The report_histogram function doesn't make any sense in clearml. The expected values are the heights of the bars. (it assumes that you've already calculated the histogram).

I think that they should rename it to "report_bar" or something like that, and "report_histogram" will calculate the histogram for you (same as matplotlib's plt.hist function. @<1574207105437536256:profile|HungryCat90>

anyway, for histogram I'm using lines plots instead, it is the only way you can compare later on with other runs.

Example:

def report_hist(title:str, series:str, data:Iterable[float], bins:int, range=(0,1)):

_x = np.array(data, dtype=float)

_x = _x[~np.isnan(_x)]

```
if len(_x) == 0:
return None
_hist, _bins = np.histogram(_x, bins=bins, range=range)
_bins_x = [(a+b)/2 for a,b in zip(_bins[:-1], _bins[1:])]
logger = clearml.Logger.current_logger()
logger.report_scatter2d(title, series, scatter=zip(_bins_x, _hist), mode="lines+markers")
```