def build_cpg_model(self):
opts = self.opts
log = self.log
replicate_names = dat.get_replicate_names(opts.train_files[0],
regex=opts.replicate_names,
nb_key=opts.nb_replicate)
if not replicate_names:
raise ValueError('No replicates found!')
print('Replicate names:')
print(', '.join(replicate_names))
print()
cpg_wlen = dat.get_cpg_wlen(opts.train_files[0], opts.cpg_wlen)
if os.path.exists(opts.cpg_model[0]):
log.info('Loading existing CpG model ...')
src_cpg_model = mod.load_model(opts.cpg_model, log=log.info)
remove_outputs(src_cpg_model)
rename_layers(src_cpg_model, 'cpg')
nb_replicate = src_cpg_model.input_shape[0][1]
if nb_replicate != len(replicate_names):
tmp = 'CpG model was trained with %d replicates but %d'
'replicates provided. Copying weight to new model ...'
tmp %= (nb_replicate, len(replicate_names))
log.info('Replicate names differ: '
'Copying weights to new model ...')
cpg_model_builder = mod.cpg.get(src_cpg_model.name)(
l1_decay=opts.l1_decay,
l2_decay=opts.l2_decay,
dropout=opts.dropout)
cpg_inputs = cpg_model_builder.inputs(cpg_wlen,
replicate_names)
cpg_model = cpg_model_builder(cpg_inputs)
mod.copy_weights(src_cpg_model, cpg_model)
else:
cpg_model = src_cpg_model
else:
log.info('Building CpG model ...')
cpg_model_builder = mod.cpg.get(opts.cpg_model[0])(
l1_decay=opts.l1_decay,
l2_decay=opts.l2_decay,
dropout=opts.dropout)
cpg_inputs = cpg_model_builder.inputs(cpg_wlen, replicate_names)
cpg_model = cpg_model_builder(cpg_inputs)
return cpg_model
def build_cpg_model(self):
opts = self.opts
log = self.log
replicate_names = dat.get_replicate_names(
opts.train_files[0],
regex=opts.replicate_names,
nb_key=opts.nb_replicate)
if not replicate_names:
raise ValueError('No replicates found!')
print('Replicate names:')
print(', '.join(replicate_names))
print()
cpg_wlen = dat.get_cpg_wlen(opts.train_files[0], opts.cpg_wlen)
if os.path.exists(opts.cpg_model[0]):
log.info('Loading existing CpG model ...')
src_cpg_model = mod.load_model(opts.cpg_model, log=log.info)
remove_outputs(src_cpg_model)
rename_layers(src_cpg_model, 'cpg')
nb_replicate = src_cpg_model.input_shape[0][1]
if nb_replicate != len(replicate_names):
tmp = 'CpG model was trained with %d replicates but %d'
'replicates provided. Copying weight to new model ...'
tmp %= (nb_replicate, len(replicate_names))
log.info('Replicate names differ: '
'Copying weights to new model ...')
cpg_model_builder = mod.cpg.get(src_cpg_model.name)(
l1_decay=opts.l1_decay,
l2_decay=opts.l2_decay,
dropout=opts.dropout)
cpg_inputs = cpg_model_builder.inputs(cpg_wlen, replicate_names)
cpg_model = cpg_model_builder(cpg_inputs)
mod.copy_weights(src_cpg_model, cpg_model)
else:
cpg_model = src_cpg_model
else:
log.info('Building CpG model ...')
cpg_model_builder = mod.cpg.get(opts.cpg_model[0])(
l1_decay=opts.l1_decay,
l2_decay=opts.l2_decay,
dropout=opts.dropout)
cpg_inputs = cpg_model_builder.inputs(cpg_wlen, replicate_names)
cpg_model = cpg_model_builder(cpg_inputs)
return cpg_model