Add negative testing support for reduce operators
* Negative testing support added for the following operators:
reduce_all, reduce_any, reduce_max, reduce_min, reduce_product, reduce_sum
Change-Id: Ife4f0307b681510e8910a23a39efc127c82ae120
Signed-off-by: Matthew Haddon <matthew.haddon@arm.com>
diff --git a/verif/tosa_test_gen.py b/verif/tosa_test_gen.py
index 8d69831..43b188d 100644
--- a/verif/tosa_test_gen.py
+++ b/verif/tosa_test_gen.py
@@ -475,11 +475,18 @@
def agAxis(testGen, opName, shapeList, dtype, error_name=None):
"""Build the axis argument for operators that take a single axis"""
axes = []
-
shape = shapeList[0]
- for a in range(0, len(shape)):
- axes.append(("axis{}".format(a), [a]))
+ if error_name == ErrorIf.AxisSmallerZero:
+ small_axis = testGen.rng.integers(-5, 0)
+ axes.append(("axis{}".format(small_axis), [small_axis]))
+ elif error_name == ErrorIf.AxisLargerRank:
+ large_axis = testGen.rng.integers(len(shape) + 1, len(shape) + 10)
+ axes.append(("axis{}".format(large_axis), [large_axis]))
+ else:
+ for a in range(0, len(shape)):
+ axes.append(("axis{}".format(a), [a]))
+
return axes
@staticmethod
@@ -1715,6 +1722,70 @@
}
return info_dict
+ @staticmethod
+ def evAxisSmallerZero(check=False, **kwargs):
+ error_name = ErrorIf.AxisSmallerZero
+ param_reqs = {"rank": None, "dtype": None, "shape": None}
+ error_result = False
+ error_reason = "Axis smaller than zero"
+
+ if check:
+ axis = kwargs['axis']
+ if axis < 0:
+ error_result = True
+
+ info_dict = {
+ "error_name": error_name,
+ "error_result": error_result,
+ "error_reason": error_reason,
+ "param_reqs": param_reqs
+ }
+ return info_dict
+
+
+ @staticmethod
+ def evAxisLargerRank(check=False, **kwargs):
+ error_name = ErrorIf.AxisLargerRank
+ param_reqs = {"rank": None, "dtype": None, "shape": None}
+ error_result = False
+ error_reason = "Axis larger than rank"
+
+ if check:
+ axis = kwargs['axis']
+ shape = kwargs['input_shape']
+ if axis > len(shape):
+ error_result = True
+
+ info_dict = {
+ "error_name": error_name,
+ "error_result": error_result,
+ "error_reason": error_reason,
+ "param_reqs": param_reqs
+ }
+ return info_dict
+
+
+ @staticmethod
+ def evShapeOfAxisNotOne(check=False, **kwargs):
+ error_name = ErrorIf.ShapeOfAxisNotOne
+ param_reqs = {"rank": None, "dtype": None, "shape": None}
+ error_result = False
+ error_reason = "shape[axis] is not equal to 1"
+
+ if check:
+ axis = kwargs['axis']
+ shape = kwargs['output_shape']
+ if (0 <= axis < len(shape)) and shape[axis] != 1:
+ error_result = True
+
+ info_dict = {
+ "error_name": error_name,
+ "error_result": error_result,
+ "error_reason": error_reason,
+ "param_reqs": param_reqs
+ }
+ return info_dict
+
class TosaInvalidValidator:
@@ -2233,13 +2304,36 @@
self.ser.addOperator(op['op'], [a.name, b.name], [result_tens.name], None, qinfo)
return result_tens
- def build_reduce(self, op, a, axis):
- result_tens = OutputShaper.reduceOp(self.ser, a, axis)
+ def build_reduce(self, op, a, axis, validator_fcns, error_name=None):
+ result_tens = OutputShaper.reduceOp(self.ser, self.rng, a, axis, error_name)
+
+ # Invalidate Input/Output list for error if checks.
+ input_list = [a.name]
+ output_list = [result_tens.name]
+ pCount, cCount = op["operands"]
+ num_operands = pCount + cCount
+ input_list, output_list = TosaErrorIfArgGen.eiInvalidateInputOutputList(self, error_name, input_list, output_list)
+
+ TosaErrorValidator.evValidateErrorIfs(
+ self.ser,
+ validator_fcns,
+ error_name,
+ op=op,
+ axis = axis,
+ input_shape = a.shape,
+ output_shape = result_tens.shape,
+ input_dtype = a.dtype,
+ output_dtype = result_tens.dtype,
+ result_tensor = result_tens,
+ input_list=input_list,
+ output_list=output_list,
+ num_operands=num_operands,
+ )
attr = ts.TosaSerializerAttribute()
attr.AxisAttribute(axis)
- self.ser.addOperator(op['op'], [a.name], result_tens.name, attr)
+ self.ser.addOperator(op['op'], input_list, output_list, attr)
return result_tens
def build_clamp(self, op, a):
@@ -3606,36 +3700,54 @@
"operands": (1, 0),
"build_fcn": (build_reduce, TosaTensorGen.tgBasic, TosaArgGen.agAxis),
"types": TYPE_BOOL,
+ "error_if_validators": (TosaErrorValidator.evAxisLargerRank, TosaErrorValidator.evAxisSmallerZero, TosaErrorValidator.evShapeOfAxisNotOne,
+ TosaErrorValidator.evWrongInputType, TosaErrorValidator.evWrongOutputType, TosaErrorValidator.evWrongRank,
+ TosaErrorValidator.evWrongInputList, TosaErrorValidator.evWrongOutputList)
},
"reduce_any": {
"op": Op.REDUCE_ANY,
"operands": (1, 0),
"build_fcn": (build_reduce, TosaTensorGen.tgBasic, TosaArgGen.agAxis),
"types": TYPE_BOOL,
+ "error_if_validators": (TosaErrorValidator.evAxisLargerRank, TosaErrorValidator.evAxisSmallerZero, TosaErrorValidator.evShapeOfAxisNotOne,
+ TosaErrorValidator.evWrongInputType, TosaErrorValidator.evWrongOutputType, TosaErrorValidator.evWrongRank,
+ TosaErrorValidator.evWrongInputList, TosaErrorValidator.evWrongOutputList)
},
"reduce_max": {
"op": Op.REDUCE_MAX,
"operands": (1, 0),
"build_fcn": (build_reduce, TosaTensorGen.tgBasic, TosaArgGen.agAxis),
"types": TYPE_INT_FP,
+ "error_if_validators": (TosaErrorValidator.evAxisLargerRank, TosaErrorValidator.evAxisSmallerZero, TosaErrorValidator.evShapeOfAxisNotOne,
+ TosaErrorValidator.evWrongInputType, TosaErrorValidator.evWrongOutputType, TosaErrorValidator.evWrongRank,
+ TosaErrorValidator.evWrongInputList, TosaErrorValidator.evWrongOutputList)
},
"reduce_min": {
"op": Op.REDUCE_MAX,
"operands": (1, 0),
"build_fcn": (build_reduce, TosaTensorGen.tgBasic, TosaArgGen.agAxis),
"types": TYPE_INT_FP,
+ "error_if_validators": (TosaErrorValidator.evAxisLargerRank, TosaErrorValidator.evAxisSmallerZero, TosaErrorValidator.evShapeOfAxisNotOne,
+ TosaErrorValidator.evWrongInputType, TosaErrorValidator.evWrongOutputType, TosaErrorValidator.evWrongRank,
+ TosaErrorValidator.evWrongInputList, TosaErrorValidator.evWrongOutputList)
},
"reduce_product": {
"op": Op.REDUCE_PRODUCT,
"operands": (1, 0),
"build_fcn": (build_reduce, TosaTensorGen.tgBasic, TosaArgGen.agAxis),
"types": TYPE_FP,
+ "error_if_validators": (TosaErrorValidator.evAxisLargerRank, TosaErrorValidator.evAxisSmallerZero, TosaErrorValidator.evShapeOfAxisNotOne,
+ TosaErrorValidator.evWrongInputType, TosaErrorValidator.evWrongOutputType, TosaErrorValidator.evWrongRank,
+ TosaErrorValidator.evWrongInputList, TosaErrorValidator.evWrongOutputList)
},
"reduce_sum": {
"op": Op.REDUCE_SUM,
"operands": (1, 0),
"build_fcn": (build_reduce, TosaTensorGen.tgBasic, TosaArgGen.agAxis),
"types": TYPE_FI32,
+ "error_if_validators": (TosaErrorValidator.evAxisLargerRank, TosaErrorValidator.evAxisSmallerZero, TosaErrorValidator.evShapeOfAxisNotOne,
+ TosaErrorValidator.evWrongInputType, TosaErrorValidator.evWrongOutputType, TosaErrorValidator.evWrongRank,
+ TosaErrorValidator.evWrongInputList, TosaErrorValidator.evWrongOutputList)
},
# Data layout operators
"concat": {
@@ -3865,13 +3977,21 @@
return ser.addOutput(shape, DType.BOOL)
@staticmethod
- def reduceOp(ser, a, axis):
-
+ def reduceOp(ser, rng, a, axis, error_name=None):
shape = a.shape.copy()
+ if error_name not in [ErrorIf.AxisSmallerZero, ErrorIf.AxisLargerRank, ErrorIf.ShapeOfAxisNotOne]:
+ shape[axis] = 1
+ if error_name == ErrorIf.ShapeOfAxisNotOne and shape[axis] == 1:
+ shape[axis] = rng.integers(2, 10)
- shape[axis] = 1
+ if error_name == ErrorIf.WrongOutputType:
+ all_dtypes = [DType.INT8, DType.INT16, DType.INT32, DType.INT48, DType.FLOAT]
+ wrong_dtypes = list(set(all_dtypes) - set([a.dtype]))
+ outputDType = rng.choice(wrong_dtypes)
+ else:
+ outputDType = a.dtype
- return ser.addOutput(shape, a.dtype)
+ return ser.addOutput(shape, outputDType)
@staticmethod
def argmaxOp(ser, a, axis):