def build_cnf():
diffeq = layers.ODEnet(
hidden_dims=hidden_dims,
input_shape=data_shape,
strides=strides,
conv=args.conv,
layer_type=args.layer_type,
nonlinearity=args.nonlinearity,
)
odefunc = layers.ODEfunc(
diffeq=diffeq,
divergence_fn=args.divergence_fn,
residual=args.residual,
rademacher=args.rademacher,
)
cnf = layers.CNF(
odefunc=odefunc,
T=args.time_length,
train_T=args.train_T,
regularization_fns=regularization_fns,
solver=args.solver,
num_steps=args.num_steps,
adjoint=args.adjoint,
)
return cnf
def build_cnf():
diffeq = layers.ODEnet(
hidden_dims=hidden_dims,
input_shape=(dims,),
strides=None,
conv=False,
layer_type=args.layer_type,
nonlinearity=args.nonlinearity,
)
odefunc = layers.ODEfunc(
diffeq=diffeq,
divergence_fn=args.divergence_fn,
residual=args.residual,
rademacher=args.rademacher,
)
cnf = layers.CNF(
odefunc=odefunc,
T=args.time_length,
train_T=args.train_T,
solver=args.solver,
atol = args.atol,
rtol = args.rtol,
test_atol = args.test_atol,
test_rtol = args.test_rtol,
poly_num_sample=args.poly_num_sample,
poly_order=args.poly_order,
adjoint=args.adjoint,
)
return cnf
def build_cnf():
diffeq = layers.ODEnet(
hidden_dims=hidden_dims,
input_shape=data_shape,
strides=strides,
conv=args.conv,
layer_type=args.layer_type,
nonlinearity=args.nonlinearity,
)
odefunc = layers.ODEfunc(
diffeq=diffeq,
divergence_fn=args.divergence_fn,
residual=args.residual,
rademacher=args.rademacher,
)
cnf = layers.CNF(
odefunc=odefunc,
T=args.time_length,
solver=args.solver,
)
return cnf
def build_cnf():
diffeq = layers.ODEnet(
hidden_dims=hidden_dims,
input_shape=(dims, ),
strides=None,
conv=False,
layer_type=args.layer_type,
nonlinearity=args.nonlinearity,
)
odefunc = layers.ODEfunc(
diffeq=diffeq,
divergence_fn=args.divergence_fn,
rademacher=args.rademacher,
)
cnf = layers.CNF(
odefunc=odefunc,
T=args.time_length,
train_T=args.train_T,
regularization_fns=regularization_fns,
solver=args.solver,
)
return cnf