plugin implementation

.gitignore

@@ -186,3 +186,6 @@ out/
 
 # vim
 *.swp
+
+# symlinked to axolotl-artifacts in docker containers
+outputs

model-out/eval_summary.csv

@@ -1,6 +0,0 @@
-metric,training,validation
-loss,1.8773103952407837,1.915901780128479
-model_preparation_time,0.0051,0.0051
-runtime,89.7635,8.9565
-samples_per_second,20.053,22.33
-steps_per_second,20.053,22.33

outputs

@@ -1 +0,0 @@
-/workspace/data/axolotl-artifacts

src/axolotl/cli/evaluate.py

@@ -3,7 +3,7 @@ CLI to run training on a model
 """
 import logging
 from pathlib import Path
-from typing import Union
+from typing import Dict, Union
 
 import fire
 from dotenv import load_dotenv
@@ -23,7 +23,7 @@ from axolotl.evaluate import evaluate
 LOG = logging.getLogger("axolotl.cli.evaluate")
 
 
-def do_evaluate(cfg, cli_args) -> None:
+def do_evaluate(cfg, cli_args) -> Dict[str, float]:
     # pylint: disable=duplicate-code
     print_axolotl_text_art()
     check_accelerate_default_config()
@@ -34,7 +34,7 @@ def do_evaluate(cfg, cli_args) -> None:
     else:
         dataset_meta = load_datasets(cfg=cfg, cli_args=cli_args)
 
-    evaluate(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
+    return evaluate(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
 
 
 def do_cli(config: Union[Path, str] = Path("examples/"), **kwargs) -> None:

src/axolotl/cli/integrations/convert_differential_transformer.py

@@ -15,7 +15,7 @@ from transformers import HfArgumentParser
 from axolotl.cli import load_cfg, print_axolotl_text_art
 from axolotl.common.cli import ConvertDiffTransformerCliArgs, load_model_and_tokenizer
 from axolotl.integrations.differential_transformer.convert import (
-    convert_to_diff_attention,
+    convert_to_differential_attention,
 )
 
 LOG = logging.getLogger(__name__)
@@ -79,7 +79,7 @@ def convert_differential_transformer(cfg, cli_args, config_path):
     # Convert attention
     LOG.info("Converting to differential attention...")
     try:
-        model = convert_to_diff_attention(
+        model = convert_to_differential_attention(
             model=model,
             zero_init=cli_args.zero_init,
             sublayer_norm=cli_args.sublayer_norm,
@@ -111,7 +111,10 @@ def convert_differential_transformer(cfg, cli_args, config_path):
             data = yaml.safe_load(file) or {}
 
         data["base_model"] = cfg.output_dir
-        data["diff_attention"] = True
+        data["differential_attention"] = True
+        data["plugins"] = [
+            "axolotl.integrations.differential_transformer.DifferentialTransformerPlugin"
+        ]
 
         with open(output_config_path, "w", encoding="utf-8") as file:
             yaml.dump(data, file)

src/axolotl/integrations/config.py

@@ -43,10 +43,12 @@ def merge_input_args():
     input_args: List[str] = plugin_manager.get_input_args()
     plugin_classes = []
     dynamic_input = ""
+
     for plugin_args in input_args:
         plugin_module, plugin_cls = plugin_args.rsplit(".", 1)
         dynamic_input += f"from {plugin_module} import {plugin_cls}\n"
         plugin_classes.append(plugin_cls)
+
     if dynamic_input:
         dynamic_input += f"class AxolotlConfigWCapabilities(AxolotlConfigWCapabilitiesBase, {', '.join(plugin_classes)}):\n    pass\n"
         dynamic_input += f"class AxolotlInputConfig(AxolotlInputConfigBase, {', '.join(plugin_classes)}):\n    pass\n"
@@ -62,4 +64,5 @@ def merge_input_args():
             "AxolotlConfigWCapabilities"
         ]
         return AxolotlConfigWCapabilities, AxolotlInputConfig
+
     return AxolotlConfigWCapabilitiesBase, AxolotlInputConfigBase

