280 lines
95 KiB
Python
280 lines
95 KiB
Python
import gym
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import numpy as np
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import pybullet as p
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import pybulletgym.envs
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import time
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def relu(x):
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return np.maximum(x, 0)
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class SmallReactivePolicy:
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"Simple multi-layer perceptron policy, no internal state"
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def __init__(self, observation_space, action_space):
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assert weights_dense1_w.shape == (observation_space.shape[0], 128)
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assert weights_dense2_w.shape == (128, 64)
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assert weights_final_w.shape == (64, action_space.shape[0])
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def act(self, ob):
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x = ob
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x = relu(np.dot(x, weights_dense1_w) + weights_dense1_b)
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x = relu(np.dot(x, weights_dense2_w) + weights_dense2_b)
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x = np.dot(x, weights_final_w) + weights_final_b
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return x
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def demo_run():
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env = gym.make("PybulletHopper-v0")
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cid = p.connect(p.SHARED_MEMORY) # only show graphics if the browser is already running....
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if cid < 0:
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cid = p.connect(p.DIRECT)
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pi = SmallReactivePolicy(env.observation_space, env.action_space)
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while 1:
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frame = 0
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score = 0
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restart_delay = 0
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obs = env.reset()
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while 1:
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time.sleep(0.01)
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a = pi.act(obs)
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obs, r, done, _ = env.step(a)
