Main Compliance FP16 support - generate and verify.
FP16 support for all existing operators for compliance:
* DOT_PRODUCT
* ULP
* EXACT
* ABS_ERROR
Signed-off-by: Jeremy Johnson <jeremy.johnson@arm.com>
Change-Id: I8d25448a793375b53880da3787d8f839767f02cf
diff --git a/verif/generator/datagenerator.py b/verif/generator/datagenerator.py
index 0d59084..9de421b 100644
--- a/verif/generator/datagenerator.py
+++ b/verif/generator/datagenerator.py
@@ -68,19 +68,33 @@
def _create_buffer(self, dtype: str, shape: tuple):
"""Helper to create a buffer of the required type."""
- size = 1
- for dim in shape:
- size *= dim
+ size = np.prod(shape)
if dtype == "FP32":
# Create buffer and initialize to zero
buffer = (ct.c_float * size)(0)
size_bytes = size * 4
+ elif dtype == "FP16":
+ size_bytes = size * 2
+ # Create buffer of bytes and initialize to zero
+ buffer = (ct.c_ubyte * size_bytes)(0)
else:
raise GenerateError(f"Unsupported data type {dtype}")
return buffer, size_bytes
+ def _convert_buffer(self, buffer, dtype: str, shape: tuple):
+ """Helper to convert a buffer to a numpy array."""
+ arr = np.ctypeslib.as_array(buffer)
+
+ if dtype == "FP16":
+ # Convert from bytes back to FP16
+ arr = np.frombuffer(arr, np.float16)
+
+ arr = np.reshape(arr, shape)
+
+ return arr
+
def _data_gen_array(self, json_config: str, tensor_name: str):
"""Generate the named tensor data and return a numpy array."""
try:
@@ -106,9 +120,7 @@
if not result:
raise GenerateError("Data generate failed")
- arr = np.ctypeslib.as_array(buffer)
- arr = np.reshape(arr, shape)
-
+ arr = self._convert_buffer(buffer, dtype, shape)
return arr
def _data_gen_write(