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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def draw_hist(self, metric, title=""):
 """Draw a series of histograms of the selected keys over different training steps. """

        # TODO: assert isinstance(list(values.values())[0], np.ndarray)

        rows = 1
        cols = 1
        limit = 10  # max steps to show

        # We need a 3D projection Subplot, so ignore the one provided to
        # as an create a new one.
        ax = self.figure.add_subplot(self.gs, projection="3d")
        ax.view_init(30, -80)

        # Compute histograms
        verts = []
        area_colors = []
        edge_colors = []
        for i, s in enumerate(metric.steps[-limit:]):
            hist, edges = np.histogram(metric.data[-i-1:])
            # X is bin centers
            x = np.diff(edges)/2 + edges[:-1]
            # Y is hist values
            y = hist
            x = np.concatenate([x[0:1], x, x[-1:]])
            y = np.concatenate([[0], y, [0]])

            # Ranges
            if i == 0:
                x_min = x.min()
                x_max = x.max()
                y_min = y.min()
                y_max = y.max()
            x_min = np.minimum(x_min, x.min())
            x_max = np.maximum(x_max, x.max())
            y_min = np.minimum(y_min, y.min())
            y_max = np.maximum(y_max, y.max())

            alpha = 0.8 * (i+1) / min(limit, len(metric.steps))
            verts.append(list(zip(x, y)))
            area_colors.append(np.array(self.theme["hist_color"] + [alpha]))
            edge_colors.append(np.array(self.theme["hist_outline_color"] + [alpha]))

        poly = PolyCollection(verts, facecolors=area_colors, edgecolors=edge_colors)
        ax.add_collection3d(poly, zs=list(range(min(limit, len(metric.steps)))), zdir='y')

        ax.set_xlim(x_min, x_max)
        ax.set_ylim(0, limit)
        ax.set_yticklabels(metric.formatted_steps[-limit:])
        ax.set_zlim(y_min, y_max)
        ax.set_title(metric.name)