Addressed review comments

Author: antonwolfy

dpnp/dpnp_iface_histograms.py

@@ -114,7 +114,7 @@ def _get_outer_edges(a, range):
         first_edge, last_edge = a.min(), a.max()
         if not (dpnp.isfinite(first_edge) and dpnp.isfinite(last_edge)):
             raise ValueError(
-                "autodetected range of [{first_edge}, {last_edge}] "
+                f"autodetected range of [{first_edge}, {last_edge}] "
                 "is not finite"
             )
 
@@ -135,6 +135,7 @@ def _get_bin_edges(a, bins, range, usm_type):
     sycl_queue = a.sycl_queue
 
     if isinstance(bins, str):
+        # TODO: implement support of string bins
         raise NotImplementedError("only integer and array bins are implemented")
 
     if numpy.ndim(bins) == 0:
@@ -318,7 +319,7 @@ def histogram(a, bins=10, range=None, density=None, weights=None):
             cum_n = _search_sorted_inclusive(sa, bin_edges)
         else:
             zero = dpnp.zeros(
-                1, dtype=ntype, sycl_queue=a.sycl_queue, usm_type=a.usm_type
+                1, dtype=ntype, sycl_queue=a.sycl_queue, usm_type=usm_type
             )
             sorting_index = dpnp.argsort(a)
             sa = a[sorting_index]

tests/test_histogram.py

@@ -1,3 +1,4 @@
+import dpctl
 import numpy
 import pytest
 from numpy.testing import (
@@ -283,6 +284,18 @@ def test_invalid_range(self, xp):
         with assert_raises_regex(ValueError, "max must be larger than"):
             xp.histogram(vals, range=[0.1, 0.01])
 
+    @pytest.mark.parametrize("xp", [numpy, dpnp])
+    @pytest.mark.parametrize("inf_val", [-numpy.inf, numpy.inf])
+    def test_infinite_edge(self, xp, inf_val):
+        v = xp.array([0.5, 1.5, inf_val])
+        min, max = v.min(), v.max()
+
+        # both first and last ranges must be finite
+        with assert_raises_regex(
+            ValueError, f"autodetected range of \[{min}, {max}\] is not finite"
+        ):
+            xp.histogram(v)
+
     def test_bin_edge_cases(self):
         v = dpnp.array([337, 404, 739, 806, 1007, 1811, 2012])
 
@@ -322,7 +335,7 @@ def test_unsigned_monotonicity_check(self, xp):
         arr = xp.array([2])
         bins = xp.array([1, 3, 1], dtype="uint64")
         with assert_raises(ValueError):
-            _, _ = xp.histogram(arr, bins=bins)
+            xp.histogram(arr, bins=bins)
 
     def test_nan_values(self):
         one_nan = numpy.array([0, 1, numpy.nan])
@@ -356,3 +369,23 @@ def test_signed_overflow_bounds(self, dtype):
         result_hist, result_edges = dpnp.histogram(iv, bins=2)
         assert_array_equal(result_hist, expected_hist)
         assert_allclose(result_edges, expected_edges)
+
+    def test_string_bins_not_implemented(self):
+        v = dpnp.arange(5)
+
+        # numpy support string bins, but not dpnp
+        _, _ = numpy.histogram(v.asnumpy(), bins="auto")
+        with assert_raises(NotImplementedError):
+            dpnp.histogram(v, bins="auto")
+
+    def test_bins_another_sycl_queue(self):
+        v = dpnp.arange(7, 12, sycl_queue=dpctl.SyclQueue())
+        bins = dpnp.arange(4, sycl_queue=dpctl.SyclQueue())
+        with assert_raises(ValueError):
+            dpnp.histogram(v, bins=bins)
+
+    def test_weights_another_sycl_queue(self):
+        v = dpnp.arange(5, sycl_queue=dpctl.SyclQueue())
+        w = dpnp.arange(7, 12, sycl_queue=dpctl.SyclQueue())
+        with assert_raises(ValueError):
+            dpnp.histogram(v, weights=w)