fix: Add version limits for torchao, ensure compat with 0.12 + AIU

fms_mo/aiu_addons/fp8/fp8_linear.py

@@ -38,6 +38,46 @@
         shard_base_linear,
     )
     from fms.modules.tp import ShardType, TPModule
+
+    # Register decomps for torchao >= 0.12 + AIU.
+    # This import only succeeds if torchao is 0.12 or higher
+    try:
+        # Third Party
+        from torchao.quantization.quant_primitives import _expand_scale_to_tensor_shape
+
+        # This function is copied from _quantize_affine_float8
+        # in torchao.quantization.quant_primitives, but removing
+        # the wrapping that turns it into a custom pytorch op
+        def _quantize_affine_float8_custom(
+            tensor: torch.Tensor,
+            scale: torch.Tensor,
+            float8_dtype: torch.dtype = torch.float8_e4m3fn,
+        ) -> torch.Tensor:
+            """
+            Quantizes the high precision floating point tensor
+            to a float8 tensor, using the given scaling factor.
+            """
+            tensor_fp32 = tensor.to(torch.float32)
+
+            # Expand scale to match tensor dimensions for block-wise quantization
+            scale_expanded = _expand_scale_to_tensor_shape(scale, tensor.shape)
+
+            tensor_scaled = tensor_fp32 / scale_expanded
+            max_value = torch.finfo(float8_dtype).max
+            tensor_clamped = tensor_scaled.clamp(min=-max_value, max=max_value)
+            fp8_tensor = tensor_clamped.to(float8_dtype)
+            return fp8_tensor
+
+        quant_lib = torch.library.Library("torchao", "FRAGMENT")
+        quant_lib.impl(
+            "quantize_affine_float8",
+            _quantize_affine_float8_custom,
+            "CompositeImplicitAutograd",
+        )
+    except ImportError:
+        pass
+
+    # Third Party
     from torchao.dtypes.affine_quantized_tensor import (
         AffineQuantizedTensor,
         to_affine_quantized_floatx,

pyproject.toml

@@ -35,7 +35,7 @@ dependencies = [
 
 [project.optional-dependencies]
 examples = ["ninja>=1.11.1.1,<2.0", "evaluate", "huggingface_hub"]
-fp8 = ["llmcompressor", "torchao"]
+fp8 = ["llmcompressor", "torchao>=0.11,<=0.12"]
 gptq = ["Cython", "gptqmodel>=1.7.3"]
 mx = ["microxcaling>=1.1"]
 opt = ["fms-model-optimizer[fp8, gptq, mx]"]

tox.ini

@@ -34,7 +34,7 @@ deps =
     pylint>=2.16.2,<4.0
     pylint-pydantic
     ibm-fms
-    torchao
+    torchao>=0.11,<=0.12
 commands =
     {basepython} -m pylint --load-plugins pylint_pydantic fms_mo/ tests/