make sure to set forward first

* fix build w pyproject to respect insalled torch version

* include in manifest

* disable duplicate code check for now

* move parser so it can be found

* add checks for correct pytorch version so this doesn't slip by again

.github/workflows/pypi.yml

@@ -41,7 +41,7 @@ jobs:
       - name: Install dependencies
         run: |
           pip3 install wheel packaging
-          pip3 install -e .
+          pip3 install --no-build-isolation -e .
           pip3 install -r requirements-dev.txt -r requirements-tests.txt
 
       - name: Extract tag name

.github/workflows/tests-nightly.yml

@@ -44,6 +44,11 @@ jobs:
           python-version: ${{ matrix.python_version }}
           cache: 'pip' # caching pip dependencies
 
+      - name: upgrade pip
+        run: |
+          pip3 install --upgrade pip
+          pip3 install --upgrade packaging setuptools wheel
+
       - name: Install PyTorch
         run: |
           pip3 install torch==${{ matrix.pytorch_version }} --index-url https://download.pytorch.org/whl/cpu
@@ -60,11 +65,15 @@ jobs:
         run: |
           pip3 install --upgrade pip
           pip3 install --upgrade packaging
-          pip3 install -U -e .
+          pip3 install --no-build-isolation -U -e .
           python scripts/unsloth_install.py | sh
           python scripts/cutcrossentropy_install.py | sh
           pip3 install -r requirements-dev.txt -r requirements-tests.txt
 
+      - name: Make sure PyTorch version wasn't clobbered
+        run: |
+          python -c "import torch; assert '${{ matrix.pytorch_version }}' in torch.__version__"
+
       - name: Ensure axolotl CLI was installed
         run: |
           axolotl --help

.github/workflows/tests.yml

@@ -78,11 +78,15 @@ jobs:
       - name: Install dependencies
         run: |
           pip3 show torch
-          pip3 install -U -e .
+          pip3 install --no-build-isolation -U -e .
           python scripts/unsloth_install.py | sh
           python scripts/cutcrossentropy_install.py | sh
           pip3 install -r requirements-dev.txt -r requirements-tests.txt
 
+      - name: Make sure PyTorch version wasn't clobbered
+        run: |
+          python -c "import torch; assert '${{ matrix.pytorch_version }}' in torch.__version__"
+
       - name: Ensure axolotl CLI was installed
         run: |
           axolotl --help
@@ -120,7 +124,7 @@ jobs:
       - name: upgrade pip
         run: |
           pip3 install --upgrade pip
-          pip3 install --upgrade packaging setuptools wheel
+          pip3 install --upgrade packaging setuptools setuptools_scm build wheel
 
       - name: Install PyTorch
         run: |
@@ -129,12 +133,16 @@ jobs:
       - name: Install dependencies
         run: |
           pip3 show torch
-          python3 setup.py sdist
-          pip3 install dist/axolotl*.tar.gz
+          python -m build --no-isolation --sdist
+          pip3 install --no-build-isolation dist/axolotl*.tar.gz
           python scripts/unsloth_install.py | sh
           python scripts/cutcrossentropy_install.py | sh
           pip3 install -r requirements-dev.txt -r requirements-tests.txt
 
+      - name: Make sure PyTorch version wasn't clobbered
+        run: |
+          python -c "import torch; assert '${{ matrix.pytorch_version }}' in torch.__version__"
+
       - name: Ensure axolotl CLI was installed
         run: |
           axolotl --help

MANIFEST.in

@@ -1,4 +1,5 @@
 include requirements.txt
 include README.md
 include LICENSE
+include src/setuptools_axolotl_dynamic_dependencies.py
 recursive-include axolotl *.py

