From 03f4beb8777bcd24b46a71b5229960c3d76a3f66 Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Mon, 18 Jun 2018 11:42:24 +0800 Subject: [PATCH] add doc for ErrorClipByValue GradientClipByValue and GradientClipByGlobalNorm --- python/paddle/fluid/clip.py | 96 ++++++++++++++++++++++++++++++++----- 1 file changed, 85 insertions(+), 11 deletions(-) diff --git a/python/paddle/fluid/clip.py b/python/paddle/fluid/clip.py index 66c3fc6b66d..adfad3b4020 100644 --- a/python/paddle/fluid/clip.py +++ b/python/paddle/fluid/clip.py @@ -24,8 +24,6 @@ __all__ = [ 'GradientClipByValue', 'GradientClipByNorm', 'GradientClipByGlobalNorm', - 'append_gradient_clip_ops', - 'error_clip_callback', ] @@ -38,6 +36,25 @@ class BaseErrorClipAttr(object): class ErrorClipByValue(BaseErrorClipAttr): + """ + Clips tensor values to the range [min, max]. + + Given a tensor t, this operation clips its value to min and max inplace. + + - Any values less than min are set to min. + - Any values greater than max are set to max. + + Args: + max (float): The maximum value to clip by. + min (float, optional): The minimum value to clip by. if not set by user, \ + will be set to -max by framework. + + Examples: + .. code-block:: python + + var = fluid.framework.Variable(..., error_clip=ErrorClipByValue(max=5.0), ...) + """ + def __init__(self, max, min=None): max = float(max) if min is None: @@ -99,6 +116,31 @@ class NullGradientClipAttr(BaseGradientClipAttr): class GradientClipByValue(BaseGradientClipAttr): + """ + Clips gradient values to the range [min, max]. + + Given a tensor t, this operation clips its value to min and max inplace. + + - Any values less than min are set to min. + - Any values greater than max are set to max. + + Args: + max (float): The maximum value to clip by. + min (float, optional): The minimum value to clip by. if not set by user, \ + will be set to -max by framework. + + Examples: + .. code-block:: python + + w_param_attrs = ParamAttr(name=None, + initializer=UniformInitializer(low=-1.0, high=1.0, seed=0), + learning_rate=1.0, + regularizer=L1Decay(1.0), + trainable=True, + clip=GradientClipByValue(-1.0, 1.0)) + y_predict = fluid.layers.fc(input=x, size=1, param_attr=w_param_attrs) + """ + def __init__(self, max, min=None): max = float(max) if min is None: @@ -120,6 +162,37 @@ class GradientClipByValue(BaseGradientClipAttr): class GradientClipByNorm(BaseGradientClipAttr): + """ + Clips tensor values to a maximum L2-norm. + + This operator limits the L2 norm of the input :math:`X` within :math:`max\_norm`. + If the L2 norm of :math:`X` is less than or equal to :math:`max\_norm`, :math:`Out` + will be the same as :math:`X`. If the L2 norm of :math:`X` is greater than + :math:`max\_norm`, :math:`X` will be linearly scaled to make the L2 norm of + :math:`Out` equal to :math:`max\_norm`, as shown in the following formula: + + .. math:: + + Out = \\frac{max\_norm * X}{norm(X)}, + + where :math:`norm(X)` represents the L2 norm of :math:`X`. + + Args: + clip_norm (float): The maximum norm value + + Examples: + .. code-block:: python + + w_param_attrs = ParamAttr(name=None, + initializer=UniformInitializer(low=-1.0, high=1.0, seed=0), + learning_rate=1.0, + regularizer=L1Decay(1.0), + trainable=True, + clip=GradientClipByNorm(clip_norm=2.0)) + y_predict = fluid.layers.fc(input=x, size=1, param_attr=w_param_attrs) + + """ + def __init__(self, clip_norm): self.clip_norm = clip_norm @@ -183,15 +256,16 @@ class GradientClipByGlobalNorm(BaseGradientClipAttr): def set_gradient_clip(clip, param_list=None, program=None): """ - To specify parameters that require gradient clip. - Args: - clip(BaseGradientClipAttr): An instance of some derived class of BaseGradientClipAttr, - which describes the type and detailed attributes of required gradient clip. - param_list(list, None by default): Parameters that require gradient clip. - It can be a list of parameter or a list of parameter's name. - When it's None, all parameters in the program will be included. - program(Program, None by default): The program where parameters are. - Will be the default main program when assigned with None. + To specify parameters that require gradient clip. + + Args: + clip(BaseGradientClipAttr): An instance of some derived class of BaseGradientClipAttr, + which describes the type and detailed attributes of required gradient clip. + param_list(list(Variable)): Parameters that require gradient clip. + It can be a list of parameter or a list of parameter's name. + When it's None, all parameters in the program will be included. + program(Program): The program where parameters are. + Will be the default main program when assigned with None. """ if not isinstance(clip, BaseGradientClipAttr): raise TypeError( -- GitLab