Initial phase of adding PyTorch support for data analysis. Added conversion nodes.

modules/numpy_wrapper/numpy_float_create.py

@@ -0,0 +1,47 @@
+from typing import Any, Dict
+import numpy as np
+import ast
+
+
+class NumpyFloatCreate:
+    """
+    Creates a NumPy ndarray with 32-bit floating point precision 
+    using values entered in the text field.
+    
+    category: Numpy
+    """
+    
+    @classmethod
+    def INPUT_TYPES(cls) -> Dict[str, Any]:
+        """
+        Defines the input types for the function.
+
+        Returns:
+            Dict[str, Any]: A dictionary specifying required input types.
+        """
+        return {
+            "required": {
+                "data": ("STRING", {"multiline": True}),
+            }
+        }
+
+    RETURN_TYPES: tuple = ("NDARRAY",)
+    FUNCTION: str = "f"
+    CATEGORY: str = "Numpy wrapper"
+
+    def f(self, data: str) -> tuple:
+        """
+        Creates a Numpy ndarray using values entered in the text field.
+
+        Args:
+            data (str): String value in the text field.
+
+        Returns:
+            tuple: A tuple containing a the DataFrame.
+        """
+        # Convert string to Python list
+        list_data = ast.literal_eval(data)
+
+        # Convert list to NumPy array
+        array = np.array(list_data, dtype=np.float32)
+        return (array,)

modules/numpy_wrapper/numpy_int_create.py

@@ -0,0 +1,48 @@
+from typing import Any, Dict
+import numpy as np
+import ast
+
+
+class NumpyIntCreate:
+    """
+    Creates a NumPy ndarray with 32-bit integer 
+    using values entered in the text field.
+    
+    category: Numpy
+    """
+    
+    @classmethod
+    def INPUT_TYPES(cls) -> Dict[str, Any]:
+        """
+        Defines the input types for the function.
+
+        Returns:
+            Dict[str, Any]: A dictionary specifying required input types.
+        """
+        return {
+            "required": {
+                "data": ("STRING", {"multiline": True}),
+            }
+        }
+
+    RETURN_TYPES: tuple = ("NDARRAY",)
+    FUNCTION: str = "f"
+    CATEGORY: str = "Numpy wrapper"
+
+    def f(self, data: str) -> tuple:
+        """
+        Creates a NumPy ndarray with 32-bit integer using values 
+        entered in the text field.
+
+        Args:
+            data (str): String value in the text field.
+
+        Returns:
+            tuple: A tuple containing the NumPy ndarray.
+        """
+        # Convert string to Python list
+        list_data = ast.literal_eval(data)
+
+        # Convert list to NumPy int32 array
+        array = np.array(list_data, dtype=np.int32)
+        return (array,)