Remove old torchao imports, require 0.7.0+

tests/recipes/test_qat_lora_finetune_distributed.py

@@ -35,7 +35,6 @@
     safe_torch_load,
     SHARD_FNAME,
 )
-from torchtune.training.quantization import _torchao_0_7_supported
 
 
 class TestQATLoRAFinetuneDistributedRecipe:
@@ -63,7 +62,6 @@ def _fetch_expected_loss_values(self, model_type):
         "micro_batch_size, gradient_accumulation_steps, should_compile",
         [(4, 1, True), (1, 4, False)],
     )
-    @pytest.mark.skipif(not _torchao_0_7_supported, reason="needs torchao 0.7+")
     def test_loss(
         self,
         micro_batch_size,
@@ -116,7 +114,6 @@ def test_loss(
             ("llama3/8B_qat_lora", "llama3", "tune", False),
         ],
     )
-    @pytest.mark.skipif(not _torchao_0_7_supported, reason="needs torchao 0.7+")
     def test_training_state_on_resume(
         self,
         config,
@@ -217,7 +214,6 @@ def test_training_state_on_resume(
         ],
     )
     @gpu_test(gpu_count=2)
-    @pytest.mark.skipif(not _torchao_0_7_supported, reason="needs torchao 0.7+")
     def test_save_and_load_merged_weights(
         self, recipe_config, model_type, ckpt_type, tmpdir, monkeypatch
     ):

tests/torchtune/modules/peft/test_lora.py

@@ -15,7 +15,6 @@
 from torchtune import training
 from torchtune.modules.common_utils import reparametrize_as_dtype_state_dict_post_hook
 from torchtune.modules.peft import LoRALinear, QATLoRALinear
-from torchtune.training.quantization import _torchao_0_7_supported
 from torchtune.training.seed import set_seed
 
 
@@ -237,7 +236,6 @@ def test_quantized_state_dict(self, dtype):
             lora_linear.weight.quantized_data, lora_linear_reload.weight.quantized_data
         )
 
-    @pytest.mark.skipif(not _torchao_0_7_supported, reason="needs torchao 0.7+")
     def test_qat_lora_forward(self, inputs, lora_linear, out_dim) -> None:
         lora_linear = lora_linear(use_bias=True, dtype=torch.float32)
         qat_lora_linear = QATLoRALinear.from_lora_linear(lora_linear)

torchtune/training/quantization.py

@@ -7,44 +7,26 @@
 from typing import Callable, Optional
 
 from torch import nn
-from torchtune.modules.peft.lora import LoRALinear, QATLoRALinear
-
 
-try:
-    # torchao 0.7+
-    from torchao.dtypes import TensorCoreTiledLayout
-except ImportError:
-    # torchao 0.6 and before
-    from torchao.dtypes import TensorCoreTiledLayoutType as TensorCoreTiledLayout
+from torchao.dtypes import TensorCoreTiledLayout
 
 from torchao.quantization import (
     int4_weight_only,
     int8_dynamic_activation_int4_weight,
     quantize_,
 )
 
-try:
-    # torchao 0.7+
-    from torchao.quantization.qat import (
-        Int4WeightOnlyQATQuantizer,
-        Int8DynActInt4WeightQATQuantizer,
-    )
-    from torchao.quantization.qat.linear import (
-        disable_4w_fake_quant,
-        disable_8da4w_fake_quant,
-        enable_4w_fake_quant,
-        enable_8da4w_fake_quant,
-    )
-except ImportError:
-    # torchao 0.6 and before
-    from torchao.quantization.prototype.qat import (
-        disable_4w_fake_quant,
-        disable_8da4w_fake_quant,
-        enable_4w_fake_quant,
-        enable_8da4w_fake_quant,
-        Int4WeightOnlyQATQuantizer,
-        Int8DynActInt4WeightQATQuantizer,
-    )
+from torchao.quantization.qat import (
+    Int4WeightOnlyQATQuantizer,
+    Int8DynActInt4WeightQATQuantizer,
+)
+from torchao.quantization.qat.linear import (
+    disable_4w_fake_quant,
+    disable_8da4w_fake_quant,
+    enable_4w_fake_quant,
+    enable_8da4w_fake_quant,
+)
+from torchtune.modules.peft.lora import LoRALinear, QATLoRALinear
 
 
 __all__ = [
@@ -58,11 +40,10 @@
 ]
 
 
-_torchao_0_7_supported = True
 try:
     from torchao.quantization import qat  # noqa: F401
-except ImportError:
-    _torchao_0_7_supported = False
+except ImportError as e:
+    raise ValueError("Need torchao version 0.7.0+") from e
 
 _quantizer_to_mode = {}
 _quantizer_mode_to_disable_fake_quant = {}