Add BF16 support to reference model

* Upgrade Eigen to 3.4.0 (for bfloat16 support) and add work-
  arounds for reduce.any() and reduce.all() bugs (introduced
  between 3.3.7 and 3.4.0)
* Truncation to bfloat16 now performed in eval() methods

Signed-off-by: James Ward <james.ward@arm.com>
Signed-off-by: Jeremy Johnson <jeremy.johnson@arm.com>
Change-Id: If5f5c988d76d3d30790acf3b97081726b89205fe

1 files changed, 21 insertions, 1 deletions

diff --git a/verif/checker/tosa_result_checker.py b/verif/checker/tosa_result_checker.py
index 8ae3218..b7a76b6 100644
--- a/verif/checker/tosa_result_checker.py
+++ b/verif/checker/tosa_result_checker.py
@@ -9,6 +9,7 @@ from enum import unique
 from pathlib import Path
 
 import numpy as np
+from generator.tosa_utils import float32_is_valid_bfloat16
 
 ##################################
 color_printing = True
@@ -63,7 +64,12 @@ TestResultErrorStr = [
 
 
 def test_check(
-    reference, result, test_name="test", quantize_tolerance=0, float_tolerance=1e-3
+    reference,
+    result,
+    test_name="test",
+    quantize_tolerance=0,
+    float_tolerance=1e-3,
+    misc_checks=[],
 ):
     """Check if the result is the same as the expected reference."""
     if not os.path.isfile(reference):
@@ -111,6 +117,20 @@ def test_check(
         )
         return (TestResult.MISMATCH, 0.0, msg)
 
+    # Perform miscellaneous checks
+    if "bf16" in misc_checks:
+        # Ensure floats are valid bfloat16 values
+        test_res_is_bf16 = all([float32_is_valid_bfloat16(f) for f in test_result.flat])
+        ref_res_is_bf16 = all(
+            [float32_is_valid_bfloat16(f) for f in reference_result.flat]
+        )
+        if not (test_res_is_bf16 and ref_res_is_bf16):
+            msg = (
+                "All output values must be valid bfloat16. "
+                "reference_result: {ref_res_is_bf16}; test_result: {test_res_is_bf16}"
+            )
+            return (TestResult.INCORRECT_FORMAT, 0.0, msg)
+
     # for quantized test, allow +-(quantize_tolerance) error
     if reference_result.dtype == np.int32 or reference_result.dtype == np.int64: