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	1.6917 GHz
hz_advertised_raw	[2400000000, 0]
hz_actual_raw	[1691718000, 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, osxsave, pae, pat, pbe, pcid, pclmulqdq, pdcm, pdpe1gb, pebs, pge, pln, pni, popcnt, pqm, pse, pse36, pts, rdrand, rdrnd, 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, tscdeadline, vme, vmx, vnmi, vpid, x2apic, xsave, ...]
l3_cache_size	20480 KB
l2_cache_size	256 KB
l1_data_cache_size	32 KB
l1_instruction_cache_size	32 KB
l2_cache_line_size	6
l2_cache_associativity	0x100
extended_model	3
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	Cython 0.29.13
71	cycler 0.10.0
72	colorlog 4.0.2
73	cmd2 0.8.9
74	cloudpickle 1.2.2
75	cliff 2.16.0
76	Click 7.0
77	chardet 3.0.4
78	certifi 2019.9.11
79	bs4 0.0.1
80	beautifulsoup4 4.8.1
81	atari-py 0.2.6
82	astor 0.8.0
83	arrow 0.15.2
84	alembic 1.2.1
85	absl-py 0.8.1
86	experiment-impact-tracker 0.1.1
87	torchcule 0.1.0
88	apex 0.1

	0
Realtime Carbon Intensity Data Source	http://www.caiso.com/outlook/SP/History/<date>/co2.csv
Realtime Carbon Intensity Average During Exp	336.77
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	18.6023
2	gpu_hours	1.70642
3	estimated_carbon_impact_kg	0.365809
4	total_power	1.0864
5	kw_hr_gpu	0.461161
6	kw_hr_cpu	0.226436
7	exp_len_hours	11.774
8	average_realtime_carbon_intensity	336.77
9	AverageReturn	18.392
10	AsymptoticReturn	20.08
11	AverageReturnPerkWh	16.9293
12	AverageEpisodeLength	1726.13
13	AverageMaximumEpisodeLength	1781