neulab/docprompting-conala huggingface dataset:
tf.raw_ops.AvgPool3DGrad Computes gradients of average pooling function.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.AvgPool3DGrad  
tf.raw_ops.AvgPool3DGrad(
    orig_input_shape, grad, ksize, strides, padding, data_format='NDHWC',
    name=None
)

 


 Args
  orig_input_shape   A Tensor of type int32. The original input dimensions.  
  grad   A Tensor. Must be one of the following types: half, bfloat16, float32, float64. Output backprop of shape [batch, depth, rows, cols, channels].  
  ksize   A list of ints that has length >= 5. 1-D tensor of length 5. The size of the window for each dimension of the input tensor. Must have ksize[0] = ksize[4] = 1.  
  strides   A list of ints that has length >= 5. 1-D tensor of length 5. The stride of the sliding window for each dimension of input. Must have strides[0] = strides[4] = 1.  
  padding   A string from: "SAME", "VALID". The type of padding algorithm to use.  
  data_format   An optional string from: "NDHWC", "NCDHW". Defaults to "NDHWC". The data format of the input and output data. With the default format "NDHWC", the data is stored in the order of: [batch, in_depth, in_height, in_width, in_channels]. Alternatively, the format could be "NCDHW", the data storage order is: [batch, in_channels, in_depth, in_height, in_width].  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as grad.
tf.raw_ops.AvgPoolGrad Computes gradients of the average pooling function.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.AvgPoolGrad  
tf.raw_ops.AvgPoolGrad(
    orig_input_shape, grad, ksize, strides, padding, data_format='NHWC',
    name=None
)

 


 Args
  orig_input_shape   A Tensor of type int32. 1-D. Shape of the original input to avg_pool.  
  grad   A Tensor. Must be one of the following types: half, bfloat16, float32, float64. 4-D with shape [batch, height, width, channels]. Gradients w.r.t. the output of avg_pool.  
  ksize   A list of ints that has length >= 4. The size of the sliding window for each dimension of the input.  
  strides   A list of ints that has length >= 4. The stride of the sliding window for each dimension of the input.  
  padding   A string from: "SAME", "VALID". The type of padding algorithm to use.  
  data_format   An optional string from: "NHWC", "NCHW". Defaults to "NHWC". Specify the data format of the input and output data. With the default format "NHWC", the data is stored in the order of: [batch, in_height, in_width, in_channels]. Alternatively, the format could be "NCHW", the data storage order of: [batch, in_channels, in_height, in_width].  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as grad.
tf.raw_ops.BandedTriangularSolve  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BandedTriangularSolve  
tf.raw_ops.BandedTriangularSolve(
    matrix, rhs, lower=True, adjoint=False, name=None
)

 


 Args
  matrix   A Tensor. Must be one of the following types: float64, float32, half, complex64, complex128.  
  rhs   A Tensor. Must have the same type as matrix.  
  lower   An optional bool. Defaults to True.  
  adjoint   An optional bool. Defaults to False.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as matrix.
tf.raw_ops.Barrier Defines a barrier that persists across different graph executions.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.Barrier  
tf.raw_ops.Barrier(
    component_types, shapes=[], capacity=-1, container='',
    shared_name='', name=None
)
 A barrier represents a key-value map, where each key is a string, and each value is a tuple of tensors. At runtime, the barrier contains 'complete' and 'incomplete' elements. A complete element has defined tensors for all components of its value tuple, and may be accessed using BarrierTakeMany. An incomplete element has some undefined components in its value tuple, and may be updated using BarrierInsertMany.
 


 Args
  component_types   A list of tf.DTypes that has length >= 1. The type of each component in a value.  
  shapes   An optional list of shapes (each a tf.TensorShape or list of ints). Defaults to []. The shape of each component in a value. Each shape must be 1 in the first dimension. The length of this attr must be the same as the length of component_types.  
  capacity   An optional int. Defaults to -1. The capacity of the barrier. The default capacity is MAX_INT32, which is the largest capacity of the underlying queue.  
  container   An optional string. Defaults to "". If non-empty, this barrier is placed in the given container. Otherwise, a default container is used.  
  shared_name   An optional string. Defaults to "". If non-empty, this barrier will be shared under the given name across multiple sessions.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type mutable string.
tf.raw_ops.BarrierClose Closes the given barrier.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BarrierClose  
tf.raw_ops.BarrierClose(
    handle, cancel_pending_enqueues=False, name=None
)
 This operation signals that no more new elements will be inserted in the given barrier. Subsequent InsertMany that try to introduce a new key will fail. Subsequent InsertMany operations that just add missing components to already existing elements will continue to succeed. Subsequent TakeMany operations will continue to succeed if sufficient completed elements remain in the barrier. Subsequent TakeMany operations that would block will fail immediately.
 


