Merge branch 'develop' of https://github.com/ROCmSoftwarePlatform/AMDMIGraphX into stridedslice_op

src/targets/gpu/gemm.cpp

 #include <migraphx/gpu/gemm.hpp>
 #include <migraphx/gpu/context.hpp>
+#include <migraphx/gpu/device/add.hpp>
 
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
 namespace gpu {
 
 template <class... Ts>
-void generic_rocblas_batched_gemm(shape::as<float>, Ts&&... xs)
+rocblas_status generic_rocblas_scal(shape::as<float>, Ts&&... xs)
 {
-    rocblas_sgemm_strided_batched(std::forward<Ts>(xs)...);
+    return rocblas_sscal(std::forward<Ts>(xs)...);
 }
 
 template <class... Ts>
-void generic_rocblas_batched_gemm(shape::as<double>, Ts&&... xs)
+rocblas_status generic_rocblas_scal(shape::as<double>, Ts&&... xs)
 {
-    rocblas_dgemm_strided_batched(std::forward<Ts>(xs)...);
+    return rocblas_dscal(std::forward<Ts>(xs)...);
+}
+
+template <class T, class... Ts>
+rocblas_status generic_rocblas_scal(shape::as<T>, Ts&&...)
+{
+    MIGRAPHX_THROW("GENERIC_ROCBLAS_SCAL: type unsupported by rocblas");
+}
+
+template <class... Ts>
+rocblas_status generic_rocblas_axpy(shape::as<half>, Ts&&... xs)
+{
+    return rocblas_haxpy(std::forward<Ts>(xs)...);
+}
+
+template <class... Ts>
+rocblas_status generic_rocblas_axpy(shape::as<float>, Ts&&... xs)
+{
+    return rocblas_saxpy(std::forward<Ts>(xs)...);
+}
+
+template <class... Ts>
+rocblas_status generic_rocblas_axpy(shape::as<double>, Ts&&... xs)
+{
+    return rocblas_daxpy(std::forward<Ts>(xs)...);
+}
+
+template <class T, class... Ts>
+rocblas_status generic_rocblas_axpy(shape::as<T>, Ts&&...)
+{
+    MIGRAPHX_THROW("GENERIC_ROCBLAS_AXPY: type unsupported by rocblas");
+}
+
+template <class... Ts>
+rocblas_status generic_rocblas_dot(shape::as<float>, Ts&&... xs)
+{
+    return rocblas_sdot(std::forward<Ts>(xs)...);
 }
 
 template <class... Ts>
-void generic_rocblas_batched_gemm(shape::as<half>, Ts&&... xs)
+rocblas_status generic_rocblas_dot(shape::as<double>, Ts&&... xs)
 {
-    rocblas_hgemm_strided_batched(std::forward<Ts>(xs)...);
+    return rocblas_ddot(std::forward<Ts>(xs)...);
 }
 
 template <class T, class... Ts>
-void generic_rocblas_batched_gemm(shape::as<T>, Ts&&...)
+rocblas_status generic_rocblas_dot(shape::as<T>, Ts&&...)
+{
+    MIGRAPHX_THROW("GENERIC_ROCBLAS_DOT: type unsupported by rocblas");
+}
+
+template <class... Ts>
+rocblas_status generic_rocblas_gemv(shape::as<float>, Ts&&... xs)
+{
+    return rocblas_sgemv(std::forward<Ts>(xs)...);
+}
+
+template <class... Ts>
+rocblas_status generic_rocblas_gemv(shape::as<double>, Ts&&... xs)
+{
+    return rocblas_dgemv(std::forward<Ts>(xs)...);
+}
+
+template <class T, class... Ts>
+rocblas_status generic_rocblas_gemv(shape::as<T>, Ts&&...)
+{
+    MIGRAPHX_THROW("GENERIC_ROCBLAS_GEMMV: type unsupported by rocblas");
+}
+
+template <class... Ts>
+rocblas_status generic_rocblas_batched_gemm(shape::as<float>, Ts&&... xs)
+{
+    return rocblas_sgemm_strided_batched(std::forward<Ts>(xs)...);
+}
+
+template <class... Ts>
+rocblas_status generic_rocblas_batched_gemm(shape::as<double>, Ts&&... xs)
+{
+    return rocblas_dgemm_strided_batched(std::forward<Ts>(xs)...);
+}
+
+template <class... Ts>
+rocblas_status generic_rocblas_batched_gemm(shape::as<half>, Ts&&... xs)
+{
+    return rocblas_hgemm_strided_batched(std::forward<Ts>(xs)...);
+}
+
+template <class T, class... Ts>
+rocblas_status generic_rocblas_batched_gemm(shape::as<T>, Ts&&...)
 {
     MIGRAPHX_THROW("GENERIC_ROCBLAS_BATCHED_GEMM: type unsupported by rocblas");
 }
 
