[API] support set None to Validator.loss (#1214)

* support set None to validator

* support set None to validator

Author: HydrogenSulfate

ppsci/solver/eval.py

@@ -108,9 +108,10 @@ def _eval_by_dataset(
                     weight_dict,
                 )
 
-            loss_dict[f"{_validator.name}/loss"] = float(
-                sum(list(validator_loss.values()))
-            )
+            if len(validator_loss) > 0:
+                loss_dict[f"{_validator.name}/loss"] = float(
+                    sum(list(validator_loss.values()))
+                )
 
             for key, output in output_dict.items():
                 all_output[key].append(
@@ -235,9 +236,10 @@ def _eval_by_batch(
                     weight_dict,
                 )
 
-            loss_dict[f"{_validator.name}/loss"] = float(
-                sum(list(validator_loss.values()))
-            )
+            if len(validator_loss) > 0:
+                loss_dict[f"{_validator.name}/loss"] = float(
+                    sum(list(validator_loss.values()))
+                )
 
             # collect batch metric
             for metric_name, metric_func in _validator.metric.items():

ppsci/solver/printer.py

@@ -76,8 +76,8 @@ def log_train_info(
     iters_width = len(str(solver.iters_per_epoch))
     log_str = (
         f"[Train][Epoch {epoch_id:>{epoch_width}}/{solver.epochs}]"
-        f"[Iter {iter_id:>{iters_width}}/{solver.iters_per_epoch}] {lr_msg}, "
-        f"{metric_msg}, {time_msg}, {ips_msg}, {eta_msg}"
+        + f"[Iter {iter_id:>{iters_width}}/{solver.iters_per_epoch}] {lr_msg}, "
+        + ", ".join(filter(None, [metric_msg, time_msg, ips_msg, eta_msg]))
     )
     if solver.benchmark_flag:
         max_mem_reserved_msg = (
@@ -136,13 +136,13 @@ def log_eval_info(
     if isinstance(epoch_id, int):
         logger.info(
             f"[Eval][Epoch {epoch_id:>{epoch_width}}/{solver.epochs}]"
-            f"[Iter {iter_id:>{iters_width}}/{iters_per_epoch}] "
-            f"{metric_msg}, {time_msg}, {ips_msg}, {eta_msg}"
+            + f"[Iter {iter_id:>{iters_width}}/{iters_per_epoch}] "
+            + ", ".join(filter(None, [metric_msg, time_msg, ips_msg, eta_msg]))
         )
     else:
         logger.info(
             f"[Eval][Iter {iter_id:>{iters_width}}/{iters_per_epoch}] "
-            f"{metric_msg}, {time_msg}, {ips_msg}, {eta_msg}"
+            + ", ".join(filter(None, [metric_msg, time_msg, ips_msg, eta_msg]))
         )
 
     # reset time information after printing

ppsci/solver/solver.py

@@ -491,10 +491,16 @@ def dist_wrapper(model: nn.Layer) -> paddle.DataParallel:
         # whether enable static for forward pass. Defaults to False
         if not cfg:
             self.to_static = to_static
-        jit.enable_to_static(self.to_static)
-        logger.message(
-            f"Set to_static={self.to_static} for computational optimization."
-        )
+
+        if self.to_static:
+            jit.enable_to_static(self.to_static)
+            logger.message("Enable jit.to_static for computational optimization.")
+            self.forward_helper.train_forward = paddle.jit.to_static(
+                self.forward_helper.train_forward
+            )
+            self.forward_helper.eval_forward = paddle.jit.to_static(
+                self.forward_helper.eval_forward
+            )
 
         # convert sympy to callable object if exist
         extra_parameters = []

ppsci/utils/expression.py

@@ -20,7 +20,6 @@
 from typing import Optional
 from typing import Tuple
 
-from paddle import jit
 from paddle import nn
 from paddle.framework import core
 
@@ -57,7 +56,6 @@ def forward(self, *args, **kwargs):
             "Use train_forward/eval_forward/visu_forward instead of forward."
         )
 
