0
python_version	3.7.5.final.0 (64 bit)
cpuinfo_version	[5, 0, 0]
arch	X86_64
bits	64
count	32
raw_arch_string	x86_64
vendor_id	GenuineIntel
brand	Intel(R) Xeon(R) CPU E5-2630 v3 @ 2.40GHz
hz_advertised	2.4000 GHz
hz_actual	1.2001 GHz
hz_advertised_raw	[2400000000, 0]
hz_actual_raw	[1200093000, 0]
stepping	2
model	63
family	6
flags	[abm, acpi, aes, aperfmperf, apic, arat, arch_perfmon, avx, avx2, bmi1, bmi2, bts, clflush, cmov, constant_tsc, cqm, cqm_llc, cqm_occup_llc, cx16, cx8, dca, de, ds_cpl, dtes64, dtherm, dts, eagerfpu, epb, ept, erms, est, f16c, flexpriority, fma, fpu, fsgsbase, fxsr, ht, ida, invpcid, invpcid_single, kaiser, lahf_lm, lm, mca, mce, mmx, monitor, movbe, msr, mtrr, nonstop_tsc, nopl, nx, pae, pat, pbe, pcid, pclmulqdq, pdcm, pdpe1gb, pebs, pge, pln, pni, popcnt, pse, pse36, pts, rdrand, rdtscp, rep_good, retpoline, sdbg, sep, smep, smx, ss, sse, sse2, sse4_1, sse4_2, ssse3, syscall, tm, tm2, tpr_shadow, tsc, tsc_adjust, tsc_deadline_timer, vme, vmx, vnmi, vpid, x2apic, xsave, xsaveopt, xtopology, xtpr]
l3_cache_size	20480 KB
l2_cache_size	256 KB
l1_data_cache_size	32 KB
l1_instruction_cache_size	32 KB
usable_cpus	16

	0
name	TITAN V
total_memory	12036 MiB
driver_version	410.78
cuda_version	10.0

	0
0	wrapt 1.11.2
1	wheel 0.33.6
2	Werkzeug 0.16.0
3	wcwidth 0.1.7
4	urllib3 1.25.6
5	ujson 1.35
6	typing 3.7.4.1
7	tqdm 4.36.1
8	torchvision 0.4.0+cu92
9	torch 1.2.0+cu92
10	thop 0.0.31.post1910280903
11	termcolor 1.1.0
12	tensorpack 0.9.8
13	tensorflow-gpu 1.14.0
14	tensorflow-estimator 1.14.0
15	tensorboard 1.14.0
16	tabulate 0.8.5
17	stevedore 1.31.0
18	stable-baselines 2.8.0
19	SQLAlchemy 1.3.10
20	soupsieve 1.9.4
21	six 1.12.0
22	Shapely 1.6.4.post2
23	setuptools 41.6.0.post20191030
24	scipy 1.3.1
25	requests 2.22.0
26	ratelim 0.1.6
27	pyzmq 18.1.0
28	PyYAML 5.1.2
29	pytz 2019.3
30	python-editor 1.0.4
31	python-dateutil 2.8.0
32	pyperclip 1.7.0
33	pyparsing 2.4.2
34	PyLaTeX 1.3.1
35	pyglet 1.3.2
36	py-cpuinfo 5.0.0
37	psutil 5.6.3
38	protobuf 3.10.0
39	prettytable 0.7.2
40	pip 19.3.1
41	Pillow 6.2.1
42	pbr 5.4.3
43	pandas 0.24.2
44	ordered-set 3.1.1
45	optuna 0.17.1
46	opencv-python 4.1.1.26
47	numpy 1.17.3
48	msgpack 0.6.2
49	msgpack-numpy 0.4.4.3
50	mpi4py 3.0.2
51	matplotlib 3.1.1
52	MarkupSafe 1.1.1
53	Markdown 3.1.1
54	Mako 1.1.0
55	kiwisolver 1.1.0
56	Keras-Preprocessing 1.1.0
57	Keras-Applications 1.0.8
58	jsonpickle 1.2
59	joblib 0.14.0
60	idna 2.8
61	h5py 2.10.0
62	gym 0.15.3
63	grpcio 1.24.3
64	google-pasta 0.1.7
65	geocoder 1.38.1
66	gast 0.3.2
67	future 0.18.1
68	deepdiff 4.0.8
69	decorator 4.4.1
70	cycler 0.10.0
71	colorlog 4.0.2
72	cmd2 0.8.9
73	cloudpickle 1.2.2
74	cliff 2.16.0
75	Click 7.0
76	chardet 3.0.4
77	certifi 2019.9.11
78	bs4 0.0.1
79	beautifulsoup4 4.8.1
80	atari-py 0.2.6
81	astor 0.8.0
82	arrow 0.15.2
83	alembic 1.2.1
84	absl-py 0.8.1
85	experiment-impact-tracker 0.1.1

	0
Realtime Carbon Intensity Data Source	http://www.caiso.com/outlook/SP/History/<date>/co2.csv
Realtime Carbon Intensity Average During Exp	352.996
Region Average Carbon Intensity	250.733
Region Average Carbon Intensity Source	https://github.com/tmrowco/electricitymap-contrib/blob/master/config/co2eq_parameters.json (ElectricityMap Average, 2019)
Assumed PUE	1.58
Compute Region	California, United States of America
Experiment Impact Tracker Version	0.1.1

	0	1
0	Key	Value
1	cpu_hours	6.56931
2	gpu_hours	0.221961
3	estimated_carbon_impact_kg	0.0845667
4	total_power	0.239635
5	kw_hr_gpu	0.07186
6	kw_hr_cpu	0.0798075
7	exp_len_hours	1.68344
8	average_realtime_carbon_intensity	352.996
9	AverageReturn	9.08632
10	AsymptoticReturn	19.04
11	AverageReturnPerkWh	37.9174
12	AverageEpisodeLength	2537.82
13	AverageMaximumEpisodeLength	2993.37