README.md

@@ -112,7 +112,7 @@ Get started with Axolotl in just a few steps! This quickstart guide will walk yo
 **Requirements**: *Nvidia* GPU (Ampere architecture or newer for `bf16` and Flash Attention) or *AMD* GPU, Python >=3.10 and PyTorch >=2.3.1.
 
 ```bash
-pip3 install axolotl[flash-attn,deepspeed]
+pip3 install --no-build-isolation axolotl[flash-attn,deepspeed]
 
 # download examples and optionally deepspeed configs to the local path
 axolotl fetch examples
@@ -131,7 +131,7 @@ from source.
 git clone https://github.com/axolotl-ai-cloud/axolotl.git
 cd axolotl
 pip3 install packaging ninja
-pip3 install -e '.[flash-attn,deepspeed]'
+pip3 install --no-build-isolation -e '.[flash-attn,deepspeed]'
 ```
 
 ### Axolotl CLI Usage
@@ -320,7 +320,7 @@ docker run --privileged --gpus '"all"' --shm-size 10g --rm -it --name axolotl --
   3. Install Axolotl along with python dependencies
         ```bash
         pip3 install packaging
-        pip3 install -e '.[flash-attn,deepspeed]'
+        pip3 install --no-build-isolation -e '.[flash-attn,deepspeed]'
         ```
   4. (Optional) Login to Huggingface to use gated models/datasets.
         ```bash
@@ -399,7 +399,7 @@ Please use WSL or Docker!
 
 Use the below instead of the install method in QuickStart.
 ```
-pip3 install -e '.'
+pip3 install --no-build-isolation -e '.'
 ```
 More info: [mac.md](/docs/mac.qmd)
 

cicd/Dockerfile.jinja

@@ -31,9 +31,9 @@ RUN if [ "$NIGHTLY_BUILD" = "true" ] ; then \
     fi
 
 RUN if [ "$AXOLOTL_EXTRAS" != "" ] ; then \
-        pip install -e .[deepspeed,flash-attn,optimizers,$AXOLOTL_EXTRAS] $AXOLOTL_ARGS; \
+        pip install --no-build-isolation -e .[deepspeed,flash-attn,optimizers,$AXOLOTL_EXTRAS] $AXOLOTL_ARGS; \
     else \
-        pip install -e .[deepspeed,flash-attn,optimizers] $AXOLOTL_ARGS; \
+        pip install --no-build-isolation -e .[deepspeed,flash-attn,optimizers] $AXOLOTL_ARGS; \
     fi
 
 RUN python scripts/unsloth_install.py | sh

cicd/cicd.sh

@@ -1,6 +1,8 @@
 #!/bin/bash
 set -e
 
+python -c "import torch; assert '$PYTORCH_VERSION' in torch.__version__"
+
 pytest -v --durations=10 -n8 --ignore=tests/e2e/ --ignore=tests/patched/ /workspace/axolotl/tests/
 # pytest -v --durations=10 -n8 --dist loadfile /workspace/axolotl/tests/patched/
 pytest -v --durations=10 -n1 --dist loadfile /workspace/axolotl/tests/e2e/patched/

docker/Dockerfile

@@ -20,9 +20,9 @@ WORKDIR /workspace/axolotl
 
 # If AXOLOTL_EXTRAS is set, append it in brackets
 RUN if [ "$AXOLOTL_EXTRAS" != "" ] ; then \
-        pip install -e .[deepspeed,flash-attn,optimizers,$AXOLOTL_EXTRAS] $AXOLOTL_ARGS; \
+        pip install --no-build-isolation -e .[deepspeed,flash-attn,optimizers,$AXOLOTL_EXTRAS] $AXOLOTL_ARGS; \
     else \
-        pip install -e .[deepspeed,flash-attn,optimizers] $AXOLOTL_ARGS; \
+        pip install --no-build-isolation -e .[deepspeed,flash-attn,optimizers] $AXOLOTL_ARGS; \
     fi
 
