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Here, I surveyed several popular dl frameworks including tensorflow, caffe2 and pytorch to check their ops' documentation. I select fully connected operator as a typical example.
Component
Feature summarization: Summary function of this op (including equation and detailed description)
Usage example: Tell how to use this op (refer PyTorch)
Python api definition: Show definition of the python api
Python wrapper location: Link to wrapper code
Parameters description: Describe each parameters in python api
CPP code location: Link to cpp source code
Highlight note: Something should pay attention to
Other
At least
Feature summarization
Python api definition
Python wrapper location
Parameter description
More
Usage example
Highlight note
CPP code location
Other
Documentation for PaddlePaddle Ops
Python api definition
[Python code snippet]
Python wrapper location
[URL]
Feature summarization
[Function summarization] [Equation and description] [Tips]
Applies linear transformation to the input data. The equation is:
$$Y = Act(W^T * X + b)$$
In the above equation:
X: input value, a tensor with rank at least 2.
W: weight, a 2D tensor with shape [M, N].
b: bias, a float scalar.
Act: function to apply non-linearity activation.
All the input variables of this function are passed in as local variables to the LayerHelper constructor.
Args
input (Variable): The input vaule, a tensor with rank at least 2.
size (int): The output size, an interge value.
num_flatten_dims (int): Column number of the input.
param_attr: The parameters/weights.
param_initializer: Initializer used to initialize transoformation weights. If None, XavierInitializer is used.
bias_attr: The bias parameter.
bias_initializer: Initializer used to initialize bias. If None, ConstantInitializer is used.
act (str): Activation type.
name (str): Name/alias of the layer.
main_program (Program): The main program calling this.
startup_program (Program): The startup program.
Returns
Variable: the tensor variable storing the transformation and non-linearity activation result
Exceptions
ValueError: if rank of input less than 2
Usage Examples
```python
data = fluid.layers.data(name='data', shape=[1], dtype='float32')
fc = fluid.layers.fc(input=data, size=10, act="tanh")
```
The text was updated successfully, but these errors were encountered:
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Survey and conclusion
Here, I surveyed several popular dl frameworks including tensorflow, caffe2 and pytorch to check their ops' documentation. I select fully connected operator as a typical example.
Component
At least
More
Documentation for PaddlePaddle Ops
[Python code snippet]
[URL]
[Function summarization] [Equation and description] [Tips]
[Description] [Data type] [Shape]
[Python code snippet]
An example
FC [python/paddle/v2/fluid/layers.py#fc]
Applies linear transformation to the input data. The equation is:
In the above equation:
All the input variables of this function are passed in as local variables to the LayerHelper constructor.
Args
Returns
Exceptions
Usage Examples
The text was updated successfully, but these errors were encountered: