未验证 提交 56a5039e 编写于 作者: Y Yiqun Liu 提交者: GitHub

Correct the doc in Python API (#15725)

* Correct the comment in control_flow.py.

* Correct the argument list of ops.
test=develop

* Update API.spec.
test=develop

* Skip op_callstack attr for all op apis.
test=develop

* Remove use_mkldnn and is_test from python api.
test=develop

* Remove use_mkldnn and is_test from op_proto_maker and hard-coding them in python when generating doc string.
test=develop
上级 72061b0a
......@@ -261,7 +261,7 @@ paddle.fluid.layers.increment ArgSpec(args=['x', 'value', 'in_place'], varargs=N
paddle.fluid.layers.array_write ArgSpec(args=['x', 'i', 'array'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.create_array ArgSpec(args=['dtype'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.less_than ArgSpec(args=['x', 'y', 'force_cpu', 'cond'], varargs=None, keywords='ignored', defaults=(None, None))
paddle.fluid.layers.equal ArgSpec(args=['x', 'y', 'cond'], varargs=None, keywords='ignored', defaults=(None,))
paddle.fluid.layers.equal ArgSpec(args=['x', 'y', 'cond'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.array_read ArgSpec(args=['array', 'i'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.array_length ArgSpec(args=['array'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.IfElse.__init__ ArgSpec(args=['self', 'cond', 'name'], varargs=None, keywords=None, defaults=(None,))
......
......@@ -51,6 +51,11 @@ class CompareOpProtoMaker : public framework::OpProtoAndCheckerMaker {
comment.type));
AddInput("Y", string::Sprintf("the right hand operand of %s operator",
comment.type));
AddAttr<int>(
"axis",
"The start dimension index for broadcasting Y onto X. [default -1]")
.SetDefault(-1)
.EqualGreaterThan(-1);
AddAttr<bool>("force_cpu",
"Force fill output variable to cpu "
"memory. Otherwise, fill output variable to the running "
......@@ -64,11 +69,6 @@ N-dim tensor. X and Y could be any type. The each element of the Out tensor is
calculated by $%s$
)DOC",
comment.equation));
AddAttr<int>(
"axis",
"The start dimension index for broadcasting Y onto X. [default -1]")
.SetDefault(-1)
.EqualGreaterThan(-1);
}
};
......
......@@ -557,7 +557,8 @@ class OpProtoHolder(object):
return {
core.op_proto_and_checker_maker.kOpRoleAttrName(),
core.op_proto_and_checker_maker.kOpRoleVarAttrName(),
core.op_proto_and_checker_maker.kOpNameScopeAttrName()
core.op_proto_and_checker_maker.kOpNameScopeAttrName(),
core.op_proto_and_checker_maker.kOpCreationCallstackAttrName()
}
......
......@@ -506,9 +506,9 @@ class While(object):
while loop control flow.
Args:
cond (Variable): condition used to compare.
cond(Variable): condition used to compare.
is_test(bool): A flag indicating whether execution is in test phase.
name (str): The name of this layer.
name(str): The name of this layer.
Examples:
.. code-block:: python
......@@ -589,7 +589,8 @@ class While(object):
def lod_rank_table(x, level=0):
"""LoD Rank Table Operator. Given an input variable **x** and a level number
"""
LoD Rank Table Operator. Given an input variable **x** and a level number
of LoD, this layer creates a LodRankTable object. A LoDRankTable object
contains a list of bi-element tuples. Each tuple consists of an index and
a length, both of which are int type. Refering to specified level of LoD,
......@@ -883,10 +884,8 @@ def less_than(x, y, force_cpu=None, cond=None, **ignored):
return cond
def equal(x, y, cond=None, **ignored):
def equal(x, y, cond=None):
"""
**equal**
This layer returns the truth value of :math:`x == y` elementwise.
Args:
......@@ -1458,7 +1457,6 @@ class DynamicRNN(object):
Returns:
The current timestep in the input sequence.
"""
self._assert_in_rnn_block_("step_input")
if not isinstance(x, Variable):
......@@ -1535,8 +1533,7 @@ class DynamicRNN(object):
@signature_safe_contextmanager
def block(self):
"""
The block for user to define operators in RNN. See the class docstring
for more details.
The block for user to define operators in RNN.
"""
if self.status != DynamicRNN.BEFORE_RNN:
raise ValueError("rnn.block() can only be invoke once")
......@@ -1640,8 +1637,7 @@ class DynamicRNN(object):
dtype(str|numpy.dtype): The data type of the initialized memory.
Returns:
the memory variable.
The memory variable.
"""
self._assert_in_rnn_block_('memory')
self._init_zero_idx_()
......@@ -1740,7 +1736,7 @@ class DynamicRNN(object):
def output(self, *outputs):
"""
mark the RNN output variables.
Mark the RNN output variables.
Args:
outputs: The output variables.
......
......@@ -24,7 +24,7 @@ from ..framework import OpProtoHolder, Variable, core, convert_np_dtype_to_dtype
from ..layer_helper import LayerHelper
__all__ = [
'deprecated', 'generate_layer_fn', 'generate_layer_fn_noattr', 'autodoc',
'deprecated', 'generate_layer_fn', 'generate_activation_fn', 'autodoc',
'templatedoc'
]
......@@ -89,6 +89,9 @@ def _generate_doc_string_(op_proto, additional_args_lines=None):
buf.write('\n')
skip_attrs = OpProtoHolder.generated_op_attr_names()
# attr use_mkldnn and is_test also should not be visible to users.
skip_attrs.add("use_mkldnn")
skip_attrs.add("is_test")
for each_attr in op_proto.attrs:
if each_attr.name in skip_attrs:
......@@ -226,7 +229,7 @@ def generate_layer_fn(op_type):
return func
def generate_layer_fn_noattr(op_type):
def generate_activation_fn(op_type):
"""Register the Python layer for an Operator without Attribute.
Args:
......@@ -246,6 +249,7 @@ def generate_layer_fn_noattr(op_type):
func.__name__ = op_type
func.__doc__ = _generate_doc_string_(op_proto)
return func
......
......@@ -14,7 +14,7 @@
from __future__ import print_function
import os
from .layer_function_generator import generate_layer_fn, generate_layer_fn_noattr
from .layer_function_generator import generate_layer_fn, generate_activation_fn
from .. import core
from ..framework import convert_np_dtype_to_dtype_
......@@ -53,7 +53,7 @@ globals()['_elementwise_div'] = generate_layer_fn('elementwise_div')
__all__ += __activations_noattr__
for _OP in set(__activations_noattr__):
globals()[_OP] = generate_layer_fn_noattr(_OP)
globals()[_OP] = generate_activation_fn(_OP)
__all__ += ["uniform_random"]
......
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