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score += r
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frame += 1
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still_open = env.render("human")
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if still_open==False:
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return
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if not done: continue
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if restart_delay==0:
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print("score=%0.2f in %i frames" % (score, frame))
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restart_delay = 60*2 # 2 sec at 60 fps
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else:
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restart_delay -= 1
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if restart_delay==0: break
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weights_dense1_w = np.array([
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[ +0.6734, +1.1364, +0.6117, +0.5185, +0.5099, -0.2038, -0.0045, -0.1448, +0.5081, +1.1685, -0.7904, -0.4623, +0.0027, -0.0473, -0.1144, +0.5095, -0.1913, +0.2021, +0.3485, +0.1104, -0.4992, +0.5207, -0.1013, -0.6947, +0.1624, +0.3533, -0.2485, -0.0012, +0.1674, +0.1253, +1.5485, +0.3576, +0.8236, +0.7361, +0.6604, -0.0834, +0.1212, -0.8404, -0.8337, +0.3709, -0.4218, -0.1011, -1.1418, -0.0554, +0.6676, +0.4739, -0.2105, +0.3187, -0.4321, -0.7018, +0.1845, +0.2525, +0.0205, +0.9391, +0.6123, +0.6868, +0.5116, +0.3483, +0.1148, +0.6747, -0.1590, +0.1879, +0.4836, +0.1997, +0.5105, -0.2695, +0.0645, +0.5566, +0.0502, +0.2292, -0.4234, -0.3778, -0.7639, -0.6084, -0.0375, -0.4799, +0.6465, -0.4097, +0.1091, -0.0681, -0.1813, +0.3625, +0.6067, +0.1837, +0.1600, -0.1706, +0.0531, -0.3710, +0.1320, +0.5035, +0.1106, +0.9955, -0.2657, +0.6051, -0.2525, -0.9118, -0.6031, +0.2025, -0.2774, +0.3985, -0.0809, +0.3601, -0.0410, -0.5067, +0.4987, +0.4126, -0.1393, -0.6596, +0.8182, -0.2352, -0.9337, +0.1438, +0.3871, -0.1844, -0.4010, -0.3338, +0.1597, +0.2381, -0.4403, +0.5105, +1.0354, -0.1503, +0.2731, +0.6555, +0.2048, +0.4932, -0.0067, +0.0413],
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[ -0.0031, -0.2183, +0.2275, -0.4836, +0.1347, +0.3581, +0.0921, +0.1900, -0.1721, +0.0150, -0.2146, +0.5346, +0.2407, -0.0791, +0.5115, -0.0763, +0.2025, +0.2792, +0.4087, +0.2082, +0.0086, -0.2742, +0.3703, +0.4297, -0.3141, -0.3896, +0.4101, -0.3967, -0.2173, -0.0532, +0.2521, +0.3938, -0.3727, +0.6136, +0.0902, -0.4617, -0.3266, -0.2273, +0.0031, +0.4605, +0.1221, +0.3603, -0.1018, +0.1839, +0.3198, -0.1404, -0.1751, -0.1030, -0.5847, +0.2526, -0.1280, +0.1644, +0.2988, -0.1793, -0.2120, +0.3398, -0.4582, +0.0758, -0.2848, -0.1537, -0.2718, -0.2207, +0.0109, +0.1374, -0.0281, -0.0494, -0.0093, +0.0098, +0.2691, +0.