neulab/docprompting-conala huggingface dataset:
tf.raw_ops.StatefulStandardNormal Outputs random values from a normal distribution. This op is deprecated in favor of op 'StatefulStandardNormalV2'  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatefulStandardNormal  
tf.raw_ops.StatefulStandardNormal(
    resource, shape, dtype=tf.dtypes.float32, name=None
)
 The generated values will have mean 0 and standard deviation 1.
 


 Args
  resource   A Tensor of type resource. The handle of the resource variable that stores the state of the RNG.  
  shape   A Tensor. The shape of the output tensor.  
  dtype   An optional tf.DType. Defaults to tf.float32. The type of the output.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type dtype.
tf.raw_ops.StatefulStandardNormalV2 Outputs random values from a normal distribution.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatefulStandardNormalV2  
tf.raw_ops.StatefulStandardNormalV2(
    resource, algorithm, shape, dtype=tf.dtypes.float32, name=None
)
 The generated values will have mean 0 and standard deviation 1.
 


 Args
  resource   A Tensor of type resource. The handle of the resource variable that stores the state of the RNG.  
  algorithm   A Tensor of type int64. The RNG algorithm.  
  shape   A Tensor. The shape of the output tensor.  
  dtype   An optional tf.DType. Defaults to tf.float32. The type of the output.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type dtype.
tf.raw_ops.StatefulTruncatedNormal Outputs random values from a truncated normal distribution.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatefulTruncatedNormal  
tf.raw_ops.StatefulTruncatedNormal(
    resource, algorithm, shape, dtype=tf.dtypes.float32, name=None
)
 The generated values follow a normal distribution with mean 0 and standard deviation 1, except that values whose magnitude is more than 2 standard deviations from the mean are dropped and re-picked.
 


 Args
  resource   A Tensor of type resource. The handle of the resource variable that stores the state of the RNG.  
  algorithm   A Tensor of type int64. The RNG algorithm.  
  shape   A Tensor. The shape of the output tensor.  
  dtype   An optional tf.DType. Defaults to tf.float32. The type of the output.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type dtype.
tf.raw_ops.StatefulUniform Outputs random values from a uniform distribution.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatefulUniform  
tf.raw_ops.StatefulUniform(
    resource, algorithm, shape, dtype=tf.dtypes.float32, name=None
)
 The generated values follow a uniform distribution in the range [0, 1). The lower bound 0 is included in the range, while the upper bound 1 is excluded.
 


 Args
  resource   A Tensor of type resource. The handle of the resource variable that stores the state of the RNG.  
  algorithm   A Tensor of type int64. The RNG algorithm.  
  shape   A Tensor. The shape of the output tensor.  
  dtype   An optional tf.DType. Defaults to tf.float32. The type of the output.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type dtype.
tf.raw_ops.StatefulUniformFullInt Outputs random integers from a uniform distribution.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatefulUniformFullInt  
tf.raw_ops.StatefulUniformFullInt(
    resource, algorithm, shape, dtype=tf.dtypes.uint64, name=None
)
 The generated values are uniform integers covering the whole range of dtype.
 


 Args
  resource   A Tensor of type resource. The handle of the resource variable that stores the state of the RNG.  
  algorithm   A Tensor of type int64. The RNG algorithm.  
  shape   A Tensor. The shape of the output tensor.  
  dtype   An optional tf.DType. Defaults to tf.uint64. The type of the output.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type dtype.
tf.raw_ops.StatefulUniformInt Outputs random integers from a uniform distribution.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatefulUniformInt  
tf.raw_ops.StatefulUniformInt(
    resource, algorithm, shape, minval, maxval, name=None
)
 The generated values are uniform integers in the range [minval, maxval). The lower bound minval is included in the range, while the upper bound maxval is excluded. The random integers are slightly biased unless maxval - minval is an exact power of two. The bias is small for values of maxval - minval significantly smaller than the range of the output (either 2^32 or 2^64).
 


 Args
  resource   A Tensor of type resource. The handle of the resource variable that stores the state of the RNG.  
  algorithm   A Tensor of type int64. The RNG algorithm.  
  shape   A Tensor. The shape of the output tensor.  
  minval   A Tensor. Minimum value (inclusive, scalar).  
  maxval   A Tensor. Must have the same type as minval. Maximum value (exclusive, scalar).  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as minval.
tf.raw_ops.StatelessCase An n-way switch statement which calls a single branch function.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatelessCase  
tf.raw_ops.StatelessCase(
    branch_index, input, Tout, branches, output_shapes=[], name=None
)
 An n-way switch statement, implementing the following:

```
switch (branch_index) {
  case 0:
    output = branches[0](input);
    break;
  case 1:
    output = branches[1](input);
    break;
  ...
  case [[nbranches-1]]:
  default:
    output = branches[nbranches-1](input);
    break;
}
```

This should only be used when the none of branches has stateful ops.

 


 Args
  branch_index   A Tensor of type int32. The branch selector, an int32 Tensor.  
  input   A list of Tensor objects. A list of input tensors passed to the branch function.  
  Tout   A list of tf.DTypes. A list of output types.  
  branches   A list of functions decorated with @Defun that has length >= 1. A list of functions each of which takes 'inputs' and returns a list of tensors, whose types are the same as what every other branch returns.  
  output_shapes   An optional list of shapes (each a tf.TensorShape or list of ints). Defaults to [].  
  name   A name for the operation (optional).   
 


 Returns   A list of Tensor objects of type Tout.
tf.raw_ops.StatelessIf output = cond ? then_branch(input) : else_branch(input)  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatelessIf  
tf.raw_ops.StatelessIf(
    cond, input, Tout, then_branch, else_branch, output_shapes=[], name=None
)

 


 Args
  cond   A Tensor. A Tensor. If the tensor is a scalar of non-boolean type, the scalar is converted to a boolean according to the following rule: if the scalar is a numerical value, non-zero means True and zero means False; if the scalar is a string, non-empty means True and empty means False. If the tensor is not a scalar, being empty means False and being non-empty means True. This should only be used when the if then/else body functions do not have stateful ops. 
 
  input   A list of Tensor objects. A list of input tensors.  
  Tout   A list of tf.DTypes. A list of output types.  
  then_branch   A function decorated with @Defun. A function that takes 'inputs' and returns a list of tensors, whose types are the same as what else_branch returns.  
  else_branch   A function decorated with @Defun. A function that takes 'inputs' and returns a list of tensors, whose types are the same as what then_branch returns.  
  output_shapes   An optional list of shapes (each a tf.TensorShape or list of ints). Defaults to [].  
  name   A name for the operation (optional).   
 


 Returns   A list of Tensor objects of type Tout.
tf.raw_ops.StatelessMultinomial Draws samples from a multinomial distribution.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatelessMultinomial  
tf.raw_ops.StatelessMultinomial(
    logits, num_samples, seed, output_dtype=tf.dtypes.int64, name=None
)

 


 Args
  logits   A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, int64, bfloat16, uint16, half, uint32, uint64. 2-D Tensor with shape [batch_size, num_classes]. Each slice [i, :] represents the unnormalized log probabilities for all classes.  
  num_samples   A Tensor of type int32. 0-D. Number of independent samples to draw for each row slice.  
  seed   A Tensor. Must be one of the following types: int32, int64. 2 seeds (shape [2]).  
  output_dtype   An optional tf.DType from: tf.int32, tf.int64. Defaults to tf.int64.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type output_dtype.
tf.raw_ops.StatelessParameterizedTruncatedNormal  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatelessParameterizedTruncatedNormal  
tf.raw_ops.StatelessParameterizedTruncatedNormal(
    shape, seed, means, stddevs, minvals, maxvals, name=None
)

 


 Args
  shape   A Tensor. Must be one of the following types: int32, int64. The shape of the output tensor.  
  seed   A Tensor. Must be one of the following types: int32, int64. 2 seeds (shape [2]).  
  means   A Tensor. Must be one of the following types: half, float32, float64. The mean parameter of each batch.  
  stddevs   A Tensor. Must have the same type as means. The standard deviation parameter of each batch. Must be greater than 0.  
  minvals   A Tensor. Must have the same type as means. The minimum cutoff. May be -infinity.  
  maxvals   A Tensor. Must have the same type as means. The maximum cutoff. May be +infinity, and must be more than the minval for each batch.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as means.
tf.raw_ops.StatelessRandomBinomial Outputs deterministic pseudorandom random numbers from a binomial distribution.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatelessRandomBinomial  
tf.raw_ops.StatelessRandomBinomial(
    shape, seed, counts, probs, dtype=tf.dtypes.int64, name=None
)
 Outputs random values from a binomial distribution. The outputs are a deterministic function of shape, seed, counts, and probs.
 


 Args
  shape   A Tensor. Must be one of the following types: int32, int64. The shape of the output tensor.  
  seed   A Tensor. Must be one of the following types: int32, int64. 2 seeds (shape [2]).  
  counts   A Tensor. Must be one of the following types: half, float32, float64, int32, int64. The counts of the binomial distribution. Must be broadcastable with probs, and broadcastable with the rightmost dimensions of shape.  
  probs   A Tensor. Must have the same type as counts. The probability of success for the binomial distribution. Must be broadcastable with counts and broadcastable with the rightmost dimensions of shape.  
  dtype   An optional tf.DType from: tf.half, tf.float32, tf.float64, tf.int32, tf.int64. Defaults to tf.int64. The type of the output.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type dtype.
tf.raw_ops.StatelessRandomGammaV2 Outputs deterministic pseudorandom random numbers from a gamma distribution.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatelessRandomGammaV2  
tf.raw_ops.StatelessRandomGammaV2(
    shape, seed, alpha, name=None
)
 Outputs random values from a gamma distribution. The outputs are a deterministic function of shape, seed, and alpha.
 


 Args
  shape   A Tensor. Must be one of the following types: int32, int64. The shape of the output tensor.  
  seed   A Tensor. Must be one of the following types: int32, int64. 2 seeds (shape [2]).  
  alpha   A Tensor. Must be one of the following types: half, float32, float64. The concentration of the gamma distribution. Shape must match the rightmost dimensions of shape.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as alpha.
tf.raw_ops.StatelessRandomGetKeyCounterAlg Picks the best algorithm based on device, and scrambles seed into key and counter.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatelessRandomGetKeyCounterAlg  
tf.raw_ops.StatelessRandomGetKeyCounterAlg(
    seed, name=None
)
 This op picks the best counter-based RNG algorithm based on device, and scrambles a shape-[2] seed into a key and a counter, both needed by the counter-based algorithm. The scrambling is opaque but approximately satisfies the property that different seed results in different key/counter pair (which will in turn result in different random numbers).
 


 Args
  seed   A Tensor. Must be one of the following types: int32, int64. 2 seeds (shape [2]).  
  name   A name for the operation (optional).   
 


 Returns   A tuple of Tensor objects (key, counter, alg).     key   A Tensor of type uint64.  
  counter   A Tensor of type uint64.  
  alg   A Tensor of type int32.
tf.raw_ops.StatelessRandomNormal Outputs deterministic pseudorandom values from a normal distribution.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatelessRandomNormal  
tf.raw_ops.StatelessRandomNormal(
    shape, seed, dtype=tf.dtypes.float32, name=None
)
 The generated values will have mean 0 and standard deviation 1. The outputs are a deterministic function of shape and seed.
 


 Args
  shape   A Tensor. Must be one of the following types: int32, int64. The shape of the output tensor.  
  seed   A Tensor. Must be one of the following types: int32, int64. 2 seeds (shape [2]).  
  dtype   An optional tf.DType from: tf.half, tf.bfloat16, tf.float32, tf.float64. Defaults to tf.float32. The type of the output.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type dtype.
tf.raw_ops.StatelessRandomNormalV2 Outputs deterministic pseudorandom values from a normal distribution.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatelessRandomNormalV2  
tf.raw_ops.StatelessRandomNormalV2(
    shape, key, counter, alg, dtype=tf.dtypes.float32, name=None
)
 The generated values will have mean 0 and standard deviation 1. The outputs are a deterministic function of shape, key, counter and alg.
 


