Move using statements from instances to a common file

library/src/tensor_operation_instance/gpu/contraction_bilinear/device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_f32_mnnn_instance.cpp

@@ -19,12 +19,6 @@ namespace tensor_operation {
 namespace device {
 namespace instance {
 
-using F32       = float;
-using F32_Tuple = ck::Tuple<F32>;
-
-using PassThrough = ck::tensor_operation::element_wise::PassThrough;
-using Bilinear    = ck::tensor_operation::element_wise::Bilinear;
-
 // A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
 // m/n/n/n are the fast changing dimension for A/B/D/E
 using device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_f32_mnnn_instance =

library/src/tensor_operation_instance/gpu/contraction_bilinear/device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_compute_f32_kknn_instance.cpp

@@ -19,13 +19,6 @@ namespace tensor_operation {
 namespace device {
 namespace instance {
 
-using F32       = float;
-using F64       = double;
-using F64_Tuple = ck::Tuple<F64>;
-
-using PassThrough = ck::tensor_operation::element_wise::PassThrough;
-using Bilinear    = ck::tensor_operation::element_wise::Bilinear;
-
 // A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
 // k/k/n/n are the fast changing dimension for A/B/D/E
 using device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_compute_f32_kknn_instance =

library/src/tensor_operation_instance/gpu/contraction_bilinear/device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_compute_f32_knnn_instance.cpp

@@ -19,13 +19,6 @@ namespace tensor_operation {
 namespace device {
 namespace instance {
 
-using F32       = float;
-using F64       = double;
-using F64_Tuple = ck::Tuple<F64>;
-
-using PassThrough = ck::tensor_operation::element_wise::PassThrough;
-using Bilinear    = ck::tensor_operation::element_wise::Bilinear;
-
 // A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
 // k/n/n/n are the fast changing dimension for A/B/D/E
 using device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_compute_f32_knnn_instance =

library/src/tensor_operation_instance/gpu/contraction_bilinear/device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_compute_f32_mknn_instance.cpp

@@ -19,13 +19,6 @@ namespace tensor_operation {
 namespace device {
 namespace instance {
 
-using F32       = float;
-using F64       = double;
-using F64_Tuple = ck::Tuple<F64>;
-
-using PassThrough = ck::tensor_operation::element_wise::PassThrough;
-using Bilinear    = ck::tensor_operation::element_wise::Bilinear;
-
 // A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
 // m/k/n/n are the fast changing dimension for A/B/D/E
 using device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_compute_f32_mknn_instance =

library/src/tensor_operation_instance/gpu/contraction_bilinear/device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_compute_f32_mnnn_instance.cpp

@@ -19,13 +19,6 @@ namespace tensor_operation {
 namespace device {
 namespace instance {
 
-using F32       = float;
-using F64       = double;
-using F64_Tuple = ck::Tuple<F64>;
-
-using PassThrough = ck::tensor_operation::element_wise::PassThrough;
-using Bilinear    = ck::tensor_operation::element_wise::Bilinear;
-
 // A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
 // m/n/n/n are the fast changing dimension for A/B/D/E
 using device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_compute_f32_mnnn_instance =

library/src/tensor_operation_instance/gpu/contraction_bilinear/device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_kknn_instance.cpp

@@ -19,12 +19,6 @@ namespace tensor_operation {
 namespace device {
 namespace instance {
 
-using F64       = double;
-using F64_Tuple = ck::Tuple<F64>;
-
-using PassThrough = ck::tensor_operation::element_wise::PassThrough;
-using Bilinear    = ck::tensor_operation::element_wise::Bilinear;
-
 // A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
 // k/k/n/n are the fast changing dimension for A/B/D/E
 using device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_kknn_instance =

library/src/tensor_operation_instance/gpu/contraction_bilinear/device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_knnn_instance.cpp

@@ -19,12 +19,6 @@ namespace tensor_operation {
 namespace device {
 namespace instance {
 
-using F64       = double;
-using F64_Tuple = ck::Tuple<F64>;
-
-using PassThrough = ck::tensor_operation::element_wise::PassThrough;
-using Bilinear    = ck::tensor_operation::element_wise::Bilinear;
-
 // A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
 // k/n/n/n are the fast changing dimension for A/B/D/E
 using device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_knnn_instance =

library/src/tensor_operation_instance/gpu/contraction_bilinear/device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_mknn_instance.cpp

@@ -19,12 +19,6 @@ namespace tensor_operation {
 namespace device {
 namespace instance {
 
-using F64       = double;
-using F64_Tuple = ck::Tuple<F64>;
-
-using PassThrough = ck::tensor_operation::element_wise::PassThrough;
-using Bilinear    = ck::tensor_operation::element_wise::Bilinear;
-
 // A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
 // m/k/n/n are the fast changing dimension for A/B/D/E
 using device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_mknn_instance =

library/src/tensor_operation_instance/gpu/contraction_bilinear/device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_mnnn_instance.cpp

@@ -19,12 +19,6 @@ namespace tensor_operation {
 namespace device {
 namespace instance {
 
-using F64       = double;
-using F64_Tuple = ck::Tuple<F64>;
-
-using PassThrough = ck::tensor_operation::element_wise::PassThrough;
-using Bilinear    = ck::tensor_operation::element_wise::Bilinear;
-
 // A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
 // m/n/n/n are the fast changing dimension for A/B/D/E
 using device_contraction_bilinear_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_f64_mnnn_instance =

library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_kkn_instance.cpp

@@ -19,13 +19,6 @@ namespace tensor_operation {
 namespace device {
 namespace instance {
 
-using BF16        = ck::bhalf_t;
-using F32         = float;
-using Empty_Tuple = ck::Tuple<>;
-
-using PassThrough = ck::tensor_operation::element_wise::PassThrough;
-using Scale       = ck::tensor_operation::element_wise::Scale;
-
 // A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
 // k/k/n/n are the fast changing dimension for A/B/D/E
 using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_kkn_instance =

library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_knn_instance.cpp

@@ -19,13 +19,6 @@ namespace tensor_operation {
 namespace device {
 namespace instance {
 
-using BF16        = ck::bhalf_t;
-using F32         = float;
-using Empty_Tuple = ck::Tuple<>;
-
-using PassThrough = ck::tensor_operation::element_wise::PassThrough;
-using Scale       = ck::tensor_operation::element_wise::Scale;
-
 // A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
 // k/n/n/n are the fast changing dimension for A/B/D/E
 using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_knn_instance =

library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_mkn_instance.cpp

@@ -19,13 +19,6 @@ namespace tensor_operation {
 namespace device {
 namespace instance {
 
-using BF16        = ck::bhalf_t;
-using F32         = float;
-using Empty_Tuple = ck::Tuple<>;
-
-using PassThrough = ck::tensor_operation::element_wise::PassThrough;
-using Scale       = ck::tensor_operation::element_wise::Scale;
-
 // A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
 // m/k/n/n are the fast changing dimension for A/B/D/E
 using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_mkn_instance =

library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_mnn_instance.cpp

@@ -19,13 +19,6 @@ namespace tensor_operation {
 namespace device {
 namespace instance {
 
-using BF16        = ck::bhalf_t;
-using F32         = float;
-using Empty_Tuple = ck::Tuple<>;
-
-using PassThrough = ck::tensor_operation::element_wise::PassThrough;
-using Scale       = ck::tensor_operation::element_wise::Scale;
-
 // A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
 // m/n/n/n are the fast changing dimension for A/B/D/E
 using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_mnn_instance =

library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f16_f16_f16_compute_f32_kkn_instance.cpp

@@ -19,13 +19,6 @@ namespace tensor_operation {
 namespace device {
 namespace instance {
 
