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Fix document of APIs, test=develop, test=document_fix (#20314)

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revert-20712-fix_depthwise_conv
huangjun12 6 years ago committed by whs
parent fa43e80e19
commit b347ca084e
3 changed files with 192 additions and 121 deletions
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10
paddle/fluid/API.spec
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@ -201,11 +201,11 @@ paddle.fluid.layers.squeeze (ArgSpec(args=['input', 'axes', 'name'], varargs=Non
paddle.fluid.layers.unsqueeze (ArgSpec(args=['input', 'axes', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'b9bd3129d36a70e7c4385df51ff71c62'))
paddle.fluid.layers.lod_reset (ArgSpec(args=['x', 'y', 'target_lod'], varargs=None, keywords=None, defaults=(None, None)), ('document', '74498d37dd622ac472cb36887fce09ea'))
paddle.fluid.layers.lod_append (ArgSpec(args=['x', 'level'], varargs=None, keywords=None, defaults=None), ('document', '37663c7c179e920838a250ea0e28d909'))
paddle.fluid.layers.lrn (ArgSpec(args=['input', 'n', 'k', 'alpha', 'beta', 'name'], varargs=None, keywords=None, defaults=(5, 1.0, 0.0001, 0.75, None)), ('document', '73d297256da8954617996958d26ee93d'))
paddle.fluid.layers.lrn (ArgSpec(args=['input', 'n', 'k', 'alpha', 'beta', 'name'], varargs=None, keywords=None, defaults=(5, 1.0, 0.0001, 0.75, None)), ('document', 'fa565b65fb98d3ca82361c79f41b06b2'))
paddle.fluid.layers.pad (ArgSpec(args=['x', 'paddings', 'pad_value', 'name'], varargs=None, keywords=None, defaults=(0.0, None)), ('document', '36b6e58678956585e5b30aa3de123a60'))
paddle.fluid.layers.pad_constant_like (ArgSpec(args=['x', 'y', 'pad_value', 'name'], varargs=None, keywords=None, defaults=(0.0, None)), ('document', '95aa1972983f30fe9b5a3713e523e20f'))
paddle.fluid.layers.label_smooth (ArgSpec(args=['label', 'prior_dist', 'epsilon', 'dtype', 'name'], varargs=None, keywords=None, defaults=(None, 0.1, 'float32', None)), ('document', '214f1dfbe95a628600bbe99e836319cf'))
paddle.fluid.layers.roi_pool (ArgSpec(args=['input', 'rois', 'pooled_height', 'pooled_width', 'spatial_scale'], varargs=None, keywords=None, defaults=(1, 1, 1.0)), ('document', '49368d724023a66b41b0071be41c0ba5'))
paddle.fluid.layers.roi_pool (ArgSpec(args=['input', 'rois', 'pooled_height', 'pooled_width', 'spatial_scale'], varargs=None, keywords=None, defaults=(1, 1, 1.0)), ('document', '6fc9bae94518bbf3e1a9e479f38f6537'))
paddle.fluid.layers.roi_align (ArgSpec(args=['input', 'rois', 'pooled_height', 'pooled_width', 'spatial_scale', 'sampling_ratio', 'name'], varargs=None, keywords=None, defaults=(1, 1, 1.0, -1, None)), ('document', '3885fd76e122ac0563fa8369bcab7363'))
paddle.fluid.layers.dice_loss (ArgSpec(args=['input', 'label', 'epsilon'], varargs=None, keywords=None, defaults=(1e-05,)), ('document', '7e8e4bf1f0f8612961ed113e8af8f0c5'))
paddle.fluid.layers.image_resize (ArgSpec(args=['input', 'out_shape', 'scale', 'name', 'resample', 'actual_shape', 'align_corners', 'align_mode', 'data_format'], varargs=None, keywords=None, defaults=(None, None, None, 'BILINEAR', None, True, 1, 'NCHW')), ('document', 'd29d829607b5ff12924197a3ba296c89'))
@ -297,7 +297,7 @@ paddle.fluid.layers.py_func (ArgSpec(args=['func', 'x', 'out', 'backward_func',
paddle.fluid.layers.psroi_pool (ArgSpec(args=['input', 'rois', 'output_channels', 'spatial_scale', 'pooled_height', 'pooled_width', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '42d5155374f69786300d90d751956998'))
paddle.fluid.layers.prroi_pool (ArgSpec(args=['input', 'rois', 'output_channels', 'spatial_scale', 'pooled_height', 'pooled_width', 'name'], varargs=None, keywords=None, defaults=(1.0, 1, 1, None)), ('document', '454c7ea8c73313dd41513929d7526303'))
