Return histogram of values.

# Aliases:

• tf.compat.v1.histogram_fixed_width
• tf.compat.v2.histogram_fixed_width

 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] Tensor of same dtype as values. 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 Tensor holding 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]

with tf.compat.v1.get_default_session() as sess:
  hist = tf.histogram_fixed_width(new_values, value_range, nbins=5)
  variables.global_variables_initializer().run()
  sess.run(hist) => [2, 1, 1, 0, 2]