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Deprecate BestOfNSampler
(#4291)
Co-authored-by: behroozazarkhalili <ermiaazarkhalili> Co-authored-by: Behrooz Azarkhalili <80390531+behroozazarkhalili@users.noreply.github.com>
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# Best of N sampling: Alternative ways to get better model output without RL based fine-tuning
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# Best of N sampling: Alternative ways to get better model output without RL based fine-tuning
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> [!WARNING]
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> Best-of-N sampling is deprecated and will be removed in TRL 0.25.0.
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Within the extras module is the `best-of-n` sampler class that serves as an alternative method of generating better model output.
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Within the extras module is the `best-of-n` sampler class that serves as an alternative method of generating better model output.
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As to how it fares against the RL based fine-tuning, please look in the `examples` directory for a comparison example
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As to how it fares against the RL based fine-tuning, please look in the `examples` directory for a comparison example
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@ -12,6 +12,7 @@
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# See the License for the specific language governing permissions and
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# limitations under the License.
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import warnings
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from typing import Any, Callable, Optional, Union
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from typing import Any, Callable, Optional, Union
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import torch
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import torch
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@ -42,8 +43,16 @@ class BestOfNSampler:
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generation_config ([`~transformers.GenerationConfig`], *optional*):
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generation_config ([`~transformers.GenerationConfig`], *optional*):
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Generation config passed to the underlying model's `generate` method. See
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Generation config passed to the underlying model's `generate` method. See
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[`~transformers.GenerationConfig`] for more details.
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[`~transformers.GenerationConfig`] for more details.
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<Deprecated version="0.24.0">
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`BestOfNSampler` is deprecated and will be removed in version 0.25.
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</Deprecated>
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"""
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"""
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warnings.warn("`BestOfNSampler` is deprecated and will be removed in TRL 0.25.", FutureWarning, stacklevel=2)
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def __init__(
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def __init__(
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self,
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self,
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model: PreTrainedModelWrapper,
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model: PreTrainedModelWrapper,
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