Save Int8/UInt8 reference outputs to native dtypes
* Int8/UInt8 reference outputs were previously saved to INT32
* Save those in their native dtypes and updated other affected code
Signed-off-by: Jerry Ge <jerry.ge@arm.com>
Georgios Pinitas <georgios.pinitas@arm.com>
Change-Id: Id65fc8773150d3c56bc2c72789a6a0d3c78cd363
diff --git a/verif/generator/tosa_test_gen.py b/verif/generator/tosa_test_gen.py
index b9352ac..28cf392 100644
--- a/verif/generator/tosa_test_gen.py
+++ b/verif/generator/tosa_test_gen.py
@@ -191,6 +191,10 @@
if dtype == DType.BOOL:
return np.bool_(self.rng.choice(a=[False, True], size=shape))
+ elif dtype == DType.INT8:
+ return np.int8(self.rng.integers(low=low, high=high, size=shape))
+ elif dtype == DType.UINT8:
+ return np.uint8(self.rng.integers(low=low, high=high, size=shape))
elif dtype in (DType.INT48, DType.SHAPE):
return np.int64(self.rng.integers(low=low, high=high, size=shape))
elif dtype in (DType.FP16, DType.BF16, DType.FP32):
@@ -2079,7 +2083,16 @@
val_adj = np.subtract(values, input_zp, dtype=np.int64)
val_adj = np.maximum(val_adj, min_shift_value_arr, dtype=np.int64)
val_adj = np.minimum(val_adj, max_shift_value_arr, dtype=np.int64)
- val_adj = np.add(val_adj, input_zp, dtype=values.dtype)
+ val_adj = np.add(val_adj, input_zp, dtype=np.int64)
+ # Check we can safely convert to the expected dtype
+ assert (
+ val_adj.all() >= np.iinfo(values.dtype).min
+ and val_adj.all() <= np.iinfo(values.dtype).max
+ )
+
+ # Force casting to output datatype
+ val_adj = val_adj.astype(values.dtype, casting="unsafe")
+
if not np.all(np.array_equal(values, val_adj)):
# Values changed so overwrite file with new values
np.save(