object CaffeLoader
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def
load[T](model: Module[T], defPath: String, modelPath: String, matchAll: Boolean = true, customizedConverters: HashMap[String, Customizable[T]] = null)(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): Module[T]
Load weight for pre-defined model
Load weight for pre-defined model
- T
data type
- model
pre-defined model
- defPath
prototxt file which defines the network
- modelPath
weight file which contains the parameters
- matchAll
if we need to match all layers from prototxt in weight file
- customizedConverters
customized converters
- ev
tensor numeric
- returns
pre-defined model populated with weights
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def
loadCaffe[T](defPath: String, modelPath: String, customizedConverters: HashMap[String, Customizable[T]] = null, outputNames: Array[String] = Array[String]())(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): (Module[T], ParallelCriterion[T])
load caffe model dynamically from prototxt and binary files
load caffe model dynamically from prototxt and binary files
- T
data type
- defPath
prototxt file which illustrates the caffe model structure
- modelPath
binary file containing the weight and bias
- customizedConverters
customized layer converter
- outputNames
additional output layer names besides the default(layers without next nodes)
- returns
created module (graph) and criterion
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