated=False, acceptable_fraction=1, dct_method='',
    name=None
)
 The attr channels indicates the desired number of color channels for the decoded image. Accepted values are:  0: Use the number of channels in the JPEG-encoded image. 1: output a grayscale image. 3: output an RGB image.  If needed, the JPEG-encoded image is transformed to match the requested number of color channels. The attr ratio allows downscaling the image by an integer factor during decoding. Allowed values are: 1, 2, 4, and 8. This is much faster than downscaling the image later. This op also supports decoding PNGs and non-animated GIFs since the interface is the same, though it is cleaner to use tf.io.decode_image.
 


 Args
  contents   A Tensor of type string. 0-D. The JPEG-encoded image.  
  channels   An optional int. Defaults to 0. Number of color channels for the decoded image.  
  ratio   An optional int. Defaults to 1. Downscaling ratio.  
  fancy_upscaling   An optional bool. Defaults to True. If true use a slower but nicer upscaling of the chroma planes (yuv420/422 only).  
  try_recover_truncated   An optional bool. Defaults to False. If true try to recover an image from truncated input.  
  acceptable_fraction   An optional float. Defaults to 1. The minimum required fraction of lines before a truncated input is accepted.  
  dct_method   An optional string. Defaults to "". string specifying a hint about the algorithm used for decompression. Defaults to "" which maps to a system-specific default. Currently valid values are ["INTEGER_FAST", "INTEGER_ACCURATE"]. The hint may be ignored (e.g., the internal jpeg library changes to a version that does not have that specific option.)  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type uint8.
tf.raw_ops.DecodeJSONExample Convert JSON-encoded Example records to binary protocol buffer strings.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DecodeJSONExample  
tf.raw_ops.DecodeJSONExample(
    json_examples, name=None
)
 This op translates a tensor containing Example records, encoded using the standard JSON mapping, into a tensor containing the same records encoded as binary protocol buffers. The resulting tensor can then be fed to any of the other Example-parsing ops.
 


 Args
  json_examples   A Tensor of type string. Each string is a JSON object serialized according to the JSON mapping of the Example proto.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type string.
tf.raw_ops.DecodePaddedRaw Reinterpret the bytes of a string as a vector of numbers.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DecodePaddedRaw  
tf.raw_ops.DecodePaddedRaw(
    input_bytes, fixed_length, out_type, little_endian=True, name=None
)

 


 Args
  input_bytes   A Tensor of type string. Tensor of string to be decoded.  
  fixed_length   A Tensor of type int32. Length in bytes for each element of the decoded output. Must be a multiple of the size of the output type.  
  out_type   A tf.DType from: tf.half, tf.float32, tf.float64, tf.int32, tf.uint16, tf.uint8, tf.int16, tf.int8, tf.int64.  
  little_endian   An optional bool. Defaults to True. Whether the input input_bytes is in little-endian order. Ignored for out_type values that are stored in a single byte, like uint8  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type out_type.
tf.raw_ops.DecodePng Decode a PNG-encoded image to a uint8 or uint16 tensor.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DecodePng  
tf.raw_ops.DecodePng(
    contents, channels=0, dtype=tf.dtypes.uint8, name=None
)
 The attr channels indicates the desired number of color channels for the decoded image. Accepted values are:  0: Use the number of channels in the PNG-encoded image. 1: output a grayscale image. 3: output an RGB image. 4: output an RGBA image.  If needed, the PNG-encoded image is transformed to match the requested number of color channels. This op also supports decoding JPEGs and non-animated GIFs since the interface is the same, though it is cleaner to use tf.io.decode_image.
 


