ERRORIF test generation fixes
TRANSPOSE - remove WrongRank testing as no limit in spec
RESIZE - make floating point test naming same format as int
- fix MaxDimExceeeded by not restricting dims and
fix max dim check to match spec
- catch stride less than/equal zero and regen
PAD - remove zero point testing as not in spec
Change-Id: I4eb0b78d7f577469d202866d95833e7d5fd2f2a8
Signed-off-by: Jeremy Johnson <jeremy.johnson@arm.com>
diff --git a/verif/tosa_test_gen.py b/verif/tosa_test_gen.py
index 1bd1b5a..9eef7fa 100644
--- a/verif/tosa_test_gen.py
+++ b/verif/tosa_test_gen.py
@@ -288,7 +288,7 @@
shape[0] = (shape[0] % testGen.args.max_batch_size) + 1
# Constrict the overall size of the shape when creating ERROR_IF tests
- if error_name:
+ if error_name and error_name != ErrorIf.MaxDimExceeded:
shape = TosaErrorIfArgGen.eiRestrictDimensions(shape)
shape_list = []
@@ -1233,55 +1233,17 @@
fp_offset_x = in_center_w - fp_stride_x * out_center_w
if outputDType == DType.FLOAT:
+ float_op = True
+ arg_str = "mode{}_shift{}_odim{}x{}_out{}_st{:.2f}x{:.2f}_off{:.2f}x{:.2f}"
shift = 0
stride = [0, 0]
offset = [0, 0]
stride_fp = [fp_stride_y, fp_stride_x]
offset_fp = [fp_offset_y, fp_offset_x]
- if error_name is not None:
- shift, stride, stride_fp, offset, offset_fp, outputDTypeNew = TosaErrorIfArgGen.eiResizeErrorIf(
- testGen,
- error_name,
- mode,
- dtype,
- shapeList,
- outputDType,
- shift,
- stride,
- stride_fp,
- offset,
- offset_fp
- )
- else:
- outputDTypeNew = outputDType
-
- arg_list.append(
- (
- "mode{}_odim{}x{}_out{}_st{:.2f}x{:.2f}_off{:.2f}x{:.2f}".format(
- "N" if mode == ResizeMode.NEAREST else "B",
- output_dims[0],
- output_dims[1],
- testGen.typeStr(outputDTypeNew),
- stride_fp[0],
- stride_fp[1],
- offset_fp[0],
- offset_fp[1],
- ),
- [
- mode,
- stride,
- offset,
- shift,
- stride_fp,
- offset_fp,
- output_dims,
- dtype,
- outputDTypeNew,
- ],
- )
- )
else:
+ float_op = False
+ arg_str = "mode{}_shift{}_odim{}x{}_out{}_st{}x{}_off{}x{}"
shift = testGen.randInt(1,12)
# Now search for a shift value (1 to 11) that will produce
# a valid and predictable resize operation
@@ -1294,7 +1256,9 @@
offset_x = int(round(fp_offset_x * unit))
if (
- stride_y >= (16 << shift)
+ stride_y <= 0
+ or stride_x <= 0
+ or stride_y >= (16 << shift)
or stride_x >= (16 << shift)
or offset_y >= (16 << shift)
or offset_x >= (16 << shift)
@@ -1337,49 +1301,50 @@
stride_fp = [0.0, 0.0]
offset_fp = [0.0, 0.0]
- if error_name is not None:
- shift, stride, stride_fp, offset, offset_fp, outputDTypeNew = TosaErrorIfArgGen.eiResizeErrorIf(
- testGen,
- error_name,
- mode,
- dtype,
- shapeList,
- outputDType,
- shift,
- stride,
- stride_fp,
- offset,
- offset_fp
- )
- else:
- outputDTypeNew = outputDType
-
- arg_list.append(
- (
- "mode{}_shift{}_odim{}x{}_out{}_st{}x{}_off{}x{}".format(
- "N" if mode == ResizeMode.NEAREST else "B",
- shift,
- output_dims[0],
- output_dims[1],
- testGen.typeStr(outputDTypeNew),
- stride[0],
- stride[1],
- offset[0],
- offset[1],
- ),
- [
- mode,
- stride,
- offset,
- shift,
- stride_fp,
- offset_fp,
- output_dims,
- dtype,
- outputDTypeNew,
- ],
- )
+ # Common for all data types
+ if error_name is not None:
+ shift, stride, stride_fp, offset, offset_fp, outputDTypeNew = TosaErrorIfArgGen.eiResizeErrorIf(
+ testGen,
+ error_name,
+ mode,
+ dtype,
+ shapeList,
+ outputDType,
+ shift,
+ stride,
+ stride_fp,
+ offset,
+ offset_fp
)
+ else:
+ outputDTypeNew = outputDType
+
+ arg_list.append(
+ (
+ arg_str.format(
+ "N" if mode == ResizeMode.NEAREST else "B",
+ shift,
+ output_dims[0],
+ output_dims[1],
+ testGen.typeStr(outputDTypeNew),
+ stride_fp[0] if float_op else stride[0],
+ stride_fp[1] if float_op else stride[1],
+ offset_fp[0] if float_op else offset[0],
+ offset_fp[1] if float_op else offset[1]
+ ),
+ [
+ mode,
+ stride,
+ offset,
+ shift,
+ stride_fp,
+ offset_fp,
+ output_dims,
+ dtype,
+ outputDTypeNew,
+ ],
+ )
+ )
return arg_list
@@ -1845,15 +1810,15 @@
"shape": [[1, 16584, 5, 1], [1, 2, 16499, 4]]
}
error_result = False
- error_reason = "At least one maximum dimension is larger than 16384"
+ error_reason = "At least one maximum dimension is greater than or equal to 16384"
if check:
input_shape = kwargs['input_shape']
output_shape = kwargs['output_shape'] # Note this is just (OH, OW)
- if ((input_shape[1] > 16384) or
- (input_shape[2] > 16384) or
- (output_shape[0] > 16384) or
- (output_shape[1] > 16384)):
+ if ((input_shape[1] >= 16384) or
+ (input_shape[2] >= 16384) or
+ (output_shape[0] >= 16384) or
+ (output_shape[1] >= 16384)):
error_result = True
info_dict = {
@@ -5067,7 +5032,7 @@
cleanRankFilter = filterDict['rankFilter']
cleanDtypeFilter = filterDict['dtypeFilter']
cleanShapeFilter = filterDict['shapeFilter']
- #print(f"Filters: S {shapeFilter}, R {cleanRankFilter}, T {cleanDtypeFilter}")
+ #print(f"Filters: S {cleanShapeFilter}, R {cleanRankFilter}, T {cleanDtypeFilter}")
for r in cleanRankFilter:
for t in cleanDtypeFilter:
@@ -6063,7 +6028,7 @@
"build_fcn": (build_pad, TosaTensorGen.tgBasic, TosaArgGen.agPad),
"qgen": TosaQuantGen.qgPad,
"types": TYPE_FIB,
- "error_if_validators": (TosaErrorValidator.evInputZeroPointNotZero, TosaErrorValidator.evWrongInputType, TosaErrorValidator.evPadSmallerZero,
+ "error_if_validators": (TosaErrorValidator.evWrongInputType, TosaErrorValidator.evPadSmallerZero,
TosaErrorValidator.evWrongOutputType, TosaErrorValidator.evWrongInputList, TosaErrorValidator.evWrongOutputList)
},
"reshape": {
@@ -6110,7 +6075,7 @@
TosaArgGen.agTranspose,
),
"types": TYPE_FIB,
- "error_if_validators": (TosaErrorValidator.evIndexOutsideBounds, TosaErrorValidator.evIndexUsedTwice, TosaErrorValidator.evWrongRank,
+ "error_if_validators": (TosaErrorValidator.evIndexOutsideBounds, TosaErrorValidator.evIndexUsedTwice,
TosaErrorValidator.evWrongInputType, TosaErrorValidator.evWrongOutputType, TosaErrorValidator.evWrongInputList, TosaErrorValidator.evWrongOutputList)
},
# Data nodes