paddle.fluid.layers.teacher_student_sigmoid_loss (ArgSpec(args=['input', 'label', 'soft_max_up_bound', 'soft_max_lower_bound'], varargs=None, keywords=None, defaults=(15.0, -15.0)), ('document', 'b0e07aa41caae04b07a8e8217cc96020'))
paddle.fluid.layers.huber_loss (ArgSpec(args=['input', 'label', 'delta'], varargs=None, keywords=None, defaults=None), ('document', '11bb8e62cc9256958eff3991fe4834da'))
paddle.fluid.layers.huber_loss (ArgSpec(args=['input', 'label', 'delta'], varargs=None, keywords=None, defaults=None), ('document', '9d93ee81f7a3e526d68bb280bc695d6c'))
paddle.fluid.layers.kldiv_loss (ArgSpec(args=['x', 'target', 'reduction', 'name'], varargs=None, keywords=None, defaults=('mean', None)), ('document', '18bc95c62d3300456c3c7da5278b47bb'))
paddle.fluid.layers.npair_loss (ArgSpec(args=['anchor', 'positive', 'labels', 'l2_reg'], varargs=None, keywords=None, defaults=(0.002,)), ('document', '3828c4bd81c25af0ab955f52d453c587'))
paddle.fluid.layers.pixel_shuffle (ArgSpec(args=['x', 'upscale_factor'], varargs=None, keywords=None, defaults=None), ('document', '7e5cac851fd9bad344230e1044b6a565'))
@ -310,7 +310,7 @@ paddle.fluid.layers.unfold (ArgSpec(args=['x', 'kernel_sizes', 'strides', 'paddi
paddle.fluid.layers.deformable_roi_pooling (ArgSpec(args=['input', 'rois', 'trans', 'no_trans', 'spatial_scale', 'group_size', 'pooled_height', 'pooled_width', 'part_size', 'sample_per_part', 'trans_std', 'position_sensitive', 'name'], varargs=None, keywords=None, defaults=(False, 1.0, [1, 1], 1, 1, None, 1, 0.1, False, None)), ('document', 'e0e7bf35da2287efb015546f1b8350df'))
paddle.fluid.layers.filter_by_instag (ArgSpec(args=['ins', 'ins_tag', 'filter_tag', 'is_lod'], varargs=None, keywords=None, defaults=None), ('document', '7703a2088af8de4128b143ff1164ca4a'))
paddle.fluid.layers.shard_index (ArgSpec(args=['input', 'index_num', 'nshards', 'shard_id', 'ignore_value'], varargs=None, keywords=None, defaults=(-1,)), ('document', '3c6b30e9cd57b38d4a5fa1ade887f779'))
paddle.fluid.layers.hard_swish (ArgSpec(args=['x', 'threshold', 'scale', 'offset', 'name'], varargs=None, keywords=None, defaults=(6.0, 6.0, 3.0, None)), ('document', '6a5152a7015c62cb8278fc24cb456459'))
paddle.fluid.layers.hard_swish (ArgSpec(args=['x', 'threshold', 'scale', 'offset', 'name'], varargs=None, keywords=None, defaults=(6.0, 6.0, 3.0, None)), ('document', 'bd763b9ca99239d624c3cb4626e3627a'))
paddle.fluid.layers.mse_loss (ArgSpec(args=['input', 'label'], varargs=None, keywords=None, defaults=None), ('document', 'd9ede6469288636e1b3233b461a165c9'))
paddle.fluid.layers.uniform_random (ArgSpec(args=['shape', 'dtype', 'min', 'max', 'seed'], varargs=None, keywords=None, defaults=('float32', -1.0, 1.0, 0)), ('document', '126ede8ce0e751244b1b54cd359c89d7'))
paddle.fluid.layers.data (ArgSpec(args=['name', 'shape', 'append_batch_size', 'dtype', 'lod_level', 'type', 'stop_gradient'], varargs=None, keywords=None, defaults=(True, 'float32', 0, VarType.LOD_TENSOR, True)), ('document', '9d7806e31bdf727c1a23b8782a09b545'))
@ -447,7 +447,7 @@ paddle.fluid.layers.polynomial_decay (ArgSpec(args=['learning_rate', 'decay_step
paddle.fluid.layers.piecewise_decay (ArgSpec(args=['boundaries', 'values'], varargs=None, keywords=None, defaults=None), ('document', 'd9f654117542c6b702963dda107a247f'))
paddle.fluid.layers.noam_decay (ArgSpec(args=['d_model', 'warmup_steps'], varargs=None, keywords=None, defaults=None), ('document', 'fd57228fb76195e66bbcc8d8e42c494d'))
paddle.fluid.layers.cosine_decay (ArgSpec(args=['learning_rate', 'step_each_epoch', 'epochs'], varargs=None, keywords=None, defaults=None), ('document', '1062e487dd3b50a6e58b5703b4f594c9'))
paddle.fluid.layers.linear_lr_warmup (ArgSpec(args=['learning_rate', 'warmup_steps', 'start_lr', 'end_lr'], varargs=None, keywords=None, defaults=None), ('document', 'dc7292c456847ba41cfd318e9f7f4363'))
paddle.fluid.layers.linear_lr_warmup (ArgSpec(args=['learning_rate', 'warmup_steps', 'start_lr', 'end_lr'], varargs=None, keywords=None, defaults=None), ('document', 'bfb548a508c34998c969f19eb47ee473'))
paddle.fluid.layers.Uniform ('paddle.fluid.layers.distributions.Uniform', ('document', '9b1a9ebdd8ae18bf562486611ed74e59'))
paddle.fluid.layers.Uniform.__init__ (ArgSpec(args=['self', 'low', 'high'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
paddle.fluid.layers.Uniform.entropy (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', 'cde9f1980a2be7939798b32ec8cd59e1'))

78
python/paddle/fluid/layers/learning_rate_scheduler.py
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@ -440,37 +440,59 @@ def cosine_decay(learning_rate, step_each_epoch, epochs):
def linear_lr_warmup(learning_rate, warmup_steps, start_lr, end_lr):
"""
Applies linear learning rate warmup before the normal learning rate
scheduling.
.. code-block:: python
if global_step < warmup_steps:
linear_step = end_lr - start_lr
lr = start_lr + linear_step * (global_step / warmup_steps)
This operator use the linear learning rate warm up strategy to adjust the learning rate preliminarily before the normal learning rate scheduling.
For more information, please refer to `Bag of Tricks for Image Classification with Convolutional Neural Networks <https://arxiv.org/abs/1812.01187>`_
When global_step < warmup_steps, learning rate is updated as:
.. code-block:: text
linear_step = end_lr - start_lr
lr = start_lr + linear_step * (global_step / warmup_steps)
where start_lr is the initial learning rate, and end_lr is the final learning rate;
When global_step >= warmup_steps, learning rate is updated as:
.. code-block:: text
lr = learning_rate
where lr is the learning_rate after warm-up.
Args:
learning_rate (float | Variable): A float value or Variable.
warmup_steps (int): The warmup steps.
start_lr (float): The start learning rate of warmup.
end_lr (float): The end learning rate of warmup.
learning_rate (Variable|float): Learning_rate after warm-up, it could be 1D-Tensor or single value with the data type of float32.
warmup_steps (int): Steps for warm up.
start_lr (float): Initial learning rate of warm up.
end_lr (float): Final learning rate of warm up.
Returns:
The decayed learning rate in warmup period.
Variable: Warm-up learning rate with the same data type as learning_rate.
Examples:
.. code-block:: python
import paddle.fluid as fluid
boundaries = [100, 200]
lr_steps = [0.1, 0.01, 0.001]
warmup_steps = 50
start_lr = 1. / 3.
end_lr = 0.1
decayed_lr = fluid.layers.linear_lr_warmup(
fluid.layers.piecewise_decay(boundaries, lr_steps),
warmup_steps, start_lr, end_lr)
.. code-block:: python
import paddle.fluid as fluid
boundaries = [100, 200]
lr_steps = [0.1, 0.01, 0.001]
learning_rate = fluid.layers.piecewise_decay(boundaries, lr_steps) #case1, 1D-Tensor
#learning_rate = 0.1 #case2, single-value
warmup_steps = 50
start_lr = 1. / 3.
end_lr = 0.1
decayed_lr = fluid.layers.linear_lr_warmup(learning_rate,
warmup_steps, start_lr, end_lr)
place = fluid.CPUPlace()
exe = fluid.Executor(place)
exe.run(fluid.default_startup_program())
out, = exe.run(fetch_list=[decayed_lr.name])
print(out)
# case1: [0.33333334]
# case2: [0.33333334]
"""
dtype = 'float32'
if isinstance(learning_rate, Variable):

225
python/paddle/fluid/layers/nn.py
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