diff --git a/develop/doc/_sources/api/v2/config/layer.rst.txt b/develop/doc/_sources/api/v2/config/layer.rst.txt index 05817ec85455ac58566e90956a54cb86541f8488..2a02baf17ba0d1119a8d222024616ef8ae33f8d5 100644 --- a/develop/doc/_sources/api/v2/config/layer.rst.txt +++ b/develop/doc/_sources/api/v2/config/layer.rst.txt @@ -11,8 +11,7 @@ Data layer data ---- -.. automodule:: paddle.v2.layer - :members: data +.. autoclass:: paddle.v2.layer.data :noindex: Fully Connected Layers @@ -22,14 +21,12 @@ Fully Connected Layers fc -- -.. automodule:: paddle.v2.layer - :members: fc +.. autoclass:: paddle.v2.layer.fc :noindex: selective_fc ------------ -.. automodule:: paddle.v2.layer - :members: selective_fc +.. autoclass:: paddle.v2.layer.selective_fc :noindex: Conv Layers @@ -37,34 +34,29 @@ Conv Layers conv_operator ------------- -.. automodule:: paddle.v2.layer - :members: conv_operator +.. autoclass:: paddle.v2.layer.conv_operator :noindex: conv_projection --------------- -.. automodule:: paddle.v2.layer - :members: conv_projection +.. autoclass:: paddle.v2.layer.conv_projection :noindex: conv_shift ---------- -.. automodule:: paddle.v2.layer - :members: conv_shift +.. autoclass:: paddle.v2.layer.conv_shift :noindex: img_conv -------- -.. automodule:: paddle.v2.layer - :members: img_conv +.. autoclass:: paddle.v2.layer.img_conv :noindex: .. _api_v2.layer_context_projection: context_projection ------------------ -.. automodule:: paddle.v2.layer - :members: context_projection +.. autoclass:: paddle.v2.layer.context_projection :noindex: Image Pooling Layer @@ -72,20 +64,17 @@ Image Pooling Layer img_pool -------- -.. automodule:: paddle.v2.layer - :members: img_pool +.. autoclass:: paddle.v2.layer.img_pool :noindex: spp --- -.. automodule:: paddle.v2.layer - :members: spp +.. autoclass:: paddle.v2.layer.spp :noindex: maxout ------ -.. automodule:: paddle.v2.layer - :members: maxout +.. autoclass:: paddle.v2.layer.maxout :noindex: Norm Layer @@ -93,26 +82,22 @@ Norm Layer img_cmrnorm ----------- -.. automodule:: paddle.v2.layer - :members: img_cmrnorm +.. autoclass:: paddle.v2.layer.img_cmrnorm :noindex: batch_norm ---------- -.. automodule:: paddle.v2.layer - :members: batch_norm +.. autoclass:: paddle.v2.layer.batch_norm :noindex: sum_to_one_norm --------------- -.. automodule:: paddle.v2.layer - :members: sum_to_one_norm +.. autoclass:: paddle.v2.layer.sum_to_one_norm :noindex: cross_channel_norm ------------------ -.. automodule:: paddle.v2.layer - :members: cross_channel_norm +.. autoclass:: paddle.v2.layer.cross_channel_norm :noindex: Recurrent Layers @@ -120,20 +105,17 @@ Recurrent Layers recurrent --------- -.. automodule:: paddle.v2.layer - :members: recurrent +.. autoclass:: paddle.v2.layer.recurrent :noindex: lstmemory --------- -.. automodule:: paddle.v2.layer - :members: lstmemory +.. autoclass:: paddle.v2.layer.lstmemory :noindex: grumemory --------- -.. automodule:: paddle.v2.layer - :members: grumemory +.. autoclass:: paddle.v2.layer.grumemory :noindex: Recurrent Layer Group @@ -141,38 +123,32 @@ Recurrent Layer Group memory ------ -.. automodule:: paddle.v2.layer - :members: memory +.. autoclass:: paddle.v2.layer.memory :noindex: recurrent_group --------------- -.. automodule:: paddle.v2.layer - :members: recurrent_group +.. autoclass:: paddle.v2.layer.recurrent_group :noindex: lstm_step --------- -.. automodule:: paddle.v2.layer - :members: lstm_step +.. autoclass:: paddle.v2.layer.lstm_step :noindex: gru_step -------- -.. automodule:: paddle.v2.layer - :members: gru_step +.. autoclass:: paddle.v2.layer.gru_step :noindex: beam_search ------------ -.. automodule:: paddle.v2.layer - :members: beam_search +.. autoclass:: paddle.v2.layer.beam_search :noindex: get_output ---------- -.. automodule:: paddle.v2.layer - :members: get_output +.. autoclass:: paddle.v2.layer.get_output :noindex: Mixed Layer @@ -182,59 +158,50 @@ Mixed Layer mixed ----- -.. automodule:: paddle.v2.layer - :members: mixed +.. autoclass:: paddle.v2.layer.mixed :noindex: .. _api_v2.layer_embedding: embedding --------- -.. automodule:: paddle.v2.layer - :members: embedding +.. autoclass:: paddle.v2.layer.embedding :noindex: scaling_projection ------------------ -.. automodule:: paddle.v2.layer - :members: scaling_projection +.. autoclass:: paddle.v2.layer.scaling_projection :noindex: dotmul_projection ----------------- -.. automodule:: paddle.v2.layer - :members: dotmul_projection +.. autoclass:: paddle.v2.layer.dotmul_projection :noindex: dotmul_operator --------------- -.. automodule:: paddle.v2.layer - :members: dotmul_operator +.. autoclass:: paddle.v2.layer.dotmul_operator :noindex: full_matrix_projection ---------------------- -.. automodule:: paddle.v2.layer - :members: full_matrix_projection +.. autoclass:: paddle.v2.layer.full_matrix_projection :noindex: identity_projection ------------------- -.. automodule:: paddle.v2.layer - :members: identity_projection +.. autoclass:: paddle.v2.layer.identity_projection :noindex: table_projection ---------------- -.. automodule:: paddle.v2.layer - :members: table_projection +.. autoclass:: paddle.v2.layer.table_projection :noindex: trans_full_matrix_projection ---------------------------- -.. automodule:: paddle.v2.layer - :members: trans_full_matrix_projection +.. autoclass:: paddle.v2.layer.trans_full_matrix_projection :noindex: Aggregate Layers @@ -244,36 +211,31 @@ Aggregate Layers pooling ------- -.. automodule:: paddle.v2.layer - :members: pooling +.. autoclass:: paddle.v2.layer.pooling :noindex: .. _api_v2.layer_last_seq: last_seq -------- -.. automodule:: paddle.v2.layer - :members: last_seq +.. autoclass:: paddle.v2.layer.last_seq :noindex: .. _api_v2.layer_first_seq: first_seq --------- -.. automodule:: paddle.v2.layer - :members: first_seq +.. autoclass:: paddle.v2.layer.first_seq :noindex: concat ------ -.. automodule:: paddle.v2.layer - :members: concat +.. autoclass:: paddle.v2.layer.concat :noindex: seq_concat ---------- -.. automodule:: paddle.v2.layer - :members: seq_concat +.. autoclass:: paddle.v2.layer.seq_concat :noindex: Reshaping Layers @@ -281,34 +243,29 @@ Reshaping Layers block_expand ------------ -.. automodule:: paddle.v2.layer - :members: block_expand +.. autoclass:: paddle.v2.layer.block_expand :noindex: .. _api_v2.layer_expand: expand ------ -.. automodule:: paddle.v2.layer - :members: expand +.. autoclass:: paddle.v2.layer.expand :noindex: repeat ------ -.. automodule:: paddle.v2.layer - :members: repeat +.. autoclass:: paddle.v2.layer.repeat :noindex: rotate ------ -.. automodule:: paddle.v2.layer - :members: rotate +.. autoclass:: paddle.v2.layer.rotate :noindex: seq_reshape ----------- -.. automodule:: paddle.v2.layer - :members: seq_reshape +.. autoclass:: paddle.v2.layer.seq_reshape :noindex: Math Layers @@ -316,64 +273,54 @@ Math Layers addto ----- -.. automodule:: paddle.v2.layer - :members: addto +.. autoclass:: paddle.v2.layer.addto :noindex: linear_comb ----------- -.. automodule:: paddle.v2.layer - :members: linear_comb +.. autoclass:: paddle.v2.layer.linear_comb :noindex: interpolation ------------- -.. automodule:: paddle.v2.layer - :members: interpolation +.. autoclass:: paddle.v2.layer.interpolation :noindex: bilinear_interp --------------- -.. automodule:: paddle.v2.layer - :members: bilinear_interp +.. autoclass:: paddle.v2.layer.bilinear_interp :noindex: power ----- -.. automodule:: paddle.v2.layer - :members: power +.. autoclass:: paddle.v2.layer.power :noindex: scaling ------- -.. automodule:: paddle.v2.layer - :members: scaling +.. autoclass:: paddle.v2.layer.scaling :noindex: slope_intercept --------------- -.. automodule:: paddle.v2.layer - :members: slope_intercept +.. autoclass:: paddle.v2.layer.slope_intercept :noindex: tensor ------ -.. automodule:: paddle.v2.layer - :members: tensor +.. autoclass:: paddle.v2.layer.tensor :noindex: .. _api_v2.layer_cos_sim: cos_sim ------- -.. automodule:: paddle.v2.layer - :members: cos_sim +.. autoclass:: paddle.v2.layer.cos_sim :noindex: trans ----- -.. automodule:: paddle.v2.layer - :members: trans +.. autoclass:: paddle.v2.layer.trans :noindex: Sampling Layers @@ -381,14 +328,12 @@ Sampling Layers maxid ----- -.. automodule:: paddle.v2.layer - :members: maxid +.. autoclass:: paddle.v2.layer.max_id :noindex: sampling_id ----------- -.. automodule:: paddle.v2.layer - :members: sampling_id +.. autoclass:: paddle.v2.layer.sampling_id :noindex: Slicing and Joining Layers @@ -396,8 +341,7 @@ Slicing and Joining Layers pad ---- -.. automodule:: paddle.v2.layer - :members: pad +.. autoclass:: paddle.v2.layer.pad :noindex: .. _api_v2.layer_costs: @@ -407,80 +351,72 @@ Cost Layers cross_entropy_cost ------------------ -.. automodule:: paddle.v2.layer - :members: cross_entropy_cost +.. autoclass:: paddle.v2.layer.cross_entropy_cost :noindex: cross_entropy_with_selfnorm_cost -------------------------------- -.. automodule:: paddle.v2.layer - :members: cross_entropy_with_selfnorm_cost +.. autoclass:: paddle.v2.layer.cross_entropy_with_selfnorm_cost :noindex: multi_binary_label_cross_entropy_cost ------------------------------------- -.. automodule:: paddle.v2.layer - :members: multi_binary_label_cross_entropy_cost +.. autoclass:: paddle.v2.layer.multi_binary_label_cross_entropy_cost :noindex: huber_cost ---------- -.. automodule:: paddle.v2.layer - :members: huber_cost +.. autoclass:: paddle.v2.layer.huber_cost :noindex: lambda_cost ----------- -.. automodule:: paddle.v2.layer - :members: lambda_cost +.. autoclass:: paddle.v2.layer.lambda_cost + :noindex: + +mse_cost +-------- +.. autoclass:: paddle.v2.layer.mse_cost :noindex: rank_cost --------- -.. automodule:: paddle.v2.layer - :members: rank_cost +.. autoclass:: paddle.v2.layer.rank_cost :noindex: sum_cost --------- -.. automodule:: paddle.v2.layer - :members: sum_cost +.. autoclass:: paddle.v2.layer.sum_cost :noindex: crf --- -.. automodule:: paddle.v2.layer - :members: crf +.. autoclass:: paddle.v2.layer.crf :noindex: crf_decoding ------------ -.. automodule:: paddle.v2.layer - :members: crf_decoding +.. autoclass:: paddle.v2.layer.crf_decoding :noindex: ctc --- -.. automodule:: paddle.v2.layer - :members: ctc +.. autoclass:: paddle.v2.layer.ctc :noindex: warp_ctc -------- -.. automodule:: paddle.v2.layer - :members: warp_ctc +.. autoclass:: paddle.v2.layer.warp_ctc :noindex: nce --- -.. automodule:: paddle.v2.layer - :members: nce +.. autoclass:: paddle.v2.layer.nce :noindex: hsigmoid --------- -.. automodule:: paddle.v2.layer - :members: hsigmoid +.. autoclass:: paddle.v2.layer.hsigmoid :noindex: Check Layer @@ -488,6 +424,5 @@ Check Layer eos --- -.. automodule:: paddle.v2.layer - :members: eos +.. autoclass:: paddle.v2.layer.eos :noindex: diff --git a/develop/doc/api/v1/trainer_config_helpers/attrs.html b/develop/doc/api/v1/trainer_config_helpers/attrs.html index 6ccd17eb9fac7fbee7f8d6cf284e6079a6184e2b..111304c97a017feaa94a2547bfb8a40741407b05 100644 --- a/develop/doc/api/v1/trainer_config_helpers/attrs.html +++ b/develop/doc/api/v1/trainer_config_helpers/attrs.html @@ -270,7 +270,7 @@ layer that not support this attribute, paddle will print an error and core.

  • drop_rate (float) – Dropout rate. Dropout will create a mask on layer output. The dropout rate is the zero rate of this mask. The details of what dropout is please refer to here.
  • -
  • device (int) –

    device ID of layer. device=-1, use CPU. device>0, use GPU. +

  • device (int) –

    device ID of layer. device=-1, use CPU. device>=0, use GPU. The details allocation in parallel_nn please refer to here.

  • diff --git a/develop/doc/api/v1/trainer_config_helpers/layers.html b/develop/doc/api/v1/trainer_config_helpers/layers.html index 249b61c7c71795c2cd3720b02f859f4655919d71..cf1439da2a5e93645206c4ebfc14f86281a85404 100644 --- a/develop/doc/api/v1/trainer_config_helpers/layers.html +++ b/develop/doc/api/v1/trainer_config_helpers/layers.html @@ -1757,11 +1757,11 @@ It performs element-wise multiplication with weight.

    paddle.trainer_config_helpers.layers.dotmul_operator(a=None, b=None, scale=1, **kwargs)

    DotMulOperator takes two inputs and performs element-wise multiplication:

    -\[out.row[i] += scale * (x.row[i] .* y.row[i])\]
    +\[out.row[i] += scale * (a.row[i] .* b.row[i])\]

    where \(.*\) means element-wise multiplication, and scale is a config scalar, its default value is one.

