diff --git a/include/backend.hpp b/include/backend.hpp
index 6a41d61..30c96a4 100644
--- a/include/backend.hpp
+++ b/include/backend.hpp
@@ -1,8 +1,10 @@
 #pragma once
 
 #include <memory>
+#include <optional>
 
 #include "shape.hpp"
+#include "tensor.hpp"
 
 namespace CUDANet {
 
@@ -22,7 +24,14 @@ class BackendFactory {
 };
 
 class Backend {
+  protected:
+    std::optional<DType> default_dtype;
   public:
+
+    virtual bool supports_dtype(DType dtype) const = 0;
+    virtual void set_default_dtype(DType dtype) = 0;
+    virtual DType get_default_dtype() const = 0;
+
     // Memory management
     virtual void* allocate(size_t bytes) = 0;
     virtual void  deallocate(void* ptr)  = 0;
diff --git a/include/backend/cuda/cuda.cuh b/include/backend/cuda/cuda.cuh
index 10d2979..db548bc 100644
--- a/include/backend/cuda/cuda.cuh
+++ b/include/backend/cuda/cuda.cuh
@@ -1,6 +1,7 @@
 #pragma once
 
 #include <cstdio>
+#include <set>
 
 #include "backend.hpp"
 #include "tensor.hpp"
@@ -29,9 +30,14 @@ namespace CUDANet::Backends {
 class CUDA : public Backend {
   private:
     int device_id;
+    std::set<DType> supported_dtypes;
   public:
     CUDA(const BackendConfig& config);
 
+    bool supports_dtype(DType dtype) const override;
+    void set_default_dtype(DType dtype) override;
+    DType get_default_dtype() const override;
+
     static bool is_cuda_available();
     void initialize();
 
diff --git a/include/shape.hpp b/include/shape.hpp
index f54a1cf..b0c97b7 100644
--- a/include/shape.hpp
+++ b/include/shape.hpp
@@ -66,6 +66,12 @@ struct Shape {
     __host__ bool operator!=(const Shape& other) const {
         return !(*this == other);
     }
+
+    __host__ __device__ bool empty() const {
+        return ndim == 0;
+    }
+
+
 };
 
 std::string format_shape(const Shape& shape) {
diff --git a/include/tensor.hpp b/include/tensor.hpp
index ab2fcf7..fb22bec 100644
--- a/include/tensor.hpp
+++ b/include/tensor.hpp
@@ -16,11 +16,14 @@ enum class DType
     // INT32,  // Not implemented yet
 };
 
+size_t dtype_size(DType dtype);
+
 class Tensor
 {
 public:
 
     Tensor() = default;
+    Tensor(Shape shape, CUDANet::Backend* backend);
     Tensor(Shape shape, DType dtype, CUDANet::Backend* backend);
 
     Tensor(Tensor&& other) noexcept;
@@ -30,6 +33,8 @@ public:
 
     ~Tensor();
 
+    DType get_dtype();
+
     size_t size() const;
     size_t numel() const;
 
diff --git a/src/backends/cuda/cuda.cu b/src/backends/cuda/cuda.cu
index 8d51d24..c2094f2 100644
--- a/src/backends/cuda/cuda.cu
+++ b/src/backends/cuda/cuda.cu
@@ -5,12 +5,15 @@
 #include <format>
 
 #include "backend/cuda/cuda.cuh"
+#include "tensor.hpp"
 
 using namespace CUDANet::Backends;
 
 
 CUDA::CUDA(const BackendConfig& config) {
     device_id = config.device_id < 0 ? 0 : config.device_id;
+    supported_dtypes = {DType::FLOAT32};
+    default_dtype = DType::FLOAT32;
     initialize();
 }
 
@@ -41,6 +44,28 @@ void CUDA::initialize() {
     std::printf("Using CUDA device %d: %s\n", device_id, deviceProp.name);
 }
 
+bool CUDA::supports_dtype(DType dtype) const {
+    return supported_dtypes.contains(dtype);
+}
+
+void CUDA::set_default_dtype(DType dtype) {
+    if (!supported_dtypes.contains(dtype)) {
+        throw std::runtime_error("Unsupported dtype");
+    }
+
+    default_dtype = dtype;
+}
+
+CUDANet::DType CUDA::get_default_dtype() const {
+    if (default_dtype) {
+        return default_dtype.value();
+    }
+    
+    const_cast<CUDA*>(this)->default_dtype = DType::FLOAT32;
+    return DType::FLOAT32;
+}
+
+
 void* CUDA::allocate(size_t bytes) {
     void* d_ptr = nullptr;
     CUDA_CHECK(cudaMalloc(&d_ptr, bytes));
diff --git a/src/tensor.cpp b/src/tensor.cpp
index 5750d49..fc42057 100644
--- a/src/tensor.cpp
+++ b/src/tensor.cpp
@@ -1,20 +1,27 @@
-#include <stdexcept>
-
 #include "tensor.hpp"
 
+#include <stdexcept>
+
 using namespace CUDANet;
 
+Tensor::Tensor(Shape shape, CUDANet::Backend* backend)
+    : Tensor(shape, backend->get_default_dtype(), backend) {}
+
 Tensor::Tensor(Shape shape, DType dtype, Backend* backend)
     : shape(shape), dtype(dtype), backend(backend), d_ptr(nullptr) {
-
     if (shape.empty()) {
         throw std::runtime_error("Tensor shape cannot be empty");
     }
-    
+
+    // Check if backend supports DType
+    if (!backend->supports_dtype(dtype)) {
+        throw std::runtime_error("Unsupported DType");
+    }
+
     // Count total elements
     size_t count = 1;
-    for (const auto& dim : shape) {
-        count *= dim;
+    for (size_t i = 0; i < shape.size(); ++i) {
+        count *= shape[i];
     }
     total_elms = count;
 
@@ -39,9 +46,8 @@ Tensor::Tensor(Tensor&& other) noexcept
       total_elms(other.total_elms),
       total_size(other.total_size),
       backend(other.backend),
-      d_ptr(other.d_ptr)
-{
-    other.d_ptr = nullptr;
+      d_ptr(other.d_ptr) {
+    other.d_ptr   = nullptr;
     other.backend = nullptr;
 }
 
@@ -51,17 +57,17 @@ Tensor& Tensor::operator=(Tensor&& other) noexcept {
         if (d_ptr != nullptr && backend != nullptr) {
             backend->deallocate(d_ptr);
         }
-        
+
         // Steal other's resources
-        shape = std::move(other.shape);
-        dtype = other.dtype;
+        shape      = std::move(other.shape);
+        dtype      = other.dtype;
         total_elms = other.total_elms;
         total_size = other.total_size;
-        backend = other.backend;
-        d_ptr = other.d_ptr;
-        
+        backend    = other.backend;
+        d_ptr      = other.d_ptr;
+
         // Leave other in valid but empty state
-        other.d_ptr = nullptr;
+        other.d_ptr   = nullptr;
         other.backend = nullptr;
     }
     return *this;