[BREAKING] [perf] refactor: Profiler api refactor (#2894)

### What does this PR do?

Refactor profiler CI to a unified way.

TODO:

- nsys use `save_path`
- nsys descrete tests are disabled
- torch profiler

cc: @davidmlw 

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### Test

> For changes that can not be tested by CI (e.g., algorithm
implementation, new model support), validate by experiment(s) and show
results like training curve plots, evaluation results, etc.

### API and Usage Example

Global profiler config:

```yaml
global_profiler:
  _target_: verl.utils.profiler.ProfilerConfig
  tool: null
  steps: null
  profile_continuous_steps: false
  save_path: outputs/profile
  tool_config:
    nsys:
      _target_: verl.utils.profiler.config.NsightToolConfig
      discrete: false
    npu:
      _target_: verl.utils.profiler.config.NPUToolConfig
      discrete: false
      contents: []
      level: level1
      analysis: true
    torch:
      _target_: verl.utils.profiler.config.TorchProfilerToolConfig
      step_start: 0
      step_end: null
```

Local profiler config:

```yaml
profiler:

  # Required when using verl.utils.omega_conf_to_dataclass to instantiate dataclass configs
  _target_: verl.utils.profiler.ProfilerConfig

  # profiler tool, default same as profiler.tool in global config
  # choices: nsys, npu, torch
  tool: ${oc.select:global_profiler.tool,null}

  # whether enable profile on critic
  enable: False

  # Whether to profile all ranks.
  all_ranks: False

  # The ranks that will be profiled. [] or [0,1,...]
  ranks: []

  # profile results saving path
  save_path: ${oc.select:global_profiler.save_path,null}

  # specific tool config
  tool_config: ${oc.select:global_profiler.tool_config,null}
```

### Design & Code Changes

> Demonstrate the high-level design if this PR is complex, and list the
specific changes.

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recipe/dapo/dapo_ray_trainer.py

@@ -97,8 +97,8 @@ class RayDAPOTrainer(RayPPOTrainer):
 
         prev_step_profile = False
         curr_step_profile = (
-            self.global_steps in self.config.trainer.profile_steps
-            if self.config.trainer.profile_steps is not None
+            self.global_steps in self.config.global_profiler.steps
+            if self.config.global_profiler.steps is not None
             else False
         )
         next_step_profile = False
@@ -114,7 +114,7 @@ class RayDAPOTrainer(RayPPOTrainer):
                 with marked_timer("start_profile", timing_raw):
                     self._start_profiling(
                         not prev_step_profile and curr_step_profile
-                        if self.config.trainer.profile_continuous_steps
+                        if self.config.global_profiler.profile_continuous_steps
                         else curr_step_profile
                     )
 
@@ -350,13 +350,13 @@ class RayDAPOTrainer(RayPPOTrainer):
 
                 with marked_timer("stop_profile", timing_raw):
                     next_step_profile = (
-                        self.global_steps + 1 in self.config.trainer.profile_steps
-                        if self.config.trainer.profile_steps is not None
+                        self.global_steps + 1 in self.config.global_profiler.steps
+                        if self.config.global_profiler.steps is not None
                         else False
                     )
                     self._stop_profiling(
                         curr_step_profile and not next_step_profile
-                        if self.config.trainer.profile_continuous_steps
+                        if self.config.global_profiler.profile_continuous_steps
                         else curr_step_profile
                     )
                     prev_step_profile = curr_step_profile

recipe/dapo/main_dapo.py

@@ -45,10 +45,13 @@ def run_ppo(config) -> None:
 
     if (
         is_cuda_available
-        and OmegaConf.select(config.trainer, "profile_steps") is not None
-        and len(OmegaConf.select(config.trainer, "profile_steps")) > 0
+        and config.global_profiler.tool == "nsys"
+        and OmegaConf.select(config.global_profiler, "steps") is not None
+        and len(OmegaConf.select(config.global_profiler, "steps")) > 0
     ):
-        nsight_options = OmegaConf.to_container(config.trainer.controller_nsight_options)
+        nsight_options = OmegaConf.to_container(
+            config.global_profiler.global_tool_config.nsys.controller_nsight_options
+        )
         runner = TaskRunner.options(runtime_env={"nsight": nsight_options}).remote()
     else:
         runner = TaskRunner.remote()