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HF_ML_Tasksmith

# Copyright 2020-2026 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""Distributed training backend abstraction."""

from contextlib import contextmanager


class DistributedBackend:
    """Abstracts distributed backend specifics (DeepSpeed ZeRO, FSDP) behind a uniform API.
    Detects the active backend once at construction from ``accelerator.state``, then provides context managers that are
    no-ops on backends where the operation is not needed.
    Args:
        accelerator ([`~accelerate.Accelerator`]):
            The accelerator instance managing the distributed state.
    Example:
    ```python
    >>> dist = DistributedBackend(accelerator)
    >>> with dist.gather_params(list(model.parameters())):
    ...     model.merge_adapter()
    >>> with dist.summon_full_params(model, recurse=False):
    ...     outputs = model.generate(inputs)
    ```
    """

    def __init__(self, accelerator):
        ds_plugin = accelerator.state.deepspeed_plugin
        fsdp_plugin = getattr(accelerator.state, "fsdp_plugin", None)
        self.zero_stage = ds_plugin.zero_stage if ds_plugin else 0
        self.fsdp_version = getattr(fsdp_plugin, "fsdp_version", None) if fsdp_plugin else None

    @property
    def is_zero3(self) -> bool:
        """Whether DeepSpeed ZeRO Stage 3 is active."""
        return self.zero_stage == 3

    @property
    def is_fsdp(self) -> bool:
        """Whether FSDP (any version) is active."""
        return self.fsdp_version is not None

    @contextmanager
    def gather_params(self, params):
        """Gather sharded parameters under DeepSpeed ZeRO-3; no-op otherwise.
        Args:
            params (iterable of `torch.nn.Parameter`):
                Parameters to gather.
        """
        if self.is_zero3:
            import deepspeed

            with deepspeed.zero.GatheredParameters(params):
                yield
        else:
            yield

    @contextmanager
    def summon_full_params(self, module, **kwargs):
        """Materialize full FSDP v1 parameters; no-op for FSDP v2 or non-FSDP backends.
        FSDP v2 parameters are always accessible and require no explicit materialization.
        Args:
            module (`torch.nn.Module`):
                The FSDP-wrapped module.
            **kwargs:
                Forwarded to ``FSDP.summon_full_params`` (e.g. ``recurse``, ``writeback``).
        """
        if self.fsdp_version == 1:
            from torch.distributed.fsdp import FullyShardedDataParallel as FSDP

            with FSDP.summon_full_params(module, **kwargs):
                yield
        else:
            yield

	# Copyright 2020-2026 The HuggingFace Team. All rights reserved.
	#
	# Licensed under the Apache License, Version 2.0 (the "License");
	# you may not use this file except in compliance with the License.
	# You may obtain a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
	# Unless required by applicable law or agreed to in writing, software
	# distributed under the License is distributed on an "AS IS" BASIS,
	# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	# See the License for the specific language governing permissions and
	# limitations under the License.

	"""Distributed training backend abstraction."""

	from contextlib import contextmanager


	class DistributedBackend:
	"""Abstracts distributed backend specifics (DeepSpeed ZeRO, FSDP) behind a uniform API.

	Detects the active backend once at construction from ``accelerator.state``, then provides context managers that are
	no-ops on backends where the operation is not needed.

	Args:
	accelerator ([`~accelerate.Accelerator`]):
	The accelerator instance managing the distributed state.

	Example:

	```python
	>>> dist = DistributedBackend(accelerator)
	>>> with dist.gather_params(list(model.parameters())):
	... model.merge_adapter()
	>>> with dist.summon_full_params(model, recurse=False):
	... outputs = model.generate(inputs)
	```
	"""

	def __init__(self, accelerator):
	ds_plugin = accelerator.state.deepspeed_plugin
	fsdp_plugin = getattr(accelerator.state, "fsdp_plugin", None)
	self.zero_stage = ds_plugin.zero_stage if ds_plugin else 0
	self.fsdp_version = getattr(fsdp_plugin, "fsdp_version", None) if fsdp_plugin else None

	@property
	def is_zero3(self) -> bool:
	"""Whether DeepSpeed ZeRO Stage 3 is active."""
	return self.zero_stage == 3

	@property
	def is_fsdp(self) -> bool:
	"""Whether FSDP (any version) is active."""
	return self.fsdp_version is not None

	@contextmanager
	def gather_params(self, params):
	"""Gather sharded parameters under DeepSpeed ZeRO-3; no-op otherwise.

	Args:
	params (iterable of `torch.nn.Parameter`):
	Parameters to gather.
	"""
	if self.is_zero3:
	import deepspeed

	with deepspeed.zero.GatheredParameters(params):
	yield
	else:
	yield

	@contextmanager
	def summon_full_params(self, module, **kwargs):
	"""Materialize full FSDP v1 parameters; no-op for FSDP v2 or non-FSDP backends.

	FSDP v2 parameters are always accessible and require no explicit materialization.

	Args:
	module (`torch.nn.Module`):
	The FSDP-wrapped module.
	**kwargs:
	Forwarded to ``FSDP.summon_full_params`` (e.g. ``recurse``, ``writeback``).
	"""
	if self.fsdp_version == 1:
	from torch.distributed.fsdp import FullyShardedDataParallel as FSDP

	with FSDP.summon_full_params(module, **kwargs):
	yield
	else:
	yield