 Args
  contents   A Tensor of type string. 0-D. The PNG-encoded image.  
  channels   An optional int. Defaults to 0. Number of color channels for the decoded image.  
  dtype   An optional tf.DType from: tf.uint8, tf.uint16. Defaults to tf.uint8.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type dtype.
tf.raw_ops.DecodeRaw Reinterpret the bytes of a string as a vector of numbers.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DecodeRaw  
tf.raw_ops.DecodeRaw(
    bytes, out_type, little_endian=True, name=None
)

 


 Args
  bytes   A Tensor of type string. All the elements must have the same length.  
  out_type   A tf.DType from: tf.half, tf.float32, tf.float64, tf.int32, tf.uint16, tf.uint8, tf.int16, tf.int8, tf.int64, tf.complex64, tf.complex128, tf.bool.  
  little_endian   An optional bool. Defaults to True. Whether the input bytes are in little-endian order. Ignored for out_type values that are stored in a single byte like uint8.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type out_type.
tf.raw_ops.DecodeWav Decode a 16-bit PCM WAV file to a float tensor.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DecodeWav  
tf.raw_ops.DecodeWav(
    contents, desired_channels=-1, desired_samples=-1, name=None
)
 The -32768 to 32767 signed 16-bit values will be scaled to -1.0 to 1.0 in float. When desired_channels is set, if the input contains fewer channels than this then the last channel will be duplicated to give the requested number, else if the input has more channels than requested then the additional channels will be ignored. If desired_samples is set, then the audio will be cropped or padded with zeroes to the requested length. The first output contains a Tensor with the content of the audio samples. The lowest dimension will be the number of channels, and the second will be the number of samples. For example, a ten-sample-long stereo WAV file should give an output shape of [10, 2].
 


 Args
  contents   A Tensor of type string. The WAV-encoded audio, usually from a file.  
  desired_channels   An optional int. Defaults to -1. Number of sample channels wanted.  
  desired_samples   An optional int. Defaults to -1. Length of audio requested.  
  name   A name for the operation (optional).   
 


 Returns   A tuple of Tensor objects (audio, sample_rate).     audio   A Tensor of type float32.  
  sample_rate   A Tensor of type int32.
tf.raw_ops.DeepCopy Makes a copy of x.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DeepCopy  
tf.raw_ops.DeepCopy(
    x, name=None
)

 


 Args
  x   A Tensor. The source tensor of type T.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as x.
tf.raw_ops.DeleteIterator A container for an iterator resource.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DeleteIterator  
tf.raw_ops.DeleteIterator(
    handle, deleter, name=None
)

 


 Args
  handle   A Tensor of type resource. A handle to the iterator to delete.  
  deleter   A Tensor of type variant. A variant deleter.  
  name   A name for the operation (optional).   
 


 Returns   The created Operation.
tf.raw_ops.DeleteMemoryCache  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DeleteMemoryCache  
tf.raw_ops.DeleteMemoryCache(
    handle, deleter, name=None
)

 


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


 Returns   The created Operation.
tf.raw_ops.DeleteMultiDeviceIterator A container for an iterator resource.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DeleteMultiDeviceIterator  
tf.raw_ops.DeleteMultiDeviceIterator(
    multi_device_iterator, iterators, deleter, name=None
)

 


 Args
  multi_device_iterator   A Tensor of type resource. A handle to the multi device iterator to delete.  
  iterators   A list of Tensor objects with type resource. A list of iterator handles (unused). This is added so that automatic control dependencies get added during function tracing that ensure this op runs after all the dependent iterators are deleted.  
  deleter   A Tensor of type variant. A variant deleter.  
  name   A name for the operation (optional).   
 


 Returns   The created Operation.
tf.raw_ops.DeleteRandomSeedGenerator  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DeleteRandomSeedGenerator  
tf.raw_ops.DeleteRandomSeedGenerator(
    handle, deleter, name=None
)

 


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


 Returns   The created Operation.
tf.raw_ops.DeleteSeedGenerator  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DeleteSeedGenerator  
tf.raw_ops.DeleteSeedGenerator(
    handle, deleter, name=None
)

 


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


 Returns   The created Operation.
tf.raw_ops.DeleteSessionTensor Delete the tensor specified by its handle in the session.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.DeleteSessionTensor  
tf.raw_ops.DeleteSessionTensor(
    handle, name=None
)

 


 Args
  handle   A Tensor of type string. The handle for a tensor stored in the session state.  
  name   A name for the operation (optional).   
 


 Returns   The created Operation.