    The example usage is:

    -
    op = dotmul_operator(x=layer1, y=layer2, scale=0.5)
    +
    op = dotmul_operator(a=layer1, b=layer2, scale=0.5)
     
    @@ -3077,9 +3077,9 @@ Input should be a vector of positive numbers, without normalization.

    mean squared error cost:

    -\[$\]
    +\[\]
    -

    rac{1}{N}sum_{i=1}^N(t _i- y_i)^2$

    +

    rac{1}{N}sum_{i=1}^N(t_i-y_i)^2

    diff --git a/develop/doc/api/v2/config/attr.html b/develop/doc/api/v2/config/attr.html index 88f9d496e56bb7baa70a5d4490ef62df13003f65..0833280c385d5e578d4c22a108d1e2f9cd4de74b 100644 --- a/develop/doc/api/v2/config/attr.html +++ b/develop/doc/api/v2/config/attr.html @@ -301,7 +301,7 @@ layer that not support this attribute, paddle will print an error and core.

  • drop_rate (float) – Dropout rate. Dropout will create a mask on layer output. The dropout rate is the zero rate of this mask. The details of what dropout is please refer to here.
  • -
  • device (int) –

    device ID of layer. device=-1, use CPU. device>0, use GPU. +

  • device (int) –

    device ID of layer. device=-1, use CPU. device>=0, use GPU. The details allocation in parallel_nn please refer to here.

  • diff --git a/develop/doc/api/v2/config/layer.html b/develop/doc/api/v2/config/layer.html index 65a9d30d3d6e4e4ffb26744fc27d0888e982b730..8350048eece2bb672e1bf116104924eb276eb086 100644 --- a/develop/doc/api/v2/config/layer.html +++ b/develop/doc/api/v2/config/layer.html @@ -277,6 +277,7 @@
  • multi_binary_label_cross_entropy_cost
  • huber_cost
  • lambda_cost
  • +
  • mse_cost
  • rank_cost
  • sum_cost
  • crf
  • @@ -330,21 +331,6 @@

    Data layer

    data

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.data(name, type, **kwargs)
    @@ -382,21 +368,6 @@ the way how to configure a neural network topology in Paddle Python code.

    Fully Connected Layers

    fc

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.fc(*args, **kwargs)
    @@ -443,21 +414,6 @@ default Bias.

    selective_fc

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.selective_fc(*args, **kwargs)
    @@ -505,21 +461,6 @@ default Bias.

    Conv Layers

    conv_operator

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.conv_operator(**kwargs)
    @@ -568,21 +509,6 @@ the filter’s shape can be (filter_size, filter_size_y).

    conv_projection

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.conv_projection(**kwargs)
    @@ -631,21 +557,6 @@ the filter’s shape can be (filter_size, filter_size_y).

    conv_shift

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.conv_shift(*args, **kwargs)
    @@ -699,21 +610,6 @@ the right size (which is the end of array) to the left.

    img_conv

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.img_conv(*args, **kwargs)
    @@ -792,21 +688,6 @@ otherwise layer_type has to be either “exconv” or

    context_projection

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.context_projection(**kwargs)
    @@ -850,21 +731,6 @@ parameter attribute is set by this parameter.

    Image Pooling Layer

    img_pool

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.img_pool(*args, **kwargs)
    @@ -929,21 +795,6 @@ Defalut is True. If set false, Otherwise use floor.

    spp

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.spp(*args, **kwargs)
    @@ -984,21 +835,6 @@ The details please refer to

    maxout

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.maxout(*args, **kwargs)
    @@ -1056,21 +892,6 @@ automatically from previous output.

    Norm Layer

    img_cmrnorm

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.img_cmrnorm(*args, **kwargs)
    @@ -1110,21 +931,6 @@ num_channels is None, it will be set automatically.

    batch_norm

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.batch_norm(*args, **kwargs)
    @@ -1197,21 +1003,6 @@ computation, referred to as facotr,

    sum_to_one_norm

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.sum_to_one_norm(*args, **kwargs)
    @@ -1249,21 +1040,6 @@ and \(out\) is a (batchSize x dataDim) output vector.<

    cross_channel_norm

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.cross_channel_norm(*args, **kwargs)
    @@ -1295,21 +1071,6 @@ factors which dimensions equal to the channel’s number.

    Recurrent Layers

    recurrent

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.recurrent(*args, **kwargs)
    @@ -1350,21 +1111,6 @@ out_{i} = act(in_{i} + out_{i+1} * W) \ \ \text{for} \ start <= i < end\en

    lstmemory

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.lstmemory(*args, **kwargs)
    @@ -1414,21 +1160,6 @@ bias.

    grumemory

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.grumemory(*args, **kwargs)
    @@ -1501,57 +1232,23 @@ will get a warning.

    Recurrent Layer Group

    memory

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    +
    +
    +paddle.v2.layer.memory
    +

    alias of MemoryV2

    +
    -# use prediction instance where needed. -parameters = paddle.parameters.create(cost) -
    -

    recurrent_group

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    +
    +
    +class paddle.v2.layer.recurrent_group
    +
    -# use prediction instance where needed. -parameters = paddle.parameters.create(cost) -
    -

    lstm_step

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.lstm_step(*args, **kwargs)
    @@ -1602,21 +1299,6 @@ be sigmoid only.

    gru_step

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.gru_step(*args, **kwargs)
    @@ -1651,39 +1333,14 @@ from previous step.

    get_output

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.get_output(*args, **kwargs)
    @@ -1720,39 +1377,14 @@ multiple outputs.

    Mixed Layer

    mixed

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    +
    +
    +class paddle.v2.layer.mixed
    +
    -# use prediction instance where needed. -parameters = paddle.parameters.create(cost) -
    -

    embedding

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.embedding(*args, **kwargs)
    @@ -1784,21 +1416,6 @@ for details.

    scaling_projection

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.scaling_projection(**kwargs)
    @@ -1833,21 +1450,6 @@ the output.

    dotmul_projection

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.dotmul_projection(**kwargs)
    @@ -1883,31 +1485,16 @@ It performs element-wise multiplication with weight.

    dotmul_operator

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.dotmul_operator(**kwargs)

    DotMulOperator takes two inputs and performs element-wise multiplication:

    -\[out.row[i] += scale * (x.row[i] .* y.row[i])\]
    +\[out.row[i] += scale * (a.row[i] .* b.row[i])\]

    where \(.*\) means element-wise multiplication, and scale is a config scalar, its default value is one.

    The example usage is:

    -
    op = dotmul_operator(x=layer1, y=layer2, scale=0.5)
    +
    op = dotmul_operator(a=layer1, b=layer2, scale=0.5)
     
    @@ -1934,21 +1521,6 @@ scale is a config scalar, its default value is one.

    full_matrix_projection

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.full_matrix_projection(**kwargs)
    @@ -1995,21 +1567,6 @@ the way how to configure a neural network topology in Paddle Python code.

    identity_projection

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.identity_projection(**kwargs)
    @@ -2056,21 +1613,6 @@ It select dimesions [offset, offset+layer_size) from input:

    table_projection

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.table_projection(**kwargs)
    @@ -2120,21 +1662,6 @@ and \(i\) is row_id.

    trans_full_matrix_projection

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.trans_full_matrix_projection(**kwargs)
    @@ -2179,21 +1706,6 @@ The simply usage is:

    Aggregate Layers

    pooling

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.pooling(*args, **kwargs)
    @@ -2233,21 +1745,6 @@ SumPooling, SquareRootNPooling.

    last_seq

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.last_seq(*args, **kwargs)
    @@ -2286,21 +1783,6 @@ of stride is -1.

    first_seq

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.first_seq(*args, **kwargs)
    @@ -2339,21 +1821,6 @@ of stride is -1.

    concat

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.concat(*args, **kwargs)
    @@ -2388,21 +1855,6 @@ Inputs can be list of paddle.v2.config_base.Layer or list of projection.

    seq_concat

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.seq_concat(*args, **kwargs)
    @@ -2453,21 +1905,6 @@ default Bias.