-    @jit.to_static
     def train_forward(
         self,
         expr_dicts: Tuple[Dict[str, Callable], ...],
@@ -145,7 +143,6 @@ def train_forward(
 
         return losses_all, losses_constraint
 
-    @jit.to_static
     def eval_forward(
         self,
         expr_dict: Dict[str, Callable],
@@ -187,11 +184,13 @@ def eval_forward(
         clear()
 
         # compute loss for each validator according to its' own output, label and weight
-        validator_losses = validator.loss(
-            output_dict,
-            label_dict,
-            weight_dict,
-        )
+        validator_losses: Dict[str, "paddle.Tensor"] = {}
+        if callable(validator.loss):
+            validator_losses = validator.loss(
+                output_dict,
+                label_dict,
+                weight_dict,
+            )
         return output_dict, validator_losses
 
     def visu_forward(

ppsci/validate/base.py

@@ -34,18 +34,18 @@ class Validator:
     Args:
         dataset (io.Dataset): Dataset for validator.
         dataloader_cfg (Dict[str, Any]): Dataloader config.
-        loss (loss.Loss): Loss functor.
-        metric (Optional[Dict[str, metric.Metric]]): Named metric functors in dict.
-        name (str): Name of validator.
+        loss (Optional[loss.Loss]): Loss functor. Defaults to None.
+        metric (Optional[Dict[str, metric.Metric]]): Named metric functors in dict. Defaults to None.
+        name (str): Name of validator. Defaults to "validator".
     """
 
     def __init__(
         self,
         dataset: io.Dataset,
         dataloader_cfg: Dict[str, Any],
-        loss: "loss.Loss",
-        metric: Optional[Dict[str, "metric.Metric"]],
-        name: str,
+        loss: Optional["loss.Loss"] = None,
+        metric: Optional[Dict[str, "metric.Metric"]] = None,
+        name: str = "validator",
     ):
         self.data_loader = data.build_dataloader(dataset, dataloader_cfg)
         self.data_iter = iter(self.data_loader)

ppsci/validate/geo_validator.py

@@ -43,7 +43,7 @@ class GeometryValidator(base.Validator):
             label, which will be a reference value to participate in the loss calculation.
         geom (geometry.Geometry): Geometry where data sampled from.
         dataloader_cfg (Dict[str, Any]): Dataloader config.
-        loss (loss.Loss): Loss functor.
+        loss (Optional[loss.Loss]): Loss functor. Defaults to None.
         random (Literal["pseudo", "Halton", "LHS"], optional): Random method for sampling data in
             geometry. Defaults to "pseudo".
         criteria (Optional[Callable]): Criteria for refining specified domain. Defaults to None.
@@ -75,7 +75,7 @@ def __init__(
         label_dict: Dict[str, Union[float, Callable]],
         geom: geometry.Geometry,
         dataloader_cfg: Dict[str, Any],
-        loss: loss.Loss,
+        loss: Optional["loss.Loss"] = None,
         random: Literal["pseudo", "Halton", "LHS"] = "pseudo",
         criteria: Optional[Callable] = None,
         evenly: bool = False,

ppsci/validate/sup_validator.py

@@ -30,8 +30,8 @@ class SupervisedValidator(base.Validator):
 
     Args:
         dataloader_cfg (Dict[str, Any]): Config of building a dataloader.
-        loss (loss.Loss): Loss functor.
-        output_expr (Optional[Dict[str, Callable]]): List of label expression.
+        loss (Optional[loss.Loss]): Loss functor. Defaults to None.
+        output_expr (Optional[Dict[str, Callable]]): List of label expression. Defaults to None.
         metric (Optional[Dict[str, metric.Metric]]): Named metric functors in dict. Defaults to None.
         name (Optional[str]): Name of validator. Defaults to None.
 
@@ -63,7 +63,7 @@ class SupervisedValidator(base.Validator):
     def __init__(
         self,
         dataloader_cfg: Dict[str, Any],
-        loss: loss.Loss,
+        loss: Optional["loss.Loss"] = None,
         output_expr: Optional[Dict[str, Callable]] = None,
         metric: Optional[Dict[str, metric.Metric]] = None,
         name: Optional[str] = None,