diff --git a/develop/doc/api/v1/trainer_config_helpers/layers.html b/develop/doc/api/v1/trainer_config_helpers/layers.html index 93a906915aac6a3f4816a074ed3f34d03b930237..5fa458b37d96cac805275dac964a2a5675b7e0ca 100644 --- a/develop/doc/api/v1/trainer_config_helpers/layers.html +++ b/develop/doc/api/v1/trainer_config_helpers/layers.html @@ -388,6 +388,12 @@ reasons.

+
+
+set_input(input)
+

Set the input for a memory layer. Can only be used for memory layer

+
+ @@ -1269,7 +1275,7 @@ will get a warning.

memoryΒΆ

-paddle.trainer_config_helpers.layers.memory(name, size, is_seq=False, boot_layer=None, boot_bias=None, boot_bias_active_type=None, boot_with_const_id=None)
+paddle.trainer_config_helpers.layers.memory(*args, **kwargs)

The memory layers is a layer cross each time step. Reference this output as previous time step layer name ‘s output.

The default memory is zero in first time step, previous time step’s @@ -1282,13 +1288,23 @@ Arguments.ids()[0] is this is_seq is true boot layer is sequence.

The same name layer in recurrent group will set memory on each time step.

+
mem = memory(size=256, name='state')
+state = fc_layer(input=mem, size=256, name='state')
+
+
+

If you do not want to specify the name, you can equivalently use set_input() +to specify the layer needs to be remembered as the following:

diff --git a/develop/doc/api/v2/config/layer.html b/develop/doc/api/v2/config/layer.html index 7f18b689131316840ae68ad8a3bdefebedac064d..fe7fc2268b64b701d919ee9f9bc9bc6de05679ea 100644 --- a/develop/doc/api/v2/config/layer.html +++ b/develop/doc/api/v2/config/layer.html @@ -3458,7 +3458,11 @@ the way how to configure a neural network topology in Paddle Python code.

  • input (paddle.v2.config_base.Layer.) – The first input layer.
  • label – The input label.
  • name (None|basestring.) – The name of this layers. It is not necessary.
    • -
  • coeff (float.) – The coefficient affects the gradient in the backward.
    • +
  • coeff (float.) – The cost is multiplied with coeff. +The coefficient affects the gradient in the backward.
    • +
  • weight (LayerOutout) – The cost of each sample is multiplied with each weight. +The weight should be a layer with size=1. Note that gradient +will not be calculated for weight.
  • layer_attr (paddle.v2.attr.ExtraAttribute) – Extra Layer Attribute.
    • diff --git a/develop/doc/searchindex.js b/develop/doc/searchindex.js index eb7b8a60dba4f623ca62cb2468fb085ff0d5e61f..1a6f7c2a7213eebfa39d6999667e9e6140485425 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/api/v1/trainer_config_helpers/layers.html b/develop/doc_cn/api/v1/trainer_config_helpers/layers.html index f6a29f690db1d41f633e7229771a8cbad4ba99af..6152d9fbe852feae80086cb8aff43701eee56270 100644 --- a/develop/doc_cn/api/v1/trainer_config_helpers/layers.html +++ b/develop/doc_cn/api/v1/trainer_config_helpers/layers.html @@ -395,6 +395,12 @@ reasons.

    Parameters:
      -
    • name (basestring) – memory’s name.
      • +
    • name (basestring) – the name of the layer which this memory remembers. +If name is None, user should call set_input() to specify the +name of the layer which this memory remembers.
    • size (int) – size of memory.
      • +
    • memory_name (basestring) – the name of the memory. +It is ignored when name is provided.
    • is_seq (bool) – is sequence for boot_layer
    • boot_layer (LayerOutput|None) – boot layer of memory.
    • boot_bias (ParameterAttribute|None) – boot layer’s bias
      • @@ -2950,7 +2966,11 @@ in width dimension.

