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[DOC][PYTHON] Fix api docs, test=develop, test=document_preview (#17629)

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* [DOC] Fix api docs, test=develop, test=document_preview

* [DOC] Fix api annotation: fluid.layers.tensor_array_to_tensor. test=develop, test=document_preview

* test=develop, test=document_preview

update MD5 of tensor_array_to_tensor
dependabot/pip/python/requests-2.20.0
Shuai Yuan 6 years ago committed by GitHub
parent 058f1f1e1b
commit 41f1186c6b
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GPG Key ID: 4AEE18F83AFDEB23
4 changed files with 55 additions and 12 deletions
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8
paddle/fluid/API.spec
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@ -123,7 +123,7 @@ paddle.fluid.layers.matmul (ArgSpec(args=['x', 'y', 'transpose_x', 'transpose_y'
paddle.fluid.layers.topk (ArgSpec(args=['input', 'k', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '2a1e9ea041ff4d6a9948bb8d03b743ea'))
paddle.fluid.layers.warpctc (ArgSpec(args=['input', 'label', 'blank', 'norm_by_times', 'use_cudnn'], varargs=None, keywords=None, defaults=(0, False, False)), ('document', '4aa9df890b47eb67d5442f04aaf9eeec'))
paddle.fluid.layers.sequence_reshape (ArgSpec(args=['input', 'new_dim'], varargs=None, keywords=None, defaults=None), ('document', 'f568714a876425004aca4ea2d4a27701'))
paddle.fluid.layers.transpose (ArgSpec(args=['x', 'perm', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'a1feac48b843d679db82312dc85885f4'))
paddle.fluid.layers.transpose (ArgSpec(args=['x', 'perm', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '8e72db173d4c082e27cb11f31d8c9bfa'))
paddle.fluid.layers.im2sequence (ArgSpec(args=['input', 'filter_size', 'stride', 'padding', 'input_image_size', 'out_stride', 'name'], varargs=None, keywords=None, defaults=(1, 1, 0, None, 1, None)), ('document', '33134416fc27dd65a767e5f15116ee16'))
paddle.fluid.layers.nce (ArgSpec(args=['input', 'label', 'num_total_classes', 'sample_weight', 'param_attr', 'bias_attr', 'num_neg_samples', 'name', 'sampler', 'custom_dist', 'seed', 'is_sparse'], varargs=None, keywords=None, defaults=(None, None, None, None, None, 'uniform', None, 0, False)), ('document', '32b3c442da0f3df682b5fcac10468116'))
paddle.fluid.layers.sampled_softmax_with_cross_entropy (ArgSpec(args=['logits', 'label', 'num_samples', 'num_true', 'remove_accidental_hits', 'use_customized_samples', 'customized_samples', 'customized_probabilities', 'seed'], varargs=None, keywords=None, defaults=(1, True, False, None, None, 0)), ('document', '5db30b8a74e8c93687943a3e8d221da0'))
@ -140,7 +140,7 @@ paddle.fluid.layers.one_hot (ArgSpec(args=['input', 'depth'], varargs=None, keyw
paddle.fluid.layers.autoincreased_step_counter (ArgSpec(args=['counter_name', 'begin', 'step'], varargs=None, keywords=None, defaults=(None, 1, 1)), ('document', '67afefa80b6cc38801bd5b631fed8a4a'))
paddle.fluid.layers.reshape (ArgSpec(args=['x', 'shape', 'actual_shape', 'act', 'inplace', 'name'], varargs=None, keywords=None, defaults=(None, None, False, None)), ('document', '323c019f257e55ddea4a824a362de62f'))
paddle.fluid.layers.squeeze (ArgSpec(args=['input', 'axes', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '06588973f613e9dcd592724322864589'))
paddle.fluid.layers.unsqueeze (ArgSpec(args=['input', 'axes', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'bbd62da391b1df984a1909d069a759b2'))
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', 'f122194c562bd674f6ecdccf33785f99'))
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', '330241f0bc57e9d16973ec322a6aef71'))
paddle.fluid.layers.pad (ArgSpec(args=['x', 'paddings', 'pad_value', 'name'], varargs=None, keywords=None, defaults=(0.0, None)), ('document', '2f189f8ef61f1c23779e1593b78755c0'))
@ -178,7 +178,7 @@ paddle.fluid.layers.flatten (ArgSpec(args=['x', 'axis', 'name'], varargs=None, k
paddle.fluid.layers.sequence_mask (ArgSpec(args=['x', 'maxlen', 'dtype', 'name'], varargs=None, keywords=None, defaults=(None, 'int64', None)), ('document', '767cea598dee8e2b94f04110fa6b7e67'))
paddle.fluid.layers.stack (ArgSpec(args=['x', 'axis'], varargs=None, keywords=None, defaults=(0,)), ('document', '43a9fef72d45df3bc58f52b93cdb61cb'))
paddle.fluid.layers.pad2d (ArgSpec(args=['input', 'paddings', 'mode', 'pad_value', 'data_format', 'name'], varargs=None, keywords=None, defaults=([0, 0, 0, 0], 'constant', 0.0, 'NCHW', None)), ('document', '3f3abdb795a5c2aad8c2312249551ce5'))
paddle.fluid.layers.unstack (ArgSpec(args=['x', 'axis', 'num'], varargs=None, keywords=None, defaults=(0, None)), ('document', '98eb9d633116efcfc6f90c114bd44fd6'))
paddle.fluid.layers.unstack (ArgSpec(args=['x', 'axis', 'num'], varargs=None, keywords=None, defaults=(0, None)), ('document', 'b0c4ca08d4eb295189e1b107c920d093'))
paddle.fluid.layers.sequence_enumerate (ArgSpec(args=['input', 'win_size', 'pad_value', 'name'], varargs=None, keywords=None, defaults=(0, None)), ('document', '2e49e97069beb57ee89d54ed088ae2da'))
paddle.fluid.layers.expand (ArgSpec(args=['x', 'expand_times', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '117d3607d1ffa0571835bbaebc7857ff'))
paddle.fluid.layers.sequence_concat (ArgSpec(args=['input', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'b992616c1afbd6b0c2a897ac23036381'))
@ -255,7 +255,7 @@ paddle.fluid.layers.create_tensor (ArgSpec(args=['dtype', 'name', 'persistable']
paddle.fluid.layers.create_parameter (ArgSpec(args=['shape', 'dtype', 'name', 'attr', 'is_bias', 'default_initializer'], varargs=None, keywords=None, defaults=(None, None, False, None)), ('document', 'b6fe28cffff32d15e45c411bcf815cb7'))
paddle.fluid.layers.create_global_var (ArgSpec(args=['shape', 'value', 'dtype', 'persistable', 'force_cpu', 'name'], varargs=None, keywords=None, defaults=(False, False, None)), ('document', '90eb79e0d1261ec2bac7c775ee4f459b'))
paddle.fluid.layers.cast (ArgSpec(args=['x', 'dtype'], varargs=None, keywords=None, defaults=None), ('document', '992eb42590fc1c380841a6db72ce78b3'))
paddle.fluid.layers.tensor_array_to_tensor (ArgSpec(args=['input', 'axis', 'name'], varargs=None, keywords=None, defaults=(1, None)), ('document', 'b12717d3d4567e6119589f7f655b0cbb'))
paddle.fluid.layers.tensor_array_to_tensor (ArgSpec(args=['input', 'axis', 'name'], varargs=None, keywords=None, defaults=(1, None)), ('document', '764c095ba4562ae740f979e970152d6e'))
paddle.fluid.layers.concat (ArgSpec(args=['input', 'axis', 'name'], varargs=None, keywords=None, defaults=(0, None)), ('document', 'f9e905b48123914c78055a45fe23106a'))
paddle.fluid.layers.sums (ArgSpec(args=['input', 'out'], varargs=None, keywords=None, defaults=(None,)), ('document', '5df743d578638cd2bbb9369499b44af4'))
paddle.fluid.layers.assign (ArgSpec(args=['input', 'output'], varargs=None, keywords=None, defaults=(None,)), ('document', 'b690184f3537df5501e4d9d8f31152a5'))

41
python/paddle/fluid/clip.py
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@ -55,7 +55,23 @@ class ErrorClipByValue(BaseErrorClipAttr):
Examples:
.. code-block:: python
var = fluid.framework.Variable(..., error_clip=ErrorClipByValue(max=5.0), ...)
import paddle.fluid as fluid
BATCH_SIZE = 128
CLIP_MAX = 2e-6
CLIP_MIN = -1e-6
prog = fluid.framework.Program()
with fluid.program_guard(main_program=prog):
image = fluid.layers.data(name='x', shape=[784], dtype='float32')
hidden1 = fluid.layers.fc(input=image, size=128, act='relu')
hidden2 = fluid.layers.fc(input=hidden1, size=64, act='relu')
predict = fluid.layers.fc(input=hidden2, size=10, act='softmax')
label = fluid.layers.data(name='y', shape=[1], dtype='int64')
cost = fluid.layers.cross_entropy(input=predict, label=label)
avg_cost = fluid.layers.mean(cost)
prog_clip = prog.clone()
prog_clip.block(0).var(hidden1.name)._set_error_clip(
fluid.clip.ErrorClipByValue(
max=CLIP_MAX, min=CLIP_MIN)
"""
def __init__(self, max, min=None):
@ -140,7 +156,8 @@ class GradientClipByValue(BaseGradientClipAttr):
learning_rate=1.0,
regularizer=fluid.regularizer.L1Decay(1.0),
trainable=True,
clip=fluid.clip.GradientClipByValue(1.0, -1.0))
gradient_clip=fluid.clip.GradientClipByValue(-1.0, 1.0))
x = fluid.layers.data(name='x', shape=[10], dtype='float32')
y_predict = fluid.layers.fc(input=x, size=1, param_attr=w_param_attrs)
"""
@ -186,12 +203,14 @@ class GradientClipByNorm(BaseGradientClipAttr):
Examples:
.. code-block:: python
w_param_attrs = flui.ParamAttr(name=None,
import paddle.fluid as fluid
w_param_attrs = fluid.ParamAttr(name=None,
initializer=fluid.initializer.UniformInitializer(low=-1.0, high=1.0, seed=0),
learning_rate=1.0,
regularizer=fluid.regularizer.L1Decay(1.0),
trainable=True,
clip=fluid.clip.GradientClipByNorm(clip_norm=2.0))
gradient_clip=fluid.clip.GradientClipByNorm(clip_norm=2.0))
x = fluid.layers.data(name='x', shape=[10], dtype='float32')
y_predict = fluid.layers.fc(input=x, size=1, param_attr=w_param_attrs)
"""
@ -240,6 +259,20 @@ class GradientClipByGlobalNorm(BaseGradientClipAttr):
Examples:
.. code-block:: python
import paddle.fluid as fluid
prog = fluid.framework.Program()
startup_program = fluid.framework.Program()
with fluid.program_guard(
main_program=prog, startup_program=startup_program):
image = fluid.layers.data(name='x', shape=[784], dtype='float32')
label = fluid.layers.data(name='y', shape=[1], dtype='int64')
hidden1 = fluid.layers.fc(input=image, size=128, act='relu')
hidden2 = fluid.layers.fc(input=hidden1, size=64, act='relu')
predict = fluid.layers.fc(input=hidden2, size=10, act='softmax')
cost = fluid.layers.cross_entropy(input=predict, label=label)
avg_cost = fluid.layers.mean(cost)
prog_clip = prog.clone()
avg_cost_clip = prog_clip.block(0).var(avg_cost.name)
p_g_clip = fluid.backward.append_backward(loss=avg_cost_clip)
with fluid.program_guard(main_program=prog_clip):

14
python/paddle/fluid/layers/nn.py
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@ -5935,9 +5935,10 @@ def transpose(x, perm, name=None):
# use append_batch_size=False to avoid prepending extra
# batch size in shape
import paddle.fluid as fluid
x = fluid.layers.data(name='x', shape=[5, 10, 15],
dtype='float32', append_batch_size=False)
x_transposed = layers.transpose(x, perm=[1, 0, 2])
x_transposed = fluid.layers.transpose(x, perm=[1, 0, 2])
"""
if len(perm) != len(x.shape):
@ -6780,8 +6781,9 @@ def unsqueeze(input, axes, name=None):
Examples:
.. code-block:: python
x = layers.data(name='x', shape=[5, 10])
y = layers.unsequeeze(input=x, axes=[1])
import paddle.fluid as fluid
x = fluid.layers.data(name='x', shape=[5, 10])
y = fluid.layers.unsqueeze(input=x, axes=[1])
"""
helper = LayerHelper("unsqueeze", **locals())
out = helper.create_variable_for_type_inference(dtype=input.dtype)
@ -9203,6 +9205,12 @@ def unstack(x, axis=0, num=None):
Returns:
list(Variable): The unstacked variables.
Examples:
.. code-block:: python
import paddle.fluid as fluid
x = fluid.layers.data(name='x', shape=[5, 10], dtype='float32')
y = fluid.layers.unstack(x, axis=1)
"""
helper = LayerHelper('unstack', **locals())

4
python/paddle/fluid/layers/tensor.py
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@ -246,7 +246,9 @@ def tensor_array_to_tensor(input, axis=1, name=None):
Examples:
.. code-block:: python
output, output_index = fluid.layers.tensor_array_to_tensor(input=tensor_array)
import paddle.fluid as fluid
tensor_array = fluid.layers.create_parameter(shape=[784, 200], dtype='float32')
output, output_index = fluid.layers.tensor_array_to_tensor(input=tensor_array)
"""
helper = LayerHelper('tensor_array_to_tensor', **locals())
out = helper.create_variable_for_type_inference(dtype=helper.input_dtype())

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