10000 Add profiling code · hzyjerry/robotics-toolbox-python@30f1368 · GitHub
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Add profiling code
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‎.gitignore

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*.sw*
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*.gif
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*.so
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data/
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*.mp4
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*.png
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.idea/*
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‎roboticstoolbox/examples/benchmark.sh

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# cd Projects/Motion/robotics-toolbox-python/
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# source activate pytorch3d
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# python roboticstoolbox/examples/chomp.py --pts 1 --vb --nq 10 > data/verbose_pts0001_nq10.txt
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# python roboticstoolbox/examples/chomp.py --pts 5 --vb --nq 10 > data/verbose_pts0005_nq10.txt
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# python roboticstoolbox/examples/chomp.py --pts 5 --vb --nq 10 > data/verbose_pts0005_nq10.txt
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# python roboticstoolbox/examples/chomp.py --pts 5 --vb --nq 10 > data/verbose_pts0005_nq10.txt
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# python roboticstoolbox/examples/chomp.py --pts 5 --vb --nq 10 > data/verbose_pts0005_nq10.txt
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# for i in 1 5 20 50 100 200 400 800 1600 3200 6400
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# do
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# a=`printf "%.4d" $i`
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# echo "data/verbose_pts${a}_nq10.txt"
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# python roboticstoolbox/examples/chomp.py --pts $i --vb --nq 10 > "data/verbose_pts${a}_nq10.txt"
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# done
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# for i in 1 5 20 50 100 200 400 800 1600 3200 6400
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for i in 6400
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do
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a=`printf "%.4d" $i`
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echo "data/noverb_pts${a}_nq10.txt"
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python roboticstoolbox/examples/chomp.py --pts $i --nq 10 > "data/noverb_pts${a}_nq10.txt"
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done

‎roboticstoolbox/examples/chomp.py

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@@ -14,11 +14,8 @@
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import math
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from numba import vectorize
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visualize = True
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verbose = False
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use_mesh = True
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MODES = {"PTS", "LINKS", "TS"}
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MODES = {"PTS", "LINKS", "TS", "NONE"}
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"""
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Speed:
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@@ -45,9 +42,10 @@
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fknm_ = None
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def chomp(mode, seed=0):
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def chomp(mode, seed=0, num_pts=1, nq=10):
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np.random.seed(seed)
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assert mode in MODES
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print(f"CHOMP Mode {mode}")
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robot = rtb.models.DH.Panda() # load Mesh version (for collisions)
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# robot = rtb.models.URDF.Panda() # load URDF version of the Panda (for visuals)
@@ -80,11 +78,9 @@ def chomp(mode, seed=0):
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# Hyperparameters
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dt = 1
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nq = 50
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lmbda = 1000
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eta = 1000
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iters = 4
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num_pts = 50
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# Make cost field, starting & end points
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cdim = len(qtraj.q[0])
@@ -112,7 +108,7 @@ def chomp(mode, seed=0):
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for t in range(iters):
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with Profiler(f"Iteration {mode}"):
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with Profiler(f"Mode {mode} iteration"):
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nabla_smooth = AA.dot(xi) + bb
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nabla_obs = np.zeros(xidim)
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xidd = AA.dot(xi)
@@ -295,7 +291,8 @@ def chomp(mode, seed=0):
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# dxi = Ainv.dot(lmbda * nabla_smooth)
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dxi = Ainv.dot(nabla_obs + lmbda * nabla_smooth)
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xi -= dxi / eta
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print(f"Iteration {t} total cost {total_cost}")
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if verbose:
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print(f"Iteration {t} total cost {total_cost}")
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if visualize:
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if __name__ == "__main__":
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chomp(mode="PTS")
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chomp(mode="LINKS")
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chomp(mode="TS")
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import argparse
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parser = argparse.ArgumentParser(description='Process some integers.')
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parser.add_argument('--pts', type=int, default=50)
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parser.add_argument('--nq', type=int, default=10)
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parser.add_argument('--vb', action="store_true", default=False)
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opt = parser.parse_args()
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visualize = True
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verbose = opt.vb
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num_pts = opt.pts
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nq = opt.nq
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use_mesh = True
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chomp(mode="NONE", num_pts=num_pts, nq=nq)
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chomp(mode="PTS", num_pts=num_pts, nq=nq)
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chomp(mode="LINKS", num_pts=num_pts, nq=nq)
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chomp(mode="TS", num_pts=num_pts, nq=nq)
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# test_parallel()

‎roboticstoolbox/tools/utils.py

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@@ -14,6 +14,7 @@
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from numba import vectorize
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fknm_ = None
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PATH = "/home/jerry/Projects/Motion/robotics-toolbox-python/roboticstoolbox/cuda/fknm"
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def vmatmul(mat1, mat2):
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# mat1: (N, a, b)
@@ -61,7 +62,7 @@ def jacob0_pts_vec(robot, end, pts, jacob_vec, qt=None, verbose=False):
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if qt is None:
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qt = robot.q
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if fknm_ is None:
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fknm_=np.ctypeslib.load_library('roboticstoolbox/cuda/fknm','.')
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fknm_=np.ctypeslib.load_library(PATH,'.')
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# Parallel, use cuda
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N = len(pts)
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pts_tool = vrepeat(np.eye(4), N)
@@ -137,7 +138,7 @@ def jacob0_vec(robot, nq, njoints, link_bases, pts, jacob_vec, qt=None, verbose=
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if qt is None:
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qt = np.tile(np.array(robot.q), nq)
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if fknm_ is None:
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fknm_=np.ctypeslib.load_library('roboticstoolbox/cuda/fknm','.')
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fknm_=np.ctypeslib.load_library(PATH,'.')
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# Parallel, use cuda
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N = len(pts)
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num_pts = int(N / len(link_bases))

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