 RUN python scripts/unsloth_install.py | sh

docker/Dockerfile-tests

@@ -24,9 +24,9 @@ RUN git fetch origin +$GITHUB_REF && \
 
 # If AXOLOTL_EXTRAS is set, append it in brackets
 RUN if [ "$AXOLOTL_EXTRAS" != "" ] ; then \
-        pip install -e .[deepspeed,flash-attn,mamba-ssm,$AXOLOTL_EXTRAS] $AXOLOTL_ARGS; \
+        pip install --no-build-isolation -e .[deepspeed,flash-attn,mamba-ssm,$AXOLOTL_EXTRAS] $AXOLOTL_ARGS; \
     else \
-        pip install -e .[deepspeed,flash-attn,mamba-ssm] $AXOLOTL_ARGS; \
+        pip install --no-build-isolation -e .[deepspeed,flash-attn,mamba-ssm] $AXOLOTL_ARGS; \
     fi
 
 # So we can test the Docker image

docs/amd_hpc.qmd

@@ -52,7 +52,7 @@ export GPU_ARCHS="gfx90a"
 cd flash-attention
 export PYTHON_SITE_PACKAGES=$(python -c 'import site; print(site.getsitepackages()[0])')
 patch "${PYTHON_SITE_PACKAGES}/torch/utils/hipify/hipify_python.py" hipify_patch.patch
-pip install .
+pip install --no-build-isolation .
 ```
 
 ### 6. Install Axolotl
@@ -63,7 +63,7 @@ Clone and install Axolotl:
 git clone https://github.com/axolotl-ai-cloud/axolotl
 cd axolotl
 pip install packaging ninja
-pip install -e .
+pip install --no-build-isolation -e .
 ```
 
 ### 7. Apply xformers Workaround

docs/debugging.qmd

@@ -71,7 +71,7 @@ Make sure you have an [editable install](https://setuptools.pypa.io/en/latest/us
 
 ```bash
 pip3 install packaging
-pip3 install -e '.[flash-attn,deepspeed]'
+pip3 install --no-build-isolation -e '.[flash-attn,deepspeed]'
 ```
 
 #### Remote Hosts
@@ -212,7 +212,7 @@ You will now be in the container.  Next, perform an editable install of Axolotl:
 
 ```bash
 pip3 install packaging
-pip3 install -e '.[flash-attn,deepspeed]'
+pip3 install --no-build-isolation -e '.[flash-attn,deepspeed]'
 ```
 
 ### Attach To Container

examples/colab-notebooks/colab-axolotl-example.ipynb

@@ -24,7 +24,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "!pip install axolotl[deepspeed]"
+    "!pip install --no-build-isolation axolotl[deepspeed]"
    ]
   },
   {

pyproject.toml

@@ -17,3 +17,10 @@ Homepage = "https://axolotl-ai-cloud.github.io/axolotl/"
 Repository = "https://github.com/axolotl-ai-cloud/axolotl.git"
 
 [tool.setuptools_scm]
+
+[tool.setuptools]
+py-modules = ["setuptools_axolotl_dynamic_dependencies"]
+include-package-data = true
+
+[tool.setuptools.cmdclass]
+build_py = "setuptools_axolotl_dynamic_dependencies.BuildPyCommand"

