(AI) implement the rest

2026-01-24 23:15:03 +01:00
parent c61aec2faf
commit 0fcb7bf7bd
33 changed files with 10749 additions and 330 deletions
@@ -0,0 +1,83 @@
+from ..helper_functions import generate_dim_variables,parse_expr, getIndexTensorAlongDim, as_tensor, commonLazy, normalize_to_common_shape,prepare_inputs
+from ..Parser.UnifiedMathVisitor import UnifiedMathVisitor
+from comfy_api.latest import io
+
+
+
+
+class MaskMathNodeOLD(io.ComfyNode):
+    """
+    Enables math expressions on Masks.
+
+    Inputs:
+        a, b, c, d: Mask inputs (b, c, d default to zero if not provided)
+        w, x, y, z: Float variables for expressions
+        Mask: Expression to apply on input masks
+
+    Outputs:
+        MASK: Result of applying expression to input masks
+    """
+
+    @classmethod
+    def define_schema(cls) -> io.Schema:
+        return io.Schema(
+            node_id="mrmth_MaskMathNode",
+            category="More math",
+            display_name="Mask math",
+            is_deprecated=True,
+            inputs=[
+                io.Mask.Input(id="a"),
+                io.Mask.Input(id="b", optional=True, lazy=True),
+                io.Mask.Input(id="c", optional=True, lazy=True),
+                io.Mask.Input(id="d", optional=True, lazy=True),
+                io.Float.Input(id="w", default=0.0, optional=True, lazy=True, force_input=True),
+                io.Float.Input(id="x", default=0.0, optional=True, lazy=True, force_input=True),
+                io.Float.Input(id="y", default=0.0, optional=True, lazy=True, force_input=True),
+                io.Float.Input(id="z", default=0.0, optional=True, lazy=True, force_input=True),
+                io.String.Input(id="Mask", default="a*(1-w)+b*w", tooltip="Expression to apply on input masks"),
+                io.Combo.Input(
+                    id="length_mismatch",
+                    options=["error", "error", "pad"],
+                    default="error",
+                    tooltip="How to handle mismatched mask batch sizes. tile: repeat shorter inputs; error: raise error on mismatch; pad: treat missing frames as zero."
+                )
+            ],
+            outputs=[
+                io.Mask.Output(),
+            ],
+        )
+
+    @classmethod
+    def check_lazy_status(cls, Mask, a, b=[], c=[], d=[], w=0, x=0, y=0, z=0, length_mismatch="tile"):
+        return commonLazy(Mask, a, b, c, d, w, x, y, z)
+
+    @classmethod
+    def execute(cls, Mask, a, b=None, c=None, d=None, w=0.0, x=0.0, y=0.0, z=0.0, length_mismatch="tile"):
+        a, b, c, d = prepare_inputs(a, b, c, d)
+
+        if(length_mismatch == "error"):
+            max_length = max(a.shape[0], b.shape[0], c.shape[0], d.shape[0])
+            for tensor, name in zip([a, b, c, d], ["a", "b", "c", "d"]):
+                if tensor.shape[0] != max_length:
+                    raise ValueError(f"Input '{name}' has shape {tensor.shape[0]}, expected {max_length} to match largest input.")
+        ae, be, ce, de = normalize_to_common_shape(a, b, c, d, mode=length_mismatch)
+
+        variables = {
+            "a": ae, "b": be, "c": ce, "d": de,
+            "w": w, "x": x, "y": y, "z": z,
+            "X": getIndexTensorAlongDim(ae, 2),
+            "Y": getIndexTensorAlongDim(ae, 1),
+            "B": getIndexTensorAlongDim(ae, 0),
+            "batch": getIndexTensorAlongDim(ae, 0),
+            "W": ae.shape[2],
+            "width": ae.shape[2],
+            "H": ae.shape[1],
+            "height": ae.shape[1],
+            "T": ae.shape[0],
+            "batch_count": ae.shape[0],
+        } | generate_dim_variables(ae)
+        tree = parse_expr(Mask);
+        visitor = UnifiedMathVisitor(variables, ae.shape)
+        result = visitor.visit(tree)
+        result = as_tensor(result, ae.shape)
+        return (result,)