refactor(shuffle): set default `shuffle` to None
@@ -87,7 +87,7 @@ class BaseSolver(ABC):
optimizer=None, criterion=None, n_batches_train=1, n_batches_valid=4,
metrics=None, n_input_units=None, n_output_units=None,
# deprecated arguments are listed below
- shuffle=False, batch_size=None):
+ shuffle=None, batch_size=None):
# deprecate argument `shuffle`
if shuffle:
warnings.warn(
@@ -624,7 +624,7 @@ class SolverSpherical(BaseSolver):
optimizer=None, criterion=None, n_batches_train=1, n_batches_valid=4, enforcer=None,
n_output_units=1,
# deprecated arguments are listed below
- shuffle=False, batch_size=None):
+ shuffle=None, batch_size=None):
if train_generator is None or valid_generator is None:
if r_min is None or r_max is None:
@@ -857,7 +857,7 @@ class Solver1D(BaseSolver):
nets=None, train_generator=None, valid_generator=None, analytic_solutions=None, optimizer=None,
criterion=None, n_batches_train=1, n_batches_valid=4, metrics=None, n_output_units=1,
# deprecated arguments are listed below
- batch_size=None, shuffle=True):
+ batch_size=None, shuffle=None):
if train_generator is None or valid_generator is None:
if t_min is None or t_max is None:
@@ -1020,7 +1020,7 @@ class Solver2D(BaseSolver):
nets=None, train_generator=None, valid_generator=None, analytic_solutions=None, optimizer=None,
criterion=None, n_batches_train=1, n_batches_valid=4, metrics=None, n_output_units=1,
# deprecated arguments are listed below
- batch_size=None, shuffle=True):
+ batch_size=None, shuffle=None):
if train_generator is None or valid_generator is None:
if xy_min is None or xy_max is None:
