tidying up tests

src/include/migraphx/op/multinomial.hpp

@@ -29,8 +29,8 @@
  *
  *          In the large number limit, the fractional counts approach the multinomial distribution.
  *
- *      Inputs:   args[0] - a vector of probabilities for each category.  Values are running totals
- as provided by op prefix_scan_sum.
+ *      Inputs:   args[0] - a vector of probabilities for each category.  Values are running 
+ *                          totals as provided by op prefix_scan_sum.
  *                          Values are log normalized (i.e. start with any set of numbers > 0, then
  *                          val[i] = log(val[i]) / sum (log(val[0]) + log(val[1])+ ...) )
  *                          This input has Rank 2.  Dimension 0 is batch #.  The size of dimension

src/onnx/parse_multinomial.cpp

@@ -80,7 +80,7 @@ struct parse_multinomial : op_parser<parse_multinomial>
         }
         instruction_ref randoms;
 
-        if(args.size() > 0)
+        if(not args.empty())
         {
             shape s0 = args[0]->get_shape();
 

test/onnx/onnx_test.cpp

@@ -4191,6 +4191,7 @@ TEST_CASE(multinomial_test)
 
 TEST_CASE(multinomial_dyn_test)
 {
+    // compile-time random seed
     migraphx::program p;
     auto* mm           = p.get_main_module();
     size_t sample_size = 13;
@@ -4206,7 +4207,6 @@ TEST_CASE(multinomial_dyn_test)
         migraphx::make_op("prefix_scan_sum", {{"axis", 1}, {"exclusive", false}}), cdf);
 
     migraphx::shape rs{migraphx::shape::float_type, {1, sample_size}};
-    std::vector<float> data(rs.elements(), 0.3f);
 
     migraphx::shape s{migraphx::shape::uint32_type, {1}};
     std::vector<float> seed_data = {seed};
@@ -4216,7 +4216,6 @@ TEST_CASE(multinomial_dyn_test)
     auto ret     = mm->add_instruction(migraphx::make_op("multinomial"), cdf, randoms);
     mm->add_return({ret});
 
-    // auto prog = optimize_onnx("multinomial_dyn_test.onnx");
     migraphx::onnx_options options;
     options.default_dyn_dim_value  = {1, 10};
     options.print_program_on_error = true;
@@ -4226,6 +4225,7 @@ TEST_CASE(multinomial_dyn_test)
 
 TEST_CASE(multinomial_autoseed_dyn_test)
 {
+    // runtime random seed
     migraphx::program p;
     auto* mm           = p.get_main_module();
     size_t sample_size = 13;
@@ -4247,7 +4247,6 @@ TEST_CASE(multinomial_autoseed_dyn_test)
     auto ret        = mm->add_instruction(migraphx::make_op("multinomial"), cdf, randoms);
     mm->add_return({ret});
 
-    // auto prog = optimize_onnx("multinomial_dyn_test.onnx");
     migraphx::onnx_options options;
     options.default_dyn_dim_value  = {1, 10};
     options.print_program_on_error = true;

test/ref_ops_test.cpp

@@ -5377,6 +5377,7 @@ TEST_CASE(multinomial_dyn_test)
     std::transform(res_dist.begin(), res_dist.end(), res_norm.begin(), [&](auto n) {
         return static_cast<double>(n) / res_dist_sum;
     });
+    // The given test tolerance is about 10x the typical error
     EXPECT(migraphx::verify::verify_range(norm, res_norm, 100000));
 }