[Mlir-commits] [mlir] 57427f8 - Support float8_e3m4 and float8_e4m3 in np_to_memref (#186453)

[llvmlistbot at llvm.org]

Author: srcarroll
Date: 2026-03-15T09:35:32-05:00
New Revision: 57427f84fe5fdda71aef4be257ed28d7b4f55d05

URL: https://github.com/llvm/llvm-project/commit/57427f84fe5fdda71aef4be257ed28d7b4f55d05
DIFF: https://github.com/llvm/llvm-project/commit/57427f84fe5fdda71aef4be257ed28d7b4f55d05.diff

LOG: Support float8_e3m4 and float8_e4m3 in np_to_memref (#186453)

This patch adds support for `float8_e3m4` and `float8_e4m3` in
`np_to_memref.py` by adding the appropriate ctypes structures

Added: 
    

Modified: 
    mlir/python/mlir/runtime/np_to_memref.py
    mlir/test/python/execution_engine.py

Removed: 
    


################################################################################
diff  --git a/mlir/python/mlir/runtime/np_to_memref.py b/mlir/python/mlir/runtime/np_to_memref.py
index 8cca1e7ad4a9e..d65ba51afdb90 100644
--- a/mlir/python/mlir/runtime/np_to_memref.py
+++ b/mlir/python/mlir/runtime/np_to_memref.py
@@ -37,12 +37,25 @@ class BF16(ctypes.Structure):
 
     _fields_ = [("bf16", ctypes.c_int16)]
 
+
 class F8E5M2(ctypes.Structure):
     """A ctype representation for MLIR's Float8E5M2."""
 
     _fields_ = [("f8E5M2", ctypes.c_int8)]
 
 
+class F8E3M4(ctypes.Structure):
+    """A ctype representation for MLIR's Float8E3M4."""
+
+    _fields_ = [("f8E3M4", ctypes.c_int8)]
+
+
+class F8E4M3(ctypes.Structure):
+    """A ctype representation for MLIR's Float8E4M3."""
+
+    _fields_ = [("f8E4M3", ctypes.c_int8)]
+
+
 # https://stackoverflow.com/questions/26921836/correct-way-to-test-for-numpy-dtype
 def as_ctype(dtp):
     """Converts dtype to ctype."""
@@ -56,6 +69,10 @@ def as_ctype(dtp):
         return BF16
     if ml_dtypes is not None and dtp == ml_dtypes.float8_e5m2:
         return F8E5M2
+    if ml_dtypes is not None and dtp == ml_dtypes.float8_e3m4:
+        return F8E3M4
+    if ml_dtypes is not None and dtp == ml_dtypes.float8_e4m3:
+        return F8E4M3
     return np.ctypeslib.as_ctypes_type(dtp)
 
 
@@ -68,15 +85,17 @@ def to_numpy(array):
     if array.dtype == F16:
         return array.view("float16")
     assert not (
-        array.dtype == BF16 and ml_dtypes is None
-    ), f"bfloat16 requires the ml_dtypes package, please run:\n\npip install ml_dtypes\n"
+        array.dtype in (BF16, F8E5M2, F8E3M4, F8E4M3) and ml_dtypes is None
+    ), f"{array.dtype=} requires the ml_dtypes package, please run:\n\npip install ml_dtypes\n"
     if array.dtype == BF16:
         return array.view("bfloat16")
-    assert not (
-        array.dtype == F8E5M2 and ml_dtypes is None
-    ), f"float8_e5m2 requires the ml_dtypes package, please run:\n\npip install ml_dtypes\n"
     if array.dtype == F8E5M2:
         return array.view("float8_e5m2")
+    if array.dtype == F8E3M4:
+        return array.view("float8_e3m4")
+    if array.dtype == F8E4M3:
+        return array.view("float8_e4m3")
+
     return array
 
