o ϯi{@sddlmZmZmZmZddlmZdejejdfdeedeededeed e d eej eff d d Z d ed e fddZ dS))CallableListOptionalTuple)nnNgfully_connected_dimsnormmid_activationfinal_activation dropout_ratereturnc Cst|tsJt|dksJtdd|DsJg}|d}|ddD]}|t|||dur<||||||}q&|t||d|dkr]|tj|d|durg||tj|}|d} || fS)uW Factory function for Multi-Layer Perceptron. These are constructed as repeated blocks of the following format where each fc represents the blocks output/input dimension. :: Linear (in=fc[i-1], out=fc[i]) ↓ Normalization (norm) ↓ Activation (mid_activation) ↓ After the repeated Perceptron blocks, a final dropout and activation layer is applied: ↓ Dropout (p=dropout_rate) ↓ Activation (final_activation) css|]}t|VqdS)N) _is_pos_int).0xrK/home/ubuntu/.local/lib/python3.10/site-packages/pytorchvideo/layers/mlp.py %sz-make_multilayer_perceptron..rN)p) isinstancelistlenallappendrLinearDropout Sequential) rrr r r layerscur_dimdimmlp output_dimrrrmake_multilayer_perceptrons&   r#numbercCst|tko |dkS)z9 Returns True if a number is a positive integer. r)typeint)r$rrrr:sr)typingrrrrtorchrReLUr&floatModuler#boolrrrrrs(   2