Revision a894aee8aeb08fecaa9da5f8395f07dc554d29ed authored by Anton Kiselev on 21 October 2019, 13:00:20 UTC, committed by Jasper Schulz on 21 October 2019, 13:00:20 UTC
* Dockerfile for GPU container. Fix for installing GPU version of MXNet * Typo fix. Replacing requirement without regex.
1 parent f1f971b
data.py
# Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License").
# You may not use this file except in compliance with the License.
# A copy of the License is located at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# or in the "license" file accompanying this file. This file is distributed
# on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
# express or implied. See the License for the specific language governing
# permissions and limitations under the License.
# Third-party imports
from mxnet import nd
def load_gp_params():
return nd.array(
[
[412263.3050, 8.0703, 57.3620],
[387.5274, 5.0673, 4.2793],
[41625.4972, 6.7450, 9.5796],
[2639.2794, 3.6458, 5.1566],
[4423.1468, 6.0896, 5.1452],
[19065.0601, 4.2969, 13.6918],
[28449.8824, 4.7820, 10.6377],
[300837.0179, 6.8132, 41.2674],
[1374.7983, 4.3378, 4.0292],
[5304.0383, 6.1224, 1.1865],
]
).expand_dims(axis=2)
def load_exact_mean():
return nd.array(
[
[
329.91,
318.8,
326.58,
352.84,
395.77,
452.58,
519.87,
594.14,
672.03,
750.42,
826.4,
897.05,
959.22,
1009.3,
1043.4,
1057.1,
1046.3,
1007.4,
938.3,
838.59,
710.16,
557.29,
386.44,
370.18,
341.38,
330.33,
338.16,
364.32,
406.87,
462.85,
528.8,
601.17,
676.64,
752.21,
825.11,
892.63,
951.82,
999.28,
1031.1,
1043.2,
1031.2,
991.72,
922.39,
822.75,
694.55,
541.99,
371.45,
376.02,
347.33,
336.44,
344.41,
370.61,
412.98,
468.49,
533.61,
604.78,
678.67,
752.35,
823.15,
888.47,
945.49,
990.94,
1021.1,
1031.7,
1018.8,
978.69,
909.16,
809.66,
681.91,
529.99,
360.27,
377.02,
348.76,
338.32,
346.72,
373.3,
415.97,
471.67,
536.82,
607.84,
681.37,
754.49,
824.52,
888.89,
944.83,
989.13,
1018.1,
1027.7,
1013.8,
973.03,
903.11,
803.53,
676.04,
524.73,
355.89,
374.28,
346.91,
337.34,
346.63,
374.14,
417.81,
474.57,
540.85,
613.01,
687.65,
761.74,
832.55,
897.41,
953.51,
997.61,
1026,
1034.8,
1020.1,
978.36,
907.64,
807.53,
679.87,
528.79,
360.61,
368.96,
343.04,
334.91,
345.67,
374.79,
420.26,
479.07,
547.66,
622.33,
699.59,
776.26,
849.41,
916.22,
973.7,
1018.5,
1047.1,
1055.3,
1039.6,
996.64,
924.63,
823.41,
694.98,
543.61,
375.65,
362.13,
338.31,
332.23,
345.12,
376.54,
424.62,
486.44,
558.45,
636.92,
718.19,
798.86,
875.77,
945.81,
1005.8,
1052.2,
1081.3,
1089.2,
1072.4,
1027.9,
954.1,
851.17,
721.38,
569.17,
400.96,
358.65,
],
[
26.239,
26.612,
26.31,
25.441,
24.318,
23.394,
23.112,
23.72,
25.148,
27.001,
28.699,
29.716,
29.81,
29.155,
28.283,
27.875,
28.464,
30.184,
32.67,
35.15,
36.697,
36.53,
34.26,
26.079,
26.356,
26.123,
25.377,
24.269,
23.133,
22.412,
22.513,
23.625,
25.603,
27.972,
30.08,
31.355,
31.549,
30.869,
29.916,
29.444,
30.048,
31.882,
34.561,
37.256,
38.964,
38.84,
36.463,
27.34,
27.022,
26.272,
25.145,
23.828,
22.661,
22.071,
22.427,
23.876,
26.22,
28.935,
31.326,
32.793,
33.079,
32.405,
31.404,
30.873,
31.438,
33.276,
35.992,
38.735,
40.468,
40.314,
37.834,
28.936,
28.179,
27.044,
25.629,
24.14,
22.91,
22.342,
22.777,
24.33,
26.785,
29.604,
32.084,
33.617,
33.942,
33.274,
32.242,
31.649,
32.13,
33.871,
36.492,
39.148,
40.809,
40.599,
38.075,
30.565,
29.545,
28.174,
26.574,
24.953,
23.624,
22.961,
23.278,
24.681,
26.963,
29.608,
31.943,
33.377,
33.648,
32.951,
31.886,
31.224,
31.584,
33.16,
35.596,
38.088,
39.641,
39.41,
36.961,
31.817,
30.693,
29.225,
27.539,
25.826,
24.371,
23.51,
23.538,
24.562,
26.408,
28.617,
30.572,
31.727,
31.828,
31.044,
29.925,
29.185,
29.41,
30.789,
33.006,
35.314,
36.788,
36.628,
34.415,
32.283,
31.18,
29.725,
28.034,
26.271,
24.68,
23.561,
23.184,
23.667,
24.883,
26.449,
27.832,
28.549,
28.369,
27.435,
26.235,
25.413,
25.505,
26.693,
28.702,
30.862,
32.327,
32.358,
30.553,
25.266,
],
[
128.95,
122.39,
120.64,
123.55,
130.36,
139.91,
150.88,
162.03,
172.42,
181.48,
189.02,
195.16,
200.19,
204.44,
208.13,
211.28,
213.65,
214.75,
213.92,
210.41,
203.54,
192.86,
178.23,
163.31,
155.31,
151.08,
150.99,
154.77,
161.58,
170.28,
179.68,
188.74,
196.76,
203.4,
208.68,
212.85,
216.27,
219.23,
