refactor: correct dtype usage

Signed-off-by: 11happy <[email protected]>

Author: 11happy

keras/src/backend/openvino/numpy.py

@@ -323,10 +323,13 @@ def average(x, axis=None, weights=None):
 
 def bincount(x, weights=None, minlength=0, sparse=False):
     x = get_ov_output(x)
+    x_type = x.get_element_type()
     weights = get_ov_output(weights)
+    weights = ov_opset.convert(weights, x_type).output(0)
     minlength = get_ov_output(minlength)
-    const_one = ov_opset.constant(1, Type.i64).output(0)
-    const_zero = ov_opset.constant(0, Type.i64).output(0)
+    minlength = ov_opset.convert(minlength, x_type).output(0)
+    const_one = ov_opset.constant(1, x_type).output(0)
+    const_zero = ov_opset.constant(0, x_type).output(0)
     max_element = ov_opset.reduce_max(x, const_zero, keep_dims=False).output(0)
     depth = ov_opset.add(max_element, const_one).output(0)
     depth = ov_opset.maximum(depth, minlength).output(0)