1589, +0.2483, +0.1394, +0.2531, +0.3884, +0.0740, -0.4444, +0.1441, +0.0768, +0.2154, +0.4015, -0.2109, -0.0985, -0.1066, -0.0167, -0.0204, -0.2345, +0.3131, +0.1026, +0.1873, +0.2644, +0.2253, -0.0173, +0.1014, +0.0781, +0.0455, -0.0489, -0.3541, -0.1257, -0.1248, +0.4402, -0.0682, -0.3045, +0.1751, +0.0397, -0.3392, -0.2758, +0.1542, -0.0460, -0.0622, +0.2255, +0.2442, +0.2070, +0.3175, -0.0913, -0.2772, +0.7036, -0.0876, +0.0907, +0.3794, +0.4784, -0.5111, +0.0982, -0.0145, +0.0397, -0.3429, -0.2727, -0.1384, +0.0512],
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[ +0.2192, +0.0688, -0.1092, +0.1436, -0.2598, -0.0012, -0.2220, -0.2450, -0.0783, -0.0078, +0.3065, +0.1604, -0.0593, -0.0759, -0.4101, -0.1819, +0.4160, +0.0141, +0.0059, -0.2494, -0.0616, -0.3100, -0.3231, -0.3935, +0.1965, -0.0352, -0.0119, +0.3883, -0.5905, -0.0536, -0.0617, -0.2884, +0.1134, +0.1539, +0.2002, -0.3158, -0.5476, -0.4131, -0.1966, +0.1083, -0.3329, +0.1219, +0.2977, -0.7132, -0.1963, -0.2359, -0.4734, +0.0130, -0.1034, -0.1376, -0.1824, +0.1999, -0.3775, -0.0697, +0.1875, -0.0673, -0.0673, -0.0555, -0.3243, +0.2020, +0.1416, +0.1995, -0.1931, -0.6125, -0.3465, +0.0640, +0.3529, -0.4684, +0.2335, -0.0449, -0.1216, +0.1921, +0.0636, -0.0420, +0.1371, -0.1246, -0.2963, +0.0264, +0.3962, -0.3106, -0.2107, -0.2983, +0.0386, -0.0458, -0.3277, -0.1686, -0.3064, +0.2433, +0.3454, +0.0046, +0.0885, -0.2479, +0.2886, -0.0804, +0.0110, -0.1369, -0.1210, +0.1901, +0.0001, -0.1155, +0.2887, -0.0943, -0.1167, +0.1746, +0.0379, +0.0964, -0.2615, -0.0209, -0.0680, +0.0031, -0.0905, -0.0618, -0.5630, -0.0664, -0.1976, -0.2367, -0.2360, -0.2243, +0.2448, +0.2446, -0.0012, -0.6920, -0.0880, -0.4630, -0.5512, +0.0312, +0.1522, -0.1278],
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[ -0.2378, +0.2783, +0.0848, -0.3973, -0.5359, +0.2541, +0.1616, +0.1856, +0.6054, +0.0894, +0.2599, -0.0082, -0.5433, -0.3567, -0.1134, -0.2706, -0.9177, +0.1949, +0.4099, -0.3198, +0.3856, -0.0285, -0.0692, +0.0882, -0.1052, -0.0122, -0.0271, -0.4122, -0.0921, -0.2014, +0.0314, -0.0638, -0.0986, +0.1912, +0.6157, -0.0856, +0.0450, +0.3492, -0.0958, -0.1261, +0.1242, +0.0930, +0.1372, -0.1914, +0.4377, +0.0586, +0.2271, -0.1985, -0.1012, -0.2074, +0.2934, -0.2271, -0.4235, -0.0077, -0.2304, -1.1012, -0.1832, -0.1528, -0.4307, -0.4059, -0.4289, +0.1290, -0.1688, -0.0446, +0.2036, -0.5397, -0.3280, +0.3672, -0.3012, -0.1896, +0.0923, +0.1472, -0.0703, -0.0328, -0.1597, -0.3102, -0.4221, +0.3261, +0.4840, +0.0083, +0.2617, -0.2548, -0.5314, -0.4192, +0.6303, +0.2605, -0.6675, -0.0837, -0.8402, -0.4546, +0.2169, +0.0480, +0.2543, +0.0004, +0.2982, -0.2037, -0.4812, +0.0583, -0.8738, +0.0586, -0.3745, -0.5477, -0.2971, -0.1551, -0.4880, -0.1060, +0.2188, -0.4043, -0.0349, -0.1349, -0.4093, -0.4371, +0.3101, +0.5219, -0.0655, -0.2546, -0.6408, +0.2019, +0.1351, +0.0971, -0.4105, +0.1299, -0.6688, -0.0550, -0.2388, -0.4246, +0.1126, -0.5573],
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[ +0.3232, -0.0110, -0.0201, -0.2022, +0.1144, -0.2510, -0.3709, +0.4360, -0.4248, +0.1316, -0.5286, -0.0186, +0.2077, +0.2049, +0.2458, -0.3234, -0.0890, +0.2950, +0.0363, +0.0579, -0.0995, +0.1529, -0.0182, -0.2339, +0.0239, -0.3706, +0.2179, +0.1782, +0.1137, +0.3492, -0.1769, +0.1565, +0.2168, -0.0898, +0.4457, +0.4303, +0.3227, +0.1329, -0.0832, +0.0037, -0.1080, -0.1041, +0.0529, +0.2101, -0.1206, +0.1770, -0.1607, -0.2222, -0.3057, +0.0691, -0.1493, -0.1024, +0.1907, +0.0748, +0.3616, -0.5097, -0.4243, +0.1401, -0.4711, -0.4066, -0.4260, -0.3973, -0.3461, +0.2407, +0.1542, -0.3836, -0.2245, -0.0567, +0.3746, -0.3234, +0.4039, +0.0513, -0.1164, +0.3607, -0.1126, +0.0400, +0.2217, +0.1035, +0.0252, -0.1768, -0.4746, -0.3228, -0.3284, -0.0242, +0.0163, -0.2037, +0.0809, -0.0400, -0.0311, +0.3103, -0.1519, +0.0303, +0.3008, +0.1998, -0.1943, +0.2562, +0.5656, -0.0671, +0.3937, +0.4006, +0.3835, -0.0457, +0.5424, +0.2108, -0.0296, -0.1178, -0.0066, -0.5670, -0.1310, +0.2254, +0.0798, +0.0547, -0.0507, -0.2947, +0.0727, -0.4834, +0.0126, +0.2459, +0.2963, +0.2442, +0.1020, +0.0645, +0.6951, -0.4037, -0.1358, +0.4485, -0.1978, -0.0996],
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[ +0.3579, +0.4973, -0.5223, +0.4582, -0.3209, -0.1405, -0.3946, +0.4934, -0.2217, +0.4501, +0.2339, -0.5480, +0.0177, -0.7866, -0.0221, +0.0816, -0.6471, +0.2561, -0.0114, +0.7428, -0.0908, +0.1886, -0.0973, +0.3981, -0.2908, +0.3556, -1.2527, -0.7678, -0.1662, -0.0463, +0.8122, -0.7603, +0.8625, -0.3672, -0.0821, +0.4161, +0.6106, +0.3156, -0.3068, +0.9691, +0.4397, +0.2930, -0.3802, -0.0977, -0.2970, -0.5699, +0.3788, +1.1378, -0.6848, -1.0195, +0.2025, +1.3364, -0.0277, -0.2723, -0.5642, +0.3973, -0.1903, +0.6823, -0.2150, +0.6972, -0.0855, -0.1414, +0.7036, -1.0000, -0.1264, -0.1947, +0.9226, +0.1346, -0.4493, -0.3550, -1.0708, +0.2620, +0.0332, -0.3827, -1.0002, +0.9836, +0.2433, -1.1610, +0.3742, -0.0695, -0.5658, -0.2597, +0.3667, +1.2486, -0.5875, -0.1238, +0.9558, +0.6116, -0.4355, +0.3359, -1.2784, +0.1217, -0.0572, -0.4791, -0.5930, -1.4577, -0.6798, +0.6478, -0.4734, +1.3337, +0.0625, -0.1462, -0.4832, -0.2721, -0.3731, +1.0106, -0.5080, -0.7930, +0.3208, -0.5621, +0.3719, +0.0714, +0.1665, +0.0678, -0.0667, -0.0222, +0.3113, -0.8660, +0.9910, -0.3596, -0.9364, -0.2329, -0.0983, -0.0231, -0.9173, -0.4387, -0.1335, +0.0457],
