diff --git a/develop/doc/_sources/api/v2/config/layer.rst.txt b/develop/doc/_sources/api/v2/config/layer.rst.txt index c3f9c18d0663a7a24880b441981875c1e4f015aa..d81481ca819c13ee0e299c204f998f3915c34bd4 100644 --- a/develop/doc/_sources/api/v2/config/layer.rst.txt +++ b/develop/doc/_sources/api/v2/config/layer.rst.txt @@ -467,7 +467,7 @@ lambda_cost :noindex: square_error_cost --------- +----------------- .. autoclass:: paddle.v2.layer.square_error_cost :noindex: @@ -533,7 +533,7 @@ Miscs ===== dropout --------------- +-------- .. autoclass:: paddle.v2.layer.dropout :noindex: diff --git a/develop/doc/_sources/api/v2/fluid/layers.rst.txt b/develop/doc/_sources/api/v2/fluid/layers.rst.txt index 842f3b18007a55fb538fbe5d5fefc3f4b75ebe14..b25009310c96c22453b2931f25ca6c1942c0bc0b 100644 --- a/develop/doc/_sources/api/v2/fluid/layers.rst.txt +++ b/develop/doc/_sources/api/v2/fluid/layers.rst.txt @@ -19,17 +19,17 @@ dynamic_lstm :noindex: data ---------- +---- .. autofunction:: paddle.v2.fluid.layers.data :noindex: mean ---------- +---- .. autofunction:: paddle.v2.fluid.layers.mean :noindex: mul ---------- +--- .. autofunction:: paddle.v2.fluid.layers.mul :noindex: @@ -45,13 +45,13 @@ elementwise_div dropout ---------- +------- .. autofunction:: paddle.v2.fluid.layers.dropout :noindex: reshape ---------- +-------- .. autofunction:: paddle.v2.fluid.layers.reshape :noindex: @@ -81,67 +81,67 @@ transpose sigmoid_cross_entropy_with_logits ---------- +--------------------------------- .. autofunction:: paddle.v2.fluid.layers.esigmoid_cross_entropy_with_logits :noindex: cast ---------- +---- .. autofunction:: paddle.v2.fluid.layers.cast :noindex: concat ---------- +------- .. autofunction:: paddle.v2.fluid.layers.concat :noindex: sums ---------- +---- .. autofunction:: paddle.v2.fluid.layers.sums :noindex: linear_chain_crf ---------- +---------------- .. autofunction:: paddle.v2.fluid.layers.linear_chain_crf :noindex: assign ---------- +------- .. autofunction:: paddle.v2.fluid.layers.embedding :noindex: split_lod_tensor ---------- +---------------- .. autofunction:: paddle.v2.fluid.layers.split_lod_tensor :noindex: merge_lod_tensor ---------- +---------------- .. autofunction:: paddle.v2.fluid.layers.merge_lod_tensor :noindex: cos_sim ---------- +-------- .. autofunction:: paddle.v2.fluid.layers.cos_sim :noindex: cross_entropy ---------- +------------- .. autofunction:: paddle.v2.fluid.layers.cross_entropy :noindex: square_error_cost ---------- +----------------- .. autofunction:: paddle.v2.fluid.layers.square_error_cost :noindex: @@ -153,68 +153,68 @@ accuracy sequence_conv ---------- +------------- .. autofunction:: paddle.v2.fluid.layers.sequence_conv :noindex: conv2d ---------- +------ .. autofunction:: paddle.v2.fluid.layers.conv2d :noindex: sequence_pool ---------- +------------- .. autofunction:: paddle.v2.fluid.layers.sequence_pool :noindex: pool2d ---------- +------ .. autofunction:: paddle.v2.fluid.layers.pool2d :noindex: batch_norm ---------- +---------- .. autofunction:: paddle.v2.fluid.layers.batch_norm :noindex: beam_search_decode ---------- +------------------ .. autofunction:: paddle.v2.fluid.layers.beam_search_decode :noindex: lod_rank_table ---------- +-------------- .. autofunction:: paddle.v2.fluid.layers.lod_rank_table :noindex: max_sequence_len ---------- +---------------- .. autofunction:: paddle.v2.fluid.layers.max_sequence_len :noindex: topk ---------- +----- .. autofunction:: paddle.v2.fluid.layers.topk :noindex: lod_tensor_to_array ---------- +------------------- .. autofunction:: paddle.v2.fluid.layers.lod_tensor_to_array :noindex: array_to_lod_tensor ---------- +------------------- .. autofunction:: paddle.v2.fluid.layers.array_to_lod_tensor :noindex: @@ -222,26 +222,26 @@ array_to_lod_tensor fill_constant ---------- +------------- .. autofunction:: paddle.v2.fluid.layers.fill_constant :noindex: fill_constant_batch_size_like ---------- +----------------------------- .. autofunction:: paddle.v2.fluid.layers.fill_constant_batch_size_like :noindex: ones ---------- +---- .. autofunction:: paddle.v2.fluid.layers.ones :noindex: zeros ---------- +----- .. autofunction:: paddle.v2.fluid.layers.zeros :noindex: @@ -253,14 +253,14 @@ increment array_write ---------- +----------- .. autofunction:: paddle.v2.fluid.layers.array_write :noindex: create_array ---------- +------------ .. autofunction:: paddle.v2.fluid.layers.create_array :noindex: @@ -272,31 +272,31 @@ less_than array_read ---------- +---------- .. autofunction:: paddle.v2.fluid.layers.array_read :noindex: shrink_memory ---------- +-------------- .. autofunction:: paddle.v2.fluid.layers.shrink_memory :noindex: array_length ---------- +------------- .. autofunction:: paddle.v2.fluid.layers.array_length :noindex: conv2d_transpose ---------- +---------------- .. autofunction:: paddle.v2.fluid.layers.conv2d_transpose :noindex: sequence_expand ---------- +--------------- .. autofunction:: paddle.v2.fluid.layers.sequence_expand :noindex: @@ -308,13 +308,13 @@ lstm_unit sequence_softmax ---------- +---------------- .. autofunction:: paddle.v2.fluid.layers.sequence_softmax :noindex: reduce_sum ---------- +---------- .. autofunction:: paddle.v2.fluid.layers.reduce_sum :noindex: diff --git a/develop/doc/_sources/api/v2/fluid/nets.rst.txt b/develop/doc/_sources/api/v2/fluid/nets.rst.txt index 2c3d075422de29c96e25458e831133a30270dd39..b792efb71f85ae643df655568da69c82414e9d5d 100644 --- a/develop/doc/_sources/api/v2/fluid/nets.rst.txt +++ b/develop/doc/_sources/api/v2/fluid/nets.rst.txt @@ -3,19 +3,19 @@ Nets =========== simple_img_conv_pool ------------ +-------------------- .. autofunction:: paddle.v2.fluid.nets.simple_img_conv_pool :noindex: img_conv_group ------------ +--------------- .. autofunction:: paddle.v2.fluid.nets.img_conv_group :noindex: sequence_conv_pool ------------ +------------------ .. autofunction:: paddle.v2.fluid.nets.sequence_conv_pool :noindex: diff --git a/develop/doc/_sources/api/v2/fluid/optimizer.rst.txt b/develop/doc/_sources/api/v2/fluid/optimizer.rst.txt index 233762fcdfb39e592740adef6721a556fae3feef..19b4940f08de3e2f7dc177f2961e538946d10a78 100644 --- a/develop/doc/_sources/api/v2/fluid/optimizer.rst.txt +++ b/develop/doc/_sources/api/v2/fluid/optimizer.rst.txt @@ -18,7 +18,7 @@ SGDOptimizer MomentumOptimizer ------------ +----------------- .. automodule:: paddle.v2.fluid.optimizer :members: MomentumOptimizer :noindex: @@ -26,14 +26,14 @@ MomentumOptimizer AdagradOptimizer ------------ +---------------- .. automodule:: paddle.v2.fluid.optimizer :members: AdagradOptimizer :noindex: AdamOptimizer ------------ +------------- .. automodule:: paddle.v2.fluid.optimizer :members: AdamOptimizer :noindex: @@ -47,7 +47,7 @@ AdamaxOptimizer DecayedAdagradOptimizer ------------ +----------------------- .. automodule:: paddle.v2.fluid.optimizer :members: DecayedAdagradOptimizer :noindex: diff --git a/develop/doc/_sources/api/v2/fluid/regularizer.rst.txt b/develop/doc/_sources/api/v2/fluid/regularizer.rst.txt index 3af2b07d2ae55d99df705fbf1ad2402eee05c435..868e225ed3d59e79aeb217fb88081ea25f80fa2c 100644 --- a/develop/doc/_sources/api/v2/fluid/regularizer.rst.txt +++ b/develop/doc/_sources/api/v2/fluid/regularizer.rst.txt @@ -3,14 +3,14 @@ Regularizer =========== WeightDecayRegularizer ------------ +---------------------- .. automodule:: paddle.v2.fluid.regularizer :members: WeightDecayRegularizer :noindex: L2DecayRegularizer ------------ +------------------ .. automodule:: paddle.v2.fluid.regularizer :members: L2DecayRegularizer :noindex: @@ -18,7 +18,7 @@ L2DecayRegularizer L1DecayRegularizer ------------ +------------------- .. automodule:: paddle.v2.fluid.regularizer :members: L1DecayRegularizer diff --git a/develop/doc/api/v2/fluid/layers.html b/develop/doc/api/v2/fluid/layers.html index 0e32789e9806aa906b845d73fa839ca8c5287923..5a6980c6566daa6b8ef34c493a99eee746e3e793 100644 --- a/develop/doc/api/v2/fluid/layers.html +++ b/develop/doc/api/v2/fluid/layers.html @@ -222,55 +222,83 @@
paddle.v2.fluid.layers.fc(input, size, num_flatten_dims=1, param_attr=None, bias_attr=None, act=None, name=None)
-