 Args
  shape   A Tensor. Must be one of the following types: int32, int64. The shape of the output tensor.  
  key   A Tensor of type uint64. Key for the counter-based RNG algorithm (shape uint64[1]).  
  counter   A Tensor of type uint64. Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used.  
  alg   A Tensor of type int32. The RNG algorithm (shape int32[]).  
  dtype   An optional tf.DType from: tf.half, tf.bfloat16, tf.float32, tf.float64. Defaults to tf.float32. The type of the output.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type dtype.
tf.raw_ops.StatelessRandomPoisson Outputs deterministic pseudorandom random numbers from a Poisson distribution.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatelessRandomPoisson  
tf.raw_ops.StatelessRandomPoisson(
    shape, seed, lam, dtype, name=None
)
 Outputs random values from a Poisson distribution. The outputs are a deterministic function of shape, seed, and lam.
 


 Args
  shape   A Tensor. Must be one of the following types: int32, int64. The shape of the output tensor.  
  seed   A Tensor. Must be one of the following types: int32, int64. 2 seeds (shape [2]).  
  lam   A Tensor. Must be one of the following types: half, float32, float64, int32, int64. The rate of the Poisson distribution. Shape must match the rightmost dimensions of shape.  
  dtype   A tf.DType from: tf.half, tf.float32, tf.float64, tf.int32, tf.int64. The type of the output.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type dtype.
tf.raw_ops.StatelessRandomUniform Outputs deterministic pseudorandom random values from a uniform distribution.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatelessRandomUniform  
tf.raw_ops.StatelessRandomUniform(
    shape, seed, dtype=tf.dtypes.float32, name=None
)
 The generated values follow a uniform distribution in the range [0, 1). The lower bound 0 is included in the range, while the upper bound 1 is excluded. The outputs are a deterministic function of shape and seed.
 


 Args
  shape   A Tensor. Must be one of the following types: int32, int64. The shape of the output tensor.  
  seed   A Tensor. Must be one of the following types: int32, int64. 2 seeds (shape [2]).  
  dtype   An optional tf.DType from: tf.half, tf.bfloat16, tf.float32, tf.float64. Defaults to tf.float32. The type of the output.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type dtype.
tf.raw_ops.StatelessRandomUniformFullInt Outputs deterministic pseudorandom random integers from a uniform distribution.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatelessRandomUniformFullInt  
tf.raw_ops.StatelessRandomUniformFullInt(
    shape, seed, dtype=tf.dtypes.uint64, name=None
)
 The generated values are uniform integers covering the whole range of dtype. The outputs are a deterministic function of shape and seed.
 


 Args
  shape   A Tensor. Must be one of the following types: int32, int64. The shape of the output tensor.  
  seed   A Tensor. Must be one of the following types: int32, int64, uint32, uint64. 2 seeds (shape [2]).  
  dtype   An optional tf.DType from: tf.int32, tf.int64, tf.uint32, tf.uint64. Defaults to tf.uint64. The type of the output.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type dtype.
tf.raw_ops.StatelessRandomUniformFullIntV2 Outputs deterministic pseudorandom random integers from a uniform distribution.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatelessRandomUniformFullIntV2  
tf.raw_ops.StatelessRandomUniformFullIntV2(
    shape, key, counter, alg, dtype=tf.dtypes.uint64, name=None
)
 The generated values are uniform integers covering the whole range of dtype. The outputs are a deterministic function of shape, key, counter and alg.
 


 Args
  shape   A Tensor. Must be one of the following types: int32, int64. The shape of the output tensor.  
  key   A Tensor of type uint64. Key for the counter-based RNG algorithm (shape uint64[1]).  
  counter   A Tensor of type uint64. Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used.  
  alg   A Tensor of type int32. The RNG algorithm (shape int32[]).  
  dtype   An optional tf.DType from: tf.int32, tf.int64, tf.uint32, tf.uint64. Defaults to tf.uint64. The type of the output.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type dtype.
tf.raw_ops.StatelessRandomUniformInt Outputs deterministic pseudorandom random integers from a uniform distribution.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatelessRandomUniformInt  
tf.raw_ops.StatelessRandomUniformInt(
    shape, seed, minval, maxval, name=None
)
 The generated values follow a uniform distribution in the range [minval, maxval). The outputs are a deterministic function of shape, seed, minval, and maxval.
 


 Args
  shape   A Tensor. Must be one of the following types: int32, int64. The shape of the output tensor.  
  seed   A Tensor. Must be one of the following types: int32, int64. 2 seeds (shape [2]).  
  minval   A Tensor. Must be one of the following types: int32, int64. Minimum value (inclusive, scalar).  
  maxval   A Tensor. Must have the same type as minval. Maximum value (exclusive, scalar).  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as minval.
tf.raw_ops.StatelessRandomUniformIntV2 Outputs deterministic pseudorandom random integers from a uniform distribution.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatelessRandomUniformIntV2  
tf.raw_ops.StatelessRandomUniformIntV2(
    shape, key, counter, alg, minval, maxval, name=None
)
 The generated values follow a uniform distribution in the range [minval, maxval). The outputs are a deterministic function of shape, key, counter, alg, minval and maxval.
 


 Args
  shape   A Tensor. Must be one of the following types: int32, int64. The shape of the output tensor.  
  key   A Tensor of type uint64. Key for the counter-based RNG algorithm (shape uint64[1]).  
  counter   A Tensor of type uint64. Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used.  
  alg   A Tensor of type int32. The RNG algorithm (shape int32[]).  
  minval   A Tensor. Must be one of the following types: int32, int64, uint32, uint64. Minimum value (inclusive, scalar).  
  maxval   A Tensor. Must have the same type as minval. Maximum value (exclusive, scalar).  
  name   A name for the operation (optional).   
 


 Returns   A Tensor. Has the same type as minval.
tf.raw_ops.StatelessRandomUniformV2 Outputs deterministic pseudorandom random values from a uniform distribution.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatelessRandomUniformV2  
tf.raw_ops.StatelessRandomUniformV2(
    shape, key, counter, alg, dtype=tf.dtypes.float32, name=None
)
 The generated values follow a uniform distribution in the range [0, 1). The lower bound 0 is included in the range, while the upper bound 1 is excluded. The outputs are a deterministic function of shape, key, counter and alg.
 


 Args
  shape   A Tensor. Must be one of the following types: int32, int64. The shape of the output tensor.  
  key   A Tensor of type uint64. Key for the counter-based RNG algorithm (shape uint64[1]).  
  counter   A Tensor of type uint64. Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used.  
  alg   A Tensor of type int32. The RNG algorithm (shape int32[]).  
  dtype   An optional tf.DType from: tf.half, tf.bfloat16, tf.float32, tf.float64. Defaults to tf.float32. The type of the output.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type dtype.
tf.raw_ops.StatelessTruncatedNormal Outputs deterministic pseudorandom values from a truncated normal distribution.  View aliases  Compat aliases for migration 
See Migration guide for more details. tf.compat.v1.raw_ops.StatelessTruncatedNormal  
tf.raw_ops.StatelessTruncatedNormal(
    shape, seed, dtype=tf.dtypes.float32, name=None
)
 The generated values follow a normal distribution with mean 0 and standard deviation 1, except that values whose magnitude is more than 2 standard deviations from the mean are dropped and re-picked. The outputs are a deterministic function of shape and seed.
 


 Args
  shape   A Tensor. Must be one of the following types: int32, int64. The shape of the output tensor.  
  seed   A Tensor. Must be one of the following types: int32, int64. 2 seeds (shape [2]).  
  dtype   An optional tf.DType from: tf.half, tf.bfloat16, tf.float32, tf.float64. Defaults to tf.float32. The type of the output.  
  name   A name for the operation (optional).   
 


 Returns   A Tensor of type dtype.