    Reshaping Layers

    block_expand

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.block_expand(*args, **kwargs)
    @@ -2526,21 +1963,6 @@ convolution neural network, and before recurrent neural network.

    expand

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.expand(*args, **kwargs)
    @@ -2580,21 +2002,6 @@ bias.

    repeat

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.repeat(*args, **kwargs)
    @@ -2631,21 +2038,6 @@ to apply concat() with num_repeats same input.

    rotate

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.rotate(*args, **kwargs)
    @@ -2685,21 +2077,6 @@ usually used when the input sample is some image or feature map.

    seq_reshape

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.seq_reshape(*args, **kwargs)
    @@ -2743,21 +2120,6 @@ default Bias.

    Math Layers

    addto

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.addto(*args, **kwargs)
    @@ -2810,21 +2172,6 @@ bias.

    linear_comb

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.linear_comb(*args, **kwargs)
    @@ -2888,21 +2235,6 @@ processed in one batch.

    interpolation

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.interpolation(*args, **kwargs)
    @@ -2942,21 +2274,6 @@ which is used in NEURAL TURING MACHINE.

    bilinear_interp

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.bilinear_interp(*args, **kwargs)
    @@ -2992,21 +2309,6 @@ the way how to configure a neural network topology in Paddle Python code.

    power

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.power(*args, **kwargs)
    @@ -3045,21 +2347,6 @@ and \(y\) is a output vector.

    scaling

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.scaling(*args, **kwargs)
    @@ -3099,21 +2386,6 @@ processed in one batch.

    slope_intercept

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.slope_intercept(*args, **kwargs)
    @@ -3151,21 +2423,6 @@ element-wise. There is no activation and weight.

    tensor

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.tensor(*args, **kwargs)
    @@ -3219,21 +2476,6 @@ default Bias.

    cos_sim

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.cos_sim(*args, **kwargs)
    @@ -3277,21 +2519,6 @@ processed in one batch.

    trans

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.trans(*args, **kwargs)
    @@ -3330,39 +2557,39 @@ the way how to configure a neural network topology in Paddle Python code.

    Sampling Layers

    maxid

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    +
    +
    +class paddle.v2.layer.max_id(*args, **kwargs)
    +

    A layer for finding the id which has the maximal value for each sample. +The result is stored in output.ids.

    +

    The example usage is:

    +
    maxid = maxid(input=layer)
     
    +
    +++ + + + + + + + +
    Parameters:
      +
    • input (paddle.v2.config_base.Layer) – Input layer name.
    • +
    • name (basestring) – Layer name.
    • +
    • layer_attr (paddle.v2.attr.ExtraAttribute) – extra layer attributes.
    • +
    +
    Returns:

    paddle.v2.config_base.Layer object.

    +
    Return type:

    paddle.v2.config_base.Layer

    +
    +
    +

    sampling_id

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.sampling_id(*args, **kwargs)
    @@ -3399,21 +2626,6 @@ Sampling one id for one sample.

    Slicing and Joining Layers

    pad

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.pad(*args, **kwargs)
    @@ -3483,21 +2695,6 @@ in width dimension.

    Cost Layers

    cross_entropy_cost

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.cross_entropy_cost(*args, **kwargs)
    @@ -3536,21 +2733,6 @@ will not be calculated for weight.

    cross_entropy_with_selfnorm_cost

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.cross_entropy_with_selfnorm_cost(*args, **kwargs)
    @@ -3587,21 +2769,6 @@ Input should be a vector of positive numbers, without normalization.

    multi_binary_label_cross_entropy_cost

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.multi_binary_label_cross_entropy_cost(*args, **kwargs)
    @@ -3637,21 +2804,6 @@ the way how to configure a neural network topology in Paddle Python code.

    huber_cost

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.huber_cost(*args, **kwargs)
    @@ -3686,21 +2838,6 @@ the way how to configure a neural network topology in Paddle Python code.

    lambda_cost

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.lambda_cost(*args, **kwargs)
    @@ -3745,23 +2882,57 @@ entire list of get gradient.
    -
    -

    rank_cost

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    +
    +

    mse_cost

    +
    +
    +class paddle.v2.layer.mse_cost(*args, **kwargs)
    +
    +

    mean squared error cost:

    +
    +\[\]
    +
    +

    rac{1}{N}sum_{i=1}^N(t_i-y_i)^2

    +
    +
    +++ + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    param name:layer name.
    type name:basestring
    param input:Network prediction.
    type input:paddle.v2.config_base.Layer
    param label:Data label.
    type label:paddle.v2.config_base.Layer
    param weight:The weight affects the cost, namely the scale of cost. +It is an optional argument.
    type weight:paddle.v2.config_base.Layer
    param layer_attr:
     layer’s extra attribute.
    type layer_attr:
     paddle.v2.attr.ExtraAttribute
    return:paddle.v2.config_base.Layer object.
    rtype:paddle.v2.config_base.Layer
    +
    +
    -# use prediction instance where needed. -parameters = paddle.parameters.create(cost) -
    +
    +

    rank_cost

    class paddle.v2.layer.rank_cost(*args, **kwargs)
    @@ -3817,21 +2988,6 @@ It is an optional argument.

    sum_cost

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.sum_cost(*args, **kwargs)
    @@ -3863,21 +3019,6 @@ the way how to configure a neural network topology in Paddle Python code.

    crf

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.crf(*args, **kwargs)
    @@ -3918,21 +3059,6 @@ optional argument.

    crf_decoding

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.crf_decoding(*args, **kwargs)
    @@ -3973,21 +3099,6 @@ decoding or 0 for correct decoding.

    ctc

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.ctc(*args, **kwargs)
    @@ -4039,21 +3150,6 @@ should also be num_classes + 1.

    warp_ctc

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.warp_ctc(*args, **kwargs)
    @@ -4114,21 +3210,6 @@ should be consistent as that used in your labels.

    nce

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.nce(*args, **kwargs)
    @@ -4173,21 +3254,6 @@ If not None, its length must be equal to num_classes.

    hsigmoid

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.hsigmoid(*args, **kwargs)
    @@ -4233,21 +3299,6 @@ False means no bias.

    Check Layer

    eos

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.eos(*args, **kwargs)
    diff --git a/develop/doc/searchindex.js b/develop/doc/searchindex.js index 07f7c60930b15c5dbb420cbb5e0de1866908f683..0af228e750fd1bf76515c910751d41132c69c0f3 100644 --- a/develop/doc/searchindex.js +++ b/develop/doc/searchindex.js @@ -1 +1 @@ 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Prediction","Activations","Parameter Attributes","DataSources","Evaluators","Layers","Networks","Optimizers","Poolings","Activation","Parameter Attribute","Layers","Networks","Optimizer","Pooling","Data Reader Interface and DataSets","Model Configuration","Training and Inference","PaddlePaddle Design Doc","Design Doc: Distributed Training","Paddle\u591a\u8bed\u8a00\u63a5\u53e3\u5b9e\u73b0","C-API \u6a21\u578b\u63a8\u65ad\u5b9e\u73b0\u6587\u6863","Python Data Reader Design Doc","Paddle\u53d1\u884c\u89c4\u8303","Simple Linear Regression","Installing from Sources","PaddlePaddle in Docker Containers","Install and Build","Debian Package installation guide","GET STARTED","RNN Models","RNN Configuration","Contribute Code","Write New Layers","HOW TO","Tune GPU Performance","Run Distributed Training","Argument Outline","Detail Description","Set Command-line Parameters","Use Case","Distributed PaddlePaddle Training on AWS with Kubernetes","Paddle On Kubernetes","<no title>","<no 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\ No newline at end of file diff --git a/develop/doc_cn/_sources/api/v2/config/layer.rst.txt b/develop/doc_cn/_sources/api/v2/config/layer.rst.txt index 05817ec85455ac58566e90956a54cb86541f8488..2a02baf17ba0d1119a8d222024616ef8ae33f8d5 100644 --- a/develop/doc_cn/_sources/api/v2/config/layer.rst.txt +++ b/develop/doc_cn/_sources/api/v2/config/layer.rst.txt @@ -11,8 +11,7 @@ Data layer data ---- -.. automodule:: paddle.v2.layer - :members: data +.. autoclass:: paddle.v2.layer.data :noindex: Fully Connected Layers @@ -22,14 +21,12 @@ Fully Connected Layers fc -- -.. automodule:: paddle.v2.layer - :members: fc +.. autoclass:: paddle.v2.layer.fc :noindex: selective_fc ------------ -.. automodule:: paddle.v2.layer - :members: selective_fc +.. autoclass:: paddle.v2.layer.selective_fc :noindex: Conv Layers @@ -37,34 +34,29 @@ Conv Layers conv_operator ------------- -.. automodule:: paddle.v2.layer - :members: conv_operator +.. autoclass:: paddle.v2.layer.conv_operator :noindex: conv_projection --------------- -.. automodule:: paddle.v2.layer - :members: conv_projection +.. autoclass:: paddle.v2.layer.conv_projection :noindex: conv_shift ---------- -.. automodule:: paddle.v2.layer - :members: conv_shift +.. autoclass:: paddle.v2.layer.conv_shift :noindex: img_conv -------- -.. automodule:: paddle.v2.layer - :members: img_conv +.. autoclass:: paddle.v2.layer.img_conv :noindex: .. _api_v2.layer_context_projection: context_projection ------------------ -.. automodule:: paddle.v2.layer - :members: context_projection +.. autoclass:: paddle.v2.layer.context_projection :noindex: Image Pooling Layer @@ -72,20 +64,17 @@ Image Pooling Layer img_pool -------- -.. automodule:: paddle.v2.layer - :members: img_pool +.. autoclass:: paddle.v2.layer.img_pool :noindex: spp --- -.. automodule:: paddle.v2.layer - :members: spp +.. autoclass:: paddle.v2.layer.spp :noindex: maxout ------ -.. automodule:: paddle.v2.layer - :members: maxout +.. autoclass:: paddle.v2.layer.maxout :noindex: Norm Layer @@ -93,26 +82,22 @@ Norm Layer img_cmrnorm ----------- -.. automodule:: paddle.v2.layer - :members: img_cmrnorm +.. autoclass:: paddle.v2.layer.img_cmrnorm :noindex: batch_norm ---------- -.. automodule:: paddle.v2.layer - :members: batch_norm +.. autoclass:: paddle.v2.layer.batch_norm :noindex: sum_to_one_norm --------------- -.. automodule:: paddle.v2.layer - :members: sum_to_one_norm +.. autoclass:: paddle.v2.layer.sum_to_one_norm :noindex: cross_channel_norm ------------------ -.. automodule:: paddle.v2.layer - :members: cross_channel_norm +.. autoclass:: paddle.v2.layer.cross_channel_norm :noindex: Recurrent Layers @@ -120,20 +105,17 @@ Recurrent Layers recurrent --------- -.. automodule:: paddle.v2.layer - :members: recurrent +.. autoclass:: paddle.v2.layer.recurrent :noindex: lstmemory --------- -.. automodule:: paddle.v2.layer - :members: lstmemory +.. autoclass:: paddle.v2.layer.lstmemory :noindex: grumemory --------- -.. automodule:: paddle.v2.layer - :members: grumemory +.. autoclass:: paddle.v2.layer.grumemory :noindex: Recurrent Layer Group @@ -141,38 +123,32 @@ Recurrent Layer Group memory ------ -.. automodule:: paddle.v2.layer - :members: memory +.. autoclass:: paddle.v2.layer.memory :noindex: recurrent_group --------------- -.. automodule:: paddle.v2.layer - :members: recurrent_group +.. autoclass:: paddle.v2.layer.recurrent_group :noindex: lstm_step --------- -.. automodule:: paddle.v2.layer - :members: lstm_step +.. autoclass:: paddle.v2.layer.lstm_step :noindex: gru_step -------- -.. automodule:: paddle.v2.layer - :members: gru_step +.. autoclass:: paddle.v2.layer.gru_step :noindex: beam_search ------------ -.. automodule:: paddle.v2.layer - :members: beam_search +.. autoclass:: paddle.v2.layer.beam_search :noindex: get_output ---------- -.. automodule:: paddle.v2.layer - :members: get_output +.. autoclass:: paddle.v2.layer.get_output :noindex: Mixed Layer @@ -182,59 +158,50 @@ Mixed Layer mixed ----- -.. automodule:: paddle.v2.layer - :members: mixed +.. autoclass:: paddle.v2.layer.mixed :noindex: .. _api_v2.layer_embedding: embedding --------- -.. automodule:: paddle.v2.layer - :members: embedding +.. autoclass:: paddle.v2.layer.embedding :noindex: scaling_projection ------------------ -.. automodule:: paddle.v2.layer - :members: scaling_projection +.. autoclass:: paddle.v2.layer.scaling_projection :noindex: dotmul_projection ----------------- -.. automodule:: paddle.v2.layer - :members: dotmul_projection +.. autoclass:: paddle.v2.layer.dotmul_projection :noindex: dotmul_operator --------------- -.. automodule:: paddle.v2.layer - :members: dotmul_operator +.. autoclass:: paddle.v2.layer.dotmul_operator :noindex: full_matrix_projection ---------------------- -.. automodule:: paddle.v2.layer - :members: full_matrix_projection +.. autoclass:: paddle.v2.layer.full_matrix_projection :noindex: identity_projection ------------------- -.. automodule:: paddle.v2.layer - :members: identity_projection +.. autoclass:: paddle.v2.layer.identity_projection :noindex: table_projection ---------------- -.. automodule:: paddle.v2.layer - :members: table_projection +.. autoclass:: paddle.v2.layer.table_projection :noindex: trans_full_matrix_projection ---------------------------- -.. automodule:: paddle.v2.layer - :members: trans_full_matrix_projection +.. autoclass:: paddle.v2.layer.trans_full_matrix_projection :noindex: Aggregate Layers @@ -244,36 +211,31 @@ Aggregate Layers pooling ------- -.. automodule:: paddle.v2.layer - :members: pooling +.. autoclass:: paddle.v2.layer.pooling :noindex: .. _api_v2.layer_last_seq: last_seq -------- -.. automodule:: paddle.v2.layer - :members: last_seq +.. autoclass:: paddle.v2.layer.last_seq :noindex: .. _api_v2.layer_first_seq: first_seq --------- -.. automodule:: paddle.v2.layer - :members: first_seq +.. autoclass:: paddle.v2.layer.first_seq :noindex: concat ------ -.. automodule:: paddle.v2.layer - :members: concat +.. autoclass:: paddle.v2.layer.concat :noindex: seq_concat ---------- -.. automodule:: paddle.v2.layer - :members: seq_concat +.. autoclass:: paddle.v2.layer.seq_concat :noindex: Reshaping Layers @@ -281,34 +243,29 @@ Reshaping Layers block_expand ------------ -.. automodule:: paddle.v2.layer - :members: block_expand +.. autoclass:: paddle.v2.layer.block_expand :noindex: .. _api_v2.layer_expand: expand ------ -.. automodule:: paddle.v2.layer - :members: expand +.. autoclass:: paddle.v2.layer.expand :noindex: repeat ------ -.. automodule:: paddle.v2.layer - :members: repeat +.. autoclass:: paddle.v2.layer.repeat :noindex: rotate ------ -.. automodule:: paddle.v2.layer - :members: rotate +.. autoclass:: paddle.v2.layer.rotate :noindex: seq_reshape ----------- -.. automodule:: paddle.v2.layer - :members: seq_reshape +.. autoclass:: paddle.v2.layer.seq_reshape :noindex: Math Layers @@ -316,64 +273,54 @@ Math Layers addto ----- -.. automodule:: paddle.v2.layer - :members: addto +.. autoclass:: paddle.v2.layer.addto :noindex: linear_comb ----------- -.. automodule:: paddle.v2.layer - :members: linear_comb +.. autoclass:: paddle.v2.layer.linear_comb :noindex: interpolation ------------- -.. automodule:: paddle.v2.layer - :members: interpolation +.. autoclass:: paddle.v2.layer.interpolation :noindex: bilinear_interp --------------- -.. automodule:: paddle.v2.layer - :members: bilinear_interp +.. autoclass:: paddle.v2.layer.bilinear_interp :noindex: power ----- -.. automodule:: paddle.v2.layer - :members: power +.. autoclass:: paddle.v2.layer.power :noindex: scaling ------- -.. automodule:: paddle.v2.layer - :members: scaling +.. autoclass:: paddle.v2.layer.scaling :noindex: slope_intercept --------------- -.. automodule:: paddle.v2.layer - :members: slope_intercept +.. autoclass:: paddle.v2.layer.slope_intercept :noindex: tensor ------ -.. automodule:: paddle.v2.layer - :members: tensor +.. autoclass:: paddle.v2.layer.tensor :noindex: .. _api_v2.layer_cos_sim: cos_sim ------- -.. automodule:: paddle.v2.layer - :members: cos_sim +.. autoclass:: paddle.v2.layer.cos_sim :noindex: trans ----- -.. automodule:: paddle.v2.layer - :members: trans +.. autoclass:: paddle.v2.layer.trans :noindex: Sampling Layers @@ -381,14 +328,12 @@ Sampling Layers maxid ----- -.. automodule:: paddle.v2.layer - :members: maxid +.. autoclass:: paddle.v2.layer.max_id :noindex: sampling_id ----------- -.. automodule:: paddle.v2.layer - :members: sampling_id +.. autoclass:: paddle.v2.layer.sampling_id :noindex: Slicing and Joining Layers @@ -396,8 +341,7 @@ Slicing and Joining Layers pad ---- -.. automodule:: paddle.v2.layer - :members: pad +.. autoclass:: paddle.v2.layer.pad :noindex: .. _api_v2.layer_costs: @@ -407,80 +351,72 @@ Cost Layers cross_entropy_cost ------------------ -.. automodule:: paddle.v2.layer - :members: cross_entropy_cost +.. autoclass:: paddle.v2.layer.cross_entropy_cost :noindex: cross_entropy_with_selfnorm_cost -------------------------------- -.. automodule:: paddle.v2.layer - :members: cross_entropy_with_selfnorm_cost +.. autoclass:: paddle.v2.layer.cross_entropy_with_selfnorm_cost :noindex: multi_binary_label_cross_entropy_cost ------------------------------------- -.. automodule:: paddle.v2.layer - :members: multi_binary_label_cross_entropy_cost +.. autoclass:: paddle.v2.layer.multi_binary_label_cross_entropy_cost :noindex: huber_cost ---------- -.. automodule:: paddle.v2.layer - :members: huber_cost +.. autoclass:: paddle.v2.layer.huber_cost :noindex: lambda_cost ----------- -.. automodule:: paddle.v2.layer - :members: lambda_cost +.. autoclass:: paddle.v2.layer.lambda_cost + :noindex: + +mse_cost +-------- +.. autoclass:: paddle.v2.layer.mse_cost :noindex: rank_cost --------- -.. automodule:: paddle.v2.layer - :members: rank_cost +.. autoclass:: paddle.v2.layer.rank_cost :noindex: sum_cost --------- -.. automodule:: paddle.v2.layer - :members: sum_cost +.. autoclass:: paddle.v2.layer.sum_cost :noindex: crf --- -.. automodule:: paddle.v2.layer - :members: crf +.. autoclass:: paddle.v2.layer.crf :noindex: crf_decoding ------------ -.. automodule:: paddle.v2.layer - :members: crf_decoding +.. autoclass:: paddle.v2.layer.crf_decoding :noindex: ctc --- -.. automodule:: paddle.v2.layer - :members: ctc +.. autoclass:: paddle.v2.layer.ctc :noindex: warp_ctc -------- -.. automodule:: paddle.v2.layer - :members: warp_ctc +.. autoclass:: paddle.v2.layer.warp_ctc :noindex: nce --- -.. automodule:: paddle.v2.layer - :members: nce +.. autoclass:: paddle.v2.layer.nce :noindex: hsigmoid --------- -.. automodule:: paddle.v2.layer - :members: hsigmoid +.. autoclass:: paddle.v2.layer.hsigmoid :noindex: Check Layer @@ -488,6 +424,5 @@ Check Layer eos --- -.. automodule:: paddle.v2.layer - :members: eos +.. autoclass:: paddle.v2.layer.eos :noindex: diff --git a/develop/doc_cn/api/v1/trainer_config_helpers/attrs.html b/develop/doc_cn/api/v1/trainer_config_helpers/attrs.html index c4bb7d3f1b0072c3deec10050ebf952a0cd4fa33..3734462e7dc6ae1a1939de5aa81ef0a3c94108a1 100644 --- a/develop/doc_cn/api/v1/trainer_config_helpers/attrs.html +++ b/develop/doc_cn/api/v1/trainer_config_helpers/attrs.html @@ -277,7 +277,7 @@ layer that not support this attribute, paddle will print an error and core.