221.88,
224.12,
225.6,
225.74,
223.82,
219.07,
210.87,
198.8,
182.79,
174.14,
167.52,
164.42,
165.1,
169.16,
175.75,
183.73,
191.99,
199.65,
206.14,
211.3,
215.28,
218.42,
221.08,
223.54,
225.85,
227.84,
229.03,
228.78,
226.33,
220.92,
211.96,
199.07,
182.29,
173.98,
167.47,
164.48,
165.21,
169.22,
175.62,
183.29,
191.13,
198.31,
204.34,
209.12,
212.84,
215.87,
218.56,
221.15,
223.64,
225.77,
227.02,
226.7,
224.03,
218.3,
208.92,
195.62,
178.46,
166,
158.67,
155.08,
155.45,
159.35,
165.87,
173.86,
182.19,
189.98,
196.7,
202.2,
206.66,
210.38,
213.7,
216.82,
219.71,
222.07,
223.4,
223,
220.13,
214.1,
204.4,
190.8,
173.44,
154.11,
145.46,
140.96,
140.92,
144.95,
152.12,
161.23,
171.03,
180.51,
189,
196.23,
202.23,
207.24,
211.54,
215.29,
218.49,
220.88,
221.98,
221.18,
217.81,
211.23,
201.01,
186.99,
169.34,
142.18,
132.2,
126.9,
126.73,
131.35,
139.83,
150.86,
163.06,
175.18,
186.35,
196.06,
204.16,
210.78,
216.11,
220.35,
223.51,
225.44,
225.78,
224.02,
219.59,
211.98,
200.83,
186.04,
167.83,
139.73,
],
[
70.415,
63.185,
60.465,
60.591,
60.143,
57.038,
52.504,
50.145,
52.795,
59.874,
67.577,
71.705,
70.705,
66.507,
62.829,
62.672,
66.912,
74.551,
83.744,
92.514,
98.891,
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97.216,
79.011,
69.417,
63.16,
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63.012,
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53.838,
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68.47,
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67.279,
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80.395,
],
[
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41.081,
40.875,
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107.94,
108.05,
107.85,
107.62,
107.08,
105.35,
101.14,
93.104,
80.215,
62.151,
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[
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114.81,
110.94,
111.76,
120.81,
139.03,
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248.92,
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272.48,
280.25,
285.71,
281.08,
260.09,
222.65,
176.54,
134.76,
109.72,
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251.31,
279.83,
301.61,
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323.64,
328.59,
332.13,
334.02,
333.01,
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317.79,
316.49,
317.49,
315.17,
300.91,
266.66,
215.01,
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181.72,
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293.62,
306.99,
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327.86,
331.65,
332.18,
328.96,
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319.06,
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318.01,
314.99,
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266.31,
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220.29,
246.36,
269.94,
288.33,
301.58,
311.6,
320.31,
328.22,
334.09,
336.21,
334.05,
329.23,
324.7,
322.64,
322.07,
318.01,
302.85,
269.56,
210.47,
],
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379.51,
379.84,
395.91,
427.92,
473.69,
529.07,
588.7,
647.08,
699.6,
743.3,
777.29,
802.52,
821.09,
835.21,
846.12,
853.17,
853.52,
842.42,
814.09,
763.04,
685.5,
580.62,
451.07,
410.65,
399.71,
402.4,
421.14,
455.94,
504.31,
561.69,
622.3,
680.28,
730.75,
770.76,
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818.74,
830.83,
838.79,
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847.73,
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426.47,
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832.79,
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841.71,
843.6,
841.34,
830.09,
803.55,
755.43,
681.02,
578.58,
450.14,
410.03,
397.89,
399.64,
418.02,
453.23,
502.83,
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],
]
)
def load_exact_std():
return nd.array(
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)
def load_xfull():
return nd.array(
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[6.0, 21.0],
[6.0, 22.0],
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).expand_dims(axis=0)
def load_ytrain():
return nd.array(
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)
Computing file changes ...