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[ +0.3956, -0.3152, +0.2209, +0.5020, -0.1946, +0.1046, +0.2062, +0.3388, +0.0394, -0.3347, +0.0989, -0.3360, -0.5885, -0.2084, -0.0802, +0.1041, +0.4200, -0.5033, +0.2403, +0.3485, -0.1897, +0.1247, -0.3015, -0.5448, -0.2833, -0.2345, +0.3037, -0.0964, -0.0418, +0.4569, +0.5159, +0.1612, -0.1066, -0.1735, +0.1562, -0.1419, +0.0397, -0.5056, +0.5741, +0.1335, -0.5054, +0.2876, +0.2772, -0.4229, +0.3375, +0.1689, -0.0673, -0.1658, -0.0537, +0.0839, +0.0286, +0.2321, +0.0324, -0.3339, +0.3598, +0.2639, -0.1830, +0.0786, +0.0150, -0.5155, -0.2999, -0.3272, -0.1231, +0.0314, -0.2119, -0.2094, +0.1294, -0.1965, +0.0588, -0.6383, -0.0198, -0.1309, +0.5456, +0.1369, +0.5467, +0.1478, +0.0873, +0.0337, -0.1971, -0.4118, +0.2234, +0.3570, -0.0030, -0.4428, +0.2950, +0.0275, -0.0361, -0.2056, +0.1671, -0.5099, +0.1179, -0.0046, -0.3599, +0.2915, -0.1620, -0.4229, +0.0425, -0.2419, +0.5708, +0.2975, +0.2598, -0.5877, -0.2703, -0.1468, -0.5714, +0.1464, -0.3119, -0.0598, +0.4885, -0.0556, -0.2712, +0.1269, -0.3214, -0.2681, -0.1313, -0.0982, -0.1379, -0.0300, -0.1540, -0.3185, -0.0519, -0.2397, -0.0479, -0.2774, +0.3924, -0.2064, -0.1053, +0.4871],
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[ -0.1492, +0.3323, -0.4775, -0.5605, -0.8677, +0.7841, +0.7171, +0.8697, +0.2130, +0.4039, +0.9357, -0.8427, +0.0227, +0.2223, -0.4140, -0.7540, -0.2611, +0.5574, +0.2121, -0.3201, +0.0518, +0.3469, +0.3044, +0.6718, +0.4063, +0.9037, +0.2910, -0.5208, +0.2262, +0.5543, -0.1615, -0.2219, -0.7828, +0.0647, +0.2140, +0.9491, +0.0749, +0.2561, +0.2599, -0.2359, +0.4074, -0.2257, +0.0635, +0.1117, +0.5031, -0.2702, -0.0526, +0.1067, -0.1765, +0.0509, +0.2734, -0.2659, -1.0558, -0.3635, +0.4609, +0.0294, -0.6205, +1.3626, -0.1060, +0.2375, -0.4266, +0.6304, -0.9487, -0.2076, +0.3588, -0.2924, +0.2451, +0.5756, -0.1227, +0.1409, -0.2573, +0.8268, -0.3649, +0.7991, -0.2339, -0.2500, -0.2263, +0.0482, +0.9563, -0.2986, +0.5015, +0.2141, -0.3226, +0.3428, +1.1022, +0.3828, -0.1544, +0.4925, -0.0866, +0.2472, -0.0740, -0.0906, +0.6950, +0.4435, -0.2513, +0.0544, +0.1793, +0.9038, +0.3841, -0.3180, -0.2950, +0.0953, +0.4973, -0.3028, -0.0141, +0.0051, +0.9349, +0.0603, -0.1071, +0.2711, +0.0975, +0.6570, +0.1094, +0.1404, +0.9337, -0.2258, -0.5518, +0.0847, +0.8611, +0.0640, -0.3152, +0.3464, -0.2628, +0.2387, -0.1313, -0.3580, +1.7605, -0.7844],
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[ -0.1598, -0.0421, -0.4126, -0.4364, -0.2147, +0.4256, -0.0339, -0.3245, -0.4184, +0.0827, -0.5233, -0.3281, -0.3892, -0.5833, -0.0462, -0.5472, +0.0374, +0.0243, -0.3826, -0.1234, -0.6757, -0.2869, -0.2674, +0.0504, +0.2552, +0.0059, -0.0716, -0.0678, -0.2011, +0.1214, -0.0007, +0.2210, -0.3461, +0.0562, -0.5642, +0.1014, -0.5826, -0.1434, -0.1884, -0.4357, -0.0456, -0.1590, -0.3123, -0.1467, -0.2865, +0.2239, -0.1522, -0.4315, -0.0772, +0.2507, -0.6389, -0.3853, -0.1505, +0.5287, +0.1969, +0.3432, +0.1255, +0.3163, -0.3674, +0.3488, +0.0463, +0.2907, -0.2616, -0.1169, -0.0705, +0.3281, +0.0255, +0.2221, -0.0777, -0.3293, -0.3078, -0.6078, -0.1859, -0.2359, -0.1811, -0.3349, -0.1777, -0.0656