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annotate utils/seriestables/series.py @ 218:4c137f16b013

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Modifications pour stocker des timestamps/cpuclock avec chaque rangée créée, selon suggestion de Yoshua ce matin
author fsavard
date Wed, 10 Mar 2010 20:13:45 -0500
parents a96fa4de06d2
children e172ef73cdc5
rev   line source
208
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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1 from tables import *
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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2 import numpy
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3 import time
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acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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4
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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5 '''
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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6 The way these "IsDescription constructor" work is simple: write the
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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7 code as if it were in a file, then exec()ute it, leaving us with
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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8 a local-scoped LocalDescription which may be used to call createTable.
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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9
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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10 It's a small hack, but it's necessary as the names of the columns
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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11 are retrieved based on the variable name, which we can't programmatically set
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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12 otherwise.
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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13 '''
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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14
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15 def _get_description_timestamp_cpuclock_columns(store_timestamp, store_cpuclock, pos=0):
4c137f16b013 Modifications pour stocker des timestamps/cpuclock avec chaque rangée créée, selon suggestion de Yoshua ce matin
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16 toexec = ""
4c137f16b013 Modifications pour stocker des timestamps/cpuclock avec chaque rangée créée, selon suggestion de Yoshua ce matin
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17
4c137f16b013 Modifications pour stocker des timestamps/cpuclock avec chaque rangée créée, selon suggestion de Yoshua ce matin
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18 if store_timestamp:
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19 toexec += "\ttimestamp = Time32Col(pos="+str(pos)+")\n"
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20 pos += 1
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21
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22 if store_cpuclock:
4c137f16b013 Modifications pour stocker des timestamps/cpuclock avec chaque rangée créée, selon suggestion de Yoshua ce matin
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23 toexec += "\tcpuclock = Float64Col(pos="+str(pos)+")\n"
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24 pos += 1
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25
4c137f16b013 Modifications pour stocker des timestamps/cpuclock avec chaque rangée créée, selon suggestion de Yoshua ce matin
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26 return toexec, pos
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27
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28 def _get_description_n_ints(int_names, int_width=64, pos=0):
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dc0d77c8a878 Commented table_series code, changed ParamsStatisticsArray to take shared params instead, create DummySeries to use when we don't want to save a named series
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29 """
dc0d77c8a878 Commented table_series code, changed ParamsStatisticsArray to take shared params instead, create DummySeries to use when we don't want to save a named series
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30 Begins construction of a class inheriting from IsDescription
dc0d77c8a878 Commented table_series code, changed ParamsStatisticsArray to take shared params instead, create DummySeries to use when we don't want to save a named series
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31 to construct an HDF5 table with index columns named with int_names.
dc0d77c8a878 Commented table_series code, changed ParamsStatisticsArray to take shared params instead, create DummySeries to use when we don't want to save a named series
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32
dc0d77c8a878 Commented table_series code, changed ParamsStatisticsArray to take shared params instead, create DummySeries to use when we don't want to save a named series
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33 See Series().__init__ to see how those are used.
dc0d77c8a878 Commented table_series code, changed ParamsStatisticsArray to take shared params instead, create DummySeries to use when we don't want to save a named series
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34 """
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acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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35 int_constructor = "Int64Col"
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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36 if int_width == 32:
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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37 int_constructor = "Int32Col"
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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38
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39 toexec = ""
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acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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40
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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41 for n in int_names:
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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42 toexec += "\t" + n + " = " + int_constructor + "(pos=" + str(pos) + ")\n"
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43 pos += 1
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acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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44
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45 return toexec, pos
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acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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46
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47 def _get_description_with_n_ints_n_floats(int_names, float_names,
4c137f16b013 Modifications pour stocker des timestamps/cpuclock avec chaque rangée créée, selon suggestion de Yoshua ce matin
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48 int_width=64, float_width=32,
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49 store_timestamp=True, store_cpuclock=True):
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acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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50 """
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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51 Constructs a class to be used when constructing a table with PyTables.
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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52
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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53 This is useful to construct a series with an index with multiple levels.
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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54 E.g. if you want to index your "validation error" with "epoch" first, then
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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55 "minibatch_index" second, you'd use two "int_names".
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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56
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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57 Parameters
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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58 ----------
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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59 int_names : tuple of str
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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60 Names of the int (e.g. index) columns
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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61 float_names : tuple of str
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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62 Names of the float (e.g. error) columns
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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63 int_width : {'32', '64'}
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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64 Type of ints.
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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65 float_width : {'32', '64'}
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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66 Type of floats.
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67 store_timestamp : bool
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68 See __init__ of Series
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69 store_cpuclock : bool
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70 See __init__ of Series
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acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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71
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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72 Returns
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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73 -------
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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74 A class object, to pass to createTable()
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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75 """
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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76
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77 toexec = "class LocalDescription(IsDescription):\n"
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78
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79 toexec_, pos = _get_description_timestamp_cpuclock_columns(store_timestamp, store_cpuclock)
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80 toexec += toexec_
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81
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82 toexec_, pos = _get_description_n_ints(int_names, int_width=int_width, pos=pos)
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83 toexec += toexec_
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acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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84
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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85 float_constructor = "Float32Col"
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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86 if float_width == 64:
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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87 float_constructor = "Float64Col"
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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88
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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89 for n in float_names:
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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90 toexec += "\t" + n + " = " + float_constructor + "(pos=" + str(pos) + ")\n"
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91 pos += 1
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acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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92
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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93 exec(toexec)
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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94
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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95 return LocalDescription
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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96
acb942530923 Completely rewrote my series module, now based on HDF5 and PyTables (in a separate directory called 'tables_series' for retrocompatibility of running code). Minor (inconsequential) changes to stacked_dae.
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97 class Series():
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98 def __init__(self, table_name, hdf5_file, index_names=('epoch',),
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99 title="", hdf5_group='/',
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100 store_timestamp=True, store_cpuclock=True):
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dc0d77c8a878 Commented table_series code, changed ParamsStatisticsArray to take shared params instead, create DummySeries to use when we don't want to save a named series
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101 """Basic arguments each Series must get.
dc0d77c8a878 Commented table_series code, changed ParamsStatisticsArray to take shared params instead, create DummySeries to use when we don't want to save a named series
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102
dc0d77c8a878 Commented table_series code, changed ParamsStatisticsArray to take shared params instead, create DummySeries to use when we don't want to save a named series
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103 Parameters
dc0d77c8a878 Commented table_series code, changed ParamsStatisticsArray to take shared params instead, create DummySeries to use when we don't want to save a named series
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104 ----------
dc0d77c8a878 Commented table_series code, changed ParamsStatisticsArray to take shared params instead, create DummySeries to use when we don't want to save a named series
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105 table_name : str
dc0d77c8a878 Commented table_series code, changed ParamsStatisticsArray to take shared params instead, create DummySeries to use when we don't want to save a named series
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106 Name of the table to create under group "hd5_group" (other parameter). No spaces, ie. follow variable naming restrictions.
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107 hdf5_file : open HDF5 file
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108 File opened with openFile() in PyTables (ie. return value of openFile).
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109 index_names : tuple of str
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110 Columns to use as index for elements in the series, other example would be ('epoch', 'minibatch'). This would then allow you to call append(index, element) with index made of two ints, one for epoch index, one for minibatch index in epoch.
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111 title : str
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112 Title to attach to this table as metadata. Can contain spaces and be longer then the table_name.
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113 hdf5_group : str
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114 Path of the group (kind of a file) in the HDF5 file under which to create the table.
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115 store_timestamp : bool
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116 Whether to create a column for timestamps and store them with each record.
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117 store_cpuclock : bool
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118 Whether to create a column for cpu clock and store it with each record.
210
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119 """
208
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120 self.table_name = table_name
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121 self.hdf5_file = hdf5_file
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122 self.index_names = index_names
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123 self.title = title
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124
218
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125 self.store_timestamp = store_timestamp
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126 self.store_cpuclock = store_cpuclock
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127
208
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128 def append(self, index, element):
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129 raise NotImplementedError
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130
218
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131 def _timestamp_cpuclock(self, newrow):
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132 newrow["timestamp"] = time.time()
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133 newrow["cpuclock"] = time.clock()
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134
210
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135 # To put in a series dictionary instead of a real series, to do nothing
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136 # when we don't want a given series to be saved.