 template <class... Ts>
-void generic_rocblas_gemm(shape::as<float>, Ts&&... xs)
+rocblas_status generic_rocblas_gemm(shape::as<float>, Ts&&... xs)
 {
-    rocblas_sgemm(std::forward<Ts>(xs)...);
+    return rocblas_sgemm(std::forward<Ts>(xs)...);
 }
 
 template <class... Ts>
-void generic_rocblas_gemm(shape::as<double>, Ts&&... xs)
+rocblas_status generic_rocblas_gemm(shape::as<double>, Ts&&... xs)
 {
-    rocblas_dgemm(std::forward<Ts>(xs)...);
+    return rocblas_dgemm(std::forward<Ts>(xs)...);
 }
 
 template <class... Ts>
-void generic_rocblas_gemm(shape::as<half>, Ts&&... xs)
+rocblas_status generic_rocblas_gemm(shape::as<half>, Ts&&... xs)
 {
-    rocblas_hgemm(std::forward<Ts>(xs)...);
+    return rocblas_hgemm(std::forward<Ts>(xs)...);
 }
 
 template <class T, class... Ts>
-void generic_rocblas_gemm(shape::as<T>, Ts&&...)
+rocblas_status generic_rocblas_gemm(shape::as<T>, Ts&&...)
 {
     MIGRAPHX_THROW("GENERIC_ROCBLAS_GEMM: type unsupported by rocblas");
 }
@@ -90,56 +169,94 @@ rocblas_half to_rocblas_type(half x) { return reinterpret_cast<const rocblas_hal
 
 shape miopen_gemm::compute_shape(const std::vector<shape>& inputs) const
 {
-    check_shapes{inputs, *this}.has(3);
-    return op.compute_shape({inputs.at(0), inputs.at(1)});
+    std::vector<shape> input_shapes(inputs.begin(), inputs.begin() + inputs.size() - 1);
+    check_shapes{input_shapes}.not_broadcasted();
+    return op.compute_shape(input_shapes);
 }
+
 argument miopen_gemm::compute(context& ctx,
                               const shape& output_shape,
                               const std::vector<argument>& args) const
 {
-    float alpha        = 1.0f;
-    float beta         = 0.0f;
-    bool transa        = args[0].get_shape().transposed();
-    bool transb        = args[1].get_shape().transposed();
-    std::size_t n_dims = args[0].get_shape().lens().size();
-    std::size_t dim_0  = n_dims - 2;
-    std::size_t dim_1  = n_dims - 1;
-    rocblas_int lda    = args[0].get_shape().strides()[transa ? dim_1 : dim_0];
-    rocblas_int ldb    = args[1].get_shape().strides()[transb ? dim_1 : dim_0];
-    rocblas_int ldc    = args[2].get_shape().strides()[dim_0];
-    auto out_lens      = output_shape.lens();
-    rocblas_int m      = out_lens[dim_0];
-    rocblas_int n      = out_lens[dim_1];
-    rocblas_int k      = args[0].get_shape().lens()[dim_1];
-    auto batch_num     = std::accumulate(
-        out_lens.rbegin() + 2, out_lens.rend(), std::size_t{1}, std::multiplies<std::size_t>());
+    bool is_3inputs = (args.size() == 4);
+    float beta      = 0.0f;
+    if(is_3inputs)
+    {
+        output_shape.visit_type([&](auto as) {
+            auto to_pointer = [&](auto&& arg) { return to_rocblas_type(as.from(arg.data())); };
+            hipMemcpyAsync(to_pointer(args[3]),
+                           to_pointer(args[2]),
+                           output_shape.bytes(),
+                           hipMemcpyDeviceToDevice,
+                           ctx.get_stream().get());
+        });
+        beta = op.beta;
+    }
+
+    auto a_lens = args[0].get_shape().lens();
+    auto b_lens = args[1].get_shape().lens();
     output_shape.visit_type([&](auto as) {
-        auto alpha_r    = to_rocblas_type(as(alpha));
-        auto beta_r     = to_rocblas_type(as(beta));
+        auto n_dim        = output_shape.lens().size();
+        auto dim_1        = n_dim - 1;
+        auto dim_0        = n_dim - 2;
+        auto alpha_r      = to_rocblas_type(as(op.alpha));
+        auto beta_r       = to_rocblas_type(as(beta));
+        bool transa       = args[0].get_shape().transposed();
+        bool transb       = args[1].get_shape().transposed();
+        rocblas_int lda   = args[0].get_shape().strides()[transa ? dim_1 : dim_0];
+        rocblas_int ldb   = args[1].get_shape().strides()[transb ? dim_1 : dim_0];
+        rocblas_int ldc   = args[2].get_shape().strides()[dim_0];
+        auto out_lens     = output_shape.lens();
+        rocblas_int m     = out_lens[dim_0];
+        rocblas_int n     = out_lens[dim_1];
+        rocblas_int k     = args[0].get_shape().lens()[dim_1];
+        auto num_matrices = std::accumulate(
+            out_lens.rbegin() + 2, out_lens.rend(), std::size_t{1}, std::multiplies<std::size_t>());
         auto to_pointer = [&](auto&& arg) { return to_rocblas_type(as.from(arg.data())); };
-        generic_rocblas_batched_gemm(as,
-                                     ctx.get_stream().get_rocblas(),
-                                     transb ? rocblas_operation_transpose : rocblas_operation_none,
-                                     transa ? rocblas_operation_transpose : rocblas_operation_none,
-                                     n,
-                                     m,
-                                     k,
-                                     &alpha_r,
-                                     to_pointer(args[1]),
-                                     ldb,
-                                     k * n,
-                                     to_pointer(args[0]),
-                                     lda,
-                                     m * k,
-                                     &beta_r,
-                                     to_pointer(args[2]),
-                                     ldc,
-                                     m * n,
-                                     batch_num);
-
+        if(num_matrices == 1)
+        {
+            generic_rocblas_gemm(as,
+                                 ctx.get_stream().get_rocblas(),
+                                 transb ? rocblas_operation_transpose : rocblas_operation_none,
+                                 transa ? rocblas_operation_transpose : rocblas_operation_none,
+                                 n,
+                                 m,
+                                 k,
+                                 &alpha_r,
+                                 to_pointer(args[1]),
+                                 ldb,
+                                 to_pointer(args[0]),
+                                 lda,
+                                 &beta_r,
+                                 (is_3inputs ? to_pointer(args[3]) : to_pointer(args[2])),
+                                 ldc);
+        }
+        else
+        {
+            generic_rocblas_batched_gemm(
+                as,
+                ctx.get_stream().get_rocblas(),
+                transb ? rocblas_operation_transpose : rocblas_operation_none,
+                transa ? rocblas_operation_transpose : rocblas_operation_none,
+                n,
+                m,
+                k,
+                &alpha_r,
+                to_pointer(args[1]),
+                ldb,
+                k * n,
+                to_pointer(args[0]),
+                lda,
+                m * k,
+                &beta_r,
+                (is_3inputs ? to_pointer(args[3]) : to_pointer(args[2])),
+                ldc,
+                m * n,
+                num_matrices);
+        }
     });
 
-    return args[2];
+    return (is_3inputs ? args[3] : args[2]);
 }
 
 } // namespace gpu

src/targets/gpu/include/migraphx/gpu/batchnorm.hpp

@@ -2,7 +2,7 @@
 #define MIGRAPHX_GUARD_RTGLIB_BATCHNORM_HPP
 
 #include <migraphx/shape.hpp>
-#include <migraphx/operators.hpp>
+#include <migraphx/op/batch_norm.hpp>
 
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {

src/targets/gpu/include/migraphx/gpu/concat.hpp

@@ -2,7 +2,7 @@
 #define MIGRAPHX_GUARD_RTGLIB_CONCAT_HPP
 
 #include <migraphx/shape.hpp>
-#include <migraphx/operators.hpp>
+#include <migraphx/op/concat.hpp>
 
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {

src/targets/gpu/include/migraphx/gpu/contiguous.hpp

@@ -2,7 +2,7 @@
 #define MIGRAPHX_GUARD_RTGLIB_CONTIGUOUS_HPP
 
 #include <migraphx/shape.hpp>
-#include <migraphx/operators.hpp>
+#include <migraphx/op/contiguous.hpp>
 
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {

src/targets/gpu/include/migraphx/gpu/convolution.hpp

@@ -2,7 +2,7 @@
 #define MIGRAPHX_GUARD_RTGLIB_CONVOLUTION_HPP
 
 #include <migraphx/shape.hpp>
-#include <migraphx/operators.hpp>
+#include <migraphx/op/convolution.hpp>
 #include <migraphx/gpu/miopen.hpp>
 
 namespace migraphx {

src/targets/gpu/include/migraphx/gpu/gather.hpp

@@ -2,6 +2,7 @@
 #define MIGRAPHX_GUARD_RTGLIB_GATHER_HPP
 
 #include <migraphx/shape.hpp>
+#include <migraphx/op/gather.hpp>
 #include <migraphx/gpu/miopen.hpp>
 
 namespace migraphx {