  • drop_rate (float) – Dropout rate. Dropout will create a mask on layer output. The dropout rate is the zero rate of this mask. The details of what dropout is please refer to here.
  • -
  • device (int) –

    device ID of layer. device=-1, use CPU. device>0, use GPU. +

  • device (int) –

    device ID of layer. device=-1, use CPU. device>=0, use GPU. The details allocation in parallel_nn please refer to here.

  • diff --git a/develop/doc_cn/api/v1/trainer_config_helpers/layers.html b/develop/doc_cn/api/v1/trainer_config_helpers/layers.html index 1cbf87242429741ac8467c60d28a8ecee7e664e8..c79d9fbda79cbb99b249d0751f9389430e05a05c 100644 --- a/develop/doc_cn/api/v1/trainer_config_helpers/layers.html +++ b/develop/doc_cn/api/v1/trainer_config_helpers/layers.html @@ -1764,11 +1764,11 @@ It performs element-wise multiplication with weight.

    paddle.trainer_config_helpers.layers.dotmul_operator(a=None, b=None, scale=1, **kwargs)

    DotMulOperator takes two inputs and performs element-wise multiplication:

    -\[out.row[i] += scale * (x.row[i] .* y.row[i])\]
    +\[out.row[i] += scale * (a.row[i] .* b.row[i])\]

    where \(.*\) means element-wise multiplication, and scale is a config scalar, its default value is one.