 

diff  --git a/mlir/test/python/execution_engine.py b/mlir/test/python/execution_engine.py
index b11340f2c19ce..858ee089042ad 100644
--- a/mlir/test/python/execution_engine.py
+++ b/mlir/test/python/execution_engine.py
@@ -8,7 +8,7 @@
 from mlir.runtime import *
 
 try:
-    from ml_dtypes import bfloat16, float8_e5m2
+    from ml_dtypes import bfloat16, float8_e5m2, float8_e3m4, float8_e4m3
 
     HAS_ML_DTYPES = True
 except ModuleNotFoundError:
@@ -623,6 +623,90 @@ def testF8E5M2Memref():
     log("TEST: testF8E5M2Memref")
 
 
+# Test f8E3M4 memrefs
+# CHECK-LABEL: TEST: testF8E3M4Memref
+def testF8E3M4Memref():
+    with Context():
+        module = Module.parse(
+            """
+    module  {
+      func.func @main(%arg0: memref<1xf8E3M4>,
+                      %arg1: memref<1xf8E3M4>) attributes { llvm.emit_c_interface } {
+        %0 = arith.constant 0 : index
+        %1 = memref.load %arg0[%0] : memref<1xf8E3M4>
+        memref.store %1, %arg1[%0] : memref<1xf8E3M4>
+        return
+      }
+    } """
+        )
+
+        arg1 = np.array([0.5]).astype(float8_e3m4)
+        arg2 = np.array([0.0]).astype(float8_e3m4)
+
+        arg1_memref_ptr = ctypes.pointer(
+            ctypes.pointer(get_ranked_memref_descriptor(arg1))
+        )
+        arg2_memref_ptr = ctypes.pointer(
+            ctypes.pointer(get_ranked_memref_descriptor(arg2))
+        )
+
+        execution_engine = ExecutionEngine(lowerToLLVM(module))
+        execution_engine.invoke("main", arg1_memref_ptr, arg2_memref_ptr)
+
+        # test to-numpy utility
+        x = ranked_memref_to_numpy(arg2_memref_ptr[0])
+        assert len(x) == 1
+        assert x[0] == 0.5
+
+
+if HAS_ML_DTYPES:
+    run(testF8E3M4Memref)
+else:
+    log("TEST: testF8E3M4Memref")
+
+
+# Test f8E4M3 memrefs
+# CHECK-LABEL: TEST: testF8E4M3Memref
+def testF8E4M3Memref():
+    with Context():
+        module = Module.parse(
+            """
+    module  {
+      func.func @main(%arg0: memref<1xf8E4M3>,
+                      %arg1: memref<1xf8E4M3>) attributes { llvm.emit_c_interface } {
+        %0 = arith.constant 0 : index
+        %1 = memref.load %arg0[%0] : memref<1xf8E4M3>
+        memref.store %1, %arg1[%0] : memref<1xf8E4M3>
+        return
+      }
+    } """
+        )
+
+        arg1 = np.array([0.5]).astype(float8_e4m3)
+        arg2 = np.array([0.0]).astype(float8_e4m3)
+
+        arg1_memref_ptr = ctypes.pointer(
+            ctypes.pointer(get_ranked_memref_descriptor(arg1))
+        )
+        arg2_memref_ptr = ctypes.pointer(
+            ctypes.pointer(get_ranked_memref_descriptor(arg2))
+        )
+
+        execution_engine = ExecutionEngine(lowerToLLVM(module))
+        execution_engine.invoke("main", arg1_memref_ptr, arg2_memref_ptr)
+
+        # test to-numpy utility
+        x = ranked_memref_to_numpy(arg2_memref_ptr[0])
+        assert len(x) == 1
+        assert x[0] == 0.5
+
+
+if HAS_ML_DTYPES:
+    run(testF8E4M3Memref)
+else:
+    log("TEST: testF8E4M3Memref")
+
+
 #  Test addition of two 2d_memref
 # CHECK-LABEL: TEST: testDynamicMemrefAdd2D
 def testDynamicMemrefAdd2D():