, -0.6531, -0.3420, -0.3709, -0.1240, -0.2513, +0.1877, +0.0152, +0.0720, +0.1846, -0.1148, -0.1539, +0.0653, +0.0752, -0.7600, -0.0605, +0.0614, -0.5569, -0.2471, -0.0556, -0.6890, -0.2103, -0.2875, -0.2620, +0.0966, -0.4809, +0.2514, +0.0813, -0.4869, -0.1030, -0.3295, -0.0645, -0.3906, -0.0294, +0.0987, -0.0403, -0.8376, -0.4490, -0.1942, -0.0488, -0.6031, -0.2849, -0.3964, +0.3836, -0.2380, -0.0565, -0.0857, +0.3379, -0.1756, +0.1558, -0.0667],
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])
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weights_dense1_b = np.array([ +0.0032, +0.0591, +0.1871, -0.0873, +0.0194, -0.1684, -0.0091, +0.0135, -0.0694, -0.3312, +0.0673, -0.1489, +0.1365, +0.0575, -0.1155, -0.0904, -0.1321, +0.0492, -0.2257, -0.2418, -0.0204, -0.1910, -0.0512, -0.0482, -0.2969, -0.3574, -0.1852, -0.1644, -0.2957, -0.1906, -0.0170, -0.0760, +0.0006, -0.1286, -0.0746, +0.0039, -0.1005, -0.0535, +0.0375, -0.2162, -0.1251, -0.0368, +0.0101, -0.3220, -0.1152, -0.3656, -0.2491, +0.0638, -0.0312, +0.0054, -0.2318, -0.2900, -0.1189, -0.0725, +0.0490, -0.0679, +0.0117, +0.0926, -0.0824, +0.0479, +0.0756, -0.0462, +0.1529, +0.0081, -0.0984, -0.1227, -0.0247, -0.1277, -0.0633, -0.1953, +0.1023, +0.1582, -0.0400, -0.1115, -0.1625, -0.2216, -0.0195, -0.0650, +0.0701, -0.1573, -0.1187, -0.0801, -0.1424, +0.1873, -0.2309, -0.1815, -0.0408, -0.1173, +0.0185, -0.1408, -0.0938, -0.2810, +0.2447, -0.4046, -0.1790, -0.0165, +0.1334, +0.0500, +0.0283, -0.0321, -0.2388, -0.0726, -0.3444, -0.3250, -0.1338, -0.0579, -0.1647, -0.0691, -0.0835, +0.0734, +0.1667, -0.1478, -0.2212, -0.0899, -0.0050, -0.2379, +0.0709, +0.0464, +0.1569, -0.2669, -0.2181, -0.4331, +0.0534, -0.0648, -0.1026, -0.1509, -0.2278, -0.0437])
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weights_dense2_w = np.array([
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[ -0.5329, -0.7876, -0.4974, +0.3381, +0.3092, +0.0208, -0.2402, -0.3306, -0.7425, +0.1489, +0.0271, -0.1945, +0.0315, +0.1836, +0.2294, -0.6615, -0.1362, +0.2090, -0.5984, -0.0163, +0.0886, +0.0679, +0.3041, -0.0070, -0.0550, +0.3623, -0.0483, -0.2679, +0.2927, +0.2728, +0.2955, -0.0641, +0.2888, +0.0278, +0.1980, +0.0714, +0.1605, +0.1879, +0.0666, -0.0505, +0.3625, +0.3155, -0.1965, -0.0301, +0.1697, -0.0102, -0.4709, -0.4190, +0.0265, -1.0402, -0.0718, +0.3172, -0.1062, -0.2538, -0.4556, -0.2825, -0.0534, -0.1540, +0.0872, +0.1585, -0.4927, -0.0311, +0.2163, -0.8230],
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[ -0.0620, -0.4689, -0.0407, -1.5569, -0.1551, -0.2028, -0.3836, -0.0306, -0.0718, -0.9097, -0.1025, +0.1040, +0.1657, +0.1093, -0.2807, +0.3353, -0.6893, +0.6661, +0.1312, -0.8763, -1.5289, -1.4383, +0.1129, +0.2337, -0.0876, -0.8757, +0.0550, -0.3456, +0.1468, -0.6056, -0.8811, -0.3539, +0.6850, +0.1739, +0.0344, -0.0354, -0.2883, -0.1680, -0.3950, -0.7221, -1.8289, -0.2404, -0.2498, +0.1401, +0.3679, -0.1029, -0.2085, -0.9932, -0.1101, -0.4335, -0.1423, -0.3566, -0.4630, +0.1845, +0.3527, -0.4799, -1.7876, +0.3755, +0.2791, +0.1744, -0.3218, -0.4807, -0.2936, +0.2639],
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[ -0.1966, +0.5649, -0.2069, +0.3588, -0.8745, +0.8721, +0.0814, +0.1852, +0.1873, -0.0432, -0.7933, -0.2585, -0.1218, -0.4980, +0.3300, +0.3064, -1.0648, -0.6760, +0.0998, +0.6166, -0.2364, +0.0741, -1.5132, -1.1618, -0.0384, +0.1799, -0.5393, +0.2645, -0.2358, +0.0418, +0.3921, -0.8185, +0.5272, +0.4155, -0.2473, +0.0026, -0.4362, -0.1113, -0.1036, -1.0282, -0.2206, +0.5201, -0.1124, +0.3642, +0.0213, +0.1247, +0.0868, +0.3541, -0.0376, -0.0735, +0.4899, -0.5098, -0.7578, -0.3030, +0.2886, -0.7427, -0.4035, +0.0161, -0.4715, +0.0235, +0.5217, -0.2785, +0.0707, -0.2289],
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[ +0.0721, +0.2423, +0.2696, -0.8249, -0.0644, -0.3427, -0.2876, -0.2066, +0.2195, +0.1008, +0.1247, +0.2757, -0.1372, -0.0132, +0.1199, -0.1206, +0.1263, +0.0607, -0.1235, -0.3237, +0.5096, -0.0538, +0.4292, -0.2570, -0.2744, -0.1671, +0.0643, +0.2648, -0.1993, +0.0420, +0.1681, +0.3126, -0.3654, -0.2719, +0.3103, +0.2754, +0.0040, -0.4387, -0.0634, +0.2868, +0.0613, -0.1423, +0.0911, -0.6027, -0.2560, -0.0131, -0.5504, -0.6812, +0.0176, +0.1782, -0.0082, -0.2754, +0.1471, +0.2872, -0.5940, +0.1319, +0.0220, +0.3727, +0.2380, +0.0558, +0.1206, +0.2882, +0.0155, +0.2597],
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|
|
[ +0.0894, +0.2394, +0.4565, +0.5095, -0.9334, -1.2892, -0.8885, +0.0167, +1.0713, -0.3041, -0.7280, +0.2223, -0.5221, -0.0032, -0.0743, +0.1534, +0.5751, -0.1298, -0.1282, -0.4674, +0.5752, +0.2239, +0.4114, +0.3252, -0.1642, +0.2532, +0.3494, -0.8035, -0.2348, +0.3177, -0.5218, +0.0481, -0.3052, -0.9177, +0.1627, +0.6603, -0.7468, +0.0274, +0.0626, +0.0355, -0.2757, +0.2697, +0.4732, -0.2061, -0.0190, +0.5470, -0.5898, -0.8168, -0.0884, -0.4522, -0.1064, -0.8207, +0.2726, +0.1109, -0.2514, +0.1580, +0.6825, +0.7124, +0.8108, +0.2258, -0.1274, +0.2130, -0.3830, -0.9575],
|
|
[ +0.0671, +0.2013, -0.4460, -1.0518, -0.0167, +0.1024, +0.0547, +0.3296, +0.0516, +0.0503, +0.1956, -0.0536, +0.0108, -0.2160, +0.1852, -0.0177, -0.4770, -0.2327, -0.2887, +0.2862, -0.0357, +0.0026, -0.6428, -0.5677, -0.0354, -0.0304, -0.1272, +0.1630, -0.1319, -0.1122, +0.3381, +0.0000, -1.0265, +0.1319, -0.2374, -0.1598, -0.0059, +0.1722, +0.2300, +0.1748, -0.0167, -0.0891, +0.0350, -0.4563, -0.5325, +0.0078, -0.2475, +0.1184, +0.0133, +0.2512, +0.3639, -1.5981, -0.5117, -0.2703, +0.0222, -0.5620, -0.1466, -0.1626, -0.3288, -0.0070, +0.0508, -0.3687, -0.4245, -0.2751]
|
|
])
|
|
|
|
weights_dense2_b = np.array([ +0.0266, +0.3395, +0.0968, +0.0097, +0.0443, -0.1722, -0.2537, +0.1501, +0.0233, -0.0174, +0.1783, -0.0513, -0.1531, -0.2145, +0.0299, -0.1589, +0.1143, +0.1132, -0.2700, -0.0481, +0.2876, +0.1824, +0.2418, +0.1009, -0.1451, +0.1637, +0.1703, +0.0336, -0.1405, -0.0162, -0.1158, +0.1691, -0.0223, -0.1828, +0.2352, +0.0209, -0.1362, -0.2636, +0.1271, -0.0936, -0.1436, +0.0606, +0.1311, -0.0989, -0.2877, +0.2593, +0.0781, -0.1118, -0.1264, +0.2478, +0.2398, -0.1515, +0.0959, -0.0821, -0.1740, +0.1116, -0.0682, +0.1743, +0.1746, -0.1950, -0.0951, +0.2190, -0.0294, +0.1950])
|
|
|
|
weights_final_w = np.array([
|
|
[ -0.6826, +0.0812, +0.5225],
|
|
[ -0.2533, +0.7043, +0.6677],
|
|
[ +0.0684, +0.6807, +0.4726],
|
|
[ +0.4605, +0.3736, -0.3187],
|
|
[ +0.4913, +0.0049, +0.4186],
|
|
[ +0.3066, +0.3756, -0.3588],
|
|
[ -0.3078, +0.3643, -0.0335],
|
|
[ -0.5433, +0.5926, -0.1254],
|
|
[ -0.2532, +0.7950, -0.1380],
|
|
[ -0.6121, -0.3012, +0.0149],
|
|
[ +0.3181, +0.0973, +0.1705],
|
|
[ +0.2236, -0.1020, +0.3147],
|
|
[ -0.0038, -0.3193, +0.1068],
|
|
[ +0.3799, -0.0215, -0.0715],
|
|
[ +0.3440, -0.2333, -0.1001],
|
|
[ +0.1852, +0.7445, +0.4295],
|
|
[ +0.4888, -0.0469, -0.1287],
|
|
[ +0.0297, -0.3913, -0.5198],
|
|
[ -0.0092, -0.1013, +0.2193],
|
|
[ +0.2590, +0.0846, +0.0886],
|
|
[ +0.0744, +0.4771, -0.3553],
|
|
[ +0.2019, +0.1670, -0.1630],
|
|
[ -0.4549, -0.6127, +0.5951],
|
|
[ -0.2582, -0.6401, -0.6541],
|
|
[ +0.0248, +0.0646, +0.1598],
|
|
[ +0.2109, -0.0794, -0.2444],
|
|
[ +0.2435, -0.4159, -0.2927],
|
|
[ -0.0713, +0.2441, -0.4683],
|
|
[ -0.0737, +0.2075, +0.4609],
|
|
[ +0.3240, -0.4084, -0.4554],
|
|
[ +0.3463, +0.4490, -0.2689],
|
|
[ +0.5252, -0.3714, +0.2808],
|
|
[ +0.5561, +0.1137, -0.0258],
|
|
[ +0.6168, +0.0587, -0.1059],
|
|
[ -0.0737, -0.6782, -0.4729],
|
|
[ -0.6030, -0.2577, +0.4194],
|
|
[ +0.4061, -0.1966, +0.2603],
|
|
[ -0.1265, +0.3940, +0.0447],
|
|
[ +0.2460, +0.3328, +0.1654],
|
|
[ -0.1878, +0.6672, +0.0333],
|
|
[ +0.5618, -0.1013, -0.2911],
|
|
[ +0.8250, -0.0788, -0.3731],
|
|
[ +0.2661, -0.2775, +0.2854],
|
|
[ -0.1036, +0.2179, -0.6408],
|
|
[ -0.5371, -0.7837, +0.1141],
|
|
[ +0.4754, -0.0923, +0.1714],
|
|
[ +0.0448, +0.4901, -0.1578],
|
|
[ +0.8797, +0.3316, +0.4349],
|
|
[ +0.1514, -0.4129, -0.3333],
|
|
[ +0.2847, +0.2285, +0.1408],
|
|
[ +0.0045, +0.3333, +0.0694],
|
|
[ +0.1553, -0.5147, +0.0549],
|
|
[ -1.0765, -0.5130, +0.1472],
|
|
[ +0.0808, -0.2612, +0.2591],
|
|
[ +0.5104, +0.3062, +0.3979],
|
|
[ -0.0758, -0.4512, -0.4422],
|
|
[ +0.3236, +0.4479, -0.1759],
|
|
[ +0.2181, -0.0028, +0.5615],
|
|
[ -0.0254, -0.1924, +0.4608],
|
|
[ -0.1566, +0.5634, -0.2498],
|
|
[ -0.0042, +0.5403, +0.0272],
|
|
[ +0.1206, +0.3941, -1.1469],
|
|
[ +0.7642, -1.0114, +0.4905],
|
|
[ +0.5071, +0.2270, +0.0046]
|
|
])
|
|
|
|
weights_final_b = np.array([ +0.4868, -0.0987, -0.0946])
|
|
|
|
if __name__=="__main__":
|
|
demo_run()
|