SymbolBlock

class SymbolBlock(outputs, inputs, params=None)

Construct block from symbol. This is useful for using pre-trained models as feature extractors. For example, you may want to extract the output from fc2 layer in AlexNet.

Parameters:

outputs : Symbol or list of Symbol

The desired output for SymbolBlock.

inputs : Symbol or list of Symbol

The Variables in output’s argument that should be used as inputs.

params : ParameterDict

Parameter dictionary for arguments and auxililary states of outputs that are not inputs.

Examples

>>> # To extract the feature from fc1 and fc2 layers of AlexNet:
>>> alexnet = gluon.model_zoo.vision.alexnet(pretrained=True, ctx=mx.cpu(),
                                             prefix='model_')
>>> inputs = mx.sym.var('data')
>>> out = alexnet(inputs)
>>> internals = out.get_internals()
>>> print(internals.list_outputs())
['data', ..., 'model_dense0_relu_fwd_output', ..., 'model_dense1_relu_fwd_output', ...]
>>> outputs = [internals['model_dense0_relu_fwd_output'],
               internals['model_dense1_relu_fwd_output']]
>>> # Create SymbolBlock that shares parameters with alexnet
>>> feat_model = gluon.SymbolBlock(outputs, inputs, params=alexnet.collect_params())
>>> x = mx.nd.random.normal(shape=(16, 3, 224, 224))
>>> print(feat_model(x))