caffe2.python.cnn.CNNModelHelper Class Reference

Inheritance diagram for caffe2.python.cnn.CNNModelHelper:

Public Member Functions
def	__init__ (self, order="NCHW", name=None, use_cudnn=True, cudnn_exhaustive_search=False, ws_nbytes_limit=None, init_params=True, skip_sparse_optim=False, param_model=None)
def	ImageInput (self, blob_in, blob_out, use_gpu_transform=False, kwargs)
def	VideoInput (self, blob_in, blob_out, kwargs)
def	PadImage (self, blob_in, blob_out, kwargs)
def	ConvNd (self, args, kwargs)
def	Conv (self, args, kwargs)
def	ConvTranspose (self, args, kwargs)
def	GroupConv (self, args, kwargs)
def	GroupConv_Deprecated (self, args, kwargs)
def	FC (self, args, kwargs)
def	PackedFC (self, args, kwargs)
def	FC_Prune (self, args, kwargs)
def	FC_Decomp (self, args, kwargs)
def	FC_Sparse (self, args, kwargs)
def	Dropout (self, args, kwargs)
def	LRN (self, args, kwargs)
def	Softmax (self, args, kwargs)
def	SpatialBN (self, args, kwargs)
def	SpatialGN (self, args, kwargs)
def	InstanceNorm (self, args, kwargs)
def	Relu (self, args, kwargs)
def	PRelu (self, args, kwargs)
def	Concat (self, args, kwargs)
def	DepthConcat (self, args, kwargs)
def	Sum (self, args, kwargs)
def	Transpose (self, args, kwargs)
def	Iter (self, args, kwargs)
def	Accuracy (self, args, kwargs)
def	MaxPool (self, args, kwargs)
def	MaxPoolWithIndex (self, args, kwargs)
def	AveragePool (self, args, kwargs)
def	XavierInit (self)
def	ConstantInit (self, value)
def	MSRAInit (self)
def	ZeroInit (self)
def	AddWeightDecay (self, weight_decay)
def	CPU (self)
def	GPU (self, gpu_id=0)
Public Member Functions inherited from caffe2.python.model_helper.ModelHelper
def	__init__ (self, name=None, init_params=True, allow_not_known_ops=True, skip_sparse_optim=False, param_model=None, arg_scope=None)
def	arg_scope (self)
def	get_name (self)
def	create_param (self, param_name, shape, initializer, tags=None)
def	get_param_info (self, param)
def	add_param_DEPRECATED (self, param, key=None, shape=None, length=None)
def	AddParameter (self, param, tags=None)
def	GetParams (self, namescope=None, top_scope=False)
def	Proto (self)
def	InitProto (self)
def	RunAllOnGPU (self, args, kwargs)
def	CreateDB (self, blob_out, db, db_type, kwargs)
def	AddGradientOperators (self, args, kwargs)
def	get_param_to_grad (self, params)
def	GetOptimizationParamInfo (self, params=None)
def	Validate (self)
def	GetComputedParams (self, namescope=None)
def	GetAllParams (self, namescope=None)
def	TensorProtosDBInput (self, unused_blob_in, blob_out, batch_size, db, db_type, kwargs)
def	GetDevices (self)
def	__getattr__ (self, op_type)
def	__dir__ (self)
def	GetCompleteNet (self)
def	ConstructInitTrainNetfromNet (self, net)

Public Attributes
	order
	use_cudnn
	cudnn_exhaustive_search
	ws_nbytes_limit
Public Attributes inherited from caffe2.python.model_helper.ModelHelper
	name
	net
	param_init_net
	param_to_grad
	params
	gradient_ops_added
	init_params
	allow_not_known_ops
	skip_sparse_optim
	weights
	biases
	grad_map

Detailed Description

A helper model so we can write CNN models more easily, without having to
manually define parameter initializations and operators separately.

Definition at line 14 of file cnn.py.

Member Function Documentation

def caffe2.python.cnn.CNNModelHelper.DepthConcat	(		self,
			args,
			kwargs
	)

The old depth concat function - we should move to use concat.

Definition at line 181 of file cnn.py.

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The documentation for this class was generated from the following file:

• caffe2/python/cnn.py