Skip to content

fix dropout and clipping settings in layer helpers. #3071

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Jul 27, 2017
Merged

fix dropout and clipping settings in layer helpers. #3071

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion python/paddle/trainer_config_helpers/attrs.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -272,7 +272,7 @@ def check(self, layer_name):
for key in self.attr:
if not hasattr(self, 'can_%s' % key) or \
not getattr(self, 'can_%s' % key):
raise NotImplementedError("Layer %s cannot support %s" %
raise NotImplementedError("Layer %s does not support %s" %
(layer_name, key))

@staticmethod
Expand Down
31 changes: 11 additions & 20 deletions python/paddle/trainer_config_helpers/layers.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -865,7 +865,7 @@ def data_layer(name, size, height=None, width=None, layer_attr=None):

@wrap_name_default("embedding")
@wrap_param_attr_default()
@layer_support(ERROR_CLIPPING)
@layer_support(ERROR_CLIPPING, DROPOUT)
def embedding_layer(input, size, name=None, param_attr=None, layer_attr=None):
"""
Define a embedding Layer.
Expand Down Expand Up @@ -1320,7 +1320,7 @@ def pooling_layer(input,
@wrap_act_default(param_names=['gate_act'], act=SigmoidActivation())
@wrap_act_default(param_names=["act", 'state_act'], act=TanhActivation())
@wrap_name_default("lstmemory")
@layer_support(DROPOUT)
@layer_support()
def lstmemory(input,
name=None,
size=None,
Expand Down Expand Up @@ -1429,7 +1429,7 @@ def lstmemory(input,
@wrap_act_default(param_names=['gate_act'], act=SigmoidActivation())
@wrap_act_default(param_names=["act"], act=TanhActivation())
@wrap_name_default("gru")
@layer_support(DROPOUT)
@layer_support()
def grumemory(input,
size=None,
name=None,
Expand Down Expand Up @@ -1793,7 +1793,7 @@ def repeat_layer(input,
@wrap_name_default("seqreshape")
@wrap_act_default(act=IdentityActivation())
@wrap_bias_attr_default(has_bias=False)
@layer_support()
@layer_support(ERROR_CLIPPING, DROPOUT)
def seq_reshape_layer(input,
reshape_size,
act=None,
Expand Down Expand Up @@ -2703,7 +2703,7 @@ def img_cmrnorm_layer(input,
default_factory=lambda _: ParamAttr(initial_mean=1.0, initial_std=0.))
@wrap_act_default(act=ReluActivation())
@wrap_name_default("batch_norm")
@layer_support(DROPOUT)
@layer_support(DROPOUT, ERROR_CLIPPING)
def batch_norm_layer(input,
act=None,
name=None,
Expand Down Expand Up @@ -2783,15 +2783,6 @@ def batch_norm_layer(input,
:return: LayerOutput object.
:rtype: LayerOutput
"""
if not isinstance(act, ReluActivation):
logger.log(logging.WARN,
"%s is not recommend for batch normalization's activation, "
"maybe the relu is better" % act.name)

if not isinstance(input.activation, LinearActivation):
logger.log(logging.WARN,
"The activation should be inside batch normalization, the "
"previous layer's activation may be Linear")

if num_channels is None:
if input.num_filters is not None:
Expand Down Expand Up @@ -2861,7 +2852,7 @@ def sum_to_one_norm_layer(input, name=None, layer_attr=None):
@wrap_name_default("addto")
@wrap_act_default(act=LinearActivation())
@wrap_bias_attr_default(has_bias=False)
@layer_support(DROPOUT)
@layer_support(DROPOUT, ERROR_CLIPPING)
def addto_layer(input, act=None, name=None, bias_attr=None, layer_attr=None):
"""
AddtoLayer.
Expand Down Expand Up @@ -2940,7 +2931,7 @@ def addto_layer(input, act=None, name=None, bias_attr=None, layer_attr=None):

@wrap_act_default(act=IdentityActivation())
@wrap_name_default("concat")
@layer_support()
@layer_support(DROPOUT, ERROR_CLIPPING)
def concat_layer(input, act=None, name=None, layer_attr=None, bias_attr=None):
"""
Concat all input vector into one huge vector.
Expand Down Expand Up @@ -3024,7 +3015,7 @@ def __reduce_concat_type__(a, b):
@wrap_name_default("seqconcat")
@wrap_act_default(act=IdentityActivation())
@wrap_bias_attr_default(has_bias=False)
@layer_support()
@layer_support(DROPOUT, ERROR_CLIPPING)
def seq_concat_layer(a, b, act=None, name=None, layer_attr=None,
bias_attr=None):
"""
Expand Down Expand Up @@ -3177,7 +3168,7 @@ def memory(name,
@wrap_act_default(param_names=['state_act'], act=TanhActivation())
@wrap_act_default(act=TanhActivation())
@wrap_name_default('lstm_step')
@layer_support(ERROR_CLIPPING, DROPOUT)
@layer_support()
def lstm_step_layer(input,
state,
size=None,
Expand Down Expand Up @@ -4480,7 +4471,7 @@ def tensor_layer(a,
@wrap_param_attr_default()
@wrap_bias_attr_default()
@wrap_act_default()
@layer_support()
@layer_support(DROPOUT, ERROR_CLIPPING)
def selective_fc_layer(input,
size,
select=None,
Expand Down Expand Up @@ -5974,7 +5965,7 @@ def crop_layer(input, offset, axis=2, shape=None, name=None, layer_attr=None):
"""
The crop layer crops images by offset and shape. User can set crop shape by
args 'shape' explicitly or by reference input layer.

The example usage is:

.. code-block:: python
Expand Down