rollout better benchmarking and use skip_checks with native threading

python/mujoco/rollout_benchmark.py

@@ -16,6 +16,7 @@
 
 import concurrent.futures
 import threading
+import time
 import timeit
 
 import mujoco
@@ -81,12 +82,33 @@ def benchmark_rollout(model_file='../../test/benchmark/testdata/humanoid200.xml'
 
     print('running benchmark')
     for nroll_i in nroll:
+        print('roll', nroll_i)
         for nstep_i in nstep:
-            nt_res = timeit.timeit(lambda: rollout.rollout(m_list[:nroll_i], d_list, initial_state[:nroll_i], nstep=nstep_i), number=10)
-            pt_res = timeit.timeit(lambda: pt.run(m_list[:nroll_i], initial_state[:nroll_i], nstep_i), number=10)
-            print('nroll: {:04d} nstep: {:04d} nt: {:0.3f} pt: {:0.3f} nt/pt: {:0.3f}'.format(nroll_i, nstep_i, nt_res, pt_res, nt_res / pt_res))
+            number = int((1*nroll[-1] * nstep[-1]) / nroll_i / nstep_i)
+            number = max(20, number)
 
-    # Generate plots
+            nt_res = timeit.timeit(lambda: rollout.rollout(m_list[:nroll_i], d_list, initial_state[:nroll_i], skip_checks=True, nstep=nstep_i), number=number)
+            pt_res = timeit.timeit(lambda: pt.run(m_list[:nroll_i], initial_state[:nroll_i], nstep_i), number=number)
+            nt_res /= number
+            pt_res /= number
+
+            # times = [time.time()]
+            # for i in range(number):
+            #   rollout.rollout(m_list[:nroll_i], d_list, initial_state[:nroll_i], skip_checks=True, nstep=nstep_i)
+            #   times.append(time.time())
+            # dt = np.diff(times)
+            # nt_res = np.mean(dt)
+
+            # times = [time.time()]
+            # for i in range(number):
+            #   pt.run(m_list[:nroll_i], initial_state[:nroll_i], nstep_i)
+            #   times.append(time.time())
+            # dt = np.diff(times)
+            # pt_res = np.mean(dt)
+
+            print('nroll: {:04d} nstep: {:04d} nt: {:0.3f} pt: {:0.3f} nt/pt: {:0.3f} {}'.format(nroll_i, nstep_i, nt_res, pt_res, nt_res / pt_res, number))
+
+    # TODO generate plots
 
 if __name__ == '__main__':
   benchmark_rollout()