    The example usage is:

    -
    op = dotmul_operator(x=layer1, y=layer2, scale=0.5)
    +
    op = dotmul_operator(a=layer1, b=layer2, scale=0.5)
     
    @@ -3084,9 +3084,9 @@ Input should be a vector of positive numbers, without normalization.

    mean squared error cost:

    -\[$\]
    +\[\]
    -

    rac{1}{N}sum_{i=1}^N(t _i- y_i)^2$

    +

    rac{1}{N}sum_{i=1}^N(t_i-y_i)^2

    diff --git a/develop/doc_cn/api/v2/config/attr.html b/develop/doc_cn/api/v2/config/attr.html index 77f96c813f75598624016dedd71fea57ba67e119..078e9a8eba6eea70071205024641f0db06d75952 100644 --- a/develop/doc_cn/api/v2/config/attr.html +++ b/develop/doc_cn/api/v2/config/attr.html @@ -308,7 +308,7 @@ layer that not support this attribute, paddle will print an error and core.

  • drop_rate (float) – Dropout rate. Dropout will create a mask on layer output. The dropout rate is the zero rate of this mask. The details of what dropout is please refer to here.
  • -
  • device (int) –

    device ID of layer. device=-1, use CPU. device>0, use GPU. +

  • device (int) –

    device ID of layer. device=-1, use CPU. device>=0, use GPU. The details allocation in parallel_nn please refer to here.

  • diff --git a/develop/doc_cn/api/v2/config/layer.html b/develop/doc_cn/api/v2/config/layer.html index c30055c1470e73f9dfac27725fd47bee4234c60b..e78a198b88aae4707670293c2bdde000db80af6d 100644 --- a/develop/doc_cn/api/v2/config/layer.html +++ b/develop/doc_cn/api/v2/config/layer.html @@ -284,6 +284,7 @@
  • multi_binary_label_cross_entropy_cost
  • huber_cost
  • lambda_cost
  • +
  • mse_cost
  • rank_cost
  • sum_cost
  • crf
  • @@ -337,21 +338,6 @@

    Data layer

    data

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.data(name, type, **kwargs)
    @@ -389,21 +375,6 @@ the way how to configure a neural network topology in Paddle Python code.

    Fully Connected Layers

    fc

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.fc(*args, **kwargs)
    @@ -450,21 +421,6 @@ default Bias.

    selective_fc

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.selective_fc(*args, **kwargs)
    @@ -512,21 +468,6 @@ default Bias.

    Conv Layers

    conv_operator

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.conv_operator(**kwargs)
    @@ -575,21 +516,6 @@ the filter’s shape can be (filter_size, filter_size_y).

    conv_projection

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.conv_projection(**kwargs)
    @@ -638,21 +564,6 @@ the filter’s shape can be (filter_size, filter_size_y).

    conv_shift

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.conv_shift(*args, **kwargs)
    @@ -706,21 +617,6 @@ the right size (which is the end of array) to the left.

    img_conv

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.img_conv(*args, **kwargs)
    @@ -799,21 +695,6 @@ otherwise layer_type has to be either “exconv” or

    context_projection

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.context_projection(**kwargs)
    @@ -857,21 +738,6 @@ parameter attribute is set by this parameter.

    Image Pooling Layer

    img_pool

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.img_pool(*args, **kwargs)
    @@ -936,21 +802,6 @@ Defalut is True. If set false, Otherwise use floor.

    spp

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.spp(*args, **kwargs)
    @@ -991,21 +842,6 @@ The details please refer to

    maxout

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.maxout(*args, **kwargs)
    @@ -1063,21 +899,6 @@ automatically from previous output.

    Norm Layer

    img_cmrnorm

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.img_cmrnorm(*args, **kwargs)
    @@ -1117,21 +938,6 @@ num_channels is None, it will be set automatically.

    batch_norm

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.batch_norm(*args, **kwargs)
    @@ -1204,21 +1010,6 @@ computation, referred to as facotr,

    sum_to_one_norm

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.sum_to_one_norm(*args, **kwargs)
    @@ -1256,21 +1047,6 @@ and \(out\) is a (batchSize x dataDim) output vector.<

    cross_channel_norm

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.cross_channel_norm(*args, **kwargs)
    @@ -1302,21 +1078,6 @@ factors which dimensions equal to the channel’s number.

    Recurrent Layers

    recurrent

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.recurrent(*args, **kwargs)
    @@ -1357,21 +1118,6 @@ out_{i} = act(in_{i} + out_{i+1} * W) \ \ \text{for} \ start <= i < end\en

    lstmemory

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.lstmemory(*args, **kwargs)
    @@ -1421,21 +1167,6 @@ bias.

    grumemory

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.grumemory(*args, **kwargs)
    @@ -1508,57 +1239,23 @@ will get a warning.

    Recurrent Layer Group

    memory

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    +
    +
    +paddle.v2.layer.memory
    +

    MemoryV2 的别名

    +
    -# use prediction instance where needed. -parameters = paddle.parameters.create(cost) -
    -

    recurrent_group

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    +
    +
    +class paddle.v2.layer.recurrent_group
    +
    -# use prediction instance where needed. -parameters = paddle.parameters.create(cost) -
    -

    lstm_step

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.lstm_step(*args, **kwargs)
    @@ -1609,21 +1306,6 @@ be sigmoid only.

    gru_step

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.gru_step(*args, **kwargs)
    @@ -1658,39 +1340,14 @@ from previous step.

    get_output

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.get_output(*args, **kwargs)
    @@ -1727,39 +1384,14 @@ multiple outputs.

    Mixed Layer

    mixed

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    +
    +
    +class paddle.v2.layer.mixed
    +
    -# use prediction instance where needed. -parameters = paddle.parameters.create(cost) -
    -

    embedding

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.embedding(*args, **kwargs)
    @@ -1791,21 +1423,6 @@ for details.

    scaling_projection

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.scaling_projection(**kwargs)
    @@ -1840,21 +1457,6 @@ the output.

    dotmul_projection

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.dotmul_projection(**kwargs)
    @@ -1890,31 +1492,16 @@ It performs element-wise multiplication with weight.

    dotmul_operator

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.dotmul_operator(**kwargs)

    DotMulOperator takes two inputs and performs element-wise multiplication:

    -\[out.row[i] += scale * (x.row[i] .* y.row[i])\]
    +\[out.row[i] += scale * (a.row[i] .* b.row[i])\]

    where \(.*\) means element-wise multiplication, and scale is a config scalar, its default value is one.

    The example usage is:

    -
    op = dotmul_operator(x=layer1, y=layer2, scale=0.5)
    +
    op = dotmul_operator(a=layer1, b=layer2, scale=0.5)
     
    @@ -1941,21 +1528,6 @@ scale is a config scalar, its default value is one.

    full_matrix_projection

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.full_matrix_projection(**kwargs)
    @@ -2002,21 +1574,6 @@ the way how to configure a neural network topology in Paddle Python code.

    identity_projection

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.identity_projection(**kwargs)
    @@ -2063,21 +1620,6 @@ It select dimesions [offset, offset+layer_size) from input:

    table_projection

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.table_projection(**kwargs)
    @@ -2127,21 +1669,6 @@ and \(i\) is row_id.

    trans_full_matrix_projection

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.trans_full_matrix_projection(**kwargs)
    @@ -2186,21 +1713,6 @@ The simply usage is:

    Aggregate Layers

    pooling

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.pooling(*args, **kwargs)
    @@ -2240,21 +1752,6 @@ SumPooling, SquareRootNPooling.

    last_seq

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.last_seq(*args, **kwargs)
    @@ -2293,21 +1790,6 @@ of stride is -1.

    first_seq

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.first_seq(*args, **kwargs)
    @@ -2346,21 +1828,6 @@ of stride is -1.

    concat

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.concat(*args, **kwargs)
    @@ -2395,21 +1862,6 @@ Inputs can be list of paddle.v2.config_base.Layer or list of projection.

    seq_concat

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.seq_concat(*args, **kwargs)
    @@ -2460,21 +1912,6 @@ default Bias.

    Reshaping Layers

    block_expand

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.block_expand(*args, **kwargs)
    @@ -2533,21 +1970,6 @@ convolution neural network, and before recurrent neural network.

    expand

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.expand(*args, **kwargs)
    @@ -2587,21 +2009,6 @@ bias.

    repeat

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.repeat(*args, **kwargs)
    @@ -2638,21 +2045,6 @@ to apply concat() with num_repeats same input.

    rotate

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.rotate(*args, **kwargs)
    @@ -2692,21 +2084,6 @@ usually used when the input sample is some image or feature map.

    seq_reshape

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.seq_reshape(*args, **kwargs)
    @@ -2750,21 +2127,6 @@ default Bias.

    Math Layers

    addto

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.addto(*args, **kwargs)
    @@ -2817,21 +2179,6 @@ bias.

    linear_comb

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.linear_comb(*args, **kwargs)
    @@ -2895,21 +2242,6 @@ processed in one batch.

    interpolation

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.interpolation(*args, **kwargs)
    @@ -2949,21 +2281,6 @@ which is used in NEURAL TURING MACHINE.

    bilinear_interp

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.bilinear_interp(*args, **kwargs)
    @@ -2999,21 +2316,6 @@ the way how to configure a neural network topology in Paddle Python code.

    power

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.power(*args, **kwargs)
    @@ -3052,21 +2354,6 @@ and \(y\) is a output vector.

    scaling

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.scaling(*args, **kwargs)
    @@ -3106,21 +2393,6 @@ processed in one batch.

    slope_intercept

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.slope_intercept(*args, **kwargs)
    @@ -3158,21 +2430,6 @@ element-wise. There is no activation and weight.

    tensor

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.tensor(*args, **kwargs)
    @@ -3226,21 +2483,6 @@ default Bias.

    cos_sim

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.cos_sim(*args, **kwargs)
    @@ -3284,21 +2526,6 @@ processed in one batch.

    trans

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.trans(*args, **kwargs)
    @@ -3337,39 +2564,39 @@ the way how to configure a neural network topology in Paddle Python code.

    Sampling Layers

    maxid

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    +
    +
    +class paddle.v2.layer.max_id(*args, **kwargs)
    +

    A layer for finding the id which has the maximal value for each sample. +The result is stored in output.ids.

    +

    The example usage is:

    +
    maxid = maxid(input=layer)
     
    +
    +++ + + + + + + + +
    参数:
      +
    • input (paddle.v2.config_base.Layer) – Input layer name.
    • +
    • name (basestring) – Layer name.
    • +
    • layer_attr (paddle.v2.attr.ExtraAttribute) – extra layer attributes.
    • +
    +
    返回:

    paddle.v2.config_base.Layer object.

    +
    返回类型:

    paddle.v2.config_base.Layer

    +
    +
    +

    sampling_id

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.sampling_id(*args, **kwargs)
    @@ -3406,21 +2633,6 @@ Sampling one id for one sample.

    Slicing and Joining Layers

    pad

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.pad(*args, **kwargs)
    @@ -3490,21 +2702,6 @@ in width dimension.

    Cost Layers

    cross_entropy_cost

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.cross_entropy_cost(*args, **kwargs)
    @@ -3543,21 +2740,6 @@ will not be calculated for weight.

    cross_entropy_with_selfnorm_cost

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.cross_entropy_with_selfnorm_cost(*args, **kwargs)
    @@ -3594,21 +2776,6 @@ Input should be a vector of positive numbers, without normalization.

    multi_binary_label_cross_entropy_cost

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.multi_binary_label_cross_entropy_cost(*args, **kwargs)
    @@ -3644,21 +2811,6 @@ the way how to configure a neural network topology in Paddle Python code.

    huber_cost

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.huber_cost(*args, **kwargs)
    @@ -3693,21 +2845,6 @@ the way how to configure a neural network topology in Paddle Python code.

    lambda_cost

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.lambda_cost(*args, **kwargs)
    @@ -3752,23 +2889,57 @@ entire list of get gradient.
    -
    -

    rank_cost

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    +
    +

    mse_cost

    +
    +
    +class paddle.v2.layer.mse_cost(*args, **kwargs)
    +
    +

    mean squared error cost:

    +
    +\[\]
    +
    +

    rac{1}{N}sum_{i=1}^N(t_i-y_i)^2

    +
    +
    +++ + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    param name:layer name.
    type name:basestring
    param input:Network prediction.
    type input:paddle.v2.config_base.Layer
    param label:Data label.
    type label:paddle.v2.config_base.Layer
    param weight:The weight affects the cost, namely the scale of cost. +It is an optional argument.
    type weight:paddle.v2.config_base.Layer
    param layer_attr:
     layer’s extra attribute.
    type layer_attr:
     paddle.v2.attr.ExtraAttribute
    return:paddle.v2.config_base.Layer object.
    rtype:paddle.v2.config_base.Layer
    +
    +
    -# use prediction instance where needed. -parameters = paddle.parameters.create(cost) -
    +
    +

    rank_cost

    class paddle.v2.layer.rank_cost(*args, **kwargs)
    @@ -3824,21 +2995,6 @@ It is an optional argument.

    sum_cost

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.sum_cost(*args, **kwargs)
    @@ -3870,21 +3026,6 @@ the way how to configure a neural network topology in Paddle Python code.

    crf

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.crf(*args, **kwargs)
    @@ -3925,21 +3066,6 @@ optional argument.

    crf_decoding

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.crf_decoding(*args, **kwargs)
    @@ -3980,21 +3106,6 @@ decoding or 0 for correct decoding.

    ctc

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.ctc(*args, **kwargs)
    @@ -4046,21 +3157,6 @@ should also be num_classes + 1.

    warp_ctc

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.warp_ctc(*args, **kwargs)
    @@ -4121,21 +3217,6 @@ should be consistent as that used in your labels.

    nce

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.nce(*args, **kwargs)
    @@ -4180,21 +3261,6 @@ If not None, its length must be equal to num_classes.

    hsigmoid

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.hsigmoid(*args, **kwargs)
    @@ -4240,21 +3306,6 @@ False means no bias.

    Check Layer

    eos

    -

    paddle.v2.layer is a part of model config packages in paddle.v2. In API v2, -we want to make Paddle a plain Python package. The model config package defined -the way how to configure a neural network topology in Paddle Python code.

    -

    The primary usage shows below.

    -
    import paddle.v2 as paddle
    -
    -img = paddle.layer.data(name='img', type=paddle.data_type.dense_vector(784))
    -hidden = paddle.layer.fc(input=img, size=200)
    -prediction = paddle.layer.fc(input=hidden, size=10,
    -                             act=paddle.activation.Softmax())
    -
    -# use prediction instance where needed.
    -parameters = paddle.parameters.create(cost)
    -
    -
    class paddle.v2.layer.eos(*args, **kwargs)
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