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[Refine] Simplify code and remove train_dataloader_cfg in most of case #711

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[Refine] Simplify code and remove train_dataloader_cfg in most of case #711

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2 changes: 1 addition & 1 deletion .pre-commit-config.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -11,7 +11,7 @@ repos:
- id: black

- repo: https://github.com/charliermarsh/ruff-pre-commit
rev: 'v0.0.272'
rev: "v0.0.272"
hooks:
- id: ruff

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2 changes: 1 addition & 1 deletion docs/zh/examples/ldc2d_steady.md
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Original file line number Diff line number Diff line change
Expand Up @@ -221,7 +221,7 @@ pde = ppsci.constraint.InteriorConstraint(
equation["NavierStokes"].equations,
{"continuity": 0, "momentum_x": 0, "momentum_y": 0},
geom["rect"],
{**train_dataloader_cfg, "batch_size": NPOINT_PDE},
{"batch_size": NPOINT_PDE},
ppsci.loss.MSELoss("sum"),
evenly=True,
weight_dict=cfg.TRAIN.weight.pde, # (1)
Expand Down
2 changes: 1 addition & 1 deletion docs/zh/examples/ldc2d_unsteady.md
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Original file line number Diff line number Diff line change
Expand Up @@ -231,7 +231,7 @@ pde = ppsci.constraint.InteriorConstraint(
equation["NavierStokes"].equations,
{"continuity": 0, "momentum_x": 0, "momentum_y": 0},
geom["time_rect"],
{**train_dataloader_cfg, "batch_size": NPOINT_PDE * NTIME_PDE},
{"batch_size": NPOINT_PDE * NTIME_PDE},
ppsci.loss.MSELoss("sum"),
evenly=True,
weight_dict=cfg.TRAIN.weight.pde, # (1)
Expand Down
16 changes: 2 additions & 14 deletions examples/darcy/darcy2d.py
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Original file line number Diff line number Diff line change
Expand Up @@ -39,12 +39,6 @@ def train(cfg: DictConfig):
# set geometry
geom = {"rect": ppsci.geometry.Rectangle((0.0, 0.0), (1.0, 1.0))}

# set dataloader config
train_dataloader_cfg = {
"dataset": "IterableNamedArrayDataset",
"iters_per_epoch": cfg.TRAIN.iters_per_epoch,
}

# set constraint
def poisson_ref_compute_func(_in):
return (
Expand All @@ -58,7 +52,7 @@ def poisson_ref_compute_func(_in):
equation["Poisson"].equations,
{"poisson": poisson_ref_compute_func},
geom["rect"],
{**train_dataloader_cfg, "batch_size": cfg.NPOINT_PDE},
{"batch_size": cfg.NPOINT_PDE},
ppsci.loss.MSELoss("sum"),
evenly=True,
name="EQ",
Expand All @@ -71,7 +65,7 @@ def poisson_ref_compute_func(_in):
* np.cos(2.0 * np.pi * _in["y"])
},
geom["rect"],
{**train_dataloader_cfg, "batch_size": cfg.NPOINT_BC},
{"batch_size": cfg.NPOINT_BC},
ppsci.loss.MSELoss("sum"),
name="BC",
)
Expand All @@ -91,10 +85,8 @@ def poisson_ref_compute_func(_in):
{"poisson": poisson_ref_compute_func},
geom["rect"],
{
"dataset": "NamedArrayDataset",
"total_size": cfg.NPOINT_PDE,
"batch_size": cfg.EVAL.batch_size.residual_validator,
"sampler": {"name": "BatchSampler"},
},
ppsci.loss.MSELoss("sum"),
evenly=True,
Expand Down Expand Up @@ -157,7 +149,6 @@ def poisson_ref_compute_func(_in):
eval_during_train=cfg.TRAIN.eval_during_train,
eval_freq=cfg.TRAIN.eval_freq,
equation=equation,
geom=geom,
validator=validator,
visualizer=visualizer,
)
Expand Down Expand Up @@ -186,7 +177,6 @@ def poisson_ref_compute_func(_in):
eval_during_train=cfg.TRAIN.lbfgs.eval_during_train,
eval_freq=cfg.TRAIN.lbfgs.eval_freq,
equation=equation,
geom=geom,
validator=validator,
visualizer=visualizer,
)
Expand Down Expand Up @@ -228,10 +218,8 @@ def poisson_ref_compute_func(_in):
{"poisson": poisson_ref_compute_func},
geom["rect"],
{
"dataset": "NamedArrayDataset",
"total_size": cfg.NPOINT_PDE,
"batch_size": cfg.EVAL.batch_size.residual_validator,
"sampler": {"name": "BatchSampler"},
},
ppsci.loss.MSELoss("sum"),
evenly=True,
Expand Down
12 changes: 1 addition & 11 deletions examples/gpinn/poisson_1d.py
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Original file line number Diff line number Diff line change
Expand Up @@ -83,18 +83,12 @@ def output_transform(
# set geometry
geom = {"line": ppsci.geometry.Interval(0, np.pi)}