Fully Connected Layer

-

This layer accepts multiple inputs and applies a linear transformation to each input. -If activation type is provided, the corresponding activation function is applied to the -output of the linear transformation. For each input \(X\), the equation is:

+
+

Fully Connected Layer

+

The fully connected layer can take multiple tensors as its inputs. It +creates a variable (one for each input tensor) called weights for each input +tensor, which represents a fully connected weight matrix from each input +unit to each output unit. The fully connected layer multiplies each input +tensor with its coresponding weight to produce an output Tensor. If +multiple input tensors are given, the results of multiple multiplications +will be sumed up. If bias_attr is not None, a biases variable will be +created and added to the output. Finally, if activation is not None, +it will be applied to the output as well.

+

This process can be formulated as follows:

-\[Out = Act(WX + b)\]
-

In the above equation:

-
-
    -
  • \(X\): Input value, a tensor with rank at least 2.
    • -
  • \(W\): Weight, a 2-D tensor with shape [M, N].
    • -
  • \(b\): Bias, a 2-D tensor with shape [M, 1].
    • -
  • \(Act\): Activation function.
    • -
  • \(Out\): Output value, same shape with \(X\).
    • -
+\[Out = Act\left({\sum_{i=0}^{N-1}W_iX_i + b}\]
-

All the input variables are passed in as local variables to the LayerHelper -constructor.

- --- - - - - - - - - - -
Parameters:
    -
  • input (Variable|list) – Input tensors. Each tensor has a rank of atleast 2
    • -
  • size (int) – Output size
    • -
  • num_flatten_dims (int) – Number of columns in input
    • -
  • param_attr (ParamAttr|list) – The parameters/weights to the FC Layer
    • -
  • bias_attr (ParamAttr|list) – Bias parameter for the FC layer
    • -
  • act (str) – Activation type
    • -
  • name (str) – Name/alias of the function
    • +

    ight)

    +
    +

    In the above equation:

    +
      +
    • \(N\): Number of the input.
      • +
    • \(X_i\): The input tensor.
      • +
    • \(W\): The weights created by this layer.
      • +
    • \(b\): The bias parameter created by this layer (if needed).
      • +
    • \(Act\): The activation funtion.
      • +
    • \(Out\): The output tensor.
    -
Returns:

The tensor variable storing the transformation and non-linearity activation result.

-
Return type:

Variable

-
Raises:

ValueError – If rank of input tensor is less than 2.

-
-

Examples

-
data = fluid.layers.data(name='data', shape=[32, 32], dtype='float32')
+

+
Args:

+
input(Variable|list): The input tensor(s) to the fully connected layer.
+size(int): The number of output units in the fully connected layer.
+num_flatten_dims(int): The fc layer can accept an input tensor with more

+

+
than two dimensions. If this happens, the
+multidimensional tensor will first be flattened
+into a 2-dimensional matrix. The parameter
+num_flatten_dims determines how the input tensor
+is flattened: the first num_flatten_dims
+dimensions will be flatten to form the first
+dimension of the final matrix (height of the
+matrix), and the rest rank(X) - num_col_dims
+dimensions are flattened to form the second
+dimension of the final matrix (width of the matrix).
+For example, suppose X is a 6-dimensional tensor
+with a shape [2, 3, 4, 5, 6], and
+x_num_col_dims = 3. Then, the flattened matrix
+will have a shape [2 x 3 x 4, 5 x 6] = [24, 30].
+By default, x_num_col_dims is set to 1.

+

+
param_attr(ParamAttr|list): The parameter attribute for learnable

+
parameters/weights of the fully connected
+layer.

+
param_initializer(ParamAttr|list): The initializer used for the

+
weight/parameter. If set None,
+XavierInitializer() will be used.

+
bias_attr(ParamAttr|list): The parameter attribute for the bias parameter

+
for this layer. If set None, no bias will be
+added to the output units.

+
bias_initializer(ParamAttr|list): The initializer used for the bias.

+
If set None, then ConstantInitializer()
+will be used.

+
act(str): Activation to be applied to the output of the fully connected

+
layer.

+

+
name(str): Name/alias of the fully connected layer.

+

+
Returns:

+
Variable: The output tensor variable.

+
Raises:

+
ValueError: If rank of the input tensor is less than 2.

+
Examples:

+
data = fluid.layers.data(name="data", shape=[32, 32], dtype="float32")
 fc = fluid.layers.fc(input=data, size=1000, act="tanh")
 

 

+

+

+
@@ -392,32 +420,45 @@ Duplicable: False Optional: False
paddle.v2.fluid.layers.mul(**kwargs)

Mul Operator.

-

This operator is used to perform matrix multiplication for input X and Y.

+

This operator is used to perform matrix multiplication for input $X$ and $Y$.

The equation is:

$$Out = X * Y$$
-

Both the input X and Y can carry the LoD (Level of Details) information, -or not. But the output only shares the LoD information with input X.

+

Both the input $X$ and $Y$ can carry the LoD (Level of Details) information, +or not. But the output only shares the LoD information with input $X$.

- diff --git a/develop/doc/api/v2/fluid/regularizer.html b/develop/doc/api/v2/fluid/regularizer.html index 3596a2553a48b5685fba1e7d051d6f83ebed5639..e97676740b058288ab283aaed68236051fc1d1cb 100644 --- a/develop/doc/api/v2/fluid/regularizer.html +++ b/develop/doc/api/v2/fluid/regularizer.html @@ -241,9 +241,9 @@ of its implementations

-
-

L1DecayRegularizer

-
+
+

L1DecayRegularizer

+
class paddle.v2.fluid.regularizer.L1DecayRegularizer(regularization_coeff=0.0)

Implements the L1 Weight Decay Regularization

diff --git a/develop/doc/operators.json b/develop/doc/operators.json index 0cb5ec825400cdb77537051056a26dd1f4708774..f3bc22319f4d8b157fc678beccc33d175a936ea0 100644 --- a/develop/doc/operators.json +++ b/develop/doc/operators.json @@ -1212,23 +1212,23 @@ } ] },{ "type" : "mul", - "comment" : "\nMul Operator. \n\nThis operator is used to perform matrix multiplication for input X and Y.\n\nThe equation is:\n\n $$Out = X * Y$$\n\nBoth the input `X` and `Y` can carry the LoD (Level of Details) information,\nor not. But the output only shares the LoD information with input `X`.\n\n", + "comment" : "\nMul Operator.\n\nThis operator is used to perform matrix multiplication for input $X$ and $Y$.\n\nThe equation is:\n\n $$Out = X * Y$$\n\nBoth the input $X$ and $Y$ can carry the LoD (Level of Details) information,\nor not. But the output only shares the LoD information with input $X$.\n\n", "inputs" : [ { "name" : "X", - "comment" : "The first input of mul op", + "comment" : "(Tensor), The first input tensor of mul op.", "duplicable" : 0, "intermediate" : 0 }, { "name" : "Y", - "comment" : "The second input of mul op", + "comment" : "(Tensor), The second input tensor of mul op.", "duplicable" : 0, "intermediate" : 0 } ], "outputs" : [ { "name" : "Out", - "comment" : "The output of mul op", + "comment" : "(Tensor), The output tensor of mul op.", "duplicable" : 0, "intermediate" : 0 } ], @@ -1236,12 +1236,12 @@ { "name" : "x_num_col_dims", "type" : "int", - "comment" : "(int, default 1) mul_op can take tensors with more than two dimensions as input `X`,\n in that case, tensors will be reshaped to a matrix. The matrix's first\n dimension(column length) will be the product of tensor's last\n `num_col_dims` dimensions, and the matrix's second dimension(row length)\n will be the product of tensor's first `rank - num_col_dims` dimensions.\n ", + "comment" : "(int, default 1), The mul_op can take tensors with more than two\n dimensions as its inputs. If the input $X$ is a tensor with more\n than two dimensions, $X$ will be flattened into a two-dimensional\n matrix first. The flattening rule is: the first `num_col_dims`\n will be flattened to form the first dimension of the final matrix\n (the height of the matrix), and the rest `rank(X) - num_col_dims`\n dimensions are flattened to form the second dimension of the final\n matrix (the width of the matrix). As a result, height of the\n flattened matrix is equal to the product of $X$'s first\n `x_num_col_dims` dimensions' sizes, and width of the flattened\n matrix is equal to the product of $X$'s last `rank(x) - num_col_dims`\n dimensions' size. For example, suppose $X$ is a 6-dimensional\n tensor with the shape [2, 3, 4, 5, 6], and `x_num_col_dims` = 3.\n Thus, the flattened matrix will have a shape [2 x 3 x 4, 5 x 6] =\n [24, 30].\n ", "generated" : 0 }, { "name" : "y_num_col_dims", "type" : "int", - "comment" : "(int, default 1) mul_op can take tensors with more than two dimensions as input `Y`,\n in that case, tensors will be reshaped to a matrix. Just like input `X`.\n ", + "comment" : "(int, default 1), The mul_op can take tensors with more than two,\n dimensions as its inputs. If the input $Y$ is a tensor with more\n than two dimensions, $Y$ will be flattened into a two-dimensional\n matrix first. The attribute `y_num_col_dims` determines how $Y$ is\n flattened. See comments of `x_num_col_dims` for more details.