work in progress

Author: smazouz42

pyccel/ast/numpyext.py

@@ -626,7 +626,6 @@ def __init__(self, *args, class_type, init_dtype = None):
         assert isinstance(class_type, NumpyNDArrayType)
         self._init_dtype = init_dtype
         self._class_type = class_type # pylint: disable=no-member
-        print(*args)
         super().__init__(*args)
 
     @property

pyccel/codegen/printing/ccode.py

@@ -2182,9 +2182,6 @@ def _print_Assign(self, expr):
         # Inhomogenous tuples are unravelled and therefore do not exist in the c printer
         if isinstance(rhs, (NumpyArray, PythonTuple)):
             return prefix_code+self.copy_NumpyArray_Data(expr)
-        if(isinstance(rhs, (CudaFull))):
-            # TODO add support for CudaFull
-            return " \n"
         if isinstance(rhs, (NumpyFull)):
             return prefix_code+self.arrayFill(expr)
         lhs = self._print(expr.lhs)

pyccel/codegen/printing/cucode.py

@@ -15,11 +15,10 @@
 from pyccel.ast.literals            import Nil
 
 from pyccel.errors.errors           import Errors
-from pyccel.ast.core                import Allocate, Deallocate
-from pyccel.ast.numpytypes          import   NumpyInt64Type
 from pyccel.ast.cudatypes           import CudaArrayType
 from pyccel.ast.datatypes           import HomogeneousContainerType
-from pyccel.ast.numpytypes          import NumpyNDArrayType, numpy_precision_map
+from pyccel.ast.numpytypes          import numpy_precision_map
+from pyccel.ast.cudaext             import CudaFull
 
 
 
@@ -147,14 +146,15 @@ def _print_ModuleHeader(self, expr):
                           "#endif // {name.upper()}_H\n"))
     def _print_Allocate(self, expr):
         variable = expr.variable
+        if not isinstance(variable.class_type, CudaArrayType):
+            return super()._print_Allocate(expr)
         shape = ", ".join(self._print(i) for i in expr.shape)
         if isinstance(variable.class_type, CudaArrayType):
             dtype = self.find_in_ndarray_type_registry(variable.dtype)
         elif isinstance(variable.class_type, HomogeneousContainerType):
             dtype = self.find_in_ndarray_type_registry(numpy_precision_map[(variable.dtype.primitive_type, variable.dtype.precision)])
         else:
             raise NotImplementedError(f"Don't know how to index {variable.class_type} type")
-        shape_dtype = self.get_c_type(NumpyInt64Type())
         shape_Assign = "int64_t shape_Assign [] = {" + shape + "};\n"
         is_view = 'false' if variable.on_heap else 'true'
         memory_location = expr.variable.memory_location
@@ -169,8 +169,19 @@ def _print_Allocate(self, expr):
     def _print_Deallocate(self, expr):
         var_code = self._print(expr.variable)
 
+        if not isinstance(expr.variable.class_type, CudaArrayType):
+            return super()._print_Deallocate(expr)
+
         if expr.variable.memory_location == 'host':
             return f"cuda_free_host({var_code});\n"
         else:
             return f"cuda_free({var_code});\n"
 
+    def _print_Assign(self, expr):
+        rhs = expr.rhs
+        if not isinstance(rhs.class_type, CudaArrayType):
+                return super()._print_Assign(expr)
+        if(isinstance(rhs, (CudaFull))):
+            # TODO add support for CudaFull
+            return " \n"
+