remove PerplexityCallback in pydantic api (#636)

### Description
Fix CI by dropping PerplexityCallback in pydantic api

### Type of changes
- [x ]  Bug fix (non-breaking change which fixes an issue)

### Usage
```bash
pytest sub-packages/bionemo-esm2/tests/bionemo/esm2/scripts/test_pydantic_train.py::test_pretrain_pydantic_cli
```

Related to
e553389

Signed-off-by: sichu <[email protected]>

Author: sichu2023

sub-packages/bionemo-llm/src/bionemo/llm/run/config_models.py

@@ -311,7 +311,8 @@ class TrainingConfig(BaseModel):
     accelerator: str = "gpu"
     # NOTE: VERY important for distributed training performance.
     gc_interval: int = 0
-    include_perplexity: bool = False
+    log_train_ppl: bool = False
+    log_val_ppl: bool = True
     enable_checkpointing: bool = True
 
 

sub-packages/bionemo-llm/src/bionemo/llm/train.py

@@ -32,7 +32,7 @@
 from pydantic import BaseModel
 
 from bionemo.core.utils.dtypes import get_autocast_dtype
-from bionemo.llm.lightning import BionemoLightningModule, PerplexityLoggingCallback
+from bionemo.llm.lightning import BionemoLightningModule
 from bionemo.llm.model.biobert.lightning import biobert_lightning_module
 from bionemo.llm.model.lr_scheduler import WarmupAnnealDecayHoldScheduler
 from bionemo.llm.run.config_models import (
@@ -132,9 +132,6 @@ def setup_trainer(
             LearningRateMonitor(),
         ]
 
-    if training_config.include_perplexity:
-        callbacks.append(PerplexityLoggingCallback())
-
     if training_config.gc_interval > 0:
         callbacks.append(
             nl_callbacks.GarbageCollectionCallback(
@@ -252,7 +249,11 @@ def train(
     )
 
     model: BionemoLightningModule = biobert_lightning_module(
-        config=bionemo_model_config, tokenizer=data.tokenizer, optimizer=optimizer
+        config=bionemo_model_config,
+        tokenizer=data.tokenizer,
+        optimizer=optimizer,
+        log_train_ppl=training_config.log_train_ppl,
+        log_val_ppl=training_config.log_val_ppl,
     )
     trainer: nl.Trainer = setup_trainer(parallel_config, training_config, nsys_config=nsys_config)
     nemo_logger: nl.NeMoLogger = nemo_logger_factory(experiment_config, wandb_config=wandb_config)