Added transpose and contigous operator ... need tests

src/include/rtg/operators.hpp

@@ -235,38 +235,44 @@ struct transpose
     {
         check_shapes{inputs}.has(1);
         auto input         = inputs.at(0);
-        auto input_size    = input.lens();
+        auto input_lens    = input.lens();
         auto input_strides = input.strides();
         auto t             = input.type();
-        if (dims.size() != input_size.size()) {
+        if (dims.size() != input_lens.size()) {
             RTG_THROW("Permutation has wrong number of axes");
         }
-
-        // DEBUG
-        for (int i = 0; i < dims.size(); i++) {
-            std::cout << dims[i] << std::endl;
-        }
-        std::cout << std::endl;
-
         std::vector<int64_t> axes(dims.size());
         std::iota(axes.begin(), axes.end(), 0);
         if (!std::is_permutation(axes.begin(), axes.end(), dims.begin())) {
             RTG_THROW("Invalid permutation");
         }
-        std::vector<size_t> output_size(input_size.size());
-        std::vector<size_t> output_strides(input_size.size());
-        for (int i = 0; i < output_size.size(); i++) {
-            output_size[i] = input_size[dims[i]];
+        std::vector<size_t> output_lens(input_lens.size());
+        std::vector<size_t> output_strides(input_lens.size());
+        for (int i = 0; i < output_lens.size(); i++) {
+            output_lens[i] = input_lens[dims[i]];
             output_strides[i] = input_strides[dims[i]];
-            //std::cout << input_size[i] << "    " << output_size[i] << std::endl;
-            //std::cout << input_strides[i] << "    " << output_strides[i] << std::endl;
         }
-        std::cout << std::endl;
-        return {t, output_size, output_strides};
+        return {t, output_lens, output_strides};
     }
     argument compute(shape, std::vector<argument>) const { RTG_THROW("not computable"); }
 };
 
+struct contiguous 
+{
+    std::vector<int64_t> dims;
+    std::string name() const { return "contiguous"; }
+    shape compute_shape(std::vector<shape> inputs) const
+    {
+        check_shapes{inputs}.has(1);
+        auto lens    = inputs.at(0).lens();
+        auto t       = inputs.at(0).type();
+        if (lens.size() < 2) {
+            RTG_THROW("Number of dimensions should exceed 1");
+        }
+        return {t, lens};
+    }
+};
+
 struct reshape
 {
     std::vector<int64_t> dims;

src/targets/cpu/cpu_target.cpp

@@ -61,30 +61,81 @@ struct cpu_transpose
     std::string name() const { return "cpu::transpose"; } 
     shape compute_shape(std::vector<shape> inputs) const { return op.compute_shape(inputs); }
     argument compute(shape output_shape, std::vector<argument> args) const
+    {
+        return {output_shape, std::move(args.front().data)};
+    }
+};
+
+struct cpu_contiguous
+{
+    contiguous op;
+    std::string name() const { return "cpu::contiguous"; }
+    shape compute_shape(std::vector<shape> inputs) const
+    {
+        return op.compute_shape(inputs);
+    }
+    argument compute(shape output_shape, std::vector<argument> args) const
     {
         argument result{output_shape};
         visit_all(result, args[0])([&](auto output, auto input) {
+            auto input_shape = args[0].get_shape();
+            auto ndim = output_shape.lens().size();
             using value_type = typename decltype(input)::value_type;
             value_type* ptr = static_cast<value_type*>(output.data());
-            auto nb = output_shape.lens()[0];
-            auto nc = output_shape.lens()[1]; 
-            auto nh = output_shape.lens()[2]; 
-            auto nw = output_shape.lens()[3];
-            for (int kk = 0; kk < 4; kk++) {
-                std::cout << "cpu_transpose: " << output_shape.lens()[kk] << "    " << output_shape.strides()[kk] << std::endl;
+            if (ndim == 2) {
+                dfor(input_shape.lens()[0],
+                     input_shape.lens()[1])(
+                    [&](std::size_t i0, std::size_t i1) {
+                        *ptr++ = input(i0,i1);
+                    });
             }
-            
-            for (int b = 0; b < nb; b++) {
-                for (int c = 0; c < nc; c++) {
-                    for (int i = 0; i < nh; i++) {
-                        for (int j = 0; j < nw; j++) {
-                            *ptr++ = input(b,c,i,j);
-                             std::cout << input(b,c,i,j) << "  ";
+            else if (ndim == 3) {
+                dfor(input_shape.lens()[0],
+                     input_shape.lens()[1],
+                     input_shape.lens()[2])(
+                    [&](std::size_t i0, std::size_t i1, std::size_t i2) {
+                        *ptr++ = input(i0,i1,i2);
+                    });
             }
+            else if (ndim == 4) {
+                dfor(input_shape.lens()[0],
+                     input_shape.lens()[1],
+                     input_shape.lens()[2],
+                     input_shape.lens()[3])(
+                    [&](std::size_t i0, std::size_t i1, std::size_t i2, std::size_t i3) {
+                        *ptr++ = input(i0,i1,i2,i3);
+                    });
             }
+            else if (ndim == 5) {
+                dfor(input_shape.lens()[0],
+                     input_shape.lens()[1],
+                     input_shape.lens()[2],
+                     input_shape.lens()[3],
+                     input_shape.lens()[4])(
+                    [&](std::size_t i0, 
+                        std::size_t i1, 
+                        std::size_t i2, 
+                        std::size_t i3, 
+                        std::size_t i4) {
+                        *ptr++ = input(i0,i1,i2,i3,i4);
+                    });
             }
+            else if (ndim == 6) {
+                dfor(input_shape.lens()[0],
+                     input_shape.lens()[1],
+                     input_shape.lens()[2],
+                     input_shape.lens()[3],
+                     input_shape.lens()[4],
+                     input_shape.lens()[5])(
+                    [&](std::size_t i0, 
+                        std::size_t i1, 
+                        std::size_t i2, 
+                        std::size_t i3, 
+                        std::size_t i4, 
+                        std::size_t i5) {
+                        *ptr++ = input(i0,i1,i2,i3,i4,i5);
+                    });
             }
-            std::cout << std::endl;
         });
         return result;
     }

test/cpu_ops_test.cpp

@@ -404,12 +404,14 @@ void transpose_test()
     p.add_instruction(rtg::transpose{perm}, l);
     p.compile(rtg::cpu::cpu_target{});
     auto result = p.eval({});
+
     std::vector<float> results_vector(12);
-    result.visit([&] (auto output){ results_vector.assign(output.begin(), output.end()); });
-    float tol = 1e-6;
-    for (int i = 0; i < results_vector.size(); i++) {
-      std::cout << results_vector[i] << std::endl;
-    }
+    result.visit([&] (auto output){
+      std::vector<size_t> new_lens = {1,3,2,2};
+      std::vector<size_t> new_strides = {12,1,6,3}; 
+      EXPECT(bool{output.get_shape().lens() == new_lens});
+      EXPECT(bool{output.get_shape().strides() == new_strides});
+      });
 }
 
 int main()