scripts/motd

@@ -13,5 +13,5 @@ cd /workspace
 rm -rf /workspace/axolotl
 git clone https://github.com/axolotl-ai-cloud/axolotl.git
 cd axolotl
-pip install --no-deps -e .
+pip install --no-build-isolation --no-deps -e .
 ```

src/axolotl/core/trainer_builder.py

@@ -996,6 +996,15 @@ class AxolotlTrainer(SchedulerMixin, Trainer):
         os.makedirs(output_dir, exist_ok=True)
         return super()._save_checkpoint(model, trial, **kwargs)
 
+    def _evaluate(self, *args, **kwargs):
+        metrics = super()._evaluate(*args, **kwargs)
+
+        # cleanup memory after evals
+        gc.collect()
+        torch.cuda.empty_cache()
+
+        return metrics
+
 
 class AxolotlMambaTrainer(AxolotlTrainer):
     """

src/axolotl/monkeypatch/models/llama/modeling_llama.py

@@ -0,0 +1,170 @@
+import contextlib
+import inspect
+import types
+
+from torchtune.training import OffloadActivations
+from transformers import LlamaConfig, LlamaForCausalLM
+
+from axolotl.monkeypatch.unsloth_ import detab_code
+
+HF_MODEL_OUTPUTS = """
+        outputs = self.model(
+            input_ids=input_ids,
+            attention_mask=attention_mask,
+            position_ids=position_ids,
+            past_key_values=past_key_values,
+            inputs_embeds=inputs_embeds,
+            use_cache=use_cache,
+            output_attentions=output_attentions,
+            output_hidden_states=output_hidden_states,
+            return_dict=return_dict,
+            cache_position=cache_position,
+            **kwargs,
+        )
+""".lstrip()
+
+PATCHED_HF_MODEL_OUTPUTS = """
+        with self.act_offloading_ctx_manager:
+            outputs = self.model(
+                input_ids=input_ids,
+                attention_mask=attention_mask,
+                position_ids=position_ids,
+                past_key_values=past_key_values,
+                inputs_embeds=inputs_embeds,
+                use_cache=use_cache,
+                output_attentions=output_attentions,
+                output_hidden_states=output_hidden_states,
+                return_dict=return_dict,
+                cache_position=cache_position,
+                **kwargs,
+            )
+""".lstrip()
+
+LCE_MODEL_OUTPUTS = """
+    outputs = self.model(
+        input_ids=input_ids,
+        attention_mask=attention_mask,
+        position_ids=position_ids,
+        past_key_values=past_key_values,
+        inputs_embeds=inputs_embeds,
+        use_cache=use_cache,
+        output_attentions=output_attentions,
+        output_hidden_states=output_hidden_states,
+        return_dict=return_dict,
+        cache_position=cache_position,
+    )
+""".lstrip()
+
+PATCHED_LCE_OUTPUTS = """
+    with self.act_offloading_ctx_manager:
+        outputs = self.model(
+            input_ids=input_ids,
+            attention_mask=attention_mask,
+            position_ids=position_ids,
+            past_key_values=past_key_values,
+            inputs_embeds=inputs_embeds,
+            use_cache=use_cache,
+            output_attentions=output_attentions,
+            output_hidden_states=output_hidden_states,
+            return_dict=return_dict,
+            cache_position=cache_position,
+        )
+""".lstrip()
+
+HF_GA_FORWARD_1 = """
+        return_dict = return_dict if return_dict is not None else self.config.use_return_dict
+
+        # decoder outputs consists of (dec_features, layer_state, dec_hidden, dec_attn)
+""".lstrip()
+
+PATCHED_HF_GA_FORWARD_1 = """
+    return_dict = return_dict if return_dict is not None else self.config.use_return_dict
+
+    # remove num_items_in_batch otherwise self.model attempts to pass it to flash_attention
+    num_items_in_batch = kwargs.pop("num_items_in_batch", None)
+
+    # decoder outputs consists of (dec_features, layer_state, dec_hidden, dec_attn)
+""".lstrip()
+
+HF_GA_FORWARD_2 = """
+        loss = None
+        if labels is not None:
+            loss = self.loss_function(logits=logits, labels=labels, vocab_size=self.config.vocab_size, **kwargs)
+""".lstrip()
+
+PATCHED_HF_GA_FORWARD_2 = """
+        loss = None
+        if labels is not None:
+            loss = self.loss_function(logits=logits, labels=labels, vocab_size=self.config.vocab_size, num_items_in_batch=num_items_in_batch, **kwargs)
+""".lstrip()
+
+
+class AxolotlLlamaForCausalLM(LlamaForCausalLM):
+    act_offloading_ctx_manager = contextlib.nullcontext()
+
+    def __init__(self, config: LlamaConfig):
+        super().__init__(config)
+
+    @classmethod
+    def set_forward(cls):
+        forward_source = inspect.getsource(LlamaForCausalLM.forward)
+        forward_source, _ = detab_code(forward_source)
+        cls.forward = types.MethodType(
+            compile(forward_source, "<forward>", "exec"), cls
+        )
+
+    @classmethod
+    def enable_act_offloading(cls):
+        forward_source = inspect.getsource(cls.forward)
+        forward_source = forward_source.replace(
+            HF_MODEL_OUTPUTS, PATCHED_HF_MODEL_OUTPUTS
+        )
+        forward_source, _ = detab_code(forward_source)
+        # replace forward method with patched version
+        cls.forward = types.MethodType(
+            compile(forward_source, "<llama_forward_w_act_offloading>", "exec"), cls
+        )
+        cls.act_offloading_ctx_manager = OffloadActivations()
+
+    @classmethod
+    def enable_liger_fce(cls, enable_act_offloading=True):
+        from liger_kernel.transformers.model.llama import (
+            lce_forward as llama_lce_forward,
+        )
+
+        if enable_act_offloading:
+            lce_source = inspect.getsource(llama_lce_forward)
+            lce_source = lce_source.replace(LCE_MODEL_OUTPUTS, PATCHED_LCE_OUTPUTS)
+            # replace forward method with patched version
+            cls.forward = types.MethodType(
+                compile(lce_source, "<llama_lce_forward_w_act_offloading>", "exec"),
+                cls,
+            )
+        else:
+            cls.forward = types.methodType(llama_lce_forward, cls)
+
+    @classmethod
+    def patch_hf_ga(cls):
+        # bugfix patch for gradient accumulation
+        forward_source = inspect.getsource(cls.forward)
+        forward_source = forward_source.replace(
+            HF_GA_FORWARD_1, PATCHED_HF_GA_FORWARD_1
+        )
+        forward_source = forward_source.replace(
+            HF_GA_FORWARD_2, PATCHED_HF_GA_FORWARD_2
+        )
+        forward_source, _ = detab_code(forward_source)
+        # replace forward method with patched version
+        cls.forward = types.MethodType(
+            compile(forward_source, "<llama_forward_ga_fix>", "exec"), cls
+        )
+
+
+def replace_auto_model():
+    from transformers import LlamaConfig
+    from transformers.models.auto import MODEL_FOR_CAUSAL_LM_MAPPING
+
+    MODEL_FOR_CAUSAL_LM_MAPPING[LlamaConfig] = AxolotlLlamaForCausalLM
+    AxolotlLlamaForCausalLM.set_forward()
+
+    return AxolotlLlamaForCausalLM

src/axolotl/utils/callbacks/__init__.py

@@ -66,10 +66,7 @@ class EvalFirstStepCallback(
         control: TrainerControl,
         **kwargs,
     ):
-        if (
-            args.evaluation_strategy == IntervalStrategy.STEPS
-            and state.global_step == 1
-        ):
+        if args.eval_strategy == IntervalStrategy.STEPS and state.global_step == 1:
             control.should_evaluate = True
         return control
 

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

@@ -679,6 +679,7 @@ class AxolotlInputConfig(
         default=False
     )
     gradient_checkpointing_kwargs: Optional[Dict[str, Any]] = None
+    activation_offloading: Optional[bool] = None
 
     unfrozen_parameters: Optional[List[str]] = None
 

src/axolotl/utils/models.py

@@ -380,6 +380,15 @@ class ModelLoader:
         plugin_manager = PluginManager.get_instance()
         plugin_manager.pre_model_load(self.cfg)
 
+        if self.cfg.model_config_type == "llama":
+            from axolotl.monkeypatch.models.llama.modeling_llama import replace_auto_model
+
+            AxolotlLlamaForCausalLM = replace_auto_model()
+
+            AxolotlLlamaForCausalLM.patch_hf_ga()
+            if self.cfg.activation_offloading:
+                AxolotlLlamaForCausalLM.enable_act_offloading()
+
         if self.cfg.fsdp:
             from axolotl.monkeypatch.trainer_fsdp_optim import (
                 patch_training_loop_for_fsdp,
@@ -1183,6 +1192,8 @@ class ModelLoader:
 
         self.apply_lora_patch()
 
+        # self.apply_patches_to_model()
+
         for _ in range(3):
             gc.collect()
             torch.cuda.empty_cache()

src/setuptools_axolotl_dynamic_dependencies.py

@@ -0,0 +1,104 @@
+"""
+dynamic requirements for axolotl
+"""
+import platform
+import re
+from importlib.metadata import PackageNotFoundError, version
+
+from setuptools.command.build_py import build_py as _build_py