# set dataloader config
train_dataloader_cfg = {
"dataset": "IterableNamedArrayDataset",
"iters_per_epoch": cfg.TRAIN.iters_per_epoch,
}

# set constraint
pde_constraint = ppsci.constraint.InteriorConstraint(
equation["gPINN"].equations,
{"res1": 0, "res2": 0},
geom["line"],
{**train_dataloader_cfg, "batch_size": cfg.NPOINT_PDE},
{"batch_size": cfg.NPOINT_PDE},
ppsci.loss.MSELoss("mean", weight={"res2": 0.01}),
evenly=True,
name="EQ",
Expand All @@ -120,10 +114,8 @@ def u_solution(in_):
{outvar: u_solution},
geom["line"],
{
"dataset": "NamedArrayDataset",
"total_size": cfg.NPOINT_PDE_EVAL,
"batch_size": cfg.EVAL.batch_size.l2rel_validator,
"sampler": {"name": "BatchSampler"},
},
ppsci.loss.MSELoss("mean"),
evenly=True,
Expand Down Expand Up @@ -250,10 +242,8 @@ def u_solution(in_):
{outvar: u_solution},
geom["line"],
{
"dataset": "NamedArrayDataset",
"total_size": cfg.NPOINT_PDE,
"batch_size": cfg.EVAL.batch_size.l2rel_validator,
"sampler": {"name": "BatchSampler"},
},
ppsci.loss.MSELoss("mean"),
evenly=True,
Expand Down
16 changes: 5 additions & 11 deletions examples/heat_pinn/heat_pinn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -40,12 +40,6 @@ def train(cfg: DictConfig):
# set geometry
geom = {"rect": ppsci.geometry.Rectangle((-1.0, -1.0), (1.0, 1.0))}

# set train dataloader config
train_dataloader_cfg = {
"dataset": "IterableNamedArrayDataset",
"iters_per_epoch": cfg.TRAIN.iters_per_epoch,
}