\n ", "generated" : 0 } ] },{ diff --git a/develop/doc/searchindex.js b/develop/doc/searchindex.js index dd192ec41ea22796fbcf532ba5ebb4a2b7ddbf89..31bed3feec8af55910b2b50b7e081ae5e869b54c 100644 --- a/develop/doc/searchindex.js +++ b/develop/doc/searchindex.js @@ -1 +1 @@ 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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 c3f9c18d0663a7a24880b441981875c1e4f015aa..d81481ca819c13ee0e299c204f998f3915c34bd4 100644 --- a/develop/doc_cn/_sources/api/v2/config/layer.rst.txt +++ b/develop/doc_cn/_sources/api/v2/config/layer.rst.txt @@ -467,7 +467,7 @@ lambda_cost :noindex: square_error_cost --------- +----------------- .. autoclass:: paddle.v2.layer.square_error_cost :noindex: @@ -533,7 +533,7 @@ Miscs ===== dropout --------------- +-------- .. autoclass:: paddle.v2.layer.dropout :noindex: diff --git a/develop/doc_cn/_sources/api/v2/fluid/layers.rst.txt b/develop/doc_cn/_sources/api/v2/fluid/layers.rst.txt index 842f3b18007a55fb538fbe5d5fefc3f4b75ebe14..b25009310c96c22453b2931f25ca6c1942c0bc0b 100644 --- a/develop/doc_cn/_sources/api/v2/fluid/layers.rst.txt +++ b/develop/doc_cn/_sources/api/v2/fluid/layers.rst.txt @@ -19,17 +19,17 @@ dynamic_lstm :noindex: data ---------- +---- .. autofunction:: paddle.v2.fluid.layers.data :noindex: mean ---------- +---- .. autofunction:: paddle.v2.fluid.layers.mean :noindex: mul ---------- +--- .. autofunction:: paddle.v2.fluid.layers.mul :noindex: @@ -45,13 +45,13 @@ elementwise_div dropout ---------- +------- .. autofunction:: paddle.v2.fluid.layers.dropout :noindex: reshape ---------- +-------- .. autofunction:: paddle.v2.fluid.layers.reshape :noindex: @@ -81,67 +81,67 @@ transpose sigmoid_cross_entropy_with_logits ---------- +--------------------------------- .. autofunction:: paddle.v2.fluid.layers.esigmoid_cross_entropy_with_logits :noindex: cast ---------- +---- .. autofunction:: paddle.v2.fluid.layers.cast :noindex: concat ---------- +------- .. autofunction:: paddle.v2.fluid.layers.concat :noindex: sums ---------- +---- .. autofunction:: paddle.v2.fluid.layers.sums :noindex: linear_chain_crf ---------- +---------------- .. autofunction:: paddle.v2.fluid.layers.linear_chain_crf :noindex: assign ---------- +------- .. autofunction:: paddle.v2.fluid.layers.embedding :noindex: split_lod_tensor ---------- +---------------- .. autofunction:: paddle.v2.fluid.layers.split_lod_tensor :noindex: merge_lod_tensor ---------- +---------------- .. autofunction:: paddle.v2.fluid.layers.merge_lod_tensor :noindex: cos_sim ---------- +-------- .. autofunction:: paddle.v2.fluid.layers.cos_sim :noindex: cross_entropy ---------- +------------- .. autofunction:: paddle.v2.fluid.layers.cross_entropy :noindex: square_error_cost ---------- +----------------- .. autofunction:: paddle.v2.fluid.layers.square_error_cost :noindex: @@ -153,68 +153,68 @@ accuracy sequence_conv ---------- +------------- .. autofunction:: paddle.v2.fluid.layers.sequence_conv :noindex: conv2d ---------- +------ .. autofunction:: paddle.v2.fluid.layers.conv2d :noindex: sequence_pool ---------- +------------- .. autofunction:: paddle.v2.fluid.layers.sequence_pool :noindex: pool2d ---------- +------ .. autofunction:: paddle.v2.fluid.layers.pool2d :noindex: batch_norm ---------- +---------- .. autofunction:: paddle.v2.fluid.layers.batch_norm :noindex: beam_search_decode ---------- +------------------ .. autofunction:: paddle.v2.fluid.layers.beam_search_decode :noindex: lod_rank_table ---------- +-------------- .. autofunction:: paddle.v2.fluid.layers.lod_rank_table :noindex: max_sequence_len ---------- +---------------- .. autofunction:: paddle.v2.fluid.layers.max_sequence_len :noindex: topk ---------- +----- .. autofunction:: paddle.v2.fluid.layers.topk :noindex: lod_tensor_to_array ---------- +------------------- .. autofunction:: paddle.v2.fluid.layers.lod_tensor_to_array :noindex: array_to_lod_tensor ---------- +------------------- .. autofunction:: paddle.v2.fluid.layers.array_to_lod_tensor :noindex: @@ -222,26 +222,26 @@ array_to_lod_tensor fill_constant ---------- +------------- .. autofunction:: paddle.v2.fluid.layers.fill_constant :noindex: fill_constant_batch_size_like ---------- +----------------------------- .. autofunction:: paddle.v2.fluid.layers.fill_constant_batch_size_like :noindex: ones ---------- +---- .. autofunction:: paddle.v2.fluid.layers.ones :noindex: zeros ---------- +----- .. autofunction:: paddle.v2.fluid.layers.zeros :noindex: @@ -253,14 +253,14 @@ increment array_write ---------- +----------- .. autofunction:: paddle.v2.fluid.layers.array_write :noindex: create_array ---------- +------------ .. autofunction:: paddle.v2.fluid.layers.create_array :noindex: @@ -272,31 +272,31 @@ less_than array_read ---------- +---------- .. autofunction:: paddle.v2.fluid.layers.array_read :noindex: shrink_memory ---------- +-------------- .. autofunction:: paddle.v2.fluid.layers.shrink_memory :noindex: array_length ---------- +------------- .. autofunction:: paddle.v2.fluid.layers.array_length :noindex: conv2d_transpose ---------- +---------------- .. autofunction:: paddle.v2.fluid.layers.conv2d_transpose :noindex: sequence_expand ---------- +--------------- .. autofunction:: paddle.v2.fluid.layers.sequence_expand :noindex: @@ -308,13 +308,13 @@ lstm_unit sequence_softmax ---------- +---------------- .. autofunction:: paddle.v2.fluid.layers.sequence_softmax :noindex: reduce_sum ---------- +---------- .. autofunction:: paddle.v2.fluid.layers.reduce_sum :noindex: diff --git a/develop/doc_cn/_sources/api/v2/fluid/nets.rst.txt b/develop/doc_cn/_sources/api/v2/fluid/nets.rst.txt index 2c3d075422de29c96e25458e831133a30270dd39..b792efb71f85ae643df655568da69c82414e9d5d 100644 --- a/develop/doc_cn/_sources/api/v2/fluid/nets.rst.txt +++ b/develop/doc_cn/_sources/api/v2/fluid/nets.rst.txt @@ -3,19 +3,19 @@ Nets =========== simple_img_conv_pool ------------ +-------------------- .. autofunction:: paddle.v2.fluid.nets.simple_img_conv_pool :noindex: img_conv_group ------------ +--------------- .. autofunction:: paddle.v2.fluid.nets.img_conv_group :noindex: sequence_conv_pool ------------ +------------------ .. autofunction:: paddle.v2.fluid.nets.sequence_conv_pool :noindex: diff --git a/develop/doc_cn/_sources/api/v2/fluid/optimizer.rst.txt b/develop/doc_cn/_sources/api/v2/fluid/optimizer.rst.txt index 233762fcdfb39e592740adef6721a556fae3feef..19b4940f08de3e2f7dc177f2961e538946d10a78 100644 --- a/develop/doc_cn/_sources/api/v2/fluid/optimizer.rst.txt +++ b/develop/doc_cn/_sources/api/v2/fluid/optimizer.rst.txt @@ -18,7 +18,7 @@ SGDOptimizer MomentumOptimizer ------------ +----------------- .. automodule:: paddle.v2.fluid.optimizer :members: MomentumOptimizer :noindex: @@ -26,14 +26,14 @@ MomentumOptimizer AdagradOptimizer ------------ +---------------- .. automodule:: paddle.v2.fluid.optimizer :members: AdagradOptimizer :noindex: AdamOptimizer ------------ +------------- .. automodule:: paddle.v2.fluid.optimizer :members: AdamOptimizer :noindex: @@ -47,7 +47,7 @@ AdamaxOptimizer DecayedAdagradOptimizer ------------ +----------------------- .. automodule:: paddle.v2.fluid.optimizer :members: DecayedAdagradOptimizer :noindex: diff --git a/develop/doc_cn/_sources/api/v2/fluid/regularizer.rst.txt b/develop/doc_cn/_sources/api/v2/fluid/regularizer.rst.txt index 3af2b07d2ae55d99df705fbf1ad2402eee05c435..868e225ed3d59e79aeb217fb88081ea25f80fa2c 100644 --- a/develop/doc_cn/_sources/api/v2/fluid/regularizer.rst.txt +++ b/develop/doc_cn/_sources/api/v2/fluid/regularizer.rst.txt @@ -3,14 +3,14 @@ Regularizer =========== WeightDecayRegularizer ------------ +---------------------- .. automodule:: paddle.v2.fluid.regularizer :members: WeightDecayRegularizer :noindex: L2DecayRegularizer ------------ +------------------ .. automodule:: paddle.v2.fluid.regularizer :members: L2DecayRegularizer :noindex: @@ -18,7 +18,7 @@ L2DecayRegularizer L1DecayRegularizer ------------ +------------------- .. automodule:: paddle.v2.fluid.regularizer :members: L1DecayRegularizer diff --git a/develop/doc_cn/api/v2/fluid/layers.html b/develop/doc_cn/api/v2/fluid/layers.html index 48e8fbc99cc832e44b4897ac59ee58d94191100d..d962453d5a4f472053f78ef9af4731bdc4eb87d5 100644 --- a/develop/doc_cn/api/v2/fluid/layers.html +++ b/develop/doc_cn/api/v2/fluid/layers.html @@ -235,55 +235,83 @@
paddle.v2.fluid.layers.fc(input, size, num_flatten_dims=1, param_attr=None, bias_attr=None, act=None, name=None)
-

Fully Connected Layer

-

This layer accepts multiple inputs and applies a linear transformation to each input. -If activation type is provided, the corresponding activation function is applied to the -output of the linear transformation. For each input \(X\), the equation is:

+
+

Fully Connected Layer

+

The fully connected layer can take multiple tensors as its inputs. It +creates a variable (one for each input tensor) called weights for each input +tensor, which represents a fully connected weight matrix from each input +unit to each output unit. The fully connected layer multiplies each input +tensor with its coresponding weight to produce an output Tensor. If +multiple input tensors are given, the results of multiple multiplications +will be sumed up. If bias_attr is not None, a biases variable will be +created and added to the output. Finally, if activation is not None, +it will be applied to the output as well.

+

This process can be formulated as follows:

-\[Out = Act(WX + b)\]
-

In the above equation:

-
-
    -
  • \(X\): Input value, a tensor with rank at least 2.
    • -
  • \(W\): Weight, a 2-D tensor with shape [M, N].
    • -
  • \(b\): Bias, a 2-D tensor with shape [M, 1].
    • -
  • \(Act\): Activation function.
    • -
  • \(Out\): Output value, same shape with \(X\).
    • -
+\[Out = Act\left({\sum_{i=0}^{N-1}W_iX_i + b}\]
-

All the input variables are passed in as local variables to the LayerHelper -constructor.

-
Parameters:
    -
  • x – The first input of mul op +
  • x – (Tensor), The first input tensor of mul op. Duplicable: False Optional: False
    • -
  • y – The second input of mul op +
  • y – (Tensor), The second input tensor of mul op. Duplicable: False Optional: False
    • -
  • x_num_col_dims (INT) – (int, default 1) mul_op can take tensors with more than two dimensions as input X, -in that case, tensors will be reshaped to a matrix. The matrix’s first -dimension(column length) will be the product of tensor’s last -num_col_dims dimensions, and the matrix’s second dimension(row length) -will be the product of tensor’s first rank - num_col_dims dimensions.
    • -
  • y_num_col_dims (INT) – (int, default 1) mul_op can take tensors with more than two dimensions as input Y, -in that case, tensors will be reshaped to a matrix. Just like input X.
    • +
  • x_num_col_dims (INT) – (int, default 1), The mul_op can take tensors with more than two +dimensions as its inputs. If the input $X$ is a tensor with more +than two dimensions, $X$ will be flattened into a two-dimensional +matrix first. The flattening rule is: the first num_col_dims +will be flattened to form the first dimension of the final matrix +(the height of the matrix), and the rest rank(X) - num_col_dims +dimensions are flattened to form the second dimension of the final +matrix (the width of the matrix). As a result, height of the +flattened matrix is equal to the product of $X$’s first +x_num_col_dims dimensions’ sizes, and width of the flattened +matrix is equal to the product of $X$’s last rank(x) - num_col_dims +dimensions’ size. For example, suppose $X$ is a 6-dimensional +tensor with the shape [2, 3, 4, 5, 6], and x_num_col_dims = 3. +Thus, the flattened matrix will have a shape [2 x 3 x 4, 5 x 6] = +[24, 30].
    • +
  • y_num_col_dims (INT) – (int, default 1), The mul_op can take tensors with more than two, +dimensions as its inputs. If the input $Y$ is a tensor with more +than two dimensions, $Y$ will be flattened into a two-dimensional +matrix first. The attribute y_num_col_dims determines how $Y$ is +flattened. See comments of x_num_col_dims for more details.
Returns:

The output of mul op

+
Returns:

(Tensor), The output tensor of mul op.
--- - - - - - - - - - -
参数:
    -
  • input (Variable|list) – Input tensors. Each tensor has a rank of atleast 2
    • -
  • size (int) – Output size
    • -
  • num_flatten_dims (int) – Number of columns in input
    • -
  • param_attr (ParamAttr|list) – The parameters/weights to the FC Layer
    • -
  • bias_attr (ParamAttr|list) – Bias parameter for the FC layer
    • -
  • act (str) – Activation type
    • -
  • name (str) – Name/alias of the function
    • +

    ight)

    +
    +

    In the above equation:

    +
      +
    • \(N\): Number of the input.
      • +
    • \(X_i\): The input tensor.
      • +
    • \(W\): The weights created by this layer.
      • +
    • \(b\): The bias parameter created by this layer (if needed).
      • +
    • \(Act\): The activation funtion.
      • +
    • \(Out\): The output tensor.
    -
返回:

The tensor variable storing the transformation and non-linearity activation result.

-
返回类型:

Variable

-
Raises:

ValueError – If rank of input tensor is less than 2.

-
-

Examples

-
data = fluid.layers.data(name='data', shape=[32, 32], dtype='float32')
+

+
Args:

+
input(Variable|list): The input tensor(s) to the fully connected layer.
+size(int): The number of output units in the fully connected layer.
+num_flatten_dims(int): The fc layer can accept an input tensor with more

+

+
than two dimensions. If this happens, the
+multidimensional tensor will first be flattened
+into a 2-dimensional matrix. The parameter
+num_flatten_dims determines how the input tensor
+is flattened: the first num_flatten_dims
+dimensions will be flatten to form the first
+dimension of the final matrix (height of the
+matrix), and the rest rank(X) - num_col_dims
+dimensions are flattened to form the second
+dimension of the final matrix (width of the matrix).
+For example, suppose X is a 6-dimensional tensor
+with a shape [2, 3, 4, 5, 6], and
+x_num_col_dims = 3. Then, the flattened matrix
+will have a shape [2 x 3 x 4, 5 x 6] = [24, 30].
+By default, x_num_col_dims is set to 1.

+

+
param_attr(ParamAttr|list): The parameter attribute for learnable

+
parameters/weights of the fully connected
+layer.

+
param_initializer(ParamAttr|list): The initializer used for the

+
weight/parameter. If set None,
+XavierInitializer() will be used.

+
bias_attr(ParamAttr|list): The parameter attribute for the bias parameter

+
for this layer. If set None, no bias will be
+added to the output units.

+
bias_initializer(ParamAttr|list): The initializer used for the bias.

+
If set None, then ConstantInitializer()
+will be used.

+
act(str): Activation to be applied to the output of the fully connected

+
layer.

+

+
name(str): Name/alias of the fully connected layer.

+

+
Returns:

+
Variable: The output tensor variable.

+
Raises:

+
ValueError: If rank of the input tensor is less than 2.

+
Examples:

+
data = fluid.layers.data(name="data", shape=[32, 32], dtype="float32")
 fc = fluid.layers.fc(input=data, size=1000, act="tanh")
 

 

+

+

+
@@ -405,32 +433,45 @@ Duplicable: False Optional: False
paddle.v2.fluid.layers.mul(**kwargs)

Mul Operator.

-

This operator is used to perform matrix multiplication for input X and Y.

+

This operator is used to perform matrix multiplication for input $X$ and $Y$.

The equation is:

$$Out = X * Y$$
-

Both the input X and Y can carry the LoD (Level of Details) information, -or not. But the output only shares the LoD information with input X.

+

Both the input $X$ and $Y$ can carry the LoD (Level of Details) information, +or not. But the output only shares the LoD information with input $X$.

- diff --git a/develop/doc_cn/api/v2/fluid/regularizer.html b/develop/doc_cn/api/v2/fluid/regularizer.html index db8023e8d1766c175f30f4e44e7674380c1249ff..4719ef143e8d0dc67d992e000e40b140ae6ff99d 100644 --- a/develop/doc_cn/api/v2/fluid/regularizer.html +++ b/develop/doc_cn/api/v2/fluid/regularizer.html @@ -254,9 +254,9 @@ of its implementations

-
-

L1DecayRegularizer

-
+
+

L1DecayRegularizer

+
class paddle.v2.fluid.regularizer.L1DecayRegularizer(regularization_coeff=0.0)

Implements the L1 Weight Decay Regularization

diff --git a/develop/doc_cn/searchindex.js b/develop/doc_cn/searchindex.js index 09ed6026db8a4fdab3aa4a2ce2265e1b26d7499b..f7aa76e69543bc57cb54b96c49f27a256edeefc9 100644 --- a/develop/doc_cn/searchindex.js +++ b/develop/doc_cn/searchindex.js @@ -1 +1 @@ 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\ No newline at end of file
参数:
    -
  • x – The first input of mul op +
  • x – (Tensor), The first input tensor of mul op. Duplicable: False Optional: False
    • -
  • y – The second input of mul op +
  • y – (Tensor), The second input tensor of mul op. Duplicable: False Optional: False
    • -
  • x_num_col_dims (INT) – (int, default 1) mul_op can take tensors with more than two dimensions as input X, -in that case, tensors will be reshaped to a matrix. The matrix’s first -dimension(column length) will be the product of tensor’s last -num_col_dims dimensions, and the matrix’s second dimension(row length) -will be the product of tensor’s first rank - num_col_dims dimensions.
    • -
  • y_num_col_dims (INT) – (int, default 1) mul_op can take tensors with more than two dimensions as input Y, -in that case, tensors will be reshaped to a matrix. Just like input X.
    • +
  • x_num_col_dims (INT) – (int, default 1), The mul_op can take tensors with more than two +dimensions as its inputs. If the input $X$ is a tensor with more +than two dimensions, $X$ will be flattened into a two-dimensional +matrix first. The flattening rule is: the first num_col_dims +will be flattened to form the first dimension of the final matrix +(the height of the matrix), and the rest rank(X) - num_col_dims +dimensions are flattened to form the second dimension of the final +matrix (the width of the matrix). As a result, height of the +flattened matrix is equal to the product of $X$’s first +x_num_col_dims dimensions’ sizes, and width of the flattened +matrix is equal to the product of $X$’s last rank(x) - num_col_dims +dimensions’ size. For example, suppose $X$ is a 6-dimensional +tensor with the shape [2, 3, 4, 5, 6], and x_num_col_dims = 3. +Thus, the flattened matrix will have a shape [2 x 3 x 4, 5 x 6] = +[24, 30].
    • +
  • y_num_col_dims (INT) – (int, default 1), The mul_op can take tensors with more than two, +dimensions as its inputs. If the input $Y$ is a tensor with more +than two dimensions, $Y$ will be flattened into a two-dimensional +matrix first. The attribute y_num_col_dims determines how $Y$ is +flattened. See comments of x_num_col_dims for more details.
返回:

The output of mul op

+
返回:

(Tensor), The output tensor of mul op.