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137 class DummySeries():
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138 def append(self, index, element):
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139 pass
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140
208
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141 class ErrorSeries(Series):
218
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142 def __init__(self, error_name, table_name,
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143 hdf5_file, index_names=('epoch',),
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144 title="", hdf5_group='/',
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145 store_timestamp=True, store_cpuclock=True):
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146 Series.__init__(self, table_name, hdf5_file, index_names, title, store_timestamp, store_cpuclock)
208
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147
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148 self.error_name = error_name
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149
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150 table_description = self._get_table_description()
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151
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152 self._table = hdf5_file.createTable(hdf5_group, self.table_name, table_description, title=title)
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153
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154 def _get_table_description(self):
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155 return _get_description_with_n_ints_n_floats(self.index_names, (self.error_name,))
208
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156
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157 def append(self, index, error):
210
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158 """
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159 Parameters
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160 ----------
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161 index : tuple of int
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162 Following index_names passed to __init__, e.g. (12, 15) if index_names were ('epoch', 'minibatch_size')
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163 error : float
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164 Next error in the series.
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165 """
208
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166 if len(index) != len(self.index_names):
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167 raise ValueError("index provided does not have the right length (expected " \
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168 + str(len(self.index_names)) + " got " + str(len(index)))
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169
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170 newrow = self._table.row
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171
210
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172 # Columns for index in table are based on index_names
208
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173 for col_name, value in zip(self.index_names, index):
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174 newrow[col_name] = value
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175 newrow[self.error_name] = error
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176
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177 self._timestamp_cpuclock(newrow)
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178
208
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179 newrow.append()
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180
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181 self.hdf5_file.flush()
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182
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183 # Does not inherit from Series because it does not itself need to
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184 # access the hdf5_file and does not need a series_name (provided
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185 # by the base_series.)
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186 class AccumulatorSeriesWrapper():
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187 """
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188
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189 """
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190 def __init__(self, base_series, reduce_every, reduce_function=numpy.mean):
210
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191 """
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192 Parameters
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193 ----------
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194 base_series : Series
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195 This object must have an append(index, value) function.
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196 reduce_every : int
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197 Apply the reduction function (e.g. mean()) every time we get this number of elements. E.g. if this is 100, then every 100 numbers passed to append(), we'll take the mean and call append(this_mean) on the BaseSeries.
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198 reduce_function : function
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199 Must take as input an array of "elements", as passed to (this accumulator's) append(). Basic case would be to take an array of floats and sum them into one float, for example.
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200 """
208
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201 self.base_series = base_series
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202 self.reduce_function = reduce_function
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203 self.reduce_every = reduce_every
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204
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205 self._buffer = []
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206
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207
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208 def append(self, index, element):
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209 """
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210 Parameters
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211 ----------
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212 index : tuple of int
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213 The index used is the one of the last element reduced. E.g. if
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214 you accumulate over the first 1000 minibatches, the index
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215 passed to the base_series.append() function will be 1000.
210
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216 element : float
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217 Element that will be accumulated.
208
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218 """
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219 self._buffer.append(element)
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220
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221 if len(self._buffer) == self.reduce_every:
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222 reduced = self.reduce_function(self._buffer)
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223 self.base_series.append(index, reduced)
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224 self._buffer = []
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225
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226 # This should never happen, except if lists
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227 # were appended, which should be a red flag.
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228 assert len(self._buffer) < self.reduce_every
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229
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230 # Outside of class to fix an issue with exec in Python 2.6.
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231 # My sorries to the God of pretty code.
218
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232 def _BasicStatisticsSeries_construct_table_toexec(index_names, store_timestamp, store_cpuclock):
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233 toexec = "class LocalDescription(IsDescription):\n"
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234
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235 toexec_, pos = _get_description_timestamp_cpuclock_columns(store_timestamp, store_cpuclock)
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236 toexec += toexec_
208
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237
218
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238 toexec_, pos = _get_description_n_ints(index_names, pos=pos)
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239 toexec += toexec_
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240
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241 toexec += "\tmean = Float32Col(pos=" + str(pos) + ")\n"
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242 toexec += "\tmin = Float32Col(pos=" + str(pos+1) + ")\n"
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243 toexec += "\tmax = Float32Col(pos=" + str(pos+2) + ")\n"
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244 toexec += "\tstd = Float32Col(pos=" + str(pos+3) + ")\n"
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245
208
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246 # This creates "LocalDescription", which we may then use
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247 exec(toexec)
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248
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249 return LocalDescription
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250
210
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251 basic_stats_functions = {'mean': lambda(x): numpy.mean(x),
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252 'min': lambda(x): numpy.min(x),
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253 'max': lambda(x): numpy.max(x),
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254 'std': lambda(x): numpy.std(x)}
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255
208
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256 class BasicStatisticsSeries(Series):
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257 """
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258 Parameters
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259 ----------
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260 series_name : str
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261 Not optional here. Will be prepended with "Basic statistics for "
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262 stats_functions : dict, optional
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263 Dictionary with a function for each key "mean", "min", "max", "std". The function must take whatever is passed to append(...) and return a single number (float).
208
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264 """
218
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265 def __init__(self, table_name, hdf5_file,
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266 stats_functions=basic_stats_functions,
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267 index_names=('epoch',), title="", hdf5_group='/',
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268 store_timestamp=True, store_cpuclock=True):
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269 Series.__init__(self, table_name, hdf5_file, index_names, title, store_timestamp, store_cpuclock)
208
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270
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271 self.hdf5_group = hdf5_group
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272
210
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273 self.stats_functions = stats_functions
208
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274
210
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275 self._construct_table()
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276
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277 def _construct_table(self):
218
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278 table_description = _BasicStatisticsSeries_construct_table_toexec(self.index_names, self.store_timestamp, self.store_cpuclock)
208
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279
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280 self._table = self.hdf5_file.createTable(self.hdf5_group, self.table_name, table_description)
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281
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282 def append(self, index, array):
210
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283 """
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284 Parameters
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285 ----------
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286 index : tuple of int
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287 Following index_names passed to __init__, e.g. (12, 15) if index_names were ('epoch', 'minibatch_size')
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288 array
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289 Is of whatever type the stats_functions passed to __init__ can take. Default is anything numpy.mean(), min(), max(), std() can take.
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290 """
208
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291 if len(index) != len(self.index_names):
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292 raise ValueError("index provided does not have the right length (expected " \
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293 + str(len(self.index_names)) + " got " + str(len(index)))
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294
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295 newrow = self._table.row
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296
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297 for col_name, value in zip(self.index_names, index):
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298 newrow[col_name] = value
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299
210
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300 newrow["mean"] = self.stats_functions['mean'](array)
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301 newrow["min"] = self.stats_functions['min'](array)
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302 newrow["max"] = self.stats_functions['max'](array)
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303 newrow["std"] = self.stats_functions['std'](array)
208
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304
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305 self._timestamp_cpuclock(newrow)
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306
208
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307 newrow.append()
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308
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309 self.hdf5_file.flush()
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310
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311 class SeriesArrayWrapper():
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312 """
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313 Simply redistributes any number of elements to sub-series to respective append()s.
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315 To use if you have many elements to append in similar series, e.g. if you have an array containing [train_error, valid_error, test_error], and 3 corresponding series, this allows you to simply pass this array of 3 values to append() instead of passing each element to each individual series in turn.
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316 """
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317
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318 def __init__(self, base_series_list):
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319 self.base_series_list = base_series_list
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320
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321 def append(self, index, elements):
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322 if len(elements) != len(self.base_series_list):
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323 raise ValueError("not enough or too much elements provided (expected " \
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324 + str(len(self.base_series_list)) + " got " + str(len(elements)))
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325
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326 for series, el in zip(self.base_series_list, elements):
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327 series.append(index, el)
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328
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329 class SharedParamsStatisticsWrapper(SeriesArrayWrapper):
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330 '''Save mean, min/max, std of shared parameters place in an array.
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331
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332 This is specifically for cases where we have _shared_ parameters,
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333 as we take the .value of each array'''
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334
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335 def __init__(self, arrays_names, new_group_name, hdf5_file, base_group='/', index_names=('epoch',), title=""):
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336 """
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337 Parameters
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338 ----------
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339 array_names : array of str
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340 Name of each array, in order of the array passed to append(). E.g. ('layer1_b', 'layer1_W', 'layer2_b', 'layer2_W')
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341 new_group_name : str
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342 Name of a new HDF5 group which will be created under base_group to store the new series.
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343 base_group : str
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344 Path of the group under which to create the new group which will store the series.
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345 title : str
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346 Here the title is attached to the new group, not a table.
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347 """
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348 base_series_list = []
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349
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350 new_group = hdf5_file.createGroup(base_group, new_group_name, title=title)
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351
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352 stats_functions = {'mean': lambda(x): numpy.mean(x.value),
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353 'min': lambda(x): numpy.min(x.value),
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354 'max': lambda(x): numpy.max(x.value),
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355 'std': lambda(x): numpy.std(x.value)}
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356
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357 for name in arrays_names:
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358 base_series_list.append(
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359 BasicStatisticsSeries(
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360 table_name=name,
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361 hdf5_file=hdf5_file,
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362 index_names=index_names,
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363 stats_functions=stats_functions,
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364 hdf5_group=new_group._v_pathname))
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365
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366 SeriesArrayWrapper.__init__(self, base_series_list)
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367
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368