initial commit

Context.py

@@ -0,0 +1,98 @@
+import configparser
+import torch
+
+from sympy.printing import str
+
+class Context:
+    accel: bool
+    device: str
+    purgeTargetDirectories: bool
+    
+    locBaseModel: str
+    locDataset: str
+    locWorkdir: str
+    locAdapter: str
+    locFull: str
+    locValidation: str
+    locGraderModel: str
+    
+    train: bool
+    storeAdapter: bool
+    trTextDsToChat: bool
+    trTextDsKeepPlainText: bool
+    trEpochs: int
+    trMaxSeqLength: int
+    trPerDeviceTrainBatchSize: int
+    trFindAutoBatchSize: bool
+    trGradientAccSteps: int
+    trGradientCheckpointing: bool
+    trGroupByLength: bool
+    trPacking: bool
+    
+    loraR: int
+    loraAlpha: int
+    loraDropout: float
+    loraBias: str
+    loraTaskType: str
+    
+    validate: bool
+    vInplace: bool
+    vAbortOnFail: bool
+    vPasses: int
+    vGenMaxTokens: int
+    vExpected: int
+    vQuantModel: bool
+    vQuantGrader: bool
+    vGraderOnCpu: bool
+    
+    mergeFull: bool
+    
+    def load(self, cfgFile):
+        cfg = configparser.ConfigParser()
+        if not cfg.read(cfgFile):
+            raise Exception("Cannot read configuration file: " + cfgFile)
+        
+        self.accel = torch.cuda.is_available() and cfg.get("Operation", "device") != "cpu"
+        self.device = (cfg.get("Operation", "device") if self.accel else "cpu") or "cpu"
+        self.purgeTargetDirectories = cfg.get("Operation", "purgeTargetDirectories").lower() == "true"
+        
+        self.locBaseModel = cfg.get("Trainer", "locBaseModel")
+        self.locDataset = cfg.get("Trainer", "locDataset")
+        self.locWorkdir = cfg.get("Trainer", "locWorkdir")
+        self.locAdapter = cfg.get("Trainer", "locAdapter")
+        self.locFull = cfg.get("Merger", "locFull")
+        self.locValidation = cfg.get("Validation", "locValidation")
+        self.locGraderModel = cfg.get("Validation", "locGraderModel")
+        
+        self.train = cfg.get("Trainer", "train").lower() == "true"
+        self.storeAdapter = cfg.get("Trainer", "storeAdapter").lower() == "true"
+        self.trTextDsToChat = cfg.get("Trainer", "trTextDsToChat").lower() == "true"
+        self.trTextDsKeepPlainText = cfg.get("Trainer", "trTextDsKeepPlainText").lower() == "true"
+        self.trEpochs = int(cfg.get("Trainer", "trEpochs") or "0") or 1
+        self.trMaxSeqLength = int(cfg.get("Trainer", "trMaxSeqLength") or "0") or None
+        self.trPerDeviceTrainBatchSize = int(cfg.get("Trainer", "trPerDeviceTrainBatchSize") or "0") or None
+        self.trFindAutoBatchSize = cfg.get("Trainer", "trFindAutoBatchSize").lower() == "true" 
+        self.trGradientAccSteps = int(cfg.get("Trainer", "trGradientAccSteps") or "0") or None
+        self.trGradientCheckpointing = cfg.get("Trainer", "trGradientCheckpointing").lower() == "true" 
+        self.trGroupByLength = cfg.get("Trainer", "trGroupByLength").lower() == "true"
+        self.trPacking = cfg.get("Trainer", "trPacking").lower() == "true"
+        
+        self.loraR = int(cfg.get("Lora", "loraR") or "0") or 64
+        self.loraAlpha = int(cfg.get("Lora", "loraAlpha") or "0") or 16
+        self.loraDropout = float(cfg.get("Lora", "loraDropout") or "0") or 0.1
+        self.loraBias = cfg.get("Lora", "loraBias") or "none"
+        self.loraTaskType = cfg.get("Lora", "loraTaskType") or "CAUSAL_LM"
+        
+        self.validate = cfg.get("Validation", "validate").lower() == "true"
+        self.vInplace = cfg.get("Validation", "vInplace").lower() == "true"
+        self.vAbortOnFail = cfg.get("Validation", "vAbortOnFail").lower() == "true"
+        self.vPasses = int(cfg.get("Validation", "vPasses") or "0") or 10
+        self.vGenMaxTokens = int(cfg.get("Validation", "vGenMaxTokens") or "0") or 100
+        self.vExpected = int(cfg.get("Validation", "vExpected") or "0") or 70
+        self.vQuantModel = cfg.get("Validation", "vQuantModel").lower() == "true"
+        self.vQuantGrader = cfg.get("Validation", "vQuantGrader").lower() == "true"
+        self.vGraderOnCpu = cfg.get("Validation", "vGraderOnCpu").lower() == "true"
+        
+        self.mergeFull = cfg.get("Merger", "mergeFull").lower() == "true"
+        
+        print(self.__dict__)