src/axolotl/integrations/differential_transformer/README.md

@@ -0,0 +1,10 @@
+# Differential Transformer
+
+### Usage
+
+```yaml
+plugins:
+  - axolotl.integrations.differential_transformer.DifferentialTransformerPlugin
+
+differential_attention: true
+```

src/axolotl/integrations/differential_transformer/__init__.py

@@ -0,0 +1,25 @@
+"""Definition of differential transformer plugin."""
+
+import logging
+
+from axolotl.integrations.base import BasePlugin
+
+LOG = logging.getLogger(__name__)
+
+
+class DifferentialTransformerPlugin(BasePlugin):
+    """
+    Plugin for differential transformer integration with Axolotl.
+    """
+
+    def get_input_args(self):
+        return "axolotl.integrations.differential_transformer.args.DifferentialTransformerArgs"
+
+    def pre_model_load(self, cfg):
+        """Apply differential attention patch before model loading if enabled."""
+        if cfg.differential_attention:
+            from axolotl.monkeypatch.attention.differential import (
+                patch_llama_attention_classes,
+            )
+
+            patch_llama_attention_classes()

src/axolotl/integrations/differential_transformer/args.py

@@ -0,0 +1,14 @@
+"""Module for handling differential transfomer input arguments."""
+
+import logging
+from typing import Optional
+
+from pydantic import BaseModel
+
+LOG = logging.getLogger(__name__)
+
+
+class DifferentialTransformerArgs(BaseModel):
+    """Input args for differential transformer."""
+
+    differential_attention: Optional[bool] = None

src/axolotl/integrations/differential_transformer/convert.py

@@ -80,7 +80,7 @@ def copy_attention_weights(
     )
 
 
-def convert_to_diff_attention(
+def convert_to_differential_attention(
     model: PreTrainedModel, zero_init: bool = False, sublayer_norm: bool = True
 ) -> PreTrainedModel:
     """Convert a pre-trained model's attention layers to differential attention"""

src/axolotl/utils/config/models/input/v0_4_1/__init__.py

@@ -724,8 +724,6 @@ class AxolotlInputConfig(
 
     eager_attention: Optional[bool] = None
 
-    diff_attention: Optional[bool] = None
-
     unsloth_cross_entropy_loss: Optional[bool] = None
     unsloth_lora_mlp: Optional[bool] = None
     unsloth_lora_qkv: Optional[bool] = None

src/axolotl/utils/models.py

@@ -444,13 +444,6 @@ class ModelLoader:
 
             patch_mistral_cross_entropy()
 
-        if self.cfg.diff_attention:
-            from axolotl.monkeypatch.attention.differential import (
-                patch_llama_attention_classes,
-            )
-
-            patch_llama_attention_classes()
-
     def patch_attention(self) -> None:
         if hasattr(self.model_config, "model_type"):
             if self.model_config.model_type == "mllama" and self.cfg.flash_attention:
@@ -721,7 +714,7 @@ class ModelLoader:
             if not self.cfg.sample_packing and self.cfg.s2_attention:
                 pass
 
-            if self.cfg.diff_attention:
+            if self.cfg.differential_attention:
                 self.model_kwargs[
                     "attn_implementation"
                 ] = "differential_flash_attention_2"
@@ -734,7 +727,7 @@ class ModelLoader:
                     "flash_attention_2"
                 )
         elif self.cfg.sdp_attention:
-            if self.cfg.diff_attention:
+            if self.cfg.differential_attention:
                 self.model_kwargs["attn_implementation"] = "differential_sdpa"
                 self.model_config._attn_implementation = (  # pylint: disable=protected-access
                     "differential_sdpa"
@@ -745,7 +738,7 @@ class ModelLoader:
                     "sdpa"
                 )
         elif self.cfg.eager_attention:
-            if self.cfg.diff_attention:
+            if self.cfg.differential_attention:
                 self.model_kwargs["attn_implementation"] = "differential_eager"
                 self.model_config._attn_implementation = (  # pylint: disable=protected-access
                     "differential_eager"
@@ -755,7 +748,7 @@ class ModelLoader:
                 self.model_config._attn_implementation = (  # pylint: disable=protected-access
                     "eager"
                 )
-        elif self.cfg.diff_attention:
+        elif self.cfg.differential_attention:
             self.model_kwargs["attn_implementation"] = "differential_eager"
             self.model_config._attn_implementation = (  # pylint: disable=protected-access
                 "differential_eager"

