Inheritance diagram for caffe::PythonLayer< Dtype >:
Public Member Functions
PythonLayer (PyObject *self, const LayerParameter ¶m)
virtual void
LayerSetUp (const vector<
Blob< Dtype > *> &bottom, const vector<
Blob< Dtype > *> &top)
Does layer-specific setup: your layer should implement this function as well as Reshape.
More...
virtual void
Reshape (const vector<
Blob< Dtype > *> &bottom, const vector<
Blob< Dtype > *> &top)
Adjust the shapes of top blobs and internal buffers to accommodate the shapes of the bottom blobs.
More...
virtual const char *
type () const
Returns the layer type.
Layer (const LayerParameter ¶m)
void
SetUp (const vector<
Blob< Dtype > *> &bottom, const vector<
Blob< Dtype > *> &top)
Implements common layer setup functionality.
More...
Dtype
Forward (const vector<
Blob< Dtype > *> &bottom, const vector<
Blob< Dtype > *> &top)
Given the bottom blobs, compute the top blobs and the loss.
More...
void
Backward (const vector<
Blob< Dtype > *> &top, const vector< bool > &propagate_down, const vector<
Blob< Dtype > *> &bottom)
Given the top blob error gradients, compute the bottom blob error gradients.
More...
vector< shared_ptr<
Blob< Dtype > > > &
blobs ()
Returns the vector of learnable parameter blobs.
Returns the layer parameter.
virtual void
ToProto (LayerParameter *param, bool write_diff=false)
Writes the layer parameter to a protocol buffer.
Dtype
loss (const int top_index) const
Returns the scalar loss associated with a top blob at a given index.
void
set_loss (const int top_index, const Dtype value)
Sets the loss associated with a top blob at a given index.
Returns the exact number of bottom blobs required by the layer, or -1 if no exact number is required.
More...
Returns the minimum number of bottom blobs required by the layer, or -1 if no minimum number is required.
More...
Returns the maximum number of bottom blobs required by the layer, or -1 if no maximum number is required.
More...
Returns the exact number of top blobs required by the layer, or -1 if no exact number is required.
More...
Returns the minimum number of top blobs required by the layer, or -1 if no minimum number is required.
More...
Returns the maximum number of top blobs required by the layer, or -1 if no maximum number is required.
More...
Returns true if the layer requires an equal number of bottom and top blobs.
More...
Return whether "anonymous" top blobs are created automatically by the layer.
More...
Return whether to allow force_backward for a given bottom blob index.
More...
Specifies whether the layer should compute gradients w.r.t. a parameter at a particular index given by param_id.
More...
Sets whether the layer should compute gradients w.r.t. a parameter at a particular index given by param_id.
Protected Member Functions
virtual void
Forward_cpu (const vector<
Blob< Dtype > *> &bottom, const vector<
Blob< Dtype > *> &top)
Using the CPU device, compute the layer output.
virtual void
Backward_cpu (const vector<
Blob< Dtype > *> &top, const vector< bool > &propagate_down, const vector<
Blob< Dtype > *> &bottom)
Using the CPU device, compute the gradients for any parameters and for the bottom blobs if propagate_down is true.
virtual void
Forward_gpu (const vector<
Blob< Dtype > *> &bottom, const vector<
Blob< Dtype > *> &top)
Using the GPU device, compute the layer output. Fall back to
Forward_cpu() if unavailable.
virtual void
Backward_gpu (const vector<
Blob< Dtype > *> &top, const vector< bool > &propagate_down, const vector<
Blob< Dtype > *> &bottom)
Using the GPU device, compute the gradients for any parameters and for the bottom blobs if propagate_down is true. Fall back to
Backward_cpu() if unavailable.
Additional Inherited Members
Member Function Documentation
◆ LayerSetUp()
template<typename Dtype >
const vector<
Blob< Dtype > *> &
top
)
inlinevirtual
Does layer-specific setup: your layer should implement this function as well as Reshape.
- Parameters
-
bottom the preshaped input blobs, whose data fields store the input data for this layer
top the allocated but unshaped output blobs
This method should do one-time layer specific setup. This includes reading and processing relevent parameters from the layer_param_. Setting up the shapes of top blobs and internal buffers should be done in Reshape, which will be called before the forward pass to adjust the top blob sizes.
Reimplemented from caffe::Layer< Dtype >.
◆ Reshape()
template<typename Dtype >
const vector<
Blob< Dtype > *> &
top
)
inlinevirtual
Adjust the shapes of top blobs and internal buffers to accommodate the shapes of the bottom blobs.
- Parameters
-
bottom the input blobs, with the requested input shapes
top the top blobs, which should be reshaped as needed
This method should reshape top blobs as needed according to the shapes of the bottom (input) blobs, as well as reshaping any internal buffers and making any other necessary adjustments so that the layer can accommodate the bottom blobs.
Implements caffe::Layer< Dtype >.
The documentation for this class was generated from the following file: