deprecations

mosaicml · Sep 25, 2024 · 6858db9 · 6858db9
1 parent 7cb1c08
commit 6858db9
Show file tree

Hide file tree

Showing 4 changed files with 4 additions and 109 deletions.
diff --git a/llmfoundry/command_utils/eval.py b/llmfoundry/command_utils/eval.py
@@ -82,7 +82,7 @@ def evaluate_model(
         warnings.warn(
             VersionedDeprecationWarning(
                 'The argument fsdp_config is deprecated. Please use parallelism_config instead.',
-                remove_version='0.13.0',
+                remove_version='0.14.0',
             ),
         )
     if fsdp_config and parallelism_config:

diff --git a/llmfoundry/models/hf/__init__.py b/llmfoundry/models/hf/__init__.py
@@ -9,7 +9,6 @@
     prepare_hf_model_for_fsdp,
 )
 from llmfoundry.models.hf.hf_t5 import ComposerHFT5
-from llmfoundry.models.hf.model_wrapper import HuggingFaceModelWithFSDP
 
 __all__ = [
     'BaseHuggingFaceModel',
@@ -18,5 +17,4 @@
     'prepare_hf_causal_lm_model_for_fsdp',
     'prepare_hf_enc_dec_model_for_fsdp',
     'prepare_hf_model_for_fsdp',
-    'HuggingFaceModelWithFSDP',
 ]
diff --git a/llmfoundry/models/hf/model_wrapper.py b/llmfoundry/models/hf/model_wrapper.py
diff --git a/tests/models/test_model.py b/tests/models/test_model.py
@@ -39,7 +39,7 @@
 
 from llmfoundry import ComposerHFCausalLM
 from llmfoundry.layers_registry import norms
-from llmfoundry.models.hf.model_wrapper import HuggingFaceModelWithFSDP
+from llmfoundry.models.hf import BaseHuggingFaceModel
 from llmfoundry.models.layers import build_alibi_bias
 from llmfoundry.models.layers.attention import (
     check_alibi_support,
@@ -2560,7 +2560,7 @@ def test_hf_init(
         False,
     )
 
-    model = HuggingFaceModelWithFSDP(model, tokenizer)
+    model = BaseHuggingFaceModel(model, tokenizer)
 
     batch = gen_random_batch(batch_size, test_cfg)
 
@@ -2609,7 +2609,7 @@ def test_head_dim_8_flash_mqa_attn(batch_size: int = 2):
 
     mpt = MPTForCausalLM(hf_config)
 
-    model = HuggingFaceModelWithFSDP(mpt, tokenizer, shift_labels=True)
+    model = BaseHuggingFaceModel(mpt, tokenizer, shift_labels=True)
 
     model = model.to(test_cfg.device)
     batch = gen_random_batch(batch_size, test_cfg)