## PyTorch ## 统计属性 主讲人：龙良曲 ## statistics - norm mean sum • prod max, min, argmin, argmax kthvalue, topk v.s. normalize ,e.g. batch norm ■ matrix norm v.s. vector norm ## V ector vs matrix Matrix In [145]: a.sum() 9 Out[145]: tensor(28.) 11 In [147]: a.argmax(), a.argmin() 12 Out[147]: (tensor(7), tensor(0)) 13 ## argmin, argmax ## ☀️ ☀️ ☁️ 1 In [149]: a=a.view(1,2,4) 2 tensor([[0., 1., 2 , 3.], 3 [4., 5., 6., 7.]]]) 5 In [151]: a.argmax() 6 Out[151]: tensor(7) 8 In [152]: a.argmin() 9 Out[152]: tensor(0) 11 In [153]: a=torch.rand(2,3,4) 12 13 In [154]: a.argmax() 14 Out[154]:

minor_ax to conform with other NDFrame objects. See Internal Refactoring for more information. • Series.argmin and Series.argmax are now aliased to Series.idxmin and Series.idxmax. These return the i min or max pandas: powerful Python data analysis toolkit, Release 0.17.0 Note: idxmin and idxmax are called argmin and argmax in NumPy. 10.5.3 Value counts (histogramming) / Mode The value_counts() Series method on values of Series. argmax([axis, out, skipna]) Index of first occurrence of maximum of values. argmin([axis, out, skipna]) Index of first occurrence of minimum of values. argsort([axis, kind, order])

minor_ax to conform with other NDFrame objects. See Internal Refactoring for more information. • Series.argmin and Series.argmax are now aliased to Series.idxmin and Series.idxmax. These return the i min or max Release 0.15.2 c 1 b 3 a NaN In [97]: df3[’A’].idxmin() Out[97]: ’d’ Note: idxmin and idxmax are called argmin and argmax in NumPy. 9.5.3 Value counts (histogramming) / Mode The value_counts Series method and ufunc (a NumPy function argmax([axis, out, skipna]) Index of first occurrence of maximum of values. argmin([axis, out, skipna]) Index of first occurrence of minimum of values. argsort([axis, kind, order])

DataFrame.select . . . . . . . . . . . . . . . . . . . . . . . . . . 26 1.2.3.2 Series.argmax and Series.argmin . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 1.2.4 Removal of prior version deprecations/changes argmax . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1735 34.6.1.31 pandas.Index.argmin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1735 34.6.1.32 pandas.Index.argsort argmax . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1776 34.10.1.35pandas.MultiIndex.argmin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1777 34.10.1.36pandas.MultiIndex.argsort

to conform with other NDFrame objects. See Internal Refactoring for more information. • Series.argmin and Series.argmax are now aliased to Series.idxmin and Series.idxmax. These return the index of the NaN In [97]: df3['A'].idxmin() Out [97]: 'd' Note: idxmin and idxmax are called argmin and argmax in NumPy. #### 9.5.3 Value counts (histogramming) / Mode The value_counts Series method (a NumPy function| |argmax(\[axis, out, skipna])|Index of first occurrence of maximum of values.| |argmin(\[axis, out, skipna])|Index of first occurrence of minimum of values.| |argsort(\[axis, kind, order])|Overrides

minor_ax to conform with other NDFrame objects. See Internal Refactoring for more information. • Series.argmin and Series.argmax are now aliased to Series.idxmin and Series.idxmax. These return the i 1.2. v0 NaN [5 rows x 1 columns] In [85]: df3[’A’].idxmin() Out[85]: ’d’ Note: idxmin and idxmax are called argmin and argmax in NumPy. 9.5.3 Value counts (histogramming) / Mode The value_counts Series method and ufunc (a NumPy function argmax([axis, out, skipna]) Index of first occurrence of maximum of values. argmin([axis, out, skipna]) Index of first occurrence of minimum of values. argsort([axis, kind, order])

Index.any ..... 1572 pandas.Index.append ..... 1573 pandas.Index.argmax ..... 1573 pandas.Index.argmin ..... 1573 pandas.Index.argsort ..... 1573 pandas.Index.asof ..... 1573 pandas.Index.asof_locs CategoricalIndex.append ..... 1599 pandas.CategoricalIndex.argmax ..... 1600 pandas.CategoricalIndex.argmin ..... 1600 pandas.CategoricalIndex.argsort ..... 1600 pandas.CategoricalIndex.as_ordered ... MultiIndex.any 1628 pandas.MultiIndex.append 1628 pandas.MultiIndex.argmax 1628 pandas.MultiIndex.argmin 1628 pandas.MultiIndex.argsort 1628 pandas.MultiIndex.asof 1628 pandas.MultiIndex.asof_locs

WITH toDateTime('2019-10-02 12:00:00') AS target_time SELECT argMin(insert_id, target_time-update_time) insert_id, argMin(flag, target_time-update_time) flag FROM classroom_all WHERE target_time-update_time

WITH toDateTime('2019-10-02 12:00:00') AS target_time SELECT argMin(insert_id, target_time-update_time) insert_id, argMin(flag, target_time-update_time) flag FROM classroom_all WHERE target_time-update_time

minor_ax to conform with other NDFrame objects. See Internal Refactoring for more information. • Series.argmin and Series.argmax are now aliased to Series.idxmin and Series.idxmax. These return the i min or max toolkit, Release 0.14.0 In [88]: df3[’A’].idxmin() Out[88]: ’d’ Note: idxmin and idxmax are called argmin and argmax in NumPy. 9.5.3 Value counts (histogramming) / Mode The value_counts Series method and ufunc (a NumPy function argmax([axis, out, skipna]) Index of first occurrence of maximum of values. argmin([axis, out, skipna]) Index of first occurrence of minimum of values. argsort([axis, kind, order])