Merge branch 'develop' into wavelet_model

profiler/src/profile_batchnorm_fwd.cpp

@@ -48,7 +48,7 @@ class BatchnormFwdArgParser
         std::cout << "--inOutLengths or -D, comma separated list of input tensor dimension lengths, must have 4 integers for nhwc" << std::endl;
         std::cout << "--reduceDims or -R, comma separated list of dimensions to reduce on" << std::endl;  
         std::cout << "--verify or -v, 1/0 to indicate whether to verify the result by comparing with the host-based batch-normalization" << std::endl;
-        std::cout << "Arg1: data type (0: fp16, 1: fp32, 3: int8, 5: bp16, 6: fp64)" << std::endl;
+        std::cout << "Arg1: data type (0: fp16, 1: fp32, 5: bp16, 6: fp64)" << std::endl;
         std::cout << "Arg2: 1/0 to indicate whether to update the moving average and variance (0=no, 1=yes)" << std::endl;
         std::cout << "Arg3: 1/0 to indicate whether to save the calculated mean and invVariance (0=no, 1=yes)" << std::endl;
         std::cout << "Arg4: init method used for bnScale and bnBias (0=no init, 1=single integer value, 2=scope integer value, 3=decimal value)" << std::endl;
@@ -141,7 +141,6 @@ int profile_batchnorm_forward(int argc, char* argv[])
     using F16  = ck::half_t;
     using F32  = float;
     using BF16 = ck::bhalf_t;
-    using I8   = int8_t;
     using F64  = double;
 
     if(arg_parser.data_type == 0)
@@ -178,23 +177,6 @@ int profile_batchnorm_forward(int argc, char* argv[])
                 averageFactor);
         };
     }
-    else if(arg_parser.data_type == 3)
-    {
-        if(arg_parser.inLengths.size() == 4 && arg_parser.reduceDims.size() == 3)
-        {
-            profile_batchnorm_forward_impl<I8, I8, F32, I8, I8, F32, 4, 3>(
-                arg_parser.do_verification,
-                arg_parser.init_method,
-                arg_parser.do_dumpout,
-                arg_parser.time_kernel,
-                arg_parser.inLengths,
-                arg_parser.reduceDims,
-                arg_parser.updateMovingAverage,
-                arg_parser.saveMeanAndInvVariance,
-                epsilon,
-                averageFactor);
-        };
-    }
     else if(arg_parser.data_type == 5)
     {
         if(arg_parser.inLengths.size() == 4 && arg_parser.reduceDims.size() == 3)

test/batchnorm_fwd/batchnorm_fwd_rank_4.cpp

@@ -90,7 +90,6 @@ class TestBatchNormFwdRank4 : public ::testing::Test
 using KernelTypes = ::testing::Types<std::tuple<F16, F16, F32, F16, F16, F32>,
                                      std::tuple<F32, F32, F32, F32, F32, F32>,
                                      std::tuple<BF16, BF16, F32, BF16, BF16, F32>,
-                                     std::tuple<I8, I8, F32, I8, I8, F32>,
                                      std::tuple<F64, F64, F64, F64, F64, F64>>;
 
 TYPED_TEST_SUITE(TestBatchNormFwdRank4, KernelTypes);