tf.histogram_fixed_width
        Return histogram of values.
  
tf.histogram_fixed_width(
    values,
    value_range,
    nbins=100,
    dtype=tf.dtypes.int32,
    name=None
)
  Given the tensor values, this operation returns a rank 1 histogram counting the number of entries in values that fell into every bin. The bins are equal width and determined by the arguments value_range and nbins.
  
 
 | Args | 
|---|
 
 | values | Numeric Tensor. | 
 | value_range | Shape [2] Tensorof samedtypeasvalues. values <= value_range[0] will be mapped to hist[0], values >= value_range[1] will be mapped to hist[-1]. | 
 | nbins | Scalar int32 Tensor. Number of histogram bins. | 
 | dtype | dtype for returned histogram. | 
 | name | A name for this operation (defaults to 'histogram_fixed_width'). | 
 
  
 
 | Returns | 
|---|
  | A 1-D Tensorholding histogram of values. | 
 
  
 
 | Raises | 
|---|
 
 | TypeError | If any unsupported dtype is provided. | 
 | tf.errors.InvalidArgumentError | If value_range does not satisfy value_range[0] < value_range[1]. | 
 
 Examples:
 
# Bins will be:  (-inf, 1), [1, 2), [2, 3), [3, 4), [4, inf)
nbins = 5
value_range = [0.0, 5.0]
new_values = [-1.0, 0.0, 1.5, 2.0, 5.0, 15]
hist = tf.histogram_fixed_width(new_values, value_range, nbins=5)
hist.numpy()
array([2, 1, 1, 0, 2], dtype=int32)