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fix API:cos, exp, ceil, elu, brelu English doc (#20032)

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* fix API:cos, exp, ceil, elu, brelu English doc
test=develop
test=document_fix
revert-20712-fix_depthwise_conv
GaoWei8 6 years ago committed by Kaipeng Deng
parent e705fede11
commit 5ea2cc6733
4 changed files with 67 additions and 43 deletions
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44
paddle/fluid/API.spec
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@ -223,14 +223,14 @@ paddle.fluid.layers.crop (ArgSpec(args=['x', 'shape', 'offsets', 'name'], vararg
paddle.fluid.layers.crop_tensor (ArgSpec(args=['x', 'shape', 'offsets', 'name'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', 'd460aaf35afbbeb9beea4789aa6e4343')) paddle.fluid.layers.crop_tensor (ArgSpec(args=['x', 'shape', 'offsets', 'name'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', 'd460aaf35afbbeb9beea4789aa6e4343'))
paddle.fluid.layers.rank_loss (ArgSpec(args=['label', 'left', 'right', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '6d49ba251e23f32cb09df54a851bb960')) paddle.fluid.layers.rank_loss (ArgSpec(args=['label', 'left', 'right', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '6d49ba251e23f32cb09df54a851bb960'))
paddle.fluid.layers.margin_rank_loss (ArgSpec(args=['label', 'left', 'right', 'margin', 'name'], varargs=None, keywords=None, defaults=(0.1, None)), ('document', '1a177f30e5013fae7ee6c45860cf4946')) paddle.fluid.layers.margin_rank_loss (ArgSpec(args=['label', 'left', 'right', 'margin', 'name'], varargs=None, keywords=None, defaults=(0.1, None)), ('document', '1a177f30e5013fae7ee6c45860cf4946'))
paddle.fluid.layers.elu (ArgSpec(args=['x', 'alpha', 'name'], varargs=None, keywords=None, defaults=(1.0, None)), ('document', '9af1926c06711eacef9e82d7a9e4d308')) paddle.fluid.layers.elu (ArgSpec(args=['x', 'alpha', 'name'], varargs=None, keywords=None, defaults=(1.0, None)), ('document', '06f669c66b3b2cc1cef01dfb42a40f08'))
paddle.fluid.layers.relu6 (ArgSpec(args=['x', 'threshold', 'name'], varargs=None, keywords=None, defaults=(6.0, None)), ('document', '538fc860b2a1734e118b94e4a1a3ee67')) paddle.fluid.layers.relu6 (ArgSpec(args=['x', 'threshold', 'name'], varargs=None, keywords=None, defaults=(6.0, None)), ('document', '538fc860b2a1734e118b94e4a1a3ee67'))
paddle.fluid.layers.pow (ArgSpec(args=['x', 'factor', 'name'], varargs=None, keywords=None, defaults=(1.0, None)), ('document', '00d437d1e0d9450ea75a0495b93b54a7')) paddle.fluid.layers.pow (ArgSpec(args=['x', 'factor', 'name'], varargs=None, keywords=None, defaults=(1.0, None)), ('document', '00d437d1e0d9450ea75a0495b93b54a7'))
paddle.fluid.layers.stanh (ArgSpec(args=['x', 'scale_a', 'scale_b', 'name'], varargs=None, keywords=None, defaults=(0.67, 1.7159, None)), ('document', 'd3f742178a7263adf5929153d104883d')) paddle.fluid.layers.stanh (ArgSpec(args=['x', 'scale_a', 'scale_b', 'name'], varargs=None, keywords=None, defaults=(0.67, 1.7159, None)), ('document', 'd3f742178a7263adf5929153d104883d'))
paddle.fluid.layers.hard_sigmoid (ArgSpec(args=['x', 'slope', 'offset', 'name'], varargs=None, keywords=None, defaults=(0.2, 0.5, None)), ('document', '607d79ca873bee40eed1c79a96611591')) paddle.fluid.layers.hard_sigmoid (ArgSpec(args=['x', 'slope', 'offset', 'name'], varargs=None, keywords=None, defaults=(0.2, 0.5, None)), ('document', '607d79ca873bee40eed1c79a96611591'))
paddle.fluid.layers.swish (ArgSpec(args=['x', 'beta', 'name'], varargs=None, keywords=None, defaults=(1.0, None)), ('document', '60b4dbe35f2b47f7290e79907a4eacec')) paddle.fluid.layers.swish (ArgSpec(args=['x', 'beta', 'name'], varargs=None, keywords=None, defaults=(1.0, None)), ('document', '60b4dbe35f2b47f7290e79907a4eacec'))
paddle.fluid.layers.prelu (ArgSpec(args=['x', 'mode', 'param_attr', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'cb417a61f701c937f33d057fe85203ab')) paddle.fluid.layers.prelu (ArgSpec(args=['x', 'mode', 'param_attr', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'cb417a61f701c937f33d057fe85203ab'))
paddle.fluid.layers.brelu (ArgSpec(args=['x', 't_min', 't_max', 'name'], varargs=None, keywords=None, defaults=(0.0, 24.0, None)), ('document', '49580538249a52c857fce75c94ad8af7')) paddle.fluid.layers.brelu (ArgSpec(args=['x', 't_min', 't_max', 'name'], varargs=None, keywords=None, defaults=(0.0, 24.0, None)), ('document', '35db66985af04bf6a91601aa4f73b54f'))
paddle.fluid.layers.leaky_relu (ArgSpec(args=['x', 'alpha', 'name'], varargs=None, keywords=None, defaults=(0.02, None)), ('document', '11352d3780f62952ea3332658714758c')) paddle.fluid.layers.leaky_relu (ArgSpec(args=['x', 'alpha', 'name'], varargs=None, keywords=None, defaults=(0.02, None)), ('document', '11352d3780f62952ea3332658714758c'))
paddle.fluid.layers.soft_relu (ArgSpec(args=['x', 'threshold', 'name'], varargs=None, keywords=None, defaults=(40.0, None)), ('document', 'f14efa9e5fd2e8b3d976cdda38eff43f')) paddle.fluid.layers.soft_relu (ArgSpec(args=['x', 'threshold', 'name'], varargs=None, keywords=None, defaults=(40.0, None)), ('document', 'f14efa9e5fd2e8b3d976cdda38eff43f'))
paddle.fluid.layers.flatten (ArgSpec(args=['x', 'axis', 'name'], varargs=None, keywords=None, defaults=(1, None)), ('document', '424ff350578992f201f2c5c30959ef89')) paddle.fluid.layers.flatten (ArgSpec(args=['x', 'axis', 'name'], varargs=None, keywords=None, defaults=(1, None)), ('document', '424ff350578992f201f2c5c30959ef89'))
@ -382,26 +382,26 @@ paddle.fluid.layers.StaticRNN.update_memory (ArgSpec(args=['self', 'mem', 'var']
paddle.fluid.layers.reorder_lod_tensor_by_rank (ArgSpec(args=['x', 'rank_table'], varargs=None, keywords=None, defaults=None), ('document', 'db67cfcdd20ff6380d125a7553d62121')) paddle.fluid.layers.reorder_lod_tensor_by_rank (ArgSpec(args=['x', 'rank_table'], varargs=None, keywords=None, defaults=None), ('document', 'db67cfcdd20ff6380d125a7553d62121'))
paddle.fluid.layers.Print (ArgSpec(args=['input', 'first_n', 'message', 'summarize', 'print_tensor_name', 'print_tensor_type', 'print_tensor_shape', 'print_tensor_lod', 'print_phase'], varargs=None, keywords=None, defaults=(-1, None, 20, True, True, True, True, 'both')), ('document', 'e57b87b4d1f9d4a6c7a3f4e6942dea10')) paddle.fluid.layers.Print (ArgSpec(args=['input', 'first_n', 'message', 'summarize', 'print_tensor_name', 'print_tensor_type', 'print_tensor_shape', 'print_tensor_lod', 'print_phase'], varargs=None, keywords=None, defaults=(-1, None, 20, True, True, True, True, 'both')), ('document', 'e57b87b4d1f9d4a6c7a3f4e6942dea10'))
paddle.fluid.layers.is_empty (ArgSpec(args=['x', 'cond'], varargs=None, keywords=None, defaults=(None,)), ('document', 'a79576af16e8ce1c6ac61b902b04f10a')) paddle.fluid.layers.is_empty (ArgSpec(args=['x', 'cond'], varargs=None, keywords=None, defaults=(None,)), ('document', 'a79576af16e8ce1c6ac61b902b04f10a'))
paddle.fluid.layers.sigmoid (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '7bd26680989f33301a4a68000d5af4b0')) paddle.fluid.layers.sigmoid (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '2d0fed39c9d28cc19aa496f0dd159fd4'))
paddle.fluid.layers.logsigmoid (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '047c2af83166a69728be73fc44e9ad9f')) paddle.fluid.layers.logsigmoid (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'c33cf66d7d2df3f3dabc5f728c70915d'))
paddle.fluid.layers.exp (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'f6b0cc458acf7ad822a0c26e72fc22a1')) paddle.fluid.layers.exp (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '56a9fcf884b888674ee3c46afc110d62'))
paddle.fluid.layers.tanh (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'a4d7e467c3a6607caab89d53bd5099d2')) paddle.fluid.layers.tanh (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'f34a62d31468fb0308a8ff82dd55ca38'))
paddle.fluid.layers.atan (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '29250d1f3af5144ba039197215df2131')) paddle.fluid.layers.atan (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '4d6ed5129aedf9efc8883541e0d0b9aa'))
paddle.fluid.layers.tanh_shrink (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '1db8f617031c17e60d428f01168d92eb')) paddle.fluid.layers.tanh_shrink (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '50e9750eff90c09b6bd80c20450ec184'))
paddle.fluid.layers.sqrt (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '13892ce3aa521fcabb29260bd65414e9')) paddle.fluid.layers.sqrt (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'a74dec54d52181979d0ea7deb8900280'))
