Add _initialize_with_initializer to PyTorch, NumPy, and OpenVINO backends

Author: praveenhosdrug123

keras/src/backend/numpy/core.py

@@ -23,6 +23,12 @@ class Variable(KerasVariable):
     def _initialize(self, value):
         self._value = value
 
+    def _initialize_with_initializer(self, initializer):
+        value = self._convert_to_tensor(
+            initializer(self._shape, dtype=self._dtype)
+        )
+        self._initialize(value)
+
     def _direct_assign(self, value):
         self._value = np.array(value, dtype=self._dtype)
 

keras/src/backend/openvino/core.py

@@ -572,6 +572,12 @@ def _initialize(self, value):
             )
             self._value = OpenVINOKerasTensor(value_const.output(0))
 
+    def _initialize_with_initializer(self, initializer):
+        value = self._convert_to_tensor(
+            initializer(self._shape, dtype=self._dtype)
+        )
+        self._initialize(value)
+
     def _direct_assign(self, value):
         self._value = value
 

keras/src/backend/torch/core.py

@@ -109,6 +109,12 @@ def _initialize(self, value):
                 requires_grad=self.trainable,
             ).to(get_device())
 
+    def _initialize_with_initializer(self, initializer):
+        value = self._convert_to_tensor(
+            initializer(self._shape, dtype=self._dtype)
+        )
+        self._initialize(value)
+
     def _direct_assign(self, value):
         with torch.no_grad():
             self.value.copy_(value)