tf.compat.v1.random_poisson
    
    
      
    
    
      
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Draws shape samples from each of the given Poisson distribution(s).
tf.compat.v1.random_poisson(
    lam,
    shape,
    dtype=tf.dtypes.float32,
    seed=None,
    name=None
)
lam is the rate parameter describing the distribution(s).
Example:
samples = tf.random.poisson([0.5, 1.5], [10])
# samples has shape [10, 2], where each slice [:, 0] and [:, 1] represents
# the samples drawn from each distribution
samples = tf.random.poisson([12.2, 3.3], [7, 5])
# samples has shape [7, 5, 2], where each slice [:, :, 0] and [:, :, 1]
# represents the 7x5 samples drawn from each of the two distributions
| Args | 
|---|
| lam | A Tensor or Python value or N-D array of type dtype.lamprovides the rate parameter(s) describing the poisson
distribution(s) to sample. | 
| shape | A 1-D integer Tensor or Python array. The shape of the output samples
to be drawn per "rate"-parameterized distribution. | 
| dtype | The type of the output: float16,float32,float64,int32orint64. | 
| seed | A Python integer. Used to create a random seed for the distributions.
See tf.random.set_seedfor behavior. | 
| name | Optional name for the operation. | 
| Returns | 
|---|
| samples | a Tensorof shapetf.concat([shape, tf.shape(lam)], axis=0)with values of typedtype. | 
  
  
 
  
    
    
      
    
    
  
       
    
    
  
  
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  Last updated 2023-10-06 UTC.
  
  
  
    
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