paddle.fluid.layers.rsqrt (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '9648ccd87867053537a54dbf0416ad6d')) paddle.fluid.layers.rsqrt (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '04e19f56984e03f8d7567283c2083b05'))
paddle.fluid.layers.abs (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '18ecb9dc8efbdce519a3a96c94b462e0')) paddle.fluid.layers.abs (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '814b865a4d426cbb6543ee0783d2a5d7'))
paddle.fluid.layers.ceil (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '668ba28052c91056ad055ed058790f1c')) paddle.fluid.layers.ceil (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'ad5da89beacf0e13d1e2ad1434b17ba5'))
paddle.fluid.layers.floor (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'd103f8b661776349ed61087c048994a3')) paddle.fluid.layers.floor (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'ede18954ba13f3337ce09ed04ecf4f20'))
paddle.fluid.layers.cos (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '748bd06996177acfe11fb5b302c24256')) paddle.fluid.layers.cos (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'df7149db3d84538708f35e76c35e8119'))
paddle.fluid.layers.acos (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'afa3db0f45c74da6c1a1c646abc27dee')) paddle.fluid.layers.acos (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'f6d0a48665c9e537584e154ea967fafd'))
paddle.fluid.layers.asin (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '0179b8944cc74610a55b148629287090')) paddle.fluid.layers.asin (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'e0725366c2a1903cbe39cca38f4cba09'))
paddle.fluid.layers.sin (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'b331a771d6d2204c7139c79a9213acf2')) paddle.fluid.layers.sin (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '096c00265a036c6b09e671af39e103cb'))
paddle.fluid.layers.round (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '5df0b9eacbbb0b91f0eb39e37446ec57')) paddle.fluid.layers.round (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '697b326fa2a44be46ab891a5ccc10870'))
paddle.fluid.layers.reciprocal (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '35f89ad821fbdf8a50ad26cd9f31b7cf')) paddle.fluid.layers.reciprocal (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '0e5a40faba795ca1780bcb33097776ce'))
paddle.fluid.layers.square (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'a684ce5a61c2c046aa5639d98aaa3acc')) paddle.fluid.layers.square (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'bff78587bfbeee4ffa8bc2a14f22e121'))
paddle.fluid.layers.softplus (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '76c853f8a013466b7f443ad166e259bd')) paddle.fluid.layers.softplus (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '9ce5e4717328eadf75af94763b3610b7'))
paddle.fluid.layers.softsign (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'e52b23bc455c708d7a26501db4ab8971')) paddle.fluid.layers.softsign (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'c19bc097c549a4f07de92ab8180787b8'))
paddle.fluid.layers.softshrink (ArgSpec(args=['x', 'alpha'], varargs=None, keywords=None, defaults=(None,)), ('document', 'ca05a2a810b78772bfda9f2d0f19ed32')) paddle.fluid.layers.softshrink (ArgSpec(args=['x', 'alpha'], varargs=None, keywords=None, defaults=(None,)), ('document', 'ca05a2a810b78772bfda9f2d0f19ed32'))
paddle.fluid.layers.hard_shrink (ArgSpec(args=['x', 'threshold'], varargs=None, keywords=None, defaults=(None,)), ('document', '386a4103d2884b2f1312ebc1e8ee6486')) paddle.fluid.layers.hard_shrink (ArgSpec(args=['x', 'threshold'], varargs=None, keywords=None, defaults=(None,)), ('document', '386a4103d2884b2f1312ebc1e8ee6486'))
paddle.fluid.layers.cumsum (ArgSpec(args=['x', 'axis', 'exclusive', 'reverse'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', 'c1f2e4c4511da09d5d89c556ea802bd1')) paddle.fluid.layers.cumsum (ArgSpec(args=['x', 'axis', 'exclusive', 'reverse'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', 'c1f2e4c4511da09d5d89c556ea802bd1'))

24
paddle/fluid/operators/activation_op.cc
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@ -176,7 +176,7 @@ $$out = \\log \\frac{1}{1 + e^{-x}}$$
)DOC"; )DOC";
UNUSED constexpr char ExpDoc[] = R"DOC( UNUSED constexpr char ExpDoc[] = R"DOC(
Exp Activation Operator. Exp Operator. Computes exp of x element-wise with a natural number :math:`e` as the base.
$out = e^x$ $out = e^x$
@ -237,7 +237,7 @@ $out = |x|$
)DOC"; )DOC";
UNUSED constexpr char CeilDoc[] = R"DOC( UNUSED constexpr char CeilDoc[] = R"DOC(
Ceil Activation Operator. Ceil Operator. Computes ceil of x element-wise.
$out = \left \lceil x \right \rceil$ $out = \left \lceil x \right \rceil$
@ -251,7 +251,7 @@ $out = \left \lfloor x \right \rfloor$
)DOC"; )DOC";
UNUSED constexpr char CosDoc[] = R"DOC( UNUSED constexpr char CosDoc[] = R"DOC(
Cosine Activation Operator. Cosine Operator. Computes cosine of x element-wise.
$out = cos(x)$ $out = cos(x)$
@ -430,8 +430,12 @@ class HardShrinkOpMaker : public framework::OpProtoAndCheckerMaker {
class BReluOpMaker : public framework::OpProtoAndCheckerMaker { class BReluOpMaker : public framework::OpProtoAndCheckerMaker {
public: public:
void Make() override { void Make() override {
AddInput("X", "Input of BRelu operator"); AddInput("X",
AddOutput("Out", "Output of BRelu operator"); "The input is a multi-dimensional Tensor. The data type is "
"float32, float64.");
AddOutput("Out",
"The output is a multi-dimensional Tensor which has same "
"dimension and data type as the ``X``.");
AddAttr<float>("t_min", "The min marginal value of BRelu") AddAttr<float>("t_min", "The min marginal value of BRelu")
.SetDefault(static_cast<float>(0)); .SetDefault(static_cast<float>(0));
AddAttr<float>("t_max", "The max marginal value of BRelu") AddAttr<float>("t_max", "The max marginal value of BRelu")
@ -439,7 +443,7 @@ class BReluOpMaker : public framework::OpProtoAndCheckerMaker {
AddComment(R"DOC( AddComment(R"DOC(
BRelu Activation Operator. BRelu Activation Operator.
$out = \max(\min(x, t_{min}), t_{max})$ $out = \min(\max(x, t_{min}), t_{max})$
)DOC"); )DOC");
} }
@ -464,8 +468,12 @@ $out = \ln(1 + \exp(\max(\min(x, threshold), -threshold)))$
class ELUOpMaker : public framework::OpProtoAndCheckerMaker { class ELUOpMaker : public framework::OpProtoAndCheckerMaker {
public: public:
void Make() override { void Make() override {
AddInput("X", "Input of ELU operator"); AddInput("X",
AddOutput("Out", "Output of ELU operator"); "The input is a multi-dimensional Tensor. The data type is "
"float32 or float64.");
AddOutput("Out",
"The output is a multi-dimensional Tensor which has same "
"dimension and data type as the ``x``.");
AddAttr<float>("alpha", "The alpha value of ELU").SetDefault(1.0f); AddAttr<float>("alpha", "The alpha value of ELU").SetDefault(1.0f);
AddComment(R"DOC( AddComment(R"DOC(
ELU Activation Operator. ELU Activation Operator.

7
python/paddle/fluid/layers/layer_function_generator.py
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@ -274,19 +274,22 @@ def generate_activation_fn(op_type):
"name(str, optional): The default value is None. Normally there is no need for user to set this property. For more information, please refer to :ref:`api_guide_Name` ." "name(str, optional): The default value is None. Normally there is no need for user to set this property. For more information, please refer to :ref:`api_guide_Name` ."
]) ])
func.__doc__ = func.__doc__ + """ func.__doc__ = func.__doc__ + """
Return type
Variable
Examples: Examples:
.. code-block:: python .. code-block:: python
import paddle.fluid as fluid import paddle.fluid as fluid
import numpy as np import numpy as np
inputs = fluid.layers.data(name="x", shape = [1], dtype='float32') inputs = fluid.data(name="x", shape = [None, 1], dtype='float32')
output = fluid.layers.%s(inputs) output = fluid.layers.%s(inputs)
exe = fluid.Executor(fluid.CPUPlace()) exe = fluid.Executor(fluid.CPUPlace())
exe.run(fluid.default_startup_program()) exe.run(fluid.default_startup_program())
img = np.array([1.0, 1.0, 1.0, 1.0]).astype(np.float32) img = np.array([1.0, 2.0, 3.0, 4.0]).astype(np.float32)
res = exe.run(fluid.default_main_program(), feed={'x':img}, fetch_list=[output]) res = exe.run(fluid.default_main_program(), feed={'x':img}, fetch_list=[output])
print(res) print(res)
""" % op_type """ % op_type

35
python/paddle/fluid/layers/nn.py
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@ -11505,19 +11505,25 @@ def elu(x, alpha=1.0, name=None):
Args: Args:
x(${x_type}): ${x_comment} x(${x_type}): ${x_comment}
alpha(${alpha_type}|1.0): ${alpha_comment} alpha(${alpha_type}|1.0): ${alpha_comment}
name(str|None): A name for this layer(optional). If set None, the layer name(str|None): The default value is None. Normally there is no need for user to set this property.
will be named automatically. For more information, please refer to :ref:`api_guide_Name`.
Returns: Returns:
output(${out_type}): ${out_comment} ${out_type}: ${out_comment}
Examples: Examples:
.. code-block:: python .. code-block:: python
import paddle.fluid as fluid import paddle.fluid as fluid
x = fluid.layers.data(name="x", shape=[3,10,32,32], dtype="float32") import numpy as np
y = fluid.layers.elu(x, alpha=0.2)
input_elu = np.array([[-1,6],[1,15.6]])
with fluid.dygraph.guard():
x = fluid.dygraph.to_variable(input_elu)
y = fluid.layers.elu(x, alpha=0.2)
print(y.numpy())
# [[-0.12642411 6. ]
# [ 1. 15.6 ]]
""" """
helper = LayerHelper('elu', **locals()) helper = LayerHelper('elu', **locals())
if not isinstance(x, Variable): if not isinstance(x, Variable):
@ -11852,18 +11858,25 @@ def brelu(x, t_min=0.0, t_max=24.0, name=None):
x(${x_type}): ${x_comment} x(${x_type}): ${x_comment}
t_min(${t_min_type}|0.0): ${t_min_comment} t_min(${t_min_type}|0.0): ${t_min_comment}
t_max(${t_max_type}|24.0): ${t_max_comment} t_max(${t_max_type}|24.0): ${t_max_comment}
name(str|None): A name for this layer(optional). If set None, the layer name(str|None): The default value is None. Normally there is no need for user to set this property.
will be named automatically. For more information, please refer to :ref:`api_guide_Name`.
Returns: Returns:
output(${out_type}): ${out_comment} ${out_type}: ${out_comment}
Examples: Examples:
.. code-block:: python .. code-block:: python
import paddle.fluid as fluid import paddle.fluid as fluid
x = fluid.layers.data(name="x", shape=[2,3,16,16], dtype="float32") import numpy as np
y = fluid.layers.brelu(x, t_min=1.0, t_max=20.0)
input_brelu = np.array([[-1,6],[1,15.6]])
with fluid.dygraph.guard():
x = fluid.dygraph.to_variable(input_brelu)
y = fluid.layers.brelu(x, t_min=1.0, t_max=10.0)
print(y.numpy())
#[[ 1. 6.]
#[ 1. 10.]]
""" """
helper = LayerHelper('brelu', **locals()) helper = LayerHelper('brelu', **locals())
out = helper.create_variable_for_type_inference(dtype=x.dtype) out = helper.create_variable_for_type_inference(dtype=x.dtype)

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