Bernoulli¶
Bernoulli - 22¶
Version¶
name: Bernoulli (GitHub)
domain:
mainsince_version:
22function:
Truesupport_level:
SupportType.COMMONshape inference:
True
This version of the operator has been available since version 22.
Summary¶
Draws binary random numbers (0 or 1) from a Bernoulli distribution. The input tensor should be a tensor containing probabilities p (a value in the range [0,1]) to be used for drawing the binary random number, where an output of 1 is produced with probability p and an output of 0 is produced with probability (1-p).
This operator is non-deterministic and may not produce the same values in different implementations (even if a seed is specified).
Attributes¶
dtype - INT :
The data type for the elements of the output tensor. if not specified, we will use the data type of the input tensor.
seed - FLOAT :
(Optional) Seed to the random generator, if not specified we will auto generate one.
Inputs¶
input (heterogeneous) - T1:
All values in input have to be in the range:[0, 1].
Outputs¶
output (heterogeneous) - T2:
The returned output tensor only has values 0 or 1, same shape as input tensor.
Type Constraints¶
T1 in (
tensor(bfloat16),tensor(double),tensor(float),tensor(float16)):Constrain input types to float tensors.
T2 in (
tensor(bfloat16),tensor(bool),tensor(double),tensor(float),tensor(float16),tensor(int16),tensor(int32),tensor(int64),tensor(int8),tensor(uint16),tensor(uint32),tensor(uint64),tensor(uint8)):Constrain output types to all numeric tensors and bool tensors.
Bernoulli - 15¶
Version¶
name: Bernoulli (GitHub)
domain:
mainsince_version:
15function:
Truesupport_level:
SupportType.COMMONshape inference:
True
This version of the operator has been available since version 15.
Summary¶
Draws binary random numbers (0 or 1) from a Bernoulli distribution. The input tensor should be a tensor containing probabilities p (a value in the range [0,1]) to be used for drawing the binary random number, where an output of 1 is produced with probability p and an output of 0 is produced with probability (1-p).
This operator is non-deterministic and may not produce the same values in different implementations (even if a seed is specified).
Attributes¶
dtype - INT :
The data type for the elements of the output tensor. if not specified, we will use the data type of the input tensor.
seed - FLOAT :
(Optional) Seed to the random generator, if not specified we will auto generate one.
Inputs¶
input (heterogeneous) - T1:
All values in input have to be in the range:[0, 1].
Outputs¶
output (heterogeneous) - T2:
The returned output tensor only has values 0 or 1, same shape as input tensor.
Type Constraints¶
T1 in (
tensor(double),tensor(float),tensor(float16)):Constrain input types to float tensors.
T2 in (
tensor(bfloat16),tensor(bool),tensor(double),tensor(float),tensor(float16),tensor(int16),tensor(int32),tensor(int64),tensor(int8),tensor(uint16),tensor(uint32),tensor(uint64),tensor(uint8)):Constrain output types to all numeric tensors and bool tensors.