+
+
+# pylint: disable=duplicate-code
+def parse_requirements():
+    _install_requires = []
+    _dependency_links = []
+    with open("./requirements.txt", encoding="utf-8") as requirements_file:
+        lines = [r.strip() for r in requirements_file.readlines()]
+        for line in lines:
+            is_extras = (
+                "flash-attn" in line
+                or "flash-attention" in line
+                or "deepspeed" in line
+                or "mamba-ssm" in line
+                or "lion-pytorch" in line
+            )
+            if line.startswith("--extra-index-url"):
+                # Handle custom index URLs
+                _, url = line.split()
+                _dependency_links.append(url)
+            elif not is_extras and line and line[0] != "#":
+                # Handle standard packages
+                _install_requires.append(line)
+
+    try:
+        xformers_version = [req for req in _install_requires if "xformers" in req][0]
+        torchao_version = [req for req in _install_requires if "torchao" in req][0]
+        autoawq_version = [req for req in _install_requires if "autoawq" in req][0]
+
+        if "Darwin" in platform.system():
+            # don't install xformers on MacOS
+            _install_requires.pop(_install_requires.index(xformers_version))
+        else:
+            # detect the version of torch already installed
+            # and set it so dependencies don't clobber the torch version
+            try:
+                torch_version = version("torch")
+            except PackageNotFoundError:
+                torch_version = "2.5.1"
+            _install_requires.append(f"torch=={torch_version}")
+
+            version_match = re.match(r"^(\d+)\.(\d+)(?:\.(\d+))?", torch_version)
+            if version_match:
+                major, minor, patch = version_match.groups()
+                major, minor = int(major), int(minor)
+                patch = (
+                    int(patch) if patch is not None else 0
+                )  # Default patch to 0 if not present
+            else:
+                raise ValueError("Invalid version format")
+
+            if (major, minor) >= (2, 5):
+                _install_requires.pop(_install_requires.index(xformers_version))
+                if patch == 0:
+                    _install_requires.append("xformers==0.0.28.post2")
+                else:
+                    _install_requires.append("xformers==0.0.28.post3")
+                _install_requires.pop(_install_requires.index(autoawq_version))
+            elif (major, minor) >= (2, 4):
+                if patch == 0:
+                    _install_requires.pop(_install_requires.index(xformers_version))
+                    _install_requires.append("xformers>=0.0.27")
+                else:
+                    _install_requires.pop(_install_requires.index(xformers_version))
+                    _install_requires.append("xformers==0.0.28.post1")
+            elif (major, minor) >= (2, 3):
+                _install_requires.pop(_install_requires.index(torchao_version))
+                if patch == 0:
+                    _install_requires.pop(_install_requires.index(xformers_version))
+                    _install_requires.append("xformers>=0.0.26.post1")
+                else:
+                    _install_requires.pop(_install_requires.index(xformers_version))
+                    _install_requires.append("xformers>=0.0.27")
+            elif (major, minor) >= (2, 2):
+                _install_requires.pop(_install_requires.index(torchao_version))
+                _install_requires.pop(_install_requires.index(xformers_version))
+                _install_requires.append("xformers>=0.0.25.post1")
+            else:
+                _install_requires.pop(_install_requires.index(torchao_version))
+                _install_requires.pop(_install_requires.index(xformers_version))
+                _install_requires.append("xformers>=0.0.23.post1")
+
+    except PackageNotFoundError:
+        pass
+    return _install_requires, _dependency_links
+
+
+class BuildPyCommand(_build_py):
+    """
+    custom build_py command to parse dynamic requirements
+    """
+
+    def finalize_options(self):
+        super().finalize_options()
+        install_requires, _ = parse_requirements()
+        self.distribution.install_requires = install_requires