 Args
  handle   A Tensor of type mutable string. The handle to a barrier.  
  cancel_pending_enqueues   An optional bool. Defaults to False. If true, all pending enqueue requests that are blocked on the barrier's queue will be canceled. InsertMany will fail, even if no new key is introduced.  
  name   A name for the operation (optional).   
 


 Returns   The created Operation.
tf.raw_ops.BarrierIncompleteSize Computes the number of incomplete elements in the given barrier.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BarrierIncompleteSize  
tf.raw_ops.BarrierIncompleteSize(
    handle, name=None
)

 


 Args
  handle   A Tensor of type mutable string. The handle to a barrier.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type int32.
tf.raw_ops.BarrierInsertMany For each key, assigns the respective value to the specified component.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BarrierInsertMany  
tf.raw_ops.BarrierInsertMany(
    handle, keys, values, component_index, name=None
)
 If a key is not found in the barrier, this operation will create a new incomplete element. If a key is found in the barrier, and the element already has a value at component_index, this operation will fail with INVALID_ARGUMENT, and leave the barrier in an undefined state.
 


 Args
  handle   A Tensor of type mutable string. The handle to a barrier.  
  keys   A Tensor of type string. A one-dimensional tensor of keys, with length n.  
  values   A Tensor. An any-dimensional tensor of values, which are associated with the respective keys. The 0th dimension must have length n.  
  component_index   An int. The component of the barrier elements that is being assigned.  
  name   A name for the operation (optional).   
 


 Returns   The created Operation.
tf.raw_ops.BarrierReadySize Computes the number of complete elements in the given barrier.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BarrierReadySize  
tf.raw_ops.BarrierReadySize(
    handle, name=None
)

 


 Args
  handle   A Tensor of type mutable string. The handle to a barrier.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type int32.
tf.raw_ops.BarrierTakeMany Takes the given number of completed elements from a barrier.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BarrierTakeMany  
tf.raw_ops.BarrierTakeMany(
    handle, num_elements, component_types, allow_small_batch=False,
    wait_for_incomplete=False, timeout_ms=-1, name=None
)
 This operation concatenates completed-element component tensors along the 0th dimension to make a single component tensor. Elements come out of the barrier when they are complete, and in the order in which they were placed into the barrier. The indices output provides information about the batch in which each element was originally inserted into the barrier.
 


 Args
  handle   A Tensor of type mutable string. The handle to a barrier.  
  num_elements   A Tensor of type int32. A single-element tensor containing the number of elements to take.  
  component_types   A list of tf.DTypes that has length >= 1. The type of each component in a value.  
  allow_small_batch   An optional bool. Defaults to False. Allow to return less than num_elements items if barrier is already closed.  
  wait_for_incomplete   An optional bool. Defaults to False.  
  timeout_ms   An optional int. Defaults to -1. If the queue is empty, this operation will block for up to timeout_ms milliseconds. Note: This option is not supported yet.  
  name   A name for the operation (optional).   
 


 Returns   A tuple of Tensor objects (indices, keys, values).     indices   A Tensor of type int64.  
  keys   A Tensor of type string.  
  values   A list of Tensor objects of type component_types.
tf.raw_ops.BatchCholesky  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BatchCholesky  
tf.raw_ops.BatchCholesky(
    input, name=None
)

 


 Args
  input   A Tensor. Must be one of the following types: float64, float32.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as input.
tf.raw_ops.BatchCholeskyGrad  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BatchCholeskyGrad  
tf.raw_ops.BatchCholeskyGrad(
    l, grad, name=None
)

 


 Args
  l   A Tensor. Must be one of the following types: float32, float64.  
  grad   A Tensor. Must have the same type as l.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as l.
tf.raw_ops.BatchDataset Creates a dataset that batches batch_size elements from input_dataset.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BatchDataset  
tf.raw_ops.BatchDataset(
    input_dataset, batch_size, output_types, output_shapes, name=None
)

 


 Args
  input_dataset   A Tensor of type variant.  
  batch_size   A Tensor of type int64. A scalar representing the number of elements to accumulate in a batch.  
  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.BatchDatasetV2 Creates a dataset that batches batch_size elements from input_dataset.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BatchDatasetV2  
tf.raw_ops.BatchDatasetV2(
    input_dataset, batch_size, drop_remainder, output_types, output_shapes,
    parallel_copy=False, name=None
)

 


 Args
  input_dataset   A Tensor of type variant.  
  batch_size   A Tensor of type int64. A scalar representing the number of elements to accumulate in a batch.  
  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.  
  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.  
  parallel_copy   An optional bool. Defaults to False.  
  name   A name for the operation (optional).   
 