# set constraint
NPOINT_PDE = 99**2
NPOINT_TOP = 25
Expand All @@ -56,7 +50,7 @@ def train(cfg: DictConfig):
equation["heat"].equations,
{"laplace": 0},
geom["rect"],
{**train_dataloader_cfg, "batch_size": NPOINT_PDE},
{"batch_size": NPOINT_PDE},
ppsci.loss.MSELoss("mean"),
evenly=True,
name="EQ",
Expand All @@ -65,7 +59,7 @@ def train(cfg: DictConfig):
{"u": lambda out: out["u"]},
{"u": 0},
geom["rect"],
{**train_dataloader_cfg, "batch_size": NPOINT_TOP},
{"batch_size": NPOINT_TOP},
ppsci.loss.MSELoss("mean"),
weight_dict={"u": cfg.TRAIN.weight.bc_top},
criteria=lambda x, y: np.isclose(y, 1),
Expand All @@ -75,7 +69,7 @@ def train(cfg: DictConfig):
{"u": lambda out: out["u"]},
{"u": 50 / 75},
geom["rect"],
{**train_dataloader_cfg, "batch_size": NPOINT_BOTTOM},
{"batch_size": NPOINT_BOTTOM},
ppsci.loss.MSELoss("mean"),
weight_dict={"u": cfg.TRAIN.weight.bc_bottom},
criteria=lambda x, y: np.isclose(y, -1),
Expand All @@ -85,7 +79,7 @@ def train(cfg: DictConfig):
{"u": lambda out: out["u"]},
{"u": 1},
geom["rect"],
{**train_dataloader_cfg, "batch_size": NPOINT_LEFT},
{"batch_size": NPOINT_LEFT},
ppsci.loss.MSELoss("mean"),
weight_dict={"u": cfg.TRAIN.weight.bc_left},
criteria=lambda x, y: np.isclose(x, -1),
Expand All @@ -95,7 +89,7 @@ def train(cfg: DictConfig):
{"u": lambda out: out["u"]},
{"u": 0},
geom["rect"],
{**train_dataloader_cfg, "batch_size": NPOINT_RIGHT},
{"batch_size": NPOINT_RIGHT},
ppsci.loss.MSELoss("mean"),
weight_dict={"u": cfg.TRAIN.weight.bc_right},
criteria=lambda x, y: np.isclose(x, 1),
Expand Down
10 changes: 2 additions & 8 deletions examples/laplace/laplace2d.py
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Original file line number Diff line number Diff line change
Expand Up @@ -48,20 +48,14 @@ def u_solution_func(out):
x, y = out["x"], out["y"]
return np.cos(x) * np.cosh(y)

# set train dataloader config
train_dataloader_cfg = {
"dataset": "IterableNamedArrayDataset",
"iters_per_epoch": cfg.TRAIN.iters_per_epoch,
}

NPOINT_TOTAL = cfg.NPOINT_INTERIOR + cfg.NPOINT_BC

# set constraint
pde_constraint = ppsci.constraint.InteriorConstraint(
equation["laplace"].equations,
{"laplace": 0},
geom["rect"],
{**train_dataloader_cfg, "batch_size": NPOINT_TOTAL},
{"batch_size": NPOINT_TOTAL},
ppsci.loss.MSELoss("sum"),
evenly=True,
name="EQ",
Expand All @@ -70,7 +64,7 @@ def u_solution_func(out):
{"u": lambda out: out["u"]},
{"u": u_solution_func},
geom["rect"],
{**train_dataloader_cfg, "batch_size": cfg.NPOINT_BC},
{"batch_size": cfg.NPOINT_BC},
ppsci.loss.MSELoss("sum"),
name="BC",
)
Expand Down
20 changes: 5 additions & 15 deletions examples/ldc/ldc2d_steady_Re10.py
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Original file line number Diff line number Diff line change
Expand Up @@ -36,12 +36,6 @@ def train(cfg: DictConfig):
# set geometry
geom = {"rect": ppsci.geometry.Rectangle((-0.05, -0.05), (0.05, 0.05))}

# set dataloader config
train_dataloader_cfg = {
"dataset": "IterableNamedArrayDataset",
"iters_per_epoch": cfg.TRAIN.iters_per_epoch,
}

