Main Compliance testing support for LOG and ACTIVATIONs

Increase exp2 allowed range to account for denormals.
Minor adjustments to verify to match spec updates for pseudo code.
Set ranges of activation function inputs to match spec.

Signed-off-by: Jeremy Johnson <jeremy.johnson@arm.com>
Change-Id: I6fcf665932ac2c9080e284b865da8f7746801f59

6 files changed, 98 insertions, 119 deletions

diff --git a/reference_model/src/generate/generate_utils.cc b/reference_model/src/generate/generate_utils.cc
index 5546269..d2168c9 100644
--- a/reference_model/src/generate/generate_utils.cc
+++ b/reference_model/src/generate/generate_utils.cc
@@ -43,11 +43,14 @@ NLOHMANN_JSON_SERIALIZE_ENUM(Op,
                                  { Op::Op_ARGMAX, "ARGMAX" },
                                  { Op::Op_AVG_POOL2D, "AVG_POOL2D" },
                                  { Op::Op_CEIL, "CEIL" },
+                                 { Op::Op_CLAMP, "CLAMP" },
                                  { Op::Op_CONV2D, "CONV2D" },
+                                 { Op::Op_ERF, "ERF" },
                                  { Op::Op_EXP, "EXP" },
                                  { Op::Op_FLOOR, "FLOOR" },
                                  { Op::Op_FULLY_CONNECTED, "FULLY_CONNECTED" },
                                  { Op::Op_IDENTITY, "IDENTITY" },
+                                 { Op::Op_LOG, "LOG" },
                                  { Op::Op_MATMUL, "MATMUL" },
                                  { Op::Op_MAXIMUM, "MAXIMUM" },
                                  { Op::Op_MAX_POOL2D, "MAX_POOL2D" },
@@ -61,7 +64,9 @@ NLOHMANN_JSON_SERIALIZE_ENUM(Op,
                                  { Op::Op_REDUCE_MAX, "REDUCE_MAX" },
                                  { Op::Op_REDUCE_MIN, "REDUCE_MIN" },
                                  { Op::Op_REDUCE_SUM, "REDUCE_SUM" },
+                                 { Op::Op_SIGMOID, "SIGMOID" },
                                  { Op::Op_SUB, "SUB" },
+                                 { Op::Op_TANH, "TANH" },
                              })
 
 }    // namespace tosa
diff --git a/reference_model/src/verify/verify_abs_error.cc b/reference_model/src/verify/verify_abs_error.cc
index 1afa7fd..b43da08 100644
--- a/reference_model/src/verify/verify_abs_error.cc
+++ b/reference_model/src/verify/verify_abs_error.cc
@@ -32,7 +32,7 @@ bool validateData(const double* ref, const double* bnd, const float* imp, const
 
     for (size_t i = 0; i < T; ++i)
     {
-        double errBound = ref[i] * exp2(-AccPrecision<float>::normal_frac) * bnd[i];
+        double errBound = std::abs(ref[i]) * exp2(-AccPrecision<float>::normal_frac) * bnd[i];
         bool valid      = tosaCheckFloatBound(imp[i], ref[i], errBound);
         if (!valid)
         {
diff --git a/reference_model/src/verify/verify_ulp.cc b/reference_model/src/verify/verify_ulp.cc
index b333810..6e78b96 100644
--- a/reference_model/src/verify/verify_ulp.cc
+++ b/reference_model/src/verify/verify_ulp.cc
@@ -30,15 +30,8 @@ bool tosaCheckULP(float testValue, double referenceValue, double ulpNum)
     double errorBound = 0.0;
     if (std::isfinite(referenceValue) && std::abs(referenceValue) != 0.0)
     {
-        // Make the sign of the reference value positive
-        // and adjust the test value appropriately.
-        if (referenceValue < 0)
-        {
-            referenceValue = -referenceValue;
-            testValue      = -testValue;
-        }
         // Find the exponent of the reference value.
-        int32_t referenceExponent = ilog2(referenceValue);
+        int32_t referenceExponent = ilog2(std::abs(referenceValue));
 