tests/e2e/integrations/test_convert_differential_transformer.py

@@ -6,12 +6,14 @@ from typing import Optional
 
 import pytest
 import yaml
+from pytest import approx
 
 from axolotl.cli import load_cfg
+from axolotl.cli.evaluate import do_evaluate
 from axolotl.cli.integrations.convert_differential_transformer import (
     convert_differential_transformer,
 )
-from axolotl.common.cli import ConvertDiffTransformerCliArgs
+from axolotl.common.cli import ConvertDiffTransformerCliArgs, EvaluateCliArgs
 
 
 @pytest.fixture()
@@ -19,9 +21,12 @@ def base_config():
     """Basic config for testing."""
     return {
         "base_model": "HuggingFaceTB/SmolLM2-135M",
+        "plugins": [
+            "axolotl.integrations.differential_transformer.DifferentialTransformerPlugin",
+        ],
         "datasets": [
             {
-                "path": "mhenrichsen/alpaca_2k_test",
+                "path": "axolotl-ai-co/alpaca_100_test",
                 "type": "alpaca",
             },
         ],
@@ -103,7 +108,9 @@ def test_conversion_cli_reproduce(tmp_path: Path, base_config):
     assert (output_dir / "axolotl_config.yml").exists()
 
 
-@pytest.mark.parametrize("attention", ["sdp_attention", "flash_attention"])
+@pytest.mark.parametrize(
+    "attention", ["eager_attention", "sdp_attention", "flash_attention"]
+)
 def test_conversion_cli_repoduce_attentions(
     tmp_path: Path, base_config, attention: Optional[str]
 ):
@@ -125,3 +132,42 @@ def test_conversion_cli_repoduce_attentions(
     assert (output_dir / "model.safetensors").exists()
     assert (output_dir / "config.json").exists()
     assert (output_dir / "axolotl_config.yml").exists()
+
+
+def test_conversion_and_eval_cli(tmp_path: Path, base_config):
+    output_dir = tmp_path / "converted"
+    base_config["output_dir"] = str(output_dir)
+
+    config_path = tmp_path / "config.yml"
+    with open(config_path, "w", encoding="utf-8") as file:
+        yaml.dump(base_config, file)
+
+    cfg = load_cfg(str(config_path))
+    cli_args = ConvertDiffTransformerCliArgs(
+        debug=True, zero_init=True, sublayer_norm=False
+    )
+    _, debug_info = convert_differential_transformer(cfg, cli_args, str(config_path))
+
+    assert debug_info["generations_match"] is True
+    assert (output_dir / "model.safetensors").exists()
+    assert (output_dir / "config.json").exists()
+    assert (output_dir / "axolotl_config.yml").exists()
+
+    eval_cfg = load_cfg(str(output_dir))
+    eval_cli_args = EvaluateCliArgs()
+    all_metrics = do_evaluate(eval_cfg, eval_cli_args)
+
+    assert list(all_metrics.keys()) == [
+        "train_loss",
+        "train_model_preparation_time",
+        "train_runtime",
+        "train_samples_per_second",
+        "train_steps_per_second",
+        "eval_loss",
+        "eval_model_preparation_time",
+        "eval_runtime",
+        "eval_samples_per_second",
+        "eval_steps_per_second",
+    ]
+    assert all_metrics["train_loss"] == approx(1.7307, rel=1e-4)
+    assert all_metrics["eval_loss"] == approx(1.8387, rel=1e-4)