Return histogram of values.
tf.raw_ops.HistogramFixedWidth( values, value_range, nbins, 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 fall into every bin. The bins are equal width and determined by the arguments value_range and nbins.
# 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.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] Args | |
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values | A Tensor. Must be one of the following types: int32, int64, float32, float64. Numeric Tensor. |
value_range | A Tensor. Must have the same type as values. 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 | A Tensor of type int32. Scalar int32 Tensor. Number of histogram bins. |
dtype | An optional tf.DType from: tf.int32, tf.int64. Defaults to tf.int32. |
name | A name for the operation (optional). |
Returns | |
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A Tensor of type dtype. |