NPOINT_PDE = 99**2
NPOINT_TOP = 101
NPOINT_BOTTOM = 101
Expand All @@ -53,7 +47,7 @@ def train(cfg: DictConfig):
equation["NavierStokes"].equations,
{"continuity": 0, "momentum_x": 0, "momentum_y": 0},
geom["rect"],
{**train_dataloader_cfg, "batch_size": NPOINT_PDE},
{"batch_size": NPOINT_PDE},
ppsci.loss.MSELoss("sum"),
evenly=True,
weight_dict=cfg.TRAIN.weight.pde,
Expand All @@ -63,7 +57,7 @@ def train(cfg: DictConfig):
{"u": lambda out: out["u"], "v": lambda out: out["v"]},
{"u": 1, "v": 0},
geom["rect"],
{**train_dataloader_cfg, "batch_size": NPOINT_TOP},
{"batch_size": NPOINT_TOP},
ppsci.loss.MSELoss("sum"),
criteria=lambda x, y: np.isclose(y, 0.05),
name="BC_top",
Expand All @@ -72,7 +66,7 @@ def train(cfg: DictConfig):
{"u": lambda out: out["u"], "v": lambda out: out["v"]},
{"u": 0, "v": 0},
geom["rect"],
{**train_dataloader_cfg, "batch_size": NPOINT_BOTTOM},
{"batch_size": NPOINT_BOTTOM},
ppsci.loss.MSELoss("sum"),
criteria=lambda x, y: np.isclose(y, -0.05),
name="BC_bottom",
Expand All @@ -81,7 +75,7 @@ def train(cfg: DictConfig):
{"u": lambda out: out["u"], "v": lambda out: out["v"]},
{"u": 0, "v": 0},
geom["rect"],
{**train_dataloader_cfg, "batch_size": NPOINT_LEFT},
{"batch_size": NPOINT_LEFT},
ppsci.loss.MSELoss("sum"),
criteria=lambda x, y: np.isclose(x, -0.05),
name="BC_left",
Expand All @@ -90,7 +84,7 @@ def train(cfg: DictConfig):
{"u": lambda out: out["u"], "v": lambda out: out["v"]},
{"u": 0, "v": 0},
geom["rect"],
{**train_dataloader_cfg, "batch_size": NPOINT_RIGHT},
{"batch_size": NPOINT_RIGHT},
ppsci.loss.MSELoss("sum"),
criteria=lambda x, y: np.isclose(x, 0.05),
name="BC_right",
Expand Down Expand Up @@ -118,10 +112,8 @@ def train(cfg: DictConfig):
{"momentum_x": 0, "continuity": 0, "momentum_y": 0},
geom["rect"],
{
"dataset": "NamedArrayDataset",
"total_size": NPOINT_EVAL,
"batch_size": cfg.EVAL.batch_size.residual_validator,
"sampler": {"name": "BatchSampler"},
},
ppsci.loss.MSELoss("sum"),
evenly=True,
Expand Down Expand Up @@ -195,10 +187,8 @@ def evaluate(cfg: DictConfig):
{"momentum_x": 0, "continuity": 0, "momentum_y": 0},
geom["rect"],
{
"dataset": "NamedArrayDataset",
"total_size": NPOINT_EVAL,
"batch_size": cfg.EVAL.batch_size.residual_validator,
"sampler": {"name": "BatchSampler"},
},
ppsci.loss.MSELoss("sum"),
evenly=True,
Expand Down
22 changes: 6 additions & 16 deletions examples/ldc/ldc2d_unsteady_Re10.py
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Original file line number Diff line number Diff line change
Expand Up @@ -43,12 +43,6 @@ def train(cfg: DictConfig):
)
}

# set dataloader config
train_dataloader_cfg = {
"dataset": "IterableNamedArrayDataset",
"iters_per_epoch": cfg.TRAIN.iters_per_epoch,
}