-using F16         = ck::half_t;
-using F32         = float;
-using Empty_Tuple = ck::Tuple<>;
-
-using PassThrough = ck::tensor_operation::element_wise::PassThrough;
-using Scale       = ck::tensor_operation::element_wise::Scale;
-
 // A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
 // k/k/n/n are the fast changing dimension for A/B/D/E
 using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f16_f16_f16_compute_f32_kkn_instance =

library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f16_f16_f16_compute_f32_knn_instance.cpp

@@ -19,13 +19,6 @@ namespace tensor_operation {
 namespace device {
 namespace instance {
 
-using F16         = ck::half_t;
-using F32         = float;
-using Empty_Tuple = ck::Tuple<>;
-
-using PassThrough = ck::tensor_operation::element_wise::PassThrough;
-using Scale       = ck::tensor_operation::element_wise::Scale;
-
 // A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
 // k/n/n/n are the fast changing dimension for A/B/D/E
 using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f16_f16_f16_compute_f32_knn_instance =

library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f16_f16_f16_compute_f32_mkn_instance.cpp

@@ -19,13 +19,6 @@ namespace tensor_operation {
 namespace device {
 namespace instance {
 
-using F16         = ck::half_t;
-using F32         = float;
-using Empty_Tuple = ck::Tuple<>;
-
-using PassThrough = ck::tensor_operation::element_wise::PassThrough;
-using Scale       = ck::tensor_operation::element_wise::Scale;
-
 // A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
 // m/k/n/n are the fast changing dimension for A/B/D/E
 using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f16_f16_f16_compute_f32_mkn_instance =

library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f16_f16_f16_compute_f32_mnn_instance.cpp

@@ -19,13 +19,6 @@ namespace tensor_operation {
 namespace device {
 namespace instance {
 
-using F16         = ck::half_t;
-using F32         = float;
-using Empty_Tuple = ck::Tuple<>;
-
-using PassThrough = ck::tensor_operation::element_wise::PassThrough;
-using Scale       = ck::tensor_operation::element_wise::Scale;
-
 // A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
 // m/n/n/n are the fast changing dimension for A/B/D/E
 using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f16_f16_f16_compute_f32_mnn_instance =

library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_compute_bf16_kkn_instance.cpp

@@ -19,13 +19,6 @@ namespace tensor_operation {
 namespace device {
 namespace instance {
 
-using BF16        = ck::bhalf_t;
-using F32         = float;
-using Empty_Tuple = ck::Tuple<>;
-
-using PassThrough = ck::tensor_operation::element_wise::PassThrough;
-using Scale       = ck::tensor_operation::element_wise::Scale;
-
 // A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
 // k/k/n/n are the fast changing dimension for A/B/D/E
 using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_compute_bf16_kkn_instance =

library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_compute_bf16_knn_instance.cpp

@@ -19,13 +19,6 @@ namespace tensor_operation {
 namespace device {
 namespace instance {
 
-using BF16        = ck::bhalf_t;
-using F32         = float;
-using Empty_Tuple = ck::Tuple<>;
-
-using PassThrough = ck::tensor_operation::element_wise::PassThrough;
-using Scale       = ck::tensor_operation::element_wise::Scale;
-
 // A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
 // k/n/n/n are the fast changing dimension for A/B/D/E
 using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_compute_bf16_knn_instance =

library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_compute_bf16_mkn_instance.cpp

@@ -19,13 +19,6 @@ namespace tensor_operation {
 namespace device {
 namespace instance {
 
-using BF16        = ck::bhalf_t;
-using F32         = float;
-using Empty_Tuple = ck::Tuple<>;
-
-using PassThrough = ck::tensor_operation::element_wise::PassThrough;
-using Scale       = ck::tensor_operation::element_wise::Scale;
-
 // A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
 // m/k/n/n are the fast changing dimension for A/B/D/E
 using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_compute_bf16_mkn_instance =