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

 


 Args
  input   A Tensor of type complex64.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type complex64.
tf.raw_ops.BatchFFT2D  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BatchFFT2D  
tf.raw_ops.BatchFFT2D(
    input, name=None
)

 


 Args
  input   A Tensor of type complex64.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type complex64.
tf.raw_ops.BatchFFT3D  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BatchFFT3D  
tf.raw_ops.BatchFFT3D(
    input, name=None
)

 


 Args
  input   A Tensor of type complex64.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type complex64.
tf.raw_ops.BatchIFFT  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BatchIFFT  
tf.raw_ops.BatchIFFT(
    input, name=None
)

 


 Args
  input   A Tensor of type complex64.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type complex64.
tf.raw_ops.BatchIFFT2D  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BatchIFFT2D  
tf.raw_ops.BatchIFFT2D(
    input, name=None
)

 


 Args
  input   A Tensor of type complex64.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type complex64.
tf.raw_ops.BatchIFFT3D  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BatchIFFT3D  
tf.raw_ops.BatchIFFT3D(
    input, name=None
)

 


 Args
  input   A Tensor of type complex64.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type complex64.
tf.raw_ops.BatchMatMul Multiplies slices of two tensors in batches.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BatchMatMul  
tf.raw_ops.BatchMatMul(
    x, y, adj_x=False, adj_y=False, name=None
)
 Multiplies all slices of Tensor x and y (each slice can be viewed as an element of a batch), and arranges the individual results in a single output tensor of the same batch size. Each of the individual slices can optionally be adjointed (to adjoint a matrix means to transpose and conjugate it) before multiplication by setting the adj_x or adj_y flag to True, which are by default False. The input tensors x and y are 2-D or higher with shape [..., r_x, c_x] and [..., r_y, c_y]. The output tensor is 2-D or higher with shape [..., r_o, c_o], where: r_o = c_x if adj_x else r_x
c_o = r_y if adj_y else c_y
 It is computed as: output[..., :, :] = matrix(x[..., :, :]) * matrix(y[..., :, :])
 


 Args
  x   A Tensor. Must be one of the following types: bfloat16, half, float32, float64, int32, int64, complex64, complex128. 2-D or higher with shape [..., r_x, c_x].  
  y   A Tensor. Must have the same type as x. 2-D or higher with shape [..., r_y, c_y].  
  adj_x   An optional bool. Defaults to False. If True, adjoint the slices of x. Defaults to False.  
  adj_y   An optional bool. Defaults to False. If True, adjoint the slices of y. Defaults to False.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as x.
tf.raw_ops.BatchMatMulV2 Multiplies slices of two tensors in batches.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BatchMatMulV2  
tf.raw_ops.BatchMatMulV2(
    x, y, adj_x=False, adj_y=False, name=None
)
 Multiplies all slices of Tensor x and y (each slice can be viewed as an element of a batch), and arranges the individual results in a single output tensor of the same batch size. Each of the individual slices can optionally be adjointed (to adjoint a matrix means to transpose and conjugate it) before multiplication by setting the adj_x or adj_y flag to True, which are by default False. The input tensors x and y are 2-D or higher with shape [..., r_x, c_x] and [..., r_y, c_y]. The output tensor is 2-D or higher with shape [..., r_o, c_o], where: r_o = c_x if adj_x else r_x
c_o = r_y if adj_y else c_y
 It is computed as: output[..., :, :] = matrix(x[..., :, :]) * matrix(y[..., :, :]) 
Note: BatchMatMulV2 supports broadcasting in the batch dimensions. More about broadcasting here.

 


 Args
  x   A Tensor. Must be one of the following types: bfloat16, half, float32, float64, int16, int32, int64, complex64, complex128. 2-D or higher with shape [..., r_x, c_x].  
  y   A Tensor. Must have the same type as x. 2-D or higher with shape [..., r_y, c_y].  
  adj_x   An optional bool. Defaults to False. If True, adjoint the slices of x. Defaults to False.  
  adj_y   An optional bool. Defaults to False. If True, adjoint the slices of y. Defaults to False.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as x.
tf.raw_ops.BatchMatrixBandPart  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BatchMatrixBandPart  
tf.raw_ops.BatchMatrixBandPart(
    input, num_lower, num_upper, name=None
)

 


 Args
  input   A Tensor.  
  num_lower   A Tensor of type int64.  
  num_upper   A Tensor of type int64.  
  name   A name for the operation (optional).   
 


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

 


 Args
  input   A Tensor. Must be one of the following types: float32, float64, complex64, complex128.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as input.
tf.raw_ops.BatchMatrixDiag  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BatchMatrixDiag  
tf.raw_ops.BatchMatrixDiag(
    diagonal, name=None
)

 


 Args
  diagonal   A Tensor.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as diagonal.
tf.raw_ops.BatchMatrixDiagPart  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BatchMatrixDiagPart  
tf.raw_ops.BatchMatrixDiagPart(
    input, name=None
)

 


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


 Returns   A Tensor. Has the same type as input.
tf.raw_ops.BatchMatrixInverse  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BatchMatrixInverse  
tf.raw_ops.BatchMatrixInverse(
    input, adjoint=False, name=None
)

 


 Args
  input   A Tensor. Must be one of the following types: float64, float32.  
  adjoint   An optional bool. Defaults to False.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as input.
tf.raw_ops.BatchMatrixSetDiag  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BatchMatrixSetDiag  
tf.raw_ops.BatchMatrixSetDiag(
    input, diagonal, name=None
)

 


 Args
  input   A Tensor.  
  diagonal   A Tensor. Must have the same type as input.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as input.
tf.raw_ops.BatchMatrixSolve  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BatchMatrixSolve  
tf.raw_ops.BatchMatrixSolve(
    matrix, rhs, adjoint=False, name=None
)

 


 Args
  matrix   A Tensor. Must be one of the following types: float64, float32.  
  rhs   A Tensor. Must have the same type as matrix.  
  adjoint   An optional bool. Defaults to False.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as matrix.
tf.raw_ops.BatchMatrixSolveLs  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BatchMatrixSolveLs  
tf.raw_ops.BatchMatrixSolveLs(
    matrix, rhs, l2_regularizer, fast=True, name=None
)

 


 Args
  matrix   A Tensor. Must be one of the following types: float64, float32.  
  rhs   A Tensor. Must have the same type as matrix.  
  l2_regularizer   A Tensor of type float64.  
  fast   An optional bool. Defaults to True.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as matrix.
tf.raw_ops.BatchMatrixTriangularSolve  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BatchMatrixTriangularSolve  
tf.raw_ops.BatchMatrixTriangularSolve(
    matrix, rhs, lower=True, adjoint=False, name=None
)

 


 Args
  matrix   A Tensor. Must be one of the following types: float64, float32.  
  rhs   A Tensor. Must have the same type as matrix.  
  lower   An optional bool. Defaults to True.  
  adjoint   An optional bool. Defaults to False.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as matrix.
tf.raw_ops.BatchNormWithGlobalNormalization Batch normalization.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.BatchNormWithGlobalNormalization  
tf.raw_ops.BatchNormWithGlobalNormalization(
    t, m, v, beta, gamma, variance_epsilon, scale_after_normalization, name=None
)
 This op is deprecated. Prefer tf.nn.batch_normalization.
 


 Args
  t   A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, complex64, int64, qint8, quint8, qint32, bfloat16, uint16, complex128, half, uint32, uint64. A 4D input Tensor.  
  m   A Tensor. Must have the same type as t. A 1D mean Tensor with size matching the last dimension of t. This is the first output from tf.nn.moments, or a saved moving average thereof.  
  v   A Tensor. Must have the same type as t. A 1D variance Tensor with size matching the last dimension of t. This is the second output from tf.nn.moments, or a saved moving average thereof.  
  beta   A Tensor. Must have the same type as t. A 1D beta Tensor with size matching the last dimension of t. An offset to be added to the normalized tensor.  
  gamma   A Tensor. Must have the same type as t. A 1D gamma Tensor with size matching the last dimension of t. If "scale_after_normalization" is true, this tensor will be multiplied with the normalized tensor.  
  variance_epsilon   A float. A small float number to avoid dividing by 0.  
  scale_after_normalization   A bool. A bool indicating whether the resulted tensor needs to be multiplied with gamma.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as t.