         // Work out the values magnitude - by raising 2 to the power of the
         // exponent and taking the normalized minimum for denormal values
diff --git a/reference_model/src/verify/verify_utils.cc b/reference_model/src/verify/verify_utils.cc
index 414f7d7..9aa6ba2 100644
--- a/reference_model/src/verify/verify_utils.cc
+++ b/reference_model/src/verify/verify_utils.cc
@@ -170,7 +170,11 @@ DType mapToDType(tosa_datatype_t dataType)
 // Like const_exp2 but for use during runtime
 double exp2(int32_t n)
 {
-    TOSA_REF_REQUIRE(-1022 <= n && n <= 1023, " Invalid exponent value (%d) in exp2", n);
+    if (n < -1075)
+    {
+        return 0.0;    // smaller than smallest denormal
+    }
+    TOSA_REF_REQUIRE(n <= 1023, " Invalid exponent value (%d) in exp2", n);
     return const_exp2(n);
 }
 
@@ -212,6 +216,9 @@ bool tosaCheckFloatBound(float testValue, double referenceValue, double errorBou
         return false;
     }
 
+    // Check the errorBound
+    TOSA_REF_REQUIRE(errorBound >= 0.f, " Invalid error bound (%g)", errorBound);
+
     // Make the sign of the reference value positive
     // and adjust the test value appropriately.
     if (referenceValue < 0)
@@ -219,10 +226,6 @@ bool tosaCheckFloatBound(float testValue, double referenceValue, double errorBou
         referenceValue = -referenceValue;
         testValue      = -testValue;
     }
-    if (errorBound < 0)
-    {
-        errorBound = -errorBound;
-    }
 
     // At this point we are ready to calculate the ULP bounds for the reference value.
     double referenceMin, referenceMax;
diff --git a/verif/conformance/tosa_main_profile_ops_info.json b/verif/conformance/tosa_main_profile_ops_info.json
index 87b14c2..35d72e8 100644
--- a/verif/conformance/tosa_main_profile_ops_info.json
+++ b/verif/conformance/tosa_main_profile_ops_info.json
@@ -403,6 +403,7 @@
         "profile": [
             "tosa-mi"
         ],
+        "support_for": [ "lazy_data_gen" ],
         "generation": {
             "standard": {
                 "generator_args": [
@@ -414,7 +415,7 @@
                         "--target-dtype",
                         "bf16",
                         "--fp-values-range",
-                        "-2.0,2.0",
+                        "-max,max",
                         "--tensor-dim-range",
                         "20,64",
                         "--target-rank",
@@ -432,7 +433,7 @@
                         "--target-dtype",
                         "bf16",
                         "--fp-values-range",
-                        "-2.0,2.0",
+                        "-max,max",
                         "--tensor-dim-range",
                         "1,20",
                         "--target-rank",
@@ -444,7 +445,7 @@
                         "--target-dtype",
                         "fp32",
                         "--fp-values-range",
-                        "-2.0,2.0",
+                        "-max,max",
                         "--target-shape",
                         "1,2,1,65536",
                         "--target-shape",
@@ -1369,6 +1370,7 @@
         "profile": [
             "tosa-mi"
         ],
+        "support_for": [ "lazy_data_gen" ],
         "generation": {
             "standard": {
                 "generator_args": [
@@ -1382,7 +1384,7 @@
                         "--target-dtype",
                         "bf16",
                         "--fp-values-range",
-                        "-2.0,2.0",
+                        "-max,max",
                         "--tensor-dim-range",
                         "15,64",
                         "--target-rank",
@@ -1398,7 +1400,7 @@
                         "--target-dtype",
                         "fp32",
                         "--fp-values-range",
-                        "-2.0,2.0",
+                        "-max,max",
                         "--tensor-dim-range",
                         "1,15",
                         "--target-rank",
@@ -1412,7 +1414,7 @@
                         "--target-dtype",
                         "fp16",
                         "--fp-values-range",
-                        "-2.0,2.0",
+                        "-max,max",
                         "--target-shape",
                         "1,65530,1,2",
                         "--target-shape",
@@ -2748,6 +2750,7 @@
         "profile": [
             "tosa-mi"
         ],
+        "support_for": [ "lazy_data_gen" ],
         "generation": {
             "standard": {
                 "generator_args": [
@@ -2759,7 +2762,7 @@
                         "--target-dtype",
                         "bf16",
                         "--fp-values-range",
-                        "-2.0,2.0",
+                        "-16.0,16.0",
                         "--tensor-dim-range",
                         "16,64",
                         "--target-rank",
@@ -2777,7 +2780,7 @@
                         "--target-dtype",
                         "bf16",
                         "--fp-values-range",
-                        "-2.0,2.0",
+                        "-16.0,16.0",
                         "--tensor-dim-range",
                         "1,19",
                         "--target-rank",
@@ -2789,7 +2792,7 @@
                         "--target-dtype",
                         "fp32",
                         "--fp-values-range",
-                        "-2.0,2.0",
+                        "-16.0,16.0",
                         "--target-shape",
                         "1,2,65538,2,1",
                         "--target-shape",
@@ -2946,6 +2949,7 @@
         "profile": [
             "tosa-mi"
         ],
+        "support_for": [ "lazy_data_gen" ],
         "generation": {
             "standard": {
                 "generator_args": [
@@ -2957,7 +2961,7 @@
                         "--target-dtype",
                         "bf16",
                         "--fp-values-range",
-                        "-2.0,2.0",
+                        "-8.0,8.0",
                         "--tensor-dim-range",
                         "18,60",
                         "--target-rank",
@@ -2975,7 +2979,7 @@
                         "--target-dtype",
                         "bf16",
                         "--fp-values-range",
-                        "-2.0,2.0",
+                        "-8.0,8.0",
                         "--tensor-dim-range",
                         "1,24",
                         "--target-rank",
@@ -2987,7 +2991,7 @@
                         "--target-dtype",
                         "fp32",
                         "--fp-values-range",
-                        "-2.0,2.0",
+                        "-8.0,8.0",
                         "--target-shape",
                         "1,65535,2,1,1",
                         "--target-shape",
@@ -3011,6 +3015,7 @@
         "profile": [
             "tosa-mi"
         ],
+        "support_for": [ "lazy_data_gen" ],
         "generation": {
             "standard": {
                 "generator_args": [
@@ -3022,7 +3027,7 @@
                         "--target-dtype",
                         "bf16",
                         "--fp-values-range",
-                        "-2.0,2.0",
+                        "-4.0,4.0",
                         "--tensor-dim-range",
                         "18,60",
                         "--target-rank",
@@ -3040,7 +3045,7 @@
                         "--target-dtype",
                         "bf16",
                         "--fp-values-range",
-                        "-2.0,2.0",
+                        "-4.0,4.0",
                         "--tensor-dim-range",
                         "1,24",
                         "--target-rank",
@@ -3052,7 +3057,7 @@
                         "--target-dtype",
                         "fp32",
                         "--fp-values-range",
-                        "-2.0,2.0",
+                        "-4.0,4.0",
                         "--target-shape",
                         "1,65535,2,1,1",
                         "--target-shape",
diff --git a/verif/generator/tosa_test_gen.py b/verif/generator/tosa_test_gen.py
index 9f65fd4..04093b8 100644
--- a/verif/generator/tosa_test_gen.py
+++ b/verif/generator/tosa_test_gen.py
@@ -405,13 +405,9 @@ class TosaTestGen:
 
         self.ser.addOperator(op["op"], input_list, output_list, attr)
 
-        if op["op"] in (Op.LOG,):
-            # TODO - add compliance support LOG
-            compliance = None
-        else:
-            compliance = self.tensorComplianceMetaData(
-                op, a.dtype, args_dict, result_tensor, error_name
-            )
+        compliance = self.tensorComplianceMetaData(
+            op, a.dtype, args_dict, result_tensor, error_name
+        )
         return TosaTestGen.BuildInfo(result_tensor, compliance)
 
     def build_binary_broadcast(
@@ -1241,8 +1237,13 @@ class TosaTestGen:
 
         return TosaTestGen.BuildInfo(result_tensor, compliance)
 
-    def build_clamp(self, op, a, validator_fcns=None, error_name=None):
-        result_tens = OutputShaper.unaryOp(self.ser, self.rng, a, error_name)
+    def build_clamp(
+        self, op, inputs, args_dict, validator_fcns=None, error_name=None, qinfo=None
+    ):
+        assert len(inputs) == 1
+        a = inputs[0]
+
+        result_tensor = OutputShaper.unaryOp(self.ser, self.rng, a, error_name)
 
         v = [self.getRandNumberDType(a.dtype), self.getRandNumberDType(a.dtype)]
 
@@ -1258,7 +1259,7 @@ class TosaTestGen:
 
         # Invalidate Input/Output list for error if checks.
         input_list = [a.name]
-        output_list = [result_tens.name]
+        output_list = [result_tensor.name]
         pCount, cCount = op["operands"]
         num_operands = pCount + cCount
         input_list, output_list = TosaErrorIfArgGen.eiInvalidateInputOutputList(
@@ -1273,10 +1274,10 @@ class TosaTestGen:
             max_val=max_val,
             min_val=min_val,
             input_shape=a.shape,
-            output_shape=result_tens.shape,
+            output_shape=result_tensor.shape,
             input_dtype=a.dtype,
-            output_dtype=result_tens.dtype,
-            result_tensors=[result_tens],
+            output_dtype=result_tensor.dtype,
+            result_tensors=[result_tensor],
             input_list=input_list,
             output_list=output_list,
             num_operands=num_operands,
@@ -1295,7 +1296,12 @@ class TosaTestGen:
             attr.ClampAttribute(self.ser.builder, min_val, max_val, 0, 0)
 
         self.ser.addOperator(op["op"], input_list, output_list, attr)
-        return result_tens
+
+        compliance = self.tensorComplianceMetaData(
+            op, a.dtype, args_dict, result_tensor, error_name
+        )
+
+        return TosaTestGen.BuildInfo(result_tensor, compliance)
 
     def build_leaky_relu(self, op, a, validator_fcns=None, error_name=None):
         result_tens = OutputShaper.unaryOp(self.ser, self.rng, a, error_name)
@@ -1313,43 +1319,17 @@ class TosaTestGen:
         self.ser.addOperator(op["op"], [a.name], [result_tens.name])
         return result_tens
 
-    def build_sigmoid(self, op, a, validator_fcns=None, error_name=None):
-        result_tens = OutputShaper.unaryOp(self.ser, self.rng, a, 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
-        )
-
-        if not TosaErrorValidator.evValidateErrorIfs(
-            self.ser,
-            validator_fcns,
-            error_name,
-            op=op,
-            input_shape=a.shape,
-            output_shape=result_tens.shape,
-            input_dtype=a.dtype,
-            output_dtype=result_tens.dtype,
-            result_tensors=[result_tens],
-            input_list=input_list,
-            output_list=output_list,
-            num_operands=num_operands,
-        ):
-            return None
-
-        self.ser.addOperator(op["op"], input_list, output_list)
-        return result_tens
+    def build_activation(
+        self, op, inputs, args_dict, validator_fcns=None, error_name=None, qinfo=None
+    ):
+        assert len(inputs) == 1
+        a = inputs[0]
 
-    def build_tanh(self, op, a, validator_fcns=None, error_name=None):
-        result_tens = OutputShaper.unaryOp(self.ser, self.rng, a, error_name)
+        result_tensor = OutputShaper.unaryOp(self.ser, self.rng, a, error_name)
 
         # Invalidate Input/Output list for error if checks.
         input_list = [a.name]
-        output_list = [result_tens.name]
+        output_list = [result_tensor.name]
         pCount, cCount = op["operands"]
         num_operands = pCount + cCount
         input_list, output_list = TosaErrorIfArgGen.eiInvalidateInputOutputList(
@@ -1362,10 +1342,10 @@ class TosaTestGen:
             error_name,
             op=op,
             input_shape=a.shape,
-            output_shape=result_tens.shape,
+            output_shape=result_tensor.shape,
             input_dtype=a.dtype,
-            output_dtype=result_tens.dtype,
-            result_tensors=[result_tens],
+            output_dtype=result_tensor.dtype,
+            result_tensors=[result_tensor],
             input_list=input_list,
             output_list=output_list,
             num_operands=num_operands,
@@ -1373,38 +1353,12 @@ class TosaTestGen:
             return None
 
         self.ser.addOperator(op["op"], input_list, output_list)
-        return result_tens
-
-    def build_erf(self, op, a, validator_fcns=None, error_name=None):
-        result_tens = OutputShaper.unaryOp(self.ser, self.rng, a, 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
+        compliance = self.tensorComplianceMetaData(
+            op, a.dtype, args_dict, result_tensor, error_name
         )
 
-        if not TosaErrorValidator.evValidateErrorIfs(
-            self.ser,
-            validator_fcns,
-            error_name,
-            op=op,
-            input_shape=a.shape,
-            output_shape=result_tens.shape,
-            input_dtype=a.dtype,
-            output_dtype=result_tens.dtype,
-            result_tensors=[result_tens],
-            input_list=input_list,
-            output_list=output_list,
-            num_operands=num_operands,
-        ):
-            return None
-
-        self.ser.addOperator(op["op"], input_list, output_list)
-        return result_tens
+        return TosaTestGen.BuildInfo(result_tensor, compliance)
 
     def build_concat(
         self, op, inputs, args_dict, validator_fcns=None, error_name=None, qinfo=None
@@ -3220,8 +3174,8 @@ class TosaTestGen:
             "build_fcn": (
                 build_clamp,
                 TosaTensorGen.tgBasic,
-                TosaTensorValuesGen.tvgDefault,
-                None,
+                TosaTensorValuesGen.tvgLazyGenDefault,
+                TosaArgGen.agNone,
             ),
             "types": TYPE_NARROW_INT_FP,
             "error_if_validators": (
@@ -3231,15 +3185,18 @@ class TosaTestGen:
                 TosaErrorValidator.evWrongInputList,
                 TosaErrorValidator.evWrongOutputList,
             ),
+            "data_gen": {
+                "fp": (gtu.DataGenType.PSEUDO_RANDOM,),
+            },
         },
         "sigmoid": {
             "op": Op.SIGMOID,
             "operands": (1, 0),
             "build_fcn": (
-                build_sigmoid,
+                build_activation,
                 TosaTensorGen.tgBasic,
-                TosaTensorValuesGen.tvgDefault,
-                None,
+                TosaTensorValuesGen.tvgLazyGenDefault,
+                TosaArgGen.agNone,
             ),
             "types": TYPE_FP,
             "error_if_validators": (
@@ -3248,15 +3205,19 @@ class TosaTestGen:
                 TosaErrorValidator.evWrongInputList,
                 TosaErrorValidator.evWrongOutputList,
             ),
+            "data_gen": {
+                "fp": (gtu.DataGenType.PSEUDO_RANDOM,),
+            },
+            "compliance": {"ulp": 5},
         },
         "tanh": {
             "op": Op.TANH,
             "operands": (1, 0),
             "build_fcn": (
-                build_tanh,
+                build_activation,
                 TosaTensorGen.tgBasic,
-                TosaTensorValuesGen.tvgDefault,
-                None,
+                TosaTensorValuesGen.tvgLazyGenDefault,
+                TosaArgGen.agNone,
             ),
             "types": TYPE_FP,
             "error_if_validators": (
@@ -3265,15 +3226,19 @@ class TosaTestGen:
                 TosaErrorValidator.evWrongInputList,
                 TosaErrorValidator.evWrongOutputList,
             ),
+            "data_gen": {
+                "fp": (gtu.DataGenType.PSEUDO_RANDOM,),
+            },
+            "compliance": {"ulp": 5},
         },
         "erf": {
             "op": Op.ERF,
             "operands": (1, 0),
             "build_fcn": (
-                build_erf,
+                build_activation,
                 TosaTensorGen.tgBasic,
-                TosaTensorValuesGen.tvgDefault,
-                None,
+                TosaTensorValuesGen.tvgLazyGenDefault,
+                TosaArgGen.agNone,
             ),
             "types": TYPE_FP,
             "error_if_validators": (
@@ -3282,6 +3247,10 @@ class TosaTestGen:
                 TosaErrorValidator.evWrongInputList,
                 TosaErrorValidator.evWrongOutputList,
             ),
+            "data_gen": {
+                "fp": (gtu.DataGenType.PSEUDO_RANDOM,),
+            },
+            "compliance": {"ulp": 5},
         },
         # Elementwise Binary Operators
         "add": {
@@ -3778,6 +3747,10 @@ class TosaTestGen:
                 TosaErrorValidator.evWrongInputList,
                 TosaErrorValidator.evWrongOutputList,
             ),
+            "data_gen": {
+                "fp": (gtu.DataGenType.PSEUDO_RANDOM,),
+            },
+            "compliance": {"ulp": 5},
         },
         "logical_not": {
             "op": Op.LOGICAL_NOT,