    • input (LayerOutput.) – The first input layer.
    • label – The input label.
    • name (None|basestring.) – The name of this layers. It is not necessary.
      • -
    • coeff (float.) – The coefficient affects the gradient in the backward.
      • +
    • coeff (float.) – The cost is multiplied with coeff. +The coefficient affects the gradient in the backward.
      • +
    • weight (LayerOutout) – The cost of each sample is multiplied with each weight. +The weight should be a layer with size=1. Note that gradient +will not be calculated for weight.
    • layer_attr (ExtraLayerAttribute) – Extra Layer Attribute.
    +
    +
    +set_input(input)
    +

    Set the input for a memory layer. Can only be used for memory layer

    +
    +
    @@ -1276,7 +1282,7 @@ will get a warning.

    memoryΒΆ

    -paddle.trainer_config_helpers.layers.memory(name, size, is_seq=False, boot_layer=None, boot_bias=None, boot_bias_active_type=None, boot_with_const_id=None)
    +paddle.trainer_config_helpers.layers.memory(*args, **kwargs)

    The memory layers is a layer cross each time step. Reference this output as previous time step layer name ‘s output.

    The default memory is zero in first time step, previous time step’s @@ -1289,13 +1295,23 @@ Arguments.ids()[0] is this is_seq is true boot layer is sequence.

    The same name layer in recurrent group will set memory on each time step.

    +
    mem = memory(size=256, name='state')
+state = fc_layer(input=mem, size=256, name='state')
+
    +
    +

    If you do not want to specify the name, you can equivalently use set_input() +to specify the layer needs to be remembered as the following:

    diff --git a/develop/doc_cn/api/v2/config/layer.html b/develop/doc_cn/api/v2/config/layer.html index 6d03a299c14ddfc439d19f57afdec833c0d99589..610b0c106c521422c41cad4a15dd476cbd767e85 100644 --- a/develop/doc_cn/api/v2/config/layer.html +++ b/develop/doc_cn/api/v2/config/layer.html @@ -3465,7 +3465,11 @@ the way how to configure a neural network topology in Paddle Python code.

  • input (paddle.v2.config_base.Layer.) – The first input layer.
  • label – The input label.
  • name (None|basestring.) – The name of this layers. It is not necessary.
    • -
  • coeff (float.) – The coefficient affects the gradient in the backward.
    • +
  • coeff (float.) – The cost is multiplied with coeff. +The coefficient affects the gradient in the backward.
    • +
  • weight (LayerOutout) – The cost of each sample is multiplied with each weight. +The weight should be a layer with size=1. Note that gradient +will not be calculated for weight.
  • layer_attr (paddle.v2.attr.ExtraAttribute) – Extra Layer Attribute.
    • diff --git a/develop/doc_cn/searchindex.js b/develop/doc_cn/searchindex.js index 773f78e69b8d07e0e0699a90aade5290e626671d..b7bf743ed0cb03d6ad230a9d4570edc1187f74bd 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:
      -
    • name (basestring) – memory’s name.
      • +
    • name (basestring) – the name of the layer which this memory remembers. +If name is None, user should call set_input() to specify the +name of the layer which this memory remembers.
    • size (int) – size of memory.
      • +
    • memory_name (basestring) – the name of the memory. +It is ignored when name is provided.
    • is_seq (bool) – is sequence for boot_layer
    • boot_layer (LayerOutput|None) – boot layer of memory.
    • boot_bias (ParameterAttribute|None) – boot layer’s bias
      • @@ -2957,7 +2973,11 @@ in width dimension.

    • input (LayerOutput.) – The first input layer.
    • label – The input label.
    • name (None|basestring.) – The name of this layers. It is not necessary.
      • -
    • coeff (float.) – The coefficient affects the gradient in the backward.
      • +
    • coeff (float.) – The cost is multiplied with coeff. +The coefficient affects the gradient in the backward.
      • +
    • weight (LayerOutout) – The cost of each sample is multiplied with each weight. +The weight should be a layer with size=1. Note that gradient +will not be calculated for weight.
    • layer_attr (ExtraLayerAttribute) – Extra Layer Attribute.