def build_double_conv_deep_net(conv_params, net_params, fp_l2_penalty=0.0):
"""Returns loss_fun(all_weights, smiles, targets), pred_fun, combined_parser."""
#conv_fp_func, conv_parser = build_double_convnet_fingerprint_fun(**conv_params)
conv_fp_func, conv_parser = build_fixed_convnet_fingerprint_fun(
**conv_params)
return build_fingerprint_deep_net(net_params, conv_fp_func, conv_parser,
fp_l2_penalty)
def build_double_morgan_deep_net(fp_length, fp_depth, net_params):
empty_parser = WeightsParser()
morgan_fp_func = build_double_morgan_fingerprint_fun(fp_length, fp_depth)
return build_fingerprint_deep_net(net_params, morgan_fp_func, empty_parser,
0)
def build_double_morgan_deep_net(fp_length, fp_depth, net_params):
empty_parser = WeightsParser()
morgan_fp_func = build_double_morgan_fingerprint_fun(fp_length, fp_depth)
return build_fingerprint_deep_net(net_params, morgan_fp_func, empty_parser, 0)
def build_double_conv_deep_net(conv_params, net_params, fp_l2_penalty=0.0):
"""Returns loss_fun(all_weights, smiles, targets), pred_fun, combined_parser."""
conv_fp_func, conv_parser = build_double_convnet_fingerprint_fun(**conv_params)
return build_fingerprint_deep_net(net_params, conv_fp_func, conv_parser, fp_l2_penalty)
def build_conv_deep_net(conv_params, net_params, fp_l2_penalty=0.0):
"""Returns loss_fun(all_weights, smiles, targets), pred_fun, combined_parser."""
conv_fp_func, conv_parser = build_convnet_fingerprint_fun(**conv_params) # V: conv_fp_func is the func that computes the fingerprints, conv_parser is the weights parser for fp net
return build_fingerprint_deep_net(net_params, conv_fp_func, conv_parser, fp_l2_penalty) # V: creates and returns loss_fun, pred_fun, combined_parser of build_vanilla_net.py, loss_fun and pred_func is of the combined net i.e. fp+vanilla net