# pde/bc constraint use t1~tn, initial constraint use t0
NPOINT_PDE, NTIME_PDE = 99**2, cfg.NTIME_ALL - 1
NPOINT_TOP, NTIME_TOP = 101, cfg.NTIME_ALL - 1
Expand All @@ -62,7 +56,7 @@ def train(cfg: DictConfig):
equation["NavierStokes"].equations,
{"continuity": 0, "momentum_x": 0, "momentum_y": 0},
geom["time_rect"],
{**train_dataloader_cfg, "batch_size": NPOINT_PDE * NTIME_PDE},
{"batch_size": NPOINT_PDE * NTIME_PDE},
ppsci.loss.MSELoss("sum"),
evenly=True,
weight_dict=cfg.TRAIN.weight.pde, # (1)
Expand All @@ -72,7 +66,7 @@ def train(cfg: DictConfig):
{"u": lambda out: out["u"], "v": lambda out: out["v"]},
{"u": 1, "v": 0},
geom["time_rect"],
{**train_dataloader_cfg, "batch_size": NPOINT_TOP * NTIME_TOP},
{"batch_size": NPOINT_TOP * NTIME_TOP},
ppsci.loss.MSELoss("sum"),
criteria=lambda t, x, y: np.isclose(y, 0.05),
name="BC_top",
Expand All @@ -81,7 +75,7 @@ def train(cfg: DictConfig):
{"u": lambda out: out["u"], "v": lambda out: out["v"]},
{"u": 0, "v": 0},
geom["time_rect"],
{**train_dataloader_cfg, "batch_size": NPOINT_DOWN * NTIME_DOWN},
{"batch_size": NPOINT_DOWN * NTIME_DOWN},
ppsci.loss.MSELoss("sum"),
criteria=lambda t, x, y: np.isclose(y, -0.05),
name="BC_down",
Expand All @@ -90,7 +84,7 @@ def train(cfg: DictConfig):
{"u": lambda out: out["u"], "v": lambda out: out["v"]},
{"u": 0, "v": 0},
geom["time_rect"],
{**train_dataloader_cfg, "batch_size": NPOINT_LEFT * NTIME_LEFT},
{"batch_size": NPOINT_LEFT * NTIME_LEFT},
ppsci.loss.MSELoss("sum"),
criteria=lambda t, x, y: np.isclose(x, -0.05),
name="BC_left",
Expand All @@ -99,7 +93,7 @@ def train(cfg: DictConfig):
{"u": lambda out: out["u"], "v": lambda out: out["v"]},
{"u": 0, "v": 0},
geom["time_rect"],
{**train_dataloader_cfg, "batch_size": NPOINT_RIGHT * NTIME_RIGHT},
{"batch_size": NPOINT_RIGHT * NTIME_RIGHT},
ppsci.loss.MSELoss("sum"),
criteria=lambda t, x, y: np.isclose(x, 0.05),
name="BC_right",
Expand All @@ -108,7 +102,7 @@ def train(cfg: DictConfig):
{"u": lambda out: out["u"], "v": lambda out: out["v"]},
{"u": 0, "v": 0},
geom["time_rect"],
{**train_dataloader_cfg, "batch_size": NPOINT_IC * NTIME_IC},
{"batch_size": NPOINT_IC * NTIME_IC},
ppsci.loss.MSELoss("sum"),
evenly=True,
name="IC",
Expand Down Expand Up @@ -139,10 +133,8 @@ def train(cfg: DictConfig):
{"momentum_x": 0, "continuity": 0, "momentum_y": 0},
geom["time_rect"],
{
"dataset": "NamedArrayDataset",
"total_size": NPOINT_EVAL,
"batch_size": cfg.EVAL.batch_size.residual_validator,
"sampler": {"name": "BatchSampler"},
},
ppsci.loss.MSELoss("sum"),
evenly=True,
Expand Down Expand Up @@ -247,10 +239,8 @@ def evaluate(cfg: DictConfig):
{"momentum_x": 0, "continuity": 0, "momentum_y": 0},
geom["time_rect"],
{
"dataset": "NamedArrayDataset",
"total_size": NPOINT_EVAL,
"batch_size": cfg.EVAL.batch_size.residual_validator,
"sampler": {"name": "BatchSampler"},
},
ppsci.loss.MSELoss("sum"),
evenly=True,
Expand Down
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