未验证 提交 df9c13a8 编写于 作者: C Cao Ying 提交者: GitHub

Merge pull request #7485 from lcy-seso/wrapper_for_elementwise_math_op

add wrapper for element-wise math operator.
......@@ -358,3 +358,132 @@ reduce_min
.. autofunction:: paddle.v2.fluid.layers.reduce_min
:noindex:
logsigmoid
----------
.. autofunction:: paddle.v2.fluid.layers.logsigmoid
:noindex:
exp
---
.. autofunction:: paddle.v2.fluid.layers.exp
:noindex:
relu
----
.. autofunction:: paddle.v2.fluid.layers.relu
:noindex:
tanh
----
.. autofunction:: paddle.v2.fluid.layers.tanh
:noindex:
tanh_shrink
-----------
.. autofunction:: paddle.v2.fluid.layers.tanh_shrink
:noindex:
softshrink
----------
.. autofunction:: paddle.v2.fluid.layers.softshrink
:noindex:
sqrt
----
.. autofunction:: paddle.v2.fluid.layers.sqrt
:noindex:
abs
----
.. autofunction:: paddle.v2.fluid.layers.abs
:noindex:
ceil
----
.. autofunction:: paddle.v2.fluid.layers.ceil
:noindex:
floor
-----
.. autofunction:: paddle.v2.fluid.layers.floor
:noindex:
round
-----
.. autofunction:: paddle.v2.fluid.layers.round
:noindex:
reciprocal
----------
.. autofunction:: paddle.v2.fluid.layers.reciprocal
:noindex:
log
---
.. autofunction:: paddle.v2.fluid.layers.log
:noindex:
square
------
.. autofunction:: paddle.v2.fluid.layers.square
:noindex:
softplus
--------
.. autofunction:: paddle.v2.fluid.layers.softplus
:noindex:
softsign
---------
.. autofunction:: paddle.v2.fluid.layers.softsign
:noindex:
brelu
-----
.. autofunction:: paddle.v2.fluid.layers.brelu
:noindex:
leaky_relu
----------
.. autofunction:: paddle.v2.fluid.layers.leaky_relu
:noindex:
soft_relu
---------
.. autofunction:: paddle.v2.fluid.layers.soft_relu
:noindex:
elu
----
.. autofunction:: paddle.v2.fluid.layers.elu
:noindex:
relu6
-----
.. autofunction:: paddle.v2.fluid.layers.relu6
:noindex:
pow
----
.. autofunction:: paddle.v2.fluid.layers.pow
:noindex:
hard_shrink
-----------
.. autofunction:: paddle.v2.fluid.layers.hard_shrink
:noindex:
thresholded_relu
----------------
.. autofunction:: paddle.v2.fluid.layers.thresholded_relu
:noindex:
hard_sigmoid
-------------
.. autofunction:: paddle.v2.fluid.layers.hard_sigmoid
:noindex:
swish
------
.. autofunction:: paddle.v2.fluid.layers.swish
:noindex:
......@@ -23,9 +23,22 @@ from memory_optimization_transpiler import memory_optimize
Tensor = LoDTensor
__all__ = framework.__all__ + executor.__all__ + [
'io', 'initializer', 'layers', 'nets', 'optimizer', 'backward',
'regularizer', 'LoDTensor', 'CPUPlace', 'CUDAPlace', 'Tensor', 'ParamAttr'
'DataFeeder', 'clip', 'DistributeTranspiler', 'memory_optimize'
'io',
'initializer',
'layers',
'nets',
'optimizer',
'backward',
'regularizer',
'LoDTensor',
'CPUPlace',
'CUDAPlace',
'Tensor',
'ParamAttr'
'DataFeeder',
'clip',
'DistributeTranspiler',
'memory_optimize',
]
......
......@@ -3,7 +3,10 @@ from . import core
import collections
import copy
__all__ = ['append_backward', 'calc_gradient']
__all__ = [
'append_backward',
'calc_gradient',
]
def _rename_arg_(op_descs, old_name, new_name, begin_idx=None, end_idx=None):
......
......@@ -3,7 +3,9 @@ import layers
from . import core
__all__ = [
'GradientClipByValue', 'append_gradient_clip_ops', 'error_clip_callback'
'GradientClipByValue',
'append_gradient_clip_ops',
'error_clip_callback',
]
......
......@@ -19,8 +19,12 @@ import threading
__tl_scope__ = threading.local()
__all__ = [
'get_cur_scope', 'enter_local_scope', 'leave_local_scope', 'var',
'find_var', 'scoped_function'
'get_cur_scope',
'enter_local_scope',
'leave_local_scope',
'var',
'find_var',
'scoped_function',
]
......
......@@ -4,7 +4,10 @@ import layers
from framework import Program, unique_name, Variable, program_guard
from layer_helper import LayerHelper
__all__ = ['Accuracy', 'ChunkEvaluator']
__all__ = [
'Accuracy',
'ChunkEvaluator',
]
def _clone_var_(block, var):
......
......@@ -7,9 +7,15 @@ import proto.framework_pb2 as framework_pb2
from . import core
__all__ = [
'Block', 'Variable', 'Program', 'Operator', 'default_startup_program',
'default_main_program', 'program_guard', 'switch_startup_program',
'switch_main_program'
'Block',
'Variable',
'Program',
'Operator',
'default_startup_program',
'default_main_program',
'program_guard',
'switch_startup_program',
'switch_main_program',
]
EMPTY_VAR_NAME = core.kEmptyVarName()
......
import framework
import numpy as np
__all__ = ['Constant', 'Uniform', 'Normal', 'Xavier']
__all__ = [
'Constant',
'Uniform',
'Normal',
'Xavier',
]
class Initializer(object):
......
......@@ -4,9 +4,15 @@ import cPickle as pickle
from paddle.v2.fluid.framework import Program, Parameter, default_main_program, Variable
__all__ = [
'save_vars', 'save_params', 'save_persistables', 'load_vars', 'load_params',
'load_persistables', "save_inference_model", "load_inference_model",
"get_inference_program"
'save_vars',
'save_params',
'save_persistables',
'load_vars',
'load_params',
'load_persistables',
'save_inference_model',
'load_inference_model',
'get_inference_program',
]
......
......@@ -9,12 +9,33 @@ from ..param_attr import ParamAttr
from tensor import concat
__all__ = [
'fc', 'embedding', 'dynamic_lstm', 'gru_unit', 'linear_chain_crf',
'crf_decoding', 'cos_sim', 'cross_entropy', 'square_error_cost', 'accuracy',
'chunk_eval', 'sequence_conv', 'conv2d', 'sequence_pool', 'pool2d',
'batch_norm', 'beam_search_decode', 'conv2d_transpose', 'sequence_expand',
'lstm_unit', 'reduce_sum', 'reduce_mean', 'reduce_max', 'reduce_min',
'sequence_first_step', 'sequence_last_step', 'dropout'
'fc',
'embedding',
'dynamic_lstm',
'gru_unit',
'linear_chain_crf',
'crf_decoding',
'cos_sim',
'cross_entropy',
'square_error_cost',
'accuracy',
'chunk_eval',
'sequence_conv',
'conv2d',
'sequence_pool',
'pool2d',
'batch_norm',
'beam_search_decode',
'conv2d_transpose',
'sequence_expand',
'lstm_unit',
'reduce_sum',
'reduce_mean',
'reduce_max',
'reduce_min',
'sequence_first_step',
'sequence_last_step',
'dropout',
]
......
from ..registry import register_layer
__activations__ = [
'abs', 'tanh', 'sigmoid', 'relu', 'sqrt', 'ceil', 'floor', 'log', 'round'
'sigmoid',
'logsigmoid',
'exp',
'relu',
'tanh',
'tanh_shrink',
'softshrink',
'sqrt',
'abs',
'ceil',
'floor',
'round',
'reciprocal',
'log',
'square',
'softplus',
'softsign',
'brelu',
'leaky_relu',
'soft_relu',
'elu',
'relu6',
'pow',
'stanh',
'hard_shrink',
'thresholded_relu',
'hard_sigmoid',
'swish',
]
__all__ = [
......
......@@ -6,8 +6,16 @@ from ..core import DataType
import numpy
__all__ = [
'create_tensor', 'create_parameter', 'cast', 'concat', 'sums', 'assign',
'fill_constant_batch_size_like', 'fill_constant', 'ones', 'zeros'
'create_tensor',
'create_parameter',
'cast',
'concat',
'sums',
'assign',
'fill_constant_batch_size_like',
'fill_constant',
'ones',
'zeros',
]
......
......@@ -121,8 +121,10 @@ class ControlFlowGraph(object):
# and dtype_to_size[cache_dtype]
if x_dtype == cache_dtype:
print(
"Hit Cache !!!! cache pool index is %d, var name is %s, cached var name is %s, var shape is %s "
%
("Hit Cache !!!! cache pool index "
"is %d, var name is %s, "
"cached var name is %s, "
"var shape is %s ") %
(index, x, cache_var, str(cache_shape)))
self.pool.pop(index)
_rename_arg_(
......
import layers
__all__ = ["simple_img_conv_pool", "sequence_conv_pool"]
__all__ = [
"simple_img_conv_pool",
"sequence_conv_pool",
]
def simple_img_conv_pool(input,
......
......@@ -8,7 +8,11 @@ import proto.framework_pb2 as framework_pb2
from framework import OpProtoHolder, Variable, Program, Operator
from paddle.v2.fluid.layer_helper import LayerHelper, unique_name
__all__ = ['deprecated', 'register_layer', 'autodoc']
__all__ = [
'deprecated',
'register_layer',
'autodoc',
]
def _convert_(name):
......@@ -80,11 +84,10 @@ def _generate_doc_string_(op_proto):
def register_layer(op_type):
"""
Register an Python layer for an Operator
"""Register the Python layer for an Operator.
Args:
op_type: The name of the operator to be created
op_type: The name of the operator to be created.
This function takes in the operator type (sigmoid, mean , average etc) and
creates the operator functionality.
......@@ -98,16 +101,16 @@ def register_layer(op_type):
if len(not_intermediate_outputs) != 1:
raise ValueError("Only one non intermediate output operator can be",
"automatically generated")
"automatically generated.")
if not_intermediate_outputs[0].duplicable:
raise ValueError(
"Only non duplicable op can be automatically generated")
"Only non duplicable op can be automatically generated.")
for output in intermediate_outputs:
if output.duplicable:
raise ValueError("The op can be automatically generated only when ",
"all intermediate ops are not duplicable")
"all intermediate ops are not duplicable.")
o_name = not_intermediate_outputs[0].name
intermediate_output_names = [output.name for output in intermediate_outputs]
......
import framework
__all__ = ['append_regularization_ops', 'L1Decay', 'L2Decay']
__all__ = [
'append_regularization_ops',
'L1Decay',
'L2Decay',
]
def append_regularization_ops(parameters_and_grads, regularization=None):
......
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