|
- axis_inp = Doc(
- 'axis',
- 'axis along which to reduce input var; if it is None, '
- 'the input would be flattened',
- 'int or None',
- 'None')
- keepdims_inp = Doc(
- 'keepdims',
- 'If True, the given axis would have be shape 1 in the output; otherwise '
- 'it would removed',
- 'bool',
- 'False')
- call_reduce_like = lambda impl: [
- 'output = _reduce_like({}, src, axis, keepdims, name, comp_node, config, '
- 'comp_graph)'.format(impl)]
-
- decl_opr('Argmax', pyname='_argmax',
- inputs=['src'],
- params=[('axis', 'Axis')])
-
- decl_opr('Argmin', pyname='_argmin',
- inputs=['src'],
- params=[('axis', 'Axis')])
-
- decl_raw_opr(
- 'argmax',
- desc='Returns the indices of the maximum values along an axis.',
- inputs=['src', axis_inp, keepdims_inp],
- body=call_reduce_like('_argmax'))
-
- decl_raw_opr(
- 'argmin',
- desc='Returns the indices of the minimum values along an axis.',
- inputs=['src', axis_inp, keepdims_inp],
- body=call_reduce_like('_argmin'))
-
- decl_opr('Argsort',
- inputs=['src'],
- params='Argsort',
- desc='The input must be an :math:`(m, n)` matrix. and this operator '
- 'sorts each row independently, so :math:`m` independent sortings are '
- 'performed. Two vars are returned: the sorted array, and the '
- 'indices. ')
-
- decl_opr('Cumsum',
- inputs=['src'], params='Cumsum',
- body=[
- 'if param.axis == (1<<31)-1:',
- ' all_inputs[0] = all_inputs[0].flatten()',
- ' param.axis = 0'
- ],
- desc='Return the cumulative sum of the elements along a given axis.'
- ' If axis is INT_MAX, compute on flattened input.', version=1)
-
- decl_opr('CondTake',
- inputs=['data', 'mask'], params='CondTake',
- desc='Take elements from *data* according to *mask* and *param*. '
- 'This operator has two outputs, both 1-dimensional: the first is '
- 'the element values, and the second is corresponding offsets of the '
- 'taken values')
-
- decl_opr('TopK',
- inputs=['data', 'k'], params='TopK',
- desc='Select the top k values from sorted result.')
-
-
- # vim: ft=python
|
