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Description
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
- 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] - Parameters description
[Description] [Data type] [Shape] - Usage example
[Python code snippet]
An example
FC [python/paddle/v2/fluid/layers.py#fc]
fc(input,
size,
num_flatten_dims=1,
param_attr=None,
bias_attr=None,
act=None,
name=None,
